1
|
Giles JR, Zu Erbach-Schoenberg E, Tatem AJ, Gardner L, Bjørnstad ON, Metcalf CJE, Wesolowski A. The duration of travel impacts the spatial dynamics of infectious diseases. Proc Natl Acad Sci U S A 2020; 117:22572-22579. [PMID: 32839329 PMCID: PMC7486699 DOI: 10.1073/pnas.1922663117] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Humans can impact the spatial transmission dynamics of infectious diseases by introducing pathogens into susceptible environments. The rate at which this occurs depends in part on human-mobility patterns. Increasingly, mobile-phone usage data are used to quantify human mobility and investigate the impact on disease dynamics. Although the number of trips between locations and the duration of those trips could both affect infectious-disease dynamics, there has been limited work to quantify and model the duration of travel in the context of disease transmission. Using mobility data inferred from mobile-phone calling records in Namibia, we calculated both the number of trips between districts and the duration of these trips from 2010 to 2014. We fit hierarchical Bayesian models to these data to describe both the mean trip number and duration. Results indicate that trip duration is positively related to trip distance, but negatively related to the destination population density. The highest volume of trips and shortest trip durations were among high-density districts, whereas trips among low-density districts had lower volume with longer duration. We also analyzed the impact of including trip duration in spatial-transmission models for a range of pathogens and introduction locations. We found that inclusion of trip duration generally delays the rate of introduction, regardless of pathogen, and that the variance and uncertainty around spatial spread increases proportionally with pathogen-generation time. These results enhance our understanding of disease-dispersal dynamics driven by human mobility, which has potential to elucidate optimal spatial and temporal scales for epidemic interventions.
Collapse
Affiliation(s)
- John R Giles
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205;
| | - Elisabeth Zu Erbach-Schoenberg
- Department of Geography and the Environment, University of Southampton, Southampton SO17 1BJ, United Kingdom
- WorldPop, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Andrew J Tatem
- Department of Geography and the Environment, University of Southampton, Southampton SO17 1BJ, United Kingdom
- WorldPop, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Lauren Gardner
- Department of Civil and Systems Engineering, Johns Hopkins Whiting School of Engineering, Baltimore, MD 21218
| | - Ottar N Bjørnstad
- Department of Entomology, Pennsylvania State University, University Park, PA 16802
| | - C J E Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544
- Princeton School of Public and International Affairs, Princeton University, Princeton, NJ 08544
| | - Amy Wesolowski
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205
| |
Collapse
|
2
|
Wesolowski A, Zu Erbach-Schoenberg E, Tatem AJ, Lourenço C, Viboud C, Charu V, Eagle N, Engø-Monsen K, Qureshi T, Buckee CO, Metcalf CJE. Multinational patterns of seasonal asymmetry in human movement influence infectious disease dynamics. Nat Commun 2017; 8:2069. [PMID: 29234011 PMCID: PMC5727034 DOI: 10.1038/s41467-017-02064-4] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Accepted: 11/03/2017] [Indexed: 11/08/2022] Open
Abstract
Seasonal variation in human mobility is globally ubiquitous and affects the spatial spread of infectious diseases, but the ability to measure seasonality in human movement has been limited by data availability. Here, we use mobile phone data to quantify seasonal travel and directional asymmetries in Kenya, Namibia, and Pakistan, across a spectrum from rural nomadic populations to highly urbanized communities. We then model how the geographic spread of several acute pathogens with varying life histories could depend on country-wide connectivity fluctuations through the year. In all three countries, major national holidays are associated with shifts in the scope of travel. Within this broader pattern, the relative importance of particular routes also fluctuates over the course of the year, with increased travel from rural to urban communities after national holidays, for example. These changes in travel impact how fast communities are likely to be reached by an introduced pathogen.
Collapse
Affiliation(s)
- Amy Wesolowski
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD, 21205, USA.
