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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.

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.

International audience; The survival of ectothermic species is heavily dependent on environmental conditions, such as temperature and water balance. Understanding their survival responses to abiotic factors could help predict impacts of climate change on their population dynamics and human health. However, making a statistical inference and formulating a predictive model for mortality rates can be challenging when the observation numbers are limited. This study proposed an expert opinion elicitation framework that integrates expert opinions as prior distributions for the effects of continuous explanatory variables, through a Bayesian Parametric Survival Model (B-PSM). A historical survival dataset of female Ixodes ricinus ticks (Acari: Ixodidae) with small sample size was used. A total of 6 acarologists were recruited as experts for interactive online interview sessions to provide their opinions on average survival time under 4 different temperature and humidity scenarios. Most experts shared similar opinions on the effects of abiotic variables, and none of the experts was confident in the interaction effect. The variation of the opinions across multiple experts was handled by two approaches: 1) pooling and 2) averaging methods. The results showed that the pooling approach retains the variations of expert opinions, it may also disregard some irrelevant opinions to the observed data. While the averaging approach forms a numerical consensus across all the experts, but it may be less informative when the opinions distinctly diverge. The survival time of I. ricinus was found to be best described by the Weibull distribution, suggesting the mortality rate of ticks increases over time (aging effects). Also, the posterior predictions revealed that I. ricinus ticks were susceptible to desiccation conditions, with an interaction effect with the temperature. Therefore, our results suggested that relative humidity is an important factor in the survival of I. ricinus that should not be disregarded when evaluating the impacts of climate change on their population dynamics. Finally, this study provided a guideline for implementing the B-PSM framework to incorporate expert opinions and develop predictive survival models that can be applied in other ecological contexts.