Poor management of dog populations causes many problems in different countries, including rabies. To strategically design a dog population management, certain sets of data are required, such as the population size and spatial distribution of dogs. However, these data are rarely available or incomplete. Hence, this study aimed to describe the characteristics of dog populations in Thailand, explore their spatial distribution and relevant factors, and estimate the number of dogs in the whole country. First, four districts were selected as representatives of each region. Each district was partitioned into grids with a 300-m resolution. The selected grids were then surveyed, and the number of dogs and related data were collected. Random forest models with a two-part approach were used to quantify the association between the surveyed dog population and predictor variables. The spatial distribution of dog populations was then predicted. A total of 1,750 grids were surveyed (945 grids with dog presence and 805 grids with dog absence). Among the surveyed dogs, 86.6% (12,027/13,895) were owned. Of these, 51% were classified as independent, followed by confined (25%), semi-independent (21%), and unidentified dogs (3%). Seventy-two percent (1,348/1,868) of the ownerless dogs were feral, and the rest were community dogs. The spatial pattern of the dog populations was highly distributed in big cities such as Bangkok and its suburbs. In owned dogs, it was linked to household demographics, whereas it was related to community factors in ownerless dogs. The number of estimated dogs in the entire country was 12.8 million heads including 11.2 million owned dogs (21.7 heads/km2) and 1.6 million ownerless dogs (3.2 heads/km2). The methods developed here are extrapolatable to a larger area and use much less budget and manpower compared to the present practices. Our results are helpful for canine rabies prevention and control programs, such as dog population management and control and rabies vaccine allocation.

Foot and mouth disease (FMD) is endemic in Nepal and significantly impacts the livelihood of farmers, national economy, and trade of Nepal. However, outbreak investigations are not frequently conducted, and there have been limited studies to understand the associated risk factors. A case-control study was performed in dairy cattle farms of Shankharapur and Kageshwari Municipalities, Kathmandu from March to April 2020 to describe the outbreak and identify the risk factors associated with FMD. There were 31 case farms, while 62 farms were selected as control farms (1:2). The information from case and control farms was collected by semi-structured questionnaire survey through field visits and observations. The univariable and multivariable logistic regressions were performed. The farm-level prevalence of FMD was 25.2% (n=31/123). Among the FMD affected farms, the proportion of positive farms in Shankharapur (61.3% (19/31)) was significantly higher than Kageshwori (38.7% (12/31)). The final multivariable logistic regression analysis identified four variables: cattle purchased within 14 days (OR=12.9; CI=2.4-69.5), milk market distance less than two kilometers from the farm (OR=32.7; CI=5.8-186.3), sharing of the bull from other farms for natural insemination (OR=5.7; CI=1.2-26.8), and no vaccination against FMD in the past six months (OR=19.1; CI=2.0-186.2) as significant risk factors for the occurrence of FMD. This study suggests farmers vaccinate their dairy cattle with FMD vaccine as per the vaccination schedule suggested by the veterinarians, practice quarantine measures when new animals are introduced to their farms, practice biosecurity measures in their farms, and do not use bulls from areas where there are ongoing FMD outbreaks.

Background/Aim To explore the prevalence of Varroa destructor and Tropilaelaps infestation in honeybees in Thailand and investigate factors associated with those diseases. Methods A quantitative cross-sectional design was employed during 2017–2018. We sampled 144 apiaries in 13 provinces from the surveillance database of the Department of Livestock Development. In total, 1,152 bee samples were collected. A microscopic exam was performed to assess if each sample was infested with Varroa destructor mites and tropilaelaps mites. A chi-square test and multivariable logistic regression were conducted. Results The prevalence of Varroa destructor and Tropilaelaps infestation at the apiary level was 50.69% and 32.64%, respectively. At the beehive level, we found that the prevalence of Varroa destructor infestation was 22.74% while that of Tropilaelaps infestation was 6.94%. The northern region saw the highest prevalence of Varroa destructor and Tropilaelaps infestation. Apiaries that received a “Good Agricultural Practice” (GAP) certificate from the Bureau of Livestock Standards and Certification, demonstrated a 42% lower chance of contracting both parasitic infestations; however, no statistically significant difference was reported. Apiaries that had a history of chemical use showed approximately 2.7 times greater odds of Tropilaelaps infestation (adjusted odds ratio [AOR] = 2.69; 95% confidence interval [CI] = 1.16–6.21) with statistical significance (p = 0.02). The probability of Varroa destructor infestation amongst apiaries with apiary movement was approximately 60% lower than amongst those without apiary movement (AOR = 0.40, 95% CI = 0.20–0.80, p = 0.01). Conclusion Varroa destructor and Tropilaelaps infestations are a critical concern for beekeeping in Thailand. Apiary movement tended to lower the risk of Varroa destructor infestation while chemical use tended to enhance the risk of Tropilaelaps infestation. Further studies that allow a more comprehensive collection of determinants of parasitic infestation in honeybees, for instance, apiary cleaning frequency and farm environments (such as temperature and rainfall), are recommended.