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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
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.
Cited by
Sorted by citations
Items 201–300 of 991
Sumner, T., Orton, R. J., Green, D. M., Kao, R. R., & Gubbins, S. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005470 · Cited by 52
Kuchler, T., Russel, D., & Stroebel, J. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3587255 · Cited by 52
Reactive vaccination in the presence of disease hotspots
Azman, A. S., & Lessler, J. (2014) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2014.1341 · Cited by 51
Yang, P., Qi, J., Zhang, S., Wang, X., Bi, G., Yang, Y., Sheng, B., & Yang, G. (2020) · PLoS ONE · doi:10.1371/journal.pone.0236857 · Cited by 51
Mapping Malaria Risk in Low Transmission Settings: Challenges and Opportunities
Sturrock, H. J. W., Bennett, A. F., Midekisa, A. A., Gosling, R. D., Gething, P. W., & Greenhouse, B. (2016) · Trends in Parasitology · doi:10.1016/j.pt.2016.05.001 · Cited by 55
Flyverbom, M., Madsen, A. K., & Rasche, A. (2017) · The Information Society · doi:10.1080/01972243.2016.1248611 · Cited by 51
The rise and fall of malaria under land-use change in frontier regions
Baeza, A., Santos‐Vega, M., Dobson, A. P., & Pascual, M. (2017) · Nature Ecology & Evolution · doi:10.1038/s41559-017-0108 · Cited by 58
Optimizing Spatial Allocation of COVID‐19 Vaccine by Agent‐Based Spatiotemporal Simulations
Zhou, S., Zhou, S., Zheng, Z., & Lu, J. (2021) · GeoHealth · doi:10.1029/2021gh000427 · Cited by 48
Fine-scale heterogeneity in population density predicts wave dynamics in dengue epidemics
Romeo-Aznar, V., Freitas, L. P., Cruz, O. G., King, A. A., & Pascual, M. (2022) · Nature Communications · doi:10.1038/s41467-022-28231-w · Cited by 50
The Stability of Malaria Elimination
Chiyaka, C., Tatem, A. J., Cohen, J., Gething, P., Johnston, G., Gosling, R., Laxminarayan, R., Hay, S. I., & Smith, D. (2013) · Science · doi:10.1126/science.1229509 · Cited by 43
Self-citationBaidjoe, A. Y., Stevenson, J. C., Knight, P., Stone, W. J., Stresman, G. H., Osoti, V., Makori, E., Owaga, C., Odongo, W., China, P., et al. (2016) · Malaria Journal · doi:10.1186/s12936-016-1362-y · Cited by 49
Carrasco‐Escobar, G., Miranda-Alban, J., Fernández-Miñope, C., Brouwer, K. C., Torres, K., Calderon, M. M., Gamboa, D., Llanos‐Cuentas, A., & Vinetz, J. M. (2017) · Malaria Journal · doi:10.1186/s12936-017-2063-x · Cited by 49
Li, Q., Bessell, L., Xiao, X., Fan, C. H., Gao, X., & Mostafavi, A. (2021) · Royal Society Open Science · doi:10.1098/rsos.201209 · Cited by 51
Exploring nationally and regionally defined models for large area population mapping
Gaughan, A. E., Stevens, F. R., Linard, C., Patel, N. N., & Tatem, A. J. (2014) · International Journal of Digital Earth · doi:10.1080/17538947.2014.965761 · Cited by 46
Self-citationVector-borne epidemics driven by human mobility
Soriano‐Paños, D., Arias-Castro, J. H., Reyna-Lara, A., Martínez, H. J., Meloni, S., & Gómez‐Gardeñes, J. (2020) · Physical Review Research · doi:10.1103/physrevresearch.2.013312 · Cited by 46
HIV transmission and source–sink dynamics in sub-Saharan Africa
Okano, J. T., Sharp, K., Valdano, E., Palk, L., & Blower, S. M. (2020) · The Lancet HIV · doi:10.1016/s2352-3018(19)30407-2 · Cited by 48
Estimating sources and sinks of malaria parasites in Madagascar
Ihantamalala, F. A., Herbreteau, V., Rakotoarimanana, F. M. J., Rakotondramanga, J. M., Cauchemez, S., Rahoilijaona, B., Pennober, G., Buckee, C. O., Rogier, C., Metcalf, C. J. E., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-06290-2 · Cited by 46
Self-citationDeterminants of Malaria Transmission at the Population LevelPreprint
Bousema, T., & Drakeley, C. (2017) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a025510 · Cited by 48