| | - Elisabeth Zu Erbach-Schoenberg
- WorldPop, Department of Geography, University of Southampton, University Road, Southampton, SO17 1BJ, UK
- Flowminder Foundation, Roslagsgatan 17, SE-11355, Stockholm, Sweden
| | - Andrew J Tatem
- WorldPop, Department of Geography, University of Southampton, University Road, Southampton, SO17 1BJ, UK
- Flowminder Foundation, Roslagsgatan 17, SE-11355, Stockholm, Sweden
| | - Christopher Lourenço
- WorldPop, Department of Geography, University of Southampton, University Road, Southampton, SO17 1BJ, UK
- Clinton Health Access Initiative, 383 Dorchester Avenue Suite 400, Boston, MA, 02127, USA
| | - Cecile Viboud
- Fogarty International Center, National Institutes of Health, 31 Center Drive, Bethesda, MD, 20892, USA
| | - Vivek Charu
- Fogarty International Center, National Institutes of Health, 31 Center Drive, Bethesda, MD, 20892, USA
| | - Nathan Eagle
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | | | - Taimur Qureshi
- Telenor Research, Snarøyveien 30, N-1360, Fornebu, Norway
| | - Caroline O Buckee
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
- Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - C J E Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, 106A Guyot Lane, Princeton, NJ, 08544, USA
- Woodrow Wilson School, Princeton University, Robertson Hall, Princeton, NJ, 08544, USA
| |
Collapse
|
3
|
Zu Erbach-Schoenberg E, Alegana VA, Sorichetta A, Linard C, Lourenço C, Ruktanonchai NW, Graupe B, Bird TJ, Pezzulo C, Wesolowski A, Tatem AJ. Dynamic denominators: the impact of seasonally varying population numbers on disease incidence estimates. Popul Health Metr 2016; 14:35. [PMID: 27777514 PMCID: PMC5062910 DOI: 10.1186/s12963-016-0106-0] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2016] [Accepted: 10/05/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Reliable health metrics are crucial for accurately assessing disease burden and planning interventions. Many health indicators are measured through passive surveillance systems and are reliant on accurate estimates of denominators to transform case counts into incidence measures. These denominator estimates generally come from national censuses and use large area growth rates to estimate annual changes. Typically, they do not account for any seasonal fluctuations and thus assume a static denominator population. Many recent studies have highlighted the dynamic nature of human populations through quantitative analyses of mobile phone call data records and a range of other sources, emphasizing seasonal changes. In this study, we use mobile phone data to capture patterns of short-term human population movement and to map dynamism in population densities. METHODS We show how mobile phone data can be used to measure seasonal changes in health district population numbers, which are used as denominators for calculating district-level disease incidence. Using the example of malaria case reporting in Namibia we use 3.5 years of phone data to investigate the spatial and temporal effects of fluctuations in denominators caused by seasonal mobility on malaria incidence estimates. RESULTS We show that even in a sparsely populated country with large distances between population centers, such as Namibia, populations are highly dynamic throughout the year. We highlight how seasonal mobility affects malaria incidence estimates, leading to differences of up to 30 % compared to estimates created using static population maps. These differences exhibit clear spatial patterns, with likely overestimation of incidence in the high-prevalence zones in the north of Namibia and underestimation in lower-risk areas when compared to using static populations. CONCLUSION The results here highlight how health metrics that rely on static estimates of denominators from censuses may differ substantially once mobility and seasonal variations are taken into account. With respect to the setting of malaria in Namibia, the results indicate that Namibia may actually be closer to malaria elimination than previously thought. More broadly, the results highlight how dynamic populations are. In addition to affecting incidence estimates, these changes in population density will also have an impact on allocation of medical resources. Awareness of seasonal movements has the potential to improve the impact of interventions, such as vaccination campaigns or distributions of commodities like bed nets.
Collapse
Affiliation(s)
- Elisabeth Zu Erbach-Schoenberg
- WorldPop, Geography and Environment, University of Southampton, University Road, Southampton, SO17 1BJ UK ; Flowminder Foundation, Roslagsgatan 17, 113 55 Stockholm, Sweden
| | - Victor A Alegana
- WorldPop, Geography and Environment, University of Southampton, University Road, Southampton, SO17 1BJ UK ; Flowminder Foundation, Roslagsgatan 17, 113 55 Stockholm, Sweden
| | - Alessandro Sorichetta
- WorldPop, Geography and Environment, University of Southampton, University Road, Southampton, SO17 1BJ UK ; Flowminder Foundation, Roslagsgatan 17, 113 55 Stockholm, Sweden
| | - Catherine Linard
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Av. FD Roosevelt 50, 1050 Brussels, Belgium ; Department of Geography, Université de Namur, Rue de Bruxelles 61, 5000 Namur, Belgium
| | - Christoper Lourenço
- WorldPop, Geography and Environment, University of Southampton, University Road, Southampton, SO17 1BJ UK ; Clinton Health Access Initiative, Boston, MA USA
| | - Nick W Ruktanonchai
- WorldPop, Geography and Environment, University of Southampton, University Road, Southampton, SO17 1BJ UK ; Flowminder Foundation, Roslagsgatan 17, 113 55 Stockholm, Sweden
| | - Bonita Graupe
- Mobile Telecommunications Limited, Windhoek, Namibia
| | - Tomas J Bird
- WorldPop, Geography and Environment, University of Southampton, University Road, Southampton, SO17 1BJ UK ; Flowminder Foundation, Roslagsgatan 17, 113 55 Stockholm, Sweden
| | - Carla Pezzulo
- WorldPop, Geography and Environment, University of Southampton, University Road, Southampton, SO17 1BJ UK ; Flowminder Foundation, Roslagsgatan 17, 113 55 Stockholm, Sweden
| | - Amy Wesolowski
- Flowminder Foundation, Roslagsgatan 17, 113 55 Stockholm, Sweden ; Center for Communicable Disease Dynamics and Department of Epidemiology, Harvard, Boston, MA USA ; Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ USA
| | - Andrew J Tatem
- WorldPop, Geography and Environment, University of Southampton, University Road, Southampton, SO17 1BJ UK ; Flowminder Foundation, Roslagsgatan 17, 113 55 Stockholm, Sweden ; Fogarty International Center, National Institutes of Health, Bethesda, MD 20892 USA
| |
Collapse
|
4
|
Alegana VA, Atkinson PM, Lourenço C, Ruktanonchai NW, Bosco C, Erbach-Schoenberg EZ, Didier B, Pindolia D, Menach AL, Katokele S, Uusiku P, Tatem AJ. Erratum: Advances in mapping malaria for elimination: fine resolution modelling of Plasmodium falciparum incidence. Sci Rep 2016; 6:32908. [PMID: 27624488 PMCID: PMC5022030 DOI: 10.1038/srep32908] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
|
5
|
Ruktanonchai NW, Bhavnani D, Sorichetta A, Bengtsson L, Carter KH, Córdoba RC, Le Menach A, Lu X, Wetter E, Zu Erbach-Schoenberg E, Tatem AJ. Census-derived migration data as a tool for informing malaria elimination policy. Malar J 2016; 15:273. [PMID: 27169470 PMCID: PMC4864939 DOI: 10.1186/s12936-016-1315-5] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2016] [Accepted: 04/27/2016] [Indexed: 11/30/2022] Open
Abstract
Background Numerous countries around the world are approaching malaria elimination. Until global eradication is achieved, countries that successfully eliminate the disease will contend with parasite reintroduction through international movement of infected people. Human-mediated parasite mobility is also important within countries near elimination, as it drives parasite flows that affect disease transmission on a subnational scale. Methods Movement patterns exhibited in census-based migration data are compared with patterns exhibited in a mobile phone data set from Haiti to quantify how well migration data predict short-term movement patterns. Because short-term movement data were unavailable for Mesoamerica, a logistic regression model fit to migration data from three countries in Mesoamerica is used to predict flows of infected people between subnational administrative units throughout the region. Results Population flows predicted using census-based migration data correlated strongly with mobile phone-derived movements when used as a measure of relative connectivity. Relative population flows are therefore predicted using census data across Mesoamerica, informing the areas that are likely exporters and importers of infected people. Relative population flows are used to identify community structure, useful for coordinating interventions and elimination efforts to minimize importation risk. Finally, the ability of census microdata inform future intervention planning is discussed in a country-specific setting using Costa Rica as an example. Conclusions These results show long-term migration data can effectively predict the relative flows of infected people to direct malaria elimination policy, a particularly relevant result because migration data are generally easier to obtain than short-term movement data such as mobile phone records. Further, predicted relative flows highlight policy-relevant population dynamics, such as major exporters across the region, and Nicaragua and Costa Rica’s strong connection by movement of infected people, suggesting close coordination of their elimination efforts. Country-specific applications are discussed as well, such as predicting areas at relatively high risk of importation, which could inform surveillance and treatment strategies. Electronic supplementary material The online version of this article (doi:10.1186/s12936-016-1315-5) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Nick W Ruktanonchai
- WorldPop, Geography and Environment, University of Southampton, Southampton, SO17 1BJ, UK. .,Flowminder Foundation, Stockholm, Sweden.
