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Quantifying the Impact of Human Mobility on Malaria
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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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Citations
Cites
Understanding individual human mobility patterns
González, M. C., Hidalgo, C. A., & Barabási, A.-Ĺ. (2008) · Nature · doi:10.1038/nature06958 · Cited by 6,186
Limits of Predictability in Human Mobility
Song, C., Qu, Z., Blumm, N., & Barabási, A.-L. (2010) · Science · doi:10.1126/science.1177170 · Cited by 3,234
Strategies for containing an emerging influenza pandemic in Southeast Asia
Ferguson, N. M., Cummings, D. A. T., Cauchemez, S., Fraser, C., Riley, S., Meeyai, A. C., Iamsirithaworn, S., & Burke, D. S. (2005) · Nature · doi:10.1038/nature04017 · Cited by 1,820
Multiscale mobility networks and the spatial spreading of infectious diseases
Balcan, D., Vittoria Colizza, A., Gonçalves, B., Hu, H., Ramasco, J. J., & Vespignani, A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0906910106 · Cited by 1,347
Containing Pandemic Influenza at the Source
Longini, I. M., Nizam, A., Xu, S., Ungchusak, K., Hanshaoworakul, W., Cummings, D. A. T., & Halloran, M. E. (2005) · Science · doi:10.1126/science.1115717 · Cited by 1,177
A new world malaria map: Plasmodium falciparum endemicity in 2010
Gething, P. W., Patil, A. P., Smith, D. L., Guerra, C. A., Elyazar, I., Johnston, G. L., Tatem, A. J., & Hay, S. I. (2011) · Malaria Journal · doi:10.1186/1475-2875-10-378 · Cited by 1,169
Self-citationPopulation Distribution, Settlement Patterns and Accessibility across Africa in 2010
Linard, C., Gilbert, M., Snow, R. W., Noor, A. M., & Tatem, A. J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0031743 · Cited by 595
Self-citationThe role of human movement in the transmission of vector-borne pathogens
Stoddard, S. T., Morrison, A. C., Vazquez-Prokopec, G. M., Paz Soldan, V., Kochel, T. J., Kitron, U., Elder, J. P., & Scott, T. W. (2009) · PLoS Neglected Tropical Diseases · doi:10.1371/journal.pntd.0000481 · Cited by 573
Stable and Unstable Malaria Hotspots in Longitudinal Cohort Studies in Kenya
Bejon, P., Williams, T. N., Liljander, A., Noor, A. M., Wambua, J., Ogada, E. A., Olotu, A., Osier, F. H. A., Hay, S. I., Färnert, A., et al. (2010) · PLoS Medicine · doi:10.1371/journal.pmed.1000304 · Cited by 269
Self-citationDye, C., & Hasibeder, G. (1986) · Transactions of the Royal Society of Tropical Medicine and Hygiene · doi:10.1016/0035-9203(86)90199-9 · Cited by 253
Research works printed but not linked: 1
- B. Rapuoda P. Achola Study on malaria and its vectors in Nairobi: A review of the distribution of the vectors and the prevalence of the disease. Proceedings of the KEMRI/KETRI Fifth Annual Medical Scientific Conference Nairobi Kenya 1984 (Kenya Medical Research Institute and Kenya Trypanosomiasis Research Institute Nairobi 1984) pp. 115–119.
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Kamis, A. A., Ding, Y., Qu, Z., & Zhang, C. (2021) · Applied Sciences · doi:10.3390/app112311227 · Cited by 3
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Robsky, K., Tram, K. H., Dowdy, D. W., & Zelner, J. (2023) · BMJ Open · doi:10.1136/bmjopen-2023-072439 · Cited by 3
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Tan, Q., Liu, J., Shi, B., Liu, Y., & Zhou, X. (2018) · IEEE International Conference on Healthcare Informatics (ICHI) · doi:10.1109/ichi.2018.00036 · Cited by 3
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Hong, Y., Li, Z., & Wang, J. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1437/1/012068 · Cited by 3
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Milusheva, S. (2019) · The World Bank Economic Review · doi:10.1093/wber/lhz036 · Cited by 3
Chang, H., Wesolowski, A., Sinha, I., Jacob, C. G., Mahmud, A. S., Uddin, D., Zaman, S. I., Hossain, M. A., Faiz, M. A., Ghose, A., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/421578 · Cited by 3
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Radford, J. P., & Lazer, D. M. J. (2019) · Wiley eBooks · doi:10.1002/9781119429333.ch24 · Cited by 2
Flow descriptors of human mobility networksPreprint
Pastor-Escuredo, D., & Frı́as-Martı́nez, E. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2003.07279 · Cited by 3
Li, Q., Bessell, L., Xiao, X., Fan, C. H., Gao, X., & Mostafavi, A. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.14157 · Cited by 3
Nkomo, S., & Matli, W. (2022) · Africa Education Review · doi:10.1080/18146627.2023.2248547 · Cited by 2
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Ayabina, D. V., Sevil, H., Kleczkowski, A., & Gomes, M. G. M. (2025) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2025.112213 · Cited by 2
Stabler, T. C., Dwivedi, A., Guo, B., Shrestha, B., Joshi, S. N., Rivas, M. R., Donfack, O. T., Guerra, C. A., García, G. A., Daubenberger, C., et al. (2025) · PLOS Global Public Health · doi:10.1371/journal.pgph.0004999 · Cited by 2
Esayas, E., Louie, W., Routledge, I., Murphy, M., Negash, N., Amaral, F. D., Aranda-Díaz, A., Greenhouse, B., Kassa, F. A., Nigusse, T., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-29271-0 · Cited by 2
