Modelling local areas of exposure to Schistosoma japonicum in a limited survey data environment

Abstract

BackgroundSpatial modelling studies of schistosomiasis (SCH) are now commonplace. Covariate values are commonly extracted at survey locations, where infection does not always take place, resulting in an unknown positional exposure mismatch. The present research aims to: (i) describe the nature of the positional exposure mismatch in modelling SCH helminth infections; (ii) delineate exposure areas to correct for such positional mismatch; and (iii) validate exposure areas using human positive cases.MethodsTo delineate exposure areas to Schistosoma japonicum, a spatial Bayesian network (sBN) was constructed. It uses data on exposure risk factors such as: potential sites for snails’ accessibility, geographical distribution of snail infection rate, and cost of the community to access nearby water bodies. Prior and conditional probabilities were obtained from the literature and inserted as weights based on their relative contribution to exposure; these probabilities were then used to calculate joint probabilities of exposure within the sBN.ResultsHigh values of probability of S. japonicum exposure correspond to polygons where snails could potentially be present, for instance in wet soils and areas with low slopes, but also where people can easily access water bodies. Low correlation (R2 = 0.3) was found between the percentage of human cases and the delineated probabilities of exposure when validation buffers are generated over the human cases.ConclusionsThe utility of a probabilistic method for the identification of exposure areas for S. japonicum, with wider application for other water-borne infections, was demonstrated. From a public health perspective, the schistosomiasis exposure sBN developed in this study could be used to guide local schistosomiasis control teams to specific potential areas of exposure, and improve efficiency of mass drug administration campaigns in places where people are likely to be exposed to the infection.Electronic supplementary materialThe online version of this article (10.1186/s13071-018-3039-6) contains supplementary material, which is available to authorized users.

Analysis of CT characteristics in the diagnosis of Schistosoma japonicum associated appendicitis with clinical and pathological correlation: a diagnostic accuracy study

“…Schistosomiasis or bilharziasis is a chronic debilitating parasitic infection caused by Schistosoma japonicum, a trematode that is still highly prevalent as intestinal schistosomiasis in Asian countries [1]. It is also considered as the second most socioeconomically devastating condition after malaria by the World Health organization because of its high prevalence in Africa and the far east causing considerable mortality and morbidity [2,3]. Especially in China, S. japonicum has reached a criterion of elimination, as well as, transmission interruption statuses with greater efforts [4], yet it remains a major health problem in the endemic villages of many provinces connected along Yellow river and Yangtze-Jiang basins [5,6].…”

Odds, challenges and new approaches in the control of helminthiasis, an Asian study

“…Complementing the eDNA approach is the utilization of probabilistic methods to identify potential risk areas for humans against exposure to S. japonicum . One such method, developed by Araujo Navas et al (Araujo Navas et al, 2018), was based on a spatial Bayesian Network (sBN) analysis and used exposure risk factors to humans that include potential snail sites, geographical distribution of snail sites with different snail infection rates, and the cost for communities to access water bodies. They used data on schistosomiasis cases, which include actual household locations, and snail infection prevalence collected from three barangays from Alangalang, Leyte in 2015 and 2016.…”

A Place-Based Conceptual Model (PBCM) of Neotricula aperta/Schistosoma mekongi habitat before and after dam construction in the Lower Mekong River

“…mekongi . The schistosomiasis exposure sBN could be used by local disease control teams to identify areas of exposure and improve the efficiency of mass drug administration [ 71 ]. A study to address how snail hosts and their interaction with S .…”

“…The PBCM could be the basis to develop a similar model for S. mekongi. The schistosomiasis exposure sBN could be used by local disease control teams to identify areas of exposure and improve the efficiency of mass drug administration [71]. A study to address how snail hosts and their interaction with S. mansoni influence model predictions indicates that model outputs, such as schistosome prevalence in human and snail populations, respond to the inclusion of snail age structure [72].…”