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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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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
Flagged first, then by citations
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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Sorted by citations
Items 601–700 of 991
Pirahmadi, S., Zakeri, S., & Raeisi, A. (2017) · PubMed Central · Cited by 7
A survey of results on mobile phone datasets analysisPreprint
Blondel, V. D., Decuyper, A., & Krings, G. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1502.03406 · Cited by 7
Urmi, T., Pant, B., Dewey, G., Quintana, A., Lang, I., Druckman, J. N., Ognyanova, K., Baum, M., Perlis, R. H., Riedl, C., et al. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2500655122 · Cited by 6
Janko, M., Navas, A. A., Ascencio, E. J., Guedes, G. R., Vasco, L., dos Santos, R. O., Damasceno, C. P., Medrano, P. G., Chacón-Uscamaita, P. R., Gunderson, A. K., et al. (2024) · BMJ Open · doi:10.1136/bmjopen-2023-078911 · Cited by 5
Early detection of critical urban events using mobile phone network data
Lemaire, P., Furno, A., Rubrichi, S., Bondu, A., Smoreda, Z., Ziemlicki, C., Faouzi, N. E., & Gaumé, É. (2024) · PLoS ONE · doi:10.1371/journal.pone.0309093 · Cited by 6
Zhang, F., Zhou, J., Liu, R., Du, Z., & Ye, X. (2016) · Sustainability · doi:10.3390/su8090926 · Cited by 6
Makanda, M., Kemunto, G., Wamuyu, L., Bargul, J. L., Muema, J. M., & Mutunga, J. M. (2019) · F1000Research · doi:10.12688/f1000research.18262.1 · Cited by 6
Peprah, S., Dhudha, H., Ally, H., Masalu, N. A., Kawira, E. L., Chao, C., Genga, I. O., Mumia, M., Were, P. A., Kinyera, T., et al. (2019) · Tropical Medicine & International Health · doi:10.1111/tmi.13225 · Cited by 6
Champagne, C., Gerhards, M., Lana, J. T., Espinosa, B. G., Bradley, C. M., González, O., Cohen, J. M., Menach, A. L., White, M. T., & Pothin, E. (2021) · Mathematical Biosciences · doi:10.1016/j.mbs.2021.108750 · Cited by 5
Path Forming of Healthcare Practitioners in an Indoor Space Using Mobile Crowdsensing
Panlaqui, B.-J. G., Fuad, M., Deb, D., & Mickle, C. F. (2022) · Sensors · doi:10.3390/s22197546 · Cited by 6
Morlighem, C., Chaiban, C., Georganos, S., Brousse, O., Van de Walle, J., van Lipzig, N. P. M., Wolff, E., Dujardin, S., & Linard, C. (2022) · Remote Sensing · doi:10.3390/rs14215381 · Cited by 6
Explore urban interactions based on floating car data – a case study of Chengdu, China
Yang, M., Yuan, Y., & Zhan, F. B. (2023) · Annals of GIS · doi:10.1080/19475683.2023.2166109 · Cited by 6
Kokoulina, O. (2023) · Computer law & security review · doi:10.1016/j.clsr.2023.105802 · Cited by 6
Lucena, T. F. R., Velho, A. P. M., Dorne, V. D., & Domingues, D. M. G. (2018) · Springer eBooks · doi:10.1007/978-3-319-76795-6_14 · Cited by 6
Yasumoto, S., Watanabe, C., Arai, A., Shibasaki, R., & Oyoshi, K. (2018) · Springer eBooks · doi:10.1007/978-981-13-2526-7_3 · Cited by 6
Mobile Phone Data for Children on the Move: Challenges and Opportunities
Sekara, V., Omodei, E., Healy, L., Beise, J., Hansen, C., You, D., Blume, S., & García–Herranz, M. (2019) · Springer eBooks · doi:10.1007/978-3-030-12554-7_3 · Cited by 7
Modeling human migration across spatial scales in Colombia
Siraj, A. S., Sorichetta, A., España, G., Tatem, A. J., & Perkins, T. A. (2020) · PLoS ONE · doi:10.1371/journal.pone.0232702 · Cited by 6
Self-citationCompanion Mobility to Assist in Future Human Location Prediction
Ngo, Q. T., Lan, D. T., Yoon, S., Jung, W.-S., Yoon, T., & Yoo, D.-S. (2022) · IEEE Access · doi:10.1109/access.2022.3186319 · Cited by 6
CDR-To-MoVis: Developing a Mobility Visualization System from CDR data
Dash, M., Koo, K. K., Decraene, J., Yap, G.-E., Wu, W., Gomes, J. B., Shi‐Nash, A., & Li, X. (2015) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde.2015.7113399 · Cited by 6
Can host ecology and kin selection predict parasite virulence?
