Search

Bluetongue disease is an infectious disease transmitted by Culicoides as vectors, mainly infecting ruminants. Because ruminants play an important role in animal husbandry in China, the outbreak of bluetongue disease can cause serious economic losses. Maxent model was applied to predict the distribution of bluetongue in China based on the data derived from domestic and foreign academic literature databases including CNKI, Wanfang Database, PubMed, Web of Science and Google Scholar. The results showed that annual mean temperature (BIO1), precipitation in driest month (BIO14), sheep density (SD) and altitude (Elev) were the relevant variables of bioclimatic suitable zones for bluetongue disease. Precipitation in wettest month (BIO13), BIO1, BIO14, Elev were the main variables affecting the habitat of the bluetongue vector Culicoides. The most suitable climate for bluetongue infection occurs in southern China, central China and parts of Xinjiang. The suitable living areas of Culicoides are mainly located in southern, central and eastern China, and the overlap of the two suitable areas is high. The study suggested that southern, central, and eastern China are high-risk areas for bluetongue due to the significant overlap of suitable habitats for both the disease and its vector. Implementing effective surveillance and targeted control strategies in these regions is crucial for mitigating the impact of bluetongue disease., Competing Interests: Declaration of Competing Interest The authors declare that they have no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Bluetongue virus (BTV) remains as an economically major concern in the world. Seroprevalence and potential risk factors of BTV were assessed in a cross-sectional study at both the herd and animal levels in Iran. A total of 73 Epidemiologic Units (E.Unit), defined as a herd, flock or village including animals with equal chance of exposure to infectious agents, were randomly selected. Serum samples from all animals (n = 34,575) within the E.Units were collected and tested for BTV sero-group antibodies by using commercially competitive ELISA test. Using cluster analysis, 90.41 % (95 %, CI: 80.85 %-95.47 %) of the E.Units and 56.13 % (95 % CI: 55.61 %-56.66 %) of the tested animals were detected seropositive against BTV. A seroprevalence rate of 57.59 % (95 % CI: 48.01 %-66.63 %), 65.65 % (95 % CI: 59.10 %-73.74 %) and 27.63 % (95 % CI: 14.40 %-46.43 %) was estimated for sheep, goats and cattle, respectively. At E.Unit (herd) level, density was identified as a great risk factor for the infection (r 2 = 0.891; P = 0.000), and particularly density of cattle significantly correlated with BTV infection within the E.Units (r 2 = 0.247; P = 0.019). Using multilevel logistic regression, adjusted odds ratios (ORs) were estimated at individual level. A significantly less risk of BTV infection was evaluated for cattle than for sheep (OR = 0.42, 95 % CI: 0.38-0.47, P < 0.001), while no significant difference was observed between sheep and goat (OR = 1.03, 95 % CI: 0.97-1.10, P = 0.345). Animals over 2 years and between 6 months and 2 years expressed 2.22 (OR = 2.22, 95 % CI: 1.96-2.52, P < 0.001) and 2.18 (OR = 2.18, 95 % CI: 1.92-2.49, P < 0.001) times higher chance for the infection than animals under 6 months. Males were at significantly less risk of the infection than females (OR=0.68, 95 % CI: 0.63-0.74, P < 0.001). Animals kept in industrial farming systems displayed 0.46 (OR=0.46, 95 % CI: 032-0.66, P < 0.001) times less chance than animals kept in traditional farming system for BTV, while animals lived in semi-industrial farming system were found to be at 2.97 (OR=2.97, 95 % CI: 2.41-3.66, P < 0.001) times higher chance for BTV than animals lived in traditional farming system. Furthermore, seropositive animals exhibited a high amount of antibodies against BTV (s) suggesting that viral exposure may have frequently occurred during their lifetimes. This large - scale study yielded information on epidemiology of BTV in Iran that is prerequisite for further research, and also for evaluation of any cost-benefit control measure to be established in an enzootic zone of the virus., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interest., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Several epidemics caused by different bluetongue virus (BTV) serotypes occurred in European ruminants since the early 2000. Studies on the spatial distribution of these vector-borne infections and the main vector species highlighted contrasted eco-climatic regions characterized by different dominant vector species. However, little work was done regarding the factors associated with the velocity of these epidemics. In this study, we aimed to quantify and compare the velocity of BTV epidemic that have affected different European countries under contrasted eco-climatic conditions and to relate these estimates to spatial factors such as temperature and host density. We used the thin plate spline regression interpolation method in combination with trend surface analysis to quantify the local velocity of different epidemics that have affected France (BTV-8 2007-2008, BTV-1 2008-2009), Italy (BTV-1 2014), Andalusia in Spain (BTV-1 2007) and the Balkans (BTV-4 2014). We found significant differences in the local velocity of BTV spread according to the country and epidemics, ranging from 7.9km/week (BTV-1 2014 Italy) to 24.4km/week (BTV-1 2008 France). We quantify and discuss the effect of temperature and local host density on this velocity., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)

