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Pongsoipetch K, Walshe R, Mukem S, Kamsri T, Singkham N, Sudathip P, Kitchakarn S, Maude RR, Maude RJ. Mapping malaria transmission foci in Northeast Thailand from 2011 to 2021: approaching elimination in a hypoendemic area. Malar J 2024; 23:212. [PMID: 39020432 PMCID: PMC11253324 DOI: 10.1186/s12936-024-05026-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 06/25/2024] [Indexed: 07/19/2024] Open
Abstract
BACKGROUND Thailand is approaching local elimination of malaria in the eastern provinces. It has successfully reduced the number of cases over the past decade, but there are persistent transmission hot spots in and around forests. This study aimed to use data from the malaria surveillance system to describe the spatiotemporal trends of malaria in Northeast Thailand and fine-scale patterns in locally transmitted cases between 2011 and 2021. METHODS Case data was stratified based on likely location of infection and parasite species. Annual Parasite Index per 1000 population (API) was calculated for different categories. Time series decomposition was performed to identify trends and seasonal patterns. Statistically significant clusters of high (hot spots) and low (cold spots) API were identified using the Getis-Ord Gi* statistic. The stability of those hot spots and the absolute change in the proportion of API density from baseline were compared by case type. RESULTS The total number of confirmed cases experienced a non-linear decline by 96.6%, from 1061 in 2011 to 36 in 2021. There has been a decline in both Plasmodium vivax and Plasmodium falciparum case numbers, with only four confirmed P. falciparum cases over the last two years-a 98.89% drop from 180 in 2011. API was generally higher in Si Sa Ket province, which had peaks every 2-3 years. There was a large outbreak in Ubon Ratchathani in 2014-2016 which had a high proportion of P. falciparum reported. The proportion of cases classified increased over the study period, and the proportion of cases classed as indigenous to the village of residence increased from 0.2% to 33.3%. There were stable hot spots of indigenous and imported cases in the south of Si Sa Ket and southeast of Ubon Ratchathani. Plasmodium vivax hot spots were observed into recent years, while those of P. falciparum decreased to zero in Ubon in 2020 and emerged in the eastern part in 2021, the same year that P. falciparum hot spots in Si Sa Ket reached zero. CONCLUSIONS There has been a large, non-linear decline in the number of malaria cases reported and an increasing proportion of cases are classed as indigenous to the patient's village of residence. Stable hot spots of ongoing transmission in the forested border areas were identified, with transmission likely persisting because of remote location and high-risk forest-going behaviours. Future efforts should include cross-border collaboration and continued targeting of high-risk behaviours to reduce the risk of imported cases seeding local transmission.
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Affiliation(s)
- Kulchada Pongsoipetch
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Rebecca Walshe
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
- Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Suwanna Mukem
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Tanong Kamsri
- Phibun Mangsahan Hospital, Ubon Ratchathani, Thailand
- Provincial Health Office, Ubon Ratchathani, Thailand
| | | | - Prayuth Sudathip
- Division of Vector Borne Diseases, Department of Disease Control, Ministry of Public Health, Nonthaburi, 11000, Thailand
| | - Suravadee Kitchakarn
- Division of Vector Borne Diseases, Department of Disease Control, Ministry of Public Health, Nonthaburi, 11000, Thailand
| | | | - Richard James Maude
- 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.
- The Open University, Milton Keynes, UK.
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Meredith HR, Wesolowski A, Okoth D, Maraga L, Ambani G, Chepkwony T, Abel L, Kipkoech J, Lokoel G, Esimit D, Lokemer S, Maragia J, Prudhomme O’Meara W, Obala AA. Characterizing mobility patterns and malaria risk factors in semi-nomadic populations of Northern Kenya. PLOS GLOBAL PUBLIC HEALTH 2024; 4:e0002750. [PMID: 38478562 PMCID: PMC10936864 DOI: 10.1371/journal.pgph.0002750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 02/12/2024] [Indexed: 03/17/2024]
Abstract
While many studies have characterized mobility patterns and disease dynamics of settled populations, few have focused on more mobile populations. Highly mobile groups are often at higher disease risk due to their regular movement that may increase the variability of their environments, reduce their access to health care, and limit the number of intervention strategies suitable for their lifestyles. Quantifying the movements and their associated disease risks will be key to developing interventions more suitable for mobile populations. Turkana, Kenya is an ideal setting to characterize these relationships. While the vast, semi-arid county has a large mobile population (>60%) and was recently shown to have endemic malaria, the relationship between mobility and malaria risk in this region has not yet been defined. Here, we worked with 250 semi-nomadic households from four communities in Central Turkana to 1) characterize mobility patterns of travelers and 2) test the hypothesis that semi-nomadic individuals are at greater risk of malaria exposure when migrating with their herds than when staying at their semi-permanent settlements. Participants provided medical and travel histories, demographics, and a dried blood spot for malaria testing before and after the travel period. Further, a subset of travelers was given GPS loggers to document their routes. Four travel patterns emerged from the logger data, Long Term, Transient, Day trip, and Static, with only Long Term and Transient trips being associated with malaria cases detected in individuals who carried GPS devices. After completing their trips, travelers had a higher prevalence of malaria than those who remained at the household (9.2% vs 4.4%), regardless of gender and age. These findings highlight the need to develop intervention strategies amenable to mobile lifestyles that can ultimately help prevent the transmission of malaria.
