ArticleJournal of the Royal Society, Interface2020
Time-aggregated mobile phone mobility data are sufficient for modelling influenza spread: the case of Bangladesh.
Article in Journal of the Royal Society, Interface, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Characterizing the impact of incorporating spatially aggregated human mobility data into infectious disease models.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Spatial Interaction Analysis of Infectious Disease Import and Export between Regions.International journal of environmental research and public health · 2024Article
- Spatiotemporal dynamics of epidemiology diseases: mobility based risk and short-term prediction modeling of COVID-19.Frontiers in public health · 2024Article
- The impact of current and future climates on spatiotemporal dynamics of influenza in a tropical setting.PNAS nexus · 2023Article
- Call detail record aggregation methodology impacts infectious disease models informed by human mobility.PLoS computational biology · 2023Article
- Estimation of mobility and population in Spain during different phases of the COVID-19 pandemic from mobile phone data.Scientific reports · 2023Article
- Understanding the impact of mobility on COVID-19 spread: A hybrid gravity-metapopulation model of COVID-19.PLoS computational biology · 2023Article
- How to avoid a local epidemic becoming a global pandemic.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Air pollution and mobility patterns in two Ugandan cities during COVID-19 mobility restrictions suggest the validity of air quality data as a measure for human mobility.Environmental science and pollution research international · 2023Article
- A real-time regional model for COVID-19: Probabilistic situational awareness and forecasting.PLoS computational biology · 2023Article
- Connecting the dots: understanding how human mobility shapes TB epidemics.Trends in microbiology · 2022Review
- Genetic Analysis of Influenza A/H1N1pdm Strains Isolated in Bangladesh in Early 2020.Tropical medicine and infectious disease · 2022Article
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6 authors.
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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 version of approximate Bayesian computation. We find a good agreement between our estimated model and the case data. We estimate transmissibility and regional spread of influenza in Bangladesh, which are useful for policy planning. Time-averaged mobility appears to be a good proxy for human mobility when modelling infectious diseases. This motivates a more general use of the time-averaged mobility, with important implications for future studies and outbreak control. Moreover, time-averaged mobility is subject to less privacy concerns than daily mobility, containing less temporal information on individual movements.
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