Identification of the causes of abortion among the huge population of small ruminants in Algeria (≈31 millions heads), is an important task for the control of livestock productivity and viability scourges to the small ruminants industry. Optimal production and utilization is constrained by a number of factors: disease, poor feeding and low management skills. Therefore, in the present study the prevalence of abortion in Algerian small ruminant's flocks was estimated and its possible association was correlated with infectious (PPR, BT and Brucellosis seropositivity) and managerial (flock size, grazing system, type of farming, and contact with other flocks) risk factors. The present study showed an overall flock prevalence of small ruminant's abortion as 75.33% (113/150) [95% CI 71.72-78.94%]. The risk factor analysis using multivariable logistic regression recognized the north-western and the steppe region as well as PPR positivity as a risk factor for abortion in Algerian small ruminant's flocks. The odds of flock abortion was 11.47 [95% CI 2.39-54.88; P=0.002] and 10.31 [95% CI 1.28-82.88; P=0.028] times higher in north-western and steppe regions respectively compared to other region. Also the presence of PPRV infection in small ruminant flocks amplified the odds by 6 times [95% CI 2.221-17.427; P=0.001].Surprisingly, the univariate analysis for the other risk factors associated with abortions in Algerian small ruminant flocks indicated no statistically significant links with bluetongue (P=1.000) and brucellosis seropositivity (P=0.334). Flock size (P=0.574), type of farming (P=0.443), grazing system (P=0.117) and contact with other flocks (P=0.245) was also not statistically significant. Our results revealed that abortion in small ruminants is a challenge to farmers and PPR was chiefly linked to it. Therefore an effective vaccination and control programme is advocated for small ruminants in Algeria., (Copyright © 2015 Elsevier B.V. All rights reserved.)

This study aims at evaluating the costs of the movement restriction policy (MRP) during the 2006 BTV-8 epidemic in France for the producers of 6-9 month old Charolais beef weaned calves (BWC), an important sector that was severely affected by the restrictions imposed. This study estimates the change in the number of BWC sold that was due to the movement restrictions, and evaluates the economic effect of the MRP. The change in BWC sold by producers located inside the restriction zone (RZ) was analyzed for 2006 by using a multivariate matching approach to control for any internal validity threat. The economic evaluation of the MRP was based on several scenarios that describe farms' capacity constraints, feeding prices, and the animal's selling price. Results show that the average farmer experienced a 21% decrease in animals sold due to the MRP. The economic evaluation of the MRP shows a potential gain during the movement standstill period in the case of no capacity constraint faced by the farm and food self-sufficiency. This gain remains limited and close to zero in case of a low selling price and when animals are held until they no longer fit the BWC market so that they cannot be sold as an intermediate product. Capacity constraints represent a tremendous challenge to farmers facing movement restrictions and the fattening profit becomes negative under such conditions. The timing and length of the movement standstill period significantly affect the profitability of the strategy employed by the farmer: for a 5.5 month-long standstill period with 3.5 months of cold weather, farmers with capacity constraints have stronger incentives to leave their animals outside during the whole period and face higher mortality and morbidity rates than paying for a boarding facility for the cold months. This is not necessarily true for a shorter standstill period. Strategies are also sensitive to the feed costs and to the food self-sufficiency of the farm. Altogether, the present work shows the farmer's vulnerability to animal movement restrictions and quantifies the costs of the standstill. These results should assist decision-makers who seek to calculate adequate subsidies/aid or to efficiently allocate resources to prevent future outbreaks., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Movement of animals from one farm to another is a potential risk and can lead to the spreading of livestock diseases. Therefore, in order to implement effective control measures, it is important to understand the movement network in a given area. Using the SANITEL data from 2005 to 2009, around 2 million cattle movements in Belgium were traced. Exploratory analysis revealed different spatial structures for the movement of different cattle types: fattening calves are mostly moved to the Antwerp region, adult cattle are moved to different parts in Belgium. Based on these differences, movement of cattle would more likely cause a spread of disease to a larger number of areas in Belgium as compared to the fattening calves. A closer inspection of the spatial and temporal patterns of cattle movement using a weighted negative binomial model, revealed a significant short-distance movement of bovine which could be an important factor contributing to the local spreading of a disease. The model however revealed hot spot areas of movement in Belgium; four areas in the Walloon region (Luxembourg, Hainaut, Namur and Liege) were found as hot spot areas while East and West Flanders are important "receivers" of movement. This implies that an introduction of a disease to these Walloon regions could result in a spread toward the East and West Flanders regions, as what happened in the case of Bluetongue BTV-8 outbreak in 2006. The temporal component in the model also revealed a linear trend and short- and long-term seasonality in the cattle movement with a peak around spring and autumn. The result of this explorative analysis enabled the identification of "hot spots" in time and space which is important in enhancing any existing monitoring and surveillance system., (Copyright © 2014 Elsevier B.V. All rights reserved.)

