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African Swine Fever (ASF) is a reportable disease of swine that causes farreaching losses to affected countries and regions. Early detection is critically important to contain and mitigate the impact of ASF outbreaks, for which timely available data is essential. This research examines the potential use of Google Trends data as an early indicator of ASF outbreaks in Southeast Asia, focusing on the three largest swine producing countries, namely, Vietnam, the Philippines, and Thailand. Cross-correlation and Kullback-Leibler (KL) divergence indicators were used to evaluate the association between Google search trends and the number of ASF outbreaks reported. Our analysis indicate strong and moderate correlations between Google search trends and number of ASF outbreaks reported in Vietnam and the Philippines, respectively. In contrast, Thailand, the country of this group in which outbreaks were reported last, exhibits the weakest correlation (KL = 2.64), highlighting variations in public awareness and disease dynamics. These findings suggest that Google search trends are valuable for early detection of ASF. As the disease becomes endemic, integrating trends with other epidemiological data may support the design and implementation of surveillance strategies for transboundary animal diseases in Southeast Asia. [ABSTRACT FROM AUTHOR]

Amblyomma ovale hard ticks are located predominantly in South and Central America but can also be found in areas of the nearctic, particularly Mexico and the southern United States (1,2). [...]

Since African Swine Fever (ASF) was detected in the Dominican Republic in July 2021, it has negatively impacted the country's swine industry. Assessing the epidemiological situation is crucial to helping local authorities and industry stakeholders control the disease. Here, data on 155 reported outbreaks in the Dominican Republic from November 2022 to June 2023 were evaluated. Descriptive spatiotemporal analysis was performed to characterize disease distribution and spread, and between-herd R0 was calculated for the study period. The Knox test and a space–time permutation model were used to evaluate clustering. Data on clinical presentation, biosecurity measures, and suspected reasons for introduction were categorized and summarized. The majority (78%) of outbreaks occurred on backyard farms which generally had low biosecurity. Across farm types, the majority of pigs were still alive at the time of depopulation. Spatiotemporal findings and R0 estimates suggest an endemic pattern of disease geographically located centrally within the country. Clustering was detected even at small temporal and spatial distances due to outbreaks amongst neighboring backyard farms. These results provide critical information on the current state of the ASF epidemic in the Dominican Republic and will aid government officials and swine industry leaders in developing effective ASF control strategies. [ABSTRACT FROM AUTHOR]

Rickettsia parkeri is an emerging pathogen that causes a spotted fever group rickettsiosis, transmitted to humans primarily by several species of ticks of the genus Amblyomma, including A. maculatum, A. [...]

Rickettsia parkeri, a member of the spotted fever group Rickettsia (SFGR), was initially identified in Amblyomma maculatum ticks in 1937, but not until 2004 was the first confirmed human infection [...]

Modeling the windborne transmission of aerosolized pathogens is challenging. We adapted an atmospheric dispersion model named the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to simulate the windborne dispersion of porcine reproductive and respiratory syndrome virus (PRRSv) between swine farms and incorporated the findings into an outbreak investigation. The risk was estimated semi-quantitatively based on the cumulative daily deposition of windborne particles and the distance to the closest emitting farm with an ongoing outbreak. Five years of data (2014:2018) were used to study the seasonal differences of the deposition thresholds of the airborne particles containing PRRSv and to evaluate the model in relation to risk prediction and barn air filtration. When the 14-day cumulative deposition was considered, in winter, above-threshold particle depositions would reach up to 30 km from emitting farms with 84% of them being within 10 km. Long-distance pathogen transmission was highest in winter and fall, lower in spring, and least in summer. The model successfully replicated the observed seasonality of PRRSv, where fall and winter posed a higher risk for outbreaks. Reaching the humidity and temperature thresholds tolerated by the virus in spring and summer reduced the survival and infectivity of aerosols beyond 10–20 km. Within the data limitations of voluntary participation, when wind was assumed to be the sole route of PRRSv transmission, the predictive performance of the model was fair with >0.64 AUC. Barn air filtration was associated with fewer outbreaks, particularly when exposed to high levels of viral particles. This study confirms the usefulness of the HYSPLIT model as a tool when determining seasonal effects and distances and informs the near real-time risk of windborne PRRSv transmission that can be useful in future outbreak investigations and for implementing timely control measures. [ABSTRACT FROM AUTHOR]

