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1. Spatial-temporal patterns and risk factors for human leptospirosis in Thailand, 2012-2018

Author

Suchada Geawduanglek, Karine Chalvet-Monfray, Julien Cappelle, Phrutsamon Wongnak, and Sudarat Chadsuthi

Subjects
Leptospirose, Soil, Maladie de l'homme, Risk Factors, Environmental health, Analyse du risque, Facteur de risque, medicine, Animals, Humans, Leptospirosis, Surveillance épidémiologique, analyse spatiale, Leptospira, Multidisciplinary, U10 - Informatique, mathématiques et statistiques, Incidence, medicine.disease, Thailand, Geography, Modélisation, S50 - Santé humaine
Abstract

Leptospirosis is a globally important zoonotic disease. The disease is particularly important in tropical and subtropical countries. Infections in humans can be caused by exposure to infected animals or contaminated soil or water, which are suitable for Leptospira. To explore the cluster area, the Global Moran’s I index was calculated for incidences per 100,000 population at the province level during 2012–2018, using the monthly and annual data. The high-risk and low-risk provinces were identified using the local indicators of spatial association (LISA). The risk factors for leptospirosis were evaluated using a generalized linear mixed model (GLMM) with zero-inflation. We also added spatial and temporal correlation terms to take into account the spatial and temporal structures. The Global Moran’s I index showed significant positive values. It did not demonstrate a random distribution throughout the period of study. The high-risk provinces were almost all in the lower north-east and south parts of Thailand. For yearly reported cases, the significant risk factors from the final best-fitted model were population density, elevation, and primary rice arable areas. Interestingly, our study showed that leptospirosis cases were associated with large areas of rice production but were less prevalent in areas of high rice productivity. For monthly reported cases, the model using temperature range was found to be a better fit than using percentage of flooded area. The significant risk factors from the model using temperature range were temporal correlation, average soil moisture, normalized difference vegetation index, and temperature range. Temperature range, which has strongly negative correlation to percentage of flooded area was a significant risk factor for monthly data. Flood exposure controls should be used to reduce the risk of leptospirosis infection. These results could be used to develop a leptospirosis warning system to support public health organizations in Thailand.

