Diseases (Oct 2022)

Spatial Analysis of Schistosomiasis in Hunan and Jiangxi Provinces in the People’s Republic of China

  • Kefyalew Addis Alene,
  • Catherine A. Gordon,
  • Archie C. A. Clements,
  • Gail M. Williams,
  • Darren J. Gray,
  • Xiao-Nong Zhou,
  • Yuesheng Li,
  • Jürg Utzinger,
  • Johanna Kurscheid,
  • Simon Forsyth,
  • Jie Zhou,
  • Zhaojun Li,
  • Guangpin Li,
  • Dandan Lin,
  • Zhihong Lou,
  • Shengming Li,
  • Jun Ge,
  • Jing Xu,
  • Xinling Yu,
  • Fei Hu,
  • Shuying Xie,
  • Donald P. McManus

DOI
https://doi.org/10.3390/diseases10040093
Journal volume & issue
Vol. 10, no. 4
p. 93

Abstract

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Understanding the spatial distribution of schistosome infection is critical for tailoring preventive measures to control and eliminate schistosomiasis. This study used spatial analysis to determine risk factors that may impact Schistosoma japonicum infection and predict risk in Hunan and Jiangxi Provinces in the People’s Republic of China. The study employed survey data collected in Hunan and Jiangxi in 2016. Independent variable data were obtained from publicly available sources. Bayesian-based geostatistics was used to build models with covariate fixed effects and spatial random effects to identify factors associated with the spatial distribution of infection. Prevalence of schistosomiasis was higher in Hunan (12.8%) than Jiangxi (2.6%). Spatial distribution of schistosomiasis varied at pixel level (0.1 × 0.1 km), and was significantly associated with distance to nearest waterbody (km, β = −1.158; 95% credible interval [CrI]: −2.104, −0.116) in Hunan and temperature (°C, β = −4.359; 95% CrI: −9.641, −0.055) in Jiangxi. The spatial distribution of schistosomiasis in Hunan and Jiangxi varied substantially and was significantly associated with distance to nearest waterbody. Prevalence of schistosomiasis decreased with increasing distance to nearest waterbody in Hunan, indicating that schistosomiasis control should target individuals in close proximity to open water sources as they are at highest risk of infection.

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