Spatial analysis of bluetongue cases and vaccination of Swiss cattle in 2008 and 2009

Bluetongue Risk Map for Vaccination and Surveillance Strategies in India

Bluetongue virus (BTV, Sedoreoviridae: Orbivirus) causes an economically important disease, namely, bluetongue (BT), in domestic and wild ruminants worldwide. BTV is endemic to South India and has occurred with varying severity every year since the virus was first reported in 1963. BT can cause high morbidity and mortality to sheep flocks in this region, resulting in serious economic losses to subsistence farmers, with impacts on food security. The epidemiology of BTV in South India is complex, characterized by an unusually wide diversity of susceptible ruminant hosts, multiple vector species biting midges (Culicoides spp., Diptera: Ceratopogonidae), which have been implicated in the transmission of BTV and numerous co-circulating virus serotypes and strains. BT presence data (1997-2011) for South India were obtained from multiple sources to develop a presence/absence model for the disease. A non-linear discriminant analysis (NLDA) was carried out using temporal Fourier transformed variables that were remotely sensed as potential predictors of BT distribution. Predictive performance was then characterized using a range of different accuracy statistics (sensitivity, specificity, and Kappa). The top ten variables selected to explain BT distribution were primarily thermal metrics (land surface temperature, i.e., LST, and middle infrared, i.e., MIR) and a measure of plant photosynthetic activity (the Normalized Difference Vegetation Index, i.e., NDVI). A model that used pseudo-absence points, with three presence and absence clusters each, outperformed the model that used only the recorded absence points and showed high correspondence with past BTV outbreaks. The resulting risk maps may be suitable for informing disease managers concerned with vaccination, prevention, and control of BT in high-risk areas and for planning future state-wide vector and virus surveillance activities.

Approaches for disease prioritization and decision-making in animal health, 2000-2021: a structured scoping review

This scoping review identifies and describes the methods used to prioritize diseases for resource allocation across disease control, surveillance, and research and the methods used generally in decision-making on animal health policy. Three electronic databases (Medline/PubMed, Embase, and CAB Abstracts) were searched for articles from 2000 to 2021. Searches identified 6, 395 articles after de-duplication, with an additional 64 articles added manually. A total of 6, 460 articles were imported to online document review management software (sysrev.com) for screening. Based on inclusion and exclusion criteria, 532 articles passed the first screening, and after a second round of screening, 336 articles were recommended for full review. A total of 40 articles were removed after data extraction. Another 11 articles were added, having been obtained from cross-citations of already identified articles, providing a total of 307 articles to be considered in the scoping review. The results show that the main methods used for disease prioritization were based on economic analysis, multi-criteria evaluation, risk assessment, simple ranking, spatial risk mapping, and simulation modeling. Disease prioritization was performed to aid in decision-making related to various categories: (1) disease control, prevention, or eradication strategies, (2) general organizational strategy, (3) identification of high-risk areas or populations, (4) assessment of risk of disease introduction or occurrence, (5) disease surveillance, and (6) research priority setting. Of the articles included in data extraction, 50.5% had a national focus, 12.3% were local, 11.9% were regional, 6.5% were sub-national, and 3.9% were global. In 15.2% of the articles, the geographic focus was not specified. The scoping review revealed the lack of comprehensive, integrated, and mutually compatible approaches to disease prioritization and decision support tools for animal health. We recommend that future studies should focus on creating comprehensive and harmonized frameworks describing methods for disease prioritization and decision-making tools in animal health.

Summer seasonal prevalence of Culicoides species from pre-alpine areas in Switzerland

Biting midges (Diptera: Ceratopogonidae) are arthropods of veterinary importance since they can transmit pathogens and cause severe allergic dermatitis in horses. Very little is known about the species at higher altitudes and their seasonal dynamics. In this work, adult Culicoides were collected with Onderstepoort UV-light suction traps (OVI) from June to September 2016 at two areas situated at around 1600 m asl (pre-alpine area I, 2 farms) and 2030 m asl (pre-alpine area II, 1 farm) in the Canton of Grisons (south-east Switzerland). Overall, 17 049 Culicoides were collected, including 871 parous females. A total of 50 individuals/trap/night (n = 1050) were identified to species (17 species) by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) or by polymerase chain reaction (PCR) and sequencing. The remaining 15 128 Culicoides were classified to species groups' level. Culicoides obsoletus (Meigen, 1818), a multivoltine species, was mainly present at 1600 m asl, whereas at high altitudes (2030 m asl), C. grisescens Edwards, 1939 I&II were the most abundant species. In particular, C. grisescens II, which seems to be univoltine, occurred later in the season but significantly increasing over time. Species diversity was higher at pre-alpine I area (n = 16 species) compared to pre-alpine II (n = 10 species).

