Next Article in Journal
Development of an Information and Communication Technology (ICT) Tool for Monitoring of Antimicrobial Use, Animal Disease and Treatment Outcome in Low-Income Countries
Previous Article in Journal
Seasonal Change in Microbial Diversity: Bile Microbiota and Antibiotics Resistance in Patients with Bilio-Pancreatic Tumors: A Retrospective Monocentric Study (2010–2020)
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Antibiotics
Volume 14
Issue 3
10.3390/antibiotics14030284
antibiotics-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Antimicrobial Stewardship Impact on Antibiotic Use in Three Tertiary Hospitals in Zambia: A Comparative Point Prevalence Survey

by
Steward Mudenda
1,*,
Kenneth Kapolowe
2,
Uchizi Chirwa
2,
Melvin Chanda
2,
Raphael Chanda
2,
Rodney Kalaba
2,
Sombo Fwoloshi
2,
Christabel Phiri
2,
Mukuka Mwamba
2,
Robert Kajaba Chirwa
2,
Kotey Nikoi
2,
Linda Musonda
2,
Kaunda Yamba
3,
Josepsh Yamweka Chizimu
3,
Chitalu Chanda
4,
Tamica Mubanga
4,
Chisha Simutowe
4,
John Kasanga
5,
Mulope Mukanwa
5,
Katongo Hope Mutengo
5,
Philip Matthew
6,
Fabian Maza Arnedo
6,
Jyoti Joshi
6,
Jonathan Mayito
6,
Ruth Nakazwe
2,
Maisa Kasanga
2,7 and
Duncan Chanda
2,*add Show full author list remove Hide full author list
1
Department of Pharmacy, School of Health Sciences, University of Zambia, Lusaka 10101, Zambia
2
University Teaching Hospitals, Lusaka 10101, Zambia
3
Antimicrobial Resistance Coordinating Committee, Zambia National Public Health Institute, Lusaka 10101, Zambia
4
Ndola Teaching Hospital, Ndola 10101, Zambia
5
Livingstone University Teaching Hospital, Livingstone 10101, Zambia
6
International Center for Antimicrobial Resistance Solutions (ICARS), Ørestads Boulevard 5, 2300 Copenhagen, Denmark
7
Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou 450001, China
*
Authors to whom correspondence should be addressed.
Antibiotics 2025, 14(3), 284; https://doi.org/10.3390/antibiotics14030284
Submission received: 18 January 2025 / Revised: 2 February 2025 / Accepted: 7 February 2025 / Published: 10 March 2025
(This article belongs to the Special Issue Antibiotics: Utilization, Resistance, and Infection Prevention)
Browse Figures
Versions Notes

Abstract

:
Introduction: Antimicrobial stewardship (AMS) can improve the rational use of antibiotics in hospitals. This study assessed the impact of a multifaceted AMS intervention on antibiotic use and prescribing patterns at three tertiary hospitals in Zambia. Methods: Point Prevalence Surveys (PPS) were conducted in three tertiary hospitals in August 2022 and in October 2023. It was part of a 3-year AMS demonstration project that aimed to optimize the use of antibiotics in treating urinary tract infections (UTIs) and bloodstream infections (BSIs) in various health sector settings in Zambia. Up to 170 medical records in 2022 and 265 in 2023 were included in the assessment. Results: Overall, the prevalence of antibiotic use in this PPS was 75%. Eighty-one percent (81%) and 71% of patients assessed were on at least one antibiotic in 2022 and 2023, respectively, indicating a decrease of 10%. Similarly, prescribing ceftriaxone, the most prescribed antibiotic, declined from an average of 48% in 2022 to 38% in 2023. Adherence to Standard Treatment Guidelines (STGs) slightly increased from 42% in 2022 to 45% in 2023. Additionally, antibiotic prescribing was reduced from 1.38 to 1.21. Conclusions: Antimicrobial stewardship had an early positive impact on antibiotic use and adherence to Standard Treatment Guidelines.

1. Introduction

The discovery of antibiotics was a great milestone that transformed the treatment of infectious diseases [1,2]. It enabled the treatment of potentially fatal infections and allowed for the execution of intricate medical procedures with lower infectious morbidity [3,4]. However, over the years, antibiotics have been used indiscriminately, with over 50% of the patients receiving unnecessary antibiotics [5,6,7,8]. Additionally, the inappropriate use of antibiotics has led to the emergence and spread of antimicrobial resistance (AMR) [9,10,11]. AMR is a threat to global health and has had a negative impact on the economy and food insecurity as well as treatment failure and increased morbidity and mortality [9,12,13,14,15,16]. If not addressed, it is predicted that more than 10 million people will die annually by the year 2050 [17,18]. Due to these impacts of AMR, there is a need to instigate strategies such as antimicrobial stewardship (AMS) programs to address its emergence and spread [18,19,20,21,22,23].
AMR is a natural phenomenon but is accelerated by the indiscriminate use of antibiotics in humans, animals, agriculture, and the environment [18,24]. Some of the critical drivers of AMR include the overuse, underuse, and misuse of antibiotics in hospitals [25,26,27], compounded by the lack of awareness and non-adherence to the recommended treatment guidelines [28,29,30,31,32]. Further, AMR is also influenced by the lack of diagnostic services in healthcare facilities, especially in low- and middle-income countries (LMICs), which leads to the inappropriate use of antibiotics [33,34,35,36,37,38]. The risk of drug-resistant infections is high in healthcare facilities with low awareness and knowledge as well as a lack of training in antimicrobial use (AMU), AMR, and AMS [27,39,40,41].
Antimicrobial stewardship (AMS) programs are essential in improving the appropriate use of antibiotics to control AMR [42,43,44,45] through educating and training health workers on treatment guidelines, causes of AMR, rational use of antibiotics, and strategies to address AMR [19,43,46,47,48,49]. To ensure a standardized AMR response, in 2015, the WHO developed the Global Action Plan (GAP) to address AMR through a One Health approach to surveillance [50,51,52,53]. Member states of the WHO were encouraged to develop National Action Plans (NAP) on AMR to address the global AMR threat [51,54]. Additionally, in 2017, the WHO developed and implemented the Access, Watch, and Reserve (AWaRe) classification of antibiotics as an AMS tool to promote the rational prescribing of antibiotics to optimize antibiotic use [55,56,57,58,59,60,61]. The AWaRe classification of antibiotics includes the Access group antibiotics that must be available at all times in healthcare facilities, have fewer side effects and lower potential for the selection of AMR, and are recommended for empiric treatment of most common infections [58,61,62]. Further, the tool contains the Watch group antibiotics that have a higher potential for the selection of AMR and are usually used in sicker hospitalized patients and need monitoring to avoid their overuse [59,61,63]. Furthermore, the tool contains the Reserve group antibiotics that are reserved for the treatment of severe infections caused by multidrug-resistant microbes [59,61,63]. The AWaRe framework recommends that 60% of the antibiotic prescriptions must emanate from the Access group [55,57,58,64]. The 2024 United Nations General Assembly (UNGA) revised this indicator and recommended that hospitals should be prescribing at least 70% of Access group antibiotics [65]. Therefore, the AWaRe classification is a useful tool for monitoring antibiotic consumption, defining targets, and monitoring the effects of stewardship policies that aim to optimize antibiotic use and curb AMR [57,60,66]. Prescribers also need to adhere to the Standard Treatment Guidelines (STGs) and Essential Medicines List (EML) to prevent adverse outcomes on patients and AMR [31,67].
The use of antibiotics in hospitals must be monitored frequently, especially in the sub-Saharan African region, with reports of high use of antibiotics of more than 50% [68,69]. Point prevalence surveys (PPS) have become useful in monitoring the use of antibiotics, adherence to treatment guidelines, and estimation of the prevalence of infections among in-patients [70,71,72]. The WHO and Global PPS methods have been used in many countries to monitor the use of antibiotics in hospitals and policy development to address the irrational use of antibiotics [73,74,75,76,77,78,79,80,81]. For instance, a PPS in Pakistan found that 77.6% of in-patients were treated with antibiotics, and most had gynecological, gastrointestinal, and lower respiratory tract infections [82]. Another study in Kenya found that 67.7% of in-patients were treated with antibiotics, mostly as medical prophylaxis after delivery [83]. These findings and others reported in similar studies show a high prevalence of antibiotic use [5,82,83,84,85], which needs to be addressed.
In Zambia, studies have reported a high prevalence of antibiotic use of up to 99.2% [7,86,87,88,89,90,91,92,93,94] and there is evidence of a high prevalence of AMR above 80% [95,96,97,98,99,100,101,102,103,104,105,106]. Further, a global PPS conducted in Uganda, Ghana, Zambia, and Tanzania found a 50% overall prevalence of antibiotic use [107], while another in Zambia found that 59% of in-patients were on antibiotics, the majority of which was ceftriaxone prescribed for empirical use [90]. However, no study has evaluated the impact of implementing AMS programs on antibiotic use in hospitals. This study therefore assessed the impact of multifaceted AMS interventions on antibiotic use and prescribing patterns in three tertiary hospitals in Zambia. The study also assessed the prevalence of antibiotic use as per the WHO AWaRe classification of antibiotics. This study was part of a 3-year AMS demonstration project led by the University Teaching Hospital (UTH) AMS team and funded by the International Center for Antimicrobial Resistance Solutions (ICARS).

2. Results

Table 1 displays the findings from two separate surveys conducted in 2022 and 2023. The median ages (i.e., 45 years for 2022 and 44 for 2023) of surveyed patients and the variation in ages (IQR for 2022: 31, 60; IQR for 2023: 29, 56) of the two samples were insignificant.
The overall combined sample and that disaggregated per survey year were almost uniformly distributed between males (54%) and females (46%), though males were slightly more (Table 1). Compared to the other two sites, LTH had a small sample in 2022. There was insufficient evidence of an association between gender and survey year (p > 0.05).
This study found an overall compliance with the national Standard Treatment Guidelines (STGs) at 44%. Table 2 shows that there was very strong evidence of an association (p-value < 0.001) between compliance status with national STGs and survey year, indicating better compliance in 2023 compared to 2022. Though the overall proportion of compliant prescriptions did not appear to change by much from 2022 (42%) to 2023 (45%), there was an obvious reduction in the proportion of prescriptions in which the compliance was not assessable, with 39% and 7.6% in 2022 and 2023, respectively. Of the three sites, LTH reported the greatest positive change in the compliant proportion from 0% to 88%, while NTH showed a reduction from 59% to 22%. Like LTH, UTH showed a positive change from 37% to 46% compliant prescriptions.
According to Table 2, though the overall data showed evidence of a strong relationship (p-value = 0.001) between patients categorized by number of prescribed antibiotics and the survey year, only NTH showed statistical significance (p-value = 0.001). However, all sites generally showed a reduction in the number and proportion of prescriptions with 3 or more antibiotics in 2023 compared to 2022. Overall, since 25% of patients were not on antibiotics, the prevalence of antibiotic use was 75% (Table 2).
Figure 1 illustrates the finding that ceftriaxone and metronidazole were the most prescribed antibiotics at LTH in both surveys. Together they accounted for about 71% in 2022 and 62% of all prescribed antibiotics. The reduction was primarily due to a change in the proportion accounted for by ceftriaxone from 42% to 39% (Figure 1).
In Figure 2, while ceftriaxone and metronidazole also accounted for the highest proportions at NTH, an increase in their combined and individual proportions was observed in 2023 compared to 2022.
Figure 3 illustrates that UTH also reported that ceftriaxone and metronidazole were the most prescribed antibiotics. However, whereas a direct relationship was noted between the proportions of the two antibiotics at the other two sites, the data from UTH exhibited an inverse relationship between the proportions of ceftriaxone and metronidazole. In this regard, there was a noticeable drop in the use of ceftriaxone, from 57% to 36%, while metronidazole increased from 20% to 34%. Overall, the average prescribing of ceftriaxone was 48% in 2022 and 38% in 2023, demonstrating a 10% reduction (Figure 3).

3. Discussion

To the best of our knowledge, this was the first PPS assessing the impact of AMS programs on antibiotic use and prescription patterns in Zambia. Overall, this study found a 75% (average of 1.27 number of antibiotics) prevalence of antibiotic use. Before the AMS intervention, 81% (average of 1.38 antibiotics) of the in-patients were on at least one antibiotic, with the majority being on ceftriaxone, indicating a high use of the Watch category of antibiotics. The prevalence of antibiotic use decreased to 71% (average of 1.21 number of antibiotics) during the AMS intervention, with most in-patients receiving ceftriaxone, followed by metronidazole, cefotaxime, and azithromycin. Overall, there were equal proportions of Access (50%) and Watch (50%) categories of antibiotics prescribed before the AMS intervention. On the other hand, following the implementation of AMS at the hospitals, 43% of the prescribed antibiotics were from the Access group while 57% were from the Watch group, indicating an increase in the use of Watch antibiotics. Additionally, compliance with the STG was 42% pre-intervention (2022) compared to 45% during the AMS intervention (2023). The results indicate an early positive impact of the AMS intervention, which would likely improve as the continued implementation of the AMS program leads to behavior change in the use of antibiotics and prescription patterns.
The pre- and post-intervention prevalence of antibiotic use in our study was higher than that found in an earlier study in Zambia [90]. The prevalence of antibiotic use found in our study was higher than the prevalence reported in 2017 in Nigeria (69.7%) [108], Botswana (70.6%) [109], and Sierra Leone (73.3%) [110], but similar to the 75% and 77.6% reported in Pakistan [82,111], 78% in Bangladesh [76], 78.9% in India [112], 80.6% in 2022 in Nigeria [113], and 82.9% in Benin [69]. The prevalence of antibiotic use reported in our study was higher than that reported in other studies, which ranged from 33.8% to 68% [77,80,85,107,114,115,116,117,118,119,120,121]. The high prescribing and use of antibiotics in hospitals require urgent attention and interventions to prevent the emergence and spread of AMR.
AMS interventions promote the rational use of antibiotics through improved awareness and knowledge of antibiotic use and AMR, reduction in antibiotic prescribing and use, and adherence to treatment guidelines [122,123,124,125], which results in a decline in antibiotic use. The decline in antibiotic use prevalence following the AMS intervention in our study demonstrates the impact AMS interventions can have on antibiotic use, which has been supported by studies elsewhere. For instance, the use of antibiotics was reduced due to the educational activities targeting healthcare workers in hospitals in Saudi Arabia, Ghana, and Uganda [126,127,128,129]. A recent study in Germany reported no decline in the use of antibiotics, although the total consumption reduced three years after the introduction of AMS programs in a University Teaching Hospital Emergency Department [130]. Another study in Ghana reported a decline in the use of antibiotics from 65% to 59.7% following the introduction of AMS programs in a District Hospital [127]. Further, similar to our findings, a study in the United Arab Emirates (UAE) reported a 6% decrease in the proportion of patients on antibiotics following the introduction of AMS interventions [131]. Therefore, strengthening a robust, coordinated, multifaceted, and sustained multidisciplinary AMS intervention has the potential to promote the rational use of antibiotics [131,132]. However, if not addressed, negative behaviors among prescribers may negatively impact the effects of AMS programs in healthcare facilities [130]. Hence, the promotion of behavior change towards rational prescribing and use of antibiotics is critical [133,134,135,136].
Ceftriaxone was the most prescribed and used antibiotic across the three tertiary hospitals pre-AMS and during the AMS intervention implementation. Other highly prescribed antibiotics included ciprofloxacin and metronidazole pre-intervention and metronidazole and azithromycin post-intervention. However, our study indicated a reduction in the use of ceftriaxone from 48% in the pre-AMS intervention to 38% in the post-AMS intervention, demonstrating a 10% decrease in the use of ceftriaxone. Similarly, the consumption of other antibiotics was reduced in the post-intervention compared to the pre-AMS intervention. The overuse of ceftriaxone in Zambian hospitals was similar to what has been reported in earlier studies [86,88,90,119,121,137,138]. Ceftriaxone is a Watch antibiotic with a low genetic barrier to resistance; therefore, if used irrationally, most pathogens would become resistant to it [139]. Additionally, being a third-generation cephalosporin, its overuse may lead to the emergence of extended-spectrum beta-lactamases (ESBLs) [140,141,142,143]. A study conducted in Malawi also revealed a 26.5% reduction in the use of ceftriaxone from 80.1% pre-AMS intervention to 53.6% post-AMS intervention [144]. Similarly, a study in Germany showed a reduction in the use of cephalosporins and fluoroquinolones after the implementation of AMS programs and an increase in the use of narrow-spectrum antibiotics [130]. An Italian study also reported a decrease in the use of ceftriaxone from 15.3% to 6% after the introduction of an effective AMS program [132]. A study in Jordan reported a reduction in the use of broad-spectrum antibiotics even though this was not sustained when the AMS program was halted, indicating the need for a sustained AMS program in the hospitals [145].
The present study found a modest increase (3%) in compliance with the national STGs from 42% in 2022 to 45% in 2023. The compliance level in our study is similar, though less than the compliance level (50.4%) in a study conducted in Malaysia [120]. Our findings are similar to those reported in a study in the UAE, which showed that instigation of AMS programs improved adherence to the treatment guidelines from 59% in 2019 to 67% in 2022 [131]. In the United States, a study reported that some low-cost interventions improved adherence to treatment guidelines in prescriptions for acute respiratory tract infections [146]. It is noteworthy that interventions to improve adherence to the treatment guidelines should be coupled with behavior change to promote the rational use of antibiotics [147]. Therefore, well-implemented AMR interventions lead to improved adherence to the treatment guidelines [45,148,149].
Our study revealed equal prescription of the Access and Watch categories pre-intervention (2022) and higher prescription of the Watch (57%) compared to the Access (43%) post-intervention (See Tables S1 and S2). In both assessments, there were no prescribed Reserve drugs. Our findings indicate an increase in the use of Watch antibiotics (mostly ceftriaxone), which is not in line with the WHO AWaRe framework recommendation that 60% of the prescribed antibiotics should be from the Access group [57,58,61]. This could be a result of a lack of information and implementation of the WHO AWaRe framework. Deviations in adherence to the WHO AWaRe classification of antibiotics have been reported in other studies [72,76,87,90,150]. The high use of Watch-group antibiotics was also reported in a PPS conducted in Japan, where 58.4% of the prescribed antibiotics were from the Watch group [151]. On the other hand, our findings are in line with a study performed in Ghana, Uganda, and Zambia in which Reserve antibiotics were not prescribed in the surveyed hospitals [107]. On the contrary, a study in Ghana reported that after the introduction of AMS programs in hospitals, the use of Access antibiotics increased from 40% to 50% while the Watch group reduced from 60% to 50%, indicating effective implementation of AMS programs [127]. Therefore, there is a need for continuous education and implementation of AMS programs in Zambia to improve and maintain the rational use of antibiotics.
We are aware of the limitations of our study. Our study was conducted in three tertiary hospitals in three out of the ten provinces in Zambia; hence, the generalization of our findings must be performed with caution. Secondly, the implementation period to detect the actual impact of AMS interventions on antibiotic use was too short. However, our findings show the early gains of introducing and implementing AMR programs in healthcare facilities.

4. Materials and Methods

4.1. Study Design, Setting, and Population

This was a before-and-after study of the effect of the AMS program on antibiotic use and prescribing patterns. The study was part of the 3-year AMS demonstration project funded by ICARS. The objective of the project is to optimize the use of antibiotics in the treatment of bloodstream infections (BSIs) and urinary tract infections (UTIs) in various health-sector settings in Zambia. We applied the WHO PPS methodology at baseline in August 2022, and a follow-on PPS followed by another one in October 2023 at the three tertiary hospitals, namely Ndola Teaching Hospital (NTH, Copperbelt Province, bed capacity of 851 and a medical ward capacity of 203), Livingstone Teaching Hospital (LTH, Southern Province, bed capacity of 242 and a medical ward capacity of 91), and University Teaching Hospitals (UTH, Lusaka Province, bed capacity of 830 and a medical ward capacity of 380). The survey sites are shown in Figure 4. The survey population included all adult in-patients admitted to the surgical and medical wards before 08:00 h on the day of the survey. All patients who were admitted to the ward by 08:00 h on the day of the survey were eligible. Antibiotics included antibacterials for oral and systemic use and intestinal anti-infective and antiprotozoal agents. Antibiotics used for HIV prophylaxis, such as co-trimoxazole, anti-tuberculous treatment (ATT), and antifungals, were excluded. Also, outpatients and daytime admissions for ambulatory patients for procedures such as endoscopy or renal dialysis and those patients on antibiotics for topical use were excluded from the survey.

4.2. Sample Size Estimation and Sampling Criteria

We selected the study sites using purposive sampling methods. This was because the three institutions were planning to strengthen AMS programs and develop deliberate interventions to improve the rational use of antibiotics. We selected all the medical and surgical patients that met the inclusion criteria. Since the targeted medical and surgical wards had bed capacities of less than 500, we included all the in-patients who met the inclusion criteria. Our sample size estimation is in line with the WHO PPS methodology recommendations, which state that for a bed capacity of less than 500, all patients that meet the inclusion criteria on the day of the PPS must be included in the study [70].

4.3. Data Collection

We used the WHO PPS tool to collect the data [70]. Data were collected through REDCap version 9.1.15, a web-based platform [152]. Access to this application was provided to all investigation teams, which included the pharmacists, laboratory scientists, nurses, and physicians, via email and uploaded onto hand-held devices.
Data were collected from patients’ medical files who were hospitalized before 08:00 h on the day of the surveys in the medical and surgical wards. Data were collected using two forms: a ward form used to record the denominators (number of beds and number of admitted patients before or at 08:00 h on the day of the PPS) and a patient form used to record detailed antimicrobial prescription (type, dose, administration route, indication, and diagnosis) for those patients who had received at least one antimicrobial before the day of the PPS. The entire data collection did not exceed three days in a single hospital or one day in each ward. Patients’ recorded data were anonymized.

4.4. Study Variables

The WHO PPS tool used standardized codes for differentiating wards in the hospitals [70]. Variables at the hospital level included the hospital name and the level of care. Further, ward-level variables included patient census data, patient name, code, and specialty of the wards. At the patient level, variables were divided into two sections, with the first section containing variables for all included in-patients and the second for only those patients on antimicrobial therapy during admission. The variables collected included demographic details such as age, gender, and admission for the same condition or a related complication arising from the previous admission [70].
Other variables included prescriber designations, reasons for prescription of antibiotics (treatment or prophylaxis), and if for prophylaxis, whether it was for medical or surgical prophylaxis. In addition, the duration of surgical prophylaxis is one dose, either one day or longer, admission diagnosis, and type of infection [70].
We collected data on antibiotics prescribed, whether prescribed on the drug sheet, whether by INN (International Nonproprietary Name) and whether it was from the Zambia STGs and Essential Medicines List (EML) [153,154], indication, start/stop date, dose, and frequency of administration.
The treatment of infections was classified into community-acquired infections (CAIs) and healthcare-associated infections (HAIs) as well as home-based care infections (HBCIs). Infections were considered CAIs if patients presented with infections or symptoms occurred <48 h from admission, HAIs if symptoms appeared >48 h after hospital admission based on chart review, and HBCIs if a terminally ill patient was transferred in from a long-term care facility due to an infection.
We categorized all the prescribed antibiotics according to the WHO AWaRe classification of antibiotics [55,56,57,61,64,155]. The results of the WHO AWaRe classification are shown in Tables S1 (for the year 2022) and Table S2 (for the year 2023).

4.5. Training and Supervision

Before the PPS, a two-day training was conducted at the University Teaching Hospital in Lusaka for the data collectors, comprising pharmacists, medical doctors, and an expert in health surveys from each of the three hospitals. The training was based on the PPS method, the study’s aims, the characteristics and contents of the questionnaires, and the procedures for data collection processes. Each team at the three hospitals was under the direct supervision of at least one principal investigator (pharmacist) during the PPS in the hospitals.
Data validation was performed by reviewing records to identify missing information and duplications. Records with incomplete information and duplicate entries were rectified after discussing with the duty physicians and nurses. Data were also evaluated for consistency and to ensure reliability using a pre-tested standardized questionnaire.

4.6. Antimicrobial Stewardship Interventions

Situational analyses and baseline PPS were conducted at the three facilities. Several gaps were identified, and interventions were put in place for a period of 15 months (from August 2022 to October 2023).
The major intervention was the setting up of AMS programs in facilities such as NTH and LTH where the program was non-existent. The AMS program was in place at UTH but was inactive and so needed strengthening. Other interventions that were put in place include the following:
  • Baseline assessment of knowledge, attitudes, and practices on AMS/AMR of healthcare workers at 3 institutions.
  • Baseline training and education in AMS for the AMS teams and the other healthcare workers (HCWs) at the facilities because inadequate knowledge of AMS was the biggest gap that was identified.
  • The AMS teams conducted quarterly continuous medical education on AMS for the HCWs.
  • Awareness and promotion of the use of STGs among the prescribers through hospital clinical meetings.
  • Introduction of antibiotic prescription charts with automatic stop orders.
  • Prospective multidisciplinary (physicians, pharmacists, nurses, and microbiologists) AMS ward rounds with real-time feedback to the prescribers once every week during the study time.

4.7. Data Analysis

The data collected through REDCap version 9.1.15 were exported to Microsoft (MS) Excel 2010. Preliminary cleaning, which included the renaming of variables of interest and ensuring consistency of data types for the concerned variables, was performed in MS Excel. The data were then imported into R version 4.4.0 for data wrangling using the dplyr package, descriptive data analysis and hypothesis testing using the gtsummary package, and data visualization using the ggplot2 package. Unless otherwise stated, a significance level of 5% was assumed.
All categorical variables were described using frequencies and percentages. This included estimations of both the proportion of prescriptions that complied with the national STG and the prescribing rates of respective antibiotics. Age being a skewed variable, it was summarized using the median and interquartile range (IQR). On the other hand, since the number of prescribed antibiotics followed a normal distribution, it was summarized using the mean and standard deviation (SD).
Assuming expected values for all cells in a cross-tabulation were greater or equal to five, the relationship between each categorical variable and the year in which the survey was conducted was tested using the chi-square test for independence. Where the aforementioned assumption was violated, Fisher’s exact test was used instead. The Wilcoxon rank sum test was used to test the relationship between each numerical variable and the year in which the survey was conducted.

5. Conclusions

This study revealed a high rate of antibiotic usage at three tertiary hospitals in Zambia, particularly preceding the Antimicrobial Stewardship (AMS) intervention. Notably, the AMS intervention yielded a significant reduction in antibiotic utilization (p-value < 0.001), specifically minimizing the prescription and administration of ceftriaxone. Furthermore, the intervention enhanced adherence to Zambia’s national Standard Treatment Guidelines (STG). However, sustaining these gains necessitates continuous implementation of AMS programs. Therefore, it is imperative to establish and maintain robust AMS initiatives across all hospitals in Zambia. This will be crucial in combating the growing threat of Antimicrobial Resistance (AMR), ultimately ensuring the long-term effectiveness of antibiotics and promoting public health.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/antibiotics14030284/s1, Table S1: Antibiotic Prescribing Patterns by AWaRe Classification in 2022; Table S2: Antibiotic Prescribing Patterns by AWaRe Classification in 2023.

Author Contributions

Conceptualization, D.C., K.K., S.F., S.M. and R.C.; methodology, S.M., U.C., K.K., M.C., R.C., R.K., S.F., M.K. and D.C; software, C.P., M.M. (Mukuka Mwamba), R.K.C., K.N. and D.C.; validation, U.C., R.C., R.N., K.Y., J.Y.C., M.M. (Mulope Mukanwa), K.H.M., M.K. and D.C.; formal analysis, S.M., M.M. (Mukuka Mwamba) and R.K.C.; investigation, S.M., U.C., K.K., M.C., R.K, L.M., R.N., K.Y., C.C., J.K., M.M. (Mulope Mukanwa), K.H.M., J.Y.C., T.M., C.S., M.K. and D.C.; resources, U.C., K.K., R.C., K.H.M., M.K. and D.C.; data curation, D.C.; writing—original draft preparation, S.M.; writing—review and editing, S.M., U.C., K.K, M.C., R.C., R.K., S.F., C.P., M.M. (Mukuka Mwamba), R.K.C., K.N, L.M., R.N., K.Y., J.Y.C., J.K., M.M (Mulope Mukanwa), K.H.M., P.M., F.M.A., J.J., J.M., M.K. and D.C.; visualization, K.K., C.P., M.M. (Mukuka Mwamba) and D.C.; supervision, D.C.; project administration, U.C., K.K., P.M., F.M.A., J.J., J.M., R.C. and D.C.; funding acquisition, D.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the International Centre for Antimicrobial Resistance Solutions (ICARS), Denmark, grant # 10010.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and was approved by the University of Zambia Biomedical Research Ethics Committee (UNZABREC), with an approval number of REF. NO. 3080-2022 (approval date: 2 September 2022).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper, if applicable.

Data Availability Statement

Data are available and can be shared on request from the corresponding author.