Gleichsner, A. M., & Minchella, D. J. (2014) · Parasitology · doi:10.1017/s0031182014000389 · Cited by 6
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Buckee, C. O. (2014) · Nature · doi:10.1038/514035c · Cited by 6
Self-citationOpen data and smallholder food and nutritional security
Jellema, A., Meijninger, W. M. L., & Addison, C. (2015) · CGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research) · Cited by 6
Uncovering patterns of inter-urban trips and spatial interactions from check-in data.Preprint
Liu, Y., Sui, Z., Kang, C., & Gao, Y. C. (2013) · arXiv (Cornell University) · Cited by 6
de Albuquerque, N. R. M., Corder, R. M., Johansen, I. C., Ladeia, W. A., Rodrigues, P. T., Ladeia-Andrade, S., da Silva, J. C. F., & Ferreira, M. U. (2025) · The Journal of Infectious Diseases · doi:10.1093/infdis/jiaf457 · Cited by 5
Savi, M. K., Pandey, B., Swain, A., Lim, J., Callo-Concha, D., Azondékon, R., Mohammed, W., & Borgemeister, C. (2024) · PLOS Global Public Health · doi:10.1371/journal.pgph.0002871 · Cited by 11
Hergott, D., Guerra, C. A., García, G. A., Eyono, J. N. M., Donfack, O. T., Iyanga, M. M., Avue, R. M. N., Nsegue, C. N. A., Mifumu, T. A. O., Rivas, M. R., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-52638-2 · Cited by 5
Self-citationBias in mobility datasets drives divergence in modeled outbreak dynamics
Chin, T., Johansson, M. A., Chowdhury, A., Chowdhury, S., Hosan, K., Quader, M. T., Buckee, C. O., & Mahmud, A. S. (2025) · Communications Medicine · doi:10.1038/s43856-024-00714-5 · Cited by 5
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Gong, W., Zhang, B., & Li, C. (2019) · International Conference on Communications · doi:10.1109/icc.2019.8761164 · Cited by 5
de Alarcon, P. A., Salevsky, A., Gheti-Kao, D., Rosalen, W., Duarte, M. C., Cuervo, C., Muñoz, J. J., Pascual, J. M., Schurig, M., Treß, T., et al. (2021) · Data & Policy · doi:10.1017/dap.2021.6 · Cited by 5
Data-driven Mobility Analysis and Modeling: Typical and Confined Life of a Metropolitan Population
Fanticelli, H. C., Rabenjamina, S., Viana, A. C., Stanica, R., de Oliveira, L. S., & Ziviani, A. (2022) · ACM Transactions on Spatial Algorithms and Systems · doi:10.1145/3517222 · Cited by 5
Bernal, E. V., Saucedo, O., & Tien, J. H. (2022) · Journal of Mathematical Biology · doi:10.1007/s00285-022-01761-z · Cited by 5
Mobility patterns and COVID growth: Moderating role of country culture
Rana, A., Mukherjee, T., & Adak, S. (2022) · International Journal of Intercultural Relations · doi:10.1016/j.ijintrel.2022.06.002 · Cited by 5
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Tian, H. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2301653120 · Cited by 8
Unconventional data, unprecedented insights: leveraging non-traditional data during a pandemic
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Xu, W., Zhou, Y., Taubenböck, H., Stokes, E. C., Zhu, Z., Lai, F., Li, X., & Xia, Z. W. (2024) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2024.173623 · Cited by 5
Semantic interpretation of mobile phone records exploiting background knowledge
Dashdorj, Z., & Serafini, L. (2013) · Cited by 5
Understanding spatial spread of emerging infectious diseases in contemporary populations
Li, H., Cheng, Q., & Wang, L. (2016) · Physics of Life Reviews · doi:10.1016/j.plrev.2016.10.008 · Cited by 5
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Aksu, H., Körpeoǧlu, İ., & Ulusoy, Ö. (2016) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2016.2627034 · Cited by 5
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Chen, I., Gosling, R. D., DRAKELEY, C. J., & Bousema, T. (2016) · The Journal of Infectious Diseases · doi:10.1093/infdis/jiw484 · Cited by 5
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Mamei, M., Cılasun, S. M., Lippi, M., Pancotto, F., & Tümen, S. (2019) · Springer eBooks · doi:10.1007/978-3-030-12554-7_19 · Cited by 5
Recurrent Mobility: Urban Conduits for Diffusion of Energy Efficiency
