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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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3
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Ferriss E, Chaponda M, Muleba M, Kabuya JB, Lupiya JS, Riley C, Winters A, Moulton LH, Mulenga M, Norris DE, Moss WJ. The Impact of Household and Community Indoor Residual Spray Coverage with Fludora Fusion in a High Malaria Transmission Setting in Northern Zambia. Am J Trop Med Hyg 2023; 109:248-257. [PMID: 37364860 PMCID: PMC10397455 DOI: 10.4269/ajtmh.22-0440] [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: 07/01/2022] [Accepted: 04/24/2023] [Indexed: 06/28/2023] Open
Abstract
Zambia's National Malaria Elimination Program transitioned to Fludora Fusion in 2019 for annual indoor residual spraying (IRS) in Nchelenge District, an area with holoendemic malaria transmission. Previously, IRS was associated with reductions in parasite prevalence during the rainy season only, presumably because of insufficient residual insecticide longevity. This study assessed the impact of transitioning from Actellic 300CS to long-acting Fludora Fusion using active surveillance data from 2014 through 2021. A difference-in-differences analysis estimated changes in rainy season parasite prevalence associated with living in a sprayed house, comparing insecticides. The change in the 2020 to 2021 dry season parasite prevalence associated with living in a house sprayed with Fludora Fusion was also estimated. Indoor residual spraying with Fludora Fusion was not associated with decreased rainy season parasite prevalence compared with IRS with Actellic 300CS (ratio of prevalence ratios [PRs], 1.09; 95% CI, 0.89-1.33). Moreover, living in a house sprayed with either insecticide was not associated with decreased malaria risk (Actellic 300CS: PR, 0.97; 95% CI, 0.86-1.10; Fludora Fusion: rainy season PR, 1.06; 95% CI, 0.89-1.25; dry season PR, 1.21; 95% CI, 0.99-1.48). In contrast, each 10% increase in community IRS coverage was associated with a 4% to 5% reduction in parasite prevalence (rainy season: PR, 0.95; 95% CI, 0.92-0.97; dry season: PR, 0.96; 95% CI, 0.94-0.99), suggesting a community-level protective effect, and corroborating the importance of high-intervention coverage.
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Affiliation(s)
- Ellen Ferriss
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | | | | | | | | | | | - Anna Winters
- Akros, Lusaka, Zambia
- University of Montana, Missoula, Montana
| | - Lawrence H. Moulton
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Pfizer Canada, Quebec, Canada
| | - Modest Mulenga
- Directorate of Research and Postgraduate Studies, Lusaka Apex Medical University, Lusaka, Zambia
| | - Douglas E. Norris
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - William J. Moss
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
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4
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Li Y, Stewart K, Han KT, Han ZY, Aung PP, Thein ZW, Htay T, Chen D, Nyunt MM, Plowe CV. Understanding Spatiotemporal Human Mobility Patterns for Malaria Control Using a Multiagent Mobility Simulation Model. Clin Infect Dis 2023; 76:e867-e874. [PMID: 35851600 PMCID: PMC10169429 DOI: 10.1093/cid/ciac568] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 06/24/2022] [Accepted: 07/07/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND More details about human movement patterns are needed to evaluate relationships between daily travel and malaria risk at finer scales. A multiagent mobility simulation model was built to simulate the movements of villagers between home and their workplaces in 2 townships in Myanmar. METHODS An agent-based model (ABM) was built to simulate daily travel to and from work based on responses to a travel survey. Key elements for the ABM were land cover, travel time, travel mode, occupation, malaria prevalence, and a detailed road network. Most visited network segments for different occupations and for malaria-positive cases were extracted and compared. Data from a separate survey were used to validate the simulation. RESULTS Mobility characteristics for different occupation groups showed that while certain patterns were shared among some groups, there were also patterns that were unique to an occupation group. Forest workers were estimated to be the most mobile occupation group, and also had the highest potential malaria exposure associated with their daily travel in Ann Township. In Singu Township, forest workers were not the most mobile group; however, they were estimated to visit regions that had higher prevalence of malaria infection over other occupation groups. CONCLUSIONS Using an ABM to simulate daily travel generated mobility patterns for different occupation groups. These spatial patterns varied by occupation. Our simulation identified occupations at a higher risk of being exposed to malaria and where these exposures were more likely to occur.
