Time-aggregated mobile phone mobility data are sufficient for modelling influenza spread: the case of Bangladesh.

ABSTRACT: Human mobility plays a major role in the spatial dissemination of infectious diseases. We develop a spatio-temporal stochastic model for influenza-like disease spread based on estimates of human mobility. The model is informed by mobile phone mobility data collected in Bangladesh. We compare predictions of models informed by daily mobility data (reference) with that of models informed by time-averaged mobility data, and mobility model approximations. We find that the gravity model overestimates the spatial synchrony, while the radiation model underestimates the spatial synchrony. Using time-averaged mobility resulted in spatial spreading patterns comparable to the daily mobility model. We fit the model to 2014-2017 influenza data from sentinel hospitals in Bangladesh, using a sequential ve

SUBMITTER: Engebretsen S 

PROVIDER: S-EPMC7328378 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature