Estimating risk factors for pathogenic dose accrual from longitudinal data

Estimating risk factors for incidence of a disease is crucial for understanding its etiology. For diseases caused by enteric pathogens, off-the-shelf statistical model-based approaches do not provide biological plausibility and ignore important sources of variability. We propose a new approach to estimating incidence risk factors built on established work in quantitative microbiological risk assessment. Excepting those risk factors which affect both dose accrual and within-host pathogen survival rates, our model's regression parameters are easily interpretable as the dose accrual rate ratio due to the risk factors under study. % So long as risk factors do not affect both dose accrual and within-host pathogen survival rates, our model parameters are easily interpretable as the dose accrual rate ratio due to the risk factors under study. We also describe a method for leveraging information across multiple pathogens. The proposed methods are available as an R package at \url{https://github.com/dksewell/ladie}. Our simulation study shows unacceptable coverage rates from generalized linear models, while the proposed approach maintains the nominal rate even when the model is misspecified. Finally, we demonstrated our proposed approach by applying our method to Nairobian infant data obtained through the PATHOME study (\url{https://reporter.nih.gov/project-details/10227256}), discovering the impact of various environmental factors on infant enteric infections.