Acknowledgments

We are grateful to the management and leadership of the three tertiary hospitals for allowing us to conduct these surveys from their institutions.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Cook, M.A.; Wright, G.D. The Past, Present, and Future of Antibiotics. Sci. Transl. Med. 2022, 14, eabo7793. [Google Scholar] [CrossRef] [PubMed]
  2. Martens, E.; Demain, A.L. The Antibiotic Resistance Crisis, with a Focus on the United States. J. Antibiot. 2017, 70, 520–526. [Google Scholar] [CrossRef]
  3. Xu, S.; Song, Z.; Han, F.; Zhang, C. Effect of Appropriate Empirical Antimicrobial Therapy on Mortality of Patients with Gram-Negative Bloodstream Infections: A Retrospective Cohort Study. BMC Infect. Dis. 2023, 23, 344. [Google Scholar] [CrossRef] [PubMed]
  4. Martínez, M.L.; Plata-Menchaca, E.P.; Ruiz-Rodríguez, J.C.; Ferrer, R. An Approach to Antibiotic Treatment in Patients with Sepsis. J. Thorac. Dis. 2020, 12, 1007–1021. [Google Scholar] [CrossRef] [PubMed]
  5. Labi, A.K.; Obeng-Nkrumah, N.; Nartey, E.T.; Bjerrum, S.; Adu-Aryee, N.A.; Ofori-Adjei, Y.A.; Yawson, A.E.; Newman, M.J. Antibiotic Use in a Tertiary Healthcare Facility in Ghana: A Point Prevalence Survey. Antimicrob. Resist. Infect. Control 2018, 7, 15. [Google Scholar] [CrossRef]
  6. Zaman, S.B.; Hussain, M.A.; Nye, R.; Mehta, V.; Mamun, K.T.; Hossain, N. A Review on Antibiotic Resistance: Alarm Bells Are Ringing. Cureus 2017, 9, e1403. [Google Scholar] [CrossRef]
  7. Ngoma, M.T.; Sitali, D.; Mudenda, S.; Mukuma, M.; Bumbangi, F.N.; Bunuma, E.; Skjerve, E.; Muma, J.B. Community Antibiotic Consumption and Associated Factors in Lusaka District of Zambia: Findings and Implications for Antimicrobial Resistance and Stewardship. JAC-Antimicrob. Resist. 2024, 6, dlae034. [Google Scholar] [CrossRef] [PubMed]
  8. Masich, A.M.; Vega, A.D.; Callahan, P.; Herbert, A.; Fwoloshi, S.; Zulu, P.M.; Chanda, D.; Chola, U.; Mulenga, L.; Hachaambwa, L.; et al. Antimicrobial Usage at a Large Teaching Hospital in Lusaka, Zambia. PLoS ONE 2020, 15, e0228555. [Google Scholar] [CrossRef]
  9. Murray, C.J.; Ikuta, K.S.; Sharara, F.; Swetschinski, L.; Robles Aguilar, G.; Gray, A.; Han, C.; Bisignano, C.; Rao, P.; Wool, E.; et al. Global Burden of Bacterial Antimicrobial Resistance in 2019: A Systematic Analysis. Lancet 2022, 399, 629–655. [Google Scholar] [CrossRef]
  10. Prestinaci, F.; Pezzotti, P.; Pantosti, A. Antimicrobial Resistance: A Global Multifaceted Phenomenon. Pathog. Glob. Health 2015, 109, 309–318. [Google Scholar] [CrossRef]
  11. Hervin, V.; Roy, V.; Agrofoglio, L.A. Antibiotics and Antibiotic Resistance—Mur Ligases as an Antibacterial Target. Molecules 2023, 28, 8076. [Google Scholar] [CrossRef] [PubMed]
  12. Chinemerem Nwobodo, D.; Ugwu, M.C.; Oliseloke Anie, C.; Al-Ouqaili, M.T.S.; Chinedu Ikem, J.; Victor Chigozie, U.; Saki, M. Antibiotic Resistance: The Challenges and Some Emerging Strategies for Tackling a Global Menace. J. Clin. Lab. Anal. 2022, 36, e24655. [Google Scholar] [CrossRef] [PubMed]
  13. Dadgostar, P. Antimicrobial Resistance: Implications and Costs. Infect. Drug Resist. 2019, 12, 3903–3910. [Google Scholar] [CrossRef] [PubMed]
  14. Shrestha, P.; Cooper, B.S.; Coast, J.; Oppong, R.; Do Thi Thuy, N.; Phodha, T.; Celhay, O.; Guerin, P.J.; Wertheim, H.; Lubell, Y. Enumerating the Economic Cost of Antimicrobial Resistance per Antibiotic Consumed to Inform the Evaluation of Interventions Affecting Their Use. Antimicrob. Resist. Infect. Control 2018, 7, 98. [Google Scholar] [CrossRef]
  15. Ikuta, K.S.; Swetschinski, L.R.; Robles Aguilar, G.; Sharara, F.; Mestrovic, T.; Gray, A.P.; Davis Weaver, N.; Wool, E.E.; Han, C.; Gershberg Hayoon, A.; et al. Global Mortality Associated with 33 Bacterial Pathogens in 2019: A Systematic Analysis for the Global Burden of Disease Study 2019. Lancet 2022, 400, 2221–2248. [Google Scholar] [CrossRef]
  16. Sartorius, B.; Gray, A.P.; Davis Weaver, N.; Robles Aguilar, G.; Swetschinski, L.R.; Ikuta, K.S.; Mestrovic, T.; Chung, E.; Wool, E.E.; Han, C.; et al. The Burden of Bacterial Antimicrobial Resistance in the WHO African Region in 2019: A Cross-Country Systematic Analysis. Lancet Glob. Health 2024, 12, e201–e216. [Google Scholar] [CrossRef]
  17. de Kraker, M.E.A.; Stewardson, A.J.; Harbarth, S. Will 10 Million People Die a Year Due to Antimicrobial Resistance by 2050? PLoS Med. 2016, 13, e1002184. [Google Scholar] [CrossRef]
  18. O’Neill, J. Tackling Drug-Resistant Infections Globally: Final Report and Recommendations. The Review on Antimicrobial Resistance. 2016. Available online: https://amr-review.org/sites/default/files/160518_Final%20paper_with%20cover.pdf (accessed on 6 February 2025).
  19. Mudenda, S.; Chabalenge, B.; Daka, V.; Mfune, R.L.; Salachi, K.I.; Mohamed, S.; Mufwambi, W.; Kasanga, M.; Matafwali, S.K. Global Strategies to Combat Antimicrobial Resistance: A One Health Perspective. Pharmacol. Pharm. 2023, 14, 271–328. [Google Scholar] [CrossRef]
  20. Gulumbe, B.H.; Haruna, U.A.; Almazan, J.; Ibrahim, I.H.; Faggo, A.A.; Bazata, A.Y. Combating the Menace of Antimicrobial Resistance in Africa: A Review on Stewardship, Surveillance and Diagnostic Strategies. Biol. Proced. Online 2022, 24, 19. [Google Scholar] [CrossRef]
  21. Godman, B.; Egwuenu, A.; Haque, M.; Malande, O.O.; Schellack, N.; Kumar, S.; Saleem, Z.; Sneddon, J.; Hoxha, I.; Islam, S.; et al. Strategies to Improve Antimicrobial Utilization with a Special Focus on Developing Countries. Life 2021, 11, 528. [Google Scholar] [CrossRef]
  22. Godman, B.; Egwuenu, A.; Wesangula, E.; Schellack, N.; Kalungia, A.C.; Tiroyakgosi, C.; Kgatlwane, J.; Mwita, J.C.; Patrick, O.; Niba, L.L.; et al. Tackling Antimicrobial Resistance across Sub-Saharan Africa: Current Challenges and Implications for the Future. Expert Opin. Drug Saf. 2022, 21, 1089–1111. [Google Scholar] [CrossRef] [PubMed]
  23. Fuller, W.; Kapona, O.; Aboderin, A.O.; Adeyemo, A.T.; Olatunbosun, O.I.; Gahimbare, L.; Ahmed, Y.A. Education and Awareness on Antimicrobial Resistance in the WHO African Region: A Systematic Review. Antibiotics 2023, 12, 1613. [Google Scholar] [CrossRef]
  24. Ikhimiukor, O.O.; Odih, E.E.; Donado-Godoy, P.; Okeke, I.N. A Bottom-up View of Antimicrobial Resistance Transmission in Developing Countries. Nat. Microbiol. 2022, 7, 757–765. [Google Scholar] [CrossRef]
  25. Hecker, M.T.; Aron, D.C.; Patel, N.P.; Lehmann, M.K.; Donskey, C.J. Unnecessary Use of Antimicrobials in Hospitalized Patients: Current Patterns of Misuse with an Emphasis on the Antianaerobic Spectrum of Activity. Arch. Intern. Med. 2003, 163, 972–978. [Google Scholar] [CrossRef] [PubMed]
  26. Werner, N.L.; Hecker, M.T.; Sethi, A.K.; Donskey, C.J. Unnecessary Use of Fluoroquinolone Antibiotics in Hospitalized Patients. BMC Infect. Dis. 2011, 11, 187. [Google Scholar] [CrossRef]
  27. Alam, M.; Saleem, Z.; Haseeb, A.; Qamar, M.U.; Sheikh, A.; Almarzoky Abuhussain, S.S.; Iqbal, M.S.; Raees, F.; Chigome, A.; Cook, A.; et al. Tackling Antimicrobial Resistance in Primary Care Facilities across Pakistan: Current Challenges and Implications for the Future. J. Infect. Public Health 2023, 16, 97–110. [Google Scholar] [CrossRef]
  28. Bonna, A.S.; Pavel, S.R.; Ferdous, J.; Khan, S.A.; Ali, M. Antibiotic Resistance: An Increasingly Threatening but Neglected Public Health Challenge in Bangladesh. Int. J. Surg. Open 2022, 49, 100581. [Google Scholar] [CrossRef]
  29. Hagen, T.L.; Hertz, M.A.; Uhrin, G.B.; Dalager-Pedersen, M.; Schønheyder, H.C.; Nielsen, H. Adherence to Local Antimicrobial Guidelines for Initial Treatment of Community-Acquired Infections. Dan. Med. J. 2017, 64, A5381. [Google Scholar]
  30. Boltena, M.T.; Woldie, M.; Siraneh, Y.; Steck, V.; El-Khatib, Z.; Morankar, S. Adherence to Evidence-Based Implementation of Antimicrobial Treatment Guidelines among Prescribers in Sub-Saharan Africa: A Systematic Review and Meta-Analysis. J. Pharm. Policy Pract. 2023, 16, 137. [Google Scholar] [CrossRef]
  31. Dellit, T.H.; Owens, R.C.; McGowan, J.E.; Gerding, D.N.; Weinstein, R.A.; Burke, J.P.; Huskins, W.C.; Paterson, D.L.; Fishman, N.O.; Carpenter, C.F.; et al. Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America Guidelines for Developing an Institutional Program to Enhance Antimicrobial Stewardship. Clin. Infect. Dis. 2007, 44, 159–177. [Google Scholar] [CrossRef]
  32. Van Der Velden, L.B.J.; Tromp, M.; Bleeker-Rovers, C.P.; Hulscher, M.; Kullberg, B.J.; Mouton, J.W.; Sturm, P.D.J.; Pickkers, P. Non-Adherence to Antimicrobial Treatment Guidelines Results in More Broad-Spectrum but Not More Appropriate Therapy. Eur. J. Clin. Microbiol. Infect. Dis. 2012, 31, 1561–1568. [Google Scholar] [CrossRef] [PubMed]
  33. Matee, M.; Mshana, S.E.; Mtebe, M.; Komba, E.V.; Moremi, N.; Lutamwa, J.; Kapona, O.; Sekamatte, M.; Mboera, L.E.G. Mapping and Gap Analysis on Antimicrobial Resistance Surveillance Systems in Kenya, Tanzania, Uganda and Zambia. Bull. Natl. Res. Cent. 2023, 47, 12. [Google Scholar] [CrossRef]
  34. Iskandar, K.; Molinier, L.; Hallit, S.; Sartelli, M.; Hardcastle, T.C.; Haque, M.; Lugova, H.; Dhingra, S.; Sharma, P.; Islam, S.; et al. Surveillance of Antimicrobial Resistance in Low- and Middle-Income Countries: A Scattered Picture. Antimicrob. Resist. Infect. Control 2021, 10, 63. [Google Scholar] [CrossRef] [PubMed]
  35. Ayukekbong, J.A.; Ntemgwa, M.; Atabe, A.N. The Threat of Antimicrobial Resistance in Developing Countries: Causes and Control Strategies. Antimicrob. Resist. Infect. Control 2017, 6, 47. [Google Scholar] [CrossRef]
  36. Kariuki, S.; Kering, K.; Wairimu, C.; Onsare, R.; Mbae, C. Antimicrobial Resistance Rates and Surveillance in Sub-Saharan Africa: Where Are We Now? Infect. Drug Resist. 2022, 15, 3589–3609. [Google Scholar] [CrossRef] [PubMed]
  37. Yamba, K.; Chizimu, J.Y.; Mudenda, S.; Lukwesa, C.; Chanda, R.; Nakazwe, R.; Simunyola, B.; Shawa, M.; Kalungia, A.C.; Chanda, D.; et al. Assessment of Antimicrobial Resistance Laboratory-Based Surveillance Capacity of Hospitals in Zambia: Findings and Implications for System Strengthening. J. Hosp. Infect. 2024, 148, 129–137. [Google Scholar] [CrossRef]
  38. Shempela, D.M.; Mudenda, S.; Kasanga, M.; Daka, V.; Kangongwe, M.H.; Kamayani, M.; Sikalima, J.; Yankonde, B.; Kasonde, C.B.; Nakazwe, R.; et al. A Situation Analysis of the Capacity of Laboratories in Faith-Based Hospitals in Zambia to Conduct Surveillance of Antimicrobial Resistance: Opportunities to Improve Diagnostic Stewardship. Microorganisms 2024, 12, 1697. [Google Scholar] [CrossRef]
  39. Shamas, N.; Stokle, E.; Ashiru-Oredope, D.; Wesangula, E. Challenges of Implementing Antimicrobial Stewardship Tools in Low to Middle-Income Countries (LMICs). Infect. Prev. Pract. 2023, 5, 100315. [Google Scholar] [CrossRef]
  40. Kiggundu, R.; Lusaya, E.; Seni, J.; Waswa, J.P.; Kakooza, F.; Tjipura, D.; Kikule, K.; Muiva, C.; Joshi, M.P.; Stergachis, A.; et al. Identifying and Addressing Challenges to Antimicrobial Use Surveillance in the Human Health Sector in Low- and Middle-Income Countries: Experiences and Lessons Learned from Tanzania and Uganda. Antimicrob. Resist. Infect. Control 2023, 12, 9. [Google Scholar] [CrossRef]
  41. Tang, K.W.K.; Millar, B.C.; Moore, J.E. Antimicrobial Resistance (AMR). Br. J. Biomed. Sci. 2023, 80, 11387. [Google Scholar] [CrossRef]
  42. Lim, J.M.; Singh, S.R.; Duong, M.C.; Legido-Quigley, H.; Hsu, L.Y.; Tam, C.C. Impact of National Interventions to Promote Responsible Antibiotic Use: A Systematic Review. J. Antimicrob. Chemother. 2020, 75, 14–29. [Google Scholar] [CrossRef] [PubMed]
  43. Dyar, O.J.; Huttner, B.; Schouten, J.; Pulcini, C. What Is Antimicrobial Stewardship? Clin. Microbiol. Infect. 2017, 23, 793–798. [Google Scholar] [CrossRef]
  44. Nathwani, D.; Varghese, D.; Stephens, J.; Ansari, W.; Martin, S.; Charbonneau, C. Value of Hospital Antimicrobial Stewardship Programs [ASPs]: A Systematic Review. Antimicrob. Resist. Infect. Control 2019, 8, 35. [Google Scholar] [CrossRef] [PubMed]
  45. Metz, J.; Oehler, P.; Burggraf, M.; Burdach, S.; Behrends, U.; Rieber, N. Improvement of Guideline Adherence After the Implementation of an Antibiotic Stewardship Program in a Secondary Care Pediatric Hospital. Front. Pediatr. 2019, 7, 478. [Google Scholar] [CrossRef]
  46. Tahoon, M.A.; Khalil, M.M.; Hammad, E.; Morad, W.S.; Awad, S.M.; Ezzat, S. The Effect of Educational Intervention on Healthcare Providers’ Knowledge, Attitude, & Practice towards Antimicrobial Stewardship Program at, National Liver Institute, Egypt. Egypt. Liver J. 2020, 10, 5. [Google Scholar] [CrossRef]
