Bayesian modeling of post-vaccination serological data suggests that yearly vaccination of dog aged <2 years old is efficient to stop rabies circulation in Cambodia.

Rabies control remains challenging in low and middle-income countries, mostly due to lack of financial resources, rapid turnover of dog populations and poor accessibility to dogs. Rabies is endemic in Cambodia, where no national rabies vaccination program is implemented. The objective of this study was to assess the short and long-term vaccination-induced immunity in Cambodian dogs under field conditions, and to propose optimized vaccination strategies. A cohort of 351 dogs was followed at regular time points following primary vaccination only (PV) or PV plus single booster (BV). Fluorescent antibody virus neutralization test (FAVNT) was implemented to determine the neutralizing antibody titer against rabies and an individual titer ≥0·5 IU/mL indicated protection. Bayesian modeling was used to evaluate the individual duration of protection against rabies and the efficacy of two different vaccination strategies. Overall, 61% of dogs had a protective immunity one year after PV. In dogs receiving a BV, this protective immunity remained for up to one year after the BV in 95% of dogs. According to the best Bayesian model, a PV conferred a protective immunity in 82% of dogs (95% CI: 75-91%) for a mean duration of 4.7 years, and BV induced a lifelong protective immunity. Annual PV of dogs less than one year old and systematic BV solely of dogs vaccinated the year before would allow to achieve the 70% World Health Organization recommended threshold to control rabies circulation in a dog population in three to five years of implementation depending on dog population dynamics. This vaccination strategy would save up to about a third of vaccine doses, reducing cost and time efforts of mass dog vaccination campaigns. These results can contribute to optimize rabies control measures in Cambodia moving towards the global goal of ending human death from dog-mediated rabies by 2030.

Isolation of Burkholderia pseudomallei from a goat in New Caledonia: implications for animal and human health monitoring and serological tool comparison.

BACKGROUND: Melioidosis is a serious bacterial infection caused by Burkholderia pseudomallei, a gram-negative bacterium commonly found in soil and water. It can affect both humans and animals, and is endemic in regions such as Southeast Asia and Northern Australia. In recent years, there have been reports of an emergence of human melioidosis in other areas, including New Caledonia. RESULTS: During standard laboratory analysis in New Caledonia in 2021, a strain of B. pseudomallei was isolated from a goat. The strain was characterized using both MLST and WGS techniques and was found to cluster with previously described local human strains from the area. In parallel, several serological tests (CFT, ELISA, Luminex (Hcp1, GroEL, BPSS1840), arrays assay and a latex agglutination test) were performed on animals from the farm where the goat originated, and/or from three other neighboring farms. Using two commercial ELISA kits, seropositive animals were found only on the farm where the infected goat originated and tests based on recombinant proteins confirmed the usefulness of the Hcp1 protein for the diagnosis of melioidosis in animals. CONCLUSIONS: Despite the regular reports of human cases, this is the first confirmed case of melioidosis in an animal in New Caledonia. These results confirm the presence of the bacterium in the region and highlight the importance of vigilance for both animal and human health. It is critical that all health partners, including breeders, veterinarians, and biologists, work together to monitor and prevent the spread of the disease.

A systematic review of mechanistic models used to study avian influenza virus transmission and control.

The global spread of avian influenza A viruses in domestic birds is causing increasing socioeconomic devastation. Various mechanistic models have been developed to better understand avian influenza transmission and evaluate the effectiveness of control measures in mitigating the socioeconomic losses caused by these viruses. However, the results of models of avian influenza transmission and control have not yet been subject to a comprehensive review. Such a review could help inform policy makers and guide future modeling work. To help fill this gap, we conducted a systematic review of the mechanistic models that have been applied to field outbreaks. Our three objectives were to: (1) describe the type of models and their epidemiological context, (2) list estimates of commonly used parameters of low pathogenicity and highly pathogenic avian influenza transmission, and (3) review the characteristics of avian influenza transmission and the efficacy of control strategies according to the mechanistic models. We reviewed a total of 46 articles. Of these, 26 articles estimated parameters by fitting the model to data, one evaluated the effectiveness of control strategies, and 19 did both. Values of the between-individual reproduction number ranged widely: from 2.18 to 86 for highly pathogenic avian influenza viruses, and from 4.7 to 45.9 for low pathogenicity avian influenza viruses, depending on epidemiological settings, virus subtypes and host species. Other parameters, such as the durations of the latent and infectious periods, were often taken from the literature, limiting the models' potential insights. Concerning control strategies, many models evaluated culling (n = 15), while vaccination received less attention (n = 6). According to the articles reviewed, optimal control strategies varied between virus subtypes and local conditions, and depended on the overall objective of the intervention. For instance, vaccination was optimal when the objective was to limit the overall number of culled flocks. In contrast, pre-emptive culling was preferred for reducing the size and duration of an epidemic. Early implementation consistently improved the overall efficacy of interventions, highlighting the need for effective surveillance and epidemic preparedness.

