Forecasting Human African Trypanosomiasis Prevalences from Population Screening Data Using Continuous Time Models.

ABSTRACT: To eliminate and eradicate gambiense human African trypanosomiasis (HAT), maximizing the effectiveness of active case finding is of key importance. The progression of the epidemic is largely influenced by the planning of these operations. This paper introduces and analyzes five models for predicting HAT prevalence in a given village based on past observed prevalence levels and past screening activities in that village. Based on the quality of prevalence level predictions in 143 villages in Kwamouth (DRC), and based on the theoretical foundation underlying the models, we consider variants of the Logistic Model-a model inspired by the SIS epidemic model-to be most suitable for predicting HAT prevalence levels. Furthermore, we demonstrate the applicability of this model to predict the effects

SUBMITTER: de Vries H 

PROVIDER: S-EPMC5033383 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature