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Khalifa A, Beres LK, Anok A, Mbabali I, Katabalwa C, Mulamba J, Thomas AG, Bugos E, Nakigozi G, Chang LW, Grabowski MK. Leveraging Ecological Momentary Assessment Data to Characterize Individual Mobility: Exploratory Pilot Study in Rural Uganda. JMIR Form Res 2024; 8:e54207. [PMID: 38857493 PMCID: PMC11196909 DOI: 10.2196/54207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 03/28/2024] [Accepted: 04/12/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND The geographical environments within which individuals conduct their daily activities may influence health behaviors, yet little is known about individual-level geographic mobility and specific, linked behaviors in rural low- and middle-income settings. OBJECTIVE Nested in a 3-month ecological momentary assessment intervention pilot trial, this study aims to leverage mobile health app user GPS data to examine activity space through individual spatial mobility and locations of reported health behaviors in relation to their homes. METHODS Pilot trial participants were recruited from the Rakai Community Cohort Study-an ongoing population-based cohort study in rural south-central Uganda. Participants used a smartphone app that logged their GPS coordinates every 1-2 hours for approximately 90 days. They also reported specific health behaviors (alcohol use, cigarette smoking, and having condomless sex with a non-long-term partner) via the app that were both location and time stamped. In this substudy, we characterized participant mobility using 3 measures: average distance (kilometers) traveled per week, number of unique locations visited (deduplicated points within 25 m of one another), and the percentage of GPS points recorded away from home. The latter measure was calculated using home buffer regions of 100 m, 400 m, and 800 m. We also evaluated the number of unique locations visited for each specific health behavior, and whether those locations were within or outside the home buffer regions. Sociodemographic information, mobility measures, and locations of health behaviors were summarized across the sample using descriptive statistics. RESULTS Of the 46 participants with complete GPS data, 24 (52%) participants were men, 30 (65%) participants were younger than 35 years, and 33 (72%) participants were in the top 2 socioeconomic status quartiles. On median, participants traveled 303 (IQR 152-585) km per week. Over the study period, participants on median recorded 1292 (IQR 963-2137) GPS points-76% (IQR 58%-86%) of which were outside their 400-m home buffer regions. Of the participants reporting drinking alcohol, cigarette smoking, and engaging in condomless sex, respectively, 19 (83%), 8 (89%), and 12 (86%) reported that behavior at least once outside their 400-m home neighborhood and across a median of 3.0 (IQR 1.5-5.5), 3.0 (IQR 1.0-3.0), and 3.5 (IQR 1.0-7.0) unique locations, respectively. CONCLUSIONS Among residents in rural Uganda, an ecological momentary assessment app successfully captured high mobility and health-related behaviors across multiple locations. Our findings suggest that future mobile health interventions in similar settings can benefit from integrating spatial data collection using the GPS technology in mobile phones. Leveraging such individual-level GPS data can inform place-based strategies within these interventions for promoting healthy behavior change.
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Affiliation(s)
- Aleya Khalifa
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States
- ICAP at Columbia University, New York, NY, United States
| | - Laura K Beres
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | - Aggrey Anok
- Rakai Health Sciences Program, Kalisizo, Uganda
| | | | | | | | - Alvin G Thomas
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States
- Department of Surgery, Johns Hopkins University, Baltimore, MD, United States
| | - Eva Bugos
- Pritzker School of Medicine, University of Chicago, Chicago, IL, United States
- Department of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Department of Internal Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, United States
| | | | - Larry W Chang
- Rakai Health Sciences Program, Kalisizo, Uganda
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - M Kate Grabowski
- Rakai Health Sciences Program, Kalisizo, Uganda
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
- Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, United States
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Khalifa A, Kim B, Regan S, Moline T, Chaix B, Chen YT, Schneider J, Duncan DT. Examination of multidimensional geographic mobility and sexual behaviour among Black cisgender sexually minoritized men in Chicago. GEOSPATIAL HEALTH 2024; 19:10.4081/gh.2024.1273. [PMID: 38752862 PMCID: PMC11194757 DOI: 10.4081/gh.2024.1273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 04/13/2024] [Indexed: 06/06/2024]
Abstract
Black sexually minoritized men (BSMM) are the most likely to acquire HIV in Chicago- a racially segregated city where their daily travel may confer different HIV-related risks. From survey and GPS data among participants of the Neighbourhoods and Networks Cohort Study, we examined spatial (proportion of total activity space away from home), temporal (proportion of total GPS points away from home), and motivation-specific (discordance between residential and frequented sex or socializing neighbourhoods) dimensions of mobility. To identify potential drivers of BSMM's risk, we then examined associations between mobility and sexual behaviours known to cause HIV transmission: condomless anal sex, condomless anal sex with a casual partner, transactional sex, group sex, and sex-drug use. Multivariable logistic regression models assessed associations. Of 269 cisgender BSMM, most were 20-29 years old, identified as gay, and lowincome. On average, 96.9% (Standard Deviation: 3.7%) of participants' activity space and 53.9% (Standard Deviation: 38.1%) of participants' GPS points occurred outside their 800m home network buffer. After covariate adjustment, those who reported sex away from home were twice as likely to report condomless sex (Odds Ratio: 2.02, [95% Confidence Interval (CI): 1.08, 3.78]). Those who reported socializing away from home were four times more likely to have condomless sex with a casual partner (Odds Ratio: 4.16 [CI: 0.99, 29.0]). BSMM are on the move in Chicago, but only motivation-specific mobility may increase HIV transmission risk. Multidimensional investigations of mobility can inform place-based strategies for HIV service delivery.
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Affiliation(s)
- Aleya Khalifa
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA; ICAP at Columbia University, New York, NY.
| | - Byoungjun Kim
- Department of Surgery, New York University Grossman School of Medicine, New York, NY.
| | - Seann Regan
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.
| | - Tyrone Moline
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY.
| | - Basile Chaix
- Sorbonne Université, INSERM, Institut Pierre Louis d'Épidémiologie et de Santé Publique, Némésis Research Team, Paris.
| | - Yen-Tyng Chen
- Edward J. Bloustein School of Planning and Public Policy, Rutgers University, New Brunswick, NJ.
| | - John Schneider
- Department of Medicine, Public Health Sciences, University of Chicago, Chicago, IL.
| | - Dustin T Duncan
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY.
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Hoek Spaans R, Mkumbwa A, Nasoni P, Jones CM, Stanton MC. Impact of four years of annually repeated indoor residual spraying (IRS) with Actellic 300CS on routinely reported malaria cases in an agricultural setting in Malawi. PLOS GLOBAL PUBLIC HEALTH 2024; 4:e0002264. [PMID: 38656965 PMCID: PMC11042720 DOI: 10.1371/journal.pgph.0002264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 04/01/2024] [Indexed: 04/26/2024]
Abstract
Indoor residual spraying (IRS) is one of the main vector control tools used in malaria prevention. This study evaluates IRS in the context of a privately run campaign conducted across a low-lying, irrigated, sugarcane estate from Illovo Sugar, in the Chikwawa district of Malawi. The effect of Actellic 300CS annual spraying over four years (2015-2018) was assessed using a negative binomial mixed effects model, in an area where pyrethroid resistance has previously been identified. With an unadjusted incidence rate ratio (IRR) of 0.38 (95% CI: 0.32-0.45) and an adjusted IRR of 0.50 (95% CI: 0.42-0.59), IRS has significantly contributed to a reduction in case incidence rates at Illovo, as compared to control clinics and time points outside of the six month protective period. This study shows how the consistency of a privately run IRS campaign can improve the health of employees. More research is needed on the duration of protection and optimal timing of IRS programmes.
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Affiliation(s)
- Remy Hoek Spaans
- Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | | | | | - Christopher M. Jones
- Illovo Sugar Malawi, Nchalo, Malawi
- Malawi-Liverpool-Wellcome Trust, Blantyre, Malawi
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Pepey A, Souris M, Kim S, Obadia T, Chy S, Ea M, Ouk S, Remoue F, Sovannaroth S, Mueller I, Witkowski B, Vantaux A. Comparing malaria risk exposure in rural Cambodia population using GPS tracking and questionnaires. Malar J 2024; 23:75. [PMID: 38475843 DOI: 10.1186/s12936-024-04890-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 02/23/2024] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND The Great Mekong Subregion has attained a major decline in malaria cases and fatalities over the last years, but residual transmission hotspots remain, supposedly fueled by forest workers and migrant populations. This study aimed to: (i) characterize the fine-scale mobility of forest-goers and understand links between their daily movement patterns and malaria transmission, using parasites detection via real time polymerase chain reaction (RT PCR) and the individual exposure to Anopheles bites by quantification of anti-Anopheles saliva antibodies via enzyme-linked immunosorbent assay; (ii) assess the concordance of questionnaires and Global Positioning System (GPS) data loggers for measuring mobility. METHODS Two 28 day follow-ups during dry and rainy seasons, including a GPS tracking, questionnaires and health examinations, were performed on male forest goers representing the population at highest risk of infection. Their time spent in different land use categories and demographic data were analyzed in order to understand the risk factors driving malaria in the study area. RESULTS Malaria risk varied with village forest cover and at a resolution of only a few kilometers: participants from villages outside the forest had the highest malaria prevalence compared to participants from forest fringe's villages. The time spent in a specific environment did not modulate the risk of malaria, in particular the time spent in forest was not associated with a higher probability to detect malaria among forest-goers. The levels of antibody response to Anopheles salivary peptide among participants were significantly higher during the rainy season, in accordance with Anopheles mosquito density variation, but was not affected by sociodemographic and mobility factors. The agreement between GPS and self-reported data was only 61.9% in reporting each kind of visited environment. CONCLUSIONS In a context of residual malaria transmission which was mainly depicted by P. vivax asymptomatic infections, the implementation of questionnaires, GPS data-loggers and quantification of anti-saliva Anopheles antibodies on the high-risk group were not powerful enough to detect malaria risk factors associated with different mobility behaviours or time spent in various environments. The joint implementation of GPS trackers and questionnaires allowed to highlight the limitations of both methodologies and the benefits of using them together. New detection and follow-up strategies are still called for.
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Affiliation(s)
- Anaïs Pepey
- Malaria Molecular Epidemiology Unit, Institut Pasteur du Cambodge, 5 Blvd Monivong, Phnom Penh 120 210, Phnom Penh, BP983, Cambodia.
| | - Marc Souris
- UMR Unité des Virus Emergents, UVE: Aix-Marseille Univ-IRD 190-Inserm 1207-IHU 5 Méditerranée Infection, 13005, Marseille, France
| | - Saorin Kim
- Malaria Molecular Epidemiology Unit, Institut Pasteur du Cambodge, 5 Blvd Monivong, Phnom Penh 120 210, Phnom Penh, BP983, Cambodia
| | - Thomas Obadia
- Institut Pasteur, G5 Infectious Disease Epidemiology and Analytics, Université Paris Cité, 75015, Paris, France
- Institut Pasteur, Bioinformatics and Biostatistics Hub, Université Paris Cité, 75015, Paris, France
| | - Sophy Chy
- Malaria Molecular Epidemiology Unit, Institut Pasteur du Cambodge, 5 Blvd Monivong, Phnom Penh 120 210, Phnom Penh, BP983, Cambodia
| | - Malen Ea
- Malaria Molecular Epidemiology Unit, Institut Pasteur du Cambodge, 5 Blvd Monivong, Phnom Penh 120 210, Phnom Penh, BP983, Cambodia
| | - Sivkeng Ouk
- Malaria Molecular Epidemiology Unit, Institut Pasteur du Cambodge, 5 Blvd Monivong, Phnom Penh 120 210, Phnom Penh, BP983, Cambodia
| | - Franck Remoue
- UMR MIVEGEC, IRD, CNRS, University of Montpellier, Montpellier, France
| | - Siv Sovannaroth
- National Centre for Parasitology Entomology and Malaria Control (CNM), Phnom Penh 120 801, Phnom Penh, Cambodia
| | - Ivo Mueller
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, University of Melbourne, Melbourne, VIC, Australia
| | - Benoit Witkowski
- Malaria Molecular Epidemiology Unit, Institut Pasteur du Cambodge, 5 Blvd Monivong, Phnom Penh 120 210, Phnom Penh, BP983, Cambodia
- Genetic and Biology of Plasmodium Unit, Institut Pasteur de Madagascar, Antananarivo, Madagascar
| | - Amélie Vantaux
- Malaria Molecular Epidemiology Unit, Institut Pasteur du Cambodge, 5 Blvd Monivong, Phnom Penh 120 210, Phnom Penh, BP983, Cambodia
- Genetic and Biology of Plasmodium Unit, Institut Pasteur de Madagascar, Antananarivo, Madagascar
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Pearson AL, Tribby C, Brown CD, Yang JA, Pfeiffer K, Jankowska MM. Systematic review of best practices for GPS data usage, processing, and linkage in health, exposure science and environmental context research. BMJ Open 2024; 14:e077036. [PMID: 38307539 PMCID: PMC10836389 DOI: 10.1136/bmjopen-2023-077036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 01/16/2024] [Indexed: 02/04/2024] Open
Abstract
Global Positioning System (GPS) technology is increasingly used in health research to capture individual mobility and contextual and environmental exposures. However, the tools, techniques and decisions for using GPS data vary from study to study, making comparisons and reproducibility challenging. OBJECTIVES The objectives of this systematic review were to (1) identify best practices for GPS data collection and processing; (2) quantify reporting of best practices in published studies; and (3) discuss examples found in reviewed manuscripts that future researchers may employ for reporting GPS data usage, processing and linkage of GPS data in health studies. DESIGN A systematic review. DATA SOURCES Electronic databases searched (24 October 2023) were PubMed, Scopus and Web of Science (PROSPERO ID: CRD42022322166). ELIGIBILITY CRITERIA Included peer-reviewed studies published in English met at least one of the criteria: (1) protocols involving GPS for exposure/context and human health research purposes and containing empirical data; (2) linkage of GPS data to other data intended for research on contextual influences on health; (3) associations between GPS-measured mobility or exposures and health; (4) derived variable methods using GPS data in health research; or (5) comparison of GPS tracking with other methods (eg, travel diary). DATA EXTRACTION AND SYNTHESIS We examined 157 manuscripts for reporting of best practices including wear time, sampling frequency, data validity, noise/signal loss and data linkage to assess risk of bias. RESULTS We found that 6% of the studies did not disclose the GPS device model used, only 12.1% reported the per cent of GPS data lost by signal loss, only 15.7% reported the per cent of GPS data considered to be noise and only 68.2% reported the inclusion criteria for their data. CONCLUSIONS Our recommendations for reporting on GPS usage, processing and linkage may be transferrable to other geospatial devices, with the hope of promoting transparency and reproducibility in this research. PROSPERO REGISTRATION NUMBER CRD42022322166.
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Affiliation(s)
- Amber L Pearson
- CS Mott Department of Public Health, Michigan State University, Flint, MI, USA
| | - Calvin Tribby
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, USA
| | - Catherine D Brown
- Department of Geography, Environment and Spatial Sciences, Michigan State University, East Lansing, Michigan, USA
| | - Jiue-An Yang
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, USA
| | - Karin Pfeiffer
- Department of Kinesiology, Michigan State University, East Lansing, Michigan, USA
| | - Marta M Jankowska
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, USA
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Collyer BS, Truscott JE, Mwandawiro CS, Njenga SM, Anderson RM. How important is the spatial movement of people in attempts to eliminate the transmission of human helminth infections by mass drug administration? Philos Trans R Soc Lond B Biol Sci 2023; 378:20220273. [PMID: 37598700 PMCID: PMC10440163 DOI: 10.1098/rstb.2022.0273] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 04/02/2023] [Indexed: 08/22/2023] Open
Abstract
Human mobility contributes to the spatial dynamics of many infectious diseases, and understanding these dynamics helps us to determine the most effective ways to intervene and plan surveillance. In this paper, we describe a novel transmission model for the spatial dynamics of hookworm, a parasitic worm which is a common infection across sub-Saharan Africa, East Asia and the Pacific islands. We fit our model, with and without mobility, to data obtained from a sub-county in Kenya, and validate the model's predictions against the decline in prevalence observed over the course of a clustered randomized control trial evaluating methods of administering mass chemotherapy. We find that our model which incorporates human mobility is able to reproduce the observed patterns in decline of prevalence during the TUMIKIA trial, and additionally, that the widespread bounce-back of infection may be possible over many years, depending on the rates of people movement between villages. The results have important implications for the design of mass chemotherapy programmes for the elimination of human helminth transmission. This article is part of the theme issue 'Challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs'.
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Affiliation(s)
- Benjamin S. Collyer
- Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, St Mary's Campus, Imperial College London, London W2 1PG, UK
| | - James E. Truscott
- Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, St Mary's Campus, Imperial College London, London W2 1PG, UK
| | | | - Sammy M. Njenga
- Eastern and Southern Africa Centre of International Parasite Control, Kenya Medical Research Institute, Nairobi, Kenya
| | - Roy M. Anderson
- Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, St Mary's Campus, Imperial College London, London W2 1PG, UK
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Tun STT, Min MC, Aguas R, Fornace K, Htoo GN, White LJ, Parker DM. Human movement patterns of farmers and forest workers from the Thailand-Myanmar border. Wellcome Open Res 2023; 6:148. [PMID: 37990719 PMCID: PMC10660292 DOI: 10.12688/wellcomeopenres.16784.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/25/2023] [Indexed: 11/23/2023] Open
Abstract
Background: Human travel patterns play an important role in infectious disease epidemiology and ecology. Movement into geographic spaces with high transmission can lead to increased risk of acquiring infections. Pathogens can also be distributed across the landscape via human travel. Most fine scale studies of human travel patterns have been done in urban settings in wealthy nations. Research into human travel patterns in rural areas of low- and middle-income nations are useful for understanding the human components of epidemiological systems for malaria or other diseases of the rural poor. The goal of this research was to assess the feasibility of using GPS loggers to empirically measure human travel patterns in this setting, as well as to quantify differing travel patterns by age, gender, and seasonality among study participants. Methods: In this pilot study we recruited 50 rural villagers from along the Myanmar-Thailand border to carry GPS loggers for the duration of a year. The GPS loggers were programmed to take a time-stamped reading every 30 minutes. We calculated daily movement ranges and multi-day trips by age and gender. We incorporated remote sensing data to assess patterns of days and nights spent in forested or farm areas, also by age and gender. Results: Our study showed that it is feasible to use GPS devices to measure travel patterns, though we had difficulty recruiting women and management of the project was relatively intensive. We found that older adults traveled farther distances than younger adults and adult males spent more nights in farms or forests. Conclusion: The results of this study suggest that further work along these lines would be feasible in this region. Furthermore, the results from this study are useful for individual-based models of disease transmission and land use.
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Affiliation(s)
- Sai Thein Than Tun
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Myo Chit Min
- Shoklo Malaria Research Unit, Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Sot, Thailand
| | - Ricardo Aguas
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Kimberly Fornace
- Centre for Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Gay Nay Htoo
- Shoklo Malaria Research Unit, Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Sot, Thailand
| | - Lisa J. White
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Daniel M. Parker
- Department of Population Health and Disease Prevention, University of California, Irvine, CA, 92697, USA
- Epidemiology and Biostatistics, University of California, Irvine, CA, 92697, USA
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Rerolle F, Dantzer E, Phimmakong T, Lover A, Hongvanthong B, Phetsouvanh R, Marshall J, Sturrock H, Bennett A. Characterizing mobility patterns of forest goers in southern Lao PDR using GPS loggers. Malar J 2023; 22:38. [PMID: 36732769 PMCID: PMC9893532 DOI: 10.1186/s12936-023-04468-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 01/24/2023] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND In the Greater Mekong Subregion (GMS), forest-going populations are considered high-risk populations for malaria and are increasingly targeted by national control programmes' elimination efforts. A better understanding of forest-going populations' mobility patterns and risk associated with specific types of forest-going trips is necessary for countries in the GMS to achieve their objective of eliminating malaria by 2030. METHODS Between March and November 2018, as part of a focal test and treat intervention (FTAT), 2,904 forest-goers were recruited in southern Lao PDR. A subset of forest-goers carried an "i-Got-U" GPS logger for roughly 2 months, configured to collect GPS coordinates every 15 to 30 min. The utilization distribution (UD) surface around each GPS trajectory was used to extract trips to the forest and forest-fringes. Trips with shared mobility characteristics in terms of duration, timing and forest penetration were identified by a hierarchical clustering algorithm. Then, clusters of trips with increased exposure to dominant malaria vectors in the region were further classified as high-risk. Finally, gradient boosting trees were used to assess which of the forest-goers' socio-demographic and behavioural characteristics best predicted their likelihood to engage in such high-risk trips. RESULTS A total of 122 forest-goers accepted carrying a GPS logger resulting in the collection of 803 trips to the forest or forest-fringes. Six clusters of trips emerged, helping to classify 385 (48%) trips with increased exposure to malaria vectors based on high forest penetration and whether the trip happened overnight. Age, outdoor sleeping structures and number of children were the best predictors of forest-goers' probability of engaging in high-risk trips. The probability of engaging in high-risk trips was high (~ 33%) in all strata of the forest-going population. CONCLUSION This study characterized the heterogeneity within the mobility patterns of forest-goers and attempted to further segment their role in malaria transmission in southern Lao People's Democratic Republic (PDR). National control programmes across the region can leverage these results to tailor their interventions and messaging to high-risk populations and accelerate malaria elimination.
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Affiliation(s)
- Francois Rerolle
- grid.266102.10000 0001 2297 6811Malaria Elimination Initiative, The Global Health Group, University of California, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Department of Epidemiology and Biostatistics, University of California, San Francisco, CA USA
| | - Emily Dantzer
- grid.266102.10000 0001 2297 6811Malaria Elimination Initiative, The Global Health Group, University of California, San Francisco, CA USA
| | - Toula Phimmakong
- grid.415768.90000 0004 8340 2282Center for Malariology, Parasitology and Entomology, Ministry of Health, Vientiane, Lao People’s Democratic Republic
| | - Andrew Lover
- grid.266683.f0000 0001 2166 5835Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA USA
| | - Bouasy Hongvanthong
- grid.415768.90000 0004 8340 2282Center for Malariology, Parasitology and Entomology, Ministry of Health, Vientiane, Lao People’s Democratic Republic
| | - Rattanaxay Phetsouvanh
- grid.415768.90000 0004 8340 2282Center for Malariology, Parasitology and Entomology, Ministry of Health, Vientiane, Lao People’s Democratic Republic
| | - John Marshall
- grid.47840.3f0000 0001 2181 7878Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, CA USA
| | - Hugh Sturrock
- grid.266102.10000 0001 2297 6811Malaria Elimination Initiative, The Global Health Group, University of California, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Department of Epidemiology and Biostatistics, University of California, San Francisco, CA USA
| | - Adam Bennett
- grid.266102.10000 0001 2297 6811Malaria Elimination Initiative, The Global Health Group, University of California, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Department of Epidemiology and Biostatistics, University of California, San Francisco, CA USA ,grid.415269.d0000 0000 8940 7771Malaria and Neglected Tropical Diseases, PATH, Seattle, WA USA
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Hast M, Mharakurwa S, Shields TM, Lubinda J, Searle K, Gwanzura L, Munyati S, Moss WJ. Characterizing human movement patterns using GPS data loggers in an area of persistent malaria in Zimbabwe along the Mozambique border. BMC Infect Dis 2022; 22:942. [PMID: 36522643 PMCID: PMC9756631 DOI: 10.1186/s12879-022-07903-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 11/29/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Human mobility is a driver for the reemergence or resurgence of malaria and has been identified as a source of cross-border transmission. However, movement patterns are difficult to measure in rural areas where malaria risk is high. In countries with malaria elimination goals, it is essential to determine the role of mobility on malaria transmission to implement appropriate interventions. METHODS A study was conducted in Mutasa District, Zimbabwe, to investigate human movement patterns in an area of persistent transmission along the Mozambique border. Over 1 year, a convenience sample of 20 participants/month was recruited from active malaria surveillance cohorts to carry an IgotU® GT-600 global positioning system (GPS) data logger during all daily activities. Consenting participants were tested for malaria at data logger distribution using rapid antigen diagnostic tests and completed a survey questionnaire. GPS data were analyzed using a trajectory analysis tool, and participant movement patterns were characterized throughout the study area and across the border into Mozambique using movement intensity maps, activity space plots, and statistical analyses. RESULTS From June 2016-May 2017, 184 participants provided movement tracks encompassing > 350,000 data points and nearly 8000 person-days. Malaria prevalence at logger distribution was 3.7%. Participants traveled a median of 2.8 km/day and spent a median of 4.6 h/day away from home. Movement was widespread within and outside the study area, with participants traveling up to 500 km from their homes. Indices of mobility were higher in the dry season than the rainy season (median km traveled/day = 3.5 vs. 2.2, P = 0.03), among male compared to female participants (median km traveled/day = 3.8 vs. 2.0, P = 0.0008), and among adults compared to adolescents (median total km traveled = 104.6 vs. 59.5, P = 0.05). Half of participants traveled outside the study area, and 30% traveled into Mozambique, including 15 who stayed in Mozambique overnight. CONCLUSIONS Study participants in Mutasa District, Zimbabwe, were highly mobile throughout the year. Many participants traveled long distances from home, including overnight trips into Mozambique, with clear implications for malaria control. Interventions targeted at mobile populations and cross-border transmission may be effective in preventing malaria introductions in this region.
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Affiliation(s)
- Marisa Hast
- grid.21107.350000 0001 2171 9311Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA
| | - Sungano Mharakurwa
- grid.418347.d0000 0004 8265 7435Biomedical Research and Training Institute, Harare, Zimbabwe ,grid.442719.d0000 0000 8930 0245Africa University, Old Mutare, Mutare, Zimbabwe
| | - Timothy M. Shields
- grid.21107.350000 0001 2171 9311Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA
| | - Jailos Lubinda
- grid.414659.b0000 0000 8828 1230Telethon Kids Institute, Malaria Atlas Project, Nedlands, WA Australia
| | - Kelly Searle
- grid.17635.360000000419368657School of Public Health, University of Minnesota, Minneapolis, MN USA
| | - Lovemore Gwanzura
- grid.418347.d0000 0004 8265 7435Biomedical Research and Training Institute, Harare, Zimbabwe
| | - Shungu Munyati
- grid.418347.d0000 0004 8265 7435Biomedical Research and Training Institute, Harare, Zimbabwe
| | - William J. Moss
- grid.21107.350000 0001 2171 9311Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA
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10
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Schaber KL, Kobayashi T, Hast M, Searle KM, Shields TM, Hamapumbu H, Lubinda J, Thuma PE, Lupiya J, Chaponda M, Munyati S, Gwanzura L, Mharakurwa S, Moss WJ, Wesolowski A. What Heterogeneities in Individual-level Mobility Are Lost During Aggregation? Leveraging GPS Logger Data to Understand Fine-scale and Aggregated Patterns of Mobility. Am J Trop Med Hyg 2022; 107:1145-1153. [PMID: 36252797 PMCID: PMC9709031 DOI: 10.4269/ajtmh.22-0202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 08/18/2022] [Indexed: 01/25/2023] Open
Abstract
Human movement drives spatial transmission patterns of infectious diseases. Population-level mobility patterns are often quantified using aggregated data sets, such as census migration surveys or mobile phone data. These data are often unable to quantify individual-level travel patterns and lack the information needed to discern how mobility varies by demographic groups. Individual-level datasets can capture additional, more precise, aspects of mobility that may impact disease risk or transmission patterns and determine how mobility differs across cohorts; however, these data are rare, particularly in locations such as sub-Saharan Africa. Using detailed GPS logger data collected from three sites in southern Africa, we explore metrics of mobility such as percent time spent outside home, number of locations visited, distance of locations, and time spent at locations to determine whether they vary by demographic, geographic, or temporal factors. We further create a composite mobility score to identify how well aggregated summary measures would capture the full extent of mobility patterns. Although sites had significant differences in all mobility metrics, no site had the highest mobility for every metric, a distinction that was not captured by the composite mobility score. Further, the effects of sex, age, and season on mobility were all dependent on site. No factor significantly influenced the number of trips to locations, a common way to aggregate datasets. When collecting and analyzing human mobility data, it is difficult to account for all the nuances; however, these analyses can help determine which metrics are most helpful and what underlying differences may be present.
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Affiliation(s)
- Kathryn L. Schaber
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Tamaki Kobayashi
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Marisa Hast
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Kelly M. Searle
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Timothy M. Shields
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | | | - Jailos Lubinda
- Telethon Kids Institute, Malaria Atlas Project, Nedlands, Australia
| | - Philip E. Thuma
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - James Lupiya
- The Tropical Diseases Research Centre, Ndola, Zambia
| | - Mike Chaponda
- The Tropical Diseases Research Centre, Ndola, Zambia
| | - Shungu Munyati
- Biomedical Research and Training Institute, Harare, Zimbabwe
| | - Lovemore Gwanzura
- Biomedical Research and Training Institute, Harare, Zimbabwe
- College of Health Sciences, University of Zimbabwe, Harare, Zimbabwe
| | - Sungano Mharakurwa
- Biomedical Research and Training Institute, Harare, Zimbabwe
- College of Health, Agriculture and Natural Sciences, Africa University, Mutare, Zimbabwe
| | - William J. Moss
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Amy Wesolowski
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
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11
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Haileselassie W, Getnet A, Solomon H, Deressa W, Yan G, Parker DM. Mobile phone handover data for measuring and analysing human population mobility in Western Ethiopia: implication for malaria disease epidemiology and elimination efforts. Malar J 2022; 21:323. [PMID: 36369036 PMCID: PMC9652832 DOI: 10.1186/s12936-022-04337-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 10/26/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Human mobility behaviour modelling plays an essential role in the understanding and control of the spread of contagious diseases by limiting the contact among individuals, predicting the spatio-temporal evolution of an epidemic and inferring migration patterns. It informs programmatic and policy decisions for effective and efficient intervention. The objective of this research is to assess the human mobility pattern and analyse its implication for malaria disease epidemiology. METHODS In this study, human mobility patterns in Benishangul-Gumuz and Gambella regions in Western Ethiopia were explored based on a cellular network mobility parameter (e.g., handover rate) via real world data. Anonymized data were retrieved for mobile active users with mobility related information. The data came from anonymous traffic records collected from all the study areas. For each cell, the necessary mobility parameter data per hour, week and month were collected. A scale factor was computed to change the mobility parameter value to the human mobility pattern. Finally, the relative human mobility probability for each scenario was estimated. MapInfo and Matlab softwares were used for visualization and analysis purposes. Hourly travel patterns in the study settings were compared with hourly malaria mosquito vector feeding behaviour. RESULTS Heterogeneous human movement patterns were observed in the two regions with some areas showing typically high human mobility. Furthermore, the number of people entering into the two study regions was high during the highest malaria transmission season. Two peaks of hourly human movement, 8:00 to 9:00 and 16:00 to 18:00, emerged in Benishangul-Gumuz region while 8:00 to 10:00 and 16:00 to 18:00 were the peak hourly human mobility time periods in Gambella region. The high human movement in the night especially before midnight in the two regions may increase the risk of getting mosquito bite particularly by early biters depending on malaria linked human behaviour of the population. CONCLUSIONS High human mobility was observed both within and outside the two regions. The population influx and efflux in these two regions is considerably high. This may specifically challenge the transition from malaria control to elimination. The daily mobility pattern is worth considering in the context of malaria transmission. In line with this malaria related behavioural patterns of humans need to be properly addressed.
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Affiliation(s)
- Werissaw Haileselassie
- grid.7123.70000 0001 1250 5688School of Public Health, Addis Ababa University, Addis Ababa, Ethiopia
| | - Ashagrie Getnet
- grid.7123.70000 0001 1250 5688Institute of Technology, Addis Ababa University, Addis Ababa, Ethiopia
| | - Hiwot Solomon
- grid.414835.f0000 0004 0439 6364Ministry of Health, Addis Ababa, Ethiopia
| | - Wakgari Deressa
- grid.7123.70000 0001 1250 5688School of Public Health, Addis Ababa University, Addis Ababa, Ethiopia
| | - Guiyun Yan
- grid.266093.80000 0001 0668 7243Program in Public Health, College of Health Sciences, University of California at Irvine, Irvine, CA 92697 USA
| | - Daniel M. Parker
- grid.266093.80000 0001 0668 7243Program in Public Health, College of Health Sciences, University of California at Irvine, Irvine, CA 92697 USA
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12
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Ippolito MM, Gebhardt ME, Ferriss E, Schue JL, Kobayashi T, Chaponda M, Kabuya JB, Muleba M, Mburu M, Matoba J, Musonda M, Katowa B, Lubinda M, Hamapumbu H, Simubali L, Mudenda T, Wesolowski A, Shields TM, Hackman A, Shiff C, Coetzee M, Koekemoer LL, Munyati S, Gwanzura L, Mutambu S, Stevenson JC, Thuma PE, Norris DE, Bailey JA, Juliano JJ, Chongwe G, Mulenga M, Simulundu E, Mharakurwa S, Agre PC, Moss WJ. Scientific Findings of the Southern and Central Africa International Center of Excellence for Malaria Research: Ten Years of Malaria Control Impact Assessments in Hypo-, Meso-, and Holoendemic Transmission Zones in Zambia and Zimbabwe. Am J Trop Med Hyg 2022; 107:55-67. [PMID: 36228903 PMCID: PMC9662223 DOI: 10.4269/ajtmh.21-1287] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 04/08/2022] [Indexed: 11/07/2022] Open
Abstract
For a decade, the Southern and Central Africa International Center of Excellence for Malaria Research has operated with local partners across study sites in Zambia and Zimbabwe that range from hypo- to holoendemic and vary ecologically and entomologically. The burden of malaria and the impact of control measures were assessed in longitudinal cohorts, cross-sectional surveys, passive and reactive case detection, and other observational designs that incorporated multidisciplinary scientific approaches: classical epidemiology, geospatial science, serosurveillance, parasite and mosquito genetics, and vector bionomics. Findings to date have helped elaborate the patterns and possible causes of sustained low-to-moderate transmission in southern Zambia and eastern Zimbabwe and recalcitrant high transmission and fatality in northern Zambia. Cryptic and novel mosquito vectors, asymptomatic parasite reservoirs in older children, residual parasitemia and gametocytemia after treatment, indoor residual spraying timed dyssynchronously to vector abundance, and stockouts of essential malaria commodities, all in the context of intractable rural poverty, appear to explain the persistent malaria burden despite current interventions. Ongoing studies of high-resolution transmission chains, parasite population structures, long-term malaria periodicity, and molecular entomology are further helping to lay new avenues for malaria control in southern and central Africa and similar settings.
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Affiliation(s)
- Matthew M. Ippolito
- Johns Hopkins University School of Medicine, Baltimore, Maryland
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Mary E. Gebhardt
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Ellen Ferriss
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Jessica L. Schue
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Tamaki Kobayashi
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | | | | | | | | | | | | | | | | | | | | | | | - Amy Wesolowski
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | | | - Andre Hackman
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Clive Shiff
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Maureen Coetzee
- Wits Research Institute for Malaria, Faculty of Health Sciences, University of the Witwatersrand and National Institute for Communicable Diseases, Johannesburg, South Africa
| | - Lizette L. Koekemoer
- Wits Research Institute for Malaria, Faculty of Health Sciences, University of the Witwatersrand and National Institute for Communicable Diseases, Johannesburg, South Africa
| | - Shungu Munyati
- Biomedical Research and Training Institute, Harare, Zimbabwe
| | - Lovemore Gwanzura
- Biomedical Research and Training Institute, Harare, Zimbabwe
- University of Zimbabwe Faculty of Medicine and Health Sciences, Harare, Zimbabwe
| | | | - Jennifer C. Stevenson
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Macha Research Trust, Choma, Zambia
| | | | - Douglas E. Norris
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | | | - Jonathan J. Juliano
- University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | | | - Modest Mulenga
- Directorate of Research and Postgraduate Studies, Lusaka Apex Medical University, Lusaka, Zambia
| | | | - Sungano Mharakurwa
- Biomedical Research and Training Institute, Harare, Zimbabwe
- Africa University, Mutare, Zimbabwe
| | - Peter C. Agre
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - William J. Moss
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
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13
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Sedda L, McCann RS, Kabaghe AN, Gowelo S, Mburu MM, Tizifa TA, Chipeta MG, van den Berg H, Takken W, van Vugt M, Phiri KS, Cain R, Tangena JAA, Jones CM. Hotspots and super-spreaders: Modelling fine-scale malaria parasite transmission using mosquito flight behaviour. PLoS Pathog 2022; 18:e1010622. [PMID: 35793345 PMCID: PMC9292116 DOI: 10.1371/journal.ppat.1010622] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 07/18/2022] [Accepted: 05/27/2022] [Indexed: 11/19/2022] Open
Abstract
Malaria hotspots have been the focus of public health managers for several years due to the potential elimination gains that can be obtained from targeting them. The identification of hotspots must be accompanied by the description of the overall network of stable and unstable hotspots of malaria, especially in medium and low transmission settings where malaria elimination is targeted. Targeting hotspots with malaria control interventions has, so far, not produced expected benefits. In this work we have employed a mechanistic-stochastic algorithm to identify clusters of super-spreader houses and their related stable hotspots by accounting for mosquito flight capabilities and the spatial configuration of malaria infections at the house level. Our results show that the number of super-spreading houses and hotspots is dependent on the spatial configuration of the villages. In addition, super-spreaders are also associated to house characteristics such as livestock and family composition. We found that most of the transmission is associated with winds between 6pm and 10pm although later hours are also important. Mixed mosquito flight (downwind and upwind both with random components) were the most likely movements causing the spread of malaria in two out of the three study areas. Finally, our algorithm (named MALSWOTS) provided an estimate of the speed of malaria infection progression from house to house which was around 200-400 meters per day, a figure coherent with mark-release-recapture studies of Anopheles dispersion. Cross validation using an out-of-sample procedure showed accurate identification of hotspots. Our findings provide a significant contribution towards the identification and development of optimal tools for efficient and effective spatio-temporal targeted malaria interventions over potential hotspot areas.
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Affiliation(s)
- Luigi Sedda
- Lancaster Ecology and Epidemiology Group, Lancaster Medical School, Lancaster University, United Kingdom
| | - Robert S. McCann
- Laboratory of Entomology, Wageningen University & Research, Wageningen, The Netherlands
- School of Global and Public Health, Kamuzu University of Health Sciences, Blantyre, Malawi
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Alinune N. Kabaghe
- School of Global and Public Health, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Steven Gowelo
- Laboratory of Entomology, Wageningen University & Research, Wageningen, The Netherlands
- School of Global and Public Health, Kamuzu University of Health Sciences, Blantyre, Malawi
- MAC Communicable Diseases Action Centre, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Monicah M. Mburu
- Laboratory of Entomology, Wageningen University & Research, Wageningen, The Netherlands
- School of Global and Public Health, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Tinashe A. Tizifa
- School of Global and Public Health, Kamuzu University of Health Sciences, Blantyre, Malawi
- Center for Tropical Medicine and Travel Medicine, University of Amsterdam, The Netherlands
| | - Michael G. Chipeta
- School of Global and Public Health, Kamuzu University of Health Sciences, Blantyre, Malawi
- Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi
| | - Henk van den Berg
- Laboratory of Entomology, Wageningen University & Research, Wageningen, The Netherlands
| | - Willem Takken
- Laboratory of Entomology, Wageningen University & Research, Wageningen, The Netherlands
| | - Michèle van Vugt
- Center for Tropical Medicine and Travel Medicine, University of Amsterdam, The Netherlands
| | - Kamija S. Phiri
- School of Global and Public Health, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Russell Cain
- Lancaster Ecology and Epidemiology Group, Lancaster Medical School, Lancaster University, United Kingdom
| | - Julie-Anne A. Tangena
- Vector Biology Department, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Christopher M. Jones
- Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi
- Vector Biology Department, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
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14
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Carrasco-Escobar G, Matta-Chuquisapon J, Manrique E, Ruiz-Cabrejos J, Barboza JL, Wong D, Henostroza G, Llanos-Cuentas A, Benmarhnia T. Quantifying the effect of human population mobility on malaria risk in the Peruvian Amazon. ROYAL SOCIETY OPEN SCIENCE 2022; 9:211611. [PMID: 35875474 PMCID: PMC9297009 DOI: 10.1098/rsos.211611] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 06/29/2022] [Indexed: 06/15/2023]
Abstract
The impact of human population movement (HPM) on the epidemiology of vector-borne diseases, such as malaria, has been described. However, there are limited data on the use of new technologies for the study of HPM in endemic areas with difficult access such as the Amazon. In this study conducted in rural Peruvian Amazon, we used self-reported travel surveys and GPS trackers coupled with a Bayesian spatial model to quantify the role of HPM on malaria risk. By using a densely sampled population cohort, this study highlighted the elevated malaria transmission in a riverine community of the Peruvian Amazon. We also found that the high connectivity between Amazon communities for reasons such as work, trading or family plausibly sustains such transmission levels. Finally, by using multiple human mobility metrics including GPS trackers, and adapted causal inference methods we identified for the first time the effect of human mobility patterns on malaria risk in rural Peruvian Amazon. This study provides evidence of the causal effect of HPM on malaria that may help to adapt current malaria control programmes in the Amazon.
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Affiliation(s)
- Gabriel Carrasco-Escobar
- Health Innovation Lab, Institute of Tropical Medicine ‘Alexander von Humboldt’, Universidad Peruana Cayetano Heredia, Lima, Peru
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Jose Matta-Chuquisapon
- Health Innovation Lab, Institute of Tropical Medicine ‘Alexander von Humboldt’, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Edgar Manrique
- Health Innovation Lab, Institute of Tropical Medicine ‘Alexander von Humboldt’, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Jorge Ruiz-Cabrejos
- Health Innovation Lab, Institute of Tropical Medicine ‘Alexander von Humboldt’, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Jose Luis Barboza
- Health Innovation Lab, Institute of Tropical Medicine ‘Alexander von Humboldt’, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Daniel Wong
- Health Innovation Lab, Institute of Tropical Medicine ‘Alexander von Humboldt’, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | - Alejandro Llanos-Cuentas
- Instituto de Medicinal Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
- Facultad de Salud Pública y Administración, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Tarik Benmarhnia
- Scripps Institution of Oceanography, University of California, San Diego, CA, USA
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15
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Pepey A, Obadia T, Kim S, Sovannaroth S, Mueller I, Witkowski B, Vantaux A, Souris M. Mobility evaluation by GPS tracking in a rural, low-income population in Cambodia. PLoS One 2022; 17:e0266460. [PMID: 35559983 PMCID: PMC9106150 DOI: 10.1371/journal.pone.0266460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 03/21/2022] [Indexed: 01/31/2023] Open
Abstract
Global Positioning System (GPS) technology is an effective tool for quantifying individuals' mobility patterns and can be used to understand their influence on infectious disease transmission. In Cambodia, mobility measurements have been limited to questionnaires, which are of limited efficacy in rural environments. In this study, we used GPS tracking to measure the daily mobility of Cambodian forest goers, a population at high risk of malaria, and developed a workflow adapted to local constraints to produce an optimal dataset representative of the participants' mobility. We provide a detailed assessment of the GPS tracking and analysis of the data, and highlight the associated difficulties to facilitate the implementation of similar studies in the future.
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Affiliation(s)
- Anaïs Pepey
- Malaria Molecular Epidemiology Unit, Institut Pasteur du Cambodge, Phnom Penh, Cambodia
- * E-mail:
| | - Thomas Obadia
- Department of Parasites and Insect Vectors, Infectious Diseases Epidemiology and Analytics, Institut Pasteur, Paris, France
- Département de Biologie Computationnelle, Hub de Bioinformatique et Biostatistique, Institut Pasteur, Paris, France
| | - Saorin Kim
- Malaria Molecular Epidemiology Unit, Institut Pasteur du Cambodge, Phnom Penh, Cambodia
| | - Siv Sovannaroth
- National Centre for Parasitology Entomology and Malaria Control (CNM), Phnom Penh, Cambodia
| | - Ivo Mueller
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
| | - Benoit Witkowski
- Malaria Molecular Epidemiology Unit, Institut Pasteur du Cambodge, Phnom Penh, Cambodia
| | - Amélie Vantaux
- Malaria Molecular Epidemiology Unit, Institut Pasteur du Cambodge, Phnom Penh, Cambodia
| | - Marc Souris
- UMR Unité des Virus Emergents, UVE: Aix-Marseille Univ–IRD 190–Inserm 1207–IHU 5 Méditerranée Infection, Marseille, France
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16
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Lai S, Sorichetta A, Steele J, Ruktanonchai CW, Cunningham AD, Rogers G, Koper P, Woods D, Bondarenko M, Ruktanonchai NW, Shi W, Tatem AJ. Global holiday datasets for understanding seasonal human mobility and population dynamics. Sci Data 2022; 9:17. [PMID: 35058466 PMCID: PMC8776767 DOI: 10.1038/s41597-022-01120-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 12/10/2021] [Indexed: 11/17/2022] Open
Abstract
Public and school holidays have important impacts on population mobility and dynamics across multiple spatial and temporal scales, subsequently affecting the transmission dynamics of infectious diseases and many socioeconomic activities. However, worldwide data on public and school holidays for understanding their changes across regions and years have not been assembled into a single, open-source and multitemporal dataset. To address this gap, an open access archive of data on public and school holidays in 2010-2019 across the globe at daily, weekly, and monthly timescales was constructed. Airline passenger volumes across 90 countries from 2010 to 2018 were also assembled to illustrate the usage of the holiday data for understanding the changing spatiotemporal patterns of population movements.
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Affiliation(s)
- Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK.
| | - Alessandro Sorichetta
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Jessica Steele
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Corrine W Ruktanonchai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
- Population Health Sciences, Virginia Tech, Blacksburg, VA, 24061, USA
| | - Alexander D Cunningham
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Grant Rogers
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Patrycja Koper
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Dorothea Woods
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Maksym Bondarenko
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Nick W Ruktanonchai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
- Population Health Sciences, Virginia Tech, Blacksburg, VA, 24061, USA
| | - Weifeng Shi
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, China
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
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17
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Tam G, Cowling BJ, Maude RJ. Analysing human population movement data for malaria control and elimination. Malar J 2021; 20:294. [PMID: 34193167 PMCID: PMC8247220 DOI: 10.1186/s12936-021-03828-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 06/22/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Human population movement poses a major obstacle to malaria control and elimination. With recent technological advances, a wide variety of data sources and analytical methods have been used to quantify human population movement (HPM) relevant to control and elimination of malaria. METHODS The relevant literature and selected studies that had policy implications that could help to design or target malaria control and elimination interventions were reviewed. These studies were categorized according to spatiotemporal scales of human mobility and the main method of analysis. RESULTS Evidence gaps exist for tracking routine cross-border HPM and HPM at a regional scale. Few studies accounted for seasonality. Out of twenty included studies, two studies which tracked daily neighbourhood HPM used descriptive analyses as the main method, while the remaining studies used statistical analyses or mathematical modelling. CONCLUSION Although studies quantified varying types of human population movement covering different spatial and temporal scales, methodological gaps remain that warrant further studies related to malaria control and elimination.
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Affiliation(s)
- Greta Tam
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing, Faculty of Medicine, The University of Hong Kong, Hong Kong, China.,Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, 10400, Thailand
| | - Benjamin J Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing, Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Richard J Maude
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, 10400, Thailand. .,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7LG, UK. .,The Open University, Milton Keynes, MK7 6AA, UK. .,Harvard TH Chan School of Public Health, Harvard University, Boston, MA, 02115, USA.
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18
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Tun STT, Min MC, Aguas R, Fornace K, Htoo GN, White LJ, Parker DM. Human movement patterns of farmers and forest workers from the Thailand-Myanmar border. Wellcome Open Res 2021. [DOI: 10.12688/wellcomeopenres.16784.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background: Human travel patterns play an important role in infectious disease epidemiology and ecology. Movement into geographic spaces with high transmission can lead to increased risk of acquiring infections. Pathogens can also be distributed across the landscape via human travel. Most fine scale studies of human travel patterns have been done in urban settings in wealthy nations. Research into human travel patterns in rural areas of low- and middle-income nations are useful for understanding the human components of epidemiological systems for malaria or other diseases of the rural poor. The goal of this research was to assess the feasibility of using GPS loggers to empirically measure human travel patterns in this setting, as well as to quantify differing travel patterns by age, gender, and seasonality. Methods: In this pilot study we recruited 50 rural villagers from along the Myanmar-Thailand border to carry GPS loggers for the duration of a year. The GPS loggers were programmed to take a time-stamped reading every 30 minutes. We calculated daily movement ranges and multi-day trips by age and gender. We incorporated remote sensing data to assess patterns of days and nights spent in forested or farm areas, also by age and gender. Results: Our study showed that it is feasible to use GPS devices to measure travel patterns, though we had difficulty recruiting women and management of the project was relatively intensive. We found that older adults traveled farther distances than younger adults and adult males spent more nights in farms or forests. Conclusion: The results of this study suggest that further work along these lines would be feasible in this region. Furthermore, the results from this study are useful for individual-based models of disease transmission and land use.
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19
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Lubinda J, Haque U, Bi Y, Shad MY, Keellings D, Hamainza B, Moore AJ. Climate change and the dynamics of age-related malaria incidence in Southern Africa. ENVIRONMENTAL RESEARCH 2021; 197:111017. [PMID: 33766570 DOI: 10.1016/j.envres.2021.111017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 02/27/2021] [Accepted: 03/11/2021] [Indexed: 06/12/2023]
Abstract
In the last decade, many malaria-endemic countries, like Zambia, have achieved significant reductions in malaria incidence among children <5 years old but face ongoing challenges in achieving similar progress against malaria in older age groups. In parts of Zambia, changing climatic and environmental factors are among those suspectedly behind high malaria incidence. Changes and variations in these factors potentially interfere with intervention program effectiveness and alter the distribution and incidence patterns of malaria differentially between young children and the rest of the population. We used parametric and non-parametric statistics to model the effects of climatic and socio-demographic variables on age-specific malaria incidence vis-à-vis control interventions. Linear regressions, mixed models, and Mann-Kendall tests were implemented to explore trends, changes in trends, and regress malaria incidence against environmental and intervention variables. Our study shows that while climate parameters affect the whole population, their impacts are felt most by people aged ≥5 years. Climate variables influenced malaria substantially more than mosquito nets and indoor residual spraying interventions. We establish that climate parameters negatively impact malaria control efforts by exacerbating the transmission conditions via more conducive temperature and rainfall environments, which are augmented by cultural and socioeconomic exposure mechanisms. We argue that an intensified communications and education intervention strategy for behavioural change specifically targeted at ≥5 aged population where incidence rates are increasing, is urgently required and call for further malaria stratification among the ≥5 age groups in the routine collection, analysis and reporting of malaria mortality and incidence data.
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Affiliation(s)
- Jailos Lubinda
- School of Geography and Environmental Sciences, Ulster University, Coleraine, UK; School of Computing, Engineering and Intelligent Systems, Ulster University, Londonderry, United Kingdom; School of Nursing, Faculty of Life & Health Sciences, Jordanstown, Newtownabbey, United Kingdom.
| | - Ubydul Haque
- Department of Biostatistics and Epidemiology, University of North Texas Health Science Centre, Fort Worth, TX, 76107, USA; Department of Geography, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - Yaxin Bi
- School of Computing, Ulster University, Jordanstown, Newtownabbey, UK
| | | | - David Keellings
- Department of Geography, University of Alabama, Tuscaloosa, AL, USA
| | - Busiku Hamainza
- Ministry of Health, National Malaria Elimination Center, Lusaka, Zambia
| | - Adrian J Moore
- School of Geography and Environmental Sciences, Ulster University, Coleraine, UK
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20
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Robsky KO, Isooba D, Nakasolya O, Mukiibi J, Nalutaaya A, Kitonsa PJ, Kamoga C, Baik Y, Kendall EA, Katamba A, Dowdy DW. Characterization of geographic mobility among participants in facility- and community-based tuberculosis case finding in urban Uganda. PLoS One 2021; 16:e0251806. [PMID: 33989343 PMCID: PMC8121348 DOI: 10.1371/journal.pone.0251806] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 05/03/2021] [Indexed: 11/18/2022] Open
Abstract
Background International and internal migration are recognized risk factors for tuberculosis (TB). Geographic mobility, including travel for work, education, or personal reasons, may also play a role in TB transmission, but this relationship is poorly defined. We aimed to define geographic mobility among participants in facility- and community-based TB case finding in Kampala, Uganda, and to assess associations between mobility, access to care, and TB disease. Methods We included consecutive individuals age ≥15 years diagnosed with TB disease through either routine health facility practices or community-based case finding (consisting of door-to-door testing, venue-based screening, and contact investigation). Each case was matched with one (for community-based enrollment) or two (health facility enrollment) TB-negative controls. We conducted a latent class analysis (LCA) of eight self-reported characteristics to identify and define mobility; we selected the best-fit model using Bayesian Information Criterion. We assessed associations between mobility and TB case status using multivariable conditional logistic regression. Results We enrolled 267 cases and 432 controls. Cases were more likely than controls to have been born in Kampala (p<0.001); there was no difference between cases and controls for remaining mobility characteristics. We selected a two-class LCA model; the “mobile” class was perfectly correlated with a single variable: travel (>3 km) from residence ≥2 times per month. Mobility was associated with a 28% reduction in odds of being a TB case (adjusted matched odds ratio 0.72 [95% confidence interval 0.49, 1.06]). Conclusion Frequency of out-of-neighborhood travel is an easily measured variable that correlates closely with predicted mobility class membership. Mobility was associated with decreased risk of TB disease; this may be in part due to the higher socioeconomic status of mobile individuals in this population. However, more research is needed to improve assessment of mobility and understand how mobility affects disease risk and transmission.
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Affiliation(s)
- Katherine O. Robsky
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
- Uganda Tuberculosis Implementation Research Consortium, Makerere University, Kampala, Uganda
- * E-mail:
| | - David Isooba
- Uganda Tuberculosis Implementation Research Consortium, Makerere University, Kampala, Uganda
| | - Olga Nakasolya
- Uganda Tuberculosis Implementation Research Consortium, Makerere University, Kampala, Uganda
| | - James Mukiibi
- Uganda Tuberculosis Implementation Research Consortium, Makerere University, Kampala, Uganda
| | - Annet Nalutaaya
- Uganda Tuberculosis Implementation Research Consortium, Makerere University, Kampala, Uganda
| | - Peter J. Kitonsa
- Uganda Tuberculosis Implementation Research Consortium, Makerere University, Kampala, Uganda
| | - Caleb Kamoga
- Uganda Tuberculosis Implementation Research Consortium, Makerere University, Kampala, Uganda
| | - Yeonsoo Baik
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
- Uganda Tuberculosis Implementation Research Consortium, Makerere University, Kampala, Uganda
| | - Emily A. Kendall
- Uganda Tuberculosis Implementation Research Consortium, Makerere University, Kampala, Uganda
- Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Achilles Katamba
- Uganda Tuberculosis Implementation Research Consortium, Makerere University, Kampala, Uganda
- Department of Medicine, Clinical Epidemiology and Biostatistics Unit, College of Health Sciences, Makerere University, Kampala, Uganda
| | - David W. Dowdy
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
- Uganda Tuberculosis Implementation Research Consortium, Makerere University, Kampala, Uganda
- Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
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21
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Comparing metapopulation dynamics of infectious diseases under different models of human movement. Proc Natl Acad Sci U S A 2021; 118:2007488118. [PMID: 33926962 PMCID: PMC8106338 DOI: 10.1073/pnas.2007488118] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Newly available datasets present exciting opportunities to investigate how human population movement contributes to the spread of infectious diseases across large geographical distances. It is now possible to construct realistic models of infectious disease dynamics for the purposes of understanding global-scale epidemics. Nevertheless, a remaining unanswered question is how best to leverage the new data to parameterize models of movement, and whether one's choice of movement model impacts modeled disease outcomes. We adapt three well-studied models of infectious disease dynamics, the susceptible-infected-recovered model, the susceptible-infected-susceptible model, and the Ross-Macdonald model, to incorporate either of two candidate movement models. We describe the effect that the choice of movement model has on each disease model's results, finding that in all cases, there are parameter regimes where choosing one movement model instead of another has a profound impact on epidemiological outcomes. We further demonstrate the importance of choosing an appropriate movement model using the applied case of malaria transmission and importation on Bioko Island, Equatorial Guinea, finding that one model produces intelligible predictions of R 0, whereas the other produces nonsensical results.
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22
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Porter TR, Finn TP, Silumbe K, Chalwe V, Hamainza B, Kooma E, Moonga H, Bennett A, Yukich JO, Steketee RW, Keating J, Miller JM, Eisele TP. Recent Travel History and Plasmodium falciparum Malaria Infection in a Region of Heterogenous Transmission in Southern Province, Zambia. Am J Trop Med Hyg 2020; 103:74-81. [PMID: 32618250 PMCID: PMC7416974 DOI: 10.4269/ajtmh.19-0660] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
As Zambia continues to reduce its malaria incidence and target elimination in Southern Province, there is a need to identify factors that can reintroduce parasites and sustain malaria transmission. To examine the relative contributions of types of human mobility on malaria prevalence, this analysis quantifies the proportion of the population having recently traveled during both peak and nonpeak transmission seasons over the course of 2 years and assesses the relationship between short-term travel and malaria infection status. Among all residents targeted by mass drug administration in the Lake Kariba region of Southern Province, 602,620 rapid diagnostic tests and recent travel histories were collected during four campaign rounds occurring between December 2014 and February 2016. Rates of short-term travel in the previous 2 weeks fluctuated seasonally from 0.3% to 1.2%. Travel was significantly associated with prevalent malaria infection both seasonally and overall (adjusted odds ratio [AOR]: 2.55; 95% CI: 2.28-2.85). The strength of association between travel and malaria infection varied by travelers' origin and destination, with those recently traveling to high-prevalence areas from low-prevalence areas experiencing the highest odds of malaria infection (AOR: 7.38). Long-lasting insecticidal net usage while traveling was associated with a relative reduction in infections (AOR: 0.74) compared with travelers not using a net. Although travel was directly associated with only a small fraction of infections, importation of malaria via human movement may play an increasingly important role in this elimination setting as transmission rates continue to decline.
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Affiliation(s)
- Travis R Porter
- Department of Tropical Medicine, Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Timothy P Finn
- Department of Tropical Medicine, Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Kafula Silumbe
- PATH Malaria Control and Elimination Partnership in Africa (MACEPA), Lusaka, Zambia
| | - Victor Chalwe
- National Malaria Elimination Centre, Zambia Ministry of Health, Lusaka, Zambia
| | - Busiku Hamainza
- National Malaria Elimination Centre, Zambia Ministry of Health, Lusaka, Zambia
| | - Emmanuel Kooma
- National Malaria Elimination Centre, Zambia Ministry of Health, Lusaka, Zambia
| | - Hawela Moonga
- National Malaria Elimination Centre, Zambia Ministry of Health, Lusaka, Zambia
| | - Adam Bennett
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, California
| | - Joshua O Yukich
- Department of Tropical Medicine, Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | | | - Joseph Keating
- Department of Tropical Medicine, Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - John M Miller
- PATH Malaria Control and Elimination Partnership in Africa (MACEPA), Lusaka, Zambia
| | - Thomas P Eisele
- Department of Tropical Medicine, Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
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23
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Marsh A, Hirve S, Lele P, Chavan U, Bhattacharjee T, Nair H, Campbell H, Juvekar S. Validating a GPS-based approach to detect health facility visits against maternal response to prompted recall survey. J Glob Health 2020; 10:010602. [PMID: 32426124 PMCID: PMC7211413 DOI: 10.7189/jogh.10.010602] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Introduction Common approaches to measure health behaviors rely on participant responses and are subject to bias. Technology-based alternatives, particularly using GPS, address these biases while opening new channels for research. This study describes the development and implementation of a GPS-based approach to detect health facility visits in rural Pune district, India. Methods Participants were mothers of under-five year old children within the Vadu Demographic Surveillance area. Participants received GPS-enabled smartphones pre-installed with a location-aware application to continuously record and transmit participant location data to a central server. Data were analyzed to identify health facility visits according to a parameter-based approach, optimal thresholds of which were calibrated through a simulation exercise. Lists of GPS-detected health facility visits were generated at each of six follow-up home visits and reviewed with participants through prompted recall survey, confirming visits which were correctly identified. Detected visits were analyzed using logistic regression to explore factors associated with the identification of false positive GPS-detected visits. Results We enrolled 200 participants and completed 1098 follow-up visits over the six-month study period. Prompted recall surveys were completed for 694 follow-up visits with one or more GPS-detected health facility visits. While the approach performed well during calibration (positive predictive value (PPV) 78%), performance was poor when applied to participant data. Only 440 of 22 251 detected visits were confirmed (PPV 2%). False positives increased as participants spent more time in areas of high health facility density (odds ratio (OR) = 2.29, 95% confidence interval (CI) = 1.62-3.25). Visits detected at facilities other than hospitals and clinics were also more likely to be false positives (OR = 2.78, 95% CI = 1.65-4.67) as were visits detected to facilities nearby participant homes, with the likelihood decreasing as distance increased (OR = 0.89, 95% CI = 0.82-0.97). Visit duration was not associated with confirmation status. Conclusions The optimal parameter combination for health facility visits simulated by field workers substantially overestimated health visits from participant GPS data. This study provides useful insights into the challenges in detecting health facility visits where providers are numerous, highly clustered within urban centers and located near residential areas of the population which they serve.
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Affiliation(s)
- Andrew Marsh
- Institute for International Programs, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.,KEM Hospital Research Centre, Sardar Moodliar Road, Rasta Peth, Pune, India
| | | | - Pallavi Lele
- KEM Hospital Research Centre, Sardar Moodliar Road, Rasta Peth, Pune, India
| | - Uddhavi Chavan
- KEM Hospital Research Centre, Sardar Moodliar Road, Rasta Peth, Pune, India
| | - Tathagata Bhattacharjee
- KEM Hospital Research Centre, Sardar Moodliar Road, Rasta Peth, Pune, India.,INDEPTH Network, 40 Mensah Wood Street, East Legon, Accra, Ghana
| | - Harish Nair
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Harry Campbell
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Sanjay Juvekar
- KEM Hospital Research Centre, Sardar Moodliar Road, Rasta Peth, Pune, India.,INDEPTH Network, 40 Mensah Wood Street, East Legon, Accra, Ghana
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24
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Floyd JR, Ogola J, Fèvre EM, Wardrop N, Tatem AJ, Ruktanonchai NW. Activity-specific mobility of adults in a rural region of western Kenya. PeerJ 2020; 8:e8798. [PMID: 32377444 PMCID: PMC7195828 DOI: 10.7717/peerj.8798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 02/25/2020] [Indexed: 11/25/2022] Open
Abstract
Improving rural household access to resources such as markets, schools and healthcare can help alleviate poverty in low-income settings. Current models of geographic accessibility to various resources rarely take individual variation into account due to a lack of appropriate data, yet understanding mobility at an individual level is key to knowing how people access their local resources. Our study used both an activity-specific survey and GPS trackers to evaluate how adults in a rural area of western Kenya accessed local resources. We calculated the travel time and time spent at six different types of resource and compared the GPS and survey data to see how well they matched. We found links between several demographic characteristics and the time spent at different resources, and that the GPS data reflected the survey data well for time spent at some types of resource, but poorly for others. We conclude that demography and activity are important drivers of mobility, and a better understanding of individual variation in mobility could be obtained through the use of GPS trackers on a wider scale.
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Affiliation(s)
- Jessica R Floyd
- WorldPop, Department of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Joseph Ogola
- International Livestock Research Institute, Nairobi, Kenya
| | - Eric M Fèvre
- International Livestock Research Institute, Nairobi, Kenya.,Institute of Infection and Global Health, University of Liverpool, Liverpool, United Kingdom
| | - Nicola Wardrop
- Department for International Development, Glasgow, United Kingdom
| | - Andrew J Tatem
- WorldPop, Department of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Nick W Ruktanonchai
- WorldPop, Department of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
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25
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Yoo EH, Roberts JE, Eum Y, Shi Y. Quality of hybrid location data drawn from GPS-enabled mobile phones: Does it matter? TRANSACTIONS IN GIS : TG 2020; 24:462-482. [PMID: 35812894 PMCID: PMC9262051 DOI: 10.1111/tgis.12612] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Despite their increasing popularity in human mobility studies, few studies have investigated the geo-spatial quality of GPS-enabled mobile phone data in which phone location is determined by special queries designed to collect location data with predetermined sampling intervals (hereafter "active mobile phone data"). We focus on two key issues in active mobile phone data-systematic gaps in tracking records and positioning uncertainty-and investigate their effects on human mobility pattern analyses. To address gaps in records, we develop an imputation strategy that utilizes local environment information, such as parcel boundaries, and recording time intervals. We evaluate the performance of the proposed imputation strategy by comparing raw versus imputed data with participants' online survey responses. The results indicate that imputed data are superior to raw data in identifying individuals' frequently visited places on a weekly basis. To assess the location accuracy of active mobile phone data, we investigate the spatial and temporal patterns of the positional uncertainty of each record and examine via Monte Carlo simulation how inaccurate location information might affect human mobility pattern indicators. Results suggest that the level of uncertainty varies as a function of time of day and the type of land use at which the position was determined, both of which are closely related to the location technology used to determine the location. Our study highlights the importance of understanding and addressing limitations of mobile phone derived positioning data prior to their use in human mobility studies.
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Affiliation(s)
- Eun-Hye Yoo
- Department of Geography, State University of New York at Buffalo, Buffalo, NY, USA
| | - John E Roberts
- Department of Geography, State University of New York at Buffalo, Buffalo, NY, USA
| | - Youngseob Eum
- Department of Geography, State University of New York at Buffalo, Buffalo, NY, USA
| | - Youdi Shi
- Department of Geography, State University of New York at Buffalo, Buffalo, NY, USA
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26
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Guerra CA, Citron DT, García GA, Smith DL. Characterising malaria connectivity using malaria indicator survey data. Malar J 2019; 18:440. [PMID: 31870353 PMCID: PMC6929427 DOI: 10.1186/s12936-019-3078-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2019] [Accepted: 12/14/2019] [Indexed: 12/13/2022] Open
Abstract
Malaria connectivity describes the flow of parasites among transmission sources and sinks within a given landscape. Because of the spatial and temporal scales at which parasites are transported by their hosts, malaria sub-populations are largely defined by mosquito movement and malaria connectivity among them is largely driven by human movement. Characterising malaria connectivity thus requires characterising human travel between areas with differing levels of exposure to malaria. Whilst understanding malaria connectivity is fundamental for optimising interventions, particularly in areas seeking or sustaining elimination, there is a dearth of human movement data required to achieve this goal. Malaria indicator surveys (MIS) are a generally under utilised but potentially rich source of travel data that provide a unique opportunity to study simple associations between malaria infection and human travel in large population samples. This paper shares the experience working with MIS data from Bioko Island that revealed programmatically useful information regarding malaria importation through human travel. Simple additions to MIS questionnaires greatly augmented the level of detail of the travel data, which can be used to characterise human travel patterns and malaria connectivity to assist targeting interventions. It is argued that MIS potentially represent very important and timely sources of travel data that need to be further exploited.
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Affiliation(s)
- Carlos A Guerra
- Medical Care Development International, 8401 Colesville Road, Suite 425, Silver Spring, MD, 20910, USA.
| | - Daniel T Citron
- Institute for Health Metrics and Evaluation, University of Washington, 2301 Fifth Avenue, Seattle, 98121, USA
| | - Guillermo A García
- Medical Care Development International, 8401 Colesville Road, Suite 425, Silver Spring, MD, 20910, USA
| | - David L Smith
- Institute for Health Metrics and Evaluation, University of Washington, 2301 Fifth Avenue, Seattle, 98121, USA
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27
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Hast M, Searle KM, Chaponda M, Lupiya J, Lubinda J, Sikalima J, Kobayashi T, Shields T, Mulenga M, Lessler J, Moss WJ. The use of GPS data loggers to describe the impact of spatio-temporal movement patterns on malaria control in a high-transmission area of northern Zambia. Int J Health Geogr 2019; 18:19. [PMID: 31426819 PMCID: PMC6701131 DOI: 10.1186/s12942-019-0183-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2019] [Accepted: 08/10/2019] [Indexed: 12/01/2022] Open
Abstract
Background Human movement is a driver of malaria transmission and has implications for sustainable malaria control. However, little research has been done on the impact of fine-scale movement on malaria transmission and control in high-transmission settings. As interest in targeted malaria control increases, evaluations are needed to determine the appropriateness of these strategies in the context of human mobility across a variety of transmission settings. Methods A human mobility study was conducted in Nchelenge District, a high-transmission setting in northern Zambia. Over 1 year, 84 participants were recruited from active malaria surveillance cohorts to wear a global positioning system data logger for 1 month during all daily activity. Participants completed a survey questionnaire and underwent malaria testing and treatment at the time of logger distribution and at collection 1 month later. Incident malaria infections were identified using polymerase chain reaction. Participant movement was characterized throughout the study area and across areas targeted for an indoor residual spraying (IRS) intervention. Participant movement patterns were compared using movement intensity maps, activity space plots, and statistical analyses. Malaria risk was characterized across participants using spatial risk maps and time spent away from home during peak vector biting hours. Results Movement data were collected from 82 participants, and 63 completed a second study visit. Participants exhibited diverse mobility patterns across the study area, including movement into and out of areas targeted for IRS, potentially mitigating the impact of IRS on parasite prevalence. Movement patterns did not differ significantly by season or age, but male participants traveled longer distances and spent more time away from home. Monthly malaria incidence was 22%, and malaria risk was characterized as high across participants. Participants with incident parasitemia traveled a shorter distance and spent more time away from home during peak biting hours; however, these relationships were not statistically significant, and malaria risk score did not differ by incident parasitemia. Conclusions Individual movement patterns in Nchelenge District, Zambia have implications for malaria control, particularly the effectiveness of targeted IRS strategies. Large and fine-scale population mobility patterns should be considered when planning intervention strategies across transmission settings. Electronic supplementary material The online version of this article (10.1186/s12942-019-0183-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Marisa Hast
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Kelly M Searle
- University of Minnesota, School of Public Health, Minneapolis, MN, USA
| | - Mike Chaponda
- The Tropical Diseases Research Centre, Ndola, Zambia
| | - James Lupiya
- The Tropical Diseases Research Centre, Ndola, Zambia
| | - Jailos Lubinda
- Macha Research Trust, Choma District, Choma, Zambia.,Ulster University, Coleraine, Northern Ireland, UK
| | - Jay Sikalima
- The Tropical Diseases Research Centre, Ndola, Zambia
| | - Tamaki Kobayashi
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Timothy Shields
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Justin Lessler
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - William J Moss
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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Guerra CA, Kang SY, Citron DT, Hergott DEB, Perry M, Smith J, Phiri WP, Osá Nfumu JO, Mba Eyono JN, Battle KE, Gibson HS, García GA, Smith DL. Human mobility patterns and malaria importation on Bioko Island. Nat Commun 2019; 10:2332. [PMID: 31133635 PMCID: PMC6536527 DOI: 10.1038/s41467-019-10339-1] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Accepted: 05/02/2019] [Indexed: 01/09/2023] Open
Abstract
Malaria burden on Bioko Island has decreased significantly over the past 15 years. The impact of interventions on malaria prevalence, however, has recently stalled. Here, we use data from island-wide, annual malaria indicator surveys to investigate human movement patterns and their relationship to Plasmodium falciparum prevalence. Using geostatistical and mathematical modelling, we find that off-island travel is more prevalent in and around the capital, Malabo. The odds of malaria infection among off-island travelers are significantly higher than the rest of the population. We estimate that malaria importation rates are high enough to explain malaria prevalence in much of Malabo and its surroundings, and that local transmission is highest along the West Coast of the island. Despite uncertainty, these estimates of residual transmission and importation serve as a basis for evaluating progress towards elimination and for efficiently allocating resources as Bioko makes the transition from control to elimination.
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Affiliation(s)
- Carlos A Guerra
- Medical Care Development International, 8401 Colesville Road, Suite 425, Silver Spring, MD, 20910, USA.
| | - Su Yun Kang
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FY, UK
| | - Daniel T Citron
- Institute for Health Metrics and Evaluation, University of Washington, 2301 Fifth Ave., Suite 600, Seattle, WA, 98121, USA
| | - Dianna E B Hergott
- University of Washington, Department of Epidemiology, 1959 NE Pacific Street, Health Sciences Bldg, F-262, Box 357236, Seattle, WA, 98195, USA
| | - Megan Perry
- Medical Care Development International, 8401 Colesville Road, Suite 425, Silver Spring, MD, 20910, USA
| | - Jordan Smith
- Medical Care Development International, Avenida Parques de Africa S/N, Malabo, Equatorial Guinea
| | - Wonder P Phiri
- Medical Care Development International, Avenida Parques de Africa S/N, Malabo, Equatorial Guinea
| | - José O Osá Nfumu
- Medical Care Development International, Avenida Parques de Africa S/N, Malabo, Equatorial Guinea
| | - Jeremías N Mba Eyono
- Medical Care Development International, Avenida Parques de Africa S/N, Malabo, Equatorial Guinea
| | - Katherine E Battle
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FY, UK
| | - Harry S Gibson
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FY, UK
| | - Guillermo A García
- Medical Care Development International, 8401 Colesville Road, Suite 425, Silver Spring, MD, 20910, USA
| | - David L Smith
- Institute for Health Metrics and Evaluation, University of Washington, 2301 Fifth Ave., Suite 600, Seattle, WA, 98121, USA
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Saita S, Pan-Ngum W, Phuanukoonnon S, Sriwichai P, Silawan T, White LJ, Parker DM. Human population movement and behavioural patterns in malaria hotspots on the Thai-Myanmar border: implications for malaria elimination. Malar J 2019; 18:64. [PMID: 30849980 PMCID: PMC6408830 DOI: 10.1186/s12936-019-2704-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 03/02/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Malaria is heterogeneously distributed across landscapes. Human population movement (HPM) could link sub-regions with varying levels of transmission, leading to the persistence of disease even in very low transmission settings. Malaria along the Thai-Myanmar border has been decreasing, but remains heterogeneous. This study aimed to measure HPM, associated predictors of travel, and HPM correlates of self-reported malaria among people living within malaria hotspots. METHODS 526 individuals from 279 households in two malaria hotspot areas were included in a prospective observational study. A baseline cross-sectional study was conducted at the beginning, recording both individual- and household-level characteristics. Individual movement and travel patterns were repeatedly observed over one dry season month (March) and one wet season month (May). Descriptive statistics, random effects logistic regressions, and logistic regressions were used to describe and determine associations between HPM patterns, individual-, household-factors, and self-reported malaria. RESULTS Trips were more common in the dry season. Malaria risk was related to the number of days doing outdoor activities in the dry season, especially trips to Myanmar, to forest areas, and overnight trips. Trips to visit forest areas were more common among participants aged 20-39, males, individuals with low income, low education, and especially among individuals with forest-related occupations. Overnight trips were more common among males, and individual with forest-related occupations. Forty-five participants reported having confirmed malaria infection within the last year. The main place of malaria blood examination and treatment was malaria post and malaria clinic, with participants usually waiting for 2-3 days from onset fever to seeking diagnosis. Individuals using bed nets, living in houses with elevated floors, and houses that received indoor residual spraying in the last year were less likely to report malaria infection. CONCLUSION An understanding of HPM and concurrent malaria dynamics is important for consideration of targeted public health interventions. Furthermore, diagnosis and treatment centres must be capable of quickly diagnosing and treating infections regardless of HPM. Coverage of diagnosis and treatment centres should be broad, maintained in areas bordering malaria hotspots, and available to all febrile individuals.
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Affiliation(s)
- Sayambhu Saita
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Wirichada Pan-Ngum
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.,Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Suparat Phuanukoonnon
- Department of Social and Environmental Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Patchara Sriwichai
- Department of Medical Entomology, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Tassanee Silawan
- Department of Community Health, Faculty of Public Health, Mahidol University, Bangkok, Thailand
| | - Lisa J White
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.,Centre for Tropical Medicine, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Daniel M Parker
- Department of Population Health and Disease Prevention, University of California, Irvine, USA.
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30
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Zhu G, Liu T, Xiao J, Zhang B, Song T, Zhang Y, Lin L, Peng Z, Deng A, Ma W, Hao Y. Effects of human mobility, temperature and mosquito control on the spatiotemporal transmission of dengue. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 651:969-978. [PMID: 30360290 DOI: 10.1016/j.scitotenv.2018.09.182] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 09/14/2018] [Accepted: 09/14/2018] [Indexed: 05/06/2023]
Abstract
Dengue transmission exhibits evident geographic variations and seasonal differences. Such heterogeneity is caused by various impact factors, in which temperature and host/vector behaviors could drive its spatiotemporal transmission, but mosquito control could stop its progression. These factors together contribute to the observed distributions of dengue incidence from surveillance systems. To effectively and efficiently monitor and response to dengue outbreak, it would be necessary to systematically model these factors and their impacts on dengue transmission. This paper introduces a new modeling framework with consideration of multi-scale factors and surveillance data to clarify the hidden dynamics accounting for dengue spatiotemporal transmission. The model is based on compartmental system which takes into account the biting-based interactions among humans, viruses and mosquitoes, as well as the essential impacts of human mobility, temperature and mosquito control. This framework was validated with real epidemic data by applying retrospectively to the 2014 dengue epidemic in the Pearl River Delta (PRD) in southern China. The results indicated that suitable condition of temperature could be responsible for the explosive dengue outbreak in the PRD, and human mobility could be the causal factor leading to its spatial transmission across different cities. It was further found that mosquito intervention has significantly reduced dengue incidence, where a total of 52,770 (95% confidence interval [CI]: 29,231-76,308) dengue cases were prevented in the PRD in 2014. The findings can offer new insights for improving the predictability and risk assessment of dengue epidemics. The model also can be readily extended to investigate the transmission dynamics of other mosquito-borne diseases.
