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A comparison of two mathematical models of the impact of mass drug administration on the transmission and control of schistosomiasis

The predictions of two mathematical models describing the transmission dynamics of schistosome infection and the impact of mass drug administration are compared. The models differ in their description of the dynamics of the parasites within the host population and in their representation of the stag...

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Detalles Bibliográficos
Autores principales: Truscott, J.E., Gurarie, D., Alsallaq, R., Toor, J., Yoon, N., Farrell, S.H., Turner, H.C., Phillips, A.E., Aurelio, H.O., Ferro, J., King, C.H., Anderson, R.M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5340850/
https://www.ncbi.nlm.nih.gov/pubmed/28279453
http://dx.doi.org/10.1016/j.epidem.2017.02.003
Descripción
Sumario:The predictions of two mathematical models describing the transmission dynamics of schistosome infection and the impact of mass drug administration are compared. The models differ in their description of the dynamics of the parasites within the host population and in their representation of the stages of the parasite lifecycle outside of the host. Key parameters are estimated from data collected in northern Mozambique from 2011 to 2015. This type of data set is valuable for model validation as treatment prior to the study was minimal. Predictions from both models are compared with each other and with epidemiological observations. Both models have difficulty matching both the intensity and prevalence of disease in the datasets and are only partially successful at predicting the impact of treatment. The models also differ from each other in their predictions, both quantitatively and qualitatively, of the long-term impact of 10 years’ school-based mass drug administration. We trace the dynamical differences back to basic assumptions about worm aggregation, force of infection and the dynamics of the parasite in the snail population in the two models and suggest data which could discriminate between them. We also discuss limitations with the datasets used and ways in which data collection could be improved.