Spatial association of Mycobacterium bovis infection in cattle and badgers at the pasture interface in an endemic area in France.

Despite control and surveillance programmes, Mycobacterium bovis, the main aetiologic agent of bovine tuberculosis (bTB), is still detected on cattle farms and in wildlife populations in France, especially in badgers in the French Côte-d'Or département. The aim of our study was to find out if infected badgers were trapped significantly closer to pastures of infected farms than non-infected badgers and, if so, to determine the most efficient distance around those pastures for badger trapping, particularly for surveillance purposes. We studied two subareas (southern and northern), chosen based on natural barriers to badger movements and according to the presence of pastures belonging to infected farms (POIFs) and infected or non-infected badgers. In each subarea, we computed the shortest distances D0 and D between badgers trapped a given year n between 2015 and 2019 (n = 59 infected and n = 1535 non-infected badgers for D0; n = 53 infected and n = 1476 non-infected badgers for D) and POIFs designated as infected between the year n - 4 and n + 1 (respectively n = 373 and n = 388 POIFs). D0 was calculated without considering spoligotypes, while D was calculated considering the possible epidemiological link between infected badgers and POIFs by using bTB spoligotype information. Then, we computed the observed mean and median of the D0 and D distances and used a bootstrap analysis to test if infected badgers were found significantly closer to POIFs than non-infected badgers. We observed that infection of badgers was not independent of distance from POIF in both subareas but distances (D0 or D) were different between the northern and southern subarea. In the northern subarea, which displays a mosaic landscape (mean and median D distances were respectively 612 m and 303 m for infected badgers), infected badgers indeed were trapped closer to POIFs, considering D0 and D. In the southern subarea, predominantly forested, infected badgers were significantly closer to POIFs than non-infected badgers when considering D0 but not for D (mean and median D distances were respectively 7148 m and 4831 m for infected badgers). These results will help to determine the most efficient distance from POIFs to trap badgers to determine their infection status in countryside landscapes. They also highlight the need to better understand the epidemiological systems at play in more forested landscapes where badgers may behave differently or other susceptible sympatric wild species might play a more important role in the circulation of M. bovis, both phenomena contributing to badger infection at greater distances from POIFs.

Risk factors associated to bovine brucellosis seroprevalence in the eastern region of Paraguay.

In Paraguay, whose main economic activity is cattle raising, bovine brucellosis is an endemic disease. Between May 2019 and October 2020, a national prevalence survey was implemented by the Paraguayan Veterinary Services. In the frame of that survey, a cross-sectional study was conducted in the eastern region of Paraguay to identify the risk factors that could be associated with brucellosis-positive farms and to estimate the bovine brucellosis seroprevalence and farmers' awareness about the disease. A questionnaire was administered to farmers to collect data on potential risk factors for bovine brucellosis as well as awareness on the disease. A logistic regression model was used to identify the risk factors associated with a farm brucellosis positive status. Blood samples were collected from 2551 cattle on 133 farms. The overall apparent seroprevalence was 27.8 % (95 % CI: 20.4-36.3 %) at the farm level, and 5.5 % (95 % CI: 4.7-6.5 %) at the animal level. Among 18 potential risk factors, four were associated with a farm brucellosis positive status. Farm size was associated with a higher risk of positive status in medium (20-80 cows) and large farms (>80 cows), compared with small farms (<20 cows). Barn disinfection had a protective effect on the risk of positive status. Conversely, presence of dogs and not incinerating/burying aborted material increased this risk. Even if 89 % of the farmers acknowledged being aware of the bovine brucellosis transmission to humans, only 46% of these farmers declared using protective gloves during calving or when handling abortions. The findings of this study emphasize the importance of implementing biosecurity measures and proper disposal of aborted material to control the disease. Therefore, to control the disease in Paraguay, vaccination campaigns should be accompanied by awareness campaigns addressing good farm management practices to minimize the risk of introduction and maintenance of brucellosis as well as the risk of human infection.