Modeling the windborne transmission of aerosolized pathogens is challenging. We adapted an atmospheric dispersion model (ADM) to simulate the windborne dispersion of porcine reproductive and respiratory syndrome virus (PRRSv) between swine farms. This work focuses on determining ADM applicable parameter values for PRRSv through a literature and expert opinion-based approach. The parameters included epidemiological features of PRRSv, characteristics of the aerosolized particles, and survival of aerosolized virus in relation to key meteorological features. A case study was undertaken to perform a sensitivity analysis on key parameters. Farms experiencing ongoing PRRSv outbreaks were assigned as particle emitting sources. The wind data from the North American Mesoscale Forecast System was used to simulate dispersion. The risk was estimated semi-quantitatively based on the median daily deposition of particles and the distance to the closest emitting farm. Among the parameters tested, the ADM was most sensitive to the number of particles emitted, followed by the model runtime, and the release height was the least sensitive. Farms within 25 km from an emitting farm were at the highest risk; with 53.66% being within 10 km. An ADM-based risk estimation of windborne transmission of PRRSv may inform optimum time intervals for air sampling, plan preventive measures, and aid in ruling out the windborne dispersion in outbreak investigations. [ABSTRACT FROM AUTHOR]

Peste des petits ruminants (PPR) is a viral transboundary disease seen in small ruminants, that causes significant damage to agriculture. This disease has not been previously registered in the Republic of Kazakhstan (RK). This paper presents an assessment of the susceptibility of the RK's territory to the spread of the disease in the event of its importation from infected countries. The negative binomial regression model that was trained on the PPR outbreaks in China, was used to rank municipal districts in the RK in terms of PPR spread risk. The outbreak count per administrative district was used as a risk indicator, while a number of socio‐economic, landscape, and climatic factors were considered as explanatory variables. Summary road length, altitude, the density of small ruminants, the maximum green vegetation fraction, cattle density, and the Engel coefficient were the most significant factors. The model demonstrated a good performance in training data (R2 = 0.69), and was transferred to the RK, suggesting a significantly lower susceptibility of this country to the spread of PPR. Hot spot analysis identified three clusters of districts at the highest risk, located in the western, eastern, and southern parts of Kazakhstan. As part of the study, a countrywide survey was conducted to collect data on the distribution of livestock populations, which resulted in the compilation of a complete geo‐database of small ruminant holdings in the RK. The research results may be used to formulate a national strategy for preventing the importation and spread of PPR in Kazakhstan through targeted monitoring in high‐risk areas. [ABSTRACT FROM AUTHOR]

Abstract Background Eradication of bovine tuberculosis (bTB) through the application of test-and-cull programs is a declared goal of developed countries in which the disease is still endemic. Here, longitudinal data from more than 1,700 cattle herds tested during a 12 year-period in the eradication program in the region of Madrid, Spain, were analyzed to quantify the within-herd transmission coefficient (β) depending on the herd-type (beef/dairy/bullfighting). In addition, the probability to recover the officially bTB free (OTF) status in infected herds depending on the type of herd and the diagnostic strategy implemented was assessed using Cox proportional hazard models. Results Overall, dairy herds showed higher β (median 4.7) than beef or bullfighting herds (2.3 and 2.2 respectively). Introduction of interferon-gamma (IFN-γ) as an ancillary test produced an apparent increase in the β coefficient regardless of production type, likely due to an increase in diagnostic sensitivity. Time to recover OTF status was also significantly lower in dairy herds, and length of bTB episodes was significantly reduced when the IFN-γ was implemented to manage the outbreak. Conclusions Our results suggest that bTB spreads more rapidly in dairy herds compared to other herd types, a likely cause being management and demographic-related factors. However, outbreaks in dairy herds can be controlled more rapidly than in typically extensive herd types. Finally, IFN-γ proved its usefulness to rapidly eradicate bTB at a herd-level.

