ArticleInfectious diseases of poverty2017
Pattern analysis of schistosomiasis prevalence by exploring predictive modeling in Jiangling County, Hubei Province, P.R. China.
Article in Infectious diseases of poverty, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 23 citations in OpenAlex.
- Effect of Health Education on Schistosomiasis Control Knowledge, Attitude, and Practice after Schistosomiasis Blocking: Results of a Longitudinal Observational Study in the Field.Tropical medicine and infectious disease · 2023Article
- Spatiotemporal distribution of schistosomiasis transmission risk in Jiangling County, Hubei Province, P.R. China.PLoS neglected tropical diseases · 2023Article
- Life expectancy and healthy life expectancy of patients with advanced schistosomiasis in Hunan Province, China.Infectious diseases of poverty · 2023Article
- A Proposed Framework for Early Prediction of Schistosomiasis.Diagnostics (Basel, Switzerland) · 2022Article
- Asian Schistosomiasis: Current Status and Prospects for Control Leading to Elimination.Tropical medicine and infectious disease · 2019Review
- Role of ecological approaches to eliminating schistosomiasis in Eryuan County evaluated by system modelling.Infectious diseases of poverty · 2018Article
- Integrating ecological approaches to interrupt schistosomiasis transmission: opportunities and challenges.Infectious diseases of poverty · 2018Article
- The Spatial-Temporal Trend Analysis of Schistosomiasis from 1997 to 2010 in Anhui Province, Eastern China.The American journal of tropical medicine and hygiene · 2018Article
- Elimination of schistosomiasis: the tools required.Infectious diseases of poverty · 2017Article
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10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe prevalence of schistosomiasis remains a key public health issue in China. Jiangling County in Hubei Province is a typical lake and marshland endemic area. The pattern analysis of schistosomiasis prevalence in Jiangling County is of significant importance for promoting schistosomiasis surveillance and control in the similar endemic areas.
methodsThe dataset was constructed based on the annual schistosomiasis surveillance as well the socio-economic data in Jiangling County covering the years from 2009 to 2013. A village clustering method modified from the K-mean algorithm was used to identify different types of endemic villages. For these identified village clusters, a matrix-based predictive model was developed by means of exploring the one-step backward temporal correlation inference algorithm aiming to estimate the predicative correlations of schistosomiasis prevalence among different years. Field sampling of faeces from domestic animals, as an indicator of potential schistosomiasis prevalence, was carried out and the results were used to validate the results of proposed models and methods.
resultsThe prevalence of schistosomiasis in Jiangling County declined year by year. The total of 198 endemic villages in Jiangling County can be divided into four clusters with reference to the 5 years' occurrences of schistosomiasis in human, cattle and snail populations. For each identified village cluster, a predictive matrix was generated to characterize the relationships of schistosomiasis prevalence with the historic infection level as well as their associated impact factors. Furthermore, the results of sampling faeces from the front field agreed with the results of the identified clusters of endemic villages.
conclusionThe results of village clusters and the predictive matrix can be regard as the basis to conduct targeted measures for schistosomiasis surveillance and control. Furthermore, the proposed models and methods can be modified to investigate the schistosomiasis prevalence in other regions as well as be used for investigating other parasitic diseases.
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