Next Article in Journal
Arthritis and Diagnostics in Lyme Disease
Next Article in Special Issue
New Contributions to the Elimination of Chagas Disease as a Public Health Problem: Towards the Sustainable Development Goals by 2030
Previous Article in Journal
The Case for the Development of a Chagas Disease Vaccine: Why? How? When?
Previous Article in Special Issue
Clinical, Cardiological and Serologic Follow-Up of Chagas Disease in Children and Adolescents from the Amazon Region, Brazil: Longitudinal Study
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Cost of Lost Productivity Due to Premature Chagas Disease-Related Mortality: Lessons from Colombia (2010–2017)

by
Mario J. Olivera
1,2,*,
Francisco Palencia-Sánchez
3 and
Martha Riaño-Casallas
4
1
Grupo de Parasitología, Instituto Nacional de Salud, Bogotá 111321, D.C., Colombia
2
Programme in Health Economics, Pontificia Universidad Javeriana, Bogotá 110231, D.C., Colombia
3
Facultad de Medicina, Departamento de Medicina Preventiva y Social, Pontificia Universidad Javeriana, Bogotá 110231, D.C., Colombia
4
Facultad de Ciencias Económicas, Universidad Nacional de Colombia, Bogotá 111321, D.C., Colombia
*
Author to whom correspondence should be addressed.
Trop. Med. Infect. Dis. 2021, 6(1), 17; https://doi.org/10.3390/tropicalmed6010017
Submission received: 13 April 2020 / Revised: 12 June 2020 / Accepted: 30 June 2020 / Published: 27 January 2021
(This article belongs to the Special Issue Chagas Disease)

Abstract

:
Background: Economic burden due to premature mortality has a negative impact not only in health systems but also in wider society. The aim of this study was to estimate the potential years of work lost (PYWL) and the productivity costs of premature mortality due to Chagas disease in Colombia from 2010 to 2017. Methods: National data on mortality (underlying cause of death) were obtained from the National Administrative Department of Statistics in Colombia between 2010 and 2017, in which Chagas disease was mentioned on the death certificate as an underlying or associated cause of death. Chagas disease as a cause of death corresponded to category B57 (Chagas disease) including all subcategories (B57.0 to B57.5), according to the Tenth Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10). The electronic database contains the number of deaths from all causes by sex and 5-year age group. Economic data, including wages, unemployment rates, labor force participation rates and gross domestic product, were derived from the Bank of the Republic of Colombia. The human capital approach was applied to estimate both the PYWL and present value of lifetime income lost due to premature deaths. A discount rate of 3% was applied and results are presented in 2017 US dollars (USD). Results: There were 1261 deaths in the study, of which, 60% occurred in males. Premature deaths from Chagas resulted in 48,621 PYWL and a cost of USD 29 million in the present value of lifetime income forgone. Conclusion: The productivity costs of premature mortality due to Chagas disease are significant. These results provide an economic measure of the Chagas burden which can help policy makers allocate resources to continue with early detection programs.

1. Introduction

Chagas disease remains a serious public health problem worldwide, having serious economic and social repercussions [1]. The infection is endemic in South America and emergent in Europe and the United States [2]. This parasitic disease affects 6–7 million people worldwide, causing more than 7000 deaths each year [3]. The cost of Chagas disease was USD 13.1 million in 2017 [4].
Chagas disease generates a significant health burden for individuals and a large economic burden in low- and middle-income countries in the Americas and in some high-income countries over recent decades [4]. Among the working-age population, the economic cost of illness-related productivity losses as a result of lower productivity at work, lost workdays, and mortality can far exceed the Chagas disease-related medical costs [5].
It is important to quantify the value of the labor productivity loss due to premature mortality in measuring the economic burden of disease. Specially, this metric should be quantified for communicable diseases in that affect low- and middle-income countries. To quantify the cost of economic losses owing to premature death in the working-age population, this value is used as the indicator of years of potential productive life lost [6,7]. In this case, we focused on economic cost. Chagas disease has been associated with excess mortality [8]. The most frequently used measures of economic loss due to premature death are years of potential life lost (YPLL) and potential years of work lost (PYWL) [6,9,10,11].
Chagas disease is a clear threat not only to human health but also the level of family income and economic growth in a country, particularly in rural areas [4]. It is estimated that 752,000 working years per year are lost due to premature deaths caused by diseases in the seven countries of South America, which corresponds to USD 1208.5 million/year [5].
Despite the high prevalence of Chagas disease estimated in Colombia 2.0% (95% CI: 1.0–4.0) [12], few studies have estimated the productivity losses associated with premature deaths from this infection in the country [4]. Therefore, this study aimed to estimate the PYWL associated with premature deaths caused by Chagas disease during the period from 2010 to 2017 in Colombia.

