Abstract
Purpose
The worldwide prevalence of Chagas Cardiomyopathy (CCM) as well as the trends in the prevalence of CCM over time have not been well characterized.
Methods
An analysis of the Global Burden of Disease (GBD) data from 1990 to 2019 was conducted to assess the burden of CCM. This study focused on determining the prevalence of CCM, along with its age-standardized prevalence rate (ASR) per 1,00,000 people, considering various patient demographics and geographical regions as defined in the GBD. Additionally, the study examined the temporal trends over this 30-year period by calculating the estimated annual percentage change (EAPC) in CCM prevalence for the global population and specific subgroups.
Results
Worldwide, the GBD reported 220,166 individuals with CCM in 1990 and 2,83,236 individuals in 2019, with a decline in the ASR from 5.23 (3.34–7.47) to 3.42 (2.2–4.91) per 1,00,000 individuals during that period. In 2019, the prevalence was highest in individuals over age 70 and in males compared to females. Among available geographic classifications in 2019, Latin American regions had the highest rates (ASR of 39.49–61.15/1,00,000), while high income North American and Western European regions had the lowest rates (ASRs of 0.67 and 0.34/1,00,000, respectively). Between 1990 and 2019, the worldwide prevalence of CCM per 1,00,000 decreased (EAPC of −0.35, −0.37 to −0.32), with similar trends among most regions and subgroups.
Conclusion
This analysis of the GBD data reveals both global and country-specific patterns in the prevalence and trends of CCM. Notably, CCM shows the highest prevalence in Latin American countries, although it’s also significantly present in regions beyond Latin America. Notably, the global age-standardized rate of CCM is on the decline, suggesting improvements in healthcare strategies or lifestyle changes across the world.
Keywords: Chagas disease, Chagas cardiomyopathy, Trypanosoma cruzi, T. cruzi
Introduction
Chagas disease, caused by the protozoa Trypanosoma cruzi, is endemic in many Latin American countries but is also encountered outside of Latin America due to global migration [1, 2]. Chronic infection with Chagas disease may manifest with gastrointestinal and/or cardiac involvement characterized by arrhythmias, thromboembolic phenomena, and chronic Chagas cardiomyopathy (CCM). With chronic Chagas infection, the annual incidence of CCM is estimated at around 2% per year. [3] Over a 10-year period, the risk of experiencing a cardiac event, including CCM, is approximately 40%. Additionally, CCM is closely associated with high levels of morbidity and mortality [4]. Presentation can range from subclinical to symptomatic heart failure, including end-stage heart failure requiring advanced therapies or palliative care, to sudden cardiac death. Although the global burden of the full range of Chagas manifestations including mortality has been well characterized, [1] there are limited data on the global burden and disease trends specifically related to CCM. Therefore, we sought to assess the burden of CCM from the Global Burden of Disease (GBD) study, with a focus on both trends and regional differences as well as subgroup insights in disease prevalence.
Methods
The data in this study were extracted from the GBD 2019 dataset using the research tools available at https://ghdx.healthdata.org/gbd-2019. GBD data were used to analyze the disease burden of heart failure due to Chagas disease between 1990 and 2019. Statistical modeling methods for estimating Chagas disease from the GBD, including data sources, have been previously described [1]. Specifically, the GBD estimated Chagas disease burden in endemic countries through country-level seroprevalence data with additional Bayesian data adjustment [1]. In non-endemic countries, the estimates were calculated by importation of prevalent cases by immigration [1]. Heart Failure within the GBD was likewise estimated using literature data, hospital data and claims data (modeled with spatiotemporal Gaussian process regression and DisMod–MR [a Bayesian metaregression method]), [5] with heart failure cause ultimately attributed to particular causes, including Chagas disease. [6]
The number of prevalent cases and their 95% uncertainty intervals (UIs) and age‐standardized prevalence rate (ASR) per 1,00,000 were determined by age, sex, year, socio-demographic index (SDI), regions, and countries and territories as characterized within the GBD. Age Standardized Rate is utilized in our analyses because it helps account for differences in the age distribution of the population across different groups and over time and is likewise indexed per 1,00,000 individuals so that prevalence estimates account for population growth and different population sizes of different groups.