Vector competence of pre-alpine Culicoides (Diptera: Ceratopogonidae) for bluetongue virus serotypes 1, 4 and 8

Background

Bluetongue disease, caused by bluetongue virus serotype 8 (BTV-8), appeared for the first time in the northern part of Europe in 2006, and subsequently rapidly spread causing severe economic losses to the farming industry. The implicated vectors of BTV in Europe are Culicoides species within the subgenus Avaritia (C. chiopterus, C. dewulfi, C. obsoletus and C. scoticus). Epidemiological data from Switzerland have shown that BTV, whose spread was eliminated at an early stage by vaccination campaigns, had not been circulating among livestock at higher altitudes where other species dominate the Culicoides fauna. In this study, we investigated the extent that Culicoides spp. prevailing at higher altitudes (mainly C. grisescens) can act as vectors for BTV.

Methods

Culicoides were collected at farms in the pre-alpine region (two sites at 1550 m above sea level, masl, referred to as pre-alpine I; one site at 2030 masl, pre-alpine II) and, for comparative purposes, from the Swiss Plateau (one site, 650 masl). They were fed on bovine blood/BTV suspensions (BTV-1, 4 or 8) and incubated for eight days under a fluctuating temperature regime (13–25 °C, mean 19 °C), reflecting a mid-summer warm spell in the pre-alpine region. Susceptibility to BTV transmission was assessed from head homogenates by RT-qPCR and virus isolation.

Results

Overall, 9196 female Culicoides were exposed to the three BTV strains through an artificial membrane, with feeding rates of 14–27%. Survival rates of blood-engorged Culicoides females at eight days post-infection depended on both virus serotype and altitude of origin. Virus dissemination (C_q ≤ the cut-off value as determined by serial virus dilutions) was confirmed only for BTV-1 in C. scoticus (dissemination efficiency 22.5%; 9/40) and C. obsoletus (5.6%; 1/18) from the Swiss Plateau area. There was no strong evidence of susceptibility to infection for Culicoides from the pre-alpine area when fed with all BTV strains (BTV-1, 4 and 8).

Conclusions

This study confirms the susceptibility of C. scoticus and C. obsoletus to BTV-1 infection, including under cooler temperatures. Culicoides grisescens, which is highly abundant at higher altitudes, cannot be considered a potential vector under these temperature conditions.

Electronic supplementary material

The online version of this article (10.1186/s13071-018-3050-y) contains supplementary material, which is available to authorized users.

Bluetongue Virus: From BTV-1 to BTV-27

Bluetongue virus (BTV) is the type species of genus Orbivirus within family Reoviridae. Bluetongue virus is transmitted between its ruminant hosts by the bite of Culicoides spp. midges. Severe BT cases are characterized by symptoms including hemorrhagic fever, particularly in sheep, loss of productivity, and death. To date, 27 BTV serotypes have been documented. These include novel isolates of atypical BTV, which have been almost fully characterized using deep sequencing technologies and do not rely on Culicoides vectors for their transmission among hosts. Due to its high economic impact, BT is an Office International des Epizooties (OIE) listed disease that is strictly controlled in international commercial exchanges. During the 20th century, BTV has been endemic in subtropical regions. In the last 15 years, novel strains of nine "typical" BTV serotypes (1, 2, 4, 6, 8, 9, 11, 14, and 16) invaded Europe, some of which caused disease in naive sheep and unexpectedly in bovine herds (particularly serotype 8). Over the past few years, three novel "atypical" serotypes (25-27) were characterized during sequencing studies of animal samples from Switzerland, Kuwait, and France, respectively. Classical serotype-specific inactivated vaccines, although expensive, were very successful in controlling outbreaks as shown with the northern European BTV-8 outbreak which started in the summer of 2006. Technological jumps in deep sequencing methodologies made rapid full characterizations of BTV genome from isolates/tissues feasible. Next-generation sequencing (NGS) approaches are powerful tools to study the variability of BTV genomes on a fine scale. This paper provides information on how NGS impacted our knowledge of the BTV genome.

Expert Opinion on the Perceived Effectiveness and Importance of On-Farm Biosecurity Measures for Cattle and Swine Farms in Switzerland