2. Materials and Methods

This study was developed based on the human capital approach to estimate the costs of productivity derived from premature mortality due to Chagas disease in Colombia. Premature mortality was defined as death from Chagas disease before the age of 62 (for men) or 57 (for women), years old. The human capital approach equates the productivity lost to an individual’s wage rate and assumes that an individual produces a stream of output over a working lifetime cut short by premature death. All expenses were reported as Colombian pesos (COP) and were converted to US dollars (1 USD (US$) = 2984 COP) from 2017 [13].

2.1. Data Source

Numbers of deaths in 2010–2017 by 5-year age group and sex between the ages of 15 and 62 were obtained from the mortality database of the National Administrative Department of Statistics (DANE) using the Tenth Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) code B57, including all subcategories (B57.0 to B57.5) [14]. The database contains number of deaths of all causes by sex and 5-year age. Economic data, including wages, unemployment rates, labor force participation rates and gross domestic product (GDP), were derived from Bank of the Republic of Colombia.

2.2. Estimation Methods

The number of deaths that could be attributed to Chagas from 2010 to 2017 by sex was extracted, and from these, PYWL for men and women were determined across the productive age groups (between 18 and 62 years old, retire at 62 (for men) or 57 (for women)—the official pensionable age in Colombia in 2017 [15]). Premature mortality costs involved multiplying, for each death, PYWL by age- and gender-stratified gross wages from age of death until to the official pensionable age. Estimates were the adjusted probability of being in work. Wage growth was calculated at 2.5% per annum, and a discount rate of 3% annually was applied. The scenario that assessed the 2017 minimum annual salary (USD 3301 per year) was modeled. In Colombia on average the growth of the real wage was 2%. Statistical analysis was performed using Stata version 14.0 (Stata Corporation LP, College Station, TX, USA). All variables included in the study were described using the appropriate univariate statistics.

2.3. Sensitivity Analyses

One-way sensitivity analysis was conducted to assess the effects of varying the parameters: the wage growth rate varied from 1.5% to 3.5% to account for uncertainty over future growth in the Colombian economy, and the minimum annual salary between USD 2715 and USD 4000. In addition, the effect of extending the retirement age was explored.

3. Results

From 2010 to 2017, 1446 deaths of Chagas disease were recorded. Of these, 185 deaths occurred in people under 18 years of age were excluded. In total, 1261 deaths were analyzed in the study, of which 60% corresponded to males. The mean age at death was 21 years. Table 1 presents the number of deaths of all ages for males and females. PYWL was lower in women than men (18,384 vs. 30,237), overall PYWL was 48,621. It noticed that the deaths each year of the analysis period.
Table 2 demonstrates the average premature mortality per PYWL by sex from 2010 to 2017. The cost per PYWL for both sexes combined was USD 29,683,913 in the study period, and it was USD 17.3 million for males and USD 12.3 million for females from 2010 to 2017. In the case of women, they tended to have lower wages and a shorter working life.
The total cost of lost productivity due to premature mortality was 39.7% higher in males than females, although the cost per PYWL was higher in females.
Table 3 shows the cost of premature mortality sex in each year of the period.
We classified the people included according to age; people who died between the ages of 18 and 25 years were categorized as young and people above 25 years old classified as adults. Therefore, Table 4 shows the impact of the cost is bigger.
Figure 1 shows a boxplot of cost of premature mortality by sex, for which the variation was higher for men per death than for women. This is because men die younger than women and they have a longer pensionable age. In the graph, the circles are outlier values of the cost of PYWL.
Figure 2 depicts the PYWL per occupational group; construction workers, farm workers and unskilled workers were the groups with the most years lost. In the graph, the circles are outlier values of the cost of PYWL in farm workers.

