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Curriculum mapping provides a systematic approach for analyzing the conformity of an educational program with a given set of standards. The Chiang Mai University Faculty of Veterinary Medicine and the University of Minnesota College of Veterinary Medicine joined together in an educational twinning project to map their Doctor of Veterinary Medicine curricula against core competencies identified by the World Organisation for Animal Health (OIE) as critically important for Day 1 veterinary graduates to meet the needs for global public good services. Details of curriculum coverage for each specific and advanced competency were collected through a review of syllabi and course descriptions, followed by in-depth interviews of key faculty members. The depth of coverage of each competency was estimated by the tabulating the number of hours assigned. The teaching methods and levels of learning were also captured. While the overall design of the curricula conformed to the OIE Guidelines for Veterinary Education Core Curricula, the mapping process identified variability in the depth and breadth of coverage on individual competencies. Coverage of the Day 1 Specific Competencies was greater early in the curricula. More gaps existed in terms of the Advanced Competencies than the specific core competencies. Discussion of the identified gaps with faculty members led to opportunities for strengthening the curricula by adjustments of individual courses throughout the curricula. Documentation of teaching methods also led to professional development of new pedagogical skills and redesign of the teaching methods for particular subjects.
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Educación en Veterinaria , Animales , Curriculum , Docentes , Salud Global , Humanos , AprendizajeRESUMEN
Campylobacter jejuni (C. jejuni), a foodborne pathogen, poses notable hazards to human health and has significant economic implications for poultry production. This study aimed to assess C. jejuni contamination levels in chicken carcasses from both backyard and commercial slaughterhouses in Chiang Mai province, Thailand. It also sought to examine the effects of different slaughtering practices on contamination levels and to offer evidence-based recommendations for reducing C. jejuni contamination. Through the sampling of 105 chicken carcasses and subsequent enumeration of C. jejuni, the study captured the impact of various slaughtering practices. Utilizing k-modes clustering on the observational and bacterial count data, the research identified distinct patterns of contamination, revealing higher levels in backyard operations compared to commercial ones. The application of k-modes clustering highlighted the impact of critical slaughtering practices, particularly chilling, on contamination levels. Notably, samples with the lowest bacterial counts were typically from the chilling step, a practice predominantly found in commercial facilities. This observation underpins the recommendation for backyard slaughterhouses to incorporate ice in their post-evisceration soaking process. Mimicking commercial practices, this chilling method aims to inhibit C. jejuni growth by reducing carcass temperature, thereby enhancing food safety. Furthermore, the study suggests backyard operations adopt additional measures observed in commercial settings, like segregating equipment for each slaughtering step and implementing regular cleaning protocols. These strategic interventions are pivotal in reducing contamination risks, advancing microbiological safety in poultry processing, and aligning with global food safety enhancement efforts.
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Introduction: Thailand experienced a nationwide outbreak of lumpy skin disease (LSD) in 2021, highlighting the need for effective prevention and control strategies. This study aimed to identify herd-level risk factors associated with LSD outbreaks in beef cattle herds across different regions of Thailand. Methods: A case-control study was conducted in upper northeastern, northeastern, and central regions, where face-to-face interviews were conducted with farmers using a semi-structured questionnaire. Univariable and multivariable mixed effect logistic regression analyses were employed to determine the factors associated with LSD outbreaks. A total of 489 beef herds, including 161 LSD outbreak herds and 328 non-LSD herds, were investigated. Results and discussion: Results showed that 66% of farmers have operated beef herds for more than five years. There were very few animal movements during the outbreak period. None of the cattle had been vaccinated with LSD vaccines. Insects that have the potential to act as vectors for LSD were observed in all herds. Thirty-four percent of farmers have implemented insect control measures. The final mixed effect logistic regression model identified herds operating for more than five years (odds ratio [OR]: 1.62, 95% confidence interval [CI]: 1.04-2.53) and the absence of insect control management on the herd (OR: 2.05, 95% CI: 1.29-3.25) to be associated with LSD outbreaks. The implementation of insect-vector control measures in areas at risk of LSD, especially for herds without vaccination against the disease, should be emphasized. This study provides the first report on risk factors for LSD outbreaks in naïve cattle herds in Thailand and offers useful information for the development of LSD prevention and control programs within the country's context.
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Introduction: In 2021, Thailand reported the highest incidence of lumpy skin disease (LSD) outbreaks in Asia. In response to the widespread outbreaks in cattle herds, the government's livestock authorities initiated comprehensive intervention measures, encompassing control strategies and a national vaccination program. Yet, the efficacy of these interventions remained unevaluated. This research sought to assess the nationwide intervention's impact on the incidence of new LSD cases through causal impact analysis. Methods: Data on weekly new LSD cases in Thailand from March to September 2021 was analyzed. The Bayesian structural time series (BSTS) analysis was employed to evaluate the causal relationship between new LSD cases in the pre-intervention phase (prior to the vaccination campaign) and the post-intervention phase (following the vaccination campaign). The assessment involved two distinct scenarios, each determined by the estimated effective intervention dates. In both scenarios, a consistent decline in new LSD cases was observed after the mass vaccination initiative, while other control measures such as the restriction of animal movement, insect control, and the enhancement of the active surveillance approach remained operational throughout the pre-intervention and the post-intervention phases. Results and discussion: According to the relative effect results obtained from scenario A and B, it was observed that the incidence of LSD cases exhibited reductions of 119% (95% Credible interval [CrI]: -121%, -38%) and 78% (95% CrI: -126, -41%), respectively. The BSTS results underscored the significant influence of these interventions, with a Bayesian one-sided tail-area probability of p < 0.05. This model-based study provides insight into the application of BSTS in evaluating the impact of nationwide LSD vaccination based on the national-level data. The present study is groundbreaking in two respects: it is the first study to quantify the causal effects of a mass vaccination intervention on the LSD outbreak in Thailand, and it stands as the only endeavor of its kind in the Asian context. The insights collected from this study hold potential value for policymakers in Thailand and other countries at risk of LSD outbreaks.