Shoval, N., Kwan, M., Reinau, K. H., & Henrik Harder, B. (2013) · Geoforum · doi:10.1016/j.geoforum.2013.09.016 · Cited by 46
Martinez, P. P., King, A. A., Yunus, M., Faruque, A. S. G., & Pascual, M. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1518977113 · Cited by 46
Seasonal Population Movements and the Surveillance and Control of Infectious Diseases
Buckee, C. O., Tatem, A. J., & Metcalf, C. J. E. (2016) · Trends in Parasitology · doi:10.1016/j.pt.2016.10.006 · Cited by 47
Self-citationBrousse, O., Wouters, H., Demuzere, M., Thiery, W., de Walle, J. V., & van Lipzig, N. P. M. (2020) · International Journal of Climatology · doi:10.1002/joc.6477 · Cited by 48
Yin, L., Zhang, H., Li, Y., Liu, K., Chen, T., Luo, W. P., Lai, S., Li, Y., Tang, X., Li, N., et al. (2021) · Journal of The Royal Society Interface · doi:10.1098/rsif.2021.0112 · Cited by 49
Prediction of future malaria hotspots under climate change in sub-Saharan Africa
Semakula, H. M., Song, G., Achuu, S. P., Shen, M., Chen, J., Mukwaya, P. I., Oulu, M., Mwendwa, P., Abalo, J., & Zhang, S. (2017) · Climatic Change · doi:10.1007/s10584-017-1996-y · Cited by 50
Mao, H., Shuai, X., Ahn, Y., & Bollen, J. (2015) · EPJ Data Science · doi:10.1140/epjds/s13688-015-0053-1 · Cited by 42
Taha, K., & Yoo, P. D. (2015) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2015.2510826 · Cited by 46
Kwan, M., Xiao, N., & Ding, G. (2014) · Geographical Analysis · doi:10.1111/gean.12040 · Cited by 44
Big Data and Social Indicators: Actual Trends and New Perspectives
di Bella, E., Leporatti, L., & Maggino, F. (2016) · Social Indicators Research · doi:10.1007/s11205-016-1495-y · Cited by 44
A New Privacy Breach: User Trajectory Recovery From Aggregated Mobility Data
Tu, Z., Xu, F., Li, Y., Zhang, P., & Jin, D. (2018) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2018.2829173 · Cited by 43
Li, Z., Li, X., Porter, D. E., Zhang, J., Jiang, Y., Olatosi, B., & Weissman, S. (2020) · JMIR Research Protocols · doi:10.2196/24432 · Cited by 44
Unveiling Spatial Epidemiology of HIV with Mobile Phone Data
Brdar, S., Gavrić, K., Culibrk, D. R., & Crnojevic, V. S. (2016) · Scientific Reports · doi:10.1038/srep19342 · Cited by 43
Nelson, M. I., Lloyd‐Smith, J. O., Simonsen, L., Rambaut, A., Holmes, E. C., Chowell, G., Miller, M. A., Spiro, D. J., Grenfell, B. T., & Viboud, C. G. (2018) · Epidemics · doi:10.1016/j.epidem.2018.10.004 · Cited by 43
Mapping road network communities for guiding disease surveillance and control strategies
Strano, E., Viana, M. P., Sorichetta, A., & Tatem, A. J. (2018) · Scientific Reports · doi:10.1038/s41598-018-22969-4 · Cited by 43
Self-citationIntercity Population Migration Conditioned by City Industry Structures
Wang, Y., Li, X., Yao, X., Li, S., & Liu, Y. (2021) · Annals of the American Association of Geographers · doi:10.1080/24694452.2021.1977110 · Cited by 43
Forecasting the scale of the COVID-19 epidemic in KenyaPreprint
Brand, S. P. C., Aziza, R., Kombe, I. K., Agoti, C. N., Hilton, J., Rock, K. S., Parisi, A., Nokes, D. J., Keeling, M. J., & Barasa, E. (2020) · medRxiv · doi:10.1101/2020.04.09.20059865 · Cited by 43
How many days are enough?: capturing routine human mobility
Stanley, K., Yoo, E.-H., Paul, T., & Bell, S. (2018) · International Journal of Geographical Information Science · doi:10.1080/13658816.2018.1434888 · Cited by 42
A general approach to detecting migration events in digital trace data
Chi, G., Lin, F., Chi, G., & Blumenstock, J. E. (2020) · PLoS ONE · doi:10.1371/journal.pone.0239408 · Cited by 41
A mathematical model of the impact of present and future malaria vaccines
Wenger, E. A., & Eckhoff, P. A. (2013) · Malaria Journal · doi:10.1186/1475-2875-12-126 · Cited by 41
Does insecticide resistance contribute to heterogeneities in malaria transmission in The Gambia?
