Schistosoma japonicum risk in Jiangsu province, People’s Republic of China: identification of a spatio-temporal risk pattern along the Yangtze River

  • Kun Yang Jiangsu Institute of Parasitic Diseases, Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, China.
  • Le-Ping Sun Jiangsu Institute of Parasitic Diseases, Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, China.
  • You-Sheng Liang Jiangsu Institute of Parasitic Diseases, Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, China.
  • Feng Wu Jiangsu Institute of Parasitic Diseases, Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, China.
  • Wei Li Jiangsu Institute of Parasitic Diseases, Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, China.
  • Jian-Feng Zhang Jiangsu Institute of Parasitic Diseases, Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, China.
  • Yi-Xin Huang Jiangsu Institute of Parasitic Diseases, Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, China.
  • De-Rong Hang Jiangsu Institute of Parasitic Diseases, Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, China.
  • Song Liang Department of Environmental and Global Health, College of Public Health and Health Professions, Emerging Pathogens Institute, University of Florida, Gainesville, United States.
  • Robert Bergquist Ingerod, Brastad, Sweden.
  • Xiao-Nong Zhou | ipdzhouxn@sh163.net National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, China.

Abstract

The risk for Schistosoma japonicum infection in Jiangsu province, People’s Republic of China, was investigated by a mouse bioassay. Various investigations were conducted in the period 2009-2011 with the presentation here representing the summary of the results from 45-50 sites in the marshlands along the Yangtze River’s course through the province. Indices representing three aspects of the infection were collected to assess risk: (i) the proportion of sentinel points where at least one mouse infection was recorded; (ii) the proportion of infected mice at each of these sites; and (iii) the average worm burdens. Directional distribution analysis and scan statistics were used to explore the spatio-temporal risk pattern. The spatial distribution was oriented along the Yangtze River and the directional distributions for the proportion of infected mice and mean worm burdens were similar for the positive sentinel sites. Four statistically significant clusters were detected in 2009, but only one in 2010 and 2011, respectively. Temporal windows for infection risk were seen in June and September. The study illustrates the utility of spatio-temporal analysis in assessing the risk for schistosomiasis. This approach should be useful with respect to surveillance and response that can be expected to be increasingly applied when moving from morbidity control to transmission control.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.
Published
2013-11-01
Info
Issue
Section
Original Articles
Keywords:
schistosomiasis, mice bioassays, spatio-temporal analysis, schistosomiasis transmission control, risk area, People’s Republic of China.
Statistics
  • Abstract views: 1472

  • PDF: 520
How to Cite
Yang, K., Sun, L.-P., Liang, Y.-S., Wu, F., Li, W., Zhang, J.-F., Huang, Y.-X., Hang, D.-R., Liang, S., Bergquist, R., & Zhou, X.-N. (2013). Schistosoma japonicum risk in Jiangsu province, People’s Republic of China: identification of a spatio-temporal risk pattern along the Yangtze River. Geospatial Health, 8(1), 133-142. https://doi.org/10.4081/gh.2013.61

Most read articles by the same author(s)

<< < 1 2 3 > >>