Extensions to Bayesian generalized linear mixed effects models for household tuberculosis transmission
Autor: | Helen E. Jenkins, Patricia Marques-Rodrigues, Laura F. White, Jerrold J. Ellner, Reynaldo Dietze, Gheorghe Doros, Mary Gaeddert, Edward C. Jones-López, Avery McIntosh |
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Rok vydání: | 2017 |
Předmět: |
Statistics and Probability
Generalized linear model Tuberculosis Epidemiology business.industry Bayesian probability medicine.disease 01 natural sciences law.invention 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine Transmission (mechanics) law Statistics Econometrics Mixed effects Medicine 030212 general & internal medicine 0101 mathematics Risk factor Biostatistics business Index case |
Zdroj: | Statistics in Medicine. 36:2522-2532 |
ISSN: | 0277-6715 |
Popis: | Household contact studies, a mainstay of tuberculosis transmission research, often assume that tuberculosis-infected household contacts of an index case were infected within the household. However, strain genotyping has provided evidence against this assumption. Understanding the household versus community infection dynamic is essential for designing interventions. The misattribution of infection sources can also bias household transmission predictor estimates. We present a household-community transmission model that estimates the probability of community infection, that is, the probability that a household contact of an index case was actually infected from a source outside the home and simultaneously estimates transmission predictors. We show through simulation that our method accurately predicts the probability of community infection in several scenarios and that not accounting for community-acquired infection in household contact studies can bias risk factor estimates. Applying the model to data from Vitoria, Brazil, produced household risk factor estimates similar to two other standard methods for age and sex. However, our model gave different estimates for sleeping proximity to index case and disease severity score. These results show that estimating both the probability of community infection and household transmission predictors is feasible and that standard tuberculosis transmission models likely underestimate the risk for two important transmission predictors. Copyright © 2017 John Wiley & Sons, Ltd. |
Databáze: | OpenAIRE |
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