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Affiliation(s)
- Yao Li
- Department of Geographical Sciences, Center for Geospatial Information Science, University of Maryland, College Park, Maryland, USA
| | - Kathleen Stewart
- Department of Geographical Sciences, Center for Geospatial Information Science, University of Maryland, College Park, Maryland, USA
| | - Kay Thwe Han
- Department of Medical Research, Ministry of Health and Sports, Yangon, Myanmar
| | - Zay Yar Han
- Department of Medical Research, Ministry of Health and Sports, Yangon, Myanmar.,Duke Global Health Institute, Duke University, Durham, North Carolina, USA
| | - Poe P Aung
- Duke Global Health Institute, Duke University, Durham, North Carolina, USA
| | - Zaw W Thein
- Duke Global Health Institute, Duke University, Durham, North Carolina, USA
| | - Thura Htay
- Duke Global Health Institute, Duke University, Durham, North Carolina, USA
| | - Dong Chen
- Department of Geographical Sciences, University of Maryland, College Park, Maryland, USA
| | - Myaing M Nyunt
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Christopher V Plowe
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, Maryland, USA
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5
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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: 1] [Impact Index Per Article: 1.0] [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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6
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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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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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Wesolowski A, 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, 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 P, Moss WJ. Policy Implications 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; 107:68-74. [PMID: 36228913 PMCID: PMC9662215 DOI: 10.4269/ajtmh.21-1288] [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: 12/13/2021] [Accepted: 05/28/2022] [Indexed: 11/07/2022] Open
Abstract
The International Centers of Excellence for Malaria Research (ICEMR) were established by the National Institute of Allergy and Infectious Diseases more than a decade ago to provide multidisciplinary research support to malaria control programs worldwide, operating in endemic areas and contributing technology, expertise, and ultimately policy guidance for malaria control and elimination. The Southern and Central Africa ICEMR has conducted research across three main sites in Zambia and Zimbabwe that differ in ecology, entomology, transmission intensity, and control strategies. Scientific findings led to new policies and action by the national malaria control programs and their partners in the selection of methods, materials, timing, and locations of case management and vector control. Malaria risk maps and predictive models of case detection furnished by the ICEMR informed malaria elimination programming in southern Zambia, and time series analyses of entomological and parasitological data motivated several major changes to indoor residual spray campaigns in northern Zambia. Along the Zimbabwe-Mozambique border, temporal and geospatial data are currently informing investigations into a recent resurgence of malaria. Other ICEMR findings pertaining to parasite and mosquito genetics, human behavior, and clinical epidemiology have similarly yielded immediate and long-term policy implications at each of the sites, often with generalizable conclusions. The ICEMR programs thereby provide rigorous scientific investigations and analyses to national control and elimination programs, without which the impediments to malaria control and their potential solutions would remain understudied.
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Affiliation(s)
- Amy Wesolowski
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Matthew M. Ippolito
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Johns Hopkins University School of Medicine, 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
| | | | | | | | | | | | | | | | | | | | | | | | | | - 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
| | - Philip E. Thuma
- 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 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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9
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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: 5] [Impact Index Per Article: 2.5] [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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10
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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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11
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Magowan EA, Maguire IE, Smith S, Redpath S, Marks NJ, Wilson RP, Menzies F, O’Hagan M, Scantlebury DM. Dead-reckoning elucidates fine-scale habitat use by European badgers Meles meles. ANIMAL BIOTELEMETRY 2022; 10:10. [PMID: 37521810 PMCID: PMC8908954 DOI: 10.1186/s40317-022-00282-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 02/23/2022] [Indexed: 05/03/2023]
Abstract
Background Recent developments in both hardware and software of animal-borne data loggers now enable large amounts of data to be collected on both animal movement and behaviour. In particular, the combined use of tri-axial accelerometers, tri-axial magnetometers and GPS loggers enables animal tracks to be elucidated using a procedure of 'dead-reckoning'. Although this approach was first suggested 30 years ago by Wilson et al. (1991), surprisingly few measurements have been made in free-ranging terrestrial animals. The current study examines movements, interactions with habitat features, and home-ranges calculated from just GPS data and also from dead-reckoned data in a model terrestrial mammal, the European badger (Meles meles). Methods Research was undertaken in farmland in Northern Ireland. Two badgers (one male, one female) were live-trapped and fitted with a GPS logger, a tri-axial accelerometer, and a tri-axial magnetometer. Thereafter, the badgers' movement paths over 2 weeks were elucidated using just GPS data and GPS-enabled dead-reckoned data, respectively. Results Badgers travelled further using data from dead-reckoned calculations than using the data from only GPS data. Whilst once-hourly GPS data could only be represented by straight-line movements between sequential points, the sub-second resolution dead-reckoned tracks were more tortuous. Although there were no differences in Minimum Convex Polygon determinations between GPS- and dead-reckoned data, Kernel Utilisation Distribution determinations of home-range size were larger using the former method. This was because dead-reckoned data more accurately described the particular parts of landscape constituting most-visited core areas, effectively narrowing the calculation of habitat use. Finally, the dead-reckoned data showed badgers spent more time near to field margins and hedges than simple GPS data would suggest. Conclusion Significant differences emerge when analyses of habitat use and movements are compared between calculations made using just GPS data or GPS-enabled dead-reckoned data. In particular, use of dead-reckoned data showed that animals moved 2.2 times farther, had better-defined use of the habitat (revealing clear core areas), and made more use of certain habitats (field margins, hedges). Use of dead-reckoning to provide detailed accounts of animal movement and highlight the minutiae of interactions with the environment should be considered an important technique in the ecologist's toolkit.