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Affiliation(s)
- Hannah R. Meredith
- Duke Global Health Institute, Durham, North Carolina, United States of America
| | - Amy Wesolowski
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Dennis Okoth
- Department of Health Services and Sanitation, Lodwar, Turkana County, Kenya
| | - Linda Maraga
- Academic Model Providing Access to Healthcare, Eldoret, Kenya
| | - George Ambani
- Academic Model Providing Access to Healthcare, Eldoret, Kenya
| | | | - Lucy Abel
- Academic Model Providing Access to Healthcare, Eldoret, Kenya
| | - Joseph Kipkoech
- Academic Model Providing Access to Healthcare, Eldoret, Kenya
| | - Gilchrist Lokoel
- Department of Health Services and Sanitation, Lodwar, Turkana County, Kenya
| | - Daniel Esimit
- Department of Health Services and Sanitation, Lodwar, Turkana County, Kenya
| | - Samuel Lokemer
- Department of Health Services and Sanitation, Lodwar, Turkana County, Kenya
| | - James Maragia
- Department of Health Services and Sanitation, Lodwar, Turkana County, Kenya
| | - Wendy Prudhomme O’Meara
- Duke Global Health Institute, Durham, North Carolina, United States of America
- School of Public Health, Moi University College of Health Sciences, Eldoret, Kenya
- School of Medicine, Duke University, Durham, North Carolina, United States of America
| | - Andrew A. Obala
- School of Medicine, Moi University College of Health Sciences, Eldoret, Kenya
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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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Meredith HR, Wesolowski A, Okoth D, Maraga L, Ambani G, Chepkwony T, Abel L, Kipkoech J, Lokoel G, Esimit D, Lokemer S, Maragia J, O’Meara WP, Obala AA. Characterizing mobility patterns and malaria risk factors in semi-nomadic populations of Northern Kenya. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.06.23299617. [PMID: 38106223 PMCID: PMC10723563 DOI: 10.1101/2023.12.06.23299617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
While many studies have characterized mobility patterns and disease dynamics of individuals from settled populations, few have focused on more mobile populations. Highly mobile groups are often at higher disease risk due to their regular movement that may increase the variability of their environments, reduce their access to health care, and limit the number of intervention strategies suitable for their lifestyles. Quantifying the movements and their associated disease risks will be key to developing intervention strategies more suitable for mobile populations. Here, we worked with four semi-nomadic communities in Central Turkana, Kenya to 1) characterize mobility patterns of travelers from semi-nomadic communities and 2) test the hypothesis that semi-nomadic individuals are at greater risk of exposure to malaria during seasonal migrations than when staying at their semi-permanent settlements. From March-October, 2021, we conducted a study in semi-nomadic households (n=250) where some members traveled with their herd while others remained at the semi-permanent settlement. Participants provided medical and travel histories, demographics, and a dried blood spot for malaria testing before and after the travel period. Further, a subset of travelers was given GPS loggers to document their routes. Four travel patterns emerged from the logger data, Long Term, Transient, Day trip, and Static, with only Long Term and Transient trips being associated with malaria cases detected in individuals who carried GPS devices. After completing their trips, travelers had a higher prevalence of malaria than those who remained at the household (9.2% vs 4.4%), regardless of gender, age group, and catchment area. These findings highlight the need to develop intervention strategies amenable to mobile lifestyles that can ultimately help prevent the transmission of malaria.
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Affiliation(s)
| | - Amy Wesolowski
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Dennis Okoth
- Department of Health Services and Sanitation, Turkana County, Kenya
| | - Linda Maraga
- Academic Model Providing Access to Healthcare, Eldoret, Uasin Gishu, Kenya
| | - George Ambani
- Academic Model Providing Access to Healthcare, Eldoret, Uasin Gishu, Kenya
| | - Tabitha Chepkwony
- Academic Model Providing Access to Healthcare, Eldoret, Uasin Gishu, Kenya
| | - Lucy Abel
- Academic Model Providing Access to Healthcare, Eldoret, Uasin Gishu, Kenya
| | - Joseph Kipkoech
- Academic Model Providing Access to Healthcare, Eldoret, Uasin Gishu, Kenya
| | - Gilchrist Lokoel
- Department of Health Services and Sanitation, Turkana County, Kenya
| | - Daniel Esimit
- Department of Health Services and Sanitation, Turkana County, Kenya
| | - Samuel Lokemer
- Department of Health Services and Sanitation, Turkana County, Kenya
| | - James Maragia
- Department of Health Services and Sanitation, Turkana County, Kenya
| | - Wendy Prudhomme O’Meara
- Duke Global Health Institute, Durham, North Carolina, USA
- School of Public Health, Moi University College of Health Sciences, Eldoret, Uasin Gishu, Kenya
- School of Medicine, Duke University, Durham, North Carolina, USA
| | - Andrew A. Obala
- School of Medicine, Moi University College of Health Sciences, Eldoret, Uasin Gishu, Kenya
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