Impact of palmiped farm density on the resilience of the poultry sector to highly pathogenic avian influenza H5N8 in France.

We analysed the interplay between palmiped farm density and the vulnerability of the poultry production system to highly pathogenic avian influenza (HPAI) H5N8. To do so, we used a spatially-explicit transmission model, which was calibrated to reproduce the observed spatio-temporal distribution of outbreaks in France during the 2016-2017 epidemic of HPAI. Six scenarios were investigated, in which the density of palmiped farms was decreased in the municipalities with the highest palmiped farm density. For each of the six scenarios, we first calculated the spatial distribution of the basic reproduction number (R0), i.e. the expected number of farms a particular farm would be likely to infect, should all other farms be susceptible. We also ran in silico simulations of the adjusted model for each scenario to estimate epidemic sizes and time-varying effective reproduction numbers. We showed that reducing palmiped farm density in the densest municipalities decreased substantially the size of the areas with high R0 values (> 1.5). In silico simulations suggested that reducing palmiped farm density, even slightly, in the densest municipalities was expected to decrease substantially the number of affected poultry farms and therefore provide benefits to the poultry sector as a whole. However, they also suggest that it would not have been sufficient, even in combination with the intervention measures implemented during the 2016-2017 epidemic, to completely prevent the virus from spreading. Therefore, the effectiveness of alternative structural preventive approaches now needs to be assessed, including flock size reduction and targeted vaccination.

Analysis of a multi-type resurgence of Mycobacterium bovis in cattle and badgers in Southwest France, 2007-2019.

Although control measures to tackle bovine tuberculosis (bTB) in cattle have been successful in many parts of Europe, this disease has not been eradicated in areas where Mycobacterium bovis circulates in multi-host systems. Here we analyzed the resurgence of 11 M. bovis genotypes (defined based on spoligotyping and MIRU-VNTR) detected in 141 farms between 2007 and 2019, in an area of Southwestern France where wildlife infection was also detected from 2012 in 65 badgers. We used a spatially-explicit model to reconstruct the simultaneous diffusion of the 11 genotypes in cattle farms and badger populations. Effective reproduction number R was estimated to be 1.34 in 2007-2011 indicating a self-sustained M. bovis transmission by a maintenance community although within-species Rs were both < 1, indicating that neither cattle nor badger populations acted as separate reservoir hosts. From 2012, control measures were implemented, and we observed a decrease of R below 1. Spatial contrasts of the basic reproduction ratio suggested that local field conditions may favor (or penalize) local spread of bTB upon introduction into a new farm. Calculation of generation time distributions showed that the spread of M. bovis has been more rapid from cattle farms (0.5-0.7 year) than from badger groups (1.3-2.4 years). Although eradication of bTB appears possible in the study area (since R < 1), the model suggests it is a long-term prospect, because of the prolonged persistence of infection in badger groups (2.9-5.7 years). Supplementary tools and efforts to better control bTB infection in badgers (including vaccination for instance) appear necessary.

"BACACIX", a spatial index combining proxies of bovine and badger space use associated with extended Mycobacterium bovis circulation in France.