  47. Rogers Van Katwyk, S.; Jones, S.L.; Hoffman, S.J. Mapping Educational Opportunities for Healthcare Workers on Antimicrobial Resistance and Stewardship around the World. Hum. Resour. Health 2018, 16, 9. [Google Scholar] [CrossRef]
  48. Sartelli, M.; Barie, P.S.; Coccolini, F.; Abbas, M.; Abbo, L.M.; Abdukhalilova, G.K.; Abraham, Y.; Abubakar, S.; Abu-Zidan, F.M.; Adebisi, Y.A.; et al. Ten Golden Rules for Optimal Antibiotic Use in Hospital Settings: The WARNING Call to Action. World J. Emerg. Surg. 2023, 18, 50. [Google Scholar] [CrossRef]
  49. Mudenda, S.; Chabalenge, B.; Daka, V.; Jere, E.; Sefah, I.A.; Wesangula, E.; Yamba, K.; Nyamupachitu, J.; Mugenyi, N.; Mustafa, Z.U.; et al. Knowledge, Awareness and Practices of Healthcare Workers Regarding Antimicrobial Use, Resistance and Stewardship in Zambia: A Multi-Facility Cross-Sectional Study. JAC-Antimicrob. Resist. 2024, 6, dlae076. [Google Scholar] [CrossRef]
  50. Mendelson, M.; Matsoso, M.P. The World Health Organization Global Action Plan for Antimicrobial Resistance. S. Afr. Med. J. 2015, 105, 325. [Google Scholar] [CrossRef]
  51. World Health Organization. Global Action Plan on Antimicrobial Resistance; World Health Organization: Geneva, Switzerland, 2015; Available online: https://apps.who.int/iris/handle/10665/193736 (accessed on 6 January 2023).
  52. World Health Organization. Global Antimicrobial Resistance Surveillance System. Manual for Early Implementation; World Health Organization: Geneva, Switzerland, 2015; Available online: https://www.who.int/publications/i/item/9789241549400 (accessed on 6 January 2025).
  53. Nabadda, S.; Kakooza, F.; Kiggundu, R.; Walwema, R.; Bazira, J.; Mayito, J.; Mugerwa, I.; Sekamatte, M.; Kambugu, A.; Lamorde, M.; et al. Implementation of the World Health Organization Global Antimicrobial Resistance Surveillance System in Uganda, 2015–2020: Mixed-Methods Study Using National Surveillance Data. JMIR Public Health Surveill. 2021, 7, e29954. [Google Scholar] [CrossRef]
  54. World Health Organization. Library of National Action Plans. Available online: https://www.who.int/teams/surveillance-prevention-control-AMR/national-action-plan-monitoring-evaluation/library-of-national-action-plans (accessed on 26 May 2024).
  55. Sharland, M.; Zanichelli, V.; Ombajo, L.A.; Bazira, J.; Cappello, B.; Chitatanga, R.; Chuki, P.; Gandra, S.; Getahun, H.; Harbarth, S.; et al. The WHO Essential Medicines List AWaRe Book: From a List to a Quality Improvement System. Clin. Microbiol. Infect. 2022, 28, 1533–1535. [Google Scholar] [CrossRef]
  56. World Health Organization. 2021 AWaRe Classification; World Health Organization: Geneva, Switzerland, 2023; Available online: https://www.who.int/publications/i/item/2021-aware-classification (accessed on 6 January 2025).
  57. World Health Organization. AWaRe Classification of Antibiotics for Evaluation and Monitoring of Use, 2023; World Health Organization: Geneva, Switzerland, 2023; Available online: https://www.who.int/publications/i/item/WHO-MHP-HPS-EML-2023.04 (accessed on 6 January 2025).
  58. Mudenda, S.; Daka, V.; Matafwali, S.K. World Health Organization AWaRe Framework for Antibiotic Stewardship: Where Are We Now and Where Do We Need to Go? An Expert Viewpoint. Antimicrob. Steward. Healthc. Epidemiol. 2023, 3, e84. [Google Scholar] [CrossRef] [PubMed]
  59. Hsia, Y.; Lee, B.R.; Versporten, A.; Yang, Y.; Bielicki, J.; Jackson, C.; Newland, J.; Goossens, H.; Magrini, N.; Sharland, M. Use of the WHO Access, Watch, and Reserve Classification to Define Patterns of Hospital Antibiotic Use (AWaRe): An Analysis of Paediatric Survey Data from 56 Countries. Lancet Glob. Health 2019, 7, e861–e871. [Google Scholar] [CrossRef] [PubMed]
  60. Mudenda, S.; Wataya, M.D.; Mufwambi, W.; Chizimu, J.Y. The World Health Organization Access, Watch, and Reserve Classification of Antibiotics: An Awareness Survey among Pharmacy Professionals in a Sub-Saharan Country, Zambia. Antimicrob. Steward. Healthc. Epidemiol. 2024, 4, e212. [Google Scholar] [CrossRef]
  61. Zanichelli, V.; Sharland, M.; Cappello, B.; Moja, L.; Getahun, H.; Pessoa-Silva, C.; Sati, H.; van Weezenbeek, C.; Balkhy, H.; Simão, M.; et al. The WHO AWaRe (Access, Watch, Reserve) Antibiotic Book and Prevention of Antimicrobial Resistance. Bull. World Health Organ. 2023, 101, 290–296. [Google Scholar] [CrossRef]
  62. Abdelsalam Elshenawy, R.; Umaru, N.; Aslanpour, Z. WHO AWaRe Classification for Antibiotic Stewardship: Tackling Antimicrobial Resistance—A Descriptive Study from an English NHS Foundation Trust Prior to and during the COVID-19 Pandemic. Front. Microbiol. 2023, 14, 1298858. [Google Scholar] [CrossRef] [PubMed]
  63. Bou-Antoun, S.; Oettle, R.C.; Leanord, A.; Seaton, R.A.; Cooper, B.S.; Muller-Pebody, B.; Conlon-Bingham, G.; Kerr, F.; Hand, K.S.; Sandoe, J.A.T.; et al. Adaptation of the WHO AWaRe (Access, Watch, Reserve) Antibiotic Classification to Support National Antimicrobial Stewardship Priorities in the UK: Findings from a Modified Delphi Approach to Achieve Expert Consensus. JAC-Antimicrob. Resist. 2025, 7, dlae218. [Google Scholar] [CrossRef]
  64. Budd, E.; Cramp, E.; Sharland, M.; Hand, K.; Howard, P.; Wilson, P.; Wilcox, M.; Muller-Pebody, B.; Hopkins, S. Adaptation of the WHO Essential Medicines List for National Antibiotic Stewardship Policy in England: Being AWaRe. J. Antimicrob. Chemother. 2019, 74, 3384–3389. [Google Scholar] [CrossRef]
  65. United Nations Environment Programme. World Leaders Commit to Decisive Action on Antimicrobial Resistance. 2024. Available online: https://www.who.int/news/item/26-09-2024-world-leaders-commit-to-decisive-action-on-antimicrobial-resistance (accessed on 6 January 2025).
  66. Nsojo, A.; George, L.; Mwasomola, D.; Tawete, J.; Mbotwa, C.H.; Mweya, C.N.; Mwakyula, I. Prescribing Patterns of Antimicrobials According to the WHO AWaRe Classification at a Tertiary Referral Hospital in the Southern Highlands of Tanzania. Infect. Prev. Pract. 2024, 6, 100347. [Google Scholar] [CrossRef]
  67. Chigome, A.; Ramdas, N.; Skosana, P.; Cook, A.; Schellack, N.; Campbell, S.; Lorenzetti, G.; Saleem, Z.; Godman, B.; Meyer, J.C. A Narrative Review of Antibiotic Prescribing Practices in Primary Care Settings in South Africa and Potential Ways Forward to Reduce Antimicrobial Resistance. Antibiotics 2023, 12, 1540. [Google Scholar] [CrossRef]
  68. Siachalinga, L.; Godman, B.; Mwita, J.C.; Sefah, I.A.; Ogunleye, O.O.; Massele, A.; Lee, I.H. Current Antibiotic Use Among Hospitals in the Sub-Saharan Africa Region; Findings and Implications. Infect. Drug Resist. 2023, 16, 2179–2190. [Google Scholar] [CrossRef]
  69. Gnimavo, M.S.; Boya, B.; Mudenda, S.; Allabi, A.C. Antibiotic Use at the Centre Hospitalier Universitaire de Zone d’Abomey Calavi/Sô-Ava (CHUZ/AS) in Benin: A Point Prevalence Survey. JAC-Antimicrob. Resist. 2024, 7, dlae220. [Google Scholar] [CrossRef] [PubMed]
  70. World Health Organization. WHO Methodology for Point Prevalence Survey on Antibiotic Use in Hospitals; World Health Organization: Geneva, Switzerland, 2018; Available online: https://apps.who.int/iris/bitstream/handle/10665/280063/WHO-EMP-IAU-2018.01-eng.pdf?ua=1 (accessed on 6 January 2025).
  71. Versporten, A.; Pauwels, I.; Drapier, N.; Goossens, H.; Zarb, P. Global Point Prevalence Survey of Antimicrobial Consumption and Resistance (2022 GLOBAL-PPS); PROTOCOL—Version February 2022. Available online: https://www.global-pps.com/wp-content/uploads/2022/02/Protocol-Global-PPS-with-optional-HAI-module_Feb2022.pdf (accessed on 6 January 2025).
  72. Pauwels, I.; Versporten, A.; Drapier, N.; Vlieghe, E.; Goossens, H. Hospital Antibiotic Prescribing Patterns in Adult Patients According to the WHO Access, Watch and Reserve Classification (AWaRe): Results from a Worldwide Point Prevalence Survey in 69 Countries. J. Antimicrob. Chemother. 2021, 76, 1614–1624. [Google Scholar] [CrossRef]
  73. Seni, J.; Mapunjo, S.G.; Wittenauer, R.; Valimba, R.; Stergachis, A.; Werth, B.J.; Saitoti, S.; Mhadu, N.H.; Lusaya, E.; Konduri, N. Antimicrobial Use across Six Referral Hospitals in Tanzania: A Point Prevalence Survey. BMJ Open 2020, 10, e042819. [Google Scholar] [CrossRef]
  74. Gwebu, P.C.; Meyer, J.C.; Schellack, N.; Matsebula-Myeni, Z.C.; Godman, B. A Web-Based Point Prevalence Survey of Antimicrobial Use and Quality Indicators at Raleigh Fitkin Memorial Hospital in the Kingdom of Eswatini and the Implications. Hosp. Pract. 2022, 50, 214–221. [Google Scholar] [CrossRef] [PubMed]
  75. Afriyie, D.K.; Sefah, I.A.; Sneddon, J.; Malcolm, W.; McKinney, R.; Cooper, L.; Kurdi, A.; Godman, B.; Andrew Seaton, R. Antimicrobial Point Prevalence Surveys in Two Ghanaian Hospitals: Opportunities for Antimicrobial Stewardship. JAC-Antimicrob. Resist. 2020, 2, dlaa001. [Google Scholar] [CrossRef] [PubMed]
  76. Rashid, M.M.; Akhtar, Z.; Chowdhury, S.; Islam, M.A.; Parveen, S.; Ghosh, P.K.; Rahman, A.; Khan, Z.H.; Islam, K.; Debnath, N.; et al. Pattern of Antibiotic Use among Hospitalized Patients According to WHO Access, Watch, Reserve (AWaRe) Classification: Findings from a Point Prevalence Survey in Bangladesh. Antibiotics 2022, 11, 810. [Google Scholar] [CrossRef]
  77. Versporten, A.; Zarb, P.; Caniaux, I.; Gros, M.F.; Drapier, N.; Miller, M.; Jarlier, V.; Nathwani, D.; Goossens, H.; Koraqi, A.; et al. Antimicrobial Consumption and Resistance in Adult Hospital Inpatients in 53 Countries: Results of an Internet-Based Global Point Prevalence Survey. Lancet Glob. Health 2018, 6, e619–e629. [Google Scholar] [CrossRef]
  78. Limato, R.; Nelwan, E.J.; Mudia, M.; De Brabander, J.; Guterres, H.; Enty, E.; Mauleti, I.Y.; Mayasari, M.; Firmansyah, I.; Hizrani, M.; et al. A Multicentre Point Prevalence Survey of Patterns and Quality of Antibiotic Prescribing in Indonesian Hospitals. JAC-Antimicrob. Resist. 2021, 3, dlab047. [Google Scholar] [CrossRef]
  79. Kurdi, A.; Hasan, A.J.; Baker, K.I.; Seaton, R.A.; Ramzi, Z.S.; Sneddon, J.; Godman, B. A Multicentre Point Prevalence Survey of Hospital Antibiotic Prescribing and Quality Indices in the Kurdistan Regional Government of Northern Iraq: The Need for Urgent Action. Expert Rev. Anti-Infect. Ther. 2021, 19, 805–814. [Google Scholar] [CrossRef]
  80. Anugulruengkitt, S.; Charoenpong, L.; Kulthanmanusorn, A.; Thienthong, V.; Usayaporn, S.; Kaewkhankhaeng, W.; Rueangna, O.; Sophonphan, J.; Moolasart, V.; Manosuthi, W.; et al. Point Prevalence Survey of Antibiotic Use among Hospitalized Patients across 41 Hospitals in Thailand. JAC-Antimicrob. Resist. 2023, 5, dlac140. [Google Scholar] [CrossRef]
  81. Gandra, S.; Singh, S.K.; Jinka, D.R.; Kanithi, R.; Chikkappa, A.K.; Sharma, A.; Dharmapalan, D.; Vasudevan, A.K.; Tunga, O.; Akula, A.; et al. Point Prevalence Surveys of Antimicrobial Use among Hospitalized Children in Six Hospitals in India in 2016. Antibiotics 2017, 6, 19. [Google Scholar] [CrossRef]
  82. Saleem, Z.; Hassali, M.A.; Versporten, A.; Godman, B.; Hashmi, F.K.; Goossens, H.; Saleem, F. A Multicenter Point Prevalence Survey of Antibiotic Use in Punjab, Pakistan: Findings and Implications. Expert Rev. Anti-Infect. Ther. 2019, 17, 285–293. [Google Scholar] [CrossRef]
  83. Okoth, C.; Opanga, S.; Okalebo, F.; Oluka, M.; Baker Kurdi, A.; Godman, B. Point Prevalence Survey of Antibiotic Use and Resistance at a Referral Hospital in Kenya: Findings and Implications. Hosp. Pract. 2018, 46, 128–136. [Google Scholar] [CrossRef]
  84. Hsieh, J.; Sati, H.; Ramon-Pardo, P.; Bruinsma, N.; Galas, M.F.; Marie Rwangabwoba, J.; Zoila Irene. Fletcher Payton, 2nd Degree in Epidemiologist; Bonet, M.; Forde, C.A.; Alladin-Karan, B.A.; et al. 2034. Standardized Point Prevalence Survey on Antibiotic Use to Inform Antimicrobial Stewardship Strategies in the Caribbean. Open Forum Infect. Dis. 2019, 6, S683–S684. [Google Scholar] [CrossRef]
  85. Al Matar, M.; Enani, M.; Binsaleh, G.; Roushdy, H.; Alokaili, D.; Al Bannai, A.; Khidir, Y.; Al-Abdely, H. Point Prevalence Survey of Antibiotic Use in 26 Saudi Hospitals in 2016. J. Infect. Public Health 2019, 12, 77–82. [Google Scholar] [CrossRef]
  86. Mudenda, S.; Chilimboyi, R.; Matafwali, S.K.; Daka, V.; Lindizyani Mfune, R.; Arielle, L.; Kemgne, M.; Bumbangi, F.N.; Hangoma, J.; Chabalenge, B.; et al. Hospital Prescribing Patterns of Antibiotics in Zambia Using the WHO Prescribing Indicators Post-COVID-19 Pandemic: Findings and Implications. JAC-Antimicrob. Resist. 2024, 6, dlae023. [Google Scholar] [CrossRef]
  87. Mudenda, S.; Nsofu, E.; Chisha, P.; Daka, V.; Chabalenge, B.; Mufwambi, W.; Kainga, H.; Kanaan, M.H.G.; Mfune, R.L.; Mwaba, F.; et al. Prescribing Patterns of Antibiotics According to the WHO AWaRe Classification during the COVID-19 Pandemic at a Teaching Hospital in Lusaka, Zambia: Implications for Strengthening of Antimicrobial Stewardship Programmes. Pharmacoepidemiology 2023, 2, 42–53. [Google Scholar] [CrossRef]