The temporal trends from 1990 to 2019 were described using estimated annual percentage change (EAPC) and corresponding 95% confidence interval (95% CI) for global population and subgroups. Estimated Annual Percent Change, which approximates average annual percent change in ASRs during the study period, allows both an evaluation of trends over time as well as comparisons in the magnitude of change to the ASR among cohorts. For example an EAPC of -0.35 suggests that the ASR of that condition declines by approximately 0.35% per year over the course of the study period. EAPC was considered to be declining if the EAPC was negative and the 95% CI excluded 0.
Results
In the GBD the total worldwide number of patients with Chagas Disease decreased between 1990 and 2019 from 7,292,889 to 6,469,285, with a corresponding decrease in ASR from 145.07 (126.74–165.59) to 79.86 (69.88–91.02).
During that period, the total number of CCM cases increased from 220,166 to 283,236 individuals, with a decline in the ASR from 5.23 (3.34–7.47) to 3.42 (2.2–4.91) per 1,00,000 individuals (Table 1). In 2019, the burden was highest in individuals over age 70 compared to younger individuals and in males compared to females. Among available geographic classifications in 2019 where CCM was noted, Latin American regions had the highest rates (ASR of 39.49–61.15/100,000), while high income North American and Western European regions had lower rates (ASRs of 0.67 and 0.34/100,000 respectively), (Table 1). The 2019 ASR for the United States was 0.71/100,000. Between 1990 and 2019, the worldwide prevalence of CCM decreased with an EAPC of -0.35 (-0.37 to -0.32), with similar trends seen among different age groups and between males and females. Declines in EAPC were also noted for Latin American regions and high income North American countries, while the EAPC increased in Western Europe and High-income Asia Pacific. The trends in ASRs and EAPCs of CCM during the study period mirrored those of Chagas Disease overall from the GBD, which saw ASRs decrease from 145.07 (126.74 to 165.59) to 79.86 (69.88 to 91.02), with an EAPC of -0.45 (−0.47 to −0.43). Among 204 countries studied in the GBD, the ASRs for the 51 countries with a detectable prevalence of CCM in 2019 are displayed in Table 2.
Table 1.
Prevalence, Age Standardized Rates, and Estimated Annual Percent Change in Chagas Cardiomyopathy
| 1990 | 2019 | 1990 | 2019 | 1990-2019 | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Number | 95% UI | Number | 95% UI | ASR | 95% UI | ASR | 95% UI | EAPC | 95% CI | ||||||
| Global | 220166 | 139752 | 315866 | 283236 | 181832 | 407165 | 5.23 | 3.34 | 7.47 | 3.42 | 2.2 | 4.91 | −0.35 | −0.37 | −0.32 |
| Age groups | |||||||||||||||
| 25-49 years | 82584 | 50994 | 122854 | 84705 | 52216 | 126847 | 4.86 | 3 | 7.23 | 3.12 | 1.92 | 4.67 | −0.36 | −0.38 | −0.33 |
