Socioeconomic determinants of small and medium-sized dairy farms in the Ecuador-Colombia border area.

The socioeconomic factors influencing small-scale dairy producers in the border area between Ecuador and Colombia were meticulously identified. Employing a non-experimental design, the study leveraged multivariate statistical analysis to discern key determinants. Data processing was executed using the statistical software SPSS v27, facilitating comprehensive analysis. A random survey was administered to 532 small and medium-scale dairy producers in the Carchi province of Ecuador, employing a structured questionnaire supplemented with a Likert scale for nuanced insights. Based on 35 original variables, seven determining factors were identified in dairy farms: political representation, adequate housing, equipment, innovation, empathy, profitability, social welfare, which combined explain 60.95% of the system's variability. Such factors affect production, the level of household income, as well as their effect on the standard of living of households. Three groups were formed, the first with a low perception of economic development (Traditionalists 33.3%); the second with a better expectation of economic development (Modernizers 27.6%); and the third, identified with greater economic development (Innovators 10.3%). Each group presents cases with a low to high standard of living perspective. The groups have peculiarities in terms of their performance that can be applied to the entire population. A significant relation was established between socioeconomic factors and standard of living.

Psychosocial factors play a central role in determining SNAP utilization for farm workforce.

Introduction: Federal food safety net programs, like the Supplemental Nutrition Assistance Program (SNAP), may not reach vulnerable populations like rural residents, immigrants, and Latinx individuals. Because these groups are overrepresented among the farm workforce, exploring SNAP utilization among farm communities may clarify the role it plays in alleviating food insecurity. Methods: In-depth interviews were conducted with 31 farmworkers and farm owners. Patterns and predictors of SNAP utilization were organized using an adapted Andersen Behavioral Model of Health Service Utilization. Results: Psychosocial factors played the central role in participants' use of SNAP. Discussion: Opportunities to improve the design and delivery of SNAP include expanded eligibility cut-offs and targeted engagement mechanisms.

Seasonal Patterns of Injury Characteristics Among Farmers and Ranchers in the U.S. Central States.

OBJECTIVE: In high-risk agricultural environments, tasks, weather, and work conditions vary throughout the year. Also, injuries peak during certain periods. The primary objective of this study was to examine operator- and farm-level characteristics as risk factors for injuries within each of the four seasons. The secondary objective was to examine seasonal differences in the incident location and primary cause of these injuries. METHOD: We analyzed data from the 2018 and 2020 Farm and Ranch Health and Safety Surveys (FRHSS), conducted in seven U.S. states by the Central States Center for Agricultural Safety and Health (CS-CASH), which were collected using a stratified random sampling approach to ensure representativeness. The survey data were merged with operation-level data from the Farm Market iD database. We employed Generalized Estimating Equations (GEE) to examine the association of seasonal injuries with individual and operation-level characteristics. The chi-square test of independence was used to assess the association between injury incident location and season, as well as injury cause and season. Pairwise Z-tests of proportions were conducted to evaluate the differences in the proportions of injuries due to specific combinations of injury location and cause across each pair of seasons. RESULTS: Surveys conducted in 2018 and 2020 yielded a combined response rate of 15.9%, with 5,428 responses and 7,915 unique operators. Of these, 903 operators reported at least one injury during the past 12 months. Seasonally, most injuries occurred in spring (34.2%), followed by summer (24.7%). Male operators had higher injury odds in the spring (adjusted OR = 1.42) and summer (aOR = 2.41). Those managing both a farm and a ranch reported increased injury risks in winter (aOR = 1.73) and spring (aOR = 1.48). Operators in cow-calf operations faced higher springtime injury risks (aOR = 1.45). High stress and exhaustion were consistent risk factors across all seasons. The highest proportion of injury incidents occurred in the farmyard (43.6%), and livestock were the most common cause of injury (24.9%). CONCLUSION: Results highlight the need for season-specific prevention and intervention strategies, considering farmers' and ranchers' risk characteristics, injury locations, and causes. These findings can inform targeted measures for high-risk populations at optimal times and locations.

Calf mortality in Turkish dairy farms: Economic impact, regional disparities, and farm-level drivers.