Here, we report the results of a cross‐sectional study designed to monitor the circulation and genetic diversity of foot and mouth disease virus (FMDV) in Uganda between 2014 and 2017. In this study, 13,614 sera and 2,068 oral‐pharyngeal fluid samples were collected from cattle and analysed to determine FMDV seroprevalence, circulating serotypes and their phylogenetic relationships. Circulation of FMDV was evidenced by the detection of antibodies against non‐structural proteins of FMDV or viral isolations in all districts sampled in Uganda. Sequence analysis revealed the presence of FMDV serotypes A, O, SAT 1 and SAT 2. FMDVs belonging to serotype O, isolated from 21 districts, were the most prevalent and were classified into six lineages within two East African topotypes, namely EA‐1 and EA‐2. Serotype A viruses belonging to the Africa G‐I topotype were isolated from two districts. SAT 1 viruses grouped within topotypes I and IV and SAT 2 viruses within topotypes VII, IV and X were isolated from six and four districts respectively. Phylogenetic analysis of SAT 1 and SAT 2 sequences from cattle clustered with historical sequences from African buffalo, indicating possible interspecies transmission at the wildlife‐livestock interface. In some cases, Uganda viruses also shared similarities to viral strains recovered from other regions in East Africa. This 3‐year study period provides knowledge about the geographical distribution of FMDV serotypes isolated in Uganda and insights into the genetic diversity of the multiple serotypes circulating in the country. Knowledge of circulating FMDV viruses will assist in antigenic matching studies to devise improved FMDV control strategies with vaccination and vaccine strain selection for Uganda. [ABSTRACT FROM AUTHOR]

The dissemination of Influenza A virus (IAV) throughout the world has become one of the main concerns for the health of both animals and human beings. An efficient and sensitive diagnostic tool is thus needed for the early detection of IAV. Here, we developed a wash-free magnetic bioassay and further integrated it with a handheld platform based on giant-magnetoresistance (GMR) sensors. The wash-free magnetic bioassay significantly accelerates and simplifies the detection process. This brand-new system was successful in detecting both IAV nucleoprotein and IAV-contained nasal swab samples from pigs on the farm. The limit of detection (LOD) is 0.3 nM for IAV nucleoprotein and 250 TCID50/mL for IAV-spiked nasal swab samples. The detection of nasal swab samples containing unpurified IAV was also performed, demonstrating the capability of the magnetic wash-free assay in the detection of biomarkers in complex sample matrix. [ABSTRACT FROM AUTHOR]

Disease spread in populations is a consequence of the interaction between host, pathogen, and environment, i.e. the epidemiological triad. Yet the influences of each triad component may vary dramatically for different settings. Comparison of environmental, demographic, socio-economic, and historical backgrounds may support tailoring site-specific control measures. Because of the long-term survival of Bacillus anthracis, Anthrax is a suitable example for studying the influence of triad components in different endemic settings. We compared the spatiotemporal patterns of historic animal Anthrax records in two endemic areas, located at northern latitudes in the western and eastern hemispheres. Our goal was to compare the spatiotemporal patterns in Anthrax progression, intensity, direction, and recurrence (disease hot spots), in relation to epidemiological factors and potential trigger events. Reported animal cases in Minnesota, USA (n = 289 cases between 1912 and 2014) and Kazakhstan (n = 3,997 cases between 1933 and 2014) were analyzed using the spatiotemporal directionality test and the spatial scan statistic. Over the last century Anthrax occurrence in Minnesota was sporadic whereas Kazakhstan experienced a long-term epidemic. Nevertheless, the seasonality was comparable between sites, with a peak in August. Declining number of cases at both sites was attributed to vaccination and control measures. The spatiotemporal directionality test detected a relative northeastern directionality in disease spread for long-term trends in Minnesota, whereas a southwestern directionality was observed in Kazakhstan. In terms of recurrence, the maximum timespans between cases at the same location were 55 and 60 years for Minnesota and Kazakhstan, respectively. Disease hotspots were recognized in both settings, with spatially overlapping clusters years apart. Distribution of the spatiotemporal cluster radii between study sites supported suggestion of site-specific control zones. Spatiotemporal patterns of Anthrax occurrence in both endemic regions were attributed to multiple potential trigger events including major river floods, changes in land use, agriculture, and susceptible livestock populations. Results here help to understand the long-term epidemiological dynamics of Anthrax while providing suggestions to the design and implementation of prevention and control programs, in endemic settings. [ABSTRACT FROM AUTHOR]