Mohammadi, N., & Taylor, J. E. (2019) · Scientific Reports · doi:10.1038/s41598-019-56372-4 · Cited by 5
Human Movement and Transmission of Antimicrobial-Resistant Bacteria
Ghany, M. A. E., Fouz, N., & Hill-Cawthorne, G. A. (2020) · The handbook of environmental chemistry · doi:10.1007/698_2020_560 · Cited by 5
Analyzing the spread of chagas disease with mobile phone data
de Monasterio, J., Salles, A., Lang, C., Weinberg, D., Minnoni, M., Travizano, M., & Sarraute, C. (2016) · Advances in Social Networks Analysis and Mining · doi:10.5555/3192424.3192538 · Cited by 5
Leng, Y., Babwany, N. A., & Pentland, A. (2021) · Humanities and Social Sciences Communications · doi:10.1057/s41599-021-00822-w · Cited by 5
Giles, J. R., Cummings, D. A. T., Grenfell, B. T., Tatem, A. J., zu Erbach-Schoenberg, E., Metcalf, C. J. E., & Wesolowski, A. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009127 · Cited by 5
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Chang, B., Yang, L., Sensi, M., Achterberg, M. A., Wang, F., Rinaldi, M., & Mieghem, P. V. (2022) · Studies in computational intelligence · doi:10.1007/978-3-030-93409-5_50 · Cited by 5
Comparison of deforestation and forest land use factors for malaria elimination in Myanmar
Hoffman-Hall, A., Puett, R., Silva, J. A., Chen, D., Bredder, A., Shevade, V., Han, Z. Y., Han, K. T., Aung, P. P., Plowe, C. V., et al. (2023) · IJID Regions · doi:10.1016/j.ijregi.2023.06.006 · Cited by 5
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Szaboova, L., Brown, K., Chaigneau, T., Coulthard, S., Daw, T. M., & James, T. (2018) · Routledge eBooks · doi:10.4324/9780429507090 · Cited by 39
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Childs, L. M., & Larremore, D. B. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-801238-3.11512-0 · Cited by 5
Mwamnyange, M., Luhanga, E. T., & Sanket, R. (2021) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2021.0120345 · Cited by 5
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Ramón, J., Albert, G., Serafica, R. B., & Lumbera, B. T. (2016) · RePEc: Research Papers in Economics · Cited by 5
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Wu, N., Ben, X., Green, B., Rough, K., Venkatramanan, S., MARATHE, M. V., Eastham, P., Sadilek, A., & O’Banion, S. (2020) · medRxiv · doi:10.1101/2020.07.27.20159996 · Cited by 5
A longitudinal study of the impact of human mobility on the incidence of COVID-19 in IndiaPreprint
Praharaj, S., & Han, H. (2020) · medRxiv · doi:10.1101/2020.12.21.20248523 · Cited by 5
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Taylor, L. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2820580 · Cited by 5
Application of Mobile Operators’ Data in Modern Geographical Research
Babkin, R. A., Вадимовна, Б. С., & Bereznyatskiy, A. (2022) · Encyclopedia · doi:10.3390/encyclopedia2040126 · Cited by 5
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de Sojo, S., Lucchini, L., Langle-Chimal, O., Fraiberger, S. P., & Alessandretti, L. (2026) · Computers Environment and Urban Systems · doi:10.1016/j.compenvurbsys.2025.102397 · Cited by 4
Gibbs, H. P., Musah, A., Seidu, O., Ampofo, W., Asiedu‐Bekoe, F., Gray, J., Adewole, W. A., Cheshire, J. A., Marks, M., & Eggo, R. M. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011368 · Cited by 4
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Carrasco‐Escobar, G., Villa, D., Barja, A., Lowe, R., Llanos‐Cuentas, A., & Benmarhnia, T. (2024) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0012560 · Cited by 3
Stražovec, A., Erlebach, M., & Halás, M. (2025) · Journal of Maps · doi:10.1080/17445647.2025.2528871 · Cited by 4
Innovations in Disease Surveillance and Monitoring
Espey, J., & Dahmm, H. (2020) · Springer eBooks · doi:10.1007/978-3-030-05325-3_16-1 · Cited by 4
Haileselassie, W., Getnet, A., Solomon, H., Deressa, W. A., Yan, G., & Parker, D. M. (2022) · Malaria Journal · doi:10.1186/s12936-022-04337-w · Cited by 4