| 50-69 years | 92358 | 59040 | 131759 | 127459 | 82264 | 183234 | 13.54 | 8.66 | 19.32 | 9.24 | 5.97 | 13.29 | −0.32 | −0.34 | −0.29 |
| 70+ years | 45224 | 30464 | 62006 | 71072 | 48034 | 97716 | 22.44 | 15.12 | 30.76 | 15.33 | 10.36 | 21.07 | −0.32 | −0.35 | −0.29 |
| Sex | |||||||||||||||
| Male | 142482 | 96950 | 194620 | 185477 | 126543 | 252930 | 7.15 | 4.91 | 9.68 | 4.67 | 3.2 | 6.35 | −0.35 | −0.37 | −0.32 |
| Female | 77684 | 43701 | 123586 | 97759 | 55500 | 155060 | 3.56 | 2 | 5.65 | 2.27 | 1.29 | 3.6 | −0.36 | −0.39 | −0.33 |
| SDI | |||||||||||||||
| High SDI | 3149 | 2004 | 4521 | 3761 | 2422 | 5393 | 0.32 | 0.2 | 0.46 | 0.25 | 0.16 | 0.36 | −0.23 | −0.26 | −0.19 |
| High-middle SDI | 89955 | 57869 | 128635 | 76580 | 49799 | 109055 | 8.23 | 5.31 | 11.76 | 3.87 | 2.51 | 5.52 | −0.53 | −0.55 | −0.51 |
| Middle SDI | 68859 | 43323 | 99626 | 118561 | 75872 | 170684 | 6.16 | 3.93 | 8.86 | 4.64 | 2.99 | 6.64 | −0.25 | −0.27 | −0.22 |
| Low SDI | 1486 | 939 | 2165 | 3075 | 1958 | 4526 | 0.58 | 0.37 | 0.84 | 0.56 | 0.36 | 0.81 | −0.04 | −0.12 | 0.06 |
| Low-middle SDI | 56711 | 35908 | 81969 | 81252 | 52212 | 116543 | 8.67 | 5.55 | 12.42 | 5.61 | 3.64 | 8.02 | −0.35 | −0.38 | −0.32 |
| Regions | |||||||||||||||
| Endemic Regions | |||||||||||||||
| Southern Latin America | 71250 | 46178 | 101313 | 48812 | 32000 | 68694 | 153.25 | 99.36 | 217.85 | 61.15 | 40.05 | 86.16 | −0.6 | −0.62 | −0.58 |
| Andean Latin America | 28915 | 18235 | 41644 | 32161 | 20744 | 46548 | 125.46 | 79.6 | 179.58 | 55.03 | 35.57 | 79.49 | −0.56 | −0.59 | −0.54 |
| Tropical Latin America | 62080 | 39374 | 90263 | 100155 | 64247 | 145470 | 60.06 | 38.42 | 86.73 | 40.15 | 25.78 | 58.31 | −0.33 | −0.36 | −0.3 |
| Central Latin America | 54182 | 33871 | 78296 | 96284 | 61396 | 137715 | 57.51 | 36.34 | 82.49 | 39.49 | 25.25 | 56.38 | −0.31 | −0.34 | −0.29 |
| Non-Endemic Regions | |||||||||||||||
| High-income North America | 2699 | 1717 | 3885 | 3396 | 2185 | 4873 | 0.84 | 0.53 | 1.21 | 0.67 | 0.43 | 0.96 | −0.21 | −0.24 | −0.17 |
| Western Europe | 826 | 532 | 1172 | 2246 | 1444 | 3221 | 0.17 | 0.11 | 0.24 | 0.34 | 0.22 | 0.5 | 1.04 | 0.93 | 1.14 |
| Australasia | 116 | 74 | 164 | 65 | 42 | 94 | 0.52 | 0.33 | 0.73 | 0.16 | 0.1 | 0.23 | −0.69 | −0.71 | −0.66 |
| Caribbean | 81 | 53 | 116 | 79 | 51 | 112 | 0.3 | 0.2 | 0.43 | 0.15 | 0.1 | 0.22 | −0.49 | −0.52 | −0.45 |
| High-income Asia Pacific | 17 | 11 | 24 | 38 | 25 | 55 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.02 | 0.51 | 0.38 | 0.65 |
UI Uncertainty Interval, CI Confidence Interval, ASR Age standardized rate per 100,000 population, EAPC Estimated annual percent change, SDI socio-demographic index. Regional groups were defined based on Global Burden of Disease classification. Age groups are not age-standardized. Prevalence reported as 0 in 25–29 year age-group. Other geographic regions had no estimated prevalence of Chagas Cardiomyopathy (estimated prevalence of 0)
Table 2.
