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The human-snail transmission environment shapes long term schistosomiasis control outcomes: Implications for improving the accuracy of predictive modeling

Author

Listed:
  • David Gurarie
  • Nathan C Lo
  • Martial L Ndeffo-Mbah
  • David P Durham
  • Charles H King

Abstract

Introduction: Schistosomiasis is a chronic parasitic trematode disease that affects over 240 million people worldwide. The Schistosoma lifecycle is complex, involving transmission via specific intermediate-host freshwater snails. Predictive mathematical models of Schistosoma transmission have often chosen to simplify or ignore the details of environmental human-snail interaction in their analyses. Schistosome transmission models now aim to provide better precision for policy planning of elimination of transmission. This heightens the importance of including the environmental complexity of vector-pathogen interaction in order to make more accurate projections. Methodology and principal findings: We propose a nonlinear snail force of infection (FOI) that takes into account an intermediate larval stage (miracidium) and snail biology. We focused, in particular, on the effects of snail force of infection (FOI) on the impact of mass drug administration (MDA) in human communities. The proposed (modified) model was compared to a conventional model in terms of their predictions. A longitudinal dataset generated in Kenya field studies was used for model calibration and validation. For each sample community, we calibrated modified and conventional model systems, then used them to model outcomes for a range of MDA regimens. In most cases, the modified model predicted more vigorous post-MDA rebound, with faster relapse to baseline levels of infection. The effect was pronounced in higher risk communities. When compared to observed data, only the modified system was able to successfully predict persistent rebound of Schistosoma infection. Conclusion and significance: The observed impact of varying location-specific snail inputs sheds light on the diverse MDA response patterns noted in operational research on schistosomiasis control, such as the recent SCORE project. Efficiency of human-to-snail transmission is likely to be much higher than predicted by standard models, which, in practice, will make local elimination by implementation of MDA alone highly unlikely, even over a multi-decade period. Author summary: Infection with blood fluke Schistosoma parasites is a major cause of disease burden around the world. Control of schistosomiasis, which is transmitted through intermediate host freshwater snails, is a priority for national and global health programs working in at-risk regions of Africa, the Mideast, Asia, the Philippines, and South America. Program planning often relies on mathematical models to project the impact of different schedules of mass drug administration (MDA) of the anti-schistosomal drug, praziquantel, in these areas. In practice, though, recent projections of standard models have failed to capture the variability of MDA program impact on community levels of infection, especially in high-risk zones. In the present study, we developed a modification of the conventional modeling approach that takes more detailed account of human-to-snail transmission. Inclusion of a revised, nonlinear form for the model’s snail infection function had profound effects on long term predictions of the impact of MDA programs for Schistosoma control. In specific, our proposed snail parameters helped to explain the persistent rebound of Schistosoma prevalence in certain high risk communities. The efficiency of human-to-snail transmission is likely to be much higher than predicted in standard models, which makes local elimination by implementation of MDA, alone, highly unlikely.

Suggested Citation

  • David Gurarie & Nathan C Lo & Martial L Ndeffo-Mbah & David P Durham & Charles H King, 2018. "The human-snail transmission environment shapes long term schistosomiasis control outcomes: Implications for improving the accuracy of predictive modeling," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 12(5), pages 1-19, May.
  • Handle: RePEc:plo:pntd00:0006514
    DOI: 10.1371/journal.pntd.0006514
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