A quantitative framework for a multi-group model of Schistosomiasis japonicum transmission dynamics and control in Sichuan, China.
A quantitative framework is presented for the site-specific characterization of schistosomiasis transmission with the object of developing local control strategies. Central to the framework is a worm-burden model using ordinary differential equations of disease transmission in risk groups defined by residence and occupation. The model incorporates temperature- and precipitation-dependent seasonality of infectious stages, snail population dynamics, and seasonal patterns of human water contact specific to the local agricultural setting. The model's parameters are separated into two main subsets, those associated with the general biology of the parasite and its life cycle in the human and the snail and those associated with directly measurable features of disease status in the local population or relevant aspects of the local environment. In this regard, the model is structured and parameterized to take maximum advantage of data that can be collected in rural China by conventional methods. For example, it includes a statistical model for egg excretion to the environment by each risk group which is based on local population surveys of the prevalence and intensity of infection. The second element of the framework of analysis relates to the strategy for parameter estimation and calibration to local conditions. We propose a Bayesian approach in which parameter estimates are refined over time by methods employing extensive computer simulations. An early analysis of data collected between 1987 and 1989 in endemic villages near Xichang City in southwestern Sichuan provides encouragement that parametric uncertainty can be reduced to levels adequate to explore effective control strategies.
Liang
Song
S
School of Public Health, Center for Occupational and Environmental Health, University of California, Berkeley, CA 94720-7360, USA.
Maszle
Don
D
Spear
Robert C
RC
D000818:Animals; D001499:Bayes Theorem; D002681:China; D003198:Computer Simulation; D005243:Feces / Q000469:parasitology; D006801:Humans; D008962:Models, Theoretical; D009010:Monte Carlo Method; D012307:Risk Factors; D012554:Schistosomiasis japonica / Q000517:prevention & control / Q000635:transmission; D012908:Snails / Q000469:parasitology*