4. Discussion

The main finding of this study was the estimation of the monetary value of the accumulated labor productivity losses during the 2010–2017 period due to deaths caused by Chagas disease in Colombia. This cost amounted to USD 29 million. Despite the magnitude of the estimated cost, the trend observed throughout the period was that of further increasing costs. However, it should be clarified that this increase in the number of deaths could be due to the strengthening of surveillance systems that allow for a better counting of deaths and to the strengthening of the health system.
In recent years, Colombia has had great social, demographic, environmental and technological transformations in a sustained manner, and despite the innumerable situations of social injustice, the living conditions of the populations have improved significantly [16,17]. However, diseases associated with contexts of social vulnerability and neglect, such as Chagas disease, still affect a considerable part of the population for example workers such as unskilled workers, farm worker and construction workers [12].
It is also worrying that the percentage of deaths from preventable Chagas disease continues to be high in the younger population. This is probably associated with barriers to timely diagnosis that persist in the country and the difficulties associated with treatment [1,18,19]. This implies support for the early detection programs [20,21].
Interestingly, 60% of the estimated losses in labor productivity can be attributed to men. This can be explained by the higher risk of death in this group and, on the other hand, by the fact that employment rates and wages were higher for men than for women. It could also be related to the difference between men and women. These results are concordantwith previous studies that have consistently reported that men have a higher risk of death than women [22,23].
Previous studies have tried to estimate the social impact of premature deaths on workers suffering from Chagas disease, but over a short time period [4]. On the other hand, some research has delved into the loss of health-related quality of life caused by the consequences of the disease [24,25]. The strengthening and implementation of public policies aimed at eliminating barriers to early diagnosis and treatment of Chagas disease can impact on the reduction of mortality [26].
It is important to note that the theoretical approach used in the present study is ttheory of human capital [27]. The main alternative approach is the so-called friction-cost method [28]. Although the methodological discussion on the strengths and weaknesses of both approaches has been intense, there is still no agreement on which is best [27]. In this study, the human capital approach was chosen due to its greater anchorage with economic theory and it is the most widely used method in the scientific literature on disease cost studies.
The main limitations include, firstly, the real wages of people killed by Chagas disease (estimated from the average wage in Colombia) were not considered. Second, there was also no information on whether the deceased worked or not (the average employment rates adjusted for age and sex). Third, the mortality database might have been vastly underreported in official statistics.

5. Conclusions

Reducing premature and preventable deaths from Chagas disease is a key health goal in the ten-year plan for Colombian public health. The size of the economic impact and the burden on society due to premature deaths from Chagas disease reinforces the need to continue investing in early detection programs, as well as initiatives that promote prosperity and well-being for all.

Author Contributions

All authors contributed equally to the design of the study, data collection, data analysis, data interpretation, and manuscript writing, and all authors have read and agreed to the published version of the manuscript. Conceptualization, M.J.O., F.P.-S. and M.R.-C.; methodology, M.J.O., F.P.-S. and M.R.-C., software, M.J.O., F.P.-S. and M.R.-C.; validation, M.J.O., F.P.-S. and M.R.-C.; formal analysis, M.J.O., F.P.-S. and M.R.-C. investigation, M.J.O., F.P.-S. and M.R.-C.; resources, M.J.O., F.P.-S. and M.R.-C.; data curation, M.J.O., F.P.-S. and M.R.-C.; writing—original draft preparation, M.J.O., F.P.-S. and M.R.-C.; writing—review and editing, M.J.O., F.P.-S. and M.R.-C.; visualization, M.J.O., F.P.-S. and M.R.-C.; supervision, M.J.O., F.P.-S. and M.R.-C.; project administration, M.J.O., F.P.-S. and M.R.-C.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare that there is no conflict of interest.

