What Does a Mathematical Model Tell About the Impact of Reinfection in Korean Tuberculosis Infection?

Abstract

ObjectivesAccording to the Korea Centers for Disease Control and Prevention, new active tuberculosis (TB) cases have increased since 2001. Some key factors explain and characterize the transmission dynamics of Korean TB infection, such as a higher ratio of latent individuals and a new reporting system implemented in 2001, among others.MethodsWe propose a mathematical TB model that includes exogenous reinfection to gain a better understanding of the recent trend for TB incidence. We divide the simulation time window into two periods, 1970–2000 and 2001–2012, according to the implementation date of a new TB detection system.ResultsTwo sets of parameters, including the transmission rate, the latent period, the recovery rate, and the proportion of exogenous reinfection, are estimated using the least-squares method and calibrated to data on the incidence of active TB.ConclusionAmong some key parameters in the model, the case finding effort turned out to be the most significant impacting component on the reduction in the active TB cases.

Modeling drug-resistant tuberculosis amplification rates and intervention strategies in Bangladesh

“…Mathematical modelling is one of the most important tools for understanding TB transmission dynamics and for predicting the epidemic trajectories [12][13][14][15][16][17][18]. In the last few decades, mathematicians and public health professionals have developed different types of mathematical models to investigate TB disease dynamics in different endemic regions.…”

“…In the last few decades, mathematicians and public health professionals have developed different types of mathematical models to investigate TB disease dynamics in different endemic regions. For example, Kim et al [13] constructed a mathematical model for TB with exogenous reinfection and examined the current situation of active TB incidence in Korea, and found that case detection was the most important intervention for decreasing active TB cases. Yang et al [14] developed another TB model with seasonality and determined that seasonality has a high impact on TB related incidence, prevalence and mortality, especially in the winter season.…”

“…For example, Kim et al . [ 13 ] constructed a mathematical model for TB with exogenous reinfection and examined the current situation of active TB incidence in Korea, and found that case detection was the most important intervention for decreasing active TB cases. Yang et al .…”

Predictors of job satisfaction and burnout among tuberculosis management nurses and physicians

“…South Korea (hereafter Korea) had the highest incidence rate and highest mortality rate of TB among the Organization for Economic Cooperation and Development (OECD) countries in 2005. In Korea, the annual incidence rate of new TB infections was 87 per 100,000 population, which was well above the OECD average of 17.7; moreover, the mortality rate of TB in Korea of 10 per 100,000 population was five times greater than the OECD average of 2.1 [ 2 ].…”

Is Tuberculosis Still the Number One Infectious Disease in Korea?

“…Relapse or reinfection is another issue related to TB infection in Korea. A previous study on the factors affecting reinfection of TB proposed a mathematical model [9] . This issue includes a paper to identify the status of relapse/reinfection in Korea using nationwide tuberculosis notification data [10] and trends in the utilization of laboratory tests for TB and mycobacterial diseases in the private sector by analyzing the National Health Insurance database.…”