To better prevent and control multi-host pathogen circulation over large areas, it is essential to identify patterns of disease persistence within host communities involved in pathogen circulation at a macroscale. The aim of this study was to design and calculate "BACACIX", a spatial index of indirect contacts between cattle and badgers, two species involved in the circulation of Mycobacterium bovis, one of the main causative agents of bovine tuberculosis (bTB), in some areas of France. The index combined spatial models of land use distribution (the probable distribution defining animal use of space) based on pasture location for cattle, and based on land cover for badgers, with proxies for animal density for both species. For badgers, we used two series of census data of badger setts in two regions of France to evaluate our model of badger space use distribution (also known as utilization distribution), and analyzed the relationship between BACACIX and the upsurge of bovine tuberculosis observed in several regions of France during the decade after the country obtained the officially bTB-free status in 2001. We observed high values of BACACIX from the southwest to the northeast of France and from Brittany to the Channel coast. Conversely, in two areas (north-central area and Mediterranean coast), index values were low, suggesting that indirect cattle-badger contacts were unlikely. In the two series of census data of badger setts that we analyzed, 96.5% and 87% of the global positioning system (GPS) locations of badger setts, respectively were located in the calculated badger space use distribution. A logistic regression model showed that after controlling bTB over the previous decade, the value of the index was positively associated with the risk of cattle outbreaks between 2001 and 2010 (OR = 1.57). In addition, the risk of bTB occurrence in cattle decreased when the pasture area outside the badger space use distribution increased. In the future, the spatial index of indirect cattle-badger contacts we propose could help to better target bTB surveillance and control in France.

Serological Responses in Cattle following Booster Vaccination against Serotypes 4 and 8 Bluetongue Virus with Two Bivalent Commercial Inactivated Vaccines.

Since the outbreak of bluetongue in Northern Europe in 2006, numerous outbreaks involving several serotypes have been observed. Since 2008, compulsory or voluntary vaccination campaigns with inactivated vaccines have been carried out to eradicate these serotypes. In France, serotypes 8 and 4 have been enzootic since 2017, and currently, the majority of vaccinations take place in the context of animal movements, to comply with the regulations of the importing countries. Several vaccine manufacturers have developed inactivated vaccines against serotypes 4 and 8 (mono or bivalent). In this study, we investigated and compared the serological responses to a booster vaccination with two different bivalent inactivated vaccines (BTVPUR suspension injectable® 4 + 8, Boehringer Ingelheim or SYVAZUL ® BTV 4 + 8, Biové) following a primary vaccination with BTVPUR® 4 + 8 in the previous year. The results show that using an alternative vaccine for booster vaccination is at least as effective as using the homologous vaccine. Indeed, the antibody response against BTV-8 is higher in the case of a heterologous vaccination and identical for BTV-4. This information could allow more flexibility in the choice of vaccines used for booster vaccination, particularly in cases where homologous vaccines are in short supply or unavailable.

Analysis of cattle movement networks in Paraguay: Implications for the spread and control of infectious diseases.

Beef exports represent a substantial part of Paraguay's agricultural sector. Cattle movements involve a high risk due to the possible spread of bovine diseases that can have a significant impact on the country's economy. We analyzed cattle movements from 2014 to 2018 using the networks analysis methodology at the holding and district levels at different temporal scales. We built two types of networks to identify network characteristics that may contribute to the spread of two diseases with different epidemiological characteristics: i) a network including all cattle movements to consider the transmission of a disease of rapid spread like foot and mouth disease, and ii) a network including only cow movements to account for bovine brucellosis, a disease of slow spread that occurs mainly in adult females. Network indicators did not vary substantially among the cattle and cow only networks. The holdings/districts included in the largest strongly connected components were distributed throughout the country. Percolation analysis performed at the holding level showed that a large number of holdings should be removed to make the largest strongly connected component disappear. Higher values of the centrality indicators were found for markets than for farms, indicating that they may play an important role in the spread of an infectious disease. At the holding level (but not at the district level), the networks exhibited characteristics of small-world networks. This property may facilitate the spread of foot and mouth disease in case of re-emergence, or of bovine brucellosis in the country through cattle movements. They should be taken into account when implementing surveillance or control measures for these diseases.

