Modelling the age-dependent force of infection for hepatitis in Plateau State using a Catalytic Linear Infection Model
DOI:
https://doi.org/10.15282/daam.v7i1.13704Keywords:
Catalytic linear infection model, Maximum likelihood estimation, Mean time to infection, Age-structured data, Infectious disease modelling, Hepatitis epidemiologyAbstract
This study investigates the age-specific transmission dynamics of hepatitis infections in Plateau State, Nigeria, using the Catalytic Linear Infection Model (CLIM). Age-stratified surveillance data from the Surveillance, Outbreak Response Management and Analysis System and the National Population Commission were analysed to estimate the force of infection and mean time to infection (MTI). Maximum likelihood estimation was employed to fit the CLIM, with bootstrap procedures providing robust uncertainty measures. Competing models, including the Weibull and Exponential infection-age models, were fitted for comparative evaluation using log-likelihood, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). The CLIM achieved the best fit, exhibiting the lowest AIC and BIC values. Estimated parameters indicated a linearly increasing force of infection after a threshold age of approximately 1.5 years, with a mean time to infection of 12.13 years ( ). A comprehensive simulation study demonstrated consistent estimator performance, with decreasing bias and RMSE as sample size increased. The findings highlight the suitability of CLIM for modelling hepatitis transmission in settings with gradual age-related exposure and provide insights for optimising age-targeted public health interventions. The study extends catalytic modelling literature and offers the first CLIM-based characterisation of hepatitis transmission in Plateau State.
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