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Introduction: Rabies, a deadly zoonotic viral disease, accounts for over 50,000 fatalities globally each year. This disease predominantly plagues developing nations, with Thailand being no exception. In the current global landscape, concerted efforts are being mobilized to curb human mortalities attributed to animal-transmitted rabies. For strategic allocation and optimization of resources, sophisticated and accurate forecasting of rabies incidents is imperative. This research aims to determine temporal patterns, and seasonal fluctuations, and project the incidence of canine rabies throughout Thailand, using various time series techniques. Methods: Monthly total laboratory-confirmed rabies cases data from January 2013 to December 2022 (full dataset) were split into the training dataset (January 2013 to December 2021) and the test dataset (January to December 2022). Time series models including Seasonal Autoregressive Integrated Moving Average (SARIMA), Neural Network Autoregression (NNAR), Error Trend Seasonality (ETS), the Trigonometric Exponential Smoothing State-Space Model with Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS), and Seasonal and Trend Decomposition using Loess (STL) were used to analyze the training dataset and the full dataset. The forecast values obtained from the time series models applied to the training dataset were compared with the actual values from the test dataset to determine their predictive performance. Furthermore, the forecast projections from January 2023 to December 2025 were generated from models applied to the full dataset. Results: The findings revealed a total of 4,678 confirmed canine rabies cases during the study duration, with apparent seasonality in the data. Among the models tested with the test dataset, TBATS exhibited superior predictive accuracy, closely trailed by the SARIMA model. Based on the full dataset, TBATS projections suggest an annual average of approximately 285 canine rabies cases for the years 2023 to 2025, translating to a monthly average of 23 cases (range: 18-30). In contrast, SARIMA projections averaged 277 cases annually (range: 208-214). Discussion: This research offers a new perspective on disease forecasting through advanced time series methodologies. The results should be taken into consideration when planning and conducting rabies surveillance, prevention, and control activities.
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Rabies is a deadly zoonotic disease responsible for almost 60,000 deaths each year, especially in Africa and Asia including Thailand. Dogs are the major reservoirs for rabies virus in these settings. This study thus used the concept of knowledge, attitudes, and practices (KAP) to identify socioeconomic factors that contribute to the differences in the canine rabies occurrences in high and low-risk areas which were classified by a Generalized Additive Model (GAM). Multistage sampling was then applied to designate the study locations and a KAP-based questionnaire was used to retrieve data and relevant perspectives from the respondents. Based on the responses from 476 participants living across four regions of Thailand, we found that the knowledge of the participants was positively correlated with their behaviors but negatively associated with the attitudes. Participants who are male, younger, educated at the level of middle to high school, or raising more dogs are likely to have negative attitudes but good knowledge on rabies prevention and control whereas farmers with lower income had better attitudes regardless of their knowledge. We found that people in a lower socioeconomic status with a lack of knowledge are not willing to pay at a higher vaccine price. Public education is a key to change dog owners' behaviors. Related authorities should constantly educate people on how to prevent and control rabies in their communities. Our findings should be applicable to other countries with similar socioeconomic statuses.
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(1) Background: Thailand has made significant progress in reducing the number of human and animal rabies cases. However, control and elimination of the last remaining pockets of dog-mediated rabies have shown to be burdensome, predominantly as a result of the large numbers of free-roaming dogs without an owner that cannot be restrained without special efforts and therefore remain unvaccinated. To reach these dogs, the feasibility, and benefits of oral rabies vaccination (ORV) as a complementary tool has been examined under field conditions. (2) Methods: ORV of dogs was tested in five study areas of four provinces in Thailand. In these areas, sites with free-roaming dogs were identified with the support of local municipal workers and dog caretakers. ORV teams visited each of five study areas and distributed rabies vaccine (SPBN GASGAS) in three bait formats that were offered to the dogs using a hand-out and retrieval model. The three bait types tested included: egg-flavored baits, egg-flavored baits pasted with commercially available cat liquid snack, and boiled-intestine baits. A dog offered a vaccine bait was considered vaccinated when the discarded sachet was perforated or if a dog chewed vaccine bait at least 5 times before it swallowed the bait, including the sachet. (3) Results: A total of 2444 free-roaming dogs considered inaccessible for parenteral vaccination were identified at 338 sites. As not all dogs were approachable, 79.0% were offered a bait; of these dogs, 91.6% accepted the bait and subsequently 83.0% were considered successfully vaccinated. (4) Conclusion: Overall, 65.6% of the free-roaming dogs at these sites were successfully vaccinated by the oral route. Such a significant increase of the vaccination coverage of the free-roaming dog population could interrupt the rabies transmission cycle and offers a unique opportunity to reach the goal to eliminate dog-mediated human rabies in Thailand by 2030.