Opondo, K., Weetman, D., Jawara, M., Diatta, M., Fofana, A., Crombé, F., Mwesigwa, J., D’Alessandro, U., & Donnelly, M. J. (2016) · Malaria Journal · doi:10.1186/s12936-016-1203-z · Cited by 40
Improving official statistics in emerging markets using machine learning and mobile phone data
Jahani, E., Sundsøy, P., Bjelland, J., Bengtsson, L., Pentland, A., & de Montjoye, Y.-A. (2017) · EPJ Data Science · doi:10.1140/epjds/s13688-017-0099-3 · Cited by 42
Predicting customer’s gender and age depending on mobile phone data
Al-Zuabi, I. M., Jafar, A., & Aljoumaa, K. (2019) · Journal Of Big Data · doi:10.1186/s40537-019-0180-9 · Cited by 42
The duration of travel impacts the spatial dynamics of infectious diseases
Giles, J. R., zu Erbach-Schoenberg, E., Tatem, A. J., Gardner, L., Bjørnstad, O. N., Metcalf, C. J. E., & Wesolowski, A. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1922663117 · Cited by 40
Self-citationAshine, T., Eyasu, A., Ebstie, Y. A., Simma, E. A., Zemene, E., Epstein, A., Brown, R., Negash, N., Kochora, A., Reynolds, A. M., et al. (2024) · Parasites & Vectors · doi:10.1186/s13071-024-06243-3 · Cited by 40
Bei, A. K., Niang, M., Dème, A. B., Daniels, R. F., Sarr, F. D., Sokhna, C., Talla, C., Faye, J., Diagne, N., Doucouré, S., et al. (2017) · The Journal of Infectious Diseases · doi:10.1093/infdis/jix580 · Cited by 41
The Impact of Human Mobility on HIV Transmission in Kenya
Msigwa, A. I., Mureithi, E., & Sumpter, D. J. T. (2015) · PLoS ONE · doi:10.1371/journal.pone.0142805 · Cited by 40
Krieger, M. S., Denison, C. E., Anderson, T. L., Nowak, M. A., & Hill, A. L. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008010 · Cited by 42
Can we model cultural ecosystem services, and are we measuring the right things?
Jones, L., Boeri, M., Christie, M., Durance, I., Evans, K. L., Fletcher, D. H., Harrison, L. J., Jørgensen, A., Masante, D., McGinlay, J., et al. (2021) · People and Nature · doi:10.1002/pan3.10271 · Cited by 40
Single-case experimental research designs.
Kazdin, A. E. (2015) · Methodological issues and strategies in clinical research (4th ed.). · doi:10.1037/14805-029 · Cited by 39
Why We Need Crowdsourced Data in Infectious Disease Surveillance
Chunara, R., Smolinski, M. S., & Brownstein, J. S. (2013) · Current Infectious Disease Reports · doi:10.1007/s11908-013-0341-5 · Cited by 39
Unveiling patterns of international communities in a global city using mobile phone data
Bajardi, P., Delfino, M., Panisson, A., Petri, G., & Tizzoni, M. (2015) · EPJ Data Science · doi:10.1140/epjds/s13688-015-0041-5 · Cited by 40
Fola, A. A., Nate, E., Harrison, G. L. A., Barnadas, C., Hetzel, M. W., Iga, J., Siba, P., Müeller, I., & Barry, A. E. (2017) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2017.11.028 · Cited by 41
Epidemiology of the zoonotic malaria Plasmodium knowlesi in changing landscapes
Cuenca, P. R., Key, S., Jumail, A., Surendra, H., Ferguson, H. M., DRAKELEY, C. J., & Fornace, K. (2021) · Advances in Parasitology/Advances in parasitology · doi:10.1016/bs.apar.2021.08.006 · Cited by 40
Miyazaki, H., Nagai, M., & Shibasaki, R. (2015) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi4041936 · Cited by 38
Lai, S., Wardrop, N. A., Huang, Z., Bosco, C., Sun, J., Bird, T. J., Wesolowski, A., Zhou, S., Zhang, Q., Zheng, C., et al. (2016) · Scientific Reports · doi:10.1038/srep39524 · Cited by 38
Self-citationLiu, Q., Yang, J., Deng, M., Song, C., & Liu, W. (2021) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2021.1899184 · Cited by 38
Fuller, D. O., Troyo, A., Alimi, T. O., & Beier, J. C. (2014) · Applied Geography · doi:10.1016/j.apgeog.2014.01.002 · Cited by 38
Assessing reliable human mobility patterns from higher order memory in mobile communications
Matamalas, J. T., Domenico, M. D., & Arenas, A. (2016) · Journal of The Royal Society Interface · doi:10.1098/rsif.2016.0203 · Cited by 34
Calling in sick: impacts of fever on intra-urban human mobility
Perkins, T. A., Paz‐Soldán, V. A., Stoddard, S. T., Morrison, A. C., Forshey, B. M., Long, K. C., Halsey, E. S., Kochel, T. J., Elder, J. P., Kitron, U. D., et al. (2016) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2016.0390 · Cited by 37