  88. Mudenda, S.; Chomba, M.; Chabalenge, B.; Hikaambo, C.N.; Banda, M.; Daka, V.; Zulu, A.; Mukesela, A.; Kasonde, M.; Lukonde, P.; et al. Antibiotic Prescribing Patterns in Adult Patients According to the WHO AWaRe Classification: A Multi-Facility Cross-Sectional Study in Primary Healthcare Hospitals in Lusaka, Zambia. Pharmacol. Pharm. 2022, 13, 379–392. [Google Scholar] [CrossRef]
  89. Mudenda, W.; Chikatula, E.; Chambula, E.; Mwanashimbala, B.; Chikuta, M.; Masaninga, F.; Songolo, P.; Vwalika, B.; Kachimba, J.S.; Mufunda, J.; et al. Prescribing Patterns and Medicine Use at the University Teaching Hospital, Lusaka, Zambia. Med. J. Zamb. 2016, 43, 94–102. [Google Scholar] [CrossRef]
  90. Kalungia, A.C.; Mukosha, M.; Mwila, C.; Banda, D.; Mwale, M.; Kagulura, S.; Ogunleye, O.O.; Meyer, J.C.; Godman, B. Antibiotic Use and Stewardship Indicators in the First- and Second-Level Hospitals in Zambia: Findings and Implications for the Future. Antibiotics 2022, 11, 1626. [Google Scholar] [CrossRef]
  91. Yamba, K.; Mudenda, S.; Mpabalwani, E.; Mainda, G.; Mukuma, M.; Samutela, M.T.; Lukwesa, C.; Chizimu, J.; Kaluba, C.K.; Mutalange, M.; et al. Antibiotic Prescribing Patterns and Carriage of Antibiotic-Resistant Escherichia Coli and Enterococcus Species in Healthy Individuals from Selected Communities in Lusaka and Ndola Districts, Zambia. JAC-Antimicrob. Resist. 2024, 6, dlae027. [Google Scholar] [CrossRef]
  92. Kalonga, J.; Hangoma, J.; Banda, M.; Munkombwe, D.; Mudenda, S. Antibiotic Prescribing Patterns in Paediatric Patients at Levy Mwanawasa University Teaching Hospital in Lusaka, Zambia. Int. J. Pharm. Pharmacol. 2020, 4, 138. [Google Scholar] [CrossRef]
  93. Chizimu, J.Y.; Mudenda, S.; Yamba, K.; Lukwesa, C.; Chanda, R.; Nakazwe, R.; Shawa, M.; Chambaro, H.; Kamboyi, H.K.; Kalungia, A.C.; et al. Antibiotic Use and Adherence to the WHO AWaRe Guidelines across 16 Hospitals in Zambia: A Point Prevalence Survey. JAC-Antimicrob. Resist. 2024, 6, dlae170. [Google Scholar] [CrossRef] [PubMed]
  94. Mudenda, S.; Simbaya, R.; Moonga, G.; Mwaba, F.; Zulu, M.; Tembo, R.; Chiyangi, H.K.; Vlahakis, P.; Mohamed, S.; Lubanga, A.F.; et al. Surveillance of Antibiotic Use and Adherence to the WHO/INRUD Core Prescribing Indicators at a Primary Healthcare Hospital in Southern Zambia: Opportunities for Antimicrobial Stewardship Programs. Pharmacol. Pharm. 2025, 16, 1–19. [Google Scholar] [CrossRef]
  95. Shawa, M.; Paudel, A.; Chambaro, H.; Kamboyi, H.; Nakazwe, R.; Alutuli, L.; Zorigt, T.; Sinyawa, T.; Samutela, M.; Chizimu, J.; et al. Trends, Patterns and Relationship of Antimicrobial Use and Resistance in Bacterial Isolates Tested between 2015–2020 in a National Referral Hospital of Zambia. PLoS ONE 2024, 19, e0302053. [Google Scholar] [CrossRef]
  96. Fwoloshi, S.; Chola, U.; Nakazwe, R.; Tatila, T.; Mateele, T.; Kabaso, M.; Muzyamba, T.; Mutwale, I.; Jones, A.S.C.; Islam, J.; et al. Why Local Antibiotic Resistance Data Matters—Informing Empiric Prescribing through Local Data Collation, App Design and Engagement in Zambia. J. Infect. Public Health 2023, 16, 69–77. [Google Scholar] [CrossRef]
  97. Mudenda, S.; Mufwambi, W.; Mohamed, S. The Burden of Antimicrobial Resistance in Zambia, a Sub-Saharan African Country: A One Health Review of the Current Situation, Risk Factors, and Solutions. Pharmacol. Pharm. 2024, 15, 403–465. [Google Scholar] [CrossRef]
  98. ASLM. MAAP Report Zambia 2016–2018; ASLM: Veldhoven, The Netherlands, 2022; Available online: https://africacdc.org/download/mapping-antimicrobial-resistance-and-antimicrobial-use-partnership-maap-country-reports/ (accessed on 6 February 2025).
  99. Yamba, K.; Lukwesa-Musyani, C.; Samutela, M.T.; Kapesa, C.; Hang’ombe, M.B.; Mpabalwani, E.; Hachaambwa, L.; Fwoloshi, S.; Chanda, R.; Mpundu, M.; et al. Phenotypic and Genotypic Antibiotic Susceptibility Profiles of Gram-Negative Bacteria Isolated from Bloodstream Infections at a Referral Hospital, Lusaka, Zambia. PLoS Glob. Public Health 2023, 3, e0001414. [Google Scholar] [CrossRef]
  100. Chizimu, J.Y.; Solo, E.S.; Bwalya, P.; Kapalamula, T.F.; Mwale, K.K.; Squarre, D.; Shawa, M.; Lungu, P.; Barnes, D.A.; Yamba, K.; et al. Genomic Analysis of Mycobacterium Tuberculosis Strains Resistant to Second-Line Anti-Tuberculosis Drugs in Lusaka, Zambia. Antibiotics 2023, 12, 1126. [Google Scholar] [CrossRef]
  101. Samutela, M.T.; Kalonda, A.; Mwansa, J.; Lukwesa-Musyani, C.; Mwaba, J.; Mumbula, E.M.; Mwenya, D.; Simulundu, E.; Kwenda, G. Molecular Characterisation of Methicillin-Resistant Staphylococcus Aureus (MRSA) Isolated at a Large Referral Hospital in Zambia. Pan Afr. Med. J. 2017, 26, 108. [Google Scholar] [CrossRef]
  102. Mwansa, T.N.; Kamvuma, K.; Mulemena, J.A.; Phiri, C.N.; Chanda, W. Antibiotic Susceptibility Patterns of Pathogens Isolated from Laboratory Specimens at Livingstone Central Hospital in Zambia. PLoS Glob. Public Health 2022, 2, e0000623. [Google Scholar] [CrossRef]
  103. Chiyangi, H.; Muma, B.; Malama, S.; Manyahi, J.; Abade, A.; Kwenda, G.; Matee, M. Identification and Antimicrobial Resistance Patterns of Bacterial Enteropathogens from Children Aged 0–59 Months at the University Teaching Hospital, Lusaka, Zambia: A Prospective Cross-Sectional Study. BMC Infect. Dis. 2017, 17, 117. [Google Scholar] [CrossRef]
  104. Bumbangi, F.N.; Llarena, A.-K.; Skjerve, E.; Hang’ombe, B.M.; Mpundu, P.; Mudenda, S.; Mutombo, P.B.; Muma, J.B. Evidence of Community-Wide Spread of Multi-Drug Resistant Escherichia Coli in Young Children in Lusaka and Ndola Districts, Zambia. Microorganisms 2022, 10, 1684. [Google Scholar] [CrossRef]
  105. Mudenda, S.; Malama, S.; Munyeme, M.; Matafwali, S.K.; Kapila, P.; Katemangwe, P.; Mainda, G.; Mukubesa, A.N.; Hadunka, M.A.; Muma, J.B. Antimicrobial Resistance Profiles of Escherichia Coli Isolated from Laying Hens in Zambia: Implications and Significance on One Health. JAC-Antimicrob. Resist. 2023, 5, dlad060. [Google Scholar] [CrossRef]
  106. Kasanga, M.; Mukosha, R.; Kasanga, M.; Siyanga, M.; Mudenda, S.; Solochi, B.B.; Chileshe, M.; Mwiikisa, M.J.; Gondwe, T.; Kantenga, T.; et al. Antimicrobial Resistance Patterns of Bacterial Pathogens Their Distribution in University Teaching Hospitals in Zambia. Future Microbiol. 2020, 16, 811–824. [Google Scholar] [CrossRef]
  107. D’Arcy, N.; Ashiru-Oredope, D.; Olaoye, O.; Afriyie, D.; Akello, Z.; Ankrah, D.; Asima, D.; Banda, D.C.; Barrett, S.; Brandish, C.; et al. Antibiotic Prescribing Patterns in Ghana, Uganda, Zambia and Tanzania Hospitals: Results from the Global Point Prevalence Survey (G-PPS) on Antimicrobial Use and Stewardship Interventions Implemented. Antibiotics 2021, 10, 1122. [Google Scholar] [CrossRef]
  108. Oduyebo, O.; Olayinka, A.; Iregbu, K.; Versporten, A.; Goossens, H.; Nwajiobi-Princewill, P.; Jimoh, O.; Ige, T.; Aigbe, A.; Ola-Bello, O.; et al. A Point Prevalence Survey of Antimicrobial Prescribing in Four Nigerian Tertiary Hospitals. Ann. Trop. Pathol. 2017, 8, 42–46. [Google Scholar] [CrossRef]
  109. Anand Paramadhas, B.D.; Tiroyakgosi, C.; Mpinda-Joseph, P.; Morokotso, M.; Matome, M.; Sinkala, F.; Gaolebe, M.; Malone, B.; Molosiwa, E.; Shanmugam, M.G.; et al. Point Prevalence Study of Antimicrobial Use among Hospitals across Botswana; Findings and Implications. Expert Rev. Anti-Infect. Ther. 2019, 17, 535–546. [Google Scholar] [CrossRef]
  110. Kamara, I.F.; Kanu, J.; Maruta, A.; Fofanah, B.D.; Kamara, K.N.; Sheriff, B.; Katawera, V.; D’Almeida, S.A.; Musoke, R.; Nuwagira, I.; et al. Antibiotic Use among Hospitalised Patients in Sierra Leone: A National Point Prevalence Survey Using the WHO Survey Methodology. BMJ Open 2023, 13, e078367. [Google Scholar] [CrossRef] [PubMed]
  111. Ambreen, S.; Safdar, N.; Ikram, A.; Baig, M.Z.I.; Farooq, A.; Amir, A.; Saeed, A.; Sabih, F.; Ahsan, Q.; Zafar, A.; et al. Point Prevalence Survey of Antimicrobial Use in Selected Tertiary Care Hospitals of Pakistan Using WHO Methodology: Results and Inferences. Medicina 2023, 59, 1102. [Google Scholar] [CrossRef]
  112. Kumar, S.; Shukla, P.; Goel, P.; Mishra, V.; Gupta, A.; Karuna, T.; Srivastava, R.; Gupta, A.; Baharani, D.; Pansey, P.; et al. Point Prevalence Study (PPS) of Antibiotic Usage and Bacterial Culture Rate (BCR) among Secondary Care Hospitals of Small Cities in Central India: Consolidating Indian Evidence. J. Lab. Physicians 2023, 15, 259–263. [Google Scholar] [CrossRef]
  113. Ogunleye, O.O.; Oyawole, M.R.; Odunuga, P.T.; Kalejaye, F.; Yinka-Ogunleye, A.F.; Olalekan, A.; Ogundele, S.O.; Ebruke, B.E.; Kalada Richard, A.; Anand Paramadhas, B.D.; et al. A Multicentre Point Prevalence Study of Antibiotics Utilization in Hospitalized Patients in an Urban Secondary and a Tertiary Healthcare Facilities in Nigeria: Findings and Implications. Expert Rev. Anti-Infect. Ther. 2022, 20, 297–306. [Google Scholar] [CrossRef]
  114. Leung, V.; Li, M.; Wu, J.H.C.; Langford, B.; Zvonar, R.; Powis, J.; Longpre, J.; Béïque, L.; Gill, S.; Ho, G.; et al. Evaluating Antimicrobial Use and Spectrum of Activity in Ontario Hospitals: Feasibility of a Multicentered Point Prevalence Study. Open Forum Infect. Dis. 2018, 5, ofy110. [Google Scholar] [CrossRef]
  115. Akhloufi, H.; Streefkerk, R.H.; Melles, D.C.; de Steenwinkel, J.E.M.; Schurink, C.A.M.; Verkooijen, R.P.; van der Hoeven, C.P.; Verbon, A. Point Prevalence of Appropriate Antimicrobial Therapy in a Dutch University Hospital. Eur. J. Clin. Microbiol. Infect. Dis. 2015, 34, 1631–1637. [Google Scholar] [CrossRef]
  116. Wambale, J.M.; Iyamba, J.L.; Mathe, D.M.; Kavuo, S.K.; Kikuni, T. Point Prevalence Study of Antibiotic Use in Hospitals in Butembo. Int. J. Med. Med. Sci. 2016, 8, 133–139. [Google Scholar] [CrossRef]
  117. Xie, D.S.; Xiang, L.L.; Li, R.; Hu, Q.; Luo, Q.; Xiong, W. A Multicenter Point-Prevalence Survey of Antibiotic Use in 13 Chinese Hospitals. J. Infect. Public Health 2015, 8, 55–61. [Google Scholar] [CrossRef]
  118. Levy Hara, G.; Rojas-Cortes, R.; Molina León, H.F.; Dreser Mansilla, A.; Alfonso Orta, I.; Rizo-Amezquita, J.N.; Santos Herrera, R.G.; Mendoza De Ayala, S.; Arce Villalobos, M.; Mantilla Ponte, H.; et al. Point Prevalence Survey of Antibiotic Use in Hospitals in Latin American Countries. J. Antimicrob. Chemother. 2022, 77, 807–815. [Google Scholar] [CrossRef]
  119. Veerapa-Mangroo, L.P.; Rasamoelina-Andriamanivo, H.; Issack, M.I.; Cardinale, E. Point Prevalence Survey on Antibiotic Use in the Hospitals of Mauritius. Front. Antibiot. 2023, 1, 1045081. [Google Scholar] [CrossRef] [PubMed]
  120. Jamaluddin, N.A.H.; Periyasamy, P.; Lau, C.L.; Ponnampalavanar, S.; Lai, P.S.M.; Ramli, R.; Tan, T.L.; Kori, N.; Yin, M.K.; Azman, N.J.; et al. Point Prevalence Survey of Antimicrobial Use in a Malaysian Tertiary Care University Hospital. Antibiotics 2021, 10, 531. [Google Scholar] [CrossRef]
  121. Horumpende, P.G.; Mshana, S.E.; Mouw, E.F.; Mmbaga, B.T.; Chilongola, J.O.; De Mast, Q. Point Prevalence Survey of Antimicrobial Use in Three Hospitals in North-Eastern Tanzania. Antimicrob. Resist. Infect. Control 2020, 9, 149. [Google Scholar] [CrossRef]
  122. Cairns, K.A.; Roberts, J.A.; Cotta, M.O.; Cheng, A.C. Antimicrobial Stewardship in Australian Hospitals and Other Settings. Infect. Dis. Ther. 2015, 4, 27–38. [Google Scholar] [CrossRef]
  123. Alabi, A.S.; Picka, S.W.; Sirleaf, R.; Ntirenganya, P.R.; Ayebare, A.; Correa, N.; Anyango, S.; Ekwen, G.; Agu, E.; Cook, R.; et al. Implementation of an Antimicrobial Stewardship Programme in Three Regional Hospitals in the South-East of Liberia: Lessons Learned. JAC-Antimicrob. Resist. 2022, 4, dlac069. [Google Scholar] [CrossRef]
  124. Kandeel, A.; Palms, D.L.; Afifi, S.; Kandeel, Y.; Etman, A.; Hicks, L.A.; Talaat, M. An Educational Intervention to Promote Appropriate Antibiotic Use for Acute Respiratory Infections in a District in Egypt- Pilot Study. BMC Public Health 2019, 19, 498. [Google Scholar] [CrossRef]
  125. Agyare, E.; Acolatse, J.E.E.; Dakorah, M.P.; Akafity, G.; Chalker, V.J.; Spiller, O.B.; Schneider, K.A.; Yevutsey, S.; Aidoo, N.B.; Blankson, S.; et al. Antimicrobial Stewardship Capacity and Antibiotic Utilisation Practices in the Cape Coast Teaching Hospital, Ghana: A Point Prevalence Survey Study. PLoS ONE 2024, 19, e0297626. [Google Scholar] [CrossRef]
  126. Al-Omari, A.; Al Mutair, A.; Alhumaid, S.; Salih, S.; Alanazi, A.; Albarsan, H.; Abourayan, M.; Al Subaie, M. The Impact of Antimicrobial Stewardship Program Implementation at Four Tertiary Private Hospitals: Results of a Five-Years Pre-Post Analysis. Antimicrob. Resist. Infect. Control 2020, 9, 95. [Google Scholar] [CrossRef]
