Non-local validated parametrization of an agent-based model of local-scale Taenia solium transmission in North-West Peru

Francesco Pizzitutti, Gabrielle Bonnet, Eloy Gonzales-Gustavson, Sarah Gabriël, William K. Pan, Ian W. Pray, Armando E. Gonzalez, Hector H. Garcia, Seth E. ONeal

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Resumen

The pork tapeworm, Taenia solium, is the cause of a preventable zoonotic disease, cysticercosis, affecting both pigs and humans. Continued endemic transmission of T. solium is a major contributor of epilepsy and other neurologic morbidity, and the source of important economic losses, in many rural areas of developing countries. Simulation modelling can play an important role in aiding the design and evaluation of strategies to control or even eliminate transmission of the parasite. In this paper, we present a new agent based model of local-scale T. solium transmission and a new, non-local, approach to the model calibration to fit model outputs to observed human taeniasis and pig cysticercosis prevalence simultaneously for several endemic villages. The model fully describes all relevant aspects of T. solium transmission, including the processes of pig and human infection, the spatial distribution of human and pig populations, the production of pork for human consumption, and the movement of humans and pigs in and out in several endemic villages of the northwest of Peru. Despite the high level of uncertainty associated with the empirical measurements of epidemiological data associated with T. solium, the non-local calibrated model parametrization reproduces the observed prevalences with an acceptable precision. It does so not only for the villages used to calibrate the model, but also for villages not included in the calibration process. This important finding demonstrates that the model, including its calibrated parametrization, can be successfully transferred within an endemic region. This will enable future studies to inform the design and optimization of T. solium control interventions in villages where the calibration may be prevented by the limited amount of empirical data, expanding the possible applications to a wider range of settings compared to previous models.

Idioma originalInglés
Número de artículoe0275247
PublicaciónPLoS ONE
Volumen17
N.º9 September
DOI
EstadoPublicada - set. 2022

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Copyright: © 2022 Pizzitutti et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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