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.

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.

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, PM_2.5, 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 PM_2.5 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 PM_2.5 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.

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.

Dead on arrival (DOA) refers to animals, particularly poultry, that die during the pre-slaughter phase. Elevated rates of DOA frequently signify substandard welfare conditions and might stem from multiple causes, resulting in diminished productivity and economic losses. This study included 18,643 truckload entries from 45 farms, encompassing a total of 23,191,809 meat-type ducks sent to a single slaughterhouse in Eastern Thailand between January 2019 and December 2023. The objective of this study was twofold: first, to classify high DOA rates (≥ 0.15%) using several predictors, including season, period of the day, number of ducks per truckload, distance, duration of transportation, age, average body weight, lairage time, and temperature at the lairage area. This classification was performed using machine learning (ML) algorithms such as Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine (SVM), Decision Tree (DT), Random Forests (RF), and Extreme Gradient Boosting (XGBoost). Additionally, several data-sampling techniques, including oversampling, undersampling, Random Over-Sampling Examples (ROSE), and Synthetic Minority Over-sampling Technique (SMOTE), were utilized to address the issue of imbalanced data. Second, to analyze variable importance contributing to the predictive outcomes. The descriptive analysis revealed a mean DOA percentage of 0.14% (range: 0 to 22.46%, SD = 0.49). The results of the high DOA classification indicated that among all models, XGBoost-Up, XGBoost-Down, and RF-Down were the top three models, achieving the highest overall scores in evaluation metrics including Area Under the ROC Curve (AUC), sensitivity, precision, and F1-score. The primary factors contributing to the high predictive performance of the models were the number of ducks per truckload, temperature at the lairage area, and average body weight. Additionally, the duration and distance of transportation, as well as the period of transportation, were secondary factors contributing to the outcome. These factors should be further investigated to minimize losses during the pre-slaughter phase in meat-type ducks. Additionally, considering these factors when managing transportation can help create conditions that reduce duck deaths.

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 (C_q) 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 C_q. 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.