ArticleeLife2021
Characterizing human mobility patterns in rural settings of sub-Saharan Africa.
Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Mapping the local effectiveness of mass drug administration for malaria using transportability methods.Nature health · 2026Article
- Modelling the effects of immigration on the re-introduction of onchocerciasis.Parasites & vectors · 2026Article
- Predicting schistosome transmission in rural Uganda using water contact data from wearable GPS devices.Nature health · 2026Article
- Molecular Epidemiology of Mycobacterium tuberculosis Across 3 Distinct Geographic Sites in South Africa.The Journal of infectious diseases · 2025Article
- Mapping seasonal human mobility across Africa using mobile phone location history and geospatial data.Research square · 2025Article
- Enhancing the gravity model for commuters: Time-and-spatial-structure-based improvements in Japan's metropolitan areas.PloS one · 2025Article
- The role of migration networks in the development of Botswana's generalized HIV epidemic.eLife · 2023Article
- Uncovering spatial and social gaps in rural mobility via mobile phone big data.Scientific reports · 2023Article
- Mobility and HIV care engagement: a research agenda.Journal of the International AIDS Society · 2023Review
- What Heterogeneities in Individual-level Mobility Are Lost During Aggregation? Leveraging GPS Logger Data to Understand Fine-scale and Aggregated Patterns of Mobility.The American journal of tropical medicine and hygiene · 2022Article
- A Bayesian modelling framework to quantify multiple sources of spatial variation for disease mapping.Journal of the Royal Society, Interface · 2022Article
- Integrating genomic and epidemiologic data to accelerate progress toward schistosomiasis elimination.eLife · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Human mobility is a core component of human behavior and its quantification is critical for understanding its impact on infectious disease transmission, traffic forecasting, access to resources and care, intervention strategies, and migratory flows. When mobility data are limited, spatial interaction models have been widely used to estimate human travel, but have not been extensively validated in low- and middle-income settings. Geographic, sociodemographic, and infrastructure differences may impact the ability for models to capture these patterns, particularly in rural settings. Here, we analyzed mobility patterns inferred from mobile phone data in four Sub-Saharan African countries to investigate the ability for variants on gravity and radiation models to estimate travel. Adjusting the gravity model such that parameters were fit to different trip types, including travel between more or less populated areas and/or different regions, improved model fit in all four countries. This suggests that alternative models may be more useful in these settings and better able to capture the range of mobility patterns observed.
Indexed as
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What OpenQuestion holds
Registered trials
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.