In order to put a halt to the Bluetongue virus serotype 8 (BTV-8) epidemic in 2008, the European Commission promoted vaccination at a transnational level as a new measure to combat BTV-8. Most European member states opted for a mandatory vaccination campaign, whereas the Netherlands, amongst others, opted for a voluntary campaign. For the latter to be effective, the farmer's willingness to vaccinate should be high enough to reach satisfactory vaccination coverage to stop the spread of the disease. This study looked at a farmer's expected utility of vaccination, which is expected to have a positive impact on the willingness to vaccinate. Decision analysis was used to structure the vaccination decision problem into decisions, events and payoffs, and to define the relationships among these elements. Two scenarios were formulated to distinguish farmers' mindsets, based on differences in dairy heifer management. For each of the scenarios, a decision tree was run for two years to study vaccination behaviour over time. The analysis was done based on the expected utility criterion. This allows to account for the effect of a farmer's risk preference on the vaccination decision. Probabilities were estimated by experts, payoffs were based on an earlier published study. According to the results of the simulation, the farmer decided initially to vaccinate against BTV-8 as the net expected utility of vaccination was positive. Re-vaccination was uncertain due to less expected costs of a continued outbreak. A risk averse farmer in this respect is more likely to re-vaccinate. When heifers were retained for export on the farm, the net expected utility of vaccination was found to be generally larger and thus was re-vaccination more likely to happen. For future animal health programmes that rely on a voluntary approach, results show that the provision of financial incentives can be adjusted to the farmers' willingness to vaccinate over time. Important in this respect are the decision moment and the characteristics of the disease. Farmers' perceptions of the disease risk and about the efficacy of available control options cannot be neglected., (Copyright © 2014 Elsevier B.V. All rights reserved.)

To monitor Bluetongue virus (BTV) activity in northern and eastern Australia the National Arbovirus Monitoring Program (NAMP) collects data from a network of sentinel herds. Groups of young cattle, previously unexposed to infection, are regularly tested to detect evidence of seroconversion. While this approach has been successful in fulfilling international surveillance requirements, it is labour and cost intensive and operationally challenging in the remote area of the northern Australian rangelands. The aim of this study was to assess the suitability of remotely sensed data as a means for predicting the distribution of BTV seroprevalence. For the period 2000-2009, bioclimatic variables were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) data products for the entire Northern Territory. A generalised linear model, based on the seasonal Normalised Difference Vegetation Index (NDVI) and minimum land surface temperature, was developed to predict BTV seropositivity. The odds of seropositivity in locations with NDVI estimates >0.45 was 3.90 (95% CI 1.11 to 13.7) times that of locations where NDVI estimates were between 0 and 0.45. Unit increases in minimum night land surface temperature in the previous winter increased the odds of seropositivity by a factor of 1.40 (95% CI 1.02 to 1.91). The area under a Receiver Operator Characteristic curve generated on the basis of the model predictions was 0.8. Uncertainty in the model's predictions was attributed to the spatio-temporal inconsistency in the precision of the available serosurveillance data. The discriminatory ability of models of this type could be improved by ensuring that exact location details and date of NAMP BTV test events are consistently recorded., (Copyright © 2012 Elsevier B.V. All rights reserved.)

