Chickens are often transported for a long distance under overcrowded conditions for human consumption, which affects their welfare, health, and even meat quality. The objective of this study was to investigate the interaction effects of transport distance (60 vs. 80 km), stocking density (0.65, 0.86, and 1.30 ft²/bird), and lairage duration (0 vs. 3 hours) on physiological, haemato-biochemical, microbial, carcass, and meat quality characteristics. A total of 324 broilers was used in a 2 × 3 × 2 factorial arrangement, with truck as the experimental unit, and linear mixed models were employed for data analysis. Higher transportation distance and more space allowance were responsible for more body weight loss during transportation (p < 0.05). Significant distance × density interactions were found for white blood cells (WBC), red blood cells (RBC), hemoglobin (Hb), packed cell volume (PCV), corticosterone, and aspartate aminotransferase (AST) (p < 0.05). Birds transported over 80 km had higher WBC, heterophil to lymphocyte ratio (H: L), lactate dehydrogenase (LDH), and glucose compared to those birds transported over 60 km (p < 0.05). The interactions between distance and lairage on triglyceride and AST indicated partial physiological recovery after 3-hour lairage (p < 0.05). The density-lairage interactions for corticosterone, triglyceride, and RBC were significant (p < 0.05). Prolonged transportation distance increased pathogenic bacterial load (log₁₀ CFU/g) and had a negative effect on meat quality characteristics, including cooking loss of thigh muscle and early postmortem pH of breast muscle (p < 0.05). Overall, extended transportation increased physiological stress and microbes, whereas increased space and lairage reduced many of the adverse effects. The study demonstrated the need to improve transportation techniques to enhance broiler welfare and meat quality.

Background: Dengue fever has emerged as a major public health concern in Bangladesh, with increasing incidence and geographic spread of outbreaks in recent years. This study aimed to investigate the lagged and non-linear associations between climatic factors and dengue incidence across all eight administrative divisions of Bangladesh from 2014 to 2025. Materials and Methods: An ecological time-series design was employed using monthly dengue case data (n = 741,338) and meteorological variables. A generalized additive model (GAM) with a negative binomial distribution was applied to account for overdispersion and capture complex relationships. Descriptive analysis was conducted to assess spatial heterogeneity, and choropleth maps were constructed to visualize the spatial distribution and regional variation in dengue burden across the country. Cross-correlation analysis was performed to identify significant lagged associations between climatic variables and dengue incidence. Results: Descriptive analysis showed substantial spatial heterogeneity, with the highest incidence observed in Dhaka (6.53 per 100,000) and the lowest in Sylhet (0.21 per 100,000). Choropleth maps illustrated distinct spatial distribution and regional variation in dengue burden across the country. Cross-correlation analysis identified significant lagged associations for temperature and rainfall (lag 1–3 months), humidity (lag 1–2 months), and wind speed (lag 2–3 months). The final GAM explained 88.6% of the deviance in dengue incidence (AIC = 7404.15; dispersion = 0.767). The approximate significance of smooth terms revealed that temperature at a lag of 1 month (p < 0.001, edf = 12.28), rainfall at a lag of 3 months (p < 0.001, edf = 2.85), and wind speed at a lag of 2 months (p < 0.001, edf = 2.25) were highly significant non-linear predictors of dengue transmission. Relative humidity was not significantly associated with dengue incidence. Non-linear effects revealed peak dengue risk at temperatures between 25 and 30 °C and moderate rainfall (~10 mm), particularly during monsoon months (June–October). A strong autoregressive effect indicated that prior dengue incidence significantly influenced current transmission. Conclusions: Overall, dengue transmission in Bangladesh is driven by complex, lagged, and non-linear interactions between climatic variables, seasonality, and regional factors. These findings provide critical evidence for climate-based early warning systems, enhance outbreak prediction, and inform evidence-based vector control strategies.