Published
2022

2. Genetic surveillance in the Greater Mekong subregion and South Asia to support malaria control and elimination

Author

Jordi Landier, Abdullah Abu Sayeed, Seila Suon, Kim-Tuyen Nguyen, Kate Rowlands, Frank Smithuis, Chanon Kunasol, Chanaki Amaratunga, Sasithon Pukrittayakamee, Keobouphaphone Chindavongsa, Jacob Almagro Garcia, Richard D. Pearson, Mozam Ali, Xin Hui S Chan, Katie Love, Naomi Park, Pascal Ringwald, Richard J. Maude, Cristina V. Ariani, Mehul Dhorda, Marie A. Onyamboko, Daniel M. Parker, Tin Maung Hlaing, Scott Goodwin, Namfon Kotanan, Thang Ngo Duc, Gilles Delmas, Huy Rekol, Rick M. Fairhurst, Victoria Simpson, Arjen M. Dondorp, Le Thanh Dong, Bouasy Hongvanthong, Tran Tinh Hien, Rapeephan R. Maude, Thomas J. Peto, Shavanthi Rajatileka, Roberto Amato, Thanat Chookajorn, Ben Jeffery, Anna E. Jeffreys, Nicole Zdrojewski, Caterina I. Fanello, Eleanor Drury, Mihir Kekre, Myo Thant, John Sillitoe, Olivo Miotto, Aung Myint Thu, James J Callery, Subrata Baidya, Paul N. Newton, Ranitha Vongpromek, Prativa K Behera, Borimas Hanboonkunupakarn, Rob W. van der Pluijm, Jim Stalker, Anupkumar R. Anvikar, Sonexay Phalivong, Dawn Muddyman, Nguyen Thuy-Nhien, Christina Hubbart, Rithea Leang, Lorenz von Seidlein, Nicholas P. J. Day, Phrutsamon Wongnak, Jonathan Keatley, Hoa Nguyen, Cinzia Malangone, Parthasarathi Satpathi, Abul Faiz, Dysoley Lek, François Nosten, Christopher G Jacob, Rupam Tripura, Sara E. Canavati, Huynh Hong Quang, Kirk A. Rockett, Neena Valecha, Thuy Nguyen, Kimberly J. Johnson, Tran Minh Nhat, Didar Uddin, Caroline O. Buckee, Akhter ul Islam, Podjanee Jittamala, Mayfong Mayxay, Amir Hossain, Viengxay Vanisaveth, Elizabeth A. Ashley, Dominic P. Kwiatkowski, Sanghamitra Satpathi, Aung Pyae Phyo, Amar Tripura, Nguyen Hoang Chau, Sónia Gonçalves, Khin Lin, Cheah Huch, Wellcome Sanger Institute [Hinxton, Royaume-Uni], Oxford University Clinical Research Unit [Ho Chi Minh City] (OUCRU), Mahosot Hospital [Vientiane, Laos], Institute of Research and Education Development [Vientiane, Lao People’s Democratic Republic], University of Health Sciences [Vientiane, Laos] (UHS), University of Oxford [Oxford], Mahidol University [Bangkok], Harvard T.H. Chan School of Public Health, Institute of Malariology, Parasitology, and Entomology [Quy Nhon, Vietnam] (IMPE), Centre of Malariology, Parasitology, and Entomology [Vientiane, Lao People’s Democratic Republic] (CMPE), National Institute of Malariology, Parasitology and Entomology [Hanoi], National Center for Parasitology, Entomology and Malaria Control [Phnom Penh, Cambodia] (CNM), National Institute of Allergy and Infectious Diseases [Bethesda] (NIAID-NIH), National Institutes of Health [Bethesda] (NIH), Shoklo Malaria Research Unit [Mae Sot, Thailand] (SMRU), Mahidol Oxford Tropical Medicine Research Unit (MORU), University of Oxford [Oxford]-Mahidol University [Bangkok]-Wellcome Trust-University of Oxford [Oxford]-Mahidol University [Bangkok]-Wellcome Trust, Chittagong Medical College Hospital [Chittagong, Bangladesh] (CMCH), World Health Organization [Geneva], Institute of Malariology, Parasitology, and Entomology [Ho Chi Minh City, Vietnam] (IMPE), Vysnova Partners Inc [Hanoi, Vietnam] (VPI), University of Kinshasa (UNIKIN), Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), University of California [Irvine] (UCI), University of California, Royal Society of Thailand [Bangkok, Thailand], Myanmar Oxford Clinical Research Unit [Yangon, Myanmar], The Department of Medical Research (Upper Myanmar), Defence Services Medical Research Centre [Naypyitaw, Myanmar] (DSMRC), Midnapore Medical College [Midnapur, India] (MMC), ispat general hospital [Rourkela, India] (IGH), Agartala Medical College [Agartala, India] (AMC), National Institute of Malaria Research [New Dehli, Inde] (NIMR), Indian Council of Medical Research [New Dehli] (ICMR), Ramu Upazila Health Complex [Cox’s Bazar, Bangladesh] (RUHC), The Wellcome Trust Sanger Institute [Cambridge], WorldWide Antimalarial Resistance Network [Bangkok] (WWARN), WorldWide Antimalarial Resistance Network (WWARN), Université de Washington Seattle-Université de Washington Seattle, The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford, University of Oxford-Mahidol University [Bangkok]-Wellcome Trust-University of Oxford-Mahidol University [Bangkok]-Wellcome Trust, University of California [Irvine] (UC Irvine), University of California (UC), University of Washington [Seattle]-University of Washington [Seattle], and Malbec, Odile

Subjects
Plasmodium, History, [SDV]Life Sciences [q-bio], Drug Resistance, global health, Drug resistance, Barcode, law.invention, law, Genotype, Biology (General), Aetiology, Microbiology and Infectious Disease, 0303 health sciences, Bangladesh, General Neuroscience, General Medicine, asia, 3. Good health, [SDV] Life Sciences [q-bio], Geography, Infectious Diseases, Democratic Republic of the Congo, Medicine, epidemiology, Genetic Engineering, Malaria control, Infection, Research Article, medicine.medical_specialty, South asia, Asia, QH301-705.5, Science, infectious disease, Plasmodium falciparum, malaria, Library science, Southeastern, India, General Biochemistry, Genetics and Molecular Biology, Antimalarials, 03 medical and health sciences, Rare Diseases, Simple sample, Clinical Research, Environmental health, medicine, Genetics, Humans, Animals, Disease Eradication, 030304 developmental biology, drug resistance, General Immunology and Microbiology, 030306 microbiology, Public health, microbiology, Genetic data, Genetic Therapy, medicine.disease, genetic surveillance, Compendium, Resistance monitoring, Data sharing, Vector-Borne Diseases, Epidemiology and Global Health, Good Health and Well Being, Communicable Disease Control, Antimicrobial Resistance, Biochemistry and Cell Biology, Malaria, 2.6 Resources and infrastructure (aetiology)
Abstract