Optimizing respiratory virus surveillance networks using uncertainty propagation
Pei, S., Teng, X., Lewis, P., & Shaman, J. L. (2021) · Nature Communications · doi:10.1038/s41467-020-20399-3 · Cited by 37
Mobile Technology Trends and their Potential for Agricultural DevelopmentPreprint
Baummller, H. (2013) · SSRN Electronic Journal · doi:10.2139/ssrn.2359465 · Cited by 37
Davis, J. K., Gebrehiwot, T., Lake, M. W., Awoke, W., Mihretie, A., Nekorchuk, D. M., & Wimberly, M. C. (2019) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2019.06.010 · Cited by 36
Statistical properties of urban mobility from location-based travel networks
Tang, J., Zhang, S., Zhang, W., Liu, F., Zhang, W., & Wang, Y. (2016) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2016.06.031 · Cited by 36
Using Social Media to Detect and Locate Wildfires
Boulton, C. A., Shotton, H., & Williams, H. T. P. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v10i2.14850 · Cited by 36
Wu, H., Liu, L., Yu, Y., Peng, Z., Jiao, H., & Niu, Q. (2019) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi8070313 · Cited by 36
High-Performance Modelling and Simulation for Big Data Applications
Kołodziej, J., & González–Vélez, H. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-16272-6 · Cited by 37
Gibbs, H. P., Nightingale, E., Liu, Y., Cheshire, J. A., Danon, L., Smeeth, L. L., Pearson, C. A. B., Grundy, C., LSHTM CMMID COVID-19 working group, Kucharski, A. J., et al. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009162 · Cited by 35
Alzaabi, M., Taha, K., & Martin, T. (2015) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2015.2451073 · Cited by 36
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Miller, A. C., Foti, N. J., Lewnard, J. A., Jewell, N. P., Guestrin, C., & Fox, E. B. (2020) · medRxiv · doi:10.1101/2020.05.07.20094441 · Cited by 36
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Jacobsen, K. A., Burch, M. G., Tien, J. H., & Rempała, G. A. (2018) · Journal of Biological Dynamics · doi:10.1080/17513758.2018.1515993 · Cited by 35
Jones, K. H., Daniels, H., Heys, S., & Ford, D. V. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.9974 · Cited by 35
Hast, M. A., Searle, K. M., Chaponda, M., Lupiya, J. S., Lubinda, J., Sikalima, J., Kobayashi, T., Shields, T., Mulenga, M., Lessler, J., et al. (2019) · International Journal of Health Geographics · doi:10.1186/s12942-019-0183-y · Cited by 35
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Soriano-Paños, D., Ghoshal, G., Arenas, A., & Gómez-Gardeñes, J. (2020) · Journal of Statistical Mechanics Theory and Experiment · doi:10.1088/1742-5468/ab6a04 · Cited by 35
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Ruktanonchai, N., Bhavnani, D., Sorichetta, A., Bengtsson, L., Carter, K. H., Córdoba, R., Menach, A. L., Lu, X. B., Wetter, E. W., zu Erbach-Schoenberg, E., et al. (2016) · Malaria Journal · doi:10.1186/s12936-016-1315-5 · Cited by 36
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Mao, L., Yin, L., Song, X., & Mei, S. (2016) · Acta Tropica · doi:10.1016/j.actatropica.2016.06.029 · Cited by 35
Social and spatial ethnic segregation
Blumenstock, J. E., & Fratamico, L. (2013) · ACM Symposium on Computing for Development (ACM DEV) · doi:10.1145/2537052.2537061 · Cited by 34
Noor, A. M., Uusiku, P., Kamwi, R., Katokele, S. T., Ntomwa, B., Alegana, V. A., & Snow, R. W. (2013) · BMC Infectious Diseases · doi:10.1186/1471-2334-13-184 · Cited by 34
Self-citationImpact of temporal scales and recurrent mobility patterns on the unfolding of epidemics
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Hlaing, T., Wai, K. T., Oo, T., Sint, N., Min, T., Myar, S., Lon, K. N., Naing, M. M., Tun, T. T., Maung, N., et al. (2015) · BMC Public Health · doi:10.1186/s12889-015-2241-0 · Cited by 34
Finding spatial outliers in collective mobility patterns coupled with social ties
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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.
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