Porcine reproductive and respiratory syndrome virus (PRRSv) infection causes a devastating economic impact to the swine industry. Active surveillance is routinely conducted in many swine herds to demonstrate freedom from PRRSv infection. The design of efficient active surveillance sampling schemes is challenging because optimum surveillance strategies may differ depending on infection status, herd structure, management, or resources for conducting sampling. Here, we present an open web-based application, named ‘OptisampleTM’, designed to optimize herd sampling strategies to substantiate freedom of infection considering also costs of testing. In addition to herd size, expected prevalence, test sensitivity, and desired level of confidence, the model takes into account the presumed risk of pathogen introduction between samples, the structure of the herd, and the process to select the samples over time. We illustrate the functionality and capacity of ‘OptisampleTM’ through its application to active surveillance of PRRSv in hypothetical swine herds under disparate epidemiological situations. Diverse sampling schemes were simulated and compared for each herd to identify effective strategies at low costs. The model results show that to demonstrate freedom from disease, it is important to consider both the epidemiological situation of the herd and the sample selected. The approach illustrated here for PRRSv may be easily extended to other animal disease surveillance systems using the web-based application available at . [ABSTRACT FROM AUTHOR]

Over a decade ago, foot-and-mouth disease (FMD) re-emerged in Southern Africa specifically in beef exporting countries that had successfully maintained disease-free areas in the past. FMD virus (FMDV) serotype SAT2 has been responsible for a majority of these outbreaks. Epidemiological studies have revealed the importance of the African buffalo as the major wildlife FMD reservoir in the region. We used phylogeographic analysis to study dynamics of FMD transmission between buffalo and domestic cattle at the interface of the major wildlife protected areas in the region currently encompassing two largest Transfrontier conservation areas: Kavango-Zambezi (KAZA) and Great Limpopo (GL). Results of this study showed restricted local occurrence of each FMDV SAT2 topotypes I, II, and III, with occasional virus migration from KAZA to GL. Origins of outbreaks in livestock are frequently attributed to wild buffalo, but our results suggest that transmission from cattle to buffalo also occurs. We used coalescent Bayesian skyline analysis to study the genetic variation of the virus in cattle and buffalo, and discussed the association of these genetic changes in the virus and relevant epidemiological events that occurred in this area. Our results show that the genetic diversity of FMDV SAT2 has decreased in buffalo and cattle population during the last decade. This study contributes to understand the major dynamics of transmission and genetic variation of FMDV SAT2 in Southern Africa, which will could ultimately help in designing efficient strategies for the control of FMD at a local and regional level. [ABSTRACT FROM AUTHOR]

We have developed a simple and sensitive method for the detection of influenza A virus based on giant magnetoresistance (GMR) biosensor. This assay employs monoclonal antibodies to viral nucleoprotein (NP) in combination with magnetic nanoparticles (MNPs). Presence of influenza virus allows the binding of MNPs to the GMR sensor and the binding is proportional to the concentration of virus. Binding of MNPs onto the GMR sensor causes change in the resistance of sensor, which is measured in a real time electrical readout. GMR biosensor detected as low as 1.5 × 10² TCID50/mL virus and the signal intensity increased with increasing concentration of virus up to 1.0 × 105 TCID50/mL. This study showed that the GMR biosensor assay is relevant for diagnostic application since the virus concentration in nasal samples of influenza virus infected swine was reported to be in the range of 10³ to 105 TCID50/mL. [ABSTRACT FROM AUTHOR]

