**Islands of Tuberculosis Elimination: An Evaluation of Community-Based Active Case Finding in North Sumatra, Indonesia**

**Elvi S. Siahaan <sup>1</sup> , Mirjam I. Bakker <sup>2</sup> , Ratna Pasaribu <sup>1</sup> , Amera Khan <sup>3</sup> , Tripti Pande <sup>4</sup> , Alwi Mujahit Hasibuan <sup>5</sup> and Jacob Creswell 3,\***


Received: 25 September 2020; Accepted: 23 October 2020; Published: 26 October 2020

**Abstract:** Community-based active case finding (ACF) is needed to reach key/vulnerable populations with limited access to tuberculosis (TB) care. Published reports of ACF interventions in Indonesia are scarce. We conducted an evaluation of a multicomponent community-based ACF intervention as it scaled from one district to nine in Nias and mainland North Sumatra. Community and health system support measures including laboratory strengthening, political advocacy, sputum transport, and community awareness were instituted. ACF was conducted in three phases: pilot (18 months, 1 district), intervention (12 months, 4 districts) and scale-up (9 months, 9 districts). The pilot phase identified 215 individuals with bacteriologically positive (B+) TB, representing 42% of B+ TB notifications. The intervention phase yielded 509, representing 54% of B+ notifications and the scale-up phase identified 1345 individuals with B+ TB (56% of notifications). We observed large increases in B+ notifications on Nias, but no overall change on the mainland despite district variation. Overall, community health workers screened 377,304 individuals of whom 1547 tested positive, and 95% were initiated on treatment. Our evaluation shows that multicomponent community-based ACF can reduce the number of people missed by TB programs. Community-based organizations are best placed for accessing and engaging hard to reach populations and providing integrated support which can have a large positive effect on TB notifications.

**Keywords:** tuberculosis; active case finding; community outreach; Indonesia; key population

#### **1. Introduction**

Tuberculosis (TB) has existed for millennia yet is the leading infectious disease killer worldwide [1]. In 2018, a United Nations (UN) High-Level Meeting reaffirmed the global commitment to meeting previously established ambitious targets and strategies to end TB by 2030 and set out interim targets for 2022 on the numbers of people treated for TB [2]. Every year, it is estimated that 3 million people with TB are undetected and/or remain unnotified to National TB Programs (NTPs) globally [1]. Lack of accessibility and availability of TB services are major drivers for this [3]. Those who are missed are often members of key/vulnerable populations (i.e., miners, prisoners, elderly, people living with human immunodeficiency virus (HIV), or people in hard to reach areas) [4,5]. Various global initiatives have been launched in an attempt to reach all people with TB including the Global Fund's Strategic Initiative on TB and the Find.Treat.All initiative which focus attention on reaching people with TB who are

missed by routine services [6,7]. To reach more people with TB, active case finding (ACF) strategies focused outside traditional health facilities are needed [8–10].

Previous literature indicates that numerous approaches have been explored to identify and diagnose people with TB through ACF. A study in Ethiopia documented the high impact on TB case notifications by using existing health extension workers to perform numerous tasks, such as community-based screening, sputum collection and laboratory techniques (i.e., community-based slide fixing) [11,12]. In Cambodia and Myanmar there have been multiple efforts to reach people with TB using mobile chest X-ray units. [13–16]. In India, ACF encompassing the use of mobile vans as well as house-to-house screening by community workers on a massive scale has been conducted through Global Fund projects and more recently by the government's ambitious initiatives [17,18]. Initiatives conducted outside of health facilities to reach individuals who are either not seeking care or are seeking care in the informal sector require a critical component of community mobilization and acceptance [19]. The inclusion of communities in such interventions to ensure access and local acceptance is crucial and, therefore, many ACF interventions are supported by community-based organizations. The Global Plan to End TB highlights the importance of increased involvement by the communities and civil society in the fight to end TB [4] and it is a critical part of the development of national strategic plans for TB [20].

Indonesia contributes to 8% of the global TB incidence, making it the third highest burden country after India and China [1]. In 2018, an estimated 845,000 people developed TB and only 563,879 (67%) were notified, meaning that 275,000 (33%) people with TB were missed [1]. Indonesia's health system is decentralized, and district health offices have the responsibility of organizing public health services through local facilities at the sub-district level called *Puskesmas* [21]. Encouraging ACF and community engagement in the TB response is one of the main strategies in Indonesia's National Strategic Plan [22].

TB patient-pathway analyses from Indonesia documented that more than 67% of symptomatic TB patients initially sought care in the private sector. The analyses highlighted the importance of 'community referrals' within the pathway [21]. However, there is limited published literature on ACF interventions in Indonesia. One study compared contact investigation and door-to-door screening by community health workers (CHWs) in Bandung City. The authors concluded that CHWs can be used to improve acceptance by the community, however no people with TB were detected in the study [23]. A modeling study comparing three case finding strategies concluded that if ACF is used to lower the proportion of people not accessing care, it can reduce mortality [24]. Due to the paucity of literature on ACF in Indonesia and the need to improve case detection, we report on the results of an evaluation of an ACF intervention in Nias archipelago and mainland North Sumatra, Indonesia funded by Stop TB partnership's TB REACH initiative [25].

#### **2. Materials and Methods**

#### *2.1. Setting*

We conducted an evaluation of scaled ACF interventions implemented in North Sumatra province. North Sumatra is the fourth most populous province in Indonesia consisting of 419 islands. The ACF intervention was conducted on Nias archipelago and mainland North Sumatra. Nias is an archipelago off the western coast of Northern Sumatra consisting of 32 inhabited islands. Many of the islands are difficult to reach and are only accessible by boat. The total population of the archipelago is approximately 800,000 people [26]. Nias is one of the poorest areas in Sumatra, and many of the indigenous residents are illiterate and do not speak Bahasa, limiting their access to official health information. Additionally, access to healthcare in Nias is often limited due to distances, high staff turnover, and lack of funding and training for healthcare staff in these remote areas. For much of the project period, Nias had only one GeneXpert machine which was mostly non-functional. Mainland North Sumatra is more developed than Nias. The total population is approximately 3 million people. Despite better access to health services compared to Nias, North Sumatra has a medium ranking for its health development index indicators (education, life expectancy and per capita income)

in most districts [27]. The districts on the mainland each had a single GeneXpert machine which was used primarily to test for drug resistance rather than diagnosis. Yayasan Menara Agung Pengharapan Internasional (YMAPI), a local non-governmental organization based in North Sumatra has provided access to health services and medicine for more than 15 years. YMAPI was the main implementer of this intervention, working in collaboration with the local District Health Offices and the NTP.

#### *2.2. Timeline and Coverage*

This community-based ACF intervention was conducted in three phases. Figure 1 presents a map of the area and timeline for the intervention and control districts. A pilot phase began in October 2014 in Nias Selatan District (population approximately 182,000) to test the intervention and help train project staff, lasting through March 2016. The ACF intervention phase (hereafter intervention phase) took place in four of the five districts within Nias (population approximately 450,000) between July 2017 and June 2018. Between April and December 2019, the ACF scale-up phase (hereafter scale-up phase) was implemented in all five districts on Nias as well as four additional districts in the mainland North Sumatra (population approximately 740,000). Two purposefully selected districts in North Sumatra with stable notifications rates and lacking other case detection interventions were used as control districts as part of TB REACH's standard monitoring and evaluation methodology [28]. Throughout the different areas and across the phases, the ACF interventions were similar but lessons learned from earlier phases were incorporated during implementation of subsequent phases.

#### *2.3. Community-Based Outreach Intervention*

A multicomponent community based ACF intervention was developed in coordination with the NTP and was conducted as part of the TB programme operations (see Figure 2). Predominantly female community-based volunteers (health promoters) who lived and worked in the communities were the core of this intervention. There were 1505 health promotors engaged in the pilot phase; 3730 in the intervention phase; and 7835 during the scale-up phase. In the pilot and intervention phase, health promotors were selected by the head of the different villages and other community leaders, while during the scale-up phase existing CHW (*posyandu kader*) were selected. The health promoters did not receive a salary but were provided small in-kind support such as transport reimbursements, T-shirts, caps, notebooks, and an official inauguration ceremony with a certificate. Health promoters were trained and supervised by project staff (health facilitators) to raise TB awareness, to sensitize community members on the importance of TB diagnosis and treatment and to screen community members for signs and symptoms of TB. The health promotors also advocated for health-seeking behaviors and provided information on nutrition, sanitation, and the harmful effects of tobacco use. The health facilitators, who received a small salary, travelled to hard-to-reach areas and villages by foot, bicycle, motorbike, and/or boat to support the screening and referral of people with presumptive TB to link them to testing, diagnosis and treatment.

The intervention targeted people at the village level. The health promoters and facilitators disseminated their health awareness messages and conducted TB screening during house to house visits and informal meetings where people congregated such as town meetings and events. A primary focus of their work was to promote the value of the local *Puskesmas* in providing high-quality medicine and care for TB as confidence in the health system was perceived as low.

Individuals were screened verbally for seven symptoms. The symptoms included: cough for more than 2 weeks, weight loss, loss of appetite, difficulty breathing, prolonged fever, night sweats and coughing blood. Anyone reporting two or more symptoms was considered to have presumptive TB and was eligible for diagnostic testing. All individuals with presumptive TB were asked to provide two sputum samples. In most situations, a health promoter or health facilitator accompanied them to the nearest *Puskesmas* for testing. A small enabler was provided to support the travel. For individuals living far from the *Puskesmas*, a health facilitator collected samples in the village and transported them to the nearest laboratory using a cold box by motorcycle and/or boat. In some instances, in very remote islands, laboratory technicians visited the communities, collected sputum and fixed slides on site. All diagnostic testing was done with sputum microscopy and individuals were eligible to initiate treatment if one of the smear results was positive/scanty in accordance with NTP guidelines. All individuals with TB were provided treatment support through the health facilitators and were also offered nutritional support consisting of food packages.


**Figure 1.** Active case finding in North Sumatra—timelines and geographic areas**. Figure 1.** Active case finding in North Sumatra—timelines and geographic areas.

**Figure 2.** Multicomponent community-based active case-finding intervention in North Sumatra, Indonesia.

To ensure the ACF activities did not overwhelm the health system's ability to provide care, YMAPI procured laboratory equipment including 17 microscopes and supplies for 85 diagnostic facilities in the intervention areas. Training sessions for laboratory and facility staff on screening, diagnostics and laboratory procedures, and treatment were also provided. People initiating TB treatment were notified through the TB registers as per standard NTP practice. YMAPI also worked with district TB officers to ensure timely and accurate reporting in the SITT (*Sistem Informasi Terpadu TB*), the national TB reporting system.

Finally, the project organized sensitization and results sharing meetings for village leaders, district heads and government staff. In these meetings people with TB currently on treatment or those who had completed their treatment were invited to participate to share their stories and advocate for more local funding for the TB program (see Figure 2).

#### *2.4. Data Collection*

Quarterly notification data from the SITT from the district and provincial offices from October 2013 to December 2019 were extracted. If online reporting data were incomplete, we complemented the reports with facility level data directly from the *Puskesmas*. The numbers of people screened and identified as having presumptive TB were collected by the health facilitators directly from the health promoters and then tracked into the facility laboratory registers to determine yield.

#### *2.5. Data Analysis*

Evaluation of the ACF intervention followed the standard monitoring and evaluation framework of TB REACH to determine the impact of case finding in a given area [28]. For all three phases, official NTP notification data were analyzed using a pre-post evaluation methodology of bacteriologically positive (B+) TB notifications in intervention areas. In addition, a control area was used for the intervention and scale-up phases. We compared the notifications in a baseline period to the notifications during the ACF intervention and did the same in control districts. Since the pilot phase lasted 6 quarters, for the baseline data we multiplied the four previous quarters of notifications by 1.5 to get a comparable result. Other periods all used actual notification numbers. We calculated the percentage change in TB notifications between baseline and intervention periods, as well as the absolute number of additional people notified. In addition, project data were used to track indicators relating to the number of presumptive cases among screened and the yield of testing during the ACF intervention to complement the results of the change in TB notifications.