Author(s): Jacob, Christopher G; Thuy-Nhien, Nguyen; Mayxay, Mayfong; Maude, Richard J; Quang, Huynh Hong; Hongvanthong, Bouasy; Vanisaveth, Viengxay; Ngo Duc, Thang; Rekol, Huy; van der Pluijm, Rob; von Seidlein, Lorenz; Fairhurst, Rick; Nosten, Francois; Hossain, Md Amir; Park, Naomi; Goodwin, Scott; Ringwald, Pascal; Chindavongsa, Keobouphaphone; Newton, Paul; Ashley, Elizabeth; Phalivong, Sonexay; Maude, Rapeephan; Leang, Rithea; Huch, Cheah; Dong, Le Thanh; Nguyen, Kim-Tuyen; Nhat, Tran Minh; Hien, Tran Tinh; Nguyen, Hoa; Zdrojewski, Nicole; Canavati, Sara; Sayeed, Abdullah Abu; Uddin, Didar; Buckee, Caroline; Fanello, Caterina I; Onyamboko, Marie; Peto, Thomas; Tripura, Rupam; Amaratunga, Chanaki; Myint Thu, Aung; Delmas, Gilles; Landier, Jordi; Parker, Daniel M; Chau, Nguyen Hoang; Lek, Dysoley; Suon, Seila; Callery, James; Jittamala, Podjanee; Hanboonkunupakarn, Borimas; Pukrittayakamee, Sasithon; Phyo, Aung Pyae; Smithuis, Frank; Lin, Khin; Thant, Myo; Hlaing, Tin Maung; Satpathi, Parthasarathi; Satpathi, Sanghamitra; Behera, Prativa K; Tripura, Amar; Baidya, Subrata; Valecha, Neena; Anvikar, Anupkumar R; Ul Islam, Akhter; Faiz, Abul; Kunasol, Chanon; Drury, Eleanor; Kekre, Mihir; Ali, Mozam; Love, Katie; Rajatileka, Shavanthi; Jeffreys, Anna E; Rowlands, Kate; Hubbart, Christina S; Dhorda, Mehul; Vongpromek, Ranitha; Kotanan, Namfon; Wongnak, Phrutsamon; Almagro Garcia, Jacob; Pearson, Richard D; Ariani, Cristina V; Chookajorn, Thanat; Malangone, Cinzia; Nguyen, T; Stalker, Jim; Jeffery, Ben | Abstract: BackgroundNational Malaria Control Programmes (NMCPs) currently make limited use of parasite genetic data. We have developed GenRe-Mekong, a platform for genetic surveillance of malaria in the Greater Mekong Subregion (GMS) that enables NMCPs to implement large-scale surveillance projects by integrating simple sample collection procedures in routine public health procedures.MethodsSamples from symptomatic patients are processed by SpotMalaria, a high-throughput system that produces a comprehensive set of genotypes comprising several drug resistance markers, species markers and a genomic barcode. GenRe-Mekong delivers Genetic Report Cards, a compendium of genotypes and phenotype predictions used to map prevalence of resistance to multiple drugs.ResultsGenRe-Mekong has worked with NMCPs and research projects in eight countries, processing 9623 samples from clinical cases. Monitoring resistance markers has been valuable for tracking the rapid spread of parasites resistant to the dihydroartemisinin-piperaquine combination therapy. In Vietnam and Laos, GenRe-Mekong data have provided novel knowledge about the spread of these resistant strains into previously unaffected provinces, informing decision-making by NMCPs.ConclusionsGenRe-Mekong provides detailed knowledge about drug resistance at a local level, and facilitates data sharing at a regional level, enabling cross-border resistance monitoring and providing the public health community with valuable insights. The project provides a rich open data resource to benefit the entire malaria community.FundingThe GenRe-Mekong project is funded by the Bill and Melinda Gates Foundation (OPP11188166, OPP1204268). Genotyping and sequencing were funded by the Wellcome Trust (098051, 206194, 203141, 090770, 204911, 106698/B/14/Z) and Medical Research Council (G0600718). A proportion of samples were collected with the support of the UK Department for International Development (201900, M006212), and Intramural Research Program of the National Institute of Allergy and Infectious Diseases.

Published
2021
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3. Author response: Genetic surveillance in the Greater Mekong subregion and South Asia to support malaria control and elimination

