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A meta-analysis of infection rates of Schistosoma japonicum in sentinel mice associated with infectious waters in mainland China over last 40 years

Qiu, C. and Zou, H. Y. and Deng, Y. and Liang, Y. S. and Lu, D. B.

PLoS Negl Trop Dis (2019) 13: e0007475

DOI: 10.1371/journal.pntd.0007475

Abstract

BACKGROUND: Schistosomiasis japonica is a zoonotic parasitic disease. After nearly 70 years of control efforts in China, Schistosomiasis transmission has been reduced to a much lower level. The absence or near absence of infections in humans or livestock, based on traditional fecal and serological tests, has made the targets and priorities of future control efforts difficult to determine. However, detection of schistosome cercariae in waters using sentinel mice could be an alternative way of identifying remaining foci of infection, or even serve as a tool for evaluation of control efficacy. This method has been employed in China over last forty years. We therefore performed a meta-analysis of the relevant research to investigate if infections in sentinel mice mirror the ongoing trend of schistosomiasis transmission in China. METHODS: We conducted a meta-analysis of studies reporting infection rates of S. japonicum in sentinel mice in China before Sep 1, 2018 in accordance with the PRISMA guidelines. We retrieved all relative studies based on five databases (CNKI, WanFang, VIP, PubMed and Web of Science) and the reference lists of resulting articles. For each individual study, the infection rate in sentinel mice is presented together with its 95% confidence interval (CI). Point estimates of the overall infection rates and their 95% CIs were calculated. Subgroup analyses were performed according to study periods, seasons or regions. RESULTS: We identified 90 articles, including 290 studies covering eight endemic provinces. The overall rate in sentinel mice was 12.31% (95% CI: 10.14-14.65%) from 1980 to 2018. The value of 3.66% (95% CI: 2.62-4.85%) estimated in 2004 to 2018 was significantly lower than in 1980 to 2003 (22.96%, 95% CI: 19.25-26.89%). The estimate was significantly higher in the middle and lower reaches than in the upper reaches of the Yangtze River. The highest estimates were obtained in Hunan (30.11%, 95% CI: 25.64-34.77%) followed by Anhui (26.34%, 95% CI: 12.88-42.44%) and then Jiangxi (13.73%, 95% CI: 6.71-22.56%). Unlike the other provinces in the middle and lower reaches, no significant reduction was seen in Hubei after 2003. Even in Hubei two studies carried out after 2014 reported infections in sentinel mice, although no infected snails were reported across the province. Infections were most found in April (17.40%, 95% CI: 1.13-45.49%), July (24.98%, 95% CI: 15.64-35.62%) and October (17.08%, 95% CI 5.94-32.05%). High degrees of heterogeneity were observed. CONCLUSION: This meta-analysis provides a comprehensive analysis of schistosome infection in sentinel mice across China. The estimates largely mirror the ongoing trends of transmission in terms of periods and regions. Infections were most likely to occur in April, July and October. In areas where no infected snails were reported infections in sentinel mice were still observed. Due to the presence of snails and infected wildlife, detection of schistosomes in waters using such a highly sensitive method as the deployment of sentinel mice, remains of importance in schistosomiasis monitoring. We would suggest the current criteria for transmission interruption or elimination of schistosomiasis in China be adjusted by integrating the results of sentinel mice based surveys.

Citation

Qiu, C., Zou, H. Y., Deng, Y., Liang, Y. S., & Lu, D. B. (2019). A meta-analysis of infection rates of Schistosoma japonicum in sentinel mice associated with infectious waters in mainland China over last 40 years. PLoS Negl Trop Dis, 13(6), e0007475. https://doi.org/10.1371/journal.pntd.0007475 Animals, Humans, Mice, China/epidemiology, *Sentinel Surveillance, Schistosoma japonicum/growth & development/*isolation & purification, Schistosomiasis japonica/*epidemiology, Water/*parasitology

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