Age standardized rates (ASR) of Prevalence per 1,00,000 Population for Chagas Cardiomyopathy in 2019
| Country | ASR | 95% IU | |
|---|---|---|---|
| Bolivia | 185.65 | 118.3 | 267.95 |
| Venezuela | 77.95 | 50.67 | 108.51 |
| Chile | 65.94 | 43.32 | 92.72 |
| Argentina | 61.43 | 39.5 | 87.86 |
| Mexico | 45.13 | 28.69 | 64.86 |
| Honduras | 41.03 | 26.44 | 58.44 |
| Brazil | 40.48 | 26 | 58.83 |
| Ecuador | 32.56 | 20.73 | 47.16 |
| Uruguay | 32.21 | 20.33 | 45.81 |
| Guatemala | 31.81 | 20.44 | 46.03 |
| Nicaragua | 30.27 | 19.96 | 43.52 |
| Peru | 28.08 | 18.28 | 40.76 |
| Paraguay | 26.36 | 16.95 | 37.95 |
| El Salvador | 25.29 | 15.94 | 36.52 |
| Panama | 24.28 | 15.5 | 34.86 |
| Costa Rica | 21.12 | 13.22 | 30.36 |
| Colombia | 11.69 | 7.63 | 16.95 |
| Spain | 2.05 | 1.31 | 2.98 |
| Belize | 0.85 | 0.52 | 1.29 |
| Grenada | 0.76 | 0.34 | 1.41 |
| Guyana | 0.74 | 0.45 | 1.13 |
| United States of America | 0.71 | 0.45 | 1.02 |
| Andorra | 0.64 | 0.34 | 1.13 |
| Puerto Rico | 0.49 | 0.31 | 0.71 |
| Israel | 0.46 | 0.29 | 0.67 |
| Italy | 0.45 | 0.28 | 0.65 |
| Suriname | 0.4 | 0.24 | 0.62 |
| Dominican Republic | 0.38 | 0.24 | 0.55 |
| Switzerland | 0.37 | 0.23 | 0.54 |
| Sweden | 0.34 | 0.21 | 0.49 |
| Canada | 0.3 | 0.19 | 0.43 |
| Portugal | 0.22 | 0.14 | 0.31 |
| Australia | 0.19 | 0.12 | 0.28 |
| Ireland | 0.15 | 0.1 | 0.23 |
| Antigua and Barbuda | 0.1 | 0.05 | 0.21 |
| Trinidad and Tobago | 0.1 | 0.05 | 0.16 |
| Netherlands | 0.09 | 0.05 | 0.12 |
| Denmark | 0.08 | 0.05 | 0.12 |
| Bahamas | 0.07 | 0.03 | 0.12 |
| France | 0.06 | 0.04 | 0.09 |
| Saint Lucia | 0.05 | 0.01 | 0.14 |
| Austria | 0.05 | 0.03 | 0.07 |
| Luxembourg | 0.03 | 0.01 | 0.07 |
| Iceland | 0.03 | 0.01 | 0.08 |
| Japan | 0.02 | 0.01 | 0.03 |
| Dominica | 0.02 | 0 | 0.12 |
| Germany | 0.02 | 0.02 | 0.04 |
| Cuba | 0.01 | 0 | 0.01 |
| Barbados | 0.01 | 0.01 | 0.01 |
| United Kingdom | 0.01 | 0 | 0.01 |
| Saint Vincent/Grenadines | 0.01 | 0.01 | 0.02 |
Discussion
Our results on the prevalence and trends of the global burden of CCM demonstrate several important findings. The prevalence of CCM is highest in endemic Chagas in Latin America, which have ASRs approximately 100 times higher than non-endemic regions, although the disease is also seen in North America, Europe, and other geographic locations worldwide. CCM is most prevalent in older individuals (over age 70) and more prevalent among males. Similar to global trends in the overall burden of Chagas disease, the burden of CCM is decreasing worldwide, although regional variability is noted. These results highlight the ongoing public health burden associated with CCM.