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Kostakos, V., & Ferreira, D. (2015) · Frontiers in ICT · doi:10.3389/fict.2015.00003 · Cited by 4
Miller, J. A., & Hoover, B. (2018) · Human dynamics in smart cities · doi:10.1007/978-3-319-73247-3_8 · Cited by 4
Švéda, M., Križan, F., & Barlík, P. (2019) · Geografický časopis - Geographical Journal · doi:10.31577/geogrcas.2019.71.3.11 · Cited by 4
Tan, Q., Liu, Y., Liu, J., Shi, B., Xia, S., & Zhou, X. (2020) · Neurocomputing · doi:10.1016/j.neucom.2019.12.145 · Cited by 4
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Pentland, A. (2020) · Journal of Social Computing · doi:10.23919/jsc.2020.0007 · Cited by 4
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Lv, J., Zhao, C., & Zeng, A. (2020) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2020.125674 · Cited by 4
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Moreau, C., Chanson, A., Peralta, V., Devogèle, T., & de Runz, C. (2021) · ACM Symposium on Applied Computing · doi:10.1145/3412841.3441920 · Cited by 4
Yang, C., Song, H., Tang, M., Danon, L., & Vigfússon, Ý. (2022) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3534678.3542678 · Cited by 5
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Shi, Z. Y., Qian, H., Li, Y., Wu, F. O., & Wu, L. (2022) · Scientific Reports · doi:10.1038/s41598-022-24670-z · Cited by 4
Maloney, P., Kompaniyets, L., Yusuf, H. R., Bonilla, L. L., Figueroa, C., & García, M. C. (2023) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2023.102459 · Cited by 4
Michalitsi-Psarrou, A., Pertselakis, M., Brantl, I., Ntanos, C., Varoutas, D. A., & Psarras, J. E. (2019) · IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) · doi:10.1109/ice.2019.8792679 · Cited by 4
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Shoghri, A. E., Liebig, J., Jurdak, R., Gardner, L., & Kanhere, S. S. (2020) · IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) · doi:10.1109/wowmom49955.2020.00020 · Cited by 4
Mohammad, M. A., Koul, S. M., Gale, C. P., Alfredsson, J., James, S. K., Fröbert, O., Ömerovic, E., & Erlinge, D. (2020) · Journal of Internal Medicine · doi:10.1111/joim.13206 · Cited by 4
The spatial dissemination of COVID-19 and associated socio-economic consequences
Zhang, Y., Wang, L., Zhu, J. J. H., & Wang, X. (2022) · Journal of The Royal Society Interface · doi:10.1098/rsif.2021.0662 · Cited by 4
Yuan, B., Lee, H., & Nishiura, H. (2021) · Theoretical Biology and Medical Modelling · doi:10.1186/s12976-021-00149-8 · Cited by 4
Mota, T., Munjal, A., & Camp, T. K. (2015) · IEEE International Conference on Mobile Data Management (MDM) · doi:10.1109/mdm.2015.84 · Cited by 4
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Carletti, L., Price, D., Giannachi, G., Sinker, R., McAuley, D., & Stack, J. (2014) · Electronic workshops in computing · doi:10.14236/ewic/eva2014.17 · Cited by 4
Hergott, D., Balkus, J. E., García, G. A., Cruz, K. R., Seilie, A. M., Masters, H., Aveika, A. A., Iyanga, M. M., Eyono, J. N. M., Guthrie, B. L., et al. (2021) · Malaria Journal · doi:10.1186/s12936-021-03844-6 · Cited by 3
Socio-Life Science and the COVID-19 Outbreak
Yano, M., Matsuda, F., Sakuntabhai, A., & Hirota, S. (2021) · Economics, law, and institutions in Asia Pacific · doi:10.1007/978-981-16-5727-6 · Cited by 4
Can Fires, Night Lights, and Mobile Phones reveal behavioral fingerprints useful for Development?Preprint
Pastor-Escuredo, D., Savy, T., & Luengo-Oroz, M. A. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1501.00549 · Cited by 4
Lokanathan, S., & Gunaratne, R. L. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2522814 · Cited by 4
Buckee, C. O., & Engø‐Monsen, K. (2016) · arXiv (Cornell University) · doi:10.13140/rg.2.1.5027.5440 · Cited by 4
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Self-citation
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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