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Affiliation(s)
- Guanghu Zhu
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; Department of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004, China; Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Tao Liu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Bing Zhang
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Tie Song
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Yonghui Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Zhiqiang Peng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Aiping Deng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Wenjun Ma
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China.
| | - Yuantao Hao
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
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31
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Floyd JR, Ruktanonchai NW, Wardrop N, Tatem AJ, Ogola J, Fèvre EM. Exploring fine-scale human and livestock movement in western Kenya. One Health 2019; 7:100081. [PMID: 30911595 PMCID: PMC6416412 DOI: 10.1016/j.onehlt.2019.100081] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Revised: 12/29/2018] [Accepted: 02/07/2019] [Indexed: 12/03/2022] Open
Abstract
Human and livestock mobility are key factors in the transmission of several high-burden zoonoses such as rift valley fever and trypanosomiasis, yet our knowledge of this mobility is relatively poor due to difficulty in quantifying population-level movement patterns. Significant variation in the movement patterns of individual hosts means it is necessary to capture their fine-scale mobility in order to gain useful knowledge that can be extrapolated to a population level. Here we explore how the movements of people and their ruminants, and their exposure to various types of land cover, correlate with ruminant ownership and other demographic factors which could affect individual exposure to zoonoses. The study was conducted in Busia County, western Kenya, where the population are mostly subsistence farmers operating a mixed crop/livestock farming system. We used GPS trackers to collect movement data from 26 people and their ruminants for 1 week per individual in July/August 2016, and the study was repeated at the end of the same year to compare movement patterns between the short rainy and dry seasons respectively. We found that during the dry season, people and their ruminants travelled further on trips outside of the household, and that people spent less time on swampland compared to the short rainy season. Our findings also showed that ruminant owners spent longer and travelled further on trips outside the household than non-ruminant owners, and that people and ruminants from poorer households travelled further than people from relatively wealthier households. These results indicate that some individual-level mobility may be predicted by season and by household characteristics such as ruminant ownership and household wealth, which could have practical uses for assessing individual risk of exposure to some zoonoses and for future modelling studies of zoonosis transmission in similar rural areas.
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Affiliation(s)
- Jessica R Floyd
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Nick W Ruktanonchai
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK.,Flowminder Foundation, Stockholm, Sweden
| | - Nicola Wardrop
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Andrew J Tatem
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK.,Flowminder Foundation, Stockholm, Sweden
| | - Joseph Ogola
- International Livestock Research Institute, Old Naivasha Road, PO BOX 30709, 00100 Nairobi, Kenya
| | - Eric M Fèvre
- International Livestock Research Institute, Old Naivasha Road, PO BOX 30709, 00100 Nairobi, Kenya.,Institute of Infection and Global Health, University of Liverpool, Leahurst Campus, Neston, UK
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32
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Truelove SA, Graham M, Moss WJ, Metcalf CJE, Ferrari MJ, Lessler J. Characterizing the impact of spatial clustering of susceptibility for measles elimination. Vaccine 2019; 37:732-741. [PMID: 30579756 PMCID: PMC6348711 DOI: 10.1016/j.vaccine.2018.12.012] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Revised: 12/07/2018] [Accepted: 12/11/2018] [Indexed: 01/16/2023]
Abstract
Measles elimination efforts are primarily focused on achieving and maintaining national vaccination coverage goals, based on estimates of the critical vaccination threshold (Vc): the proportion of the population that must be immune to prevent sustained epidemics. Traditionally, Vc estimates assume evenly mixing populations, an invalid assumption. If susceptible individuals preferentially contact one another, communities may remain vulnerable to epidemics even when vaccination coverage targets are met at the national level. Here we present a simple method to estimate Vc and the effective reproductive number, R, while accounting for spatial clustering of susceptibility. For measles, assuming R0 = 15 and 95% population immunity, adjustment for high clustering of susceptibility increases R from 0.75 to 1.29, Vc from 93% to 96%, and outbreak probability after a single introduction from <1% to 23%. The impact of clustering remains minimal until vaccination coverage nears elimination levels. We illustrate our approach using Demographic and Health Survey data from Tanzania and show how non-vaccination clustering potentially contributed to continued endemic transmission of measles virus during the last two decades. Our approach demonstrates why high national vaccination coverage sometimes fails to achieve measles elimination, and that a shift from national to subnational focus is needed as countries approach elimination.
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Affiliation(s)
- Shaun A Truelove
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
| | - Matthew Graham
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA; The Hospital for Tropical Diseases, Wellcome Trust Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
| | - William J Moss
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - C Jessica E Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA; Office of Population Research, Woodrow Wilson School, Princeton University, Princeton, NJ, USA
| | - Matthew J Ferrari
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA; Department of Biology, The Pennsylvania State University, University Park, PA, USA
| | - Justin Lessler
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
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33
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Carrasco-Escobar G, Castro MC, Barboza JL, Ruiz-Cabrejos J, Llanos-Cuentas A, Vinetz JM, Gamboa D. Use of open mobile mapping tool to assess human mobility traceability in rural offline populations with contrasting malaria dynamics. PeerJ 2019; 7:e6298. [PMID: 30697487 PMCID: PMC6346981 DOI: 10.7717/peerj.6298] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 12/18/2018] [Indexed: 11/20/2022] Open
Abstract
Infectious disease dynamics are affected by human mobility more powerfully than previously thought, and thus reliable traceability data are essential. In rural riverine settings, lack of infrastructure and dense tree coverage deter the implementation of cutting-edge technology to collect human mobility data. To overcome this challenge, this study proposed the use of a novel open mobile mapping tool, GeoODK. This study consists of a purposive sampling of 33 participants in six villages with contrasting patterns of malaria transmission that demonstrates a feasible approach to map human mobility. The self-reported traceability data allowed the construction of the first human mobility framework in rural riverine villages in the Peruvian Amazon. The mobility spectrum in these areas resulted in travel profiles ranging from 2 hours to 19 days; and distances between 10 to 167 km. Most Importantly, occupational-related mobility profiles with the highest displacements (in terms of time and distance) were observed in commercial, logging, and hunting activities. These data are consistent with malaria transmission studies in the area that show villages in watersheds with higher human movement are concurrently those with greater malaria risk. The approach we describe represents a potential tool to gather critical information that can facilitate malaria control activities.
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Affiliation(s)
- Gabriel Carrasco-Escobar
- Laboratorio ICEMR-Amazonia, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru.,Division of Infectious Diseases, Department of Medicine, University of California, San Diego, La Jolla, CA, United States of America
| | - Marcia C Castro
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America
| | - Jose Luis Barboza
- Laboratorio ICEMR-Amazonia, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Jorge Ruiz-Cabrejos
- Laboratorio ICEMR-Amazonia, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Alejandro Llanos-Cuentas
- Instituto de Medicinal Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Joseph M Vinetz
- Instituto de Medicinal Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru.,Department of Infectious diseases, School of Medicine, Yale University, New Haven, CT, United States of America
| | - Dionicia Gamboa
- Laboratorio ICEMR-Amazonia, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru.,Instituto de Medicinal Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru.,Departamento de Ciencias Celulares y Moleculares, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
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34
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Measuring and characterizing night time human behaviour as it relates to residual malaria transmission in sub-Saharan Africa: a review of the published literature. Malar J 2019; 18:6. [PMID: 30634963 PMCID: PMC6329148 DOI: 10.1186/s12936-019-2638-9] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Accepted: 01/08/2019] [Indexed: 11/29/2022] Open
Abstract
Background Malaria cases and deaths decreased dramatically in recent years, largely due to effective vector control interventions. Persistence of transmission after good coverage has been achieved with high-quality vector control interventions, namely insecticide-treated nets or indoor residual spraying, poses a significant challenge to malaria elimination efforts. To understand when and where remaining transmission is occurring, it is necessary to look at vector and human behaviour, and where they overlap. To date, a review of human behaviour related to residual malaria transmission has not been conducted. Methods Studies were identified through PubMed and Google Scholar. Hand searches were conducted for all references cited in articles identified through the initial search. The review was limited to English language articles published between 2000 and 2017. Publications with primary data from a malaria endemic setting in sub-Saharan Africa and a description of night time human behaviours were included. Results Twenty-six publications were identified that met inclusion criteria. Study results fit into two broad categories: when and where people are exposed to malaria vectors and what people are doing at night that may increase their contact with malaria vectors. Among studies that quantified human-vector interaction, a majority of exposure occurred indoors during sleeping hours for unprotected individuals, with some variation across time, contexts, and vector species. Common night time activities across settings included household chores and entertainment during evening hours, as well as livelihood and large-scale socio-cultural events that can last throughout the night. Shifting sleeping patterns associated with travel, visitors, illness, farming practices, and outdoor sleeping, which can impact exposure and use of prevention measures, were described in some locations. Conclusions While the importance of understanding human-vector interaction is well-established, relatively few studies have included human behaviour when measuring exposure to malaria vectors. Broader application of a standardized approach to measuring human-vector interaction could provide critical information on exposure across settings and over time. In-depth understanding of night time activities that occur during times when malaria vectors are active and barriers to prevention practices in different contexts should also be considered. This information is essential for targeting existing interventions and development and deployment of appropriate complementary prevention tools.
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35
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Mapping Rural Road Networks from Global Positioning System (GPS) Trajectories of Motorcycle Taxis in Sigomre Area, Siaya County, Kenya. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 2018. [DOI: 10.3390/ijgi7080309] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Effective transport infrastructure is an essential component of economic integration, accessibility to vital social services and a means of mitigation in times of emergency. Rural areas in Africa are largely characterized by poor transport infrastructure. This poor state of rural road networks contributes to the vulnerability of communities in developing countries by hampering access to vital social services and opportunities. In addition, maps of road networks are incomplete, and not up-to-date. Lack of accurate maps of village-level road networks hinders determination of access to social services and timely response to emergencies in remote locations. In some countries in sub-Saharan Africa, communities in rural areas and some in urban areas have devised an alternative mode of public transport system that is reliant on motorcycle taxis. This new mode of transport has improved local mobility and has created a vibrant economy that depends on the motorcycle taxi business. The taxi system also offers an opportunity for understanding local-level mobility and the characterization of the underlying transport infrastructure. By capturing the spatial and temporal characteristics of the taxis, we could design detailed maps of rural infrastructure and reveal the human mobility patterns that are associated with the motorcycle taxi system. In this study, we tracked motorcycle taxis in a rural area in Kenya by tagging volunteer riders with Global Positioning System (GPS) data loggers. A semi-automatic method was applied on the resulting trajectories to map rural-level road networks. The results showed that GPS trajectories from motorcycle taxis could potentially improve the maps of rural roads and augment other mapping initiatives like OpenStreetMap.
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36
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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: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [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.
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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
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