This study investigates the economic burden of calf mortality in Turkish dairy farms and its impact on the national economy. We gathered research data by directly surveying dairy farms in seven provinces, each representing a distinct region of Turkiye. By conducting these surveys, we captured data on various aspects of calf mortality, including losses among non-pregnant cows aged two and older, pregnant cows, and those experiencing complications during birth, as well as losses within the 0-6 month age bracket. These figures were then amalgamated to establish the overall calf loss rate. Using a fractional probit model, we examined the empirical relationship between total calf loss rates and the socio-demographic characteristics of farm operators and their establishments. Our findings revealed that approximately 82 % of farms experienced some degree of calf loss, with the calf loss rate among dairy cattle farming accounting for nearly 20 %. Notably, regional disparities emerged as a key observation, alongside the identification of certain socio-demographic farm characteristics that proved statistically significant. Specifically, factors such as the prevalence of local cattle breeds, the proportion of crossbred bulls, as well as the numbers of heifers and calves, stood out as influential. Further scrutiny, fortified by ANOVA tests and relationships between the number of cows and total calf loss rate, underscored pronounced geographical disparities in post-estimation calf loss rates. Meanwhile, correlation heatmaps illuminated noteworthy relationships between specific cattle traits and the extent of calf losses. These findings not only underscore the severity of the issue but also highlight the urgency of preventive measures. In light of these insights, we offer pertinent policy recommendations to stakeholders and policymakers aimed at mitigating this considerable economic burden effectively.

Emergency Medical Service Transport Time in Rural Farm and Non-Farm Pediatric Trauma.

OBJECTIVES: Pediatric farm injuries tend to be more severe and have poorer outcomes compared to injuries sustained in non-farm settings. Timely emergency medical service (EMS) response and transport to definitive care is crucial for optimizing outcomes for trauma patients. We aimed to determine if pediatric farm injuries were associated with longer EMS response and transport times compared to pediatric non-farm injuries in rural communities. METHODS: The 2021 National EMS Information System (NEMSIS) database was used to identify rural EMS activations where injured pediatric patients who were transported to a hospital. Median transport times for farm and non-farm injuries, as well as other components of prehospital time and use of air EMS transport, were compared between injuries on farms and injuries in non-farm rural settings. RESULTS: The analytic sample included 22,248 rural EMS activations for pediatric injuries, of which 156 (1%) were for pediatric farm injuries. For non-farm and farm injuries, the median transport times were 20 minutes and 28 minutes, respectively. Median total prehospital time was 50 minutes compared to 62 minutes, and 9.8% of patients with non-farm injuries versus 20.5% of those with farm injuries were transported to a hospital by air EMS units. After multivariable adjustment, farm vs. non-farm injury location was associated with a 4 minute increase in EMS transport time, but no difference in initial EMS response time, EMS time on scene, or use of air EMS units. CONCLUSION: Among children sustaining an injury that resulted in rural EMS activation, farm injuries were associated with prolonged transport time compared to non-farm injuries, which may contribute to worse in-hospital outcomes described to pediatric farm injuries in prior research.

Assessing the impact of socio-demographics and farming activity on ward-level mortality patterns using farm and population decennial censuses.

INTRODUCTION AND OBJECTIVE: Farmers experience a specific set of unique dangers, which increases their risk of mortality compared with any other occupation. This study hypothesised that Northern Ireland's (NIs) agriculturally saturated Wards have a higher risk of mortality compared against non-agriculturally based Wards. DESIGN: The Population Census and Farm Census information were downloaded from the Northern Ireland Neighbourhood Service (NINIS) online depository to compile three mortality-based data sets (2001, 2011, pooled data sets). Assessing the impact of socio-demographics and farming activity on Ward-level mortality patterns using farm and population decennial censuses. This study analysed all 582 Ward areas of NI, which enclosed the entire populace of the country in 2001 and 2011. FINDINGS: Path analysis was utilised to examine direct and indirect paths linked with mortality within two census years (2001; 2011), alongside testing pathways for invariance between census years (pooled data set). Ward-level results provided evidence for exogenous variables to mortality operating through three/four endogenous variables via: (i) direct effects (age), (ii) summed indirect effects (age; males; living alone; farming profit; and deprivation) and (iii) total effects (age; males; living alone; and deprivation). Multi-group results cross-validated these cause-and-effect relationships relating to mortality. DISCUSSION AND CONCLUSION: This study demonstrated that farming intensity scores, farming profits and socio-demographics' influence on mortality risk in a Ward were dependent on the specific social-environmental characteristics within that area. In line with earlier area level research, results support the aggregated interpretation that higher levels of farming activity within a Ward increase the risk of mortality within those Wards of NI. This was an essential study to enable future tailoring of new strategies and upgrading of current policies to bring about significant mortality risk change at local level.

Emergency presentations for farm-related injuries in older adults residing in south-western Victoria, Australia.

INTRODUCTION: Farm workers are at high risk for injuries, and epidemiological data are needed to plan resource allocation. OBJECTIVE: This study identified regions with high farm-related injury rates in the Barwon South West region of Victoria, Australia, for residents aged ≥50 yr. DESIGN: Retrospective synthesis using electronic medical records of emergency presentations occurring during 2017-2019 inclusive for Local Government Areas (LGA) in the study region. For each LGA, age-standardised incidence rates (per 1000 population/year) were calculated. FINDINGS: For men and women combined, there were 31 218 emergency presentations for any injury, and 1150 (3.68%) of these were farm-related. The overall age-standardised rate for farm-related injury presentations was 2.6 (95% CI 2.4-2.7); men had a higher rate than women (4.1, 95% CI 3.9-4.4 versus 1.2, 95% CI 1.0-1.3, respectively). For individual LGAs, the highest rates of farm-related emergency presentations occurred in Moyne and Southern Grampians, both rural LGAs. Approximately two-thirds of farm-related injuries occurred during work activities (65.0%), and most individuals arrived at the hospital by transport classified as "other" (including private car, 83.3%). There were also several common injury causes identified: "other animal related injury" (20.2%), "cutting, piercing object" (19.5%), "fall ⟨1 m" (13.1%), and "struck by or collision with object" (12.5%). Few injuries were caused by machinery (1.7%) and these occurred mainly in the LGA of Moyne (65%). DISCUSSION AND CONCLUSION: This study provides data to inform future research and resource allocation for the prevention of farm-related injuries.

Summary of Roadway Incidents Involving Farm Equipment in Five Midwestern States Using the Fatality Analysis Reporting System (FARS).

Roadway incidents involving farm equipment is a growing area of concern among agricultural safety and health and public health professionals. The aim of this project was to evaluate the usefulness of the Fatality Analysis Reporting System (FARS) and analyze the number of roadway fatal incidents that involve farm equipment. Data collected from the FARS through the National Highway Traffic Safety Administration was used to summarize roadway incidents involving farm equipment. Cases from five midwestern states were analyzed from January to December 2020 using SPSS. Incidents involving farm equipment resulted in 25 cases with Iowa, Michigan, and Wisconsin all reporting six cases each. The most common manner of incidents were single-vehicle crashes and rear-ending incidents. Most of the events occurred during busy agricultural seasons, most often occurring in June and August with five cases each. The FARS dataset is a useful tool to identify cases, but it faces limitations, such as only reporting fatalities and lack of information on specific farm equipment involved in incidents. The results from the study are helpful to better understand roadway incidents and guide future intervention strategies.

Ageing threatens sustainability of smallholder farming in China.

Rapid demographic ageing substantially affects socioeconomic development1-4 and presents considerable challenges for food security and agricultural sustainability5-8, which have so far not been well understood. Here, by using data from more than 15,000 rural households with crops but no livestock across China, we show that rural population ageing reduced farm size by 4% through transferring cropland ownership and land abandonment (approximately 4 million hectares) in 2019, taking the population age structure in 1990 as a benchmark. These changes led to a reduction of agricultural inputs, including chemical fertilizers, manure and machinery, which decreased agricultural output and labour productivity by 5% and 4%, respectively, further lowering farmers' income by 15%. Meanwhile, fertilizer loss increased by 3%, resulting in higher pollutant emissions to the environment. In new farming models, such as cooperative farming, farms tend to be larger and operated by younger farmers, who have a higher average education level, hence improving agricultural management. By encouraging the transition to new farming models, the negative consequences of ageing can be reversed. Agricultural input, farm size and farmer's income would grow by approximately 14%, 20% and 26%, respectively, and fertilizer loss would reduce by 4% in 2100 compared with that in 2020. This suggests that management of rural ageing will contribute to a comprehensive transformation of smallholder farming to sustainable agriculture in China.

