Seasonal Dynamics of Tuberculosis Epidemics and Implications for Multidrug-resistant Infection Risk Assessment

Overview

Journal Epidemiol Infect

Publisher Cambridge University Press

Specialties Infectious Diseases
Public Health

Date 2013 May 17

PMID 23676258

Citations 8

Authors

Y-J Lin

C-M Liao

Affiliations

Soon will be listed here.

Abstract

Understanding how seasonality shapes the dynamics of tuberculosis (TB) is essential in determining risks of transmission and drug resistance in (sub)tropical regions. We developed a relative fitness-based multidrug-resistant (MDR) TB model incorporated with seasonality and a probabilistic assessment model to assess infection risk in Taiwan regions. The model accurately captures the seasonal transmission and population dynamics of TB incidence during 2006-2008 and MDR TB in high TB burden areas during 2006-2010 in Taiwan. There is ~3% probability of having exceeded 50% of the population infected attributed to MDR TB. Our model not only provides insight into the understanding of the interactions between seasonal dynamics of TB and environmental factors but is also capable of predicting the seasonal patterns of TB incidence associated with MDR TB infection risk. A better understanding of the mechanisms of TB seasonality will be critical in predicting the impact of public control programmes.

Citing Articles

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Wang F, Yuan Z, Qin S, Qin F, Zhang J, Mo C BMC Public Health. 2024; 24(1):1333.

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Forecasting New Tuberculosis Cases in Malaysia: A Time-Series Study Using the Autoregressive Integrated Moving Average (ARIMA) Model.

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Spatio-temporal distribution of tuberculosis and the effects of environmental factors in China.

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Population-level mathematical modeling of antimicrobial resistance: a systematic review.

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Estimating the incidence of tuberculosis cases reported at a tertiary hospital in Ghana: a time series model approach.

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