  127. Amponsah, O.K.O.; Courtenay, A.; Kwame Ayisi-Boateng, N.; Abuelhana, A.; Opoku, D.A.; Kobina Blay, L.; Abruquah, N.A.; Osafo, A.B.; Danquah, C.B.; Tawiah, P.; et al. Assessing the Impact of Antimicrobial Stewardship Implementation at a District Hospital in Ghana Using a Health Partnership Model. JAC-Antimicrob. Resist. 2023, 5, dlad084. [Google Scholar] [CrossRef]
  128. Kiggundu, R.; Waswa, J.P.; Nakambale, H.N.; Kakooza, F.; Kassuja, H.; Murungi, M.; Akello, H.; Morries, S.; Joshi, M.P.; Stergachis, A.; et al. Development and Evaluation of a Continuous Quality Improvement Programme for Antimicrobial Stewardship in Six Hospitals in Uganda. BMJ Open Qual. 2023, 12, e002293. [Google Scholar] [CrossRef]
  129. Momattin, H.; Al-Ali, A.Y.; Mohammed, K.; Al-Tawfiq, J.A. Benchmarking of Antibiotic Usage: An Adjustment to Reflect Antibiotic Stewardship Program Outcome in a Hospital in Saudi Arabia. J. Infect. Public Health 2018, 11, 310–313. [Google Scholar] [CrossRef]
  130. Arenz, L.; Porger, A.; De Michel, M.; Weber, A.; Jung, J.; Horns, H.; Gscheidle, S.; Weiglein, T.; Pircher, J.; Becker-Lienau, J.; et al. Effect and Sustainability of a Stepwise Implemented Multidisciplinary Antimicrobial Stewardship Programme in a University Hospital Emergency Department. JAC-Antimicrob. Resist. 2024, 6, dlae026. [Google Scholar] [CrossRef]
  131. Shamseddine, J.; Sadeq, A.; Yousuf, K.; Abukhater, R.; Yahya, L.O.; Espil, M.A.; Hassan, M.E.; Fadl, R.E.; Ahmed, R.T.E.; Elkonaissi, I.; et al. Impact of Antimicrobial Stewardship Interventions on Days of Therapy and Guideline Adherence: A Comparative Point-Prevalence Survey Assessment. Front. Trop. Dis. 2023, 3, 1050344. [Google Scholar] [CrossRef]
  132. Mandelli, G.; Dore, F.; Langer, M.; Garbero, E.; Alagna, L.; Bianchin, A.; Ciceri, R.; Di Paolo, A.; Giani, T.; Giugni, A.; et al. Effectiveness of a Multifaced Antibiotic Stewardship Program: A Pre-Post Study in Seven Italian ICUs. J. Clin. Med. 2022, 11, 4409. [Google Scholar] [CrossRef]
  133. Lohiniva, A.L.; Heweidy, I.; Girgis, S.; Abouelata, O.; Ackley, C.; Samir, S.; Talaat, M. Developing a Theory-Based Behavior Change Intervention to Improve the Prescription of Surgical Prophylaxis. Int. J. Clin. Pharm. 2022, 44, 227–234. [Google Scholar] [CrossRef]
  134. Rawson, T.M.; Moore, L.S.P.; Tivey, A.M.; Tsao, A.; Gilchrist, M.; Charani, E.; Holmes, A.H. Behaviour Change Interventions to Influence Antimicrobial Prescribing: A Cross-Sectional Analysis of Reports from UK State-of-the-Art Scientific Conferences. Antimicrob. Resist. Infect. Control 2017, 6, 11. [Google Scholar] [CrossRef]
  135. Wilkinson, A.; Ebata, A.; Macgregor, H. Interventions to Reduce Antibiotic Prescribing in LMICs: A Scoping Review of Evidence from Human and Animal Health Systems. Antibiotics 2019, 8, 2. [Google Scholar] [CrossRef]
  136. World Health Organization. Health Workers’ Education and Training on Antimicrobial Resistance: Curricula Guide; World Health Organization: Geneva, Switzerland, 2019; Available online: https://iris.who.int/bitstream/handle/10665/329380/9789241516358-eng.pdf (accessed on 6 February 2025).
  137. Sonda, T.B.; Horumpende, P.G.; Kumburu, H.H.; van Zwetselaar, M.; Mshana, S.E.; Alifrangis, M.; Lund, O.; Aarestrup, F.M.; Chilongola, J.O.; Mmbaga, B.T.; et al. Ceftriaxone Use in a Tertiary Care Hospital in Kilimanjaro, Tanzania: A Need for a Hospital Antibiotic Stewardship Programme. PLoS ONE 2019, 14, e0220261. [Google Scholar] [CrossRef]
  138. Afriyie, D.K.; Amponsah, S.K.; Dogbey, J.; Agyekum, K.; Kesse, S.; Truter, I.; Meyer, J.C.; Godman, B. A Pilot Study Evaluating the Prescribing of Ceftriaxone in Hospitals in Ghana: Findings and Implications. Hosp. Pract. 2017, 45, 143–149. [Google Scholar] [CrossRef]
  139. Iredell, J.; Brown, J.; Tagg, K. Antibiotic Resistance in Enterobacteriaceae: Mechanisms and Clinical Implications. BMJ 2016, 352, h6420. [Google Scholar] [CrossRef]
  140. Teklu, D.S.; Negeri, A.A.; Legese, M.H.; Bedada, T.L.; Woldemariam, H.K.; Tullu, K.D. Extended-Spectrum Beta-Lactamase Production and Multi-Drug Resistance among Enterobacteriaceae Isolated in Addis Ababa, Ethiopia. Antimicrob. Resist. Infect. Control 2019, 8, 39. [Google Scholar] [CrossRef]
  141. Perez, F.; Endimiani, A.; Hujer, K.M.; Bonomo, R.A. The Continuing Challenge of ESBLs. Curr. Opin. Pharmacol. 2007, 7, 459–469. [Google Scholar] [CrossRef]
  142. Ibrahim, D.R.; Dodd, C.E.R.; Stekel, D.J.; Meshioye, R.T.; Diggle, M.; Lister, M.; Hobman, J.L. Multidrug-Resistant ESBL-Producing E. Coli in Clinical Samples from the UK. Antibiotics 2023, 12, 169. [Google Scholar] [CrossRef]
  143. El Aila, N.A.; Al Laham, N.A.; Ayesh, B.M. Prevalence of Extended Spectrum Beta Lactamase and Molecular Detection of BlaTEM, BlaSHV and BlaCTX-M Genotypes among Gram-Negative Bacilli Isolates from Pediatric Patient Population in Gaza Strip. BMC Infect. Dis. 2023, 23, 99. [Google Scholar] [CrossRef]
  144. Lester, R.; Haigh, K.; Wood, A.; Macpherson, E.E.; Maheswaran, H.; Bogue, P.; Hanger, S.; Kalizang’Oma, A.; Srirathan, V.; Kulapani, D.; et al. Sustained Reduction in Third-Generation Cephalosporin Usage in Adult Inpatients Following Introduction of an Antimicrobial Stewardship Program in a Large, Urban Hospital in Malawi. Clin. Infect. Dis. 2020, 71, E478–E486. [Google Scholar] [CrossRef]
  145. Yusef, D.; Hayajneh, W.A.; Bani Issa, A.; Haddad, R.; Al-Azzam, S.; Lattyak, E.A.; Lattyak, W.J.; Gould, I.; Conway, B.R.; Bond, S.; et al. Impact of an Antimicrobial Stewardship Programme on Reducing Broad-Spectrum Antibiotic Use and Its Effect on Carbapenem-Resistant Acinetobacter Baumannii (CRAb) in Hospitals in Jordan. J. Antimicrob. Chemother. 2021, 76, 516–523. [Google Scholar] [CrossRef]
  146. Hingorani, R.; Mahmood, M.; Alweis, R. Improving Antibiotic Adherence in Treatment of Acute Upper Respiratory Infections: A Quality Improvement Process. J. Community Hosp. Intern. Med. Perspect. 2015, 5, 27472. [Google Scholar] [CrossRef]
  147. Craig, J.; Sriram, A.; Sadoff, R.; Bennett, S.; Bahati, F.; Beauvais, W. Behavior-Change Interventions to Improve Antimicrobial Stewardship in Human Health, Animal Health, and Livestock Agriculture: A Systematic Review. PLoS Glob. Public Health 2023, 3, e0001526. [Google Scholar] [CrossRef] [PubMed]
  148. Mzumara, G.W.; Mambiya, M.; Iroh Tam, P.Y. Protocols, Policies and Practices for Antimicrobial Stewardship in Hospitalized Patients in Least-Developed and Low-Income Countries: A Systematic Review. Antimicrob. Resist. Infect. Control 2023, 12, 131. [Google Scholar] [CrossRef]
  149. Otieno, P.A.; Campbell, S.; Maley, S.; Obinju Arunga, T.; Otieno Okumu, M. A Systematic Review of Pharmacist-Led Antimicrobial Stewardship Programs in Sub-Saharan Africa. Int. J. Clin. Pract. 2022, 2022, 3639943. [Google Scholar] [CrossRef]
  150. Yin, J.; Li, H.; Sun, Q. Analysis of Antibiotic Consumption by AWaRe Classification in Shandong Province, China, 2012–2019: A Panel Data Analysis. Front. Pharmacol. 2021, 12, 790817. [Google Scholar] [CrossRef]
  151. Ishibashi, N.; Pauwels, I.; Tomori, Y.; Gu, Y.; Yamaguchi, T.; Handa, T.; Yamaoka, M.; Ito, D.; Sakimoto, T.; Kimura, T.; et al. Point Prevalence Surveys of Antimicrobial Prescribing in a Non-Acute Care Hospital in Saitama Prefecture, Japan. Can. J. Infect. Dis. Med. Microbiol. 2022, 2022, 2497869. [Google Scholar] [CrossRef]
  152. Vanderbilt Software—REDCap. REDCap—Research Electronic Data Capture. 2017. Available online: https://projectredcap.org/software/ (accessed on 6 February 2025).
  153. Republic of Zambia Ministry of Health. Zambia Standard Treatment Guidelines 2020; Republic of Zambia Ministry of Health: Lusaka, Zambia, 2020. Available online: https://www.moh.gov.zm/?wpfb_dl=32 (accessed on 6 February 2025).
  154. Ministry of Health. Zambia Essential Medicines List (ZEML); Ministry of Health: Lusaka, Zambia, 2020. Available online: https://www.moh.gov.zm/?wpfb_dl=39 (accessed on 6 February 2025).
  155. Sharland, M.; Pulcini, C.; Harbarth, S.; Zeng, M.; Gandra, S.; Mathur, S.; Magrini, N. Classifying Antibiotics in the WHO Essential Medicines List for Optimal Use—Be AWaRe. Lancet Infect. Dis. 2018, 18, 18–20. [Google Scholar] [CrossRef] [PubMed]
Antibiotics 14 00284 g001
Figure 1. Antibiotic prescribing rate at Livingstone TH at baseline (2022) and follow-up (2023).
Figure 1. Antibiotic prescribing rate at Livingstone TH at baseline (2022) and follow-up (2023).
Antibiotics 14 00284 g001
Antibiotics 14 00284 g002
Figure 2. Antibiotic prescribing rate at Ndola TH at baseline (2022) and follow-up (2023).
Figure 2. Antibiotic prescribing rate at Ndola TH at baseline (2022) and follow-up (2023).
Antibiotics 14 00284 g002
Antibiotics 14 00284 g003
Figure 3. Antibiotic prescribing rate at UTH (Lusaka) at baseline (2022) and follow-up (2023).
Figure 3. Antibiotic prescribing rate at UTH (Lusaka) at baseline (2022) and follow-up (2023).
Antibiotics 14 00284 g003
Antibiotics 14 00284 g004
Figure 4. Map of Zambia showing the location of the surveyed hospitals.
Figure 4. Map of Zambia showing the location of the surveyed hospitals.
Antibiotics 14 00284 g004
Table 1. Demographic characteristics at baseline (2022) and follow-up (2023) point prevalence surveys.
Table 1. Demographic characteristics at baseline (2022) and follow-up (2023) point prevalence surveys.
All SitesLivingstone THNdola THUTH (Lusaka)
VARIABLESOverall
N = 437 1		2022
N = 172 1		2023
N = 265 1		Pr 2Overall
N = 64 1		2022
N = 21 1		2023
N = 43 1		Pr 2Overall
N = 148 1		2022
N = 74 1		2023
N = 74 1		Pr 2Overall
N = 223 1		2022
N = 75 1		2023
N = 148 1		Pr 2
Age of patient in years 0.4 0.8 0.3 0.7
Median
(Q1, Q3)		44
(30, 58)		45
(31, 60)		44
(29, 56)		 40
(25, 53)		40
(23, 53)		41
(26, 52)		 48
(32, 65)		50
(35, 65)		46
(30, 65)		 43
(29, 55)		43
(28, 54)		44
(32, 56)
*129 1 1 4 4 4 4
Gender of patient >0.9 0.12 0.8 0.5
Female199
(46%)		78
(47%)		121
(46%)		 27
(42%)		6
(29%)		21
(49%)		 70
(48%)		36
(49%)		34
(47%)		 102
(47%)		36
(50%)		66
(45%)
Male230
(54%)		89
(53%)		141
(54%)		 37
(58%)		15
(71%)		22
(51%)		 77
(52%)		38
(51%)		39
(53%)		 116
(53%)		36
(50%)		80
(55%)
*853 1 532
1 n (%); * missing values; Q1: quartile 1; Q3: quartile 3; 2 Wilcoxon rank sum tests; Pearson’s chi-squared test.
Table 2. Prescribing behavior at baseline (2022) and follow-up (2023).
Table 2. Prescribing behavior at baseline (2022) and follow-up (2023).
All SitesLivingstone THNdola THUTH (Lusaka)
VARIABLESOverall
N = 427 1		2022
N = 172 1		2023
N = 265 1		Pr 2Overall
N = 64 1		2022
N = 21 1		2023
N = 43 1		Pr 2Overall
N = 148 1		2022
N = 74 1		2023
N = 74 1		Pr 2Overall
N = 223 1		2022
N = 75 1		2023
N = 148 1		Pr 2
Compliance with STGs <0.001 <0.001 <0.001 <0.001
Compliance137
(44%)		59
(42%)		78
(45%)		 21
(50%)		021
(88%)		 47
(44%)		37
(59%)		10
(22%)		 69
(42%)		22
(37%)		47
(46%)
Insufficient Information25
(8.0%)		6
(4.3%)		19
(11%)		 1
(2.4%)		01
(4.2%)		 20
(19%)		2
(3.2%)		18
(40%)		 4
(2.5%)		4
(6.7%)		0
Non-Compliance83
(27%)		21
(15%)		62
(36%)		 12
(29%)		11
(61%)		1
(4.2%)		 10
(9.3%)		2
(3.2%)		8
(18%)		 61
(37%)		8
(13%)		53
(51%)
Not Assessable68
(22%)		55
(39%)		13
(7.6%)		 8
(19%)		7
(39%)		1
(4.2%)		 31
(29%)		22
(35%)		9
(20%)		 29
(18%)		26
(43%)		3
(2.9%)
*1243193 22319 401129 601545
Patients categories 0.001 0.11 0.001 0.083
No antibiotics prescribed110
(25%)		32
(19%)		78
(29%)		 17
(27%)		2
(9.5%)		15
(35%)		 38
(26%)		10
(14%)		28
(38%)		 53
(24%)		18
(24%)		35
(24%)
1 Antibiotic prescribed126
(29%)		63
(37%)		63
(24%)		 17
(27%)		6
(29%)		11
(26%)		 40
(27%)		26
(35%)		14
(19%)		 69
(31%)		31
(41%)		38
(26%)
2 Antibiotics prescribed175
(40%)		60
(35%)		115
(43%)		 25
(39%)		10
(48%)		15
(35%)		 58
(39%)		26
(35%)		32
(43%)		 92
(41%)		24
(32%)		68
(46%)
3 Antibiotics prescribed23
(5.3%)		14
(8.1%)
9
(3.4%)		 4
(6.3%)		2
(9.5%)		2
(4.7%)		 10
(6.8%)		10
(14%)		0 9
(4.0%)		2
(2.7%)		7
(4.7%)
4 Antibiotics prescribed3
(0.7%)		3
(1.7%)		0 1
(1.6%)		1
(4.8%)		0 2
(1.4%)		2
(2.7%)		0 000
Number prescribed 0.2 0.026 0.004 0.10
Mean
(SD)		1.27
(0.92)		1.38
(0.94)		1.21
(0.91)		 1.30
(0.99)		1.71
(0.96)		1.09
(0.95)		 1.31
(0.97)		1.57
(0.98)		1.05
(0.90)		 1.26
(0.87)		1.13
(0.81)		1.32
(0.89)
1 n (%); * missing values; 2 Pearson’s chi-squared tests; Fisher’s exact test; Wilcoxon rank sum test.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Mudenda, S.; Kapolowe, K.; Chirwa, U.; Chanda, M.; Chanda, R.; Kalaba, R.; Fwoloshi, S.; Phiri, C.; Mwamba, M.; Chirwa, R.K.; et al. Antimicrobial Stewardship Impact on Antibiotic Use in Three Tertiary Hospitals in Zambia: A Comparative Point Prevalence Survey. Antibiotics 2025, 14, 284. https://doi.org/10.3390/antibiotics14030284

