Research Article

A new approach to modelling schistosomiasis transmission based on stratified worm burden

D. GURARIEa1 c1, C. H. KINGa2 and X. WANGa1

a1 Department of Mathematics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, Ohio 44106 USA

a2 Center for Global Health and Diseases, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, Ohio 44106 USA


Background/Objective. Multiple factors affect schistosomiasis transmission in distributed meta-population systems including age, behaviour, and environment. The traditional approach to modelling macroparasite transmission often exploits the ‘mean worm burden’ (MWB) formulation for human hosts. However, typical worm distribution in humans is overdispersed, and classic models either ignore this characteristic or make ad hoc assumptions about its pattern (e.g., by assuming a negative binomial distribution). Such oversimplifications can give wrong predictions for the impact of control interventions. Methods. We propose a new modelling approach to macro-parasite transmission by stratifying human populations according to worm burden, and replacing MWB dynamics with that of ‘population strata’. We developed proper calibration procedures for such multi-component systems, based on typical epidemiological and demographic field data, and implemented them using Wolfram Mathematica. Results. Model programming and calibration proved to be straightforward. Our calibrated system provided good agreement with the individual level field data from the Msambweni region of eastern Kenya. Conclusion. The Stratified Worm Burden (SWB) approach offers many advantages, in that it accounts naturally for overdispersion and accommodates other important factors and measures of human infection and demographics. Future work will apply this model and methodology to evaluate innovative control intervention strategies, including expanded drug treatment programmes proposed by the World Health Organization and its partners.

(Received January 19 2010)

(Revised March 17 2010)

(Revised April 21 2010)

(Accepted April 22 2010)

(Online publication July 13 2010)