ArticleScientific reports2019
Utilizing general human movement models to predict the spread of emerging infectious diseases in resource poor settings.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
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Who cites it
58 citing papers in PubMed.
- How important is the spatial movement of people in attempts to eliminate the transmission of human helminth infections by mass drug administration?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Trial
- 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
- Mobility-informed metapopulation models predict the spatio-temporal spread of respiratory epidemics across scales.BMC global and public health · 2026Article
- Article
- [Environmental medicine and AI, migration, and emerging and reemerging diseases in Mexico].Revista medica del Instituto Mexicano del Seguro Social · 2026Article
- Dengue forecasting and outbreak detection in Brazil using LSTM: integrating human mobility and climate factors.Infectious Disease Modelling · 2026Article
- Forecasting dengue across Brazil with LSTM neural networks and SHAP-driven lagged climate and spatial effects.BMC public health · 2025Article
- Comparing and integrating human mobility data sources for measles transmission modeling in Zambia.PLOS global public health · 2025Article
- Toward optimal disease surveillance with graph-based active learning.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- EpiFusion: Joint inference of the effective reproduction number by integrating phylodynamic and epidemiological modelling with particle filtering.PLoS computational biology · 2024Article
- Modeling tuberculosis transmission flow in China, 2010-2012.BMC infectious diseases · 2024Article
- Modeling the Regional Distribution of International Travelers in Spain to Estimate Imported Cases of Dengue and Malaria: Statistical Inference and Validation Study.JMIR public health and surveillance · 2024Article
- Spatial Interaction Analysis of Infectious Disease Import and Export between Regions.International journal of environmental research and public health · 2024Article
- Review
- Building a pathway to One Health surveillance and response in Asian countries.Science in One Health · 2024Review
- Navigating the Complex Landscape of Ebola Infection Treatment: A Review of Emerging Pharmacological Approaches.Infectious diseases and therapy · 2024Review
- Call detail record aggregation methodology impacts infectious disease models informed by human mobility.PLoS computational biology · 2023Article
- Genomic assessment of invasion dynamics of SARS-CoV-2 Omicron BA.1.Science (New York, N.Y.) · 2023Article
- Diffusion capacity of single and interconnected networks.Nature communications · 2023Article
- Cost benefit analysis of alternative testing and quarantine policies for travelers for infection control: A case study of Singapore during the COVID-19 pandemic.Frontiers in public health · 2023Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
Human mobility is an important driver of geographic spread of infectious pathogens. Detailed information about human movements during outbreaks are, however, difficult to obtain and may not be available during future epidemics. The Ebola virus disease (EVD) outbreak in West Africa between 2014-16 demonstrated how quickly pathogens can spread to large urban centers following one cross-species transmission event. Here we describe a flexible transmission model to test the utility of generalised human movement models in estimating EVD cases and spatial spread over the course of the outbreak. A transmission model that includes a general model of human mobility significantly improves prediction of EVD's incidence compared to models without this component. Human movement plays an important role not only to ignite the epidemic in locations previously disease free, but over the course of the entire epidemic. We also demonstrate important differences between countries in population mixing and the improved prediction attributable to movement metrics. Given their relative rareness, locally derived mobility data are unlikely to exist in advance of future epidemics or pandemics. Our findings show that transmission patterns derived from general human movement models can improve forecasts of spatio-temporal transmission patterns in places where local mobility data is unavailable.
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