Mathematical Modelling of the Impact of Treating Latent Tuberculosis Infection in the Elderly in a City with Intermediate Tuberculosis Burden

Overview

Journal Sci Rep

Specialty Science

Date 2019 Mar 21

PMID 30890762

Citations 11

Authors

Ka Chun Chong

Chi Chiu Leung

Wing Wai Yew

Benny Chung Ying Zee

Greta Chun Huen Tam

Maggie Haitian Wang

Katherine Min Jia

Pui Hong Chung

Steven Yuk Fai Lau

Xiaoran Han

Eng Kiong Yeoh

Affiliations

Soon will be listed here.

Abstract

Hong Kong is a high-income city with intermediate tuberculosis (TB) burden primarily driven by endogenous reactivations. A high proportion of remote latently infected people, particularly elderly, hinders the effectiveness of current strategies focusing on passive TB detection. In this study, we developed a mathematical model to evaluate the impact of treating latent TB infection (LTBI) in the elderly in addition to current TB control strategies. The model was calibrated using the annual age-stratified TB notifications from 1965-2013 in Hong Kong. Our results showed that at present, approximately 75% of annual new notifications were from reactivations. Given the present treatment completion rate, even if only a low to moderate proportion (approximately 20% to 40%) of elderly people were screened and treated for LTBI, the overall TB incidence could be reduced by almost 50%, to reach the 2025 milestone of the global End TB Strategy. Nevertheless, due to a high risk of hepatotoxicity in elderly population, benefit-risk ratios were mostly below unity; thus, intervention programs should be carefully formulated, including prioritising LTBI treatment for high-risk elderly groups who are closely monitored for possible adverse side effects.

Citing Articles

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