In 2006, Bluetongue serotype 8 was notified for the first time in north-western Europe, more specifically in Belgium, the Netherlands, Luxemburg, Germany and France. The disease spread very rapidly, affecting mainly cattle and sheep farms. In this paper, we examined risk factors affecting the spatial incidence of reported Bluetongue events during the first outbreak in 2006. Previous studies suggested that the Bluetongue incidence was enhanced by environmental factors, such as temperature and wind speed and direction, as well as by human interventions, such as the transport of animals. In contrast to the previous studies, which were based on univariable analyses, a multivariable epidemiological analysis describing the spatial relationship between Bluetongue incidence and possible risk factors is proposed in this paper. This disentangles the complex interplay between different risk factors. Our model shows that wind is the most important factor affecting the incidence of the disease. In addition, areas with high precipitation are slightly more sensitive to the spread of the infection via the wind. Another important risk factor is the land cover; high-risk areas for infection being characterized by a fragmentation of the land cover, especially the combination of forests and urban areas. Precipitation and temperature are also significant risk factors. High precipitation in areas with a large coverage of forests and/or pasture increases the risk whereas high temperature increases the risk considerably in municipalities covered mainly with pasture. Local spread via the vector is strongest in areas with a large coverage of forests and smallest in highly urbanized areas. Finally, the transport of animals from infected areas is a risk factor., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Bluetongue virus serotype 8 (BTV-8) emerged in north-western Europe in 2006. In 2007, one of the affected countries (the Netherlands) implemented a sentinel network in dairy cattle. This data offered the opportunity to estimate transmission parameters. From our field data, the number of secondary infected cows that became infected by one infectious cow in a completely susceptible herd through the bites of infectious Culicoides i.e. the basic reproduction ratio (R(0)) was calculated. With that information, the R(0) of BTV-8 was estimated using an formulae of a general SIR model. In 2007, the BTV-8 epidemic started in the south and spread northwards in the following months. R(0) could be estimated for 197 herds in which transmission occurred. The median R(0) was 2.3 and the mean R(0) was 3.7 (5th percentile=1.8; 95th percentile=11.0). In the northern region where BTV-8 transmission occurred later in the season with less favorable conditions for transmission, R(0) remained significantly lower than in the south. Our model differed from earlier published more theoretical models on BTV-8 transmission because we estimated transmission from serological field data while other models used literature based assumptions for the majority of the parameters included in their models. Although there were many differences between our model and the previously developed more theoretical models, the results showed similar ranges of R(0) for BTV-8. The reasons for the similarity between the results may be that, although the part of the vector was not included with parameters in our model, the transmission based on serological field data in cows represented both BTV-8 transmission influenced by cows and by its vector, Culicoides. Furthermore, in the earlier models the assumptions made on the vector part, although derived from literature, probably gave a good representation of the true behavior of the Culicoides species that were associated with BTV-8 transmission in north-western Europe., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Empirical analyses founded on sound economic principles are essential in advising policy makers on the efficiency of resource use for disease mitigation. Surveillance and intervention are resource-using activities directed at mitigation. Surveillance helps to offset negative disease effects by promoting successful intervention. Intervention is the process of implementing measures (e.g. vaccination or medication) to reduce or remove a hazard in a population. The scale and ratios in which the two are combined affect the efficiency of mitigation, its costs, benefits, and thus net effect on society's well-being. The Swiss national mitigation programme for bluetongue virus serotype 8 was used as case study to investigate the economic efficiency of mitigation. In 2008, Switzerland implemented a vaccination programme to avoid and reduce disease and infection in its ruminant population. To monitor the vaccination programme and the vector dynamics, a surveillance system consisting of serological and entomological surveillance was established. Retrospective analyses for the years 2008-2009 and prospective analyses for the years 2010-2012 were conducted to investigate if the mitigation programme was economically beneficial. In the retrospective analysis, the implemented programme (=comparative scenario) was compared to a hypothesised baseline scenario of voluntary vaccination and surveillance. In the prospective analysis, the comparative scenario assumed to continue was compared to two baseline scenarios: one of voluntary vaccination combined with surveillance and one of no vaccination combined with surveillance. For each scenario, monetary surveillance, intervention and disease costs were calculated. The comparison of baseline and comparative scenarios yielded estimates for the total benefit (=disease costs avoided), margin over intervention cost and the net value of the programme. For 2008-2009, in aggregate, the mean biannual total benefit was 17.46 m Swiss francs (CHF) (1CHF=0.66€ at the time of analysis) and the mean net benefit after subtraction of the intervention and surveillance cost was 3.95 m CHF. For the three years 2010-2012, overall net costs were estimated at 12.93 m and 8.11 m CHF, respectively, for comparison of the implemented mitigation programme with the two baseline scenarios. It was concluded that the surveillance and intervention programme implemented in 2008-2009 was economically beneficial, while its continuation in the same form in 2010-2012 would produce net costs. These costs were due to the mean intervention cost remaining constant at a level of approximately 11 m CHF per year while the mean total benefit would be gradually reduced in 2010-2012 due to the reduced occurrence of disease in a fully vaccinated population., (Copyright © 2011 Elsevier B.V. All rights reserved.)