Biosecurity is crucial for safeguarding livestock from infectious diseases. Despite the plethora of biosecurity recommendations, published scientific evidence on the effectiveness of individual biosecurity measures is limited. The objective of this study was to assess the perception of Swiss experts about the effectiveness and importance of individual on-farm biosecurity measures for cattle and swine farms (31 and 30 measures, respectively). Using a modified Delphi method, 16 Swiss livestock disease specialists (8 for each species) were interviewed. The experts were asked to rank biosecurity measures that were written on cards, by allocating a score from 0 (lowest) to 5 (highest). Experts ranked biosecurity measures based on their importance related to Swiss legislation, feasibility, as well as the effort required for implementation and the benefit of each biosecurity measure. The experts also ranked biosecurity measures based on their effectiveness in preventing an infectious agent from entering and spreading on a farm, solely based on transmission characteristics of specific pathogens. The pathogens considered by cattle experts were those causing Bluetongue (BT), Bovine Viral Diarrhea (BVD), Foot and Mouth Disease (FMD) and Infectious Bovine Rhinotracheitis (IBR). Swine experts expressed their opinion on the pathogens causing African Swine Fever (ASF), Enzootic Pneumonia (EP), Porcine Reproductive and Respiratory Syndrome (PRRS), as well as FMD. For cattle farms, biosecurity measures that improve disease awareness of farmers were ranked as both most important and most effective. For swine farms, the most important and effective measures identified were those related to animal movements. Among all single measures evaluated, education of farmers was perceived by the experts to be the most important and effective for protecting both Swiss cattle and swine farms from disease. The findings of this study provide an important basis for recommendation to farmers and policy makers.

Cost and sensitivity of on-farm versus slaughterhouse surveys for prevalence estimation and substantiating freedom from disease

Within the framework of Swiss surveillance for epizootic diseases, dairy cattle are sampled using bulk tank milk while non-dairy cattle are sampled on the farm. The latter method is costly, time-demanding and dangerous for the personnel. However, slaughterhouses could be an alternative sampling point for this population. To assess the cost-effectiveness and sensitivity of such an approach, surveillance using slaughterhouse sampling was modelled with data from the 2012 Swiss animal movement database (AMD). We simulated a cross-sectional study for bluetongue (BT), and surveillance programmes to substantiate freedom from infectious bovine rhinotracheitis (IBR) and enzootic bovine leucosis (EBL) (combined) to compare the outcome of random on-farm sampling versus slaughterhouse sampling. We found that, under Swiss conditions, slaughterhouse sampling results in low herd-level sensitivities because animals are sent by owners to slaughter individually and not in large groups, restricting the number of samples per herd. This makes slaughterhouse sampling inappropriate for prevalence surveys at the herd-level. However, for prevalence surveys at the animal-level and for substantiation of freedom from disease, slaughterhouse surveillance is equally or more cost-efficient than on-farm sampling.

Did vaccination slow the spread of bluetongue in France?

Vaccination is one of the most efficient ways to control the spread of infectious diseases. Simulations are now widely used to assess how vaccination can limit disease spread as well as mitigate morbidity or mortality in susceptible populations. However, field studies investigating how much vaccines decrease the velocity of epizootic wave-fronts during outbreaks are rare. This study aimed at investigating the effect of vaccination on the propagation of bluetongue, a vector-borne disease of ruminants. We used data from the 2008 bluetongue virus serotype 1 (BTV-1) epizootic of southwest France. As the virus was newly introduced in this area, natural immunity of livestock was absent. This allowed determination of the role of vaccination in changing the velocity of bluetongue spread while accounting for environmental factors that possibly influenced it. The average estimated velocity across the country despite restriction on animal movements was 5.4 km/day, which is very similar to the velocity of spread of the bluetongue virus serotype 8 epizootic in France also estimated in a context of restrictions on animal movements. Vaccination significantly reduced the propagation velocity of BTV-1. In comparison to municipalities with no vaccine coverage, the velocity of BTV-1 spread decreased by 1.7 km/day in municipalities with immunized animals. For the first time, the effect of vaccination has been quantified using data from a real epizootic whilst accounting for environmental factors known to modify the velocity of bluetongue spread. Our findings emphasize the importance of vaccination in limiting disease spread across natural landscape. Finally, environmental factors, specifically those related to vector abundance and activity, were found to be good predictors of the velocity of BTV-1 spread, indicating that these variables need to be adequately accounted for when evaluating the role of vaccination on bluetongue spread.

The impact of spatial scales and spatial smoothing on the outcome of bayesian spatial model

Discretization of a geographical region is quite common in spatial analysis. There have been few studies into the impact of different geographical scales on the outcome of spatial models for different spatial patterns. This study aims to investigate the impact of spatial scales and spatial smoothing on the outcomes of modelling spatial point-based data. Given a spatial point-based dataset (such as occurrence of a disease), we study the geographical variation of residual disease risk using regular grid cells. The individual disease risk is modelled using a logistic model with the inclusion of spatially unstructured and/or spatially structured random effects. Three spatial smoothness priors for the spatially structured component are employed in modelling, namely an intrinsic Gaussian Markov random field, a second-order random walk on a lattice, and a Gaussian field with Matérn correlation function. We investigate how changes in grid cell size affect model outcomes under different spatial structures and different smoothness priors for the spatial component. A realistic example (the Humberside data) is analyzed and a simulation study is described. Bayesian computation is carried out using an integrated nested Laplace approximation. The results suggest that the performance and predictive capacity of the spatial models improve as the grid cell size decreases for certain spatial structures. It also appears that different spatial smoothness priors should be applied for different patterns of point data.