Due to the highly transmissible nature of porcine reproductive and respiratory syndrome (PRRS), implementation of regional programs to control the disease may be critical. Because PRRS is not reported in the US, numerous voluntary regional control projects (RCPs) have been established. However, the effect of RCPs on PRRS control has not been assessed yet. This study aims to quantify the extent to which RCPs contribute to PRRS control by proposing a methodological framework to evaluate the progress of RCPs. Information collected between July 2012 and June 2015 from the Minnesota Voluntary Regional PRRS Elimination Project (RCP-N212) was used. Demography of premises (e.g. composition of farms with sows = SS and without sows = NSS) was assessed by a repeated analysis of variance. By using general linear mixed-effects models, active participation of farms enrolled in the RCP-N212, defined as the decision to share (or not to share) PRRS status, was evaluated and used as a predictor, along with other variables, to assess the PRRS trend over time. Additionally, spatial and temporal patterns of farmers’ participation and the disease dynamics were investigated. The number of farms enrolled in RCP-N212 and its geographical coverage increased, but the proportion of SS and NSS did not vary significantly over time. A significant increasing (p<0.001) trend in farmers’ decision to share PRRS status was observed, but with NSS producers less willing to report and a large variability between counties. The incidence of PRRS significantly (p<0.001) decreased, showing a negative correlation between degree of participation and occurrence of PRRS (p<0.001) and a positive correlation with farm density at the county level (p = 0.02). Despite a noted decrease in PRRS, significant spatio-temporal patterns of incidence of the disease over 3-weeks and 3-kms during the entire study period were identified. This study established a systematic approach to quantify the effect of RCPs on PRRS control. Despite an increase in number of farms enrolled in the RCP-N212, active participation is not ensured. By evaluating the effect of participation on the occurrence of PRRS, the value of sharing information among producers may be demonstrated, in turn justifying the existence of RCPs. [ABSTRACT FROM AUTHOR]

Classical phylogenetic methods such as neighbor-joining or maximum likelihood trees, provide limited inferences about the evolution of important pathogens and ignore important evolutionary parameters and uncertainties, which in turn limits decision making related to surveillance, control, and prevention resources. Bayesian phylodynamic models have recently been used to test research hypotheses related to evolution of infectious agents. However, few studies have attempted to model the evolutionary dynamics of porcine reproductive and respiratory syndrome virus (PRRSV) and, to the authors' knowledge, no attempt has been made to use large volumes of routinely collected data, sometimes referred to as big data, in the context of animal disease surveillance. The objective of this study was to explore and discuss the applications of Bayesian phylodynamic methods for modeling the evolution and spread of a notable 1-7-4 RFLP-type PRRSV between 2014 and 2015. A convenience sample of 288 ORF5 sequences was collected from 5 swine production systems in the United States between September 2003 and March 2015. Using coalescence and discrete trait phylodynamic models, we were able to infer population growth and demographic history of the virus, identified the most likely ancestral system (root state posterior probability = 0.95) and revealed significant dispersal routes (Bayes factor > 6) of viral exchange among systems. Results indicate that currently circulating viruses are evolving rapidly, and show a higher level of relative genetic diversity over time, when compared to earlier relatives. Biological soundness of model results is supported by the finding that sow farms were responsible for PRRSV spread within the systems. Such results cannot be obtained by traditional phylogenetic methods, and therefore, our results provide a methodological framework for molecular epidemiological modeling of new PRRSV outbreaks and demonstrate the prospects of phylodynamic models to inform decision-making processes for routine surveillance and, ultimately, to support prevention and control of food animal disease at local and regional scales. [ABSTRACT FROM AUTHOR]

DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the Direccion General de Ganaderia, Dominican Republic. On 28 July 2021, two ASF outbreaks were confirmed in the Dominican Republic, affecting the provinces of Montecristi and Sánchez Ramírez (OIE, 2021a). African swine fever (ASF) is a devastating disease of domestic and wild swine caused by infection with a DNA virus of the I Asfaviridae i family generically referred to as ASF virus (ASFv). [Extracted from the article]

The article focuses on the lessons learned and knowledge gaps about the epidemiology and control of porcine reproductive and respiratory syndrome virus (PRRSV) in North America. Topics include vaccination found to be useful in shedding of PRRSV, occurrence of between-farm spread of PRRSV through a number of routes including live pigs, semen, and vehicles, and various control and elimination programs for PRRSV conducted at the farm level and regional level.

