ArticleThe American journal of tropical medicine and hygiene2015
Exploring the contribution of host susceptibility to epidemiological patterns of Schistosoma japonicum infection using an individual-based model.
Article in The American journal of tropical medicine and hygiene, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Identification of optimum scopes of environmental drivers for schistosome-transmittingParasitology · 2024Article
- Revisiting the impact of Schistosoma mansoni regulating mechanisms on transmission dynamics using SchiSTOP, a novel modelling framework.PLoS neglected tropical diseases · 2024Article
- SCHISTOX: An individual based model for the epidemiology and control of schistosomiasis.Infectious Disease Modelling · 2021Article
- Modelling exposure heterogeneity and density dependence in onchocerciasis using a novel individual-based transmission model, EPIONCHO-IBM: Implications for elimination and data needs.PLoS neglected tropical diseases · 2019Article
- Opportunities and challenges for modelling epidemiological and evolutionary dynamics in a multihost, multiparasite system: Zoonotic hybrid schistosomiasis in West Africa.Evolutionary applications · 2018Article
- Exposure versus Susceptibility as Alternative Bases for New Approaches to Surveillance for Schistosoma japonicum in Low Transmission Environments.PLoS neglected tropical diseases · 2016Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
We recently reported the analysis of epidemiological data suggesting variability in individual susceptibility to infection by Schistosoma japonicum among rural villagers who reside in Sichuan Province of southwestern China. By supplementing the data used in the earlier analysis from other studies we have reported from this region, we presented improved estimates of cercarial exposure, which in turn, result in stronger evidence of susceptibility. This analysis was conducted using an individual-based mathematical model (IBM) whose use was motivated by the nature and extent of field data from the low-transmission environments exemplified by one of our datasets and typical of the current situation in most endemic areas of China. In addition to individual susceptibility and water contact, the model includes stochastic aspects of cercarial exposure as well as of diagnostic procedures, the latter being particularly relevant to the low-transmission environment. The simulation studies show that, to produce key aspects of the epidemiological findings, the distribution of susceptibility ranges over several orders of magnitude and is highly right skewed. We found no compelling evidence that the distribution of susceptibility differed between the two populations that underlie both the epidemiological and simulation results.
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