#### *2.6. Ethics Statement*

This intervention was approved by the District Administration as part of programmatic services thus no additional ethical approval was required. All patient information was anonymized, and only aggregate data were used in the analyses.

#### **3. Results**

During the 18-month pilot phase (Q4 2014–Q1 2016), ACF in one district (Nias Selatan) was conducted. This involved five of the 11 Puskesmas with TB testing facilities and three Satellite Puskesmas. As shown in Table 1, during the pilot phase, health facilitators identified 3261 people who had presumptive TB, and were able to ensure 2983 (91.5%) were tested by linking them to laboratory services. Data on numbers of people screened were not collected in a systematic manner during the pilot phase. The ACF yielded 215 people with B+ TB (7.2% positivity rate), all of whom initiated treatment. Overall, there were 509 people with B+ TB notified in Nias Selatan during this phase, meaning community outreach efforts were responsible for 42% of the total B+ notifications during the pilot period. The computed 18-month B+ TB notifications prior to the pilot phase in Nias Selatan were 444, signifying a 15% increase using a pre/post analysis (Table 2).



TB: tuberculosis; N/A: data unavailable, B+: bacteriologically positive. # Pilot Phase included 1 district (Q4 2014–Q1 2016). <sup>+</sup> Intervention Phase included 4 districts on Nias Island (Q3 2017–Q2 2018). & Scale up Phase included 9 districts total (5 districts on Nias Island and 4 districts on mainland North Sumatra; Q2 2019–Q4 2019). Diagnosis was through sputum smear microscopy. \*\* Includes only data from active case finding (ACF) Intervention phase and Scale-up phase since pilot phase did not track screening numbers.

**Table 2.** Active case finding yield and impact on bacteriologically positive TB notifications, North Sumatra.



**Table 2.** *Cont.*

Notifications only include people who initiated anti-TB treatment. \* Pilot Phase included 1 district (Q4 2014–Q1 2016). ˆ Baseline in pilot phase includes 4 quarters of notification numbers prior to pilot phase (*n* = 296) multiplied by 1.5 (for 6 quarters, *n* = 444) since the intervention in the pilot phase lasted 6 quarters. <sup>+</sup> ACF Intervention Phase included 4 districts on Nias Island (Q3 2017–Q2 2018). & Scale up Phase included 9 districts total (5 districts on Nias Island and 4 districts on mainland. North Sumatra; Q2 2019–Q4 2019). ACF = active case finding. B+ = bacteriologically positive.

During the 12-month intervention phase (Q3 2017–Q2 2018) outreach was conducted in four districts in Nias. Health facilitators verbally screened 124,430 individuals. There were 6084 individuals who screened positive and were referred for testing (4.9% of those screened). The vast majority of individuals with presumptive TB, were tested (5807 or 95.4%). Of those tested, 509 (8.8%) had B+ results and 492 (96.7%) of them initiated anti-TB treatment (Table 1). Total B+ notifications during the intervention phase in the evaluation area, including passive case finding, was 916, indicating that community based ACF contributed 54% of B+ notifications. In the four quarters prior to the intervention phase, there were 495 B+ notifications in the same districts meaning that B+ TB notifications increased 85% in the four intervention districts. At the same time, we observed a modest increase in B+ TB notifications in the control population during the intervention phase, moving from 1424 to 1653, (+16%) (Table 2).

The scale-up phase included an additional district on Nias and four districts on mainland North Sumatra meaning a total of nine districts were covered. During the scale-up phase the number of people screened was 252,774 and the numbers were similar between Nias and the mainland. Of those screened, 9744 (3.9%) were referred for testing and 8962 symptomatic individuals (92.0%) were tested. Higher rates of presumptive TB were found on Nias compared to the mainland (4.3% vs. 3.4%), and the proportion tested among those referred was also higher on Nias (96.8% vs. 85.9%). Among people identified by the ACF who were tested, 823 (9.2%) had B+ results and 758 (92.1%) initiated treatment. Pretreatment loss to follow-up was slightly higher on Nias (9.6% vs. 8.3%). Across all the nine districts, there were 1345 B+ TB notifications during the scale-up phase meaning that the ACF activities identified 56% of the total B+ cases notified. ACF in districts on Nias contributed slightly more than the yield on the mainland (58% vs. 55%). B+ notifications on Nias island continued to rise compared to the baseline period (+22%), while on the mainland there was almost no change (−2%). When the change by district on the mainland was evaluated, we noted a wide range from an increase of 130% in Kabupaten Humbang Hasundutan, to a decrease of 41% in Kabupaten Tapanuli Utara, but the overall change was minimal. The control population had B+ notifications that also remained almost unchanged (+1%) with no variation between the control districts. Overall, the outreach activities screened 377,204 people, and tested 17,752 for TB, identifying 1547 people with B+ TB, and linking 94.7% of them to treatment.

#### **4. Discussion**

To our knowledge, our results are the first published account of large-scale ACF for TB in Indonesia. Our results show that combining health system strengthening, community mobilization, and ACF activities reached 1547 people with B+ TB and linked 95% of them to treatment. Despite a longstanding focus on bringing basic services to people with TB, our evaluation suggests many people in Indonesia

with TB need additional measures to reach them. Previously, ACF has been used in numerous settings with different outreach models [11–18,29–32]. While Indonesia has a strong private sector where many people with TB seek care [22], evidently there are places, especially in remote rural areas, where community-based approaches are needed to reach people with TB.

ACF is often effective in situations where there is poor access to care due to stigma, travel times, distances, and/or cost barriers [15,31,32]. Although we did not measure the impact of this intervention on out-of-pocket costs for people with TB, ACF has been shown to reduce catastrophic costs for people with TB [33]. In addition, ACF reaches people earlier in their disease progression, although this has not translated into improved treatment outcomes, it may lessen individual suffering [34].

We believe our intervention was successful, not only because of the outreach efforts for screening of villagers, but because of the multifaceted approach that was taken including supporting public health facilities with laboratory supplies and political advocacy. While ACF found more than 50% of the total TB notifications during the intervention, the numbers of diagnostic tests undertaken were also very large. Identifying individuals with presumptive TB and getting their samples to laboratories through the provision of enablers and a transport system for sputum was critical [35]. To identify more people with TB, large numbers of people must be tested. In Nigeria and India, ACF studies demonstrated these increases in testing were necessary to generate gains in notifications [36,37]. ACF efforts can place an enormous burden on the laboratory system and this was one of the main reasons to also strengthen the infrastructure and the capacity of laboratories to diagnose TB.

In addition to the community-based screening, the intervention focused on improving health information and the promotion of health-seeking behavior in the communities. It also supported the district TB officers to improve recording and reporting and provided political advocacy for local government to provide more support for the health services in the area. These comprehensive actions were aimed at strengthening the overall health services and promoting the accessibility to the services within the community for longer-term sustainability [38].

While the ACF intervention increased the numbers of people detected with TB, national disease estimates suggest people with TB are still being missed. In our evaluation, the rates of bacteriologically negative TB (clinically diagnosed) overall were low (~24%), and in the first two phases it was only 10% of all forms (AF) notifications. On North Sumatra there were higher proportions, up to 55% (data not shown). On Nias and its surrounding islands it remains difficult to make a clinical diagnosis of TB at the *Puskesmas* level as there is only one X-ray machine available on the island. Presumptive individuals must be referred and bear the cost of the X-ray which is a disincentive. Additionally, we only used symptom screening to identify presumptive TB. Multiple prevalence surveys across Asia have shown that confining testing to only symptomatic people will miss a large proportion (40–79%) of people with TB [39]. Since we did not have access to X-ray services, people with TB were probably missed. Finally, it is well known that the sensitivity of smear microscopy is poor [40,41]. Ideally Xpert MTB/RIF testing would be used in ACF situations. However, despite large investments in Xpert in Indonesia with more than 500 machines procured as of 2017 [42] and efforts to expand testing, access to diagnostic Xpert testing on Nias Island and Sumatra was very low. Ensuring testing for all people with presumptive TB is a challenge globally; while it is recommended in many national guidelines, only a few countries are able to provide access to rapid molecular tests for initial diagnosis [21]. Expanding access to testing should be strongly considered to conform to World Health Organization (WHO) recommendations [43] and to identify more people with bacteriologically confirmed TB [44,45].

While the ACF contributed to large increases in B+ notifications on Nias, the same activities had a variable impact on mainland North Sumatra. We are not sure why these results were different but have some hypotheses. The interventions were implemented on the mainland for a short period of time, which did not permit the same level of collaboration with local authorities, a factor that is hard to measure, but we feel is important to community-based work. Mainland North Sumatra is also more developed and access to diagnostic and treatment facilities is better than on Nias. We did see variation between the districts on the mainland with the most developed districts showing a decrease in notifications while the less-developed districts had an increase. ACF will not perform the same in all areas and for all populations and thus tailoring the outreach to address local barriers is critical.

Limitations of this intervention include the fact that neither the intervention nor control areas were randomly selected, and by using as baseline for the scale-up phase in Nias the three quarters directly following the intervention phase, we may have slightly underestimated the effect, as some of the sensitization activities can be expected to have a lasting effect beyond the intervention itself. In addition, we were not able to use molecular diagnostic tests, culture, nor X-ray due to the resources available in the project areas. These tools would have likely helped identify more people with TB, however the reality in many countries is that access to modern tools of TB diagnosis are often limited to well-equipped urban areas [46]. Since smear microscopy and Xpert are not 100% specific there is a possibility that a proportion of the sputum smear positive individuals may have false positive results, a risk that all ACF interventions where positivity rates are low must consider [47]. The laboratory positivity rate in our interventions was close to 9%, which is actually higher than documented yields in some TB programs and similar to passive case finding [48,49]. As we describe the results of an evaluation of a specific programmatic intervention, the impact of a similar approach in other parts of Indonesia or other countries may not be generalizable. However, with the growing body of evidence around the impact of ACF interventions [50] we believe there are likely many areas where remote rural populations could benefit from similar activities. Our results are from a programmatic implementation, not a controlled research experiment, limiting the data we can collect and conclusions we can draw, but also providing a better understanding of what is feasible in a 'real world' situation.

#### **5. Conclusions**

Despite a well-established TB program, there are many poor and remote communities where access to health services is lacking in Indonesia. By combining community-based education and outreach with training and infrastructure support to health services and political advocacy, large numbers of people with TB can be reached. These comprehensive types of intervention should be considered in other areas with deficient access to care. Expanding the screening approach to include both X-ray and Xpert to identify asymptomatic cases through better screening and enhance diagnostic sensitivity would likely improve results even more.

**Author Contributions:** Conceptualization, E.S.S. and R.P.; methodology, E.S.S., R.P., M.I.B. and J.C.; validation, E.S.S., R.P., M.I.B., A.K., A.M.H. and T.P.; formal analysis, M.I.B., A.K., T.P. and J.C.; investigation, E.S.S., R.P., and A.M.H.; data curation, E.S.S., M.I.B. and R.P.; writing—original draft preparation, J.C.; writing—review and editing, E.S.S., R.P., M.I.B., A.K., T.P. and J.C.; visualization, T.P. and J.C.; supervision, E.S.S., R.P. and A.M.H.; funding acquisition, E.S.S. and R.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** The intervention and the evaluation was supported by Stop TB Partnership's TB REACH initiative. TB REACH is funded by Global Affairs Canada.

**Acknowledgments:** We would like to acknowledge and thank the thousands of health volunteers and facilitators who worked to conduct the community outreach for this project. We also want to recognize and thank the district TB officers in Nias and North Sumatra, the National TB Program, and Ministry of Health of Indonesia for supporting the intervention over the years.

**Conflicts of Interest:** A.K. and J.C. are members of Stop TB Partnership and TB REACH. They do not make any funding decisions but provide technical assistance to selected projects. TP is a member of the Research Institute of McGill University Health Center which has a knowledge management grant from the Stop TB Partnership, TB REACH initiative.

