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.

翻译：估计疾病发病风险因素对于理解其病因至关重要。对于由肠道病原体引起的疾病，现有基于统计模型的方法缺乏生物学合理性，且忽略了重要的变异来源。我们提出了一种基于定量微生物风险评估领域成熟工作的新方法，用于估计发病率风险因素。除同时影响剂量累积速率和宿主内病原体存活率的因素外，本模型回归参数可直观解释为所研究风险因素导致的剂量累积率比。我们还提出了一种整合多病原体信息的方法。所提方法已封装为R软件包（\url{https://github.com/dksewell/ladie}）。模拟研究表明广义线性模型会产生不可接受的覆盖率，而本方法即使在模型设定错误时仍能保持名义覆盖率。最后，我们通过将方法应用于PATHOME研究（\url{https://reporter.nih.gov/project-details/10227256}）获取的内罗毕婴儿数据，验证了所提方法，揭示了多种环境因素对婴儿肠道感染的影响。