The impact of active case finding among high-risk populations on the decline of tuberculosis incidence
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Faculty of Mathematics and Computer Science, University of Warmia and Mazury in Olsztyn, Poland
Submission date: 2021-04-22
Final revision date: 2021-07-28
Acceptance date: 2021-07-28
Online publication date: 2021-09-28
Corresponding author
Aleksandra Tomczak   

Faculty of Mathematics and Computer Science, University of Warmia and Mazury in Olsztyn, Sloneczna 54, 10-710 Olsztyn, Poland.
Pol. Ann. Med. 2021;28(2):174-180
Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. In 2019 the WHO reported approximately 10 million TB cases and 1.4 million deaths worldwide. TB still remains one of the leading causes of death in humans. Brazil is one of 30 countries with the highest TB burden with 96,000 new cases and 6,700 deaths reported in 2019. From 2015 the TB incidence is increasing by 2%–3% annually. It means that TB control programs need to be improved.

Our aim is to show the impact of active case finding of TB cases among a high-risk subpopulation on decline of the incidence in the general population.

Material and methods:
We use a SIS-type compartmental mathematical model to describe the disease dynamics. We consider the population as a heterogeneous population which differ in disease transmission risk. Using best-fit techniques we compare the actual data with the model. For the fitted parameters we calculate the basic reproduction number and estimate the TB trends for the next few years applying several preventative protocols.

Results and discussion:
Using numerical simulations we examine the impact of ACF on the disease dynamics. We show that active screening among high risk subpopulations can help to reduce TB spread. We show how the reproduction number and estimated incidence decline depend on the detection rate.

Active screening is one of the most effective ways for reducing the spread of disease. However, due to financial constraints, it can only be used to a limited extent. Properly applied detection can limit the spread of