Previous Bayesian phylogeographic studies of H5N1 highly pathogenic avian influenza viruses (HPAIVs) explored the origin and spread of the epidemic from China into Russia, indicating that HPAIV circulated in Russia prior to its detection there in 2005. In this study, we extend this research to explore the evolution and spread of HPAIV within Europe during the 2005-2010 epidemic, using all available sequences of the hemagglutinin (HA) and neuraminidase (NA) gene regions that were collected in Europe and Russia during the outbreak. We use discrete-trait phylodynamic models within a Bayesian statistical framework to explore the evolution of HPAIV. Our results indicate that the genetic diversity and effective population size of HPAIV peaked between mid-2005 and early 2006, followed by drastic decline in 2007, which coincides with the end of the epidemic in Europe. Our results also suggest that domestic birds were the most likely source of the spread of the virus from Russia into Europe. Additionally, estimates of viral dispersal routes indicate that Russia, Romania, and Germany were key epicenters of these outbreaks. Our study quantifies the dynamics of a major European HPAIV pandemic and substantiates the ability of phylodynamic models to improve molecular surveillance of novel AIVs. [ABSTRACT FROM AUTHOR]

This study assesses the relation between hypothesized risk factors and African swine fever virus (ASFV) distribution in Sardinia (Italy) after the beginning of the eradication program in 1993, using a Bayesian multivariable logistic regression mixed model. Results indicate that the probability of ASFV occurrence in Sardinia was associated to particular socio-cultural, productive and economical factors found in the region, particularly to large number of confined (i.e., closed) farms (most of them backyard), high road density, high mean altitude, large number of open fattening farms, and large number of pigs per commune. Conversely, large proportion of open farms with at least one census and large proportion of open farms per commune, were found to be protective factors for ASFV. Results suggest that basic preventive and control strategies, such as yearly census or registration of the pigs per farm and better control of the public lands where pigs are usually raised, together with endanced effords of outreach and communication with pig producers should help in the success of the eradication program for ASF in the Island. Methods and results presented here will inform decision making to better control and eradicate ASF in Sardinia and in all those areas with similar management and epidemiological conditions. [ABSTRACT FROM AUTHOR]

OBJECTIVE To measure incidence and estimate temporal and spatial dynamics of porcine reproductive and respiratory syndrome virus (PRRSV) infection in US sow herds. ANIMALS 371 sow herds in the United States from 14 production companies. PROCEDURES The exponentially weighted moving average was used to monitor incident PRRSV infections for onset of an epidemic. The spatial scan statistic was used to identify areas at significantly high risk of PRRS epidemics. A %2 test was used to estimate whether there were significant differences in the quarterly and annual PRRS incidence among time periods, and a bivariable logistic regression model was used to estimate whether PRRSV infection during a given year increased the odds of that herd being infected in the following year. RESULTS During the 4-year period of this study, 29% (91/319; 2009 to 2010), 33% (106/325; 2010 to 2011), 38% (135/355; 2011 to 2012), and 32% (117/371; 2012 to 2013) of the herds reported new infections. Weekly incidence was low during spring and summer and high during fall and winter. The exponentially weighted moving average signaled the onset of a PRRSV epidemic during the middle 2 weeks of October each year. Disease incidence was spatially clustered. Infection in the previous year increased the odds of infection in 2010 to 2011 and 2011 to 2012. CONCLUSIONS AND CLINICAL RELEVANCE Results indicated a striking repeatability in annual PRRSV temporal and spatial patterns across 4 years of data among herds from 14 production companies, which suggested that efforts to control PRRSV at a regional level should continue to be supported. [ABSTRACT FROM AUTHOR]

Objective--To characterize the temporal and spatial distribution and reproductive ratio of vesicular stomatitis (VS) outbreaks reported in Mexico in 2008. Animals--Bovine herds in Mexico in which VS outbreaks were officially reported and confirmed from January 1 through December 31, 2008. Procedures--The Poisson model of the space-time scan statistic was used to identify periods and geographical locations at highest risk for VS in Mexico in 2008. The herd reproductive ratio (Rh) of the epidemic was computed by use of the doubling-time method. Results--1 significant space-time cluster of VS was detected in the state of Michoacan from September 4 through December 10, 2008. The temporal extent of the VS outbreaks and the value and pattern of decrease of the Rh were different in the endemic zone of Tabasco and Chiapas, compared with findings in the region included in the space-time cluster. Conclusions and Clinical Relevance--The large number of VS outbreaks reported in Mexico in 2008 was associated with the spread of the disease from the endemic zone in southern Mexico to areas sporadically affected by the disease. Results suggested that implementation of a surveillance system in the endemic zone of Mexico aimed at early detection of changes in the value of Rh and space-time clustering of the disease could help predict occurrence of future VS outbreaks originating from this endemic zone. This information will help prevent VS spread into regions of Mexico and neighboring countries that are only sporadically affected by the disease. [ABSTRACT FROM AUTHOR]

