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Quantifying the Impact of Human Mobility on Malaria
Open accessAbstract
Mobile Phone “Hot Spots”: An obstacle to developing effective national malaria control programs is a lack of understanding of human movements, which are an important component of disease transmission. As mobile phones have become increasingly ubiquitous, it is now possible to collect individual-level, longitudinal data on human movements on a massive scale. Wesolowski et al. (p. 267 ) analyzed mobile phone call data records representing the travel patterns of 15 million mobile phone owners in Kenya over the course of a year. This was combined with a detailed malaria risk map, to estimate malaria parasite movements across the country that could be caused by human movement. This information enabled detailed analysis of parasite sources and sinks between hundreds of local settlements. Estimates were compared with hospital data from Nairobi to show that local pockets of transmission likely occur around the periphery of Nairobi, accounting for locally acquired cases, contrary to the accepted idea that there is no transmission in the capital.
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“Yet, human mobility plays an important role in the transmission of vector‐borne diseases, as population movements lead to continuous pathogen reintroductions (Buckee et al., 2013; Wesolowski et al., 2012).”
From Spatial Optimization Methods for Malaria Risk Mapping in Sub‐Saharan African Cities Using Demographic and Health Surveys (2023) · cites this paper as Wesolowski et al., 2012
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“Pathogen transmission by mosquitoes has been characterized as being highly local and focal, with transmission foci and hotspots.75”
From Recasting the theory of mosquito-borne pathogen transmission dynamics and control (2014) · cites this paper as [75]
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“Recent evidence suggests that human social networks are just as important for transmission within cities as mosquito ecology,108 and that movement networks are a critical element of transmission within and among countries.109,110”
From Recasting the theory of mosquito-borne pathogen transmission dynamics and control (2014) · cites this paper as [110]
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“Apart from the above infectious diseases, mobility has been shown to play a major role in spreading other diseases like malaria [111]—people travelling to different cities carry the parasite and infect the mosquitoes there and in turn the population.”
From Human-centred artificial intelligence for mobile health sensing: challenges and opportunities (2023) · cites this paper as [111]
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Metadata
- Authors
- Wesolowski, A., Eagle, N., Tatem, A. J., Smith, D. L., Noor, A. M., Snow, R. W., & Buckee, C. O.
- Affiliations
- Carnegie Mellon University (US)
- Northeastern University (US)
- National Institutes of Health (US)
- Kenya Medical Research Institute (KE)
- Harvard University (US)
- Corresponding author
- Buckee, Caroline O.
- ORCID
- Venue
- Science
- Published
- 2012-10-12
- Volume
- 338
- Issue
- 6104
- Pages
- 267-270
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC3675794
- OpenAlex
- W1994682066
- Cited by
- 992
- References
- 26
- Citations by year
- 2026: 36 · 2025: 55 · 2024: 43 · 2023: 50 · 2022: 79 · 2021: 144 · 2020: 129 · 2019: 81 · 2018: 77 · 2017: 58 · 2016: 74 · 2015: 69 · 2014: 58 · 2013: 36 · 2012: 3
- FWCI
- 50.96
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- ePrints Soton (University of Southampton) (submittedVersion)
- Funders
- Wellcome Trust (095127, 092654, 079080)
- National Institute of General Medical Sciences (U54GM088558)
- National Institute of Allergy and Infectious Diseases (U19AI089674)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Malaria Research and Control
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Travel-related health issues
- Keywords
- malaria, human mobility, mobile phone data, malaria transmission, malaria risk mapping, Nairobi, local transmission, malaria control
- MeSH terms
- Animals, Communicable Disease Control, Humans, Kenya, Culicidae, Plasmodium falciparum, Travel, Prevalence, Malaria, Falciparum, Cell Phone
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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