Quantitative risk assessment for the introduction of bluetongue virus into mainland Europe by long-distance wind dispersal of Culicoides spp.: A case study from Sardinia.

Europe faces regular introductions and reintroductions of bluetongue virus (BTV) serotypes, most recently exemplified by the incursion of serotype 3 in the Netherlands. Although the long-distance wind dispersal of the disease vector, Culicoides spp., is recognized as a virus introduction pathway, it remains understudied in risk assessments. A Quantitative Risk Assessment framework was developed to estimate the risk of BTV-3 incursion into mainland Europe from Sardinia, where the virus has been present since 2018. We used an atmospheric transport model (HYbrid Single-Particle Lagrangian Integrated Trajectory) to infer the probability of airborne dispersion of the insect vector. Epidemiological disease parameters quantified the virus prevalence in vector population in Sardinia and its potential first transmission after introduction in a new area. When assuming a 24h maximal flight duration, the risk of BTV introduction from Sardinia is limited to the Mediterranean Basin, mainly affecting the southwestern area of the Italian Peninsula, Sicily, Malta, and Corsica. The risk extends to the northern and central parts of Italy, Balearic archipelago, and mainland France and Spain, mostly when maximal flight duration is longer than 24h. Additional knowledge on vector flight conditions and Obsoletus complex-specific parameters could improve the robustness of the model. Providing both spatial and temporal insights into BTV introduction risks, our framework is a key tool to guide global surveillance and preparedness against epizootics.

Framework for Estimating Indirect Costs in Animal Health Using Time Series Analysis.

Traditionally, cost-benefit analyses (CBAs) focus on the direct costs of animal disease, including animal mortality, morbidity, and associated response costs. However, such approaches often fail to capture the wider, dynamic market impacts that could arise. The duration of these market dislocations could last well after an initial disease outbreak. More generally, current approaches also muddle definitions of indirect costs, confusing debate on the scope of the totalities of disease-induced economic impacts. The aim of this work was to clarify definitions of indirect costs in the context of animal diseases and to apply this definition to a time series methodological framework to estimate the indirect costs of animal disease control strategies, using a foot and mouth disease (FMD) outbreak in Scotland as a case study. Time series analysis is an econometric method for analyzing statistical relationships between data series over time, thus allowing insights into how market dynamics may change following a disease outbreak. First an epidemiological model simulated FMD disease dynamics based on alternative control strategies. Output from the epidemiological model was used to quantify direct costs and applied in a multivariate vector error correction model to quantify the indirect costs of alternative vaccine stock strategies as a result of FMD. Indirect costs were defined as the economic losses incurred in markets after disease freedom is declared. As such, our definition of indirect costs captures the knock-on price and quantity effects in six agricultural markets after a disease outbreak. Our results suggest that controlling a FMD epidemic with vaccination is less costly in direct and indirect costs relative to a no vaccination (i.e., "cull only") strategy, when considering large FMD outbreaks in Scotland. Our research clarifies and provides a framework for estimating indirect costs, which is applicable to both exotic and endemic diseases. Standard accounting CBAs only capture activities in isolation, ignore linkages across sectors, and do not consider price effects. However, our framework not only delineates when indirect costs start, but also captures the wider knock-on price effects between sectors, which are often omitted from CBAs but are necessary to support decision-making in animal disease prevention and control strategies.

Assessing the Economic Impact of Vaccine Availability When Controlling Foot and Mouth Disease Outbreaks.