Fatal Animal Related Incidents on Australian Farms - a 20-Year Review.

Objectives To assess demographic and causal factors of fatal farm incidents involving animals in Australia. Methods Descriptive study of the National Coronial Information System for persons fatally injured by an animal on an Australian farm over the 2001-20 period. Data were analysed in relation to age, sex, state where incident occurred, work-relatedness and causal agents. Results There has been little change in the mean number of animal-related injury deaths across Australia in the 2001-20 period (mean 6.5), however this is a 35% reduction on an earlier 1989-92 assessment (mean 10). The majority of incidents (81%) involved horses (n = 75) and cattle (n = 31). Males were involved in 86 (66%) cases, with 54 female cases. People aged 60 years and over accounted for 46% of the cases, with more than half occurring during work. Of the decedents, 85% fell from or were struck by an animal at the time of the incident, with 40% resulting in a head injury. Conclusion While annualized case numbers have decreased slightly, the leading agents remain consistent with previous studies. The lack of genuine progress in addressing fatalities related to horses and cattle, along with the representation of older persons in the cohort, require attention drawing on the Hierarchy of Controls.

IOT-Based Medical Informatics Farming System with Predictive Data Analytics Using Supervised Machine Learning Algorithms.

In the farming industry, the Internet of Things (IoT) is crucial for boosting utility. Innovative agriculture practices and medical informatics have the potential to increase crop yield while using the same amount of input. Individuals can benefit from the Internet of Things in various ways. The intelligent farms require the creation of an IoT-based infrastructure based on sensors, actuators, embedded systems, and a network connection. The agriculture sector will gain new advantages from machine learning and IoT data analytics in terms of improving crop output quantity and quality to fulfill rising food demand. This paper described an intelligent medical informatics farming system with predictive data analytics on sensing parameters, utilizing a supervised machine learning approach in an intelligent agricultural system. The four essential components of the proposed approach are the cloud layer, fog layer, edge layer, and sensor layer. The primary goal is to enhance production and provide organic farming by adjusting farming conditions as per plant needs that are considered in experimentation. The use of machine learning on acquired sensor data from a prototype embedded model is investigated for regulating the actuators in the system. Then, an analytics and decision-making system was built at the fog layer, employing two supervised machine learning approaches including classification and regression algorithms using a support vector machine (SVM) and artificial neural network (ANN) for effective computation over the cloud layer. The experimental results are evaluated and analyzed in MATLAB software, and it is found that the classification accuracy using SVM is much better as compared to ANN and other state of art methods.

Repeated cross-sectional sampling of pigs at slaughter indicates varying age of hepatitis E virus infection within and between pig farms.

Humans can become infected with hepatitis E virus (HEV) by consumption of undercooked pork. To reduce the burden of HEV in humans, mitigation on pig farms is needed. HEV is found on most pig farms globally, yet within-farm seroprevalence estimates vary considerably. Understanding of the underlying variation in infection dynamics within and between farms currently lacks. Therefore, we investigated HEV infection dynamics by sampling 1711 batches of slaughter pigs from 208 Dutch farms over an 8-month period. Four farm types, conventional, organic, and two types with strict focus on biosecurity, were included. Sera were tested individually with an anti-HEV antibody ELISA and pooled per batch with PCR. All farms delivered seropositive pigs to slaughter, yet batches (resembling farm compartments) had varying results. By combining PCR and ELISA results, infection moment and extent per batch could be classified as low transmission, early, intermediate or late. Cluster analysis of batch infection moments per farm resulted in four clusters with distinct infection patterns. Cluster 1 farms delivered almost exclusively PCR negative, ELISA positive batches to slaughter (PCR-ELISA+), indicating relatively early age of HEV infection. Cluster 2 and 3 farms delivered 0.3 and 0.7 of batches with intermediate infection moment (PCR+ELISA+) respectively and only few batches with early infection. Cluster 4 farms delivered low transmission (PCR-ELISA-) and late infection (PCR+ELISA-) batches, demonstrating that those farms can prevent or delay HEV transmission to farm compartments. Farm type partly coincided with cluster assignment, indicating that biosecurity and management are related to age of HEV infection.