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Şendir, M. (2014) · Journal of EAHIL · doi:10.7490/f1000research.1095837.1 · Cited by 2
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Toole, J. L., de Montjoye, Y.-A., González, M. C., & Pentland, A. (2018) · Springer eBooks · doi:10.1007/978-3-319-98161-1_2 · Cited by 2
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Spoorenberg, T. (2022) · International handbooks of population · doi:10.1007/978-3-031-02040-7_16 · Cited by 2
Stresman, G. H., Stratil, A.-S., Gomane, S., Armando, S., Rodrigues, M. D. L. V., Candrinho, B. N., & Roca‐Feltrer, A. (2022) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.22-0166 · Cited by 2
Sunish, I. P., Shriram, A. N., De, A., Sugunan, A. P., & Vijayachari, P. (2022) · International Journal of Microbiology Research · doi:10.4103/ijmr.ijmr_3189_21 · Cited by 2
Ghosh, N., Sarkar, U., & Nagesh, P. (2023) · Springer geography · doi:10.1007/978-3-031-24767-5_36 · Cited by 2
Ryckman, T. S., Hopkins, L., Tang, L., Biché, P., Mohlamonyane, M., Morolo, M., Nonyane, B. A. S., Ahmed, K., Martinson, N. A., Hanrahan, C. F., et al. (2025) · The Journal of Infectious Diseases · doi:10.1093/infdis/jiaf326 · Cited by 2
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Wang, H., Kwok, K. O., Li, R., & Riley, S. (2025) · Epidemics · doi:10.1016/j.epidem.2025.100856 · Cited by 2
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Isoda, S., Kawanaka, S., Matsuda, Y., Suwa, H., & Yasumoto, K. (2020) · ACM Conference on Embedded Networked Sensor Systems (SenSys) · doi:10.1145/3384419.3430593 · Cited by 2
Zhou, S., Yi-tong, L. I. A. O., & Zheng, Z. (2021) · 自然资源学报 · doi:10.31497/zrzyxb.20210906 · Cited by 2
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Illangakoon, C., McLeod, R. D., & Friesen, M. (2014) · IEEE Canada International Humanitarian Technology Conference · doi:10.1109/ihtc.2014.7147546 · Cited by 2
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Mieghem, P. V. (2014) · Cambridge University Press eBooks · doi:10.1017/cbo9781107415874.018 · Cited by 2
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Kwan, M. (2016) · doi:10.4324/9781315541280-6 · Cited by 2
Nkomo, S., & Matli, W. (2022) · IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) · doi:10.1109/ice/itmc-iamot55089.2022.10033311 · Cited by 2
Martín, Y. (2020) · Boletín de la Asociación de Geógrafos Españoles · doi:10.21138/bage.2848 · Cited by 2
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Hawelka, B., Sitko, I., Kazakopoulos, P., & Beinat, E. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1510.06582 · Cited by 2
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Flyverbom, M., & Rasche, A. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2698026 · Cited by 2
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Williams, N. E., & Ghimire, D. J. (2018) · doi:10.1002/9781118884997.ch20 · Cited by 2
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Xiong, C., Darzi, A., Pan, Y., Ghader, S., & Zhang, L. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2012.04776 · Cited by 2
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Das, A. M., Hetzel, M. W., Yukich, J. O., Stuck, L. H., Fakih, B. S., Al-mafazy, A.-W. H., Ali, A., & Chitnis, N. (2022) · medRxiv · doi:10.1101/2022.09.06.22279643 · Cited by 2
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Epstein, A., Aramanzan, O., Nabende, I., Kayondo, T. M., Obbo, M., Tumwesigye, R., Wiringilimaana, I., Mbabazi, M., Kagurusi, B. A., Tukwasibwe, S., et al. (2025) · medRxiv · doi:10.1101/2025.05.14.25327608 · Cited by 2
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Andris, C., & Andris, Z. (2015) · IEEE International Conference on Mobile Data Management (MDM) · doi:10.1109/mdm.2015.28 · Cited by 1
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Link, H., Wendt, J., Field, R. V., & Marthe, J. (2017) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1145/3110025.3116195 · Cited by 1
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Sa-ngamuang, C., Yin, M. S., Barkowsky, T., Lawpoolsri, S., Bicout, D., & Haddawy, P. (2026) · Scientific Reports · doi:10.1038/s41598-026-39007-3 · Cited by 1
Liu, Y., Guo, J., Ge, Y., Wang, D., Zheng, X., & Peng, X. (2026) · BMC Public Health · doi:10.1186/s12889-026-26562-7 · Cited by 1
Roh, M. E., Tong, Y., Heitmann, G. B., Jia, J., Ciré, E. B. K., Ndiaye, J. L., Fogelson, A., Milligan, P. J., Seck, A., Diallo, A., et al. (2026) · Nature Health · doi:10.1038/s44360-026-00094-1 · Cited by 1
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Olivera, M. J. (2026) · Tropical Medicine and Infectious Disease · doi:10.3390/tropicalmed11060151 · Cited by 1
Pullano, G., Bansal, S., Rubrichi, S., & Colizza, V. (2026) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1014427 · Cited by 3
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Abdi, M. S., Adan, A. M., Ahmed, N., Sudi, L. A., Abdi, Y. H., Mohamed, M. D., Abdullahi, Y. B., Bashir, S., Khalif, I. A., & Hassan, A. A. (2026) · Frontiers in Digital Health · doi:10.3389/fdgth.2026.1879638 · Cited by 1
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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
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