Estimating risk factors for pathogenic dose accrual from longitudinal data
Daniel K. Sewell, Kelly K. Baker

TL;DR
This paper introduces a biologically-informed statistical method for estimating risk factors for pathogen dose accumulation, improving interpretability and variability modeling over traditional models, demonstrated through simulation and infant infection data.
Contribution
A new mechanistic approach for assessing risk factors in pathogen dose accrual, incorporating biological mechanisms and variability, with an R package implementation.
Findings
Generalized linear models have poor coverage rates.
Proposed method maintains nominal coverage even with model misspecification.
Application reveals environmental factors affecting infant enteric infections.
Abstract
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 consider the biological mechanisms through which infection occurs and thus can only be used to make comparatively weak statements about association between risk factors and incidence. Building off of established work in quantitative microbiological risk assessment, we propose a new approach to determining the association between risk factors and dose accrual rates. Our more mechanistic approach achieves a higher degree of biological plausibility, incorporates currently-ignored sources of variability, and provides regression parameters that are easily interpretable as the dose accrual rate ratio due to changes in the risk factors under study. We also describe a method for leveraging information…
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Taxonomy
TopicsAdvanced Causal Inference Techniques · Health Systems, Economic Evaluations, Quality of Life · Data-Driven Disease Surveillance