#### **References**


**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

### *Perspective* **The TB REACH Initiative: Supporting TB Elimination E**ff**orts in the Asia-Pacific**

**Jacob Creswell 1,\* , Amera Khan <sup>1</sup> , Mirjam I Bakker <sup>2</sup> , Miranda Brouwer <sup>3</sup> , Vishnu Vardhan Kamineni <sup>4</sup> , Christina Mergenthaler <sup>2</sup> , Marina Smelyanskaya <sup>1</sup> , Zhi Zhen Qin <sup>1</sup> , Oriol Ramis <sup>5</sup> , Robert Stevens <sup>6</sup> , K Srikanth Reddy <sup>7</sup> and Lucie Blok <sup>2</sup>**


Received: 26 September 2020; Accepted: 16 October 2020; Published: 26 October 2020

**Abstract:** After many years of TB 'control' and incremental progress, the TB community is talking about ending the disease, yet this will only be possible with a shift in the way we approach the TB response. While the Asia-Pacific region has the highest TB burden worldwide, it also has the opportunity to lead the quest to end TB by embracing the four areas laid out in this series: using data to target hotspots, initiating active case finding, provisioning preventive TB treatment, and employing a biosocial approach. The Stop TB Partnership's TB REACH initiative provides a platform to support partners in the development, evaluation and scale-up of new and innovative technologies and approaches to advance TB programs. We present several approaches TB REACH is taking to support its partners in the Asia-Pacific and globally to advance our collective response to end TB.

**Keywords:** tuberculosis; active case finding; TB preventive therapy; innovation; End TB; TB REACH

#### **1. Introduction**

Since the tuberculosis (TB) epidemic was declared an emergency by the World Health Organization (WHO) in the 1990s, different global TB strategies, each growing more comprehensive and ambitious in their plans and goals, have been developed and deployed. Moving from a focus on adults with TB seeking care in the public sector, strategies have evolved to provide more emphasis on children, people living with HIV, engaging the private sector, involving communities, pro-actively reaching out to people with limited access to care and addressing catastrophic costs incurred by people who have TB [1–3]. Once aiming to identify 70% of incident TB cases, we now understand this will not suffice to end TB and new targets call for universal access to TB care and prevention [4–6]. In 2018, the TB community came together at a UN High Level Meeting (UNHLM) to agree on ambitious global targets and called for an end to the epidemic in the next decade [3,7,8]. Business as usual approaches will not be sufficient to reach these targets, and this is what drives Stop TB Partnership's Global Plan: The Paradigm Shift [7].

The TB community has been criticized for lacking ambition and being timid in its approach to combatting the disease [9,10]. The current series of this journal, Innovation and Evidence for

Achieving TB Elimination in the Asia–Pacific Region, brings together several important topics for the TB community. The Asia-Pacific region accounts for more than two thirds of incident TB globally (using generally accepted countries rather than WHO's grouping) [11,12]. However, the region has also been a leader in innovation and research in the TB field. Recent large increases in case notification primarily came from this region and bold new research is highlighting the path towards ending TB [11,13,14]. Strongly correlated with reductions in TB incidence, is socio-economic development and the Asia-Pacific region is also leading the world in GDP growth [15]. Below, we present how the Stop TB Partnership's TB REACH initiative has addressed the different areas outlined in the Lancet Series "How to Eliminate Tuberculosis" [16] with particular attention paid to the Asia-Pacific.

#### **2. The TB REACH Initiative**

The Stop TB Partnership's TB REACH initiative [17] was established in 2009 to bring new ideas and thinking to promote bold action in the fight against TB. With foundational support from Global Affairs Canada, and additional support from USAID and The Bill and Melinda Gates Foundation, TB REACH provides rapid funding to partners to quickly implement case finding and treatment support interventions whilst conducting continuous monitoring and evaluation. Despite a focus on service delivery, each TB REACH project is given strong independent monitoring and evaluation support to track historical and prospective TB notification data as well as intervention specific indicators, so results are rigorously documented. TB REACH works with innovators and grassroots organizations, testing new approaches and technologies that many traditional donors, are less inclined to support. With eight waves of funding, TB REACH has provided USD 63.4 million to countries in the Asia-Pacific region through 134 grants (Figure 1).

**Figure 1.** Map of TB REACH grants in the Asia-Pacific region.

Unlike other funding mechanisms, TB REACH is not constrained by WHO guidelines as to what it can fund, which allows implementers to take risks and test new approaches or technologies. For example, TB REACH supported Xpert testing in Tanzania in mobile vans before WHO guidance was issued on the assay in 2011. The assay was used by other TB REACH projects as a front-line

diagnostic while most countries were still using it only as a drug sensitivity test [18,19]. Additionally, TB REACH efforts in Nigeria and Cambodia presented interesting results from a novel pooled sputum strategy to save Xpert cartridge costs and time [20,21]. While the use of artificial intelligence (AI) in health has gained interest recently, TB REACH has been supporting AI to read chest x-rays (CXR) well before this approach was reviewed by WHO [22–24]. Current projects are testing new handheld X-ray machines that can be brought into communities for screening.

TB REACH projects are limited in both time and scope. Projects generally last between 12–18 months and their funding cannot exceed USD 1 million. These limitations create the need for longer term support from governments and other donors to scale-up and sustain successful interventions. As such, TB REACH has worked with partners and donors to stimulate the adoption of new and innovative approaches by national TB programs, the Global Fund [25], and Unitaid among others [26].

Much of the data and examples included in this article come from experiences and results of TB REACH projects. Where possible, data has been referenced, but in some instances, results have not been published yet and been abstracted from project reports.

#### **3. Data and Hotspots**

The 3 million people with TB who are missed every year by routine health programs, "the missing millions", are at the center of global discussions. At the national level, treatment coverage quantifies how well TB programs are reaching all people with TB [11]. However, these numbers fail to capture the substantial heterogeneity in treatment coverage at regional or district levels. This heterogeneity exists because of geographic features, demographics, key populations and other factors such as access to health care [27,28]. Furthermore, because people with TB are not homogenously distributed across geographical areas, mapping hotspots to help identify where best to focus active case finding (ACF) efforts is critical [29]. Often, TB REACH projects are specifically designed to focus on these hotspot areas and key populations, such as sex workers, transgender populations, people who inject drugs, prisoners, migrants, miners, ethnic minorities and indigenous populations, and other poor and/or remote communities, who have poor access to care and high burdens of TB [30]. These projects use intervention data to improve case finding as part of a rigorous monitoring and evaluation process. The continued monitoring and evaluation of TB REACH interventions ensures an understanding of the target populations demographics and specifically, how many people are reached, screened, tested and diagnosed, and where people drop out of the care cascade. A number of mobile screening applications to track people through the care cascade as well as systems to track Xpert testing have been developed [31,32].

#### **4. Active Case Finding**

Passive case finding (PCF) is the standard approach for TB programs globally. PCF relies on people who have chest symptoms to visit diagnostic facilities and be tested, generally with smear microscopy. While the approach is inexpensive, and can reach large parts of the population, it often misses many groups such as children, people with HIV, and many of the key populations mentioned above who have difficulties accessing care because of stigma, financial, structural, cultural and/or socio-economic barriers [5,6]. Ten years ago, TB REACH began to support innovative approaches to improve case detection including ACF programs which involve moving outside the health facility to reach people who are ill [33]. ACF often uses community members to conduct activities, and increasingly has employed CXR to identify people with TB who do not complain about symptoms. ACF is a complement to routine PCF and usually is measured by how many undiagnosed people with TB are identified and how this impacts the total notifications in a population [34]. Some differences between ACF and PCF are presented in Table 1. ACF is now an integral part of many national strategic plans for TB [34–36]. Here, and in this Series, we document numerous examples demonstrating the power of ACF in the Asia-Pacific region. In Indonesia, a community-based organization (CBO) increased TB

notification numbers significantly through ACF initiatives aimed at remote island populations [37]. Similar increases have been attributed to ACF initiatives in Pakistan [38,39] and Cambodia [40].


**Table 1.** Characteristics of Passive and Active Case Finding for Tuberculosis.

Contact investigation is a core component of ACF. Although contact investigation has not lead to large increases in case notifications, it does focus on a high risk group, assists in early identification, and is the main entry point for TB preventive treatment (TPT). Furthermore, when done comprehensively, people with TB identified through contact investigation can contribute more than 10% of the total case notifications in a given population [41,42]. Despite being part of WHO and country guidelines, contact investigation is not always regularly conducted in many countries in the region.

While a systematic review has shown that ACF alone does not impact treatment outcomes [43], the outreach associated with ACF presents better opportunities to support people with TB and ensure they successfully complete treatment, often through community health workers. In India, a CBO developed a highly successful outreach effort employing local lay workers on motorcycles to visit, screen and provide treatment support to tribal communities. The results were impressive, with a first-year pilot improving case notifications by 84% and a scale-up intervention producing similar results [44]. Moreover, pre-treatment loss to follow-up and treatment outcomes improved even with the added testing and treatment burden as the lay workers supported people with TB by visiting them consistently throughout treatment. Cambodia has been one of the earliest adopters of ACF by repurposing prevalence survey equipment to reach communities with poor access to care with both CXR and modern diagnostics such as Xpert [20,40,45,46]. While it is clear that ACF reaches people with TB earlier and can greatly improve the numbers of people treated [47,48], it is also clear that ACF alone will not be enough to end TB.

#### **5. Treating TB Infection**

In this series, Harries et al. presents a strong argument for the importance of including treating TB infection as we move to end TB [49]. We note that while ACF has found a strong following in the last ten years, the scale up of TPT has seen many obstacles. Harries et al. describe several challenges for TPT scale up including imperfect and expensive diagnostic tests for TB infection, long regimens, high pill burden, expensive shorter regimens, and limited recommendations on risk groups to receive treatment. However, there are a few initiatives trying to address these issues. In many cases, ACF in the form of contact investigation will be a necessary precursor to successful TPT. Numerous early adopters, such as the Zero TB Cities Initiative [50], are combining ACF and TPT to move more quickly towards the goal of ending TB. On the islands of Cu Lao Cham and Cat Ba in Viet Nam, community screening campaigns called SWEEP-TB integrated ACF and TB infection testing and treatment to create islands of elimination. These campaigns consisted of community mobilization and TB infection testing, using either the tuberculin skin test (TST) or the QuantiFERON-TB Gold Plus (QFT), in public places of congregation and subsequent door-to-door campaigns. Two days later, participants presented for evaluation of the TST or QFT results and CXR screening for active TB disease and were placed on either TB treatment or TPT as appropriate. These efforts achieved an estimated 72% population coverage with a cumulative TB infection testing of 4782 people and screening over 3100 people by CXR for the detection and treatment of 20 TB patients, two individuals with multidrug-resistant TB, and 1494 persons with TB infection. Repeat visits will attempt to document the impact of the campaigns. In the Marshall Islands, similar work was conducted combining ACF and TPT to eliminate TB from the islands. In the process, the intervention treated 4237 people with TPT and 305 for active disease [51]. Projects in other countries in the region have also shown great promise including large increases in childhood TPT enrolment in Mymensingh, Bangladesh working with both public and private providers as well as the introduction of new shorter regimens. In Indonesia, large scale Zero TB efforts are getting underway as part of a TB REACH Wave 7 project in Yogyakarta which seeks to massively scale up new shorter TPT regimens by combining ACF, and integration with community-based Maternal Child Health and Sexual Reproductive Health activities. These initiatives on TPT will identify program bottlenecks and allow TB programs to address issues during the impending scale-up of prevention efforts to meet the ambitious targets set out at the UNHLM [8].

#### **6. Biosocial Approaches**

TB is linked to poverty; its epidemiology and biology are highly dependent on social and economic factors impacting the communities where it spreads [52]. TB also aggravates poverty due to the costs of seeking care even though diagnosis and treatment itself may be free [53]. Ending TB thus means tackling the root causes of poverty, and the causes of stigma and marginalization which includes gender inequality, discrimination, racial and ethnic biases, and others. The difficulty of navigating the health care sector can add additional costs and result in people to drop out of the care cascade [54]. TB REACH supported projects in India using Accredited Social Health Activists (commonly known as ASHAs), an existing cadre working in the community as outreach workers, to guide patients through the diagnostic and treatment process, have led to substantially increased notifications [55,56]. A study in Nepal demonstrated how ACF can reduce catastrophic costs for people with TB as well as bringing health services to the community [57]. Traditional facility-based directly observed therapy requires persons with TB to regularly travel to health facilities, which can result in the incurring of travel and time costs as well as the loss of autonomy and privacy [58]. TB REACH has supported novel ways to improve treatment outcomes and enhance TB care including a portfolio of projects exploring the use of digital adherence technologies (DAT) as treatment support. The use of DAT is part of a shift towards people-centred care, empowering people with TB to take charge of their treatment and enabling health care providers to maintain contact with them and to identify individuals who may need additional support measures. In the Asia-Pacific region, current projects in Thailand, Philippines, and Bangladesh are assessing the feasibility and acceptability of these approaches as well as their effectiveness in relation to adherence and treatment outcomes with promising preliminary results [59–61]. In Thailand, the use of near field communication technology allowing migrants to store and share their digital treatment

records, showed a 21% increase in treatment success rates in the intervention period compared to pre-intervention period.