A Survey of Chinese Pig Farms and Human Healthcare Isolates Reveals Separate Human and Animal Methicillin-Resistant Staphylococcus aureus Populations.

There has been increasing concern that the overuse of antibiotics in livestock farming is contributing to the burden of antimicrobial resistance in people. Farmed animals in Europe and North America, particularly pigs, provide a reservoir for livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA ST398 lineage) found in people. This study is designed to investigate the contribution of MRSA from Chinese pig farms to human infection. A collection of 483 MRSA are isolated from 55 farms and 4 hospitals in central China, a high pig farming density area. CC9 MRSA accounts for 97.2% of all farm isolates, but is not present in hospital isolates. ST398 isolates are found on farms and hospitals, but none of them formed part of the "LA-MRSA ST398 lineage" present in Europe and North America. The hospital ST398 MRSA isolate form a clade that is clearly separate from the farm ST398 isolates. Despite the presence of high levels of MRSA found on Chinese pig farms, the authors find no evidence of them spilling over to the human population. Nevertheless, the ST398 MRSA obtained from hospitals appear to be part of a widely distributed lineage in China. The new animal-adapted ST398 lineage that has emerged in China is of concern.

Prevalence of Bovine Rotavirus and Coronavirus in Neonatal Calves in Dairy Farms of Addis Ababa, Ethiopia: Preliminary Study.

BACKGROUND: Bovine rotavirus (BRV) and bovine coronavirus (BCoV) are the most common viral agents in neonatal calf diarrhea and result in serious economic consequences. The aim of the study was to determine the epidemiology of those viruses in randomly selected dairy farms of Addis Ababa. METHODS: A cross-sectional study was conducted from November 2018 to April 2019 using a probability proportional to size (PPS) sampling technique. A total of 110 calves, less than 30 days of age, from 57 dairy herds were involved in the study. Associated factors of herds and calves were collected using semistructured interviews from farm owners and through physical observation of selected calves. Fecal samples were collected and analyzed using the sandwich ELISA method. Data generated from both semistructured interviews and laboratory investigation were analyzed using STATA_MP version 15. RESULTS: From the total 110 calves, 42 (38.18%) had diarrhea during the survey. The prevalence of bovine rotavirus and coronavirus was 3.64% (4/110) and 0.91% (1/110), respectively. Diarrhea, feeding colostrum timing, and sex of the neonatal calves had statistically significant association with bovine rotavirus infection (p < 0.05). All rotavirus-positive neonatal calves were identified in small scale dairy farms and in dairy farms that reported mortality though they lack statistically significant association. Only one coronavirus case was detected among the neonatal calves. The case was identified among small scale herds and in a herd with diarrheal cases. The sex of the coronavirus calf was female, diarrheic, and among 11-20 days old. CONCLUSION: The prevalence of rotavirus and coronavirus infections in neonatal calves was seldom in dairy farms of the study area. Rotavirus was more common than coronavirus, and further studies should be initiated on other (infectious and noninfectious) causes of neonatal calf diarrhea in the area.

Occurrence of the Colistin Resistance Gene mcr-1 and Additional Antibiotic Resistance Genes in ESBL/AmpC-Producing Escherichia coli from Poultry in Lebanon: A Nationwide Survey.

