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- Title
Modeling Parasite Infection Dynamics when there Is Heterogeneity and Imperfect Detectability.
- Authors
Cui, Na; Chen, Yuguo; Small, Dylan S.
- 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.
- Subjects
PARASITIC diseases; GIARDIA lamblia; HIERARCHICAL Bayes model; MARKOV chain Monte Carlo; PANEL analysis; HEALTH planning; WEIBULL distribution
- Publication
Biometrics, 2013, Vol 69, Issue 3, p683
- ISSN
0006-341X
- Publication type
Article
- DOI
10.1111/biom.12050