The current analysis expands on prior data about the prevalence of CCM. Prior to this analysis, there were limited data on worldwide prevalence and individual country prevalence outside of Latin America, including in the United States [2]. Additionally, there have been limited data regarding the trends in CCM. The current analysis confirms that CCM trends appear to mirror the previously reported declining prevalence of Chagas disease. The declining prevalence of Chagas disease has been attributed to multiple factors including improved screening of blood transfusion and vector control in endemic regions [7] with programs like the Southern Cone initiative and the Central American Initiative (IPCA), and initiatives to reduce maternal fetal transmission such as elimination of mother-to-child transmission (EMTCT) Plus. In addition, both the national and international level programs have been formalized to support diagnosis and treatment of individuals with Chagas disease, for example the Bolivian Chagas Platform and the National Chagas Program in Colombia.
The GBD prevalence data presented here need to be viewed in context of other prevalence estimates, including those that have described significantly higher prevalence of CCM in the US [8]. There may be various reasons for differences in prevalence estimates across studies and these differences may in part relate to underdiagnosis of CCM. Both acute Chagas infection and cardiomyopathy may be asymptomatic and CCM may be misdiagnosed as cardiomyopathy of alternate etiology, which may affect regional prevalence estimates. Underdiagnosis may occur because of healthcare system resource limitations or differences in what is perceived as cardiomyopathy, and these factors for underestimation may have geographic variation. The prevalence of CCM may also be underestimated because CCM may present with sudden cardiac death [2]. Additionally, prevalence data remain dependent on different statistical modeling approaches, which may explain differences among datasets.
We also highlight that CCM is more prevalent in older individuals and among males. The higher burden of both Chagas disease and CCM, as well as higher rates of mortality in males, [9] have been previously reported. These may be attributed to greater comorbidity burden in males or due to sex-specific effects of Chagas disease on the heart as noted by differences in myocardial damage noted on cardiovascular magnetic resonance imaging [10]. Regarding observations based on age, older individuals may be more likely to be diagnosed with CCM because they may be more likely to seek health care in certain regions or because age-associated comorbidities contribute to the risks of CCM [11]. Regarding regional trends, we note that CCM appears to be decreasing globally, although geographic variation exists. Western Europe and High incomes Asia Pacific countries did not demonstrate the declines in ASRs over time that was noted in other countries, which may be due to differences in transmission and migration patterns or greater focus on cardiomyopathy diagnosis among high-risk populations; although these trends need to be interpreted with caution due to low disease prevalence in these regions.
This analysis has limitations. This analysis does not evaluate the mortality associated with CCM but rather focuses on the prevalence of CCM itself with the goal of estimating the prevalence of this key consequence of Chagas Disease. It is notable that the prevalence estimates of Chagas Disease and, by extension, CCM from the GBD database demonstrate variations when compared to other sources. This discrepancy raises concerns about the potential underestimation of Chagas Disease and CCM cases in the GBD data, which might affect the perceived extent of these conditions. However, the strength of the GBD dataset lies in its consistent and reliable methodological approach [1] applied across a wide, global cohort over an extended period. This uniformity enhances the reliability and comparability of the data, contributing to a more accurate analysis of both prevalence and trends of these conditions across multiple countries. Therefore, despite its limitations, the GBD dataset remains a crucial resource for understanding the global patterns of Chagas Disease and CCM, offering significant insights for global health research and policymaking. Furthermore, it is important to collect consistent epidemiological data on understudied conditions such as Chagas Disease and CCM. Additional systemic public health efforts regarding Chagas Disease and CCM surveillance both in endemic regions and non-endemic regions will therefore be important to reduce collection bias and optimize future prevalence estimates.
In conclusion, this analysis from the GBD provides a comprehensive overview of the global and country-specific prevalence, along with trends, of CCM. CCM is most prevalent in Latin American countries, yet its presence is notable worldwide. Notably, the global prevalence of CCM is in decline, mirroring the trends observed in Chagas disease prevalence. These findings hold significant implications for public health initiatives. They underscore the necessity for targeted efforts to effectively characterize, prevent, and manage CCM on a global scale.
