ArticlePLoS computational biology2015
Evaluating Spatial Interaction Models for Regional Mobility in Sub-Saharan Africa.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- Slowing the spread of treatment failure to artemisinin-based combination therapies in Uganda.Nature communications · 2026Article
- Predicting schistosome transmission in rural Uganda using water contact data from wearable GPS devices.Nature health · 2026Article
- Measurement of urban vitality with time-lapsed street-view images and object-detection for scalable assessment of pedestrian-sidewalk dynamics.ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS) · 2025Article
- Bias in mobility datasets drives divergence in modeled outbreak dynamics.Communications medicine · 2025Article
- Modeling tuberculosis transmission flow in China, 2010-2012.BMC infectious diseases · 2024Article
- Modeling policy interventions for slowing the spread of artemisinin-resistant pfkelch R561H mutations in Rwanda.Nature medicine · 2023Article
- National-scale simulation of human movement in a spatially coupled individual-based model of malaria in Burkina Faso.Scientific reports · 2023Article
- Characterisation of urban environment and activity across space and time using street images and deep learning in Accra.Scientific reports · 2022Article
- Integrating genomic and epidemiologic data to accelerate progress toward schistosomiasis elimination.eLife · 2022Review
- Existing human mobility data sources poorly predicted the spatial spread of SARS-CoV-2 in Madagascar.Epidemics · 2022Article
- Generalized radiation model for human migration.Scientific reports · 2021Article
- Article
- Existing human mobility data sources poorly predicted the spatial spread of SARS-CoV-2 in Madagascar.medRxiv : the preprint server for health sciences · 2021Article
- Article
- Comparing metapopulation dynamics of infectious diseases under different models of human movement.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Ensemble model for estimating continental-scale patterns of human movement: a case study of Australia.Scientific reports · 2021Article
- Megacities as drivers of national outbreaks: The 2017 chikungunya outbreak in Dhaka, Bangladesh.PLoS neglected tropical diseases · 2021Article
- Deriving fine-scale models of human mobility from aggregated origin-destination flow data.PLoS computational biology · 2021Article
- Kernel-based formulation of intervening opportunities for spatial interaction modelling.Scientific reports · 2021Article
- Incorporating human mobility data improves forecasts of Dengue fever in Thailand.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Simple spatial interaction models of human mobility based on physical laws have been used extensively in the social, biological, and physical sciences, and in the study of the human dynamics underlying the spread of disease. Recent analyses of commuting patterns and travel behavior in high-income countries have led to the suggestion that these models are highly generalizable, and as a result, gravity and radiation models have become standard tools for describing population mobility dynamics for infectious disease epidemiology. Communities in Sub-Saharan Africa may not conform to these models, however; physical accessibility, availability of transport, and cost of travel between locations may be variable and severely constrained compared to high-income settings, informal labor movements rather than regular commuting patterns are often the norm, and the rise of mega-cities across the continent has important implications for travel between rural and urban areas. Here, we first review how infectious disease frameworks incorporate human mobility on different spatial scales and use anonymous mobile phone data from nearly 15 million individuals to analyze the spatiotemporal dynamics of the Kenyan population. We find that gravity and radiation models fail in systematic ways to capture human mobility measured by mobile phones; both severely overestimate the spatial spread of travel and perform poorly in rural areas, but each exhibits different characteristic patterns of failure with respect to routes and volumes of travel. Thus, infectious disease frameworks that rely on spatial interaction models are likely to misrepresent population dynamics important for the spread of disease in many African populations.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.