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Affiliation(s)
- E. A. Magowan
- School of Biological Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL Northern Ireland UK
- Randox Laboratories Ltd. Crumlin, Antrim, Northern Ireland UK
| | - I. E. Maguire
- School of Biological Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL Northern Ireland UK
- Randox Laboratories Ltd. Crumlin, Antrim, Northern Ireland UK
| | - S. Smith
- School of Biological Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL Northern Ireland UK
| | - S. Redpath
- School of Biological Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL Northern Ireland UK
| | - N. J. Marks
- School of Biological Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL Northern Ireland UK
| | - R. P. Wilson
- Department of Biological Sciences, Institute of Environmental Sustainability, Swansea University, Swansea, UK
| | - F. Menzies
- Department of Agriculture, Environment and Rural Affairs, Veterinary Epidemiology Unit, Belfast, UK
| | - M. O’Hagan
- Department of Agriculture, Environment and Rural Affairs, Veterinary Epidemiology Unit, Belfast, UK
| | - D. M. Scantlebury
- School of Biological Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL Northern Ireland UK
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12
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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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13
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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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14
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Ghanbarnejad A, Turki H, Yaseri M, Raeisi A, Rahimi-Foroushani A. Spatial Modelling of Malaria in South of Iran in Line with the Implementation of the Malaria Elimination Program: A Bayesian Poisson-Gamma Random Field Model. J Arthropod Borne Dis 2021; 15:108-125. [PMID: 34277860 PMCID: PMC8271232 DOI: 10.18502/jad.v15i1.6490] [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: 08/13/2020] [Accepted: 03/30/2021] [Indexed: 12/07/2022] Open
Abstract
Background: Malaria is the third most important infectious disease in the world. WHO propose programs for controlling and elimination of the disease. Malaria elimination program has begun in first phase in Iran from 2010. Climate factors play an important role in transmission and occurrence of malaria infection. The main goal is to investigate the spatial distribution of incidence of malaria during April 2011 to March 2018 in Hormozgan Province and its association with climate covariates. Methods: The data included 882 confirmed cases gathered from CDC in Hormozgan University of Medical Sciences. A Poisson-Gamma Random field model with Bayesian approach was used for modeling the data and produces the smoothed standardized incidence rate (SIR). Results: The SIR for malaria ranged from 0 (Abu Musa and Haji Abad districts) to 280.57 (Bandar–e-Jask). Based on model, temperature (RR= 2.29; 95% credible interval: (1.92–2.78)) and humidity (RR= 1.04; 95% credible interval: (1.03–1.06)) had positive effect on malaria incidence, but rainfall (RR= 0.92; 95% credible interval: (0.90–0.95)) had negative impact. Also, smoothed map represent hot spots in the east of the province and in Qeshm Island. Conclusion: Based on the analysis of the study results, it was found that the ecological conditions of the region (temperature, humidity and rainfall) and population displacement play an important role in the incidence of malaria. Therefore, the malaria surveillance system should continue to be active in the region, focusing on high-risk areas of malaria.
