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There is growing concern about climate change and its impact on human health. Specifically, global warming could increase the probability of emerging infectious diseases, notably because of changes in the geographical and seasonal distributions of disease vectors such as mosquitoes and ticks. For example, the range of Ixodes ricinus, the most common and widespread tick species in Europe, is currently expanding northward and at higher altitudes. However, little is known about the seasonal variation in tick abundance in different climates. Seasonality of I. ricinus is often based on expert opinions while field surveys are usually limited in time. Our objective was to describe seasonal variations in I. ricinus abundance under different climates. To this end, a seven-year longitudinal study, with monthly collections of I. ricinus host-seeking nymphs, was carried out in France, in six locations corresponding to different climates. Tick data were log-transformed and grouped between years so as to obtain seasonal variations for a typical year. Daily average temperature was measured during the study period. Seasonal patterns of nymph abundance were established for the six different locations using linear harmonic regression. Model parameters were estimated separately for each location. Seasonal patterns appeared different depending on the climate considered. Western temperate sites showed an early spring peak, a summer minimum and a moderate autumn and winter abundance. More continental sites showed a later peak in spring, and a minimum in winter. The peak occurred in summer for the mountainous site, with an absence of ticks in winter. In all cases except the mountainous site, the timing of the spring peak could be related to the sum of degree days since the beginning of the year. Winter abundance was positively correlated to the corresponding temperature. Our results highlight clear patterns in the different sites corresponding to different climates, which allow further forecast of tick seasonality under changing climate conditions.

Fleas and ticks are major ectoparasites of dogs globally. Their control is based on regular treatments with ectoparasiticides, which represent the most important part of veterinary drugs worth around 3 billion Euros per year. In many parts of the world, dogs are also at risk of infection by endoparasites like heartworm, eyeworm, and lungworm. In these areas, endectoparasiticide formulations are used to prevent the risk of ecto- and endoparasite infections. Since 2014, oral formulations of insecticidal-acaricidal drugs have been launched, followed by endectoparasiticide formulations. These oral formulations facilitate the treatment by the owners and are now the market leaders. Intense work has been done during their development to enhance their palatability through their consistence (hard to soft) and their flavors. Palatable oral formulations facilitate the dog-owner relationship and help ensuring compliance. The most recent palatable formulations include isoxazoline as the ecto-parasiticide molecule. They also include anthelmintics (milbemycin oxime or moxidectin + pyrantel) to provide control of parasitic nematodes. Being very similar in terms of spectrum of activity, any differences in palatability may be a key differentiating factor for the owners. The present study was conducted to verify if dogs exhibited a preference between two endectoparasiticide oral formulations, NexGard Spectra&#174 (afoxolaner and milbemycin oxime) and Credelio&#174 Plus (lotilaner and milbemycin oxime). For four consecutive days, 100 dogs were offered the choice between both products and consumption was recorded. If one product was more consumed than the other, it was defined as the preferred product. A total of 375 chewable tablets were consumed over the four days, with a significantly higher consumption (p 0.0001) for NexGard Spectra&#174 (272 chews, 72.5%) compared to Credelio&#174 Plus (103 chews, 27.5%). Seventy-six dogs showed a preference for a product amongst whom 68 preferred NexGard Spectra&#174 (89.5%) and 8 preferred Credelio&#174 Plus (10.5%), resulting in a preference ratio of 8.5 to 1 for NexGard Spectra&#174 (p 0.0001).

