About 681 acute febrile patients were approached during the study period. 152 patients were excluded because 149 patients were positive for malaria, 2 patients were refused to give a blood sample and 1 patient was not mentally fit thus, data from 529 patients were considered for analysis. The proportions of female and male respondents were 57.3% and 42.7% respectively, with male to female ratio 0.75:1.Participants within the age group of 20 - 39 years accounted for 48.4% followed by the age group of under 20 years, 28.9%. Of the study participants, 39.9% had only primary school level education, 7.8% higher grade completed and 31.1% had no formal education. Most study participants (86.8%) were rural residents. Concerning their occupation, farmers, students, and housewives accounted for 38.8%, 22.7% and 19.7%, respectively (Table 1).
Out of 529 participants, 79 (14.9%) were found to be positive for IgG and 38 (7.2%) were positive for IgM of yellow fever virus by indirect immunofluorescent assay (IIFA). Male participants (15.0%) had a slightly higher rate of exposure to yellow fever virus infection compared to female participants (14.85%) although the difference was not found to be statistically significant (P > 0.05). The distribution of positive cases by age showed participants’ age group under 20 years had more exposure to yellow fever virus (26.8%), followed by those in the age group above 60 years (26.5%). Further, the prevalence of yellow fever virus among urban residents and those who had primary school level education was 37.1% and 11.9% respectively. None of the socio-demographic factors such as age, sex, occupation, educational status, and resident site were found to be associated with yellow fever infection (Table 1).
30.18% and 11.83% of the study participants who do not use bed-net were positive for IgG and IgM respectively. 21.51% of those study participants who lived around the stagnant water was positive for IgG. 6.3% and 7.8% of those who had heard about the Yellow fever virus and had a recent mosquito bite are positive for IgG. However, there was no statistically significant association between those variables and the Yellow fever virus infection (Table 2).
Table 3 summarizes the exposure of Yellow fever virus infection and its association with different clinical factors. Majority, 11.02% of study participants manifested constitutionals symptoms, followed by cough, 7.5%, and headache, 6.7%. Other clinical features that the study participants experienced include neck stiffness 2.0%, eye blurred vision 2.01%, hearing loss 0.13%, sore throat 1.02%, crepitation 1.7%, abnormal heart sound 0.2%, enlarged liver 2.7%, flank pain 1.9%, tenderness 0.54% and rash 0.5%.(Table 3)
In bivariate analysis, candidate variables like blurred vision, rash, Headache, Diarrhea, high body temperature, and constitutional symptoms, occupation like an employee, student and age group of 20–39 are selected. In multivariate logistic regression, however, Yellow fever virus was only associated with constitutional symptoms (AOR = 0.28; 95% CI 0.30—0.72; p = 0.032). Out of 66 study participants who had Constitutional symptoms and positive for Yellow fever virus: 8.0% had only acute fever, 5.5% had acute fever and fatigue, 9.4% had fever and loss of appetite, 14.3% had fever, fatigue, and loss of appetite, 3.2% had acute fever, fatigue, loss of appetite and night sweet and 1.6% had acute fever, loss of appetite and night sweet
Overall there were no significant associations between factors such as sex, age residence, resent mosquito bite, use of bed net, use of mosquito repellant, stagnant water in the village and clinical sign and symptoms like headache, vomit, urination, abdominal pain, cough, shortness of breath