Foot and mouth disease virus: transmission, pathogenesis, diagnosis and surveillance / Le virus de la fièvre aphteuse : transmission, pathogenèse, diagnostic et surveillance

Foot-and-mouth disease (FMD) is one of the most contagious viral animal diseases. It is an old disease which still poses a permanent threat of re-emergence for free zones. Foot-and-Mouth Disease Virus (FMDV), a Picornavirus belonging to genus Aphthovirus affects domestic and wild artiodactyls. FMD has a considerable socio-economic impact on agricultural production and trade in endemic regions, but also when incursions occur into FMD free areas, as in Europe in 2001. FMDV is historically one of the most studied viruses. Due to its high genetic and antigenic variability, the absence of cross-immunity between its seven serotypes, its ability to survive in the environment, its high contagiousness, its wide range of hosts and its particular biology, FMDV remains of major interest in animal health and the subject of many research projects. This review presents different aspects of FMDV infection, ranging from basic biology to diagnosis, surveillance and control.

La fièvre aphteuse (FA) est l'une des maladies virales animales les plus contagieuses. Bien que très ancienne, la FA reste toujours d'actualité et représente une menace permanente de réémergence pour les pays indemnes. Le virus de la FA ou FMDV (pour foot-and-mouth disease virus), de la famille Picornaviridae, genre Aphthovirus, affecte les artiodactyles domestiques comme sauvages (principalement bovins, ovins, caprins, porcins, camélidés et cervidés). La fièvre aphteuse a un impact socio-économique considérable sur la production et le commerce agricoles en zone d'enzootie mais également en cas d'incursion dans une zone précédemment indemne comme ce fut le cas en 2001 en Europe. Le virus de la FA est historiquement l'un des virus les plus étudiés. Par sa grande variabilité génétique et antigénique, l'absence d'immunité croisée entre ses sept sérotypes, sa capacité de survie dans l'environnement, sa grande contagiosité, son large spectre d'hôtes ainsi que sa biologie particulière, ce virus reste d'intérêt majeur en santé animale et l'objet de nombreux travaux de recherche. Cette revue vise à présenter différents aspects de l'infection par le virus de la fièvre aphteuse et ses problématiques actuelles, de la biologie fondamentale au diagnostic en passant par la surveillance et les moyens de lutte.

Mechanistic models of Rift Valley fever virus transmission: A systematic review.

Rift Valley fever (RVF) is a zoonotic arbovirosis which has been reported across Africa including the northernmost edge, South West Indian Ocean islands, and the Arabian Peninsula. The virus is responsible for high abortion rates and mortality in young ruminants, with economic impacts in affected countries. To date, RVF epidemiological mechanisms are not fully understood, due to the multiplicity of implicated vertebrate hosts, vectors, and ecosystems. In this context, mathematical models are useful tools to develop our understanding of complex systems, and mechanistic models are particularly suited to data-scarce settings. Here, we performed a systematic review of mechanistic models studying RVF, to explore their diversity and their contribution to the understanding of this disease epidemiology. Researching Pubmed and Scopus databases (October 2021), we eventually selected 48 papers, presenting overall 49 different models with numerical application to RVF. We categorized models as theoretical, applied, or grey, depending on whether they represented a specific geographical context or not, and whether they relied on an extensive use of data. We discussed their contributions to the understanding of RVF epidemiology, and highlighted that theoretical and applied models are used differently yet meet common objectives. Through the examination of model features, we identified research questions left unexplored across scales, such as the role of animal mobility, as well as the relative contributions of host and vector species to transmission. Importantly, we noted a substantial lack of justification when choosing a functional form for the force of infection. Overall, we showed a great diversity in RVF models, leading to important progress in our comprehension of epidemiological mechanisms. To go further, data gaps must be filled, and modelers need to improve their code accessibility.

Two major epidemics of highly pathogenic avian influenza virus H5N8 and H5N1 in domestic poultry in France, 2020-2022.