Predictive models have been used extensively to assess the likely effectiveness of vaccination policies as part of control measures in the event of a foot and mouth disease (FMD) outbreak. However, the availability of vaccine stocks and the impact of vaccine availability on disease control strategies represent a key uncertainty when assessing potential control strategies. Using an epidemiological, spatially explicit, simulation model in combination with a direct cost calculator, we assessed how vaccine availability constraints may affect the economic benefit of a "vaccination-to-live" strategy during a FMD outbreak in Scotland, when implemented alongside culling of infected premises and dangerous contacts. We investigated the impact of vaccine stock size and restocking delays on epidemiological and economic outcomes. We also assessed delays in the initial decision to vaccinate, maximum daily vaccination capacity, and vaccine efficacy. For scenarios with conditions conducive to large outbreaks, all vaccination strategies perform better than the strategy where only culling is implemented. A stock of 200,000 doses, enough to vaccinate 12% of the Scottish cattle population, would be sufficient to maximize the relative benefits of vaccination, both epidemiologically and economically. However, this generates a wider variation in economic cost than if vaccination is not implemented, making outcomes harder to predict. The probability of direct costs exceeding £500 million is reduced when vaccination is used and is steadily reduced further as the size of initial vaccine stock increases. If only a suboptimal quantity of vaccine doses is initially available (100,000 doses), restocking delays of more than 2 weeks rapidly increase the cost of controlling outbreaks. Impacts of low vaccine availability or restocking delays are particularly aggravated by delays in the initial decision to vaccinate, or low vaccine efficacy. Our findings confirm that implementing an emergency vaccination-to-live strategy in addition to the conventional stamping out strategy is economically beneficial in scenarios with conditions conducive to large FMD outbreaks in Scotland. However, the size of the initial vaccine stock available at the start of the outbreak and the interplay with other factors, such as vaccine efficacy and delays in restocking or implementing vaccination, should be considered in making decisions about optimal control strategies for FMD outbreaks.

Data-Driven Risk Assessment from Small Scale Epidemics: Estimation and Model Choice for Spatio-Temporal Data with Application to a Classical Swine Fever Outbreak.

Livestock epidemics have the potential to give rise to significant economic, welfare, and social costs. Incursions of emerging and re-emerging pathogens may lead to small and repeated outbreaks. Analysis of the resulting data is statistically challenging but can inform disease preparedness reducing potential future losses. We present a framework for spatial risk assessment of disease incursions based on data from small localized historic outbreaks. We focus on between-farm spread of livestock pathogens and illustrate our methods by application to data on the small outbreak of Classical Swine Fever (CSF) that occurred in 2000 in East Anglia, UK. We apply models based on continuous time semi-Markov processes, using data-augmentation Markov Chain Monte Carlo techniques within a Bayesian framework to infer disease dynamics and detection from incompletely observed outbreaks. The spatial transmission kernel describing pathogen spread between farms, and the distribution of times between infection and detection, is estimated alongside unobserved exposure times. Our results demonstrate inference is reliable even for relatively small outbreaks when the data-generating model is known. However, associated risk assessments depend strongly on the form of the fitted transmission kernel. Therefore, for real applications, methods are needed to select the most appropriate model in light of the data. We assess standard Deviance Information Criteria (DIC) model selection tools and recently introduced latent residual methods of model assessment, in selecting the functional form of the spatial transmission kernel. These methods are applied to the CSF data, and tested in simulated scenarios which represent field data, but assume the data generation mechanism is known. Analysis of simulated scenarios shows that latent residual methods enable reliable selection of the transmission kernel even for small outbreaks whereas the DIC is less reliable. Moreover, compared with DIC, model choice based on latent residual assessment correlated better with predicted risk.

Drivers of Live Cattle Price in the Livestock Trading System of Central Cameroon.

Livestock production and trade are critical for the food security and welfare of rural households in sub-Saharan Africa. In Cameroon, animal trade consists mainly of live cattle commercialized through livestock markets. Identifying the factors contributing to cattle price formation is critical for designing effective policies for sustainable production and for increasing food availability. In this study, we evaluated the influence of a range of individual- and market-level factors on the price of cattle that were sold in all transactions (n = 118,017) recorded over a 12-month period from 31 livestock markets in the main cattle production area of the country. An information-theoretic approach using a generalized additive mixed-effect model was implemented to select the best explanatory model as well as evaluate the robustness of the identified drivers and the predictive ability of the model. The age and gender of the cattle traded were consistently found to be important drivers of the price (p < 0.01). Also, strong, but complex, relationships were found between cattle prices and both local human and bovine population densities. Finally, the model highlighted a positive association between the number of incoming trading connections of a livestock market and the price of the traded live cattle (p < 0.01). Although our analysis did not account for factors informing on specific phenotypic traits nor breed characteristics of cattle traded, nearly 50% of the observed variation in live cattle prices was explained by the final model. Ultimately, our model gives a large scale overview of drivers of cattle price formation in Cameroon and to our knowledge is the first study of this scale in Central Africa. Our findings represent an important milestone in designing efficient and sustainable animal health management programme in Cameroon and ensure livelihood sustainability for rural households.