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Affiliation(s)
- Amin Ghanbarnejad
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Habibollah Turki
- Infectious and Tropical Diseases Research Center, Hormozgan Health Institute, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Mehdi Yaseri
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Ahmad Raeisi
- Departments of Medical Parasitology and Mycology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.,Center for Communicable Diseases Control, Ministry of Health and Medical Education, Tehran, Iran
| | - Abbas Rahimi-Foroushani
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
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15
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Wimberly MC, de Beurs KM, Loboda TV, Pan WK. Satellite Observations and Malaria: New Opportunities for Research and Applications. Trends Parasitol 2021; 37:525-537. [PMID: 33775559 PMCID: PMC8122067 DOI: 10.1016/j.pt.2021.03.003] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 03/04/2021] [Accepted: 03/05/2021] [Indexed: 12/15/2022]
Abstract
Satellite remote sensing provides a wealth of information about environmental factors that influence malaria transmission cycles and human populations at risk. Long-term observations facilitate analysis of climate–malaria relationships, and high-resolution data can be used to assess the effects of agriculture, urbanization, deforestation, and water management on malaria. New sources of very-high-resolution satellite imagery and synthetic aperture radar data will increase the precision and frequency of observations. Cloud computing platforms for remote sensing data combined with analysis-ready datasets and high-level data products have made satellite remote sensing more accessible to nonspecialists. Further collaboration between the malaria and remote sensing communities is needed to develop and implement useful geospatial data products that will support global efforts toward malaria control, elimination, and eradication.
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Affiliation(s)
- Michael C Wimberly
- Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK, USA.
| | - Kirsten M de Beurs
- Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK, USA
| | - Tatiana V Loboda
- Department of Geographical Sciences, University of Maryland, College Park, MD, USA
| | - William K Pan
- Duke Global Health Institute, Duke University, Durham, NC, USA
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16
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Wojtusiak J, Bagchi P, Durbha SSKRTN, Mobahi H, Mogharab Nia R, Roess A. COVID-19 Symptom Monitoring and Social Distancing in a University Population. JOURNAL OF HEALTHCARE INFORMATICS RESEARCH 2021; 5:114-131. [PMID: 33437913 PMCID: PMC7790352 DOI: 10.1007/s41666-020-00089-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 11/20/2020] [Accepted: 12/03/2020] [Indexed: 12/14/2022]
Abstract
This paper reports on our efforts to collect daily COVID-19-related symptoms for a large public university population, as well as study relationship between reported symptoms and individual movements. We developed a set of tools to collect and integrate individual-level data. COVID-19-related symptoms are collected using a self-reporting tool initially implemented in Qualtrics survey system and consequently moved to .NET framework. Individual movement data are collected using off-the-shelf tracking apps available for iPhone and Android phones. Data integration and analysis are done in PostgreSQL, Python, and R. As of September 2020, we collected about 184,000 daily symptom responses for 20,000 individuals, as well as over 15,000 days of GPS movement data for 175 individuals. The analysis of the data indicates that headache is the most frequently reported symptom, present almost always when any other symptoms are reported as indicated by derived association rules. It is followed by cough, sore throat, and aches. The study participants traveled on average 223.61 km every week with a large standard deviation of 254.53 and visited on average 5.77 ± 4.75 locations each week for at least 10 min. However, there is no evidence that reported symptoms or prior COVID-19 contact affects movements (p > 0.3 in most models). The evidence suggests that although some individuals limit their movements during pandemics, the overall study population do not change their movements as suggested by guidelines.
