Ascaridia galli infection compromises the health and productivity of chickens. this study aimed to determine the prevalence, pathology, and control of A. galli in backyard chickens. Four hundred and fifty-six faecal samples were tested using direct smear and concentration techniques. sixty chickens were grouped based on egg per gram into untreated control, mebendazole-treated, and derivative-treated. Key epidemiologic host based and environmental variables were recorded and analysed statistically (p < 0.05 significance level). Histopathological changes in the intestine were also assessed. Overall prevalence of A. galli was 72% (330/456). Infection was high in females (74%, 200/267) than in males (68%, 130/189). Adult chickens had a higher infection rate than young (64% vs 55%; p < 0.05). Weak chickens showed a markedly higher prevalence (96%, 150/156) than healthy chickens (60%, 180/300) (p < 0.05). Geographically, prevalence was highest in Swat (85.53%), followed by Lower Dir (72.3%) and Malakand (59.21%), with statistically significant differences (p < 0.05). Management system influenced infection: free range chickens had (63%) compared to semi-free range (37%), scavenging chickens were more infected (75%) compared to receiving supplemental feed (53%) (p < 0.05). The non-dewormed chickens had a significantly higher prevalence (92%) than the dewormed group (20%) (p < 0.05). Seasonal infection peaked during the rainy season (86%) compared to the dry season (44%) (p < 0.05). Intestinal histology revealed inflammation, epithelial necrosis, villous atrophy, and crypt hyperplasia. Treatment of the chickens nematodes using mebendazole resulted in 70% (14/20) of the treated eggs being egg-negative, and the comparison of treatment of the egg-negative derivative compound resulted in 80% (16/20) of the treated eggs being egg-negative. The A. galli infection are very common, and cause intestine damage. The mebendazole and its derivative decrease egg shedding significantly, Husbandry, management and treatment should be enhanced for effective control strategies.

Analysis of count event data such as mortality cases, were often modelled using Poisson regression model. Maximum likelihood procedures were used by using SAS software to estimate the model parameters of a Poisson regression model. However, the Negative Binomial distribution has been widely suggested as the alternative to the Poisson when there is proof of overdispersion phenomenon. We modelled the mortality cases as the dependent variable using Poisson and Negative Binomial regression and compare both of the models. The procedures were done in SAS by using the function PROC GENMOD. The results showed that the mortality data in Poisson regression exhibit large ratio values between deviance to degree of freedom which indicate model misspecification or overdispersion. This large ratio was found to be reduced in Negative Binomial regression. The Normal probability plot of Pearson residual confirmed that the Negative Binomial regression is a better model than Poisson regression in modelling the mortality data. The objective of this study is to compare the goodness of fit of Poisson regression model and Negative Binomial regression model in the application of air pollution epidemiologic time series study by using SAS software.