TB programs cannot exist in a medicalized vacuum of vertical service delivery. To achieve elimination, TB programming must cut across other issues that are pertinent to communities impacted by TB. For example, malnutrition—a key symptom of poverty—can be addressed through TB programming. Interventions in Pakistan and Indonesia introduced food incentives and enablers to help people with TB and their families continue treatment and improve their overall nutritional status [37,42]. A TB REACH project in India is currently documenting the impact of India's direct benefit transfer program plus additional food support on treatment outcomes. A CBO in Pakistan worked in collaboration with transgender women and male sex worker community leaders to provide both social and nutritional support. The project tested over 7000 people for TB and initiated anti-TB treatment for more than 600 individuals, documenting high rates of both TB and HIV among these key populations [62].

Workplaces are another setting where interventions to improve TB detection and treatment can incorporate biosocial approaches. Some settings have crowded working conditions which can increase the risk of occupational exposure to TB. Many factory workers often lack time and resources to access health care. Employees found to have TB are often at risk for discrimination, stigma, and the potential for losing their job. TB REACH has supported ACF factory-based projects for garment workers in Bangladesh and is currently supporting projects in Myanmar and in Indonesia. These projects not only focus on identifying and treating people with TB, they also work to provide education on TB awareness, stigma, and confidentiality to help empower workers to seek care in a safe environment while being able to continue to work.

During the introduction of GeneXpert technology, TB REACH made large investments in not only the diagnostic tests, but also the infrastructure, electricity, and health systems to help reach more people. While the assay is a clear improvement over smear microscopy to diagnose TB and drug resistance, its implementation in settings that lack proper power supply, space, efficient laboratory networks, and/or functional health facilities was challenging and additional investments were needed [63]. A laboratory test alone will not reach more people who are ill, and results have shown that simply placing Xpert within the health system is not enough to increase TB diagnoses [64]. New diagnostics must be placed in a functional health system including community structures/involvement with organized outreach to expand access to the technology and benefit many people [65,66].

TB epidemiology in the Asia Pacific Region indicates a higher risk for males [67], but women often carry the burden of TB disease differently—through being the unpaid caretakers, having their healthcare deprioritized for the benefit of their male counterparts, and carrying a heavy burden of stigma associated with the disease [68]. In addition, in many high burden TB settings women also suffer from high rates of gender-based violence, HIV and other co-occurring biosocial phenomena [69,70]. In line with the Canada's Feminist International Assistance Policy [71] and the Sustainable Development Goals [72], TB REACH is currently working on cultivating the links between empowering women, development and TB—an initiative first of its kind for the TB community [73]. Notably, Asia-Pacific region already has examples of strong female leadership at community level that are challenging existing gender norms and promoting gender equality through TB programming. In India, women from the community are trained to be agents of change and conduct TB education and case finding activities, as well as link people with TB to private and public health facilities for treatment [74]. In Indonesia, grassroots mobilization of female community volunteers brought a significant increase in TB notifications [37], but also strengthened the status of women in communities. In another project in Pakistan, the Kiran Sitara program trains young schoolgirls leadership and communication skills, while also advancing the TB response [75].

#### **7. Conclusions**

Moving from TB control to ending TB is a large shift in global policy and ambition. The Asia Pacific Region has embraced these ideas at the highest political levels [76,77]. To work towards ending TB, the TB community needs to be innovative, bold, and try things that have never been done at scale by working to bring the highest standards of care to all of those who need it. We need to make targeted investments to reach populations missed by the current approaches. ACF will be a necessary part of reaching people with TB earlier, in greater numbers, and bending the downward curve of incidence globally. However, ACF, and other innovations must be accompanied by a scale up of TPT to stem new cases from developing among people who are infected. The TB community must also embrace interventions that address the biosocial aspects of the disease, as solely medicalized approaches are insufficient to end TB. TB REACH was envisioned to test and evaluate new approaches and set them on a path to scale. We applaud the efforts to end TB in the Asia Pacific, and globally, and will continue to support new ideas to move us closer to this goal.

**Author Contributions:** J.C. wrote the first draft, which was critically reviewed by A.K., M.I.B., M.B., V.V.K., C.M., O.R., M.S., Z.Z.Q., R.S., K.S.R., L.B., and J.C. All authors contributed to subsequent drafts and agreed upon and approved the final version. All authors have read and agreed to the published version of the manuscript.

**Funding:** The article received no external funding, but Stop TB Partnership's TB REACH initiative is provided foundational funding by Global Affairs Canada, with USAID and The Bill and Melinda Gates Foundation providing additional support.

**Acknowledgments:** The work of TB REACH is implemented by more than 100 different partners across more than 50 countries who bring new ideas to the TB community, and we are grateful for the enthusiasm and excellent work that they all have done. We would like to acknowledge Katy Addison for her review and edits.

**Conflicts of Interest:** None declared.

#### **References**


**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Tropical Medicine and Infectious Disease*

#### *Article*

### **Enhanced Private Sector Engagement for Tuberculosis Diagnosis and Reporting through an Intermediary Agency in Ho Chi Minh City, Viet Nam**

**Luan Nguyen Quang Vo 1,2,\* , Andrew James Codlin <sup>1</sup> , Huy Ba Huynh <sup>1</sup> , Thuy Doan To Mai <sup>1</sup> , Rachel Jeanette Forse <sup>1</sup> , Vinh Van Truong <sup>3</sup> , Ha Minh Thi Dang <sup>3</sup> , Bang Duc Nguyen <sup>3</sup> , Lan Huu Nguyen <sup>3</sup> , Tuan Dinh Nguyen <sup>4</sup> , Hoa Binh Nguyen <sup>4</sup> , Nhung Viet Nguyen <sup>4</sup> , Maxine Caws 5,6, Knut Lonnroth <sup>7</sup> and Jacob Creswell <sup>8</sup>**


Received: 31 July 2020; Accepted: 1 September 2020; Published: 14 September 2020

**Abstract:** Under-detection and -reporting in the private sector constitute a major barrier in Viet Nam's fight to end tuberculosis (TB). Effective private-sector engagement requires innovative approaches. We established an intermediary agency that incentivized private providers in two districts of Ho Chi Minh City to refer persons with presumptive TB and share data of unreported TB treatment from July 2017 to March 2019. We subsidized chest x-ray screening and Xpert MTB/RIF testing, and supported test logistics, recording, and reporting. Among 393 participating private providers, 32.1% (126/393) referred at least one symptomatic person, and 3.6% (14/393) reported TB patients treated in their practice. In total, the study identified 1203 people with TB through private provider engagement. Of these, 7.6% (91/1203) were referred for treatment in government facilities. The referrals led to a post-intervention increase of +8.5% in All Forms TB notifications in the intervention districts. The remaining 92.4% (1112/1203) of identified people with TB elected private-sector treatment and were not notified to the NTP. Had this private TB treatment been included in official notifications, the increase in All Forms TB notifications would have been +68.3%. Our evaluation showed that an intermediary agency model can potentially engage private providers in Viet Nam to notify many people with TB who are not being captured by the current system. This could have a substantial impact on transparency into disease burden and contribute significantly to the progress towards ending TB.

**Keywords:** tuberculosis; private sector; intermediary agency; referral; notification; Viet Nam

#### **1. Introduction**

Tuberculosis (TB) is a curable disease, yet an estimated 10 million people develop active TB and 1.5 million people succumb to TB each year [1]. It remains the deadliest disease caused by a single infectious agent and a major source of avoidable deaths worldwide. Over the first 6 months of 2020, an estimated 867,000 persons died of TB as a negative consequence of the Covid-19 pandemic [2]. Moreover, it is estimated that about one-quarter of the world's population is infected with subclinical, noninfectious TB [3].

Viet Nam has a well-organized National Tuberculosis Control Programme (NTP). TB treatment is provided free of charge at all public sector sites and reported TB treatment outcomes are high. In 2014, Viet Nam committed to reduce TB prevalence to 20 per 100,000 by 2030 [4]. However, following the second national prevalence survey in 2018 [5], the country's estimated TB incidence rate was revised upward from 124 to 174 per 100,000, suggesting that just 57% of the estimated burden was captured by the NTP's official TB case notification statistics [6].

In 1986, the government initiated a package of reforms [7] that shifted Viet Nam's centralized, public healthcare sector towards neoliberalism and later to New Public Management, which resulted in the rapid development of a private healthcare sector [8]. Fueled by the country's strong economic growth and rising population welfare, demand for private sector services due to greater convenience and quality perceptions has similarly increased [9].

People often prefer to seek care with non-NTP facilities owing to their flexibility regarding diagnostic procedures, drug regimens and treatment observation methods, more convenient operating hours and locations, and lower administrative burden [10]. Studies have shown that pharmacies and private clinics represent the initial point of health care seeking for 50−70% of people with TB in Viet Nam [11–13]. Despite the existence of a mandatory notification law since 2007 [14], the implementation of this policy has been suboptimal. As such, the private healthcare sector is a major driver of 'missed people with TB' and loss to follow-up (LTFU) [15].

The Ministry of Health subsequently passed a law in 2013 (Circular 02/2013/TT-BYT) to enable systematic inclusion of private providers and public institutions outside of the NTP via four public-private mix (PPM) engagement models: (1) referral; (2) diagnosis; and referral; (3) directly observed treatment (DOT) provider and (4) full-service TB care facility [16]. The law has resulted in roughly 10% of TB case notifications at the national-level coming from PPM initiatives. Yet over 80% of these PPM notifications originate from public institutions, such as general care, military, and police hospitals that are not specialized in TB care and thereby are outside of the technical supervision of the NTP. This implies that private providers contribute only 2% to annual notifications nationwide. Meanwhile, it is estimated that about half of Viet Nam's 'missing cases' are taking their TB treatment outside of the NTP network [17]. More importantly, there is evidence that private sector TB care is often of substandard quality. Patients may suffer diagnostic delays with no bacteriological confirmation and receive inappropriate or inadequate treatment regimens. Poor adherence support has resulted in loss to follow-up rates of up to 65% [18–21].

A key reason for the limited engagement of private providers is the restrictive nature of Circular 02/2013/TT-BYT. Providers that wish to retain their clientele are expected to participate as a full-service TB facility and fulfill associated diagnostic and reporting requirements, while submitting to close oversight and supervision by the NTP. Meanwhile, benefits of participation, such as capacity building, free medicines, and eligibility for monetary stipends at government rates, may be insufficiently powered or implemented [16]. This has proven untenable for many non-NTP providers apart from large public tertiary care facilities. As a result, it is critical to develop and evaluate engagement schemes, which take into account the economic interests of smaller private providers.

One such scheme is the Private Provider Interface Agency (PPIA) model that has subsequently been scaled through the Joint Effort for Elimination of Tuberculosis (JEET) to 23 states of India [22,23]. This model employs intermediary agencies [15,24] that aim to offer a tangible value proposition with bottom-line impact rather than appeal to altruistic motivations [25,26]. This value proposition includes free or discounted access to nucleic acid amplification testing (NAAT) and medicines at pre-negotiated price-points for providers and patients and, perhaps most importantly, the option for private providers to retain their customers and thereby their livelihoods [27]. The implementation of PPIA's showed

promising results in multiple sites throughout India [28,29] and has been recognized as one avenue of sustainably scaling private sector engagement for TB worldwide [30].