The spread of highly pathogenic avian influenza (HPAI) viruses worldwide has serious consequences for animal health and a major economic impact on the poultry production sector. Since 2014, Europe has been severely hit by several HPAI epidemics, with France being the most affected country. Most recently, France was again affected by two devastating HPAI epidemics in 2020-21 and 2021-22. We conducted a descriptive analysis of the 2020-21 and 2021-22 epidemics, as a first step towards identifying the poultry sector's remaining vulnerabilities regarding HPAI viruses in France. We examined the spatio-temporal distribution of outbreaks that occurred in France in 2020-21 and 2021-22, and we assessed the outbreaks' spatial distribution in relation to the 2016-17 epidemic and to the two 'high-risk zones' recently incorporated into French legislation to strengthen HPAI prevention and control. There were 468 reported outbreaks during the 2020-21 epidemic and 1375 outbreaks during the 2021-22 epidemic. In both epidemics, the outbreaks' distribution matched extremely well that of 2016-17, and most outbreaks (80.6% and 68.4%) were located in the two high-risk zones. The southwestern high-risk zone was affected in both epidemics, while the western high-risk zone was affected for the first time in 2021-22, explaining the extremely high number of outbreaks reported. As soon as the virus reached the high-risk zones, it started to spread between farms at very high rates, with each infected farm infecting between two and three other farms at the peaks of transmission. We showed that the spatial distribution model used to create the two high-risk zones was able to predict the location of outbreaks for the 2020-21 and 2021-22 epidemics. These zones were characterized by high poultry farm densities; future efforts should, therefore, focus on reducing the density of susceptible poultry in highly dense areas.

Predicting veal-calf trading events in France.

Global trade has been ranked as one of the top five drivers of infectious disease threat events. More specifically, livestock trade is known to increase the speed at which infectious diseases circulate and to facilitate their dissemination over large distances Therefore, predicting animal movements arising from trade is crucial for assessing epidemic risk and the impact of preventive measures. In this study, we developed a statistical framework for predicting trading events using predictors accessible from routinely collected data. We focused on veal calves, a category of animals with significant commercial value; the dataset considered the veal calf trade in France between January 2011 and June 2019. A subset of farms with consistent trade behaviour over time was built to be used throughout the study. To predict sale or purchase event occurrences, our predictive framework was based on random forests as a binary classification tool, an approach that allows a large number of potential predictors. We explored the robustness of model predictions with respect to the delay in data acquisition and prediction lag time. Overall, sales were more accurately predicted than purchasing events. Unsurprisingly, a delay in data acquisition led to a decrease in the performance of indicators, whereas prediction lag time had little impact. Sale-related predictors mostly reflected past trading events, whereas purchase-related predictors were associated with past trading events, farm management and general farm characteristics. The model outputs also suggested that the veal calf trading network is driven by sales rather than by purchases. Regardless of the length of the delay in data acquisition and prediction lag, the random forest approach fitted on data with municipality as trading unit and a 28-day trading period provided better performance scores (F1-score, positive predictive value and negative predictive value) than scenarios with finer temporal and spatial aggregation units. Predicted trade events can therefore be used to reconstruct the entire veal calf trading network and transfers between selling and purchasing units for each period. This predicted network could be further used to simulate the spread of pathogens via animal trade.

Modelling Japanese encephalitis virus transmission dynamics and human exposure in a Cambodian rural multi-host system.

Japanese encephalitis (JE) is a vector-borne zoonosis and the leading cause of human viral encephalitis in Asia. Its transmission cycle is usually described as involving wild birds as reservoirs and pigs as amplifying hosts. JE is endemic in Cambodia, where it circulates in areas with low pig densities (<70 pigs per km2), and could be maintained in a multi-host system composed of pigs, but also poultry as competent hosts, and dogs, cattle and humans as non-competent hosts. We used a mathematical model representing Japanese encephalitis virus (JEV) transmission in a traditional Cambodian village that we calibrated with field data collected in 3 districts of Kandal province, Cambodia. First, R0 calculations allowed us to assess the capacity of the epidemiological system to be invaded by JEV and sustain virus transmission in villages in the 3 districts, and we predicted human exposure at the epidemiological equilibrium, based on simulations. Changes in spatial density of livestock, in agricultural practices, and epizootics (e.g., African swine fever), can profoundly alter the composition of host communities, which could affect JEV transmission and its impact on human health. In a second step, we then used the model to analyse how host community composition affected R0 and the predicted human exposure. Lastly, we evaluated the potential use of dog JE seroprevalence as an indicator of human exposure to JEV. In the modeled villages, the calculated R0 ranged from 1.07 to 1.38. Once the equilibrium reached, predicted annual probability of human exposure ranged from 9% to 47%, and predicted average age at infection was low, between 2 and 11 years old, highlighting the risk of severe forms of JEV infection and the need to intensify child immunization. According to the model, increasing the proportion of competent hosts induced a decrease in age at infection. The simulations also showed that JEV could invade a multi-host system with no pigs, reinforcing the assumption of poultry acting as reservoirs. Finally, the annual human exposure probability appeared linearly correlated with dog seroprevalence, suggesting that in our specific study area, dog seroprevalence would be a good proxy for human exposure.