AMA Style

Mudenda S, Kapolowe K, Chirwa U, Chanda M, Chanda R, Kalaba R, Fwoloshi S, Phiri C, Mwamba M, Chirwa RK, et al. Antimicrobial Stewardship Impact on Antibiotic Use in Three Tertiary Hospitals in Zambia: A Comparative Point Prevalence Survey. Antibiotics. 2025; 14(3):284. https://doi.org/10.3390/antibiotics14030284

Chicago/Turabian Style

Mudenda, Steward, Kenneth Kapolowe, Uchizi Chirwa, Melvin Chanda, Raphael Chanda, Rodney Kalaba, Sombo Fwoloshi, Christabel Phiri, Mukuka Mwamba, Robert Kajaba Chirwa, and et al. 2025. "Antimicrobial Stewardship Impact on Antibiotic Use in Three Tertiary Hospitals in Zambia: A Comparative Point Prevalence Survey" Antibiotics 14, no. 3: 284. https://doi.org/10.3390/antibiotics14030284

APA Style

Mudenda, S., Kapolowe, K., Chirwa, U., Chanda, M., Chanda, R., Kalaba, R., Fwoloshi, S., Phiri, C., Mwamba, M., Chirwa, R. K., Nikoi, K., Musonda, L., Yamba, K., Chizimu, J. Y., Chanda, C., Mubanga, T., Simutowe, C., Kasanga, J., Mukanwa, M., ... Chanda, D. (2025). Antimicrobial Stewardship Impact on Antibiotic Use in Three Tertiary Hospitals in Zambia: A Comparative Point Prevalence Survey. Antibiotics, 14(3), 284. https://doi.org/10.3390/antibiotics14030284

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop