The situation of human rabies in Thailand has gradually declined over the past four decades. However, the number of animal rabies cases has slightly increased in the last ten years. This study thus aimed to describe the characteristics of animal rabies between 2017 and 2018 in Thailand in which the prevalence was fairly high and to quantify the association between monthly rabies occurrences and explainable variables using the generalized additive models (GAMs) to predict the spatial risk areas for rabies spread. Our results indicate that the majority of animals affected by rabies in Thailand are dogs. Most of the affected dogs were owned, free or semi-free roaming, and unvaccinated. Clusters of rabies were highly distributed in the northeast, followed by the central and the south of the country. Temporally, the number of cases gradually increased after June and reached a peak in January. Based on our spatial models, human and cattle population density as well as the spatio-temporal history of rabies occurrences, and the distances from the cases to the secondary roads and country borders are identified as the risk factors. Our predictive maps are applicable for strengthening the surveillance system in high-risk areas. Nevertheless, the identified risk factors should be rigorously considered and integrated into the strategic plans for the prevention and control of animal rabies in Thailand.

SummaryEffectiveness of current passive zoonotic disease surveillance systems is limited by the under-reporting of disease outbreaks in the domestic animal population. Evaluating the acceptability of passive surveillance and its economic, social and cultural determinants appears a critical step for improving it. A participatory rural appraisal was implemented in a rural subdistrict of Thailand. Focus group interviews were used to identify sanitary risks perceived by native chicken farmers and describe the structure of their value chain. Qualitative individual interviews with a large diversity of actors enabled to identify perceived costs and benefits associated with the reporting of HPAI suspicions to sanitary authorities. Besides, flows of information on HPAI suspected cases were assessed using network analysis, based on data collected through individual questionnaires. Results show that the presence of cockfighting activities in the area negatively affected the willingness of all chicken farmers and other actors to report suspected HPAI cases. The high financial and affective value of fighting cocks contradicted the HPAI control policy based on mass culling. However, the importance of product quality in the native chicken meat value chain and the free veterinary services and products delivered by veterinary officers had a positive impact on suspected case reporting. Besides, cockfighting practitioners had a significantly higher centrality than other actors in the information network and they facilitated the spatial diffusion of information. Social ties built in cockfighting activities and the shared purpose of protecting valuable cocks were at the basis of the diffusion of information and the informal collective management of diseases. Building bridges with this informal network would greatly improve the effectiveness of passive surveillance.

No abstract

Rabies is a fatal disease that has been a serious health concern, especially in developing countries. Although rabies is preventable by vaccination, the spread still occurs sporadically in many countries, including Thailand. Geographical structures, habitats, and behaviors of host populations are essential factors that may result in an enormous impact on the mechanism of propagation and persistence of the disease. To investigate the role of geographical structures on the transmission dynamics of canine rabies, we developed a stochastic individual-based model that integrates the exact configuration of buildings and roads. In our model, the spatial distribution of dogs was estimated based on the distribution of buildings, with roads considered to facilitate dog movement. Two contrasting areas with high- and low-risk of rabies transmission in Thailand, namely, Hatyai and Tepha districts, were chosen as study sites. Our modeling results indicated that the distinct geographical structures of buildings and roads in Hatyai and Tepha could contribute to the difference in the rabies transmission dynamics in these two areas. The high density of buildings and roads in Hatyai could facilitate more rabies transmission. We also investigated the impacts of rabies intervention, including reducing the dog population, restricting owned dog movement, and dog vaccination on the spread of canine rabies in these two areas. We found that reducing the dog population alone might not be sufficient for preventing rabies transmission in the high-risk area. Owned dog confinement could reduce more the likelihood of rabies transmission. Finally, a higher vaccination coverage may be required for controlling rabies transmission in the high-risk area compared to the low-risk area.