Modeling parasite infection dynamics when there is heterogeneity and imperfect detectability
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Updated: May 9, 2026

Oral Bacterial Infection and Shedding in Drosophila melanogaster
Published on: May 31, 2018
Na Cui1, Yuguo Chen, Dylan S Small
1Department of Statistics, University of Illinois at Urbana-Champaign, 725 S. Wright Street, Champaign, Illinois 61820, U.S.A.
Abstract:
Understanding the infection and recovery rate from parasitic infections is valuable for public health planning. Two challenges in modeling these rates are (1) infection status is only observed at discrete times even though infection and recovery take place in continuous time and (2) detectability of infection is imperfect. We address these issues through a Bayesian hierarchical model based on a random effects Weibull distribution. The model incorporates heterogeneity of the infection and recovery rate among individuals and allows for imperfect detectability. We estimate the model by a Markov chain Monte Carlo algorithm with data augmentation. We present simulation studies and an application to an infection study about the parasite Giardia lamblia among children in Kenya.
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