Collective activities of the Thai Coordinating Unit for One Health (CUOH): Past activities and future directions.

In Thailand, One Health concepts have been implemented among government agencies, academic institutions, intergovernment, and civil society organizations. The Thai Coordinating Unit for One Health (CUOH) was established as a collaborating body for One Health-related activities in the country in 2014. To better understand what activities CUOH has completed thus far and to assess future activities, we conducted a network analysis to identify and visualize linkages between organizations and activities from 2015 to 2021. Activities were divided into four categories: organizing meetings, developing products, providing funds, and managing resources. Most of the 114 CUOH-managed meeting participants were representatives from 72 government and 20 academic institutions. The Thai Ministry of Public Health's Department of Disease Control participated in 148 meetings, the highest attendance among all organizations working with CUOH. The first CUOH guideline or manual was published in 2020, and 11 were published in 2021. In funding management, the CUOH worked with 25 organizations to carry out 71 projects from 2015 to 2021. Additionally, the CUOH played an important role in allocating COVID-19 vaccines during the COVID-19 pandemic. The CUOH has connected organizations working in different health sectors to collaborate jointly through meetings and projects that use a One Health approach, which can holistically improve health management in Thailand. Diverse funding sources are needed to ensure the sustainability of the unit in the future.

A network analysis of the local pig supply chain in a repeated outbreak area of human streptococcosis in Thailand.

AIMS: The present study employed a network analysis approach to scrutinize a pig supply chain in a repeated outbreak province for human streptococcosis in Thailand and identified important actors that should be focused on for tailoring appropriate interventions. METHODS AND RESULTS: Nakhon Sawan province was chosen as the study site as the cases of human streptococcosis have been consecutively reported since 2014, with the number of cases ranging from 21 to 63. A questionnaire survey was used to collect data from actors along the pig supply chain, including pig farms, slaughterhouses, pork sellers, restaurants and customers. A one-mode-directed network was then constructed. Degree and betweenness centrality values were measured. We found that the supply chain of pork products comprised 314 nodes and 296 directed ties. A retailer got the highest overall degree, out-degree and betweenness centrality values at 35, 34, and 65.3, respectively. For in-degree centrality, the highest was identified in a customer at 9. Interestingly, this customer bought pork products from nine different mobile groceries. CONCLUSIONS: Both public health and veterinary authorities should extend their surveillance activities to cover all actors in the supply chain to strengthen overall disease prevention and control for streptococcosis.

An overlooked poultry trade network of the smallholder farms in the border provinces of Thailand, 2021: implications for avian influenza surveillance.

Introduction: In Thailand, community-level poultry trade is conducted on a small-scale involving farmers and traders with many trade networks. Understanding the poultry movements may help identify different activities that farmers and traders might contribute to the spread of avian influenza. Methods: This study aimed to describe the characteristics of players involved in the poultry trade network at the northeastern border of Thailand using network analysis approaches. Mukdahan and Nakhon Phanom provinces, which border Laos, and Ubon Ratchathani province, which borders both Laos and Cambodia, were selected as survey sites. Results: Local veterinary officers identified and interviewed 338 poultry farmers and eight poultry traders in 2021. A weighted directed network identified incoming and outgoing movements of where the subdistricts traded chickens. Ninety-nine subdistricts and 181 trade links were captured. A self-looping (trader and consumer in the same subdistrict) feedback was found in 56 of 99 subdistricts. The median distance of the movements was 14.02 km (interquartile range (IQR): 6.04-102.74 km), with a maximum of 823.08 km. Most subdistricts in the network had few poultry trade connections, with a median of 1. They typically connected to 1-5 other subdistricts, most often receiving poultry from 1 to 2.5 subdistricts, and sending to 1-2 subdistricts. The subdistricts with the highest overall and in-degree centrality were located in Mukdahan province, whereas one with the highest out-degree centrality was found in Nakhon Phanom province. Discussion: The poultry movement pattern observed in this network helps explain how avian influenza could spread over the networks once introduced.

Prevalence and characterization of antimicrobial-resistant Escherichia coli isolated from veterinary staff, pets, and pet owners in Thailand.

BACKGROUND: Companion animals may act as antimicrobial resistance (AMR) reservoirs. This study investigated the prevalence and AMR patterns of Escherichia coli in pets and people in close contact with pets. METHODS: A total of 955 samples were collected from veterinary clinics across Thailand by rectal and skin or ear swabs from dogs and cats and fecal swabs from veterinarians, veterinary assistants, and pet owners. The minimum inhibitory concentrations (MICs) of the obtained isolates were investigated using Sensititre™ MIC plates against 21 different antimicrobial drugs. RESULTS: Escherichia coli from pets was frequently resistant to ampicillin (100%) and amoxicillin-clavulanic acid (100%), whereas E. coli from pet owners, veterinarians, and veterinary assistants was mostly resistant to tetracycline. The multiple antibiotic resistance index revealed that multidrug-resistant E. coli isolates were frequently found in dogs (34.92%), cats (62.12%), veterinarians (61.11%), veterinarian assistants (36.36%), and pet owners (47.62%). The most common AMR genes identified in this study were blaCTX-M, blaTEM, tetA, and tetB, which were associated with the antimicrobial susceptibility results. Additionally, extended-spectrum beta-lactamase (ESBL)-associated genes (i.e., blaCTX-M, blaTEM, and blaSHV) were found in 21.69%, 71.97%, 27.78%, and 21.43% of E. coli isolated from dogs, cats, veterinarians, and pet owners, respectively. CONCLUSIONS: Our findings demonstrated the presence of AMR genes, particularly ESBL-associated genes, in E. coli isolated from healthy pets and veterinarians. This implies that these sources of E. coli could potentially be reservoirs for antibiotic resistance, thereby increasing the risk of harm to both humans and animals. These findings highlight the importance of implementing effective AMR control measures in veterinary practices, as bacteria resistant to commonly used antimicrobials are present in humans and animals.

Stakeholder attitudes and perspectives on wildlife disease surveillance as a component of a One Health approach in Thailand.

Coordinated wildlife disease surveillance (WDS) can help professionals across disciplines effectively safeguard human, animal, and environmental health. The aims of this study were to understand how WDS in Thailand is utilized, valued, and can be improved within a One Health framework. An online questionnaire was distributed to 183 professionals (55.7% response rate) across Thailand working in wildlife, marine animal, livestock, domestic animal, zoo animal, environmental, and public health sectors. Twelve semi-structured interviews with key professionals were then performed. Three-quarters of survey respondents reported using WDS data and information. Sectors agreed upon ranking disease control (76.5% of respondents) as the most beneficial outcome of WDS, while fostering new ideas through collaboration was valued by few participants (2.0%). Accessing data collected by one's own sector was identified as the most challenging (50%) yet least difficult to improve (88.3%). Having legal authority to conduct WDS was the second most frequently identified challenge. Interviewees explained that legal documentation required for cross-institutional collaborations posed a barrier to efficient communication and use of human resources. Survey respondents identified allocation of human resources (75.5%), adequate budget (71.6%), and having a clear communication system between sectors (71.6%) as highest priority areas for improvement to WDS in Thailand. Authorization from administrative officials and support from local community members were identified as challenges during in-person interviews. Future outreach may be directed toward these groups. As 42.9% of marine health professionals had difficulty knowing whom to contact in other sectors and 28.4% of survey respondents indicated that communication with marine health professionals was not applicable to their work, connecting the marine sector with other sectors may be prioritized. This study identifies priorities for addressing current challenges in the establishment of a general WDS system and information management system in Thailand while presenting a model for such evaluation in other regions.

Identifying high-risk areas for dog-mediated rabies using Bayesian spatial regression.

Despite ongoing control efforts, rabies remains an endemic zoonotic disease in many countries. Determining high-risk areas and the space-time patterns of rabies spread, as it relates to epidemiologically important factors, can support policymakers and program managers alike to develop evidence-based targeted surveillance and control programs. In this One Health approach which selected Thailand as the example site, the location-based risk of contracting dog-mediated rabies by both human and animal populations was quantified using a Bayesian spatial regression model. Specifically, a conditional autoregressive (CAR) Bayesian zero-inflated Poisson (ZIP) regression was fitted to the reported human and animal rabies case counts of each district, from the 2012-2017 period. The human population was used as an offset. The epidemiologically important factors hypothesized as risk modifiers and therefore tested as predictors included: number of dog bites/attacks, the population of dogs and cats, number of Buddhist temples, garbage dumps, animal vaccination, post-exposure prophylaxis, poverty, and shared administrative borders. Disparate sources of data were used to improve the estimated associations and predictions. Model performance was assessed using cross-validation. Results suggested that accounting for the association between human and animal rabies with number of dog bites/attacks, number of owned and un-owned dogs; shared country borders, number of Buddhist temples, poverty levels, and accounting for spatial dependence between districts, may help to predict the risk districts for dog-mediated rabies in Thailand. The fitted values of the spatial regression were mapped to illustrate the risk of dog-mediated rabies. The cross-validation indicated an adequate performance of the spatial regression model (AUC = 0.81), suggesting that had this spatial regression approach been used to identify districts at risk in 2015, the cases reported in 2016/17 would have been predicted with model sensitivity and specificity of 0.71 and 0.80, respectively. While active surveillance is ideal, this approach of using multiple data sources to improve risk estimation may inform current rabies surveillance and control efforts including determining rabies-free zones, and the roll-out of human post-exposure prophylaxis and anti-rabies vaccines for animals in determining high-risk areas.

Modeling of the combined dynamics of leptospirosis transmission and seroconversion in herds.

Leptospirosis is a zoonotic disease-causing illness in both humans and animals resulting in related economic impacts due to production loss as well as prevention and control efforts. Several mathematical models have been proposed to study the dynamics of infection but none of them has so far taken into account the dynamics of seroconversion. In this study, we have developed a general framework, based on the kinetic model for animal leptospirosis, that combines both the antibody (exposure marker) and infection dynamics to simultaneously follows both seroconversion and infection status of leptospirosis in a herd population. It is a stochastic compartmental model (for transition rates) with time delay (for seroconversion) which describes the progression of infection by a SEIRS (susceptible, exposed, infected, removed and susceptible) approach and seroconversion by four-state antibody kinetics (antibody negative and three antibody positive states of different antibody levels). The model shows that it is possible to assess and follow both seroconversion and infection status through the prism of diagnostic testing. Such an approach of combined kinetics could prove very useful to assist the competent authorities in their analyzes of epidemic situations and in the implementation of strategies for controlling and managing the associated risks.

Competitive evolution of H1N1 and H3N2 influenza viruses in the United States: A mathematical modeling study.

Seasonal influenza causes vast public health and economic impact globally. The prevention and control of the annual epidemics remain a challenge due to the antigenic evolution of the viruses. Here, we presented a novel modeling framework based on changes in amino acid sequences and relevant epidemiological data to retrospectively investigate the competitive evolution and transmission of H1N1 and H3N2 influenza viruses in the United States during October 2002 and April 2019. To do so, we estimated the time-varying disease transmission rate from the reported influenza cases and the time-varying antigenic change rate of the viruses from the changes in amino acid sequences. By incorporating the time-varying antigenic change rate into the transmission models, we found that the models could capture the evolutionary transmission dynamics of influenza viruses in the United States. Our modeling results also showed that the antigenic change of the virus plays an essential role in seasonal influenza dynamics.

Dynamic Models of Within-Herd Transmission and Recommendation for Vaccination Coverage Requirement in the Case of African Swine Fever in Vietnam.

African swine fever (ASF) is a highly contagious disease that is caused by the ASF virus (ASFV) with a high fatality rate in domestic pigs resulting in a high socio-economic impact. The pig business in Vietnam was recently affected by ASF for the first time. This study thus aimed to develop a disease dynamic model to explain how ASFV spreads in Vietnamese pig populations and suggest a protective vaccine coverage level required to prevent future outbreaks. The outbreak data were collected from ten private small-scale farms within the first wave of ASF outbreaks in Vietnam. Three methods were used to estimate the basic reproduction number (R0), including the exponential growth method, maximum likelihood method, and attack rate method. The average R0 values were estimated at 1.49 (95%CI: 1.05-2.21), 1.58 (95%CI: 0.92-2.56), and 1.46 (95%CI: 1.38-1.57), respectively. Based on the worst-case scenario, all pigs in a herd would be infected and removed within 50 days. We suggest vaccinating at least 80% of pigs on each farm once a commercially approved ASF vaccine is available. However, an improvement in biosecurity levels in small-scale farms is still greatly encouraged to prevent the introduction of the virus.

Emerging infectious diseases may spread across pig trade networks in Thailand once introduced: a network analysis approach.

In Thailand, pork is one of the most consumed meats nationwide. Pig farming is hence an important business in the country. However, 95% of the farms were considered smallholders raising only 50 pigs or less. With limited budgets and resources, the biosecurity level in these farms is relatively low. Pig movements have been previously identified as a risk factor in the spread of infectious diseases. Therefore, the present study aimed to explicitly analyze the pig movement network structure and assess its vulnerability to the spread of emerging diseases in Thailand. We used official electronic records of nationwide pig movements throughout the year 2021 to construct a directed weighted one-mode network. Degree centrality, degree distribution, connected components, network community, and modularity were measured to explore the network architectures and properties. In this network, 484,483 pig movements were captured. In which, 379,948 (78.42%) were moved toward slaughterhouses and hence excluded from further analyses. From the remaining links, we suggested that the pig movement network in Thailand was vulnerable to the spread of emerging infectious diseases. Within the network, we found a strongly connected component (SCC) connecting 1044 subdistricts (38.6% of the nodes), a giant weakly connected component (GWCC) covering 98.2% of the nodes (2654/2704), and inter-regional communities with overall network modularity of 0.68. The disease may rapidly spread throughout the country. A better understanding of the nationwide pig movement networks is helpful in tailoring control interventions to cope with the newly emerged diseases once introduced.

The effects of geographical distributions of buildings and roads on the spatiotemporal spread of canine rabies: An individual-based modeling study.

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.

A Cutoff Determination of Real-Time Loop-Mediated Isothermal Amplification (LAMP) for End-Point Detection of Campylobacter jejuni in Chicken Meat.

Campylobacter jejuni is one of the leading causes of foodborne illness worldwide. C. jejuni is commonly found in poultry. It is the most frequent cause of contamination and thus resulting in not only public health concerns but also economic impacts. To test for this bacterial contamination in food processing plants, this study attempted to employ a simple and rapid detection assay called loop-mediated isothermal amplification (LAMP). The best cutoff value for the positive determination of C. jejuni calculated using real-time LAMP quantification cycle (Cq) was derived from the receiver operating characteristic (ROC) curve modeling. The model showed an area under curve (AUC) of 0.936 (95% Wald CI: 0.903-0.970). Based on Youden's J statistic, the optimal cutoff value which had the highest sensitivity and specificity from the model was calculated as 18.07. The LAMP assay had 96.9% sensitivity, 95.8% specificity, and 93.9 and 97.9% positive and negative predictive values, respectively, compared to a standard culture approach for C. jejuni identification. Among all non-C. jejuni strains, the LAMP assay gave each of 12.5% false-positive results to C. coli and E. coli (1 out of 8 samples). The assay can detect C. jejuni at the lowest concentration of 103 CFU/mL. Our results suggest a preliminary indicator for the application of end-point LAMP assays, such as turbidity and UV fluorescence tests, to detect C. jejuni in field operations. The LAMP assay is an alternative screening test for C. jejuni contamination in food samples. The method provides a rapid detection, which requires only 9 min with a cutoff value of Cq. We performed the extraction of DNA from pure cultures and the detection of C. jejuni using the LAMP assay within 3 h. However, we were not able to reduce the time for the process of enrichment involved in our study. Therefore, we suggest that alternative enrichment media and rapid DNA extraction methods should be considered for further study. Compared to other traditional methods, our proposed assay requires less equipment and time, which is applicable at any processing steps in the food production chain.

Current characteristics of animal rabies cases in Thailand and relevant risk factors identified by a spatial modeling approach.

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.

The Impact of Socioeconomic Factors on Knowledge, Attitudes, and Practices of Dog Owners on Dog Rabies Control in Thailand.

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.

Identification of Escherichia coli and Related Enterobacteriaceae and Examination of Their Phenotypic Antimicrobial Resistance Patterns: A Pilot Study at A Wildlife-Livestock Interface in Lusaka, Zambia.