Vector Competence of Mediterranean Mosquitoes for Rift Valley Fever Virus: A Meta-Analysis.

Rift Valley fever (RVF) is a zoonotic disease caused by a virus mainly transmitted by Aedes and Culex mosquitoes. Infection leads to high abortion rates and considerable mortality in domestic livestock. The combination of viral circulation in Egypt and Libya and the existence of unregulated live animal trade routes through endemic areas raise concerns that the virus may spread to other Mediterranean countries, where there are mosquitoes potentially competent for RVF virus (RVFV) transmission. The competence of vectors for a given pathogen can be assessed through laboratory experiments, but results may vary greatly with the study design. This research aims to quantify the competence of five major potential RVFV vectors in the Mediterranean Basin, namely Aedes detritus, Ae. caspius, Ae. vexans, Culex pipiens and Cx. theileri, through a systematic literature review and meta-analysis. We first computed the infection rate, the dissemination rate among infected mosquitoes, the overall dissemination rate, the transmission rate among mosquitoes with a disseminated infection and the overall transmission rate for these five mosquito species. We next assessed the influence of laboratory study designs on the variability of these five parameters. According to experimental results and our analysis, Aedes caspius may be the most competent vector among the five species considered.

A Bayesian evolutionary model towards understanding wildlife contribution to F4-family Mycobacterium bovis transmission in the South-West of France.

In two "départements" in the South-West of France, bovine tuberculosis (bTB) outbreaks due to Mycobacterium bovis spoligotype SB0821 have been identified in cattle since 2002 and in wildlife since 2013. Using whole genome sequencing, the aim of our study was to clarify badger contribution to bTB transmission in this area. We used a Bayesian evolutionary model, to infer phylogenetic trees and migration rates between two pathogen populations defined by their host-species. In order to account for sampling bias, sub-population structure was inferred using the marginal approximation of the structured coalescent (Mascot) implemented in BEAST2. We included 167 SB0821 strains (21 isolated from badgers and 146 from cattle) and identified 171 single nucleotide polymorphisms. We selected a HKY model and a strict molecular clock. We estimated a badger-to-cattle transition rate (median: 2.2 transitions/lineage/year) 52 times superior to the cattle-to-badger rate (median: 0.042 transitions/lineage/year). Using the maximum clade credibility tree, we identified that over 75% of the lineages from 1989 to 2000 were present in badgers. In addition, we calculated a median of 64 transition events from badger-to-cattle (IQR: 10-91) and a median of zero transition event from cattle-to-badger (IQR: 0-3). Our model enabled us to infer inter-species transitions but not intra-population transmission as in previous epidemiological studies, where relevant units were farms and badger social groups. Thus, while we could not confirm badgers as possible intermediaries in farm-to-farm transmission, badger-to-cattle transition rate was high and we confirmed long-term presence of M. bovis in the badger population in the South-West of France.

Joint assessment of temporal segmentation, time unit and detection algorithms in syndromic surveillance.