| | | | - Alessandro Sorichetta
- WorldPop, Geography and Environment, University of Southampton, Southampton, SO17 1BJ, UK.,Flowminder Foundation, Stockholm, Sweden
| | - Linus Bengtsson
- WorldPop, Geography and Environment, University of Southampton, Southampton, SO17 1BJ, UK.,Flowminder Foundation, Stockholm, Sweden.,Karolinska Institute, Stockholm, Sweden
| | - Keith H Carter
- Pan American Health Organization/World Health Organization, Washington, DC, USA
| | - Roberto C Córdoba
- Department of Health Surveillance, Costa Rica Ministry of Health, San Jose, Costa Rica
| | | | - Xin Lu
- Flowminder Foundation, Stockholm, Sweden.,Karolinska Institute, Stockholm, Sweden
| | - Erik Wetter
- Flowminder Foundation, Stockholm, Sweden.,Stockholm School of Economics, Stockholm, Sweden
| | - Elisabeth Zu Erbach-Schoenberg
- WorldPop, Geography and Environment, University of Southampton, Southampton, SO17 1BJ, UK.,Flowminder Foundation, Stockholm, Sweden
| | - Andrew J Tatem
- WorldPop, Geography and Environment, University of Southampton, Southampton, SO17 1BJ, UK.,Flowminder Foundation, Stockholm, Sweden.,Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
| |
Collapse
|
6
|
Wilson R, Zu Erbach-Schoenberg E, Albert M, Power D, Tudge S, Gonzalez M, Guthrie S, Chamberlain H, Brooks C, Hughes C, Pitonakova L, Buckee C, Lu X, Wetter E, Tatem A, Bengtsson L. Rapid and Near Real-Time Assessments of Population Displacement Using Mobile Phone Data Following Disasters: The 2015 Nepal Earthquake. PLoS Curr 2016; 8:ecurrents.dis.d073fbece328e4c39087bc086d694b5c. [PMID: 26981327 PMCID: PMC4779046 DOI: 10.1371/currents.dis.d073fbece328e4c39087bc086d694b5c] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
INTRODUCTION Sudden impact disasters often result in the displacement of large numbers of people. These movements can occur prior to events, due to early warning messages, or take place post-event due to damages to shelters and livelihoods as well as a result of long-term reconstruction efforts. Displaced populations are especially vulnerable and often in need of support. However, timely and accurate data on the numbers and destinations of displaced populations are extremely challenging to collect across temporal and spatial scales, especially in the aftermath of disasters. Mobile phone call detail records were shown to be a valid data source for estimates of population movements after the 2010 Haiti earthquake, but their potential to provide near real-time ongoing measurements of population displacements immediately after a natural disaster has not been demonstrated. METHODS A computational architecture and analytical capacity were rapidly deployed within nine days of the Nepal earthquake of 25th April 2015, to provide spatiotemporally detailed estimates of population displacements from call detail records based on movements of 12 million de-identified mobile phones users. RESULTS Analysis shows the evolution of population mobility patterns after the earthquake and the patterns of return to affected areas, at a high level of detail. Particularly notable is the movement of an estimated 390,000 people above normal from the Kathmandu valley after the earthquake, with most people moving to surrounding areas and the highly-populated areas in the central southern area of Nepal. DISCUSSION This analysis provides an unprecedented level of information about human movement after a natural disaster, provided within a very short timeframe after the earthquake occurred. The patterns revealed using this method are almost impossible to find through other methods, and are of great interest to humanitarian agencies.
Collapse
Affiliation(s)
- Robin Wilson
- Flowminder Foundation, Stockholm, Sweden; Geography & Environment, University of Southampton, Southampton, UK
| | | | - Maximilian Albert
- Flowminder Foundation, Stockholm, Sweden; Faculty of Engineering & the Environment, University of Southampton, Southampton, UK
| | - Daniel Power
- Flowminder Foundation, Stockholm, Sweden; Electronics & Computer Science, University of Southampton, Southampton, UK
| | - Simon Tudge
- Flowminder Foundation, Stockholm, Sweden; Electronics & Computer Science, University of Southampton, Southampton, UK
| | - Miguel Gonzalez
- Flowminder Foundation, Stockholm, Sweden; Electronics & Computer Science, University of Southampton, Southampton, UK
| | - Sam Guthrie
- Flowminder Foundation, Stockholm, Sweden; Politics & International Relations, University of Southampton, Southampton, UK
| | - Heather Chamberlain
- Flowminder Foundation, Stockholm, Sweden; Geography & Environment, University of Southampton, Southampton, UK
| | - Christopher Brooks
- Flowminder Foundation, Stockholm, Sweden; Geography & Environment, University of Southampton, Southampton, UK
| | - Christopher Hughes
- Flowminder Foundation, Stockholm, Sweden; Electronics & Computer Science, University of Southampton, Southampton, UK; Oxford Internet Institute, University of Oxford, Southampton, UK
| | - Lenka Pitonakova
- Flowminder Foundation, Stockholm, Sweden; Electronics & Computer Science, University of Southampton, Southampton, UK
| | - Caroline Buckee
- Flowminder Foundation, Stockholm, Sweden; Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, USA
| | - Xin Lu
- Flowminder Foundation, Stockholm, Sweden; Department of Public Health Sciences, Karolinska Institute, Stockholm, Sweden; College of Information System and Management, National University of Defense Technology, Changsha, China
| | - Erik Wetter
- Flowminder Foundation, Stockholm, Sweden; Stockholm School of Economics, Stockholm, Sweden
| | - Andrew Tatem
- Flowminder Foundation, Stockholm, Sweden; Geography & Environment, University of Southampton, Southampton, UK
| | - Linus Bengtsson
- Flowminder Foundation, Stockholm, Sweden; Dept. of Public Health Sciences, Karolinska Institute, Sweden
| |
Collapse
|