The Importance of Socio-Economic Versus Environmental Risk Factors for Reported Dengue Cases in Java, Indonesia.

BACKGROUND: Dengue is a major mosquito-borne viral disease and an important public health problem. Identifying which factors are important determinants in the risk of dengue infection is critical in supporting and guiding preventive measures. In South-East Asia, half of all reported fatal infections are recorded in Indonesia, yet little is known about the epidemiology of dengue in this country. METHODOLOGY/PRINCIPAL FINDINGS: Hospital-reported dengue cases in Banyumas regency, Central Java were examined to build Bayesian spatial and spatio-temporal models assessing the influence of climatic, demographic and socio-economic factors on the risk of dengue infection. A socio-economic factor linking employment type and economic status was the most influential on the risk of dengue infection in the Regency. Other factors such as access to healthcare facilities and night-time temperature were also found to be associated with higher risk of reported dengue infection but had limited explanatory power. CONCLUSIONS/SIGNIFICANCE: Our data suggest that dengue infections are triggered by indoor transmission events linked to socio-economic factors (employment type, economic status). Preventive measures in this area should therefore target also specific environments such as schools and work areas to attempt and reduce dengue burden in this community. Although our analysis did not account for factors such as variations in immunity which need further investigation, this study can advise preventive measures in areas with similar patterns of reported dengue cases and environment.

Small-scale pig farmers' behavior, silent release of African swine fever virus and consequences for disease spread.

The expanding distribution of African swine fever (ASF) is threatening the pig industry worldwide. Most outbreaks occur in backyard and small-scale herds, where poor farmers often attempt to limit the disease's economic consequences by the emergency sale of their pigs. The risk of African swine fever virus (ASFV) release via this emergency sale was investigated. Simulation modeling was used to study ASFV transmission in backyard and small-scale farms as well as the emergency sale of pigs, and the potential impact of improving farmers and traders' clinical diagnosis ability-its timeliness and/or accuracy-was assessed. The risk of ASFV release was shown to be high, and improving farmers' clinical diagnosis ability does not appear sufficient to effectively reduce this risk. Estimates obtained also showed that the distribution of herd size within the backyard and small-scale sectors influences the relative contribution of these farms to the risk of release of infected pigs. These findings can inform surveillance and control programs.

Mapping brucellosis risk in communities in the Republic of Armenia.

We describe the geographical patterns and identified factors associated with serological evidence of brucellosis in ruminants in Armenian communities during 2006 and 2007. The data comprised the two first complete years of the current national test-and-slaughter control programme for cattle, sheep and goats. Overall, 29% and 21% of the 858 communities involved in this study reported brucellosis in their respective cattle and small ruminant populations. The national brucellosis control data showed a widespread and uneven distribution of brucellosis throughout the Republic of Armenia for both cattle and small ruminants. The geographical areas of greater risk of communities having seropositive animals were different for cattle and small ruminant populations but most of the associated factors were similar. Several areas where the likelihood of disease occurrence was predicted poorly by the statistical models were also identified. These latter findings are indicative of either less than perfect testing and reporting procedures or unexplained epidemiological factors operating in those particular areas. The analyses provided valuable insights into understanding the brucellosis epidemiology at the community level which operates in small ruminant and cattle populations, and identified priority areas for implementing targeted risk-based surveillance and disease control interventions.