  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.