References

  1. Olivera, M.J.; Porras, J.; Toquica, C.; Rodríguez, J. Barriers to diagnosis dccess for Chagas disease in Colombia. J. Parasitol. Res. 2018, 2018, 4940796. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Pinto Dias, J.C. Human Chagas disease and migration in the context of globalization: Some particular aspects. J. Trop. Med. 2013, 2013, 789758. [Google Scholar] [CrossRef] [Green Version]
  3. World Health Organization. Chagas disease in Latin America: An epidemiological update based on 2010 estimates. Wkly. Epidemiol. Rec. 2015, 90, 33–44. [Google Scholar]
  4. Olivera, M.J.; Buitrago, G. Economic costs of Chagas disease in Colombia in 2017: A social perspective. Int. J. Infect. Dis. 2020, 91, 196–201. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. World Health Organization. First WHO Report on Neglected Tropical Diseases: Working to Overcome the Global Impact of Neglected Tropical Diseases. France, 2010. Available online: https://www.who.int/neglected_diseases/2010report/en/ (accessed on 6 March 2020).
  6. Gardner, J.W.; Sanborn, J.S. Years of potential life lost (YPLL)-What does it measure? Epidemiology 1990, 1, 322–329. [Google Scholar] [CrossRef]
  7. Darbà, J.; Marsà, A. The cost of lost productivity due to premature lung cancer-related mortality: Results from Spain over a 10-year period. BMC Cancer 2019, 19, 992. [Google Scholar] [CrossRef]
  8. Cucunubá, Z.M.; Okuwoga, O.; Basáñez, M.G.; Nouvellet, P. Increased mortality attributed to Chagas disease: A systematic review and meta-analysis. Parasites Vectors 2016, 9, 42. [Google Scholar] [CrossRef] [Green Version]
  9. Wise, R.P.; Livengood, J.R.; Berkelman, R.L.; Goodman, R.A. Methodological alternatives for measuring premature mortality. Am. J. Prev. Med. 1988, 4, 268–273. [Google Scholar] [CrossRef]
  10. Romeder, J.M.; McWhinnie, J.R. Potential years of life lost between ages 1 and 70: An indicator of premature mortality for health planning. Int. J. Epidemiol. 1977, 6, 143–151. [Google Scholar] [CrossRef]
  11. Zhong, Y.; Li, D. Potential years of life lost and work tenure lost when silicosis is compared with other pneumoconioses. Scand. J. Work Environ. Health 1995, 21, 91–94. [Google Scholar]
  12. Olivera, M.J.; Fory, J.A.; Porras, J.F.; Buitrago, G. Prevalence of Chagas disease in Colombia: A systematic review and meta-analysis. PLoS ONE 2019, 14, e0210156. [Google Scholar] [CrossRef] [PubMed]
  13. Banco de la República Colombia. Tasa Representativa del Mercado (TRM-Peso por dólar). Available online: https://www.banrep.gov.co/es/estadisticas/trm (accessed on 24 February 2020).
  14. Departamento Administrativo Nacional de Estadística. Mortalidad en Colombia, 2017. Available online: https://www.dane.gov.co/index.php/estadisticas-por-tema/demografia-y-poblacion/nacimientos-y-defunciones (accessed on 6 March 2020).
  15. Congreso de Colombia. Ley 100 de 1993. Por la Cual se Crea el Sistema de Seguridad Social Integral y se Dictan Otras Disposiciones. Available online: http://www.secretariasenado.gov.co/senado/basedoc/ley_0100_1993.html (accessed on 6 March 2020).