In 2017, Friends for International TB Relief piloted a private-sector engagement initiative called Proper Care Private Sector (PCPS), modeled after the successful PPIA pilots from India [27]. This pilot investigated the feasibility of building a portfolio of private providers and measured the outputs of incentivizing and supporting referral and reporting of private TB treatment.

#### **2. Materials and Methods**

#### *2.1. Study Setting*

This pilot was conducted in two districts of Ho Chi Minh City (HCMC), Viet Nam—District 10 and Go Vap—between July 2017 and March 2019. The intervention area had a combined population of 1.2 million people and notified 1070 people with All Forms of TB in the 12 months preceding the study. In each district, there is a District TB Unit (DTU) responsible for managing diagnosis, treatment and notification of TB according to NTP guidelines and for coordinating patient management with primary health facilities. There were no official private sector TB-reporting entities in the evaluation area before this study's implementation.

#### *2.2. Private Provider Engagement*

We obtained lists of licensed private healthcare providers from each intervention district's regulatory authority. These providers included pharmacies, single-doctor practices and multi-doctor clinics. In collaboration with licensing, health, and TB authorities, through consensus we conducted a mapping exercise to identify priority providers with a high likelihood of encountering people who had pulmonary TB, while categorically excluding certain specialists, such as dermatologists, obstetricians, and gynecologists. Through repeated in-person and telephonic engagement, we recruited eligible providers. Interested providers were invited to capacity building events organized in collaboration with the Pham Ngoc Thach provincial lung hospital (PNT). The scope of these training events included new diagnostic tests for TB and specifically Xpert MTB/RIF (Xpert) and the newly recommended MTB/RIF Ultra assay [31], standardized TB treatment regimens, and follow-up schedules according to NTP guidelines. We complemented these formal training events with one-on-one provider detailing activities [32] to elaborate on the study's procedures, the provider's role and responsibilities, and the benefits of participation. Providers were eligible to participate through two principal strategies: diagnostic referral and private TB treatment reporting (Figure 1).

**Figure 1.** Schematic of the two private sector engagement strategies; the grey boxes show in which parts of the tuberculosis (TB) care cascade private providers were engaged by the study.

#### *2.3. Diagnostic Referral Strategy*

In this strategy, participating providers verbally screened their customers for TB symptoms and distributed referral vouchers to anyone reporting at least one TB symptom, i.e., (productive) cough or hemoptysis, weight/appetite loss, fatigue, fever, night sweats, chest pain, dyspnea. Symptomatic persons could use the voucher to access a chest X-ray (CXR) subsidy of VND 50,000 (USD 2.20 at an exchange rate of VND 22,700 = USD 1) at one of the study's 12 participating radiology sites. As the cost per CXR charged by these radiology sites ranged from VND 80,000 (USD 3.52) to VND 120,000 (USD 5.29), the radiography site collected the balance payment from the health-seeking person. In comparison, the price for one CXR at the District TB Unit was VND 49,000 (USD 2.16) at the start of the study and was subsequently raised to VND 69,000 (USD 3.04). Patients who elected to take their TB treatment with a private provider were charged a consultation fee of between VND 80,000 and VND 150,000 (USD 6.61) in addition to drugs and other services. According to field staff estimates, the approximate average cost per visit per person at private facilities was VND 200,000 (USD 8.81).

Persons assessed with parenchymal abnormalities on CXR by the X-ray technician and verified by the attending radiologist at the radiography site provided a sputum sample for free follow-on testing with the Xpert assay. At selected sites, health-seeking persons also underwent smear microscopy, in which case these results were requested from the participating provider as well. Sputum was collected at the radiography site or by the referring private provider. Study staff collected sputum specimens for transport to a designated government Xpert laboratory in Go Vap district. People with Xpert-positive results were encouraged to take treatment at their closest DTU, or at PNT if their Xpert result showed rifampicin resistance. When an individual was diagnosed and treated for TB via this strategy, the private provider making the initial referral received a VND 500,000 (USD 22.07) payment or approximately 2.5x the estimated average cost per visit per person. If the person chose to take TB treatment with a private provider, the treatment was recorded through the study's second strategy.

#### *2.4. Private TB Treatment Reporting Strategy*

The second strategy focused on documenting private TB treatment practices. Once a month, study staff collected TB treatment information from participating private providers. This information included individuals diagnosed through the diagnostic referral strategy above that elected treatment outside of the NTP. Providers were paid VND 500,000 (USD 22.07) for each complete patient report, which included the patient's name, age, sex, address, CXR results, sputum test results (Xpert, smear, culture, other), type of TB (pulmonary, extra-pulmonary), treatment regimen, and initiation dates. Treatment outcomes were not systematically assessed in this pilot study due to resource limitations and data provided by providers were sparse as providers did not conduct post-treatment follow-up with patients.

Despite the attempts to characterize these treatment reports in detail, they were not recognized by the NTP for official notification for several reasons. The primary reason was that these providers were not registered as official PPM model 4 participants in accordance to 02/2013/TT-BYT and therefore had not undergone required capacity building and site assessment by the NTP.

#### *2.5. Statistical Analyses*

We tabulated descriptive statistics for private provider engagement and participation, the number and proportion of referred people progressing through the study's TB care cascade by intervention district and the private TB treatment reported to our study. We calculated the ratio of bacteriologic confirmation over the number of successful CXR referrals. Official TB notifications were collected from the two intervention districts for three years prior to the study and during the study period to analyze trends of official TB notifications before and during the pilot. Additional notifications and percent change from baseline were calculated using a pre-/post-intervention comparison of official notification data in the intervention districts. Due to barriers outlined above, the collected private TB

treatment cases were not included in the official NTP notification statistics, so that a second additionality model was constructed to assess the impact of including these privately treated individuals in official TB statistics for the intervention districts. Statistical analyses were performed on Stata version 13 (StataCorp, College Station, TX, USA).

#### *2.6. Ethical Considerations*

The Institutional Review Boards of Pham Ngoc Thach Hospital (155/NCKH-PNT) and the Hanoi School of Public Health (324/2019/YTCC-HD3) granted scientific and ethical approval for this study. The Ho Chi Minh City Provincial People's Committee approved the implementation of the intervention (4699/QD-UBND). Participating private providers granted permission to use data for the analyses based on the terms and conditions of their practice. All personally identifying information was removed prior to analysis.

#### **3. Results**

#### *3.1. Private Provider Engagement and Participation*

The study enumerated 1107 licensed private providers in the two intervention districts (Table 1). Of these, 67.0% (742/1107) were targeted for recruitment based on the initial mapping exercise and 53.0% (393/742) of those targeted agreed to participate. Among participants, at least one staff member of 48.6% of centers (191/393) attended a capacity building event. By the end of the study, we recorded at least one referral for CXR from 32.1% (126/393).



Of the 126 private providers with at least one successful CXR referral (Table 2), 58.7% were multi-doctor clinics and 25.4% were single-doctor practices. These two provider types accounted for 70.0% and 18.9% of referrals, respectively. The remaining referrals were from pharmacies, hospitals or could not be traced to the source. The bacteriologic positivity rate among successful CXR referrals was highest among single pulmonologist practices at 58.6%, followed by multi-doctor clinics at 21.9% and single-doctor practices with no specialty focus at 11.2%. Eighty-two point two percent of the people diagnosed with TB via the diagnostic referral strategy were referred by just ten private providers constituting 7.9% (10/126) of those making at least one successful CXR referral and 2.5% (10/393) of those signing participation agreements.

The study received TB diagnosis and treatment data from 3.6% (14/393) of participating private providers. These consisted of 71.4% (10/14) single-doctor practices and 28.6% (4/14) multi-doctor clinics. The top five providers supplying TB diagnosis and treatment data reported 81.7% (907/1112) of patients on private TB treatment.


**Table 2.** Summary of chest X-ray (CXR) referrals and Bac(+) TB detection by type of private provider (2017-Q3 to 2019-Q1).

1 Indicates referrals from a separate community-based ACF initiative that accessed a private sector radiology site for CXR screening.

#### *3.2. Detection and Reporting Yield*

The study identified 1203 people with TB of whom 7.6% (91/1203) were referred and linked to care with the NTP (Figure 2), while 92.4% (1112/1203) consisted of private TB treatment reports and remained un-notified (Table 3). All 91 TB patients linked to care with the NTP were bacteriologically confirmed. Among persons treated in the private sector, the proportion with bacteriologic confirmation was 30.5% (339/1112). Together, the total proportion of TB patients with bacteriologic confirmation was 35.7% (430/1203). Overall, 1.2% (15/1203) were people with Multi-drug resistant TB (MDR-TB). Patients diagnosed with rifampicin resistance were largely referred by private providers to NTP facilities. Particularly, diagnostic referrals generated 93.3% (14/15) of persons detected with rifampicin resistance (Figure 2). Meanwhile, private TB treatment reports included one MDR-TB case (Table 3). In addition to persons treated for active TB, four persons were treated for latent TB infection by private providers.

were not systematically recorded, so that it was not possible to estimate a denominator or calculate a proportion.

**Figure 2.** Care cascade among persons screened and referred (2017-Q3 to 2019-Q1).


**Table 3.** Summary characteristics of reported private TB treatment by district.

1 Includes second-line regimen.

The results of the study's diagnostic referral strategy are in Figure 2. The 12 radiology centers recorded 4984 CXR results, of which 817 were abnormal (16.4% of those with CXR results). Sputum specimens were collected from 65.4% (534/817) of these individuals and tested on the Xpert assay with a positivity of 25.8% (138/534) including 14 individuals with rifampicin-resistant TB (14/138 = 10.1%). An additional 528 smear microscopy tests were conducted for individuals who did not get a CXR or presented no radiographic abnormalities suggestive of TB but still reported TB symptoms, resulting in the detection of 31 (31/528 = 5.9%) people with smear-positive TB. Of the total 169 people diagnosed with bacteriologically-confirmed TB, 95.9% (162/169) were linked to care, corresponding to a ratio of 3.2% among successfully referred persons with a CXR screen. Among patients linked to care, 56.2% (91/162) were initiated on treatment at a NTP facility, while 43.8% (71/162) elected to take treatment with the initially referring private provider. These patients are included in the private TB treatment reports.

The characteristics of the privately-treated, un-notified 1112 individuals are in Table 3. Of these, 30.5% (339/1112) had either a positive smear microscopy, Xpert, and/or culture result. Just 29.0% (322/1112) of those taking private TB treatment lived inside the study's intervention area, with another 41.1% (455/1112) living in one of HCMC's other 22 districts. About 28.7% (319/1112) of privately treated persons were registered residents of other provinces, while the remaining 1.3% (14/1112) of people had no documented address. Overall, 68.3% (759/1112) of people privately treated for TB were prescribed a standard first-line regimen as per NTP guidelines, while the records for another 27.6% (307/1112) of people showed the correct drugs but were modified from the standard regimen or missing information on duration. Three percent (33/1112) of treatments included streptomycin, and 1.1% (12/1112) included levofloxacin.

#### *3.3. Notification Impact*

Table 4 and Figure 3 summarize changes in the NTP's TB case notifications in the study's intervention area and present the modeled impact of including private TB treatment on official notification statistics. Bacteriologically-confirmed and All Forms TB notifications increased by +17.0% (+177 TB cases) and +8.5% (+158 TB cases), respectively, over six quarters of implementation. If private TB treatment had been eligible for inclusion in the official notification statistics, bacteriologically-confirmed and All Forms of TB notifications would have increased by +49.7% (+516 TB cases) and +68.3% (+1270 TB cases), respectively.


**Table 4.** Changes in public-sector TB case notification and private TB treatment by district and type of TB.

Baseline period = (2016-Q3 to 2017-Q2)\*2 + 2017-Q3. Intervention period = 2017-Q3 to 2019-Q1.

**Figure 3.** Pre- and post-intervention trends in public-sector TB case notifications and private TB treatment in the study area.

#### **4. Discussion**

Our pilot study showed that the PPIA model was effective in engaging a large number of private providers in the Vietnamese urban setting to contribute to TB care and prevention efforts. We found a substantial number of persons treated for TB in the private sector of HCMC, the vast majority of whom were not known to the NTP. This indicates that creating enabling mechanisms, as well as further scale-up and evaluation of private TB treatment reporting approaches, should be a critical component of the TB response in Viet Nam's urban areas.