Author

Jordi Landier, Frank Smithuis, Huy Rekol, Amar Tripura, Rapeephan R. Maude, Keobouphaphone Chindavongsa, Thomas J. Peto, Khin Lin, Dominic P. Kwiatkowski, Cristina V. Ariani, Naomi Park, Cheah Huch, Jacob Almagro Garcia, Sanghamitra Satpathi, Kimberly J. Johnson, Daniel M. Parker, Dawn Muddyman, Rithea Leang, Arjen M. Dondorp, Anna E. Jeffreys, Tin Maung Hlaing, Richard D. Pearson, Hoa Nguyen, Le Thanh Dong, Caroline O. Buckee, Scott Goodwin, Seila Suon, Ben Jeffery, Mihir Kekre, Caterina I. Fanello, Rupam Tripura, Kate Rowlands, Kirk A. Rockett, Rob W. van der Pluijm, Rick M. Fairhurst, Sonexay Phalivong, Namfon Kotanan, Sasithon Pukrittayakamee, Abdullah Abu Sayeed, Thang Ngo Duc, Nicholas P. J. Day, Shavanthi Rajatileka, Aung Myint Thu, James J Callery, Huynh Hong Quang, Eleanor Drury, Victoria Simpson, Myo Thant, Sara E. Canavati, Abul Faiz, Akhter ul Islam, Dysoley Lek, Christopher G Jacob, Jim Stalker, Anupkumar R. Anvikar, Chanon Kunasol, Lorenz von Seidlein, Podjanee Jittamala, Mayfong Mayxay, Elizabeth A. Ashley, Subrata Baidya, Paul N. Newton, Prativa K Behera, Parthasarathi Satpathi, François Nosten, Tran Minh Nhat, Borimas Hanboonkunupakarn, Pascal Ringwald, Neena Valecha, Thuy Nguyen, Didar Uddin, Christina Hubbart, Amir Hossain, Cinzia Malangone, Bouasy Hongvanthong, Aung Pyae Phyo, Tran Tinh Hien, Nicole Zdrojewski, Kim-Tuyen Nguyen, Ranitha Vongpromek, Chanaki Amaratunga, Nguyen Hoang Chau, Katie Love, Marie A. Onyamboko, Richard J. Maude, Xin Hui S Chan, Nguyen Thuy-Nhien, Phrutsamon Wongnak, Sónia Gonçalves, Jonathan Keatley, Mozam Ali, Mehul Dhorda, Roberto Amato, John Sillitoe, Olivo Miotto, Gilles Delmas, Viengxay Vanisaveth, and Thanat Chookajorn

Subjects
South asia, Geography, Socioeconomics, Malaria control
Published
2021
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4. A ‘what-if’ scenario: Nipah virus attacks pig trade chains in Thailand

Author

Weerapong Thanapongtharm, Krittanat Sutassananon, Anuwat Wiratsudakul, Wantanee Kalpravidh, Kachen Wongsathapornchai, Sarattha Karnjanapreechakorn, Phrutsamon Wongnak, Worapan Kusakunniran, Unité Mixte de Recherche d'Épidémiologie des maladies Animales et zoonotiques (UMR EPIA), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Department of Livestock Development (DLD), Faculty of Information and Communication Technology, Mahidol University [Bangkok], Food and Agriculture Organization of the United Nations, Global Emergency Centre for Transboundary Animal Diseases (ECTAD), Food and Agriculture Organization of the United Nations, and Department of Clinical Sciences and Public Health, and the Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals, Faculty of Veterinary Science

Subjects
Swine, [SDV]Life Sciences [q-bio], Nipah virus, 030231 tropical medicine, Central plain, Transportation, Network modeling, Decision Support Techniques, Disease Outbreaks, 03 medical and health sciences, 0302 clinical medicine, Chiroptera, Animals, Humans, Socioeconomics, Animal movement, 030304 developmental biology, Henipavirus Infections, Swine Diseases, 2. Zero hunger, 0303 health sciences, lcsh:Veterinary medicine, General Veterinary, Outbreak, General Medicine, Thailand, 3. Good health, Geography, Risk map, lcsh:SF600-1100, Research Article, Spatial risk
Abstract

Background Nipah virus (NiV) is a fatal zoonotic agent that was first identified amongst pig farmers in Malaysia in 1998, in an outbreak that resulted in 105 fatal human cases. That epidemic arose from a chain of infection, initiating from bats to pigs, and which then spilled over from pigs to humans. In Thailand, bat-pig-human communities can be observed across the country, particularly in the central plain. The present study therefore aimed to identify high-risk areas for potential NiV outbreaks and to model how the virus is likely to spread. Multi-criteria decision analysis (MCDA) and weighted linear combination (WLC) were employed to produce the NiV risk map. The map was then overlaid with the nationwide pig movement network to identify the index subdistricts in which NiV may emerge. Subsequently, susceptible-exposed-infectious-removed (SEIR) modeling was used to simulate NiV spread within each subdistrict, and network modeling was used to illustrate how the virus disperses across subdistricts. Results Based on the MCDA and pig movement data, 14 index subdistricts with a high-risk of NiV emergence were identified. We found in our infectious network modeling that the infected subdistricts clustered in, or close to the central plain, within a range of 171 km from the source subdistricts. However, the virus may travel as far as 528.5 km (R0 = 5). Conclusions In conclusion, the risk of NiV dissemination through pig movement networks in Thailand is low but not negligible. The risk areas identified in our study can help the veterinary authority to allocate financial and human resources to where preventive strategies, such as pig farm regionalization, are required and to contain outbreaks in a timely fashion once they occur.

Published
2020
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