The objective of the present study was to determine genomic characteristics of expanded-spectrum cephalosporin (ESC)-resistant Escherichia coli spreading in healthy broilers in Lebanon in 2018. Rectal swabs (n = 280) from 56 farms were screened for the presence of ESC-resistant E. coli isolates. Antimicrobial susceptibility and extended-spectrum ß-lactamase (ESBL)/AmpC production were determined by the disk diffusion method. Whole-genome sequencing (WGS) of 102 representative isolates of E. coli was performed to determine their phylogenetic diversity, serotypes, sequence types (ST), acquired resistance genes, and virulence-associated genes. Fifty-two out of 56 farms housed broilers carrying ESC-resistant E. coli isolates. These farms had large and recurrent antimicrobial practices, using, for some of them, critically important antibiotics for prophylactic and therapeutic purposes. Among the 102 sequenced multidrug-resistant (MDR) E. coli isolates, the proportion of ESBL, plasmid-mediated AmpC ß-lactamase (pAmpC) producers, and ESBL/pAmpC coproducers was 60%, 27.6%, and 12.4%, respectively. The most prevalent ESBL/pAmpC genes were blaCMY-2, blaCTX-M-3, blaCTX-M-15, blaCTX-M-27, and blaCTX-M-14b (n = 42, n = 31, n =15, n = 9, and n = 7, respectively). These ESBL/pAmpC producers were distributed in different STs, most being well-known avian-associated and sometimes pathogenic STs (ST-10, ST-48, ST-93, ST-115, ST-117, and ST-457). Phylogenetic single nucleotide polymorphism (SNP) analysis confirmed their genetic diversity and wide dispersion across the Lebanese territory. Most isolates were also resistant to ciprofloxacin (101/102 with 3 QRDR mutations), and 19/102 isolates from 11 unrelated STs also carried the mobile resistance gene mcr-1. This survey illustrates the alarming prevalence of MDR E. coli resistant to medically important antibiotics in broilers in Lebanon. This advocates the need for surveillance programs of antimicrobial resistance in Lebanon and the reduction of excessive use of antibiotics to limit the spread of MDR E. coli in food-producing animals. IMPORTANCE Poultry production is a main contributor of the global trend of antimicrobial resistance arising from food-producing animals worldwide. In Lebanon, inappropriate use of antibiotics is frequent in chickens for prophylactic reasons and to improve productivity, resulting in an alarming prevalence of extended-spectrum ß-lactamase (ESBL)/AmpC-producing Escherichia coli, also resistant to other medically important antibiotics (i.e., colistin and ciprofloxacin). Their complex genomic epidemiology highlighted by an important genetic diversity suggests that these resistance determinants are largely spreading in enteric bacteria in Lebanese poultry. Further molecular surveillance is needed to understand the country-specific epidemiology of ESBL/AmpC and mcr-1 genes in Lebanese poultry production. In addition, decisive interventions are urgently needed in order to ban the use of critically important antibiotics for human medicine in food-producing animals and limit the spread of antibiotic resistance in Lebanon.

Occurrence and aetiology of subclinical mastitis in water buffalo in Bangladesh.

Subclinical mastitis (SCM) in water buffalo is a production disease associated with decreased milk yield and impaired milk quality and safety. Water buffalo is an important livestock species in Bangladesh, but information about the occurrence and aetiology of SCM in this species is scarce. A cross-sectional study was conducted as part of the Udder Health Bangladesh Programme to (i) determine the occurrence of SCM and bulk milk somatic cell count (SCC) in water buffalo in Bangladesh, (ii) identify pathogens causing SCM and (iii) evaluate penicillin resistance in isolated staphylococci strains. Sixteen buffalo farms in the Bagerhat and Noakhali regions of Bangladesh were selected for study and a bulk milk sample was collected from each farm. In addition, 299 udder quarter milk samples were collected from 76 animals. The bulk milk samples were assessed by direct SCC and the quarter milk samples by California mastitis test (CMT). The occurrence of SCM calculated at quarter and animal level was 42.5 and 81.6%, respectively. Milk samples from 108 CMT-positive quarters in 48 animals and 38 randomly selected CMT-negative quarters in 24 animals were investigated using bacteriological culture. Estimated mean bulk milk SCC was 195 000 cells/ml milk (range 47 000- 587 000 cells/ml milk). On culture, estimated quarter-level intramammary infection (IMI) was 40.4%. The identity of isolated bacteria was confirmed by MALDI-TOF mass spectrometry. Non-aureus staphylococci (NAS) were the most common pathogens (24.7%) and, among 36 NAS tested, 36.1% were resistant to penicillin. Thus there was high occurrence of SCM on the study farms, with relatively high penicillin resistance in NAS. Further studies are needed to identify underlying risk factors and develop an udder health control strategy for water buffalo in Bangladesh.

A Mortality-Based Description of EHDV and BTV Prevalence in Farmed White-Tailed Deer (Odocoileus virginianus) in Florida, USA.