  16. Augustovski, F.; Alcaraz, A.; Caporale, J.; García Martí, S.; Pichon Riviere, A. Institutionalizing health technology assessment for priority setting and health policy in Latin America: From regional endeavors to national experiences. Expert Rev. Pharmacoecon. Outcomes Res. 2015, 15, 9–12. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Departamento Administrativo Nacional de Estadística. Encuesta Nacional de Calidad de vida 2018. 2019. Available online: https://www.dane.gov.co/index.php/estadisticas-por-tema/pobreza-y-condiciones-de-vida/calidad-de-vida-ecv (accessed on 6 March 2020).
  18. Olivera, M.J.; Cucunuba, Z.M.; Alvarez, C.A.; Nicholls, R.S. Safety profile of nifurtimox and treatment interruption for chronic Chagas disease in Colombian adults. Am. J. Trop. Med. Hyg. 2015, 93, 1224–1230. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  19. Olivera, M.J.; Cucunuba, Z.M.; Valencia-Hernandez, C.A.; Herazo, R.; Agreda-Rudenko, D.; Florez, C.; Duque, S.; Nicholls, R.S. Risk factors for treatment interruption and severe adverse effects to benznidazole in adult patients with Chagas disease. PLoS ONE 2017, 12, e0185033. [Google Scholar] [CrossRef] [PubMed]
  20. Olivera, M.J.; Fory, J.A.; Olivera, A.J. Quality assessment of clinical practice guidelinesfor Chagas disease. Rev. Soc. Bras. Med. Trop. 2015, 48, 343–346. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  21. Olivera, M.J.; Fory, J.A.; Olivera, A.J. Therapeutic drug monitoring of benznidazole and nifurtimox: A systematic review and quality assessment of published clinical practice guidelines. Rev. Soc. Bras. Med. Trop. 2017, 50, 748–755. [Google Scholar] [CrossRef] [Green Version]
  22. Basquiera, A.L.; Sembaj, A.; Aguerri, A.M.; Omelianiuk, M.; Guzmán, S.; Moreno Barral, J.; Caeiro, T.F.; Madoery, R.J.; Salomone, O.A. Risk progression to chronic Chagas cardiomyopathy: Influence of male sex and of parasitaemia detected by polymerase chain reaction. Heart 2003, 89, 1186–1190. [Google Scholar] [CrossRef] [Green Version]
  23. Sabino, E.C.; Ribeiro, A.L.; Salemi, V.M.C.; Di Lorenzo Oliveira, C.; Antunes, A.P.; Menezes, M.M.; Lanni, B.M.; Nastari, L.; Fernandes, F.; Patavino, G.M.; et al. Ten-year incidence of Chagas cardiomyopathy among asymptomatic trypanosoma cruzi-seropositive former blood donors. Circulation 2013, 127, 1105–1115. [Google Scholar] [CrossRef] [Green Version]
  24. Pelegrino, V.M.; Dantas, R.A.S.; Ciol, M.A.; Clark, A.M.; Rossi, L.A.; Simoes, M.V. Health-related quality of life in Brazilian outpatients with Chagas and non-Chagas cardiomyopathy. Heart Lung 2011, 40, e25–e31. [Google Scholar] [CrossRef]
  25. Oliveira, B.G.; Abreu, M.N.S.; Abreu, C.D.G.; da Costa Rocha, M.O.; Ribeiro, A.L. Health-related quality of life in patients with Chagas disease. Rev. Soc. Bras. Med. Trop. 2011, 44, 150–156. [Google Scholar] [CrossRef] [Green Version]
  26. Olivera, M.J.; Chaverra, K.A. New diagnostic algorithm for Chagas disease: Impact on access to diagnosis and out-of-pocket expenditures in Colombia. Iran. J. Public Health 2019, 48, 1379–1381. [Google Scholar] [CrossRef] [PubMed]
  27. Drummond, M.; Sculpher, M.; Claxton, K.; Stoddart, G.; Torrance, G. Methods for the Economic Evaluation of Health Care Programmes, 4th ed.; Oxford University Press: Oxford, UK, 2015. [Google Scholar]