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Affiliation(s)
- Janusz Wojtusiak
- Health Informatics Program, Department of Health Administration and Policy, George Mason University, Fairfax, VA USA
| | - Pramita Bagchi
- Department of Statistics, George Mason University, Fairfax, VA USA
| | | | - Hedyeh Mobahi
- Health Informatics Program, Department of Health Administration and Policy, George Mason University, Fairfax, VA USA
| | - Reyhaneh Mogharab Nia
- Health Informatics Program, Department of Health Administration and Policy, George Mason University, Fairfax, VA USA
| | - Amira Roess
- Department of Global and Community Health, George Mason University, Fairfax, VA USA
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17
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Garber MD, McCullough LE, Mooney SJ, Kramer MR, Watkins KE, Lobelo RF, Flanders WD. At-risk-measure Sampling in Case-Control Studies with Aggregated Data. Epidemiology 2021; 32:101-110. [PMID: 33093327 PMCID: PMC7707160 DOI: 10.1097/ede.0000000000001268] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 09/23/2020] [Indexed: 11/26/2022]
Abstract
Transient exposures are difficult to measure in epidemiologic studies, especially when both the status of being at risk for an outcome and the exposure change over time and space, as when measuring built-environment risk on transportation injury. Contemporary "big data" generated by mobile sensors can improve measurement of transient exposures. Exposure information generated by these devices typically only samples the experience of the target cohort, so a case-control framework may be useful. However, for anonymity, the data may not be available by individual, precluding a case-crossover approach. We present a method called at-risk-measure sampling. Its goal is to estimate the denominator of an incidence rate ratio (exposed to unexposed measure of the at-risk experience) given an aggregated summary of the at-risk measure from a cohort. Rather than sampling individuals or locations, the method samples the measure of the at-risk experience. Specifically, the method as presented samples person-distance and person-events summarized by location. It is illustrated with data from a mobile app used to record bicycling. The method extends an established case-control sampling principle: sample the at-risk experience of a cohort study such that the sampled exposure distribution approximates that of the cohort. It is distinct from density sampling in that the sample remains in the form of the at-risk measure, which may be continuous, such as person-time or person-distance. This aspect may be both logistically and statistically efficient if such a sample is already available, for example from big-data sources like aggregated mobile-sensor data.
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Affiliation(s)
- Michael D. Garber
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
| | - Lauren E. McCullough
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
| | - Stephen J. Mooney
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA
- Harborview Injury Prevention & Research Center, University of Washington, Seattle, WA
| | - Michael R. Kramer
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
| | - Kari E. Watkins
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA
| | - R.L. Felipe Lobelo
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA
| | - W. Dana Flanders
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA
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18
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Hast MA, Stevenson JC, Muleba M, Chaponda M, Kabuya JB, Mulenga M, Shields T, Moss WJ, Norris DE, For The Southern And Central Africa International Centers Of Excellence In Malaria Research. The Impact of Three Years of Targeted Indoor Residual Spraying with Pirimiphos-Methyl on Household Vector Abundance in a High Malaria Transmission Area of Northern Zambia. Am J Trop Med Hyg 2020; 104:683-694. [PMID: 33350376 PMCID: PMC7866301 DOI: 10.4269/ajtmh.20-0537] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Accepted: 10/13/2020] [Indexed: 11/07/2022] Open
Abstract
The global malaria burden has decreased substantially, but gains have been uneven both within and between countries. In Zambia, the malaria burden remains high in northern and eastern regions of the country. To effectively reduce malaria transmission in these areas, evidence-based intervention strategies are needed. Zambia’s National Malaria Control Centre conducted targeted indoor residual spraying (IRS) in 40 high-burden districts from 2014 to 2016 using the novel organophosphate insecticide pirimiphos-methyl. The Southern and Central Africa International Centers of Excellence for Malaria Research conducted an evaluation of the impact of the IRS campaign on household vector abundance in Nchelenge District, Luapula Province. From April 2012 to July 2017, field teams conducted indoor overnight vector collections from 25 to 30 households per month using Centers for Disease Control light traps. Changes in indoor anopheline counts before versus after IRS were assessed by species using negative binomial regression models with robust standard errors, controlling for geographic and climatological covariates. Counts of Anopheles funestus declined by approximately 50% in the study area and within areas targeted for IRS, and counts of Anopheles gambiae declined by approximately 40%. Within targeted areas, An. funestus counts declined more in sprayed households than in unsprayed households; however, this relationship was not observed for An. gambiae. The moderate decrease in indoor vector abundance indicates that IRS with pirimiphos-methyl is an effective vector control measure, but a more comprehensive package of interventions is needed with sufficient coverage to effectively reduce the malaria burden in this setting.
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Affiliation(s)
- Marisa A Hast
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Jennifer C Stevenson
- Macha Research Trust, Choma, Zambia.,W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Mbanga Muleba
- The Tropical Diseases Research Centre, Ndola, Zambia
| | - Mike Chaponda
- The Tropical Diseases Research Centre, Ndola, Zambia
| | | | - Modest Mulenga
- Department of Public Health, Michael Chilufya Sata School of Medicine, The Copperbelt University, Kitwe, Zambia
| | - Timothy Shields
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - William J Moss
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Douglas E Norris
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
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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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