The choice of the aggregation that defines the temporal unit of epidemiological surveillance is part of the more theoretical framework of the modifiable temporal unit problem (MTUP). It has been demonstrated that this choice influences temporal cluster detection and may lead to false-positive results and poor estimation of regression model parameters. In syndromic surveillance (SyS), despite the choice of which temporal aggregation to use being crucial, it has not yet been addressed in the literature. In most SyS systems, this choice is driven by the frequency of the data collection and/or human resources available, although neither the temporal unit's influence on the performance of anomaly detection algorithms nor on the efficiency of the SyS are known.The main objective of our study was to analyze the influence of the temporal aggregation unit on the performances of SyS detection algorithms used routinely, according to the characteristics of specific syndromes and outbreaks. Simulating daily time series of various syndromes, we tested three different time series aggregation methods. For each of four anomaly detection algorithms and their variants, we calculated seven performance indicators and multi-criteria scores to guide epidemiologists in their choice of which temporal aggregation of surveillance to use. From 19,200 analyzed time series, we observed an effect of temporal aggregation on the performance of the detection algorithms tested. Results also showed that the time aggregation unit was linked to the detection algorithm used, and that strong aggregation-algorithm interactions need to be taken into account when deciding on which aggregation-algorithm pair to use. Using theoretical data, our study also showed that no one ideal aggregation-algorithm pair exists for all contexts when deciding on which temporal unit of surveillance to use, and that the choice depends on several parameters.Our results can help public health practitioners choose the most appropriate time series aggregation and algorithm according to their specific needs. Finally, the present work enabled us to develop recommendations for a One Health project where the same time aggregation type and detection method could be used for both human and animal syndromic surveillance data.

How far away do you keep your equines? Estimation of the equine population's spatial distribution in France.

It is essential to have an accurate picture of the spatial distribution of equines to be able to monitor equine health events effectively. In France, this information is only available for certain categories of live equines kept in professional structures and for dead equines removed by renderers. This limits the surveillance, prevention and control methods able to be used to prevent the spread of equine diseases. Our study aimed to provide a realistic estimate of the spatial distribution of the French equine population at the detailed scale of the French commune (France's smallest administrative unit). For this purpose, we adapted the Bayesian method used by Lo Lacono et al., based on the distance between the owner's location and the location of his/her equines, and on the percentage of urban coverage. To assess whether the location of dead equines could be representative of the location of live equines, the distribution of distances between equines and owners was calculated from a sample of live equines on the one hand, and a sample of dead equines on the other, both accurately located. We also tested two different assignment methods for locating equines: Method 1 assigned to each owner a single holding commune, while Method 2 allowed more variability in holding communes for owners associated with multiple equines. A marked difference was observed between Methods 1 and 2 regardless of the sample used, with only 2.4% and 4.3% respectively of the communes having the same number of equines. Conversely, little difference was observed in the results whether the live or dead equine sample was used, with approximately 45% of the communes having the same number of equines. Regarding differences in spatial distribution, Method 1 based on the live equine sample estimated higher local densities of equines without considering urban areas. In contrast, Method 2 provided more dispersed maps, with low densities in the densest urban areas. In conclusion, dead equines appeared to be representative of live equines and some of our estimates are consistent with the information collected by the French horse and riding institute (IFCE). These results now have to be compared with field data to test their relevance.

Identification of diffusion routes of O/EA-3 topotype of foot-and-mouth disease virus in Africa and Western Asia between 1974 and 2019 - a phylogeographic analysis.

Foot-and-mouth disease (FMD) affects the livestock industry and socioeconomic sustainability of many African countries. The success of FMD control programs in Africa depends largely on understanding the dynamics of FMD virus (FMDV) spread. In light of the recent outbreaks of FMD that affected the North-Western African countries in 2018 and 2019, we investigated the evolutionary phylodynamics of the causative serotype O viral strains all belonging to the East-Africa 3 topotype (O/EA-3). We analyzed a total of 489 sequences encoding the FMDV VP1 genome region generated from samples collected from 25 African and Western Asian countries between 1974 and 2019. Using Bayesian evolutionary models on genomic and epidemiological data, we inferred the routes of introduction and migration of the FMDV O/EA-3 topotype at the inter-regional scale. We inferred a mean substitution rate of 6.64 × 10-3  nt/site/year and we predicted that the most recent common ancestor for our panel of samples circulated between February 1967 and November 1973 in Yemen, likely reflecting the epidemiological situation in under sampled cattle-exporting East African countries. Our study also reinforces the role previously described of Sudan and South Sudan as a frequent source of FMDVs spread. In particular, we identified two transboundary routes of O/EA-3 diffusion: the first from Sudan to North-East Africa, and from the latter into Israel and Palestine AT; a second from Sudan to Nigeria, Cameroon, and from there to further into West and North-West Africa. This study highlights the necessity to reinforce surveillance at an inter-regional scale in Africa and Western Asia, in particular along the identified migration routes for the implementation of efficient control measures in the fight against FMD.