National audience; Context: Ixodes ricinus ticks (Acari: Ixodidae) are the most important vector for Lyme borreliosis in Europe, including France. The life cycles and key ecological processes of I. ricinus, suchas mortality, development rate, and questing behavior, are sensitive to weather and environmental conditions. Therefore, variations in these conditions contribute to the regulation of the dynamics of tick abundance, phenology of questing activity, and eventually, human-tick exposure risks throughout the year.Objective: This study aimed to determine the effects of environmental factors on questing activity of I. ricinus nymphs across diverse climatic types in France over a long-term period.Methods: Questing nymph activity was observed using a repeated removal sampling design with a cloth-dragging technique in 11 sampling sites from 7 tick observatories from 2014 to 2021 at approximately 1-month intervals. The environment of each sampling site were described by meteorological (temperature, relative humidity, daytime duration), bioclimatic (annual temperature, precipitation), topography (elevation), and habitat characteristics (forest fragmentation, soil pH, land cover types). Highly correlated variables were summarized using a Principal Component Analysis (PCA). Subsequently, a multivariate mixed-effectsnegative binomial regression model was used to assess the effect of environmental factors on the nymph activities.Results: A total of 631 sampling campaigns were involved in this study. Three phenological patterns were observed, potentially following a climatic gradient. The first 2 dimensions of the PCA described the land cover (Dimension 1) and the topographical/bioclimatic (Dimension 2), respectively. The mixed-effects negative binomial regression revealed that observed nymph counts were driven by different interval-average meteorological variables, including one-month average temperature, previous-season average temperature, and half-year average minimum relative humidity. The interaction effects indicated that the phenology incolder climates peaked differently from that of warmer climates. Also, the land cover characteristics that support the highest baseline abundance were moderate forest fragmentation with transition borders with agricultural areas.Conclusion: Finally, our model could potentially be used to predict seasonal human-tick exposure risks in France that could contribute to mitigating Lyme borreliosis risks.

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.

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.

In Thailand, pork is one of the most consumed meats nationwide. Pig farming is hence an important business in the country. However, 95% of the farms were considered smallholders raising only 50 pigs or less. With limited budgets and resources, the biosecurity level in these farms is relatively low. Pig movements have been previously identified as a risk factor in the spread of infectious diseases. Therefore, the present study aimed to explicitly analyze the pig movement network structure and assess its vulnerability to the spread of emerging diseases in Thailand. We used official electronic records of nationwide pig movements throughout the year 2021 to construct a directed weighted one-mode network. Degree centrality, degree distribution, connected components, network community, and modularity were measured to explore the network architectures and properties. In this network, 484,483 pig movements were captured. In which, 379,948 (78.42%) were moved toward slaughterhouses and hence excluded from further analyses. From the remaining links, we suggested that the pig movement network in Thailand was vulnerable to the spread of emerging infectious diseases. Within the network, we found a strongly connected component (SCC) connecting 1044 subdistricts (38.6% of the nodes), a giant weakly connected component (GWCC) covering 98.2% of the nodes (2654/2704), and inter-regional communities with overall network modularity of 0.68. The disease may rapidly spread throughout the country. A better understanding of the nationwide pig movement networks is helpful in tailoring control interventions to cope with the newly emerged diseases once introduced.

Annually, hundreds of severe foodborne cases related to Streptococcus suis (S. suis) have been reported in Southeast Asia, including Thailand. This study aimed at quantitatively evaluating the S. suis contaminations in pork and surrounding environment in pork production chains and its contributions to human illnesses. Pig-associated and environmental samples were collected from four pork supply chains in Bangkok, and cross-sectional pork samples were collected from traditional market and supermarkets in eight provinces in Thailand. All samples were enumerated for S. suis serotype 2 using standard plate count method, and bacterial species were confirmed by biochemical tests together with PCR assays and Quellung method. A quantitative microbial risk assessment (QMRA) was performed to evaluate the S. suis serotype 2 illness risk from consuming pork in Thailand. Among four pork supply chains, the mean S. suis prevalence of pig-associated, and environmental samples were 10.9% (54/496), and 5.21% (25/480), respectively. S. suis has the highest prevalence (56.3%) (9/16), and the highest concentration (5.6 log CFU/g) in palatine tonsils. S. suis was isolated from 0.93% (11/1180) of pork samples; none of them was serotype 2. The QMRA model revealed a mean daily probability of S. suis serotype 2 illness as 2.32 × 10−8, corresponding to 502 and 31 annual cases and deaths, respectively. Additionally, the illness risk from consuming raw pork was predicted at 5.47 × 10−6. In conclusion, even the probability of S. suis illnesses from consuming pork was considerably low; however, the illnesses could lead to serious health consequences among susceptible populations.

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.

Additional file 1: Table S1. The list of high risk subdistricts for NiV occurrence at subdistrict level. Table S2. The list of medium risk subdistricts for NiV occurrence at subdistrict level. Table S3. The list of low risk subdistricts for NiV occurrence at subdistrict level. Table S4. The list of very low risk subdistricts for NiV occurrence at subdistrict level.