A cross-sectional study was used to identify and assess prevalence and phenotypic antimicrobial resistance (AMR) profiles of Escherichia coli and other enterobacteria isolated from healthy wildlife and livestock cohabiting at a 10,000 acres game ranch near Lusaka, Zambia. Purposive sampling was used to select wildlife and livestock based on similarities in behavior, grazing habits and close interactions with humans. Isolates (n = 66) from fecal samples collected between April and August 2018 (n = 84) were examined following modified protocols for bacteria isolation, biochemical identification, molecular detection, phylogenetic analysis, and antimicrobial susceptibility testing by disc diffusion method. Data were analyzed using R software, Genetyx ver.12 and Mega 6. Using Applied Profile Index 20E kit for biochemical identification, polymerase chain reaction assay and sequencing, sixty-six isolates were identified to species level, of which Escherichia coli (72.7%, 48/66), E. fergusonii (1.5%, 1/66), Shigella sonnei (22.7%, 14/66), Sh. flexinerri (1.5%, 1/66) and Enterobacteriaceae bacterium (1.5%, 1/66), and their relationships were illustrated in a phylogenetic tree. Phenotypic antimicrobial resistance or intermediate sensitivity expression to at least one antimicrobial agent was detected in 89.6% of the E. coli, and 73.3% of the Shigella isolates. The E. coli isolates exhibited the highest resistance rates to ampicillin (27%), ceftazidime (14.3%), cefotaxime (9.5%), and kanamycin (9.5%). Multidrug resistance (MDR) was detected in 18.8% of E. coli isolates while only 13.3% Shigella isolates showed MDR. The MDR was detected among isolates from impala and ostrich (wild animals in which no antimicrobial treatment was used), and in isolates from cattle, pigs, and goats (domesticated animals). This study indicates the possible transmission of drug-resistant microorganisms between animals cohabiting at the wildlife-livestock interface. It emphasizes the need for further investigation of the role of wildlife in the development and transmission of AMR, which is an issue of global concern.

Effects of COVID-19 government travel restrictions on mobility in a rural border area of Northern Thailand: A mobile phone tracking study.

BACKGROUND: Thailand is among the top five countries with effective COVID-19 transmission control. This study examines how news of presence of COVID-19 in Thailand, as well as varying levels of government restriction on movement, affected human mobility in a rural Thai population along the border with Myanmar. METHODS: This study makes use of mobility data collected using a smartphone app. Between November 2019 and June 2020, four major events concerning information dissemination or government intervention give rise to five time intervals of analysis. Radius of gyration is used to analyze movement in each interval, and movement during government-imposed curfew. Human mobility network visualization is used to identify changes in travel patterns between main geographic locations of activity. Cross-border mobility analysis highlights potential for intervillage and intercountry disease transmission. RESULTS: Inter-village and cross-border movement was common in the pre-COVID-19 period. Radius of gyration and cross-border trips decreased following news of the first imported cases. During the government lockdown period, radius of gyration was reduced by more than 90% and cross-border movement was mostly limited to short-distance trips. Human mobility was nearly back to normal after relaxation of the lockdown. CONCLUSIONS: This study provides insight into the impact of the government lockdown policy on an area with extremely low socio-economic status, poor healthcare resources, and highly active cross-border movement. The lockdown had a great impact on reducing individual mobility, including cross-border movement. The quick return to normal mobility after relaxation of the lockdown implies that close monitoring of disease should be continued to prevent a second wave.

The effects of flooding and weather conditions on leptospirosis transmission in Thailand.

The epidemic of leptospirosis in humans occurs annually in Thailand. In this study, we have developed mathematical models to investigate transmission dynamics between humans, animals, and a contaminated environment. We compared different leptospire transmission models involving flooding and weather conditions, shedding and multiplication rate in a contaminated environment. We found that the model in which the transmission rate depends on both flooding and temperature, best-fits the reported human data on leptospirosis in Thailand. Our results indicate that flooding strongly contributes to disease transmission, where a high degree of flooding leads to a higher number of infected individuals. Sensitivity analysis showed that the transmission rate of leptospires from a contaminated environment was the most important parameter for the total number of human cases. Our results suggest that public education should target people who work in contaminated environments to prevent Leptospira infections.

Spatial Distribution and Population Estimation of Dogs in Thailand: Implications for Rabies Prevention and Control.

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.

The Spread of Rabies Among Dogs in Pranburi District, Thailand: A Metapopulation Modeling Approach.

Rabies, a deadly zoonotic disease, is causing serious public health problems worldwide. Dogs are considered the main reservoir for rabies infection in humans. A better understanding of the dissemination of rabies in the dog population is crucial. The present study, therefore, aimed to explore the subpopulation of dogs roaming around rabies-outbreak areas and the model of its possible spread. We used a Cross-K function to investigate the spatial clustering between the locations of dog rabies cases and the feeding points of a stray dog feeder. We then observed the social interaction of dogs in a community using a metapopulation analysis and further simulated the possible spread of rabies within this population. We found that the reported rabies cases were spatially clustered with the routes of the dog feeder. Therefore, more sustainable stray dog management is required. Based on our community dog observations, we found 20 groups comprising 222 dogs with an average of 11 dogs per group. In our infectious model, we suggested that 47.7% of dogs are likely to be infected in a year if no interventions are implemented. Therefore, the veterinary authorities should rigorously strengthen their rabies prevention and control strategies to protect both animal and human health.