  28. Pike, J.; Grosse, S.D. Friction cost estimates of productivity costs in cost-of-illness studies in comparison with human capital estimates: A review. Appl. Health Econ. Health Policy 2018, 16, 765–778. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Cost of productivity lost due to premature mortality by sex (USD 2017).
Figure 1. Cost of productivity lost due to premature mortality by sex (USD 2017).
Tropicalmed 06 00017 g001
Figure 2. Potential Years of Work Lost (PYWL) by occupation.
Figure 2. Potential Years of Work Lost (PYWL) by occupation.
Tropicalmed 06 00017 g002
Table 1. The number of deaths and estimated Potential Years of Work Lost (PYWL) by sex from 2010 to 2017.
Table 1. The number of deaths and estimated Potential Years of Work Lost (PYWL) by sex from 2010 to 2017.
Year20102011201220132014201520162017Total
Number of Deaths
Males1028710111011393132128866
Females5851597179859285580
Total1601381601811921782242131446
Deaths at Working Age
Males846988959383117112741
Females5245516472768476520
Total1361141391591651592011881261
PYWL
Males3441282235943900377733484772458330,237
Females1854159318242263252126822968267918,384
Total5295441554186163629860307740726248,621
Table 2. Premature mortality cost by sex per death and per Potential Years of Work Lost (PYWL) (USD 2017).
Table 2. Premature mortality cost by sex per death and per Potential Years of Work Lost (PYWL) (USD 2017).
Total Premature Mortality Cost% of the TotalPremature Mortality Cost per DeathPremature Mortality Cost per PYWL
Males17,301,2375823,348572
Females12,382,6764223,813674
Total29,683,91310023,540611
Table 3. Premature mortality cost per sex 2010–2017 (USD 2017).
Table 3. Premature mortality cost per sex 2010–2017 (USD 2017).
Year20102011201220132014201520162017
Males1,862,8731,541,7992,008,1752,198,7822,206,1531,986,0682,793,3212,704,067
Females1,174,1361,023,4841,183,1871,509,2321,736,9161,846,5842,040,4001,868,737
Total3,037,0092,565,2833,191,3623,708,0143,943,0693,832,6524,833,7224,572,803
Table 4. Premature mortality cost per group age 2010–2017 (USD 2017).
Table 4. Premature mortality cost per group age 2010–2017 (USD 2017).
Age Group/Year20102011201220132014201520162017
Adults22,59768,20346,16547,10696,49172,932170,01298,320
Young 3,014,4122,497,0813,145,1973,660,9083,846,5783,759,7194,663,7104,474,483
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Olivera, M.J.; Palencia-Sánchez, F.; Riaño-Casallas, M. The Cost of Lost Productivity Due to Premature Chagas Disease-Related Mortality: Lessons from Colombia (2010–2017). Trop. Med. Infect. Dis. 2021, 6, 17. https://doi.org/10.3390/tropicalmed6010017

AMA Style

Olivera MJ, Palencia-Sánchez F, Riaño-Casallas M. The Cost of Lost Productivity Due to Premature Chagas Disease-Related Mortality: Lessons from Colombia (2010–2017). Tropical Medicine and Infectious Disease. 2021; 6(1):17. https://doi.org/10.3390/tropicalmed6010017

Chicago/Turabian Style

Olivera, Mario J., Francisco Palencia-Sánchez, and Martha Riaño-Casallas. 2021. "The Cost of Lost Productivity Due to Premature Chagas Disease-Related Mortality: Lessons from Colombia (2010–2017)" Tropical Medicine and Infectious Disease 6, no. 1: 17. https://doi.org/10.3390/tropicalmed6010017

Article Metrics

Back to TopTop