Age-Specific Mathematical Model for Tuberculosis Transmission Dynamics in South Korea

Mathematics

Jin-Won Kwon¹  Hae-Young Park¹  Hohyung Ryu²  Sunmi Lee² 

[1] BK21 FOUR Community-Based Intelligent Novel Drug Discovery Education Unit, College of Pharmacy, Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu 41566, Korea;Department Applied Mathematics, Kyung Hee University, Yongin 17104, Korea;

关键词: TB mathematical model with two-age groups;    transmission rate;    treatment rate;    early detection and treatment rate;    relapse rate;    the basic reproduction number;   

DOI  :  10.3390/math9080804

来源: DOAJ

【 摘 要 】

Korea has the highest burden of tuberculosis (TB) among Organization for Economic Co-operation and Development countries. Various strategies have been implemented to eradicate TB in Korea, and it is critical to evaluate previous TB management outcomes before framing future TB policies. Over the past few decades, the rapid increase in the aging population in Korea has substantially impacted the incidence of TB among the elderly. Thus, in this study, we aimed to develop a mathematical model for the assessment of TB management outcomes incorporating special features of TB transmission dynamics in Korea. First, we incorporate 2-age groups in our TB model because TB epidemics in Korea are different between the elderly and the non-elderly (<65 years vs. ≥65 years). Second, because the public-private mix has had a full-fledged impact since 2012, this study was divided into two periods (2001–2011 and 2012–2018). We developed a mathematical model of TB transmission dynamics with 2-age groups and age-specific model parameters were estimated based on actual TB epidemic data from 2001 to 2018. These parameters included transmission rates, relapse rates, and recovery rates. We conducted sensitivity analyses of various parameters, and investigated the impacts of these parameters on TB incidence. Our results demonstrate that the overall outcomes of both age-groups improved in the period of 2012–2018 compared with that in the period of 2001–2011. Age-specific interventions should be implemented to reduce the overall TB incidence. More intensive treatment efforts should be focused on the elderly, while the early detection and treatment rates for latent TB were the most significant factor to reduce TB incidence in both groups.

【 授权许可】

Unknown