We report an ongoing regional outbreak of an emerging porcine reproductive and respiratory syndrome virus (PRRSV2) variant within Lineage 1C affecting 154 breeding and grow-finishing sites in the Midwestern U.S. Transmission seemed to have occurred in two waves, with the first peak of weekly cases occurring between October and December 2020 and the second starting in April 2021. Most of cases occurred within a 120 km radius. Both orf5 and whole genome sequencing results suggest that this represents the emergence of a new variant within Lineage 1C distinct from what has been previously circulating. A case-control study was conducted with 50 cases (sites affected with the newly emerged variant) and 58 controls (sites affected with other PRRSV variants) between October and December 2020. Sites that had a market vehicle that was not exclusive to the production system had 0.04 times the odds of being a case than a control. A spatial cluster (81.42 km radius) with 1.68 times higher the number of cases than controls was found. The average finishing mortality within the first 4 weeks after detection was higher amongst cases (4.50%) than controls (0.01%). The transmission of a highly similar virus between different farms carrying on trough spring rises concerns for the next high transmission season of PRRS.

Lumpy skin disease virus (LSDV) is an infectious disease of cattle transmitted by arthropod vectors which results in substantial economic losses due to impact on production efficiency and profitability, and represents an emerging threat to international trade of livestock products and live animals. Since 2015, the disease has spread into the Northern Hemisphere including Azerbaijan, Kazakhstan, the Russian Federation and the Balkans. The rapid expansion of LSDV in those regions represented the emergence of the virus in more temperate regions than those in which LSDV traditionally occurred. The goal of this study was to assess the risk for further LSDV spread through the (a) analysis of environmental factors conducive for LSDV, and (b) estimate of the underlying LSDV risk, using a combination of ecological niche modelling and fine spatiotemporally explicit Bayesian hierarchical model on LSDV outbreak occurrence data. We used ecological niche modelling to estimate the potential distribution of LSDV outbreaks for 2014-2016. That analysis resulted in a spatial representation of environmental limits where, if introduced, LSDV is expected to efficiently spread. The Bayesian space-time model incorporated both environmental factors and the changing spatiotemporal distribution of the disease to capture the dynamics of disease spread and predict areas in which there is an increased risk for LSDV occurrence. Variables related to the average temperature, precipitation, wind speed, as well as land cover and host densities were important drivers explaining the observed distribution of LSDV in both modelling approaches. Areas of elevated LSDV risks were identified mainly in Russia, Turkey, Serbia and Bulgaria. The results suggest that, if current ecological and epidemiological conditions persist, further spread of LSDV in Eurasia may be expected. The results presented here advance our understanding of the ecological requirements of LSDV in temperate regions and may help in the design and implementation of prevention and surveillance strategies in the region.

Highlights In Uruguay (Uy), bTB highly prevalent dairy herds have emerged. Johne's disease (JD) control programs lack at the national level in Uy. In high prevalence coinfected herds, bTB- and JD-diagnosis interact. An integrated control program is needed for high prevalent coinfected dairies in Uy.

BackgroundBovine tuberculosis (bTB) diagnosis is impaired by numerous factors including cross-reactivity with Mycobacterium avium subspecies paratuberculosis, which causes Johne’s disease (JD). In addition, the effect of repeated bTB-intradermal testing on the performance of JD diagnostic tests is not fully understood. This study aimed to evaluate the impact of repeated bTB-intradermal tests under field conditions in Spain on the JD serological status of cattle.MethodsbTB-positive herds (n=264) from Castilla-y-Leon region were selected and matched with officially tuberculosis-free control herds. The association between JD and bTB status at the herd level was assessed using conditional logistic regression and, in herds with both JD-positive and bTB-positive animals, a Bayesian hierarchical mixed-effect model was used for individual-level analysis.ResultsA significantly higher risk of being JD positive (OR: 1.48; 95 per cent CI: 1.01 to 2.15) was found for bTB-positive herds compared with controls. Individual results indicated that cattle tested more than three times per year, within the last 90 days and more than 12 months were more likely to be JD positive. A skin test-related boost in antibody response could be the cause of an apparent increase of the sensitivity of the JD-absorbed ELISA.ConclusionThe results demonstrate the interaction between bTB repeated testing and JD individual and herd-level results and this improved knowledge will facilitate the design of more effective control programmes in herds coinfected with two of the most important endemic diseases affecting cattle in Spain.