Objective--To estimate the time of seroconversion to the New Jersey serotype of vesicular stomatitis virus (VSNJV) in sentinel cattle of dairy herds located at high and low elevations in southern Mexico and to determine the factors associated with an increase in VSNJV transmission. Animals--471 dairy cattle in 4 free-ranging dairy herds located at high and low elevations in southern Mexico. Procedures--Serum samples from all cattle were screened by use of serum neutralization (SN) tests for antibodies against VSNJV. Cattle with SN titers < 1:20 were designated as sentinel cattle and tested every 10 weeks for seroconversion to VSNJV (SN titer > 1:80). A Cox proportional hazards regression model was used to compare the hazard for seroconversion between sentinel cattle located at high and low elevations and kept under similar management and nutritional conditions. Results--Hazard of VSNJV seroconversion was significantly higher for sentinel cattle located at high elevations, compared with the hazard for sentinel cattle located at low elevations. Dairy cattle located at high elevations seroconverted to VSNJV more frequently during the rainy season and the beginning of the dry season. Conclusions and Clinical Relevance--Seroconversion to VSNJV was more likely in dairy cattle in southern Mexico located at high elevations than in dairy cattle located at low elevations, These findings should contribute to understanding the dynamics of VSNJV infection in endemic areas and should be useful in the design of effective preventive and control strategies to decrease the impact of future VSV incursions. [ABSTRACT FROM AUTHOR]

Endemic foot and mouth disease (FMD) in East African cattle systems is one factor that limits access to export markets. The probability of FMD transmission associated with export from such systems have never been quantified and there is a need for data and analyses to guide strategies for livestock exports from regions where FMD remains endemic. The probability of infection among animals at slaughter is an important contributor to the risk of FMD transmission associated with the final beef product. In this study, we built a stochastic model to estimate the probability that beef cattle reach slaughter while infected with FMD virus for four production systems in two East African countries (Kenya and Uganda). Input values were derived from the primary literature and expert opinion. We found that the risk that FMD-infected animals reach slaughter under current conditions is high in both countries (median annual probability ranging from 0.05 among cattle from Kenyan feedlots to 0.62 from Ugandan semi-intensive systems). Cattle originating from feedlot and ranching systems in Kenya had the lowest overall probabilities of the eight systems evaluated. The final probabilities among cattle from all systems were sensitive to the likelihood of acquiring new infections en route to slaughter and especially the probability and extent of commingling with other cattle. These results give insight into factors that could be leveraged by potential interventions to lower the probability of FMD among beef cattle at slaughter. Such interventions should be evaluated considering the cost, logistics, and tradeoffs of each, ultimately guiding resource investment that is grounded in the values and capacity of each country. [ABSTRACT FROM AUTHOR]

Objective--To estimate when foot-and-mouth disease virus (FMDV) would first be detected in bulk tank milk of dairies after exposure to FMDV. Sample Population--Hypothetical dairy herds milking 100, 500, or 1,000 cows. Procedures--For each day after herd exposure to FMDV, infection, milk yield, and virolactia were simulated for individual cows with low and high rates of intraherd transmission to estimate when a PCR assay would detect virus in bulk tank milk. Detection limits were based on assumptions for the number of virus genomes per milliliter of milk and for analytical sensitivity of a PCR assay. Results--A mean of 10% of the cows was predicted to have FMD lesions from 7 to 8 days and from 13.5 to 15 days after herd exposure for herds with high and low intraherd transmission rates, respectively. Herd bulk milk volume decreased by 10% by 8.5 to 9.5 days and by 15 to 16.5 days after herd exposure for herds with high and low transmission rates, respectively. Mean times by which FMDV would be first detected in bulk milk were 2.5 days and 6.5 to 8 days after herd exposure, which were extended for 10 to 11 days and 17 to 18 days for herds with high and low transmission rates, respectively. Conclusions and Clinical Relevance--PCR screening of bulk milk for FMDV would likely detect FMDV in dairy herds several days sooner than might be expected for owner reporting of clinical signs and thus should be worthy of consideration for regional, national, or global FMD surveillance. [ABSTRACT FROM AUTHOR]