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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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The unfavorable effects of global climate change, which are mostly the result of human activities, have had a particularly negative effect on human health and the planet's ecosystems. This study attempted to determine the seasonality and association of air pollution, in addition to climate conditions, with two respiratory infections, influenza and pneumonia, in Chiang Mai, Thailand, which has been considered the most polluted city on Earth during the hot season. We used a seasonal-trend decomposition procedure based on loess regression (STL) and a seasonal cycle subseries (SCS) plot to determine the seasonality of the two diseases. In addition, multivariable negative binomial regression (NBR) models were used to assess the association between the diseases and environmental variables (temperature, precipitation, relative humidity, PM2.5, and PM10). The data revealed that influenza had a clear seasonal pattern during the cold months of January and February, whereas the incidence of pneumonia showed a weak seasonal pattern. In terms of forecasting, the preceding month's PM2.5 and temperature (lag1) had a significant association with influenza incidence, while the previous month's temperature and relative humidity influenced pneumonia. Using air pollutants as an indication of respiratory disease, our models indicated that PM2.5 lag1 was correlated with the incidence of influenza, but not pneumonia. However, there was a linear association between PM10 and both diseases. This research will help in allocating clinical and public health resources in response to potential environmental changes and forecasting the future dynamics of influenza and pneumonia in the region due to air pollution.
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The COVID-19 pandemic affected the food supply chain, retailers, and consumers owing to infection awareness. This study evaluated the impacts COVID-19 on ASF retailers' businesses and consumers' livelihoods, as well as their knowledge toward the disease, attitudes, and food safety practices to prevent infections. The study includes a cross-sectional component that was conducted in urban/peri-urban (U/PU) and rural areas in Chiang Mai province. In another part of the study, a structured questionnaire was developed for animal source food (ASF) retailers and consumers, with three primary parts for data analysis: general information, COVID-19 impacts, and knowledge, attitudes, and practices (KAP) assessment. Data corresponding to three periods of interest (before the COVID-19 outbreak, during partial lockdown, and present) were gathered and analyzed. In this study, 155 retailers and 150 consumers participated, of which the majority of the respondents were female (70.3% and 82.7%, respectively) with average ages of 47.4 and 44.9 years, respectively. The most noticeable effect of COVID-19 was a decline in income for retailers and consumers. The KAP scores of consumers in both areas were not significantly different, whereas the retailer attitudes toward COVID-19 prevention and food safety practices scored more highly in rural areas than in U/PU. During the partial lockdown, food safety practices significantly improved relative to the time preceding the outbreak, and these practices have remained constant to the present day. The results revealed that gender, age group, business type, and type of ASF retailers were associated with the KAP of the retailers, whereas gender, age group, education, number of family members, and occupation were associated with the KAP of the consumers. Our findings provide in-depth information about the effects of COVID-19 on ASF retailers and consumers, as well as their KAP regarding the outbreak and food safety, which may serve as support in developing policies for improved health and food safety.
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COVID-19 , Pandemias , Animales , COVID-19/epidemiología , COVID-19/prevención & control , Control de Enfermedades Transmisibles , Estudios Transversales , Femenino , Inocuidad de los Alimentos , Conocimientos, Actitudes y Práctica en Salud , Humanos , Masculino , Ocupaciones , Pandemias/prevención & control , TailandiaRESUMEN
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.
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In this research, we aimed to reduce the bacterial loads of Salmonella Enteritidis, Salmonella Typhimurium, Escherichia coli, Campylobacter jejuni, Staphylococcus aureus, and Pseudomonas aeruginosa in pork and chicken meat with skin by applying cold plasma in a liquid state or liquid plasma. The results showed reductions in S. Enteritidis, S. Typhimurium, E. coli, and C. jejuni on the surface of pork and chicken meat after 15 min of liquid plasma treatment on days 0, 3, 7, and 10. However, the efficacy of the reduction in S. aureus was lower after day 3 of the experiment. Moreover, P. aeruginosa could not be inactivated under the same experimental conditions. The microbial decontamination with liquid plasma did not significantly reduce the microbial load, except for C. jejuni, compared with water immersion. When compared with a control group, the pH value and water activity of pork and chicken samples treated with liquid plasma were significantly different (p ≤ 0.05), with a downward trend that was similar to those of the control and water groups. Moreover, the redness (a*) and yellowness (b*) values (CIELAB) of the meat decreased. Although the liquid plasma group resulted in an increase in the lightness (L*) values of the pork samples, these values did not significantly change in the chicken samples. This study demonstrated the efficacy of liquid plasma at reducing S. Enteritidis, S. Typhimurium, E. coli, C. jejuni, and S. aureus on the surface of pork and chicken meat during three days of storage at 4-6 °C with minimal undesirable meat characteristics.