LYMFASIM, a simulation model for predicting the impact of lymphatic filariasis control: quantification for African villages.
LYMFASIM is a simulation model for lymphatic filariasis transmission and control. We quantified its parameters to simulate Wuchereria bancrofti transmission by Anopheles mosquitoes in African villages, using a wide variety of reported data. The developed model captures the general epidemiological patterns, but also the differences between communities. It was calibrated to represent the relationship between mosquito biting rate and the prevalence of microfilariae (mf) in the human population, the age-pattern in mf prevalence, and the relation between mf prevalence and geometric mean mf intensity. Explorative simulations suggest that the impact of mass treatment depends strongly on the mosquito biting rate and on the assumed coverage, compliance and efficacy. Our sensitivity analysis showed that some biological parameters strongly influence the predicted equilibrium pre-treatment mf prevalence (e.g. the lifespan of adult worms and mf). Other parameters primarily affect the post-treatment trends (e.g. severity of density dependence in the mosquito uptake of infection from the human blood, between-person variability in exposure to mosquito bites). The longitudinal data, which are being collected for evaluation of ongoing elimination programmes, can help to further validate the model. The model can help to assess when ongoing elimination activities in African populations can be stopped and to design surveillance schemes. It can be a valuable tool for decision making in the Global Programme to Eliminate Lymphatic Filariasis.
|Keywords||Africa, Wuchereria bancroft, anopheles, elimination, lymphatic filariasis, mass treatment, simulation model, transmission dynamics|
|Persistent URL||dx.doi.org/10.1017/S0031182008000437, hdl.handle.net/1765/13900|
Stolk, W.A., de Vlas, S.J., Borsboom, G.J.J.M., & Habbema, J.D.F.. (2008). LYMFASIM, a simulation model for predicting the impact of lymphatic filariasis control: quantification for African villages.. Parasitology (Cambridge), 135(13), 1583–1598. doi:10.1017/S0031182008000437