Evidence map›Paper›PMID 40524274›Full record

ArticleInfectious diseases of poverty2025

Estimation and prediction on the economic burden of schistosomiasis in 25 endemic countries.

Xian-Fa Chen, Qin Li, Robert Bergquist, Jin-Xin Zheng, Su-Ying Guo, Qiu-Feng Lan, Zheng-Ze He, Li-Juan Zhang, Chun-Li Cao, Jing Xu and 1 more

Abstract read
In one paragraph

Article in Infectious diseases of poverty, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Xian-Fa ChenNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases; Key Laboratory On Parasite and Vector Biology, National Health Commission; WHO Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.
Qin LiNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases; Key Laboratory On Parasite and Vector Biology, National Health Commission; WHO Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.
Robert BergquistGeospatial Health, Ingerod, Brastad, Sweden.
Jin-Xin ZhengSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Su-Ying GuoNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases; Key Laboratory On Parasite and Vector Biology, National Health Commission; WHO Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.
Qiu-Feng LanNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases; Key Laboratory On Parasite and Vector Biology, National Health Commission; WHO Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.
Zheng-Ze HeNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases; Key Laboratory On Parasite and Vector Biology, National Health Commission; WHO Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.
Li-Juan ZhangNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases; Key Laboratory On Parasite and Vector Biology, National Health Commission; WHO Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.
Chun-Li CaoNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases; Key Laboratory On Parasite and Vector Biology, National Health Commission; WHO Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.
Jing XuNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases; Key Laboratory On Parasite and Vector Biology, National Health Commission; WHO Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China.
Xiao-Nong ZhouNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases; Key Laboratory On Parasite and Vector Biology, National Health Commission; WHO Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, 200025, China. zhouxn1@chinacdc.cn.ORCID http://orcid.org/0000-0003-1417-8427

Funding

National Key Research and Development Program of China 2021YFC2300803National Key Research and Development Program of China No. 2021YFC2300800National Natural Science Foundation of China No. 81973108
6 · The paper itself

Abstract

backgroundSchistosomiasis is a neglected tropical disease, primarily prevalent in tropical and subtropical regions. It imposes a significant health and economic burden in low- and middle-income countries, but a study of its comprehensive economic impact of the disease at the global level has not been carried out. As this is essential for evidence-based decision-making, this study aims to estimate the macroeconomic burden of schistosomiasis in 25 endemic countries.

methodsWe used a health-augmented macroeconomic (HAM) model, as well as observed data from 2010 to 2021 and projected data from 2022 to 2050, to model gross domestic product (GDP) under two scenarios: with and without schistosomiasis. The data were obtained from the Global Burden of Disease Study 2021 (GBD 2021), the World Bank database, the International Monetary Fund (IMF) database, the International Labour Organization (ILO) database, the United Nations Population Division's World Population Prospects 2022 database, the Barro-Lee Educational Attainment dataset, the Penn World Table (PWT) database, and relevant literature. The economic burden was quantified as the difference in GDP between these two scenarios. The HAM model considered: (i) the impact of schistosomiasis mortality and morbidity on labor supply; (ii) age and gender differences in education and work experience among schistosomiasis patients; and (iii) the impact of schistosomiasis treatment costs on physical capital accumulation. To be able to compare the purchasing power of different countries, we used international dollars (INT$), a hypothetical currency unit based on purchasing power parity.

resultsWe estimated the macroeconomic burden of schistosomiasis in 25 schistosomiasis endemic countries was INT$ 49,504 million [uncertainty interval (UI): 48,668-50,339] for the study period, using a 3% discount rate in the main analysis. The result implies that the economic burden of schistosomiasis across these 25 countries during study period is equivalent to 0.0174% (UI: 0.0171-0.0177) of total GDP. Among all schistosomiasis-endemic countries included, Egypt had the largest absolute economic burden (INT$ 11,400 million, UI: 11,221-11,578), followed by Brazil (INT$ 9779 million, UI: 9717-9841) and South Africa (INT$ 6744 million, UI: 6676-6811).

conclusionsThe global economic burden of schistosomiasis remains substantial and is inequitably distributed among countries and regions. Our study highlights the need for increased investment and global collaborative efforts to control schistosomiasis and its associated health and economic burdens. By advancing the elimination of schistosomiasis, substantial economic returns can be achieved.

Indexed as

Cost of IllnessEndemic DiseasesSchistosomiasisAdultFemaleGlobal HealthGross Domestic ProductHumansMaleMiddle AgedEconomic burdenEliminationEndemic countryGlobal burdenMacroeconomic modelSchistosomiasis

Identifiers

PMID40524274
PMCPMC12168328

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.