Hemorrhagic disease (HD) caused by bluetongue virus (BTV) and epizootic hemorrhagic disease virus (EHDV) is the most important viral disease of farmed and wild white-tailed deer (WTD; Odocoileus virginianus) and can cause substantial mortality in susceptible hosts. Captive cervid farming is an emerging industry in Florida, an HD-enzootic region. Morbidity and mortality due to HD are major concerns among deer farmers, but the impact of HD on Florida's cervid farming industry is unknown. Our primary objective was to determine the prevalence of epizootic hemorrhagic disease virus (EHDV) and bluetongue virus (BTV) among WTD submitted to the University of Florida Institute of Food and Agricultural Sciences Cervidae Health Research Initiative (CHeRI) for post-mortem diagnostics. Our secondary objectives were to identify the predominant circulating EHDV serotypes during each sampling year and to determine the age class with the greatest proportion of EHDV- and BTV-positive post-mortem specimens. From 2016 to 2020, spleen samples from 539 farmed WTD with unexplained mortality were tested for the presence of EHDV and BTV by RT-qPCR. Overall, the prevalence of EHDV, BTV, or EHDV/BTV coinfection was 26%, 16%, and 10%, respectively, and 44% of deer (237/539) were diagnosed with HD by RT-qPCR. The predominant circulating EHDV serotype varied by year. Overall, EHDV-2 was the most commonly identified serotype (55% of PCR-positive cases), and EHDV-1 was the least frequently identified serotype (16% of PCR-positive cases). The greatest proportion of EHDV/BTV positives among mortality cases was observed in young WTD aged 3-6 months (50%-82% positive). There was a significant difference in the prevalence of EHDV/BTV by age when comparing specimens from WTD over 1 year old (p = 0.029, n = 527). Among these samples, the number of reported mortalities and the prevalence of EHDV/BTV were highest in yearling animals (56%). These data provide the first estimate of EHDV and BTV prevalence and virus serotypes among farmed WTD in Florida, identify the WTD age groups with the greatest proportions of EHDV- and BTV-positive specimens, and suggest that HD caused by these two viruses may be a major source of mortality challenging the captive cervid farming industry in Florida.

Women's empowerment in agriculture and productivity change: The case of Bangladesh rice farms.

Using productivity change as a measure of farm economic performance, we analyze the relationship between women's empowerment in agriculture and farm productivity change and its components, which include efficiency change, technological change, and scale efficiency change. A non-parametric Malmquist approach is used to measure farm specific productivity change and its decomposition. We use a bootstrap regression to analyze factors that cause differences in productivity change and its components, testing, in particular, the role women's empowerment plays. The empirical application focuses on a sample of Bangladesh rice farms over the crop cultivation period 2011 and 2014. Results suggest that improvements in women's empowerment in agriculture were associated with higher levels of productivity change, efficiency change, and technical change, while they had no impact on scale efficiency change. We find that empowering women, specifically, improving their ability to make independent choices regarding agricultural production had a statistically significant positive association with productivity change, efficiency change, and technical change. We also find that lowering the gender parity gap is positively related with improving productivity of the sample farms.

Chronic Wasting Disease Transmission Risk Assessment for Farmed Cervids in Minnesota and Wisconsin.

CWD (chronic wasting disease) has emerged as one of the most important diseases of cervids and continues to adversely affect farmed and wild cervid populations, despite control and preventive measures. This study aims to use the current scientific understanding of CWD transmission and knowledge of farmed cervid operations to conduct a qualitative risk assessment for CWD transmission to cervid farms and, applying this risk assessment, systematically describe the CWD transmission risks experienced by CWD-positive farmed cervid operations in Minnesota and Wisconsin. A systematic review of literature related to CWD transmission informed our criteria to stratify CWD transmission risks to cervid operations into high-risk low uncertainty, moderate-risk high uncertainty, and negligible-risk low uncertainty categories. Case data from 34 CWD-positive farmed cervid operations in Minnesota and Wisconsin from 2002 to January 2019 were categorized by transmission risks exposure and evaluated for trends. The majority of case farms recorded high transmission risks (56%), which were likely sources of CWD, but many (44%) had only moderate or negligible transmission risks, including most of the herds (62%) detected since 2012. The presence of CWD-positive cervid farms with only moderate or low CWD transmission risks necessitates further investigation of these risks to inform effective control measures.