Log-Linear Modelling of Effect of Age and Gender on the Spread of Hepatitis B Virus Infection in Lagos State, Nigeria

BACKGROUND: The effect of age and gender on the transmission of any infectious disease can be of great important because the age at which the host contact the disease may be a determinant on the rate at which the disease will spread. AIM: The purpose of this research is to model the significant effect of age and gender on the spread of hepatitis B virus using data collected from Lagos State, Nigeria. MATERIAL AND METHODS: The data that was used for this research is a ten years data covering the period of 2006 to 2015, which was collected from Nigeria Institute of Medical Research (NIMR). A log-linear modelling approach was employed using R programming language software. Akaike Information Criterion (AIC) method of model selection was used in selecting the best model. RESULTS: It was discovered from the analysis that both factors (age and gender) have a significant effect on the spread of hepatitis B infection. This means that the age at which an individual is tested positive to hepatitis B virus will affect the spread of the disease. In choosing the best model among the four models that were developed, model AY: GY (age & year: gender and year) was found to be the best model. CONCLUSION: Age and gender were found to act as a risk influencer that could have a great effect on the transmission of hepatitis B virus infections in Lagos state, Nigeria.