Numerous studies have shown that effective engagement of private providers to screen for TB and refer presumptive cases for diagnostic testing can be an efficient way to close the detection gap [33–35]. This was corroborated by the results of our study and particularly by the increase in All Forms TB notifications compared to the baseline period. Moreover, this share of private provider contribution to notifications (+8.5%) was over five times Viet Nam's 2017 national average private sector contribution rate (1727/105,733 = 1.6%) [36]. Lastly, and perhaps most telling, un-notified private TB treatment reports corresponded to about 70% of the officially notified patient load in these two districts managed by the NTP. Even though these districts are not representative of the average district in Viet Nam, they present a compelling argument to expand novel private provider engagement models in the country's urban areas.

Meanwhile, the efficiency of this approach was evidenced by the high ratio of positively detected cases among those successfully referred. This high ratio suggests a pre-screening step performed by these healthcare professionals or self-selection by patients. The high ratio consequently implies the risk of false-negative assessments and missed opportunities to engage persons with TB. Therefore, more advocacy for providers and the general population to raise top-of-mind awareness about TB is warranted.

As observed on our study and documented by PPM projects in other settings, a referral strategy in isolation remains limited in both novelty and impact [37]. A more comprehensive engagement strategy is required to identify TB patients accessing treatment via the private sector. Including the reported private TB treatments into the NTP's routine surveillance would have represented a substantial increase in case notifications in the two study districts. However, since these providers did not complete the NTP's registration process as an accredited PPM partner, the private TB treatment records were not recognized as official notifications. The registration process is arduous and accompanied by external inspections and laborious reporting requirements, which can inhibit PPM participation for TB in Viet Nam [16]. This suggests the need for bold policies that promote private provider participation. This need is well-understood and has shown substantial impact in other settings once addressed [38,39].

Notification gains represent only the initial milestone. While all people with TB detected and notified through the referral strategy were bacteriologically confirmed, we observed low levels of bacteriologic confirmation among private-sector TB treatments, as only one-third was substantiated by a positive sputum test. We further observed that clinical diagnoses and follow-up testing for bacteriologically-confirmed patients oftentimes did not follow national treatment guidelines. As this study focused on case detection, treatment outcomes were optional to report and sparse when collected. Private providers did not employ a systematic follow-up process but also did not permit the study to directly engage their customers for household contact investigations due to fears of reputational damages from breaching patient confidentiality. This has also been observed in other settings [35] and represents a crucial opportunity to improve quality of private-sector TB care. This is particularly the case in light of the low attendance rate on the capacity building sessions offered by the study, as they were not mandatory for study participation. Consequently, while the goal of policy reform should be to remove unnecessary bureaucratic barriers to promote private provider participation, this reform should be designed with the long-term goal of improving quality of care among all stakeholders in mind.

Meanwhile, access to Xpert testing constituted a unique selling proposition of the PPIA to these providers, which they could pass on to their clientele. This study was the first to enable commercial access to Xpert testing for non-PPM providers in Viet Nam, so that the consistent message across size and geography of providers was that the ability to offer NAAT to their clients was a critical catalyst for participation. While this dynamic may be a temporary effect until market access is established through registration and formalization of a commercial distribution channel, intermediary agencies in other settings should leverage these dynamics to build the private provider network. Increased acceptance of Xpert testing has also been observed to result in a reduction of clinical diagnosis [40], so that increasing private-sector Xpert uptake could substantially reduce the rate of over-diagnosis and contribute to improved individual and public health outcomes. Efforts to optimize NAAT access have proven effective in several settings through the Initiative for Promoting Affordable, Quality TB tests [24,38,41].

An important lesson across both strategies was the need to sufficiently power monetary and non-monetary incentives. Evidence suggests that referral and notification incentives can represent a welcome income generation opportunity [42,43]. However, determining the appropriate threshold at which the individual cost-benefit analysis turns favorable is critical. The level of USD 22.07 proved sufficient to elicit private TB treatment reports among some, but it is safe to say that the 14 reporting providers in our study did not constitute the entire spectrum of private TB treatment. For example, risk-averse providers and those with a small caseload may have found the incentive to be insufficient to offset the risk exposure and expected value of penalties of un-notified TB treatment. These incentives may have also created inefficiencies whereby pulmonologists referred persons with TB through our study that would also have been referred in our absence as this level of incentive was high compared to traditionally paid amounts in Viet Nam [19,44,45]. Nevertheless, the costs of incentives paid by our study to detect a person with TB were a fraction of estimated total costs of detecting a new case through other systematic screening strategies [46] and warrant further optimization and evaluation.

A key success factor of the study was the broad coverage and participation of a diverse set of private providers. This was evidenced by the fact that we received referrals from all types of providers listed above and detected TB cases from most provider types. This effectiveness in generating leads and detecting TB patients also suggests that we were able to target the right providers. One reason for this was likely the detailed a priori landscaping and targeting, which allows implementers to have a better sense of the options people have for care seeking and coverage of their interventions [22,47].

Our study faced several limitations. With respect to private-sector TB treatment, our study was observational in nature, so that we did not attempt to change clinical practices. Similarly, we did not systematically incentivize and collect treatment outcomes in this study, but we intend to do so in future engagements. As such, provider willingness to alter behavior to meet international standards of TB care and the extent to which previously mentioned aspiration of improving diagnostic and treatment quality are feasible remain critical research questions to be answered on future studies. Another limitation was that we were only able to verify private TB treatment through reviews and abstractions of data, which were only available in patient records, as private providers did not permit direct engagement of their customers. The study's implementation area was limited, so that it is necessary to test the model at a greater scale to strengthen the generalizability of these results. Lastly, it also remains unclear, if this model or an adaptation thereof were appropriate in non-urban areas.

Nevertheless, this pilot study has elucidated the potential gains inherent in effective private sector engagement to national and provincial stakeholders in Viet Nam. As has been noted elsewhere, future work should focus on strengthening data systems, including the use of direct electronic data capture to track referrals and loss to follow up between referral and CXR [38]. This work should also employ mechanisms to verify that private TB treatment reports are genuine individuals who have not already been reported elsewhere in the TB notification system. Finally, policy changes are required to facilitate the scale-up of this approach.

#### **5. Conclusions**

Private providers in HCMC are treating many people with TB who are not reported to the national program, and it is critical to improve engagement approaches that arrive at a system, which allows private providers to notify through the NTP. To achieve public health targets, this system will also need to ensure the highest level of care adherent to national standards. Scaling effective private-sector engagement efforts, such as this enhanced intermediary model, could have a strong impact on the progress towards ending TB, and we recommend the NTP to scale up the model and through it to build capacity for improvements in quality of TB diagnosis and care.

**Author Contributions:** Conceptualization and protocol development, L.N.Q.V., R.J.F., H.M.T.D. and M.C.; data collection, H.B.H., B.D.N. and R.J.F.; data analysis and interpretation, L.N.Q.V., T.D.T.M. and A.J.C.; writing—original draft preparation, L.N.Q.V. and A.J.C.; writing—review and editing, L.N.Q.V., A.J.C., R.J.F., M.C., K.L. and J.C.; supervision, V.V.T., L.H.N., T.D.N., H.B.N., N.V.N.; funding acquisition, L.N.Q.V. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was supported by the TB REACH initiative of the Stop TB Partnership, grant number STBP/TBREACH/GSA/W5-25, with funding from the Global Affairs Canada. Additional support for its evaluation was provided by the European Commission Horizon 2020 Programme IMPACT TB grant number 733174.

**Acknowledgments:** The authors express their sincere gratitude to the Viet Nam National Tuberculosis Control Programme, the Pham Ngoc Thach Hospital and the staff working at the District TB Units in the study's intervention areas (District 10 and Go Vap) for their participation. The authors also wish to thank Giang T. Le, Thanh N. Vu and the Ho Chi Minh City Public Health Association and all participating private providers.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Tropical Medicine and Infectious Disease*

### *Article* **Does Drug-Resistant Extrapulmonary Tuberculosis Hinder TB Elimination Plans? A Case from Delhi, India**

**Sheelu Lohiya 1,\*, Jaya Prasad Tripathy <sup>2</sup> , Karuna Sagili <sup>3</sup> , Vishal Khanna <sup>1</sup> , Ravinder Kumar <sup>4</sup> , Arun Ojha <sup>1</sup> , Anuj Bhatnagar <sup>5</sup> and Ashwani Khanna <sup>1</sup>**


Received: 11 March 2020; Accepted: 28 May 2020; Published: 1 July 2020

**Abstract:** Extrapulmonary drug-resistant tuberculosis (DR-EPTB) poses a formidable diagnostic and therapeutic challenge.Besides associated with high morbidity, it is a major financial burden for the patient and the health system. In spite of this, it has often been neglected as it does not "pose" a visible public health threat. We study clinical profiles, treatment outcomes, and factors associated with unfavourable outcomes among DR-EPTB patients under programmatic settings in New Delhi, India, and evaluate how this could impact TB elimination. A retrospective analysis of all DR-EPTB patients registered at three nodal DR-TB centres in Delhi in 2016 was carried out. Of the 1261 DR-TB patients registered, 203 (16%) were DR-EPTB, with lymph nodes (118, 58%) being the most common site, followed by bone (69, 34%). Nearly 29% (*n* = 58) experienced adverse drug reactions with severe vomiting (26, 13 %), joint pain (21, 10%) and behavioral disorder (15, 7%). History of previous TB treatment was observed in a majority of the cases (87.7%). Nearly one-third of DR-EPTB cases (33%) had unfavourable treatment outcomes, with loss-to-follow-up (*n* = 40, 58%) or death (*n* = 14, 20%) being the most common unfavourable outcomes. In the adjusted analysis, weight band 31–50 kilograms (aRR = 1.8, 1.2–3.4) and h/o previous TB (aRR = 2.1, 1.1–4.8) were mainly associated with unfavourable outcomes. TB elimination efforts need to focus on all forms of TB, including DR-EPTB, leaving no one behind, in order to realise the dream of ending TB.

**Keywords:** adverse drug reactions; unfavourable outcome; lymph node TB; bone TB; TB elimination; extrapulmonary tuberculosis

#### **1. Introduction**

Tuberculosis (TB) remains the top infectious killer, ranking above HIV/AIDS, with 10.0 million cases and 1.4 million deaths in 2018 [1]. *Mycobacterium tuberculosis* (MTB), the causative agent, usually affects the lungs (pulmonary TB/PTB). However, MTB may spread through lymphatic or hematogenous routes to virtually any organ in the body, resulting in extrapulmonary TB (EPTB). The most common sites of EPTB infection include peripheral lymph nodes, pleura, genitourinary sites, bones and joints, abdomen (peritoneum and gastrointestinal tract), and the central nervous system.

While EPTB has existed for millennia, pulmonary TB has remained the prime focus of global TB control programmes. EPTB is often less contagious than PTB, and is therefore overlooked even though it constitutes about 15% of all forms of TB, amounting to nearly 1 million incident cases notified in 2018, as per the WHO Global TB report [1]. Additionally, EPTB results in significant morbidity and mortality due to various diagnostic and therapeutic challenges that lead to delayed care.

In the present era of HIV pandemic coupled with global emergence of multidrug-resistant TB (MDR TB) and extensively drug-resistant TB (XDRTB), drug-resistant EPTB (DR-EPTB) presents a real and new public health challenge that has yet to receive serious attention. While drug resistance in PTB has been extensively studied, DR-EPTB has been neglected. Several systematic reviews and individual patient meta-analysis have reported treatment outcomes of MDR-TB, without disaggregated outcomes of DR-EPTB [2–5]. The WHO MDR-TB update, as per the global TB report, shows treatment success of 55%, a death rate of 15%, 14% lost to follow up, 8% of failed treatment and 7% of the patients not evaluated [6]. However, there is little information on outcomes disaggregated by type of TB, especially DR-EPTB. Interestingly, the National Tuberculosis Program of India does not report treatment outcomes separately for PTB and EPTB in DRTB reports.