Author contributions
AMKM and DA conceptualized the idea. AMKM performed data analyses. AMKM, RM, and DA wrote the initial draft of the manuscript. SSV, MDS, JRM, EVE, and JTA critically reviewed the manuscript and modified portions of the manuscript. All authors reviewed the manuscript.
Funding
Open access funding provided by SCELC, Statewide California Electronic Library Consortium.
Data availability
The data are publicaly available.
Declarations
Conflict of interest
The authors declare no competing interests.
References
- 1.Gómez-Ochoa SA, Rojas LZ, Echeverría LE, Muka T, Franco OH. Global, regional, and national trends of Chagas disease from 1990 to 2019: comprehensive analysis of the global burden of disease study. Glob Heart. 2022;17(1):59. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Nunes MCP, Beaton A, Acquatella H, Bern C, Bolger AF, Echeverria LE, Dutra WO, Gascon J, Morillo CA, Oliveira-Filho J. Chagas cardiomyopathy: an update of current clinical knowledge and management: a scientific statement from the American Heart Association. Circulation. 2018;138:e169–209. [DOI] [PubMed] [Google Scholar]
- 3.Chadalawada S, Sillau S, Archuleta S, Mundo W, Bandali M, Parra-Henao G, Rodriguez-Morales AJ, Villamil-Gomez WE, Suárez JA, Shapiro L. Risk of chronic cardiomyopathy among patients with the acute phase or indeterminate form of Chagas disease: a systematic review and meta-analysis. JAMA Netw Open. 2020;3:e2015072–e2015072. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Chadalawada S, Rassi A Jr, Samara O, Monzon A, Gudapati D, Vargas Barahona L, Hyson P, Sillau S, Mestroni L, Taylor M. Mortality risk in chronic Chagas cardiomyopathy: a systematic review and meta-analysis. ESC Heart Fail. 2021;8:5466–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Salerno PR, Chen Z, Wass S, Motairek I, Elamm C, Salerno LM, Hassani NS, Deo SV, Al-Kindi SG. Sex-specific heart failure burden across the United States: Global burden of disease 1990–2019. Am Heart J. 2024;269:35–44. [DOI] [PubMed] [Google Scholar]
- 6.Yan T, Zhu S, Yin X, Xie C, Xue J, Zhu M, Weng F, Zhu S, Xiang B, Zhou X. Burden, trends, and inequalities of heart failure globally, 1990 to 2019: a secondary analysis based on the global burden of disease 2019 study. J Am Heart Assoc. 2023;12:e027852. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Dias JCP. Evolution of Chagas disease screening programs and control programs: historical perspective. Glob Heart. 2015;10:193–202. [DOI] [PubMed] [Google Scholar]
- 8.Irish A, Whitman JD, Clark EH, Marcus R, Bern C. Updated estimates and mapping for prevalence of Chagas disease among adults United States. Emerg Infect Dis. 2022;28:1313. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Mansur AP, Pereira-Barretto AC, Del Carlo CH, Ianni BM, Avakian SD, Gonçalinho GH, Nakagawa NK, César LA, Bocchi EA. Sex differences in prognosis of heart failure due to chronic chagas cardiomyopathy. JACC Heart Fail. 2023;11(9):1284-1286. [DOI] [PubMed] [Google Scholar]
- 10.Assunção AN, Jerosch-Herold M, Melo RL, Mauricio AV, Rocha L, Torreão JA, Fernandes F, Ianni BM, Mady C, Ramires JA. Chagas’ heart disease: gender differences in myocardial damage assessed by cardiovascular magnetic resonance. J Cardiovasc Magn Reson. 2017;18:1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Pereira LD, Freitas EC, Fidalgo AS, Andrade MC, Candido DD, Silva Filho JD, Michailowsky V, Oliveira MD, Queiroz JA. Clinical and epidemiological profile of elderly patients with Chagas disease followed between 2005–2013 by pharmaceutical care service in Ceará State Northeastern Brazil. Revista do Instituto de Medicina Tropical de São Paulo. 2015;57:145–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data are publicaly available.
