Towards eradicating the tropical disease schistosomiasis – integrative mathematical and statistical modeling combining intrinsic and extrinsic parameters

Schistosomiasis poses a significant public health threat in Sub-Saharan Africa, particularly affecting impoverished rural communities. This disease is predominantly caused by S. mansoni and S. haematobium parasites, transmitted by freshwater snails of the Biomphalaria and Bulinus species. East Africa, characterized by densely populated rural areas, bears the highest disease burden within the region, with specific hotspots identified in Uganda, Kenya, and Tanzania. Various factors, including climatic variability, geographical features, environmental/habitat suitability, biodiversity, and anthropogenic influences, influence the distribution patterns of intermediate host (IH) snails and schistosomiasis transmission across different geographic scales. The new WHO roadmap emphasizes a One Health approach, recommending targeted snail control and alternative methods. However, limited knowledge exists about the determinants of community structure of the two genera and their role in schistosomiasis transmission, prevalence, and distribution under various scenarios, such as climatic variability in East Africa. This study reveals significant extrinsic parameters influencing the distribution of IH snails at both local (Western Uganda) and regional (East Africa) geographical scales, using Random forest, a machine learning technique. On a smaller scale, geography, diversity of the associated mollusk fauna, and climate emerged as important predictors for the presence of Biomphalaria, whereas mollusk diversity, water chemistry, and geography primarily controlled the occurrence of Bulinus. Mollusk diversity and geography were found to be relevant for the presence of both genera combined. On a regional scale, the results indicated geography and climate as primary factors for Biomphalaria, while Bulinus occurrence was additionally influenced by soil clay content and nitrogen concentration. These parameters signify the processes involved in meta-community assembly, encompassing factors like dispersal limitation, environmental filtering, and biotic interactions that influence the establishment of genera. Furthermore, mathematical models were formulated to quantify the dynamics of schistosomiasis transmission, focusing on the role of IH and all stakeholders in transmission and management (climate variability and control strategies). Within East Africa, this study revealed varied incidence rates among countries based on temperature and rainfall patterns, characterized by seasonal schistosomiasis emergencies and re-emergences. Conditions with temperatures between 20-27°C and precipitation ranging from 5-140 mm were found to be conducive for schistosomiasis, while June and July marked a period with fewer reported cases, attributed to adverse temperatures around 26-30°C and lower precipitation levels (5.0 to 91.8 mm). Furthermore, Biomphalaria snails demonstrated higher population growth and susceptibility to infection than Bulinus snails, particularly below 25°C, with their populations declining above this temperature threshold and it is optimal for intensifying snail interventions. Expanding the scope, this study revealed that specific non-host competitor snails and predator behaviors such as attack and handling times, can directly control the population of IH snails. However, employing a singular snail competitor or predator alone did not achieve complete disease eradication, while their simultaneous application resulted in a significant decrease in the IH snail population. This reduction brought the reproductive number below unity, indicating the effectiveness of disease control measures. Moreover, model evaluating the individual and tiered impact of remaining control strategies in the current study, including chemotherapy, awareness programs, snail removal, and environmentally dependent chemical control, revealed that no single or combination of 2-3 tiered approaches could entirely eradicate schistosomiasis, except for a four-tiered strategy that integrates all assessed interventions. All work in this dissertation contributes to a better understanding of the community structure of IH snails (where and why their distribution occurs) as well as the impact of climate variability, non-host snails, and predators, as well as evaluating the effectiveness of all stakeholders. It enables the optimization of resources, adaptation of interventions, and supports evidence-based decision-making, fostering community trust.

Collections

Dissertationen/Habilitationen

Full item page

Towards eradicating the tropical disease schistosomiasis – integrative mathematical and statistical modeling combining intrinsic and extrinsic parameters

Files

Date

Authors

Advisors/Reviewers

Further Contributors

Contributing Institutions

Publisher

Journal Title

Journal ISSN

Volume Title

Publisher

License

Quotable link

Abstract

Link to publications or other datasets

Description

Notes

Original publication in

Original publication in

Anthology

Collections

URI of original publication

Forschungsdaten

Series

Citation