SCHISTOSIM: a microsimulation model for the epidemiology and control of schistosomiasis

S. J. De VlasCentre for Decision Sciences in Tropical Disease Control, Department of Public Health, Erasmus University Rotterdam, Rotterdam, The Netherlands; Department of Parasitology and Tropical Medicine, University of Leiden, Leiden, The Netherlands

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G. J. Van OortmarssenCentre for Decision Sciences in Tropical Disease Control, Department of Public Health, Erasmus University Rotterdam, Rotterdam, The Netherlands; Department of Parasitology and Tropical Medicine, University of Leiden, Leiden, The Netherlands

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B. GryseelsCentre for Decision Sciences in Tropical Disease Control, Department of Public Health, Erasmus University Rotterdam, Rotterdam, The Netherlands; Department of Parasitology and Tropical Medicine, University of Leiden, Leiden, The Netherlands

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A. M. PoldermanCentre for Decision Sciences in Tropical Disease Control, Department of Public Health, Erasmus University Rotterdam, Rotterdam, The Netherlands; Department of Parasitology and Tropical Medicine, University of Leiden, Leiden, The Netherlands

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A. P. PlaisierCentre for Decision Sciences in Tropical Disease Control, Department of Public Health, Erasmus University Rotterdam, Rotterdam, The Netherlands; Department of Parasitology and Tropical Medicine, University of Leiden, Leiden, The Netherlands

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J. D. F. HabbemaCentre for Decision Sciences in Tropical Disease Control, Department of Public Health, Erasmus University Rotterdam, Rotterdam, The Netherlands; Department of Parasitology and Tropical Medicine, University of Leiden, Leiden, The Netherlands

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A computer simulation model, SCHISTOSIM, has been developed for the epidemiology and control of schistosomiasis, based on the stochastic microsimulation technique. The eventual aim is to evaluate and predict the effects of different control strategies. In the current state of the model, human-, worm-, and infection-related aspects have been included. However, many others, including most transmission and transmission-related mechanisms, have yet to be modeled. By simulating a series of surveys and treatments in Burundi, short-term effects of this program were satisfactorily explained by the model. However, long-term predictions did not match the observed data. Possible extensions of the model to properly describe these effects are identified. The potential of SCHISTOSIM as a tool for the prediction of outcomes of alternative control strategies is illustrated and discussed.

Author Notes

Authors' addresses: S. J. De Vlas, G. J. Van Oortmarssen, A. P. Plaisier, and J. D. F. Habbema, Centre for Decision Sciences in Tropical Disease Control, Department of Public Health, Room Ee-2042, Erasmus University Rotterdam, PO Box 1738, 3000 DR Rotterdam, The Netherlands. B. Gryseels, Prince Leopold Institute of Tropical Medicine, Nationalestraat 155, B-2000 Antwerp, Belgium. A. M. Polderman, Department of Parasitology, University of Leiden, PO Box 9605, 2300 RC Leiden, The Netherlands.

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