Accuracy of new or alternative diagnostic tests is typically estimated in relation to a well-standardized reference test referred to as a gold standard. However, for bovine tuberculosis (bTB), a chronic disease of cattle, affecting animal and public health, no reliable gold standard is available. In this context, latent-class models implemented using a Bayesian approach can help to assess the accuracy of diagnostic tests incorporating previous knowledge on test performance and disease prevalence. In Uruguay, bTB-prevalence has increased in the past decades partially because of the limited accuracy of the diagnostic strategy in place, based on intradermal testing (caudal fold test, CFT, for screening and comparative cervical test, CCT, for confirmation) and slaughter of reactors. Here, we evaluated the performance of two alternative bTB-diagnostic tools, the interferon-gamma assay, IGRA, and the enzyme-linked immunosorbent assay (ELISA), which had never been used in Uruguay in the absence of a gold standard. In order to do so animals from two heavily infected dairy herds and tested with CFT-CCT were also analyzed with the IGRA using two antigens (study 1) and the ELISA (study 2). The accuracy of the IGRA and ELISA was assessed fitting two latent-class models: a two test-one population model (LCA-a) based on the analysis of CFT/CFT-CCT test results and one in-vitro test (IGRA/ELISA), and a one test-one population model (LCA-b) using the IGRA or ELISA information in which the prevalence was modeled using information from the skin tests. Posterior estimates for model LCA-a suggested that IGRA was as sensitive (75–78%) as the CFT and more sensitive than the serial use of CFT-CCT. Its specificity (90–96%) was superior to the one for the CFT and equivalent to the use of CFT-CCT. Estimates from LCA-b models consistently yielded lower posterior Se estimates for the IGRA but similar results for its Sp. Estimates for the Se (52% 95%PPI:44.41-71.28) and the Sp (92% 95%PPI:78.63–98.76) of the ELISA were however similar regardless of the model used. These results suggest that the incorporation of IGRA for detection of bTB in highly infected herds could be a useful tool to improve the sensitivity of the bTB-control in Uruguay.

Bovine tuberculosis (bTB) prevalence substantially increased over the past two decades with relatively high impact on large dairy herds, raising the concern of regulatory authorities and industry stakeholders, and threatening animal and public health.Lack of resources, together with the economic and social consequences of wholeherd stamping-out, makes depopulation an impractical disease control alternative in these herds. The increase in bTB prevalence was associated with demographic and

surface water to supply ∼1,700,000 people. Infected calves on all farms were within 20-900 m of a natural surface watercourse draining the farmland, 10 of which flowed into six water treatment plants located 9-108 km downstream. Four watercourses flowed downstream into Aguas Corrientes. Calves are reservoirs of zoonotic C. parvum subtypes in Uruguay and pose a public health risk.

Chronic wasting disease (CWD) is a disease affecting cervids and is caused by prions accumulating as pathogenic fibrils in lymphoid tissue and the central nervous system. Approaches for detecting CWD prions historically relied on antibody-based assays. However, recent advancements in protein amplification technology provided the foundation for a new class of CWD diagnostic tools. In particular, real-time quaking-induced conversion (RT-QuIC) has rapidly become a feasible option for CWD diagnosis. Despite its increased usage for CWD-focused research, there lacks a consensus regarding the interpretation of RT-QuIC data for diagnostic purposes. It is imperative then to identify a standardized and replicable method for determining CWD status from RT-QuIC data. Here, we assessed variables that could impact RT-QuIC results and explored the use of maxpoint ratios (maximumRFU/backgroundRFU) to improve the consistency of RT-QuIC analysis. We examined a variety of statistical analyses to retrospectively analyze CWD status based on RT-QuIC and ELISA results from 668 white-tailed deer lymph nodes. Our results revealed an MPR threshold of 2.0 for determining the rate of amyloid formation, and MPR analysis showed excellent agreement with independent ELISA results. These findings suggest that the use of MPR is a statistically viable option for normalizing between RT-QuIC experiments and defining CWD status.