India continues to have the highest number of TB cases in the world, with nearly 2.69 million cases in 2018 [7]. It also features among the top 10 high MDR-TB burden countries, with nearly 130,000 MDR/RR-TB cases notified in 2018 [1]. The Revised National Tuberculosis Control Programme (RNTCP) has reported poor treatment outcomes of successive MDR-TB cohorts [5,8]. Previous studies in four large states of India also reported poor overall treatment outcomes (40%–56%) among DR-TB patients, with high rates of death and lost-to-follow-up (LTFU) [9,10]. However, there is scarce information in the country on the profile and treatment outcomes of DR-EPTB patients and their associated risk factors. While it may be expected that treatment outcomes and associated risk factors of DR-EPTB are different from those of DR-PTB, there is no scientific evidence to support this.

India aims to eliminate TB by 2025; however, this goal will remain unachieved if EPTB, especially the drug-resistant cases, continues to be ignored [11]. Compared to the rest of the country, the situation is different in Delhi, with 42% EPTB among all TB cases, probably due to better availability of diagnostic services [8]. However, there are no estimates of the burden of DR-EPTB since disaggregate figures are not routinely reported in the programme. A previous study by Kant et al. in North India has reported a 13.4% prevalence of drug resistance among all EPTB cases [12]. Another study in Mumbai showed resistance in 29% of Mycobacterium isolates in extrapulmonary specimens [13]. A similar study from Chennai found that 37/189 (19%) of extrapulmonary TB specimens were multidrug-resistant, while one was extensively drug-resistant (XDR) [14].

A better understanding of this small yet significant group of patients is necessary to design effective interventions that might help reduce morbidity and mortality and improve treatment success rates. When the global community talks about TB elimination, it talks about TB per se; however, most interventions and strategies are focused on pulmonary TB. The strategy and milestones to end the global TB epidemic include all diagnosed TB cases and latent TB cases [7], hence we need specific interventions to focus on extrapulmonary TB, both sensitive and resistant.

Indicators such as TB treatment coverage, treatment success rates, the percentage of TB-affected households that experience catastrophic costs due to TB and drug-susceptibility testing (DST) coverage for TB patients is difficult to measure, and sustainable development goals (SDGs) cannot be achieved without giving due importance to DR-EPTB [15].

To address these gaps, we carried out this operational research in order to study the demographics, clinical profiles, and treatment outcomes of patients with DR-EPTB registered at three selected DR-TB nodal centres in Delhi in 2016, and explored risk factors associated with unfavourable treatment outcomes.

#### **2. Methods**

#### *2.1. Study Design*

This is a retrospective cohort study involving a record review of routine program data.

#### *2.2. Setting*

#### General Setting

Delhi is the capital of India inhabited by 18.6 million people, with a large number of migrants. It has one of the highest population densities of 11,320 persons per square km, and a literacy rate of 86% [16]. Delhi has the highest rate of TB notification in the country, probably due to better diagnostic facilities in tertiary care hospitals [17].

The Programmatic Management of Drug-Resistant TB (PMDT) services were launched in India in 2006 and obtained full geographical coverage in 2013. PMDT services started in Delhi in 2008 with a culture and drug susceptibility testing (C & DST) laboratory located at the state-owned Intermediate Reference Laboratory (IRL). Other tests, such as the cartridge-based nucleic acid amplification test (CBNAAT) and line probe assay (LPA), are also available at the IRL. PMDT services are provided through 25 chest clinics and four Nodal DR-TB centres in Delhi. Since 2018, all the chest clinics in Delhi have been designated as district DR-TB centres.

Microbiological confirmation of disease for DR-EPTB patients is preferred for diagnosis. This is done using either CBNAAT or culture or both. However, clinical diagnosis is also reached with the help of fine needle aspiration cytology (FNAC), histopathology findings, or interferon gamma release assays (IGRA), along with other signs and symptoms of TB, especially among those not responding to the WHO drug-sensitive ATT regimen. The patients are usually diagnosed at the district DR-TB centres or nodal DR-TB centres, and a sample, if available, is sent to the IRL along with a filled form requesting C&DST. Patients are started on the conventional MDR regimen at the Nodal DR-TB centres after pretreatment evaluation, as per NTP guidelines. Further follow-up and management is done at the district DR-TB centres. The diagnostic algorithm, which is common for both pulmonary and EPTB, is given in Figure 1 [18].

The conventional RNTCP regimen for MDR-TB is given to the patients with DR-EPTB, i.e., intensive phase with six drugs for 6–9 months (kanamycin, ofloxacin, ethionamide, cycloserine, pyrazinamide, ethambutol and pyridoxine), followed by a continuous phase with four drugs for 18 months (ofloxacin, ethionamide, cycloserine and ethambutol) as per RNTCP PMDT guidelines 2016 [7]. The patients found to be fluoroquinolone-resistant or resistant to other injectable drugs are started on the pre-XDRTB regimen (switched to high dose moxifloxacin and PAS).

Clinical monitoring is mainly based on clinical parameters such as weight gain, change in the size of lymph nodes/lesions, the appearance of new lymph nodes/lesions and monitoring of other EP sites located deep in the body by ultrasound, magnetic resonance imaging, computed tomography scan, and ESR (erythrocyte sedimentation rate). Surgery is considered in the absence of response to chemotherapy despite 6–9 months of treatment [18,19].

Treatment outcome definitions used by the RNTCP are given in Box 1. They are similar for pulmonary and extrapulmonary DR-TB patients. After the completed course of treatment, outcomes are assessed based on the response to treatment in terms of the resolution of symptoms and healing of lesions assessed through culture reports of specimens taken from discharging sinuses (if available) and investigation reports (e.g., ultrasonography, bone X-ray and magnetic resonance imaging).

Regular monitoring of side effects of drugs is done by blood tests (complete blood count, serum urea, creatinine, electrolytes, blood glucose, alkaline phosphatases, transaminases, total bilirubin), audiometry, thyroid function tests, ocular examinations, ECG for QT prolongation and other tests, if needed.

**Figure 1.** Diagnostic algorithm of drug-resistant tuberculosis as per PMDT India 2017. RR-TB, rifampicin-resistant tuberculosis; RS-TB, rifampicin-sensitive tuberculosis. SL-LPA, second line, line probe assay; FL-LPA, first line, line probe assay. FQ, fluoroquinolone; SLI, second line injectable; H, isoniazid; DRTB, drug-resistant TB; EPTB, extrapulmonary TB.

**Box 1.** Operational definitions for treatment outcomes in patients with multidrug-resistant TB (MDR TB).

**Cure:** Treatment completed as recommended by the national policy without evidence of failure, and three or more consecutive cultures taken at least 30 days apart during CP are negative, including culture at the end of treatment.

**Treatment completed:** Treatment completed as recommended by the national policy without evidence of failure, but no record that three or more consecutive cultures taken at least 30 days apart are negative after the intensive phase.

**Treatment success:** This is a combination of cure plus treatment completed.

**Treatment failure:** Treatment terminated or a need for permanent regimen change of at least two or more anti-TB drugs in CP because of the lack of microbiological conversion by the end of the extended intensive phase or microbiological reversion in the continuation phase after conversion to negative or evidence of additional acquired resistance to FQ or SLI drugs or adverse drug reactions (ADR).

**Death:** A patient who dies for any reason during the course of treatment.

**Treatment lost-to-follow-up:** A patient whose treatment was interrupted for one month or more for any reasons prior to being declared as failed.

*Not evaluated:* A patient for whom no treatment outcome is assigned.

*Regimen changed:* A TB patient's need for permanent regimen change of at least one or more anti-TB drugs prior to being declared as failed.

**Treatment stopped due to adverse drug reactions:** A patient who develops adverse drug reactions and cannot continue the M/XDR-TB treatment in spite of the management of adverse drug reactions as per the defined protocols and a decision has been taken by the DR-TB Centre committee to stop treatment.

#### *2.3. Study Site*

The study was conducted in three designated Nodal DR-TB centres under RNTCP in the state of Delhi.

#### *2.4. Study Population*

The study population included all DR-EPTB patients registered from 1 January 2016 to 31 December 2016 in the three selected nodal DR-TB centres in Delhi. These patients were admitted to a common TB hospital and initiated on a conventional MDR-TB regimen.

Those with associated pulmonary TB or on ITR (individualised treatment protocol) or XDR treatment regimen were excluded from the study; there were only three cases of associated pulmonary TB.

#### 2.4.1. Data Variables, Sources of Data and Data Collection

A list of all eligible DR-EPTB patients registered in 2016 at the selected nodal DR-TB centres was prepared. The principal investigator (SL) extracted data from the patient treatment cards and PMDT registers from September 2018 to February 2019 into a structured data collection instrument.

Socio-demographic and clinical variables like PMDT TB number, date of registration, nodal DR-TB centre, age, sex, type of disease (primary/secondary MDR), site/s involved, history of previous TB treatment, site involved in previous TB episode, basis of diagnosis, resistance to drugs, comorbidities like HIV, diabetes, initial weight (in kilograms), final weight (in kilograms), adverse drug reaction, number of missed doses, treatment outcome (see Box 1) and date of outcome were included. Primary and secondary MDR was based on the previous TB treatment history.

#### 2.4.2. Data Analysis and Statistics

Data collected were double-entered and validated using EpiData version 3.1, and discrepancies were corrected by referring to the data collection forms or the original patient files. Data analysis was carried out using EpiData analysis version 2.2.2.183 (EpiData Association, Odense, Denmark) and STATA version 13.0. Number and proportion were used to summarise categorical variables, and mean (standard deviation) or median (interquartile ranges (IQR)), as applicable, were used to summarise continuous variables. A chi-square test was performed to find the association of various socio-demographic and clinical variables with the treatment outcome. Binomial regression was done to explore the predictors of unfavourable treatment outcomes after controlling for confounders. The strength of association was expressed using relative risks (RRs) and 95% confidence intervals (95% CI). Variables with *p* < 0.2 on univariable analysis were included in the final regression model. Unfavourable outcomes were defined as death, loss to follow-up, treatment failure, not evaluated, regimen change, or stopped treatment due to reasons other than adverse drug reactions. Favourable outcome was defined as treatment completed and cured.

#### **3. Ethics Approval**

Administrative approval was obtained from the State TB Office, Delhi, India. Ethics approval was obtained from the Ethics Advisory Group of the International Union Against Tuberculosis and Lung Disease, Paris, France. Names of patients were not captured. The PMDT registration number was used to identify patients.

#### **4. Results**

#### *4.1. Patient Characteristics*

Of the total 1261 DR-TB patients registered in the three selected DR-TB sites in Delhi in 2016, 1058 (84%) were pulmonary and 203 (16%) were DR-EPTB cases, all of whom were included in the study.

Most patients were female (111, 54.7%), aged 15–44 years (147, 72.4%). Around two-thirds of the patients (134, 66.0%) weighed less than 50 kilograms. Lymph node (118, 58.1%) was the most common site of involvement, followed by bone and joint (69, 34.0%). A large majority of patients had a previous history of TB (178, 87.7%). CBNAAT was the basis of diagnosis in 173 patients (85.2%) and LPA in 20 (9.9%) cases (Table 1**).**


**Table 1.** Baseline demographic and clinical characteristics of drug-resistant extrapulmonary TB patients in Delhi in 2016 (*n* = 203).


**Table 1.** *Cont.*

TB: tuberculosis; HR: isoniazid, rifampicin CBNAAT: cartridge-based nucleic acid amplification test; DR-TB: drug-resistant tuberculosis. All CBNAAT-negative, culture-positive samples were subjected to second-line DST and put on LPA for first-line DST.

#### *4.2. Adverse Drug Reactions (ADRs)*

Nearly 28.6% (*n* = 58) experienced at least one ADR, with severe vomiting (26, 12.8%), joint pain (21, 10.3%), behavioral disorder (15, 7.4%) and hearing loss (7, 3.4%) being the most commonly observed ADRs (Table 2).

**Table 2.** Adverse drug reactions among drug-resistant extrapulmonary TB cases in Delhi in 2016 (*n* = 58).


Others include ocular disturbance, hemiparesis.

#### *4.3. Delay in Treatment Initiation*

The median (IQR) number of days from diagnosis to registration for treatment was 15 [9–25] days, whereas from diagnosis to initiation of treatment was 14 days [8–24].

#### *4.4. Treatment Outcomes*

Overall treatment success was 66% (*n* = 134). Of the 69 (34%) patients with unfavourable treatment outcomes, most of them were due to LTFU (*n* = 40, 58.0%) or death (*n* = 14, 20.3%) (Table 3).


**Table 3.** Treatment outcomes of drug-resistant extrapulmonary TB cases in Delhi, 2016.

ADR = adverse drug reaction.

In the adjusted analysis, weight band 31–50 kilograms (aRR = 1.8, 1.2–3.4, *p*-value = 0.02), DR-TB centre (aRR = 1.5, 1.0–2.5, *p*-value = 0.05) and history of previous TB (aRR = 2.1, 1.1–4.8, *p*-value = 0.03) were significantly associated with unfavourable treatment outcomes (Table 4).


**Table 4.** Socio-demographic and clinical factors associated with unfavourable treatment outcomes among drug-resistant extrapulmonary TB cases in Delhi, 2016.

TB: tuberculosis; HR: isoniazid, rifampicin; ADR: adverse drug reaction; CBNAAT: cartridge-based nucleic acid amplification test.

Stratified analysis was conducted to study the associations with unfavorable treatment outcomes in two different age groups (< 15 years and ≥ 15 years; Tables S1 and S2 in supplementary materials) Weight was not associated with unfavourable treatment outcomes among both children (< 15 years) and adults. Type of DR-TB centre was associated with the outcome among children and age ≥ 45 years was a significant predictor of unfavourable treatment outcome.

#### **5. Discussion**

The key findings of our study are: (i) one in every six registered DR-TB patients has DR-EPTB, (ii) lymph node is the most common site of involvement, followed by bone, in DR-EPTB patients, (iii) one-third of all DR-EPTB cases had unsuccessful treatment outcomes, and (iv) baseline weight, DR-TB centre and history of previous TB were significantly associated with unsuccessful treatment outcomes.

Of all DR-TB patients registered, 16% were DR-EPTB cases. These figures are comparable to the prevalence of EP disease in drug-sensitive cases [20]. This is probably due to the availability and scale-up of rapid TB diagnostics (CBNAAT) in the region. With universal access to DST, DR-EPTB is an important and clinically challenging subgroup to tackle. A 10-year epidemiological study in China observed a higher proportion of MDR TB among patients with EPTB [21]. They observed a large increase in MDR TB, from 17.3% to 35.7%, for pleural TB cases. A similar high proportion of drug resistance has also been observed from extrapulmonary specimens in India [12–14]. The increasing drug resistance among EPTB highlights the need for drug susceptibility testing and the formulation of more effective regimens for extrapulmonary TB treatment.

Lymph node involvement is the most common EPTB, in general. We encountered a similar pattern in the DR-EPTB cases in the previous literature from the Netherlands (39%), the United States (40%), and the United Kingdom (37%) [11,22]. Pleural TB is the most prevalent form of extrapulmonary TB in Poland (36%) and Romania (58%), and bone TB (41%) is the most common site in China [21]. This study shows that bone TB (includes musculoskeletal TB) is the second most common site of DR-EPTB, accounting for nearly one-third of the cases. This finding is supported by other studies in the literature [23,24].

Nearly two-thirds of DR-EPTB cases (66%) had favourable treatment outcomes. This is better than the outcomes of the overall national DR-TB cohort (47%) notified between the 3rd quarter of 2014 to the 2nd quarter of 2015, which ranged between 36%–61% across all states [8]. Similarly, previous studies from India have also reported lower success rates among different DR-TB cohorts [5,9,10].

A recent study at a DR-TB centre in Mumbai reported a much higher completion rate of 82% among DR-EPTB patients, probably because it was a single centre study with different patient profiles and the use of a shorter regimen, which showed much better treatment completion rates [23].

A review found that the death rates among DR-EPTB patients were widely ranged from 0%–80% in different studies across the globe [11]. This wide variation in death rates could be due to various factors such as patient profiles, delayed diagnosis, comorbidities, severity of the disease, and type of regimen/treatment protocol. The present study reports 14 deaths (6.9%), probably because of treatment with suboptimal regimens. Culture DST or 2nd line LPA is not always possible, either due to insufficient clinical samples or inability to obtain samples from an inaccessible site, which renders resistance profiling difficult. Newer treatment options with newer drugs may be tried.

LTFU is common, which was seen among one-fifth of the patients. However, newer initiatives such as mobile adherence support, online web-based platform (Nikshay) for real-time reporting, efficient referral systems using Nikshay ID and newer treatment guidelines (all-oral H mono-resistant DRTB regimens, shorter MDR TB regimens, all-oral longer MDR TB regimens) could contribute to a decrease in LTFU.

The risk factors for unfavourable treatment outcomes help in stratifying patients for additional monitoring and improving outcomes. Patients with a previous history of TB have worse outcomes, which supports the findings in other studies [9,11]. This calls for more aggressive monitoring of treatment in such patients.

Patients registered at DR-TB Centre 2 had a higher risk of unfavourable treatment outcomes, mostly LTFU or transferred out, because the centre receives a large number of patients from regions

outside Delhi, who are eventually lost to follow-up. This calls for close monitoring, and better linkages and tracking of such patients.

A weight band between 31–50 kg at baseline was found to be significantly associated with unfavourable treatment outcomes compared to a weight band of < 30 kg. This has to be interpreted with caution as the role of unexplained confounders cannot be ruled out. A stratified analysis was conducted to study the association of weight bands on treatment outcomes in different age groups (children < 15 years and adults > 15 years). Although statistical significance was not seen, the proportion of outcomes among the 31–50 kg weight band was higher compared to other weight bands. Statistical nonsignificance could be due to small numbers and fewer numbers of outcomes in exposure categories, especially among children. This warrants a better understanding of the role of initial weight in determining treatment outcomes. We also need to explore whether a change in weight during the course of treatment or body mass index are better indicators compared to baseline weight in predicting outcomes.

The strength of this study is that it was conducted within the routine programmatic setting in three designated Nodal DR-TB centres under RNTCP in Delhi. All the cases of DR-EPTB registered during the study period from three out of four nodal DR TB centres (covering 21 out of 25 chest clinics) in Delhi were included in the study without any exclusion, which covered nearly 90% of all such cases during the study period. This lends generalizability to the study findings. The study also adhered to Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines for conducting and reporting on observational studies [25]. There were some limitations as well. First, as this is a retrospective study using programmatic data, information on other possible predictors for TB treatment outcomes, such as socio-economic status, adherence to treatment, smoking and alcohol intake status, were not available. Second, a large majority of the cases were bacteriologically confirmed, thus indicating that many clinically diagnosed cases may have been missed. Third, the MDR-TB treatment regimens have changed in the last couple of years, such as the replacement of ofloxacin with levofloxacin or moxifloxacin, which might affect treatment outcomes. This requires similar analysis of the successive cohorts.

The study results have four important programmatic implications. First, high rates of death and LTFU among DR-EPTB patients need to be addressed urgently. Besides the risk factors identified in this study, some of which are non-modifiable, a shorter and easier-to-follow DR-TB treatment regimen with newer oral drugs such as bedaquiline or delamanid is probably the answer to reducing mortality and LTFU in this patient group. With the recent evidence from trials and large observational cohorts, the WHO stance has also departed from conventional treatment approaches for MDR TB in favour of shorter regimens with noninjectables [14,26,27]. However, newer drugs are being given only for pulmonary DRTB at present in India. The high LTFU could also well be due to the fact that a large chunk of the residents in the study area are mobile migrants. Delhi, being the capital city and a medical hub with modern health care facilities, receives patients from all over the country for diagnosis, who do not usually remain in the city to complete their treatment. Thus, close monitoring of the transfer-out-policy is necessary in order to understand the referral system, identify any loopholes within, and address them accordingly. Nikshay is a welcome step in this regard, wherein a unique ID is given to each patient to enable tracking. However, the objective of Nikshay ID is far from being achieved. More operational research is needed to identify the gaps in the referral mechanism and streamline the process to minimise leakages.

Second, low weight was also one of the risk factors for unfavourable treatment outcomes, which require tailored interventions to improve treatment outcomes for these patient sub-groups, especially those with poor weight at baseline and with a previous history of TB. The national program has initiated "Nikshay Poshan Yojana" which provides incentives for nutritional support to TB patients, which is a welcome step; however, studies have reported poor implementation of this [7]. Proper implementation of such schemes, with further customised options such as packaged groceries, would be more beneficial.

Third, the proportion of DR EP-TB diagnosed clinically stands at a dismal 4% in this study. The diagnosed drug-sensitive EP-TB cases in Delhi constitute about 40%–45% of all TB cases, as per the India TB Report, while DR EP-TB is usually 15% to 20% of all DR-TB cases. It shows that we are probably missing clinically diagnosed EP-DRTB cases. Clinical nonresponders of EP-TB need to be reported too. In addition, there is over-reliance on bacteriological confirmation and drug sensitivity testing for the diagnosis of DR EP-TB, which is resulting in the underestimation of clinically diagnosed cases. Thus, diagnosis should be based on clinical judgement supported by culture/Xpert results, and not solely on bacteriological tests, as is common practice.

Fourth, those with a previous history of TB could be followed-up for at least two years to document relapse-free survival. For this, an aggressive strategy of follow-up and monitoring needs to be in place.

#### **6. Conclusions**

DR-EPTB constitutes a significant subgroup of the DR-TB cases that needs urgent attention. Every third DR-EPTB patient has unfavourable treatment outcomes, with high rates of LTFU that needs to be tackled if we are to realise the goal of ending TB. The use of shorter regimens and close monitoring/tracking of the migrant population and the transfer-out cases are required to minimise LTFU. Those with a previous history of TB need to be monitored closely for compliance to treatment. Further studies are needed to understand the operational reasons for the low proportion of clinically diagnosed DR EP-TB and explore the role of baseline weight or other proxy indicators, such as body mass index or weight gain during the treatment, in predicting treatment outcomes.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2414-6366/5/3/109/s1.

**Author Contributions:** Conceptualization, S.L., J.P.T. and K.S.; methodology, S.L., J.P.T., K.S. and A.K.; data collection, S.L., V.K., R.K., A.O. and A.B.; data curation and analysis, S.L., J.P.T., K.S.; resources, S.L., V.K., R.K., A.O., A.B., A.K.; writing—original draft preparation, S.L., J.P.T. and K.S.; writing—review and editing, S.L., V.K., R.K., A.O., A.B. and A.K.; supervision, S.L., V.K., R.K., A.O., A.B. and A.K.; project administration, S.L., V.K., R.K., A.O., A.B. and A.K. All authors have read and agreed to the published version of the manuscript.

**Funding:** No funding was obtained for this study. The training course under which this research was conducted and the open access publication charges were funded by The Global Fund to Fight AIDS, Tuberculosis and Malaria (GFATM). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

**Acknowledgments:** This research was conducted as a part of the "National Operational Research Training Course 2018–2019" organised by Project Axshya, funded by The Global Fund and implemented by The International Union Against Tuberculosis and Lung Diseases (The Union), South-East Asia Regional Office, New Delhi, India. The training course was conducted in collaboration with Revised National Tuberculosis Control Program, Ministry of Health and Family Welfare, Government of India, and National Institute for TB and Respiratory Diseases, New Delhi, India. The training is based on "The Union/Medécins sans Frontières (MSF)" model OR course and has been acknowledged/accredited by the Special Programme for Research and Training in Tropical Diseases at the World Health Organization (WHO/TDR) under SORT IT (Structured Operational Research and Training Initiative). Mentorship and facilitation for this course was provided through The Union South-East Asia Office, New Delhi; the Centre for Operational Research, The Union, Paris, France; Baroda Medical College, Vadodara; Médecins Sans Frontières, New Delhi; ESIC Medical College and PGIMSR, Bengaluru; North Delhi Municipal Corporation Medical College, Hindu Rao Hospital, New Delhi; GMERS Medical College, Vadodara; Postgraduate Institute of Medical Education and Research, Chandigarh, India; Yenepoya Medical College, Mangalore. We acknowledge the support of S.M. Abbas, Rashmi, Mahesh and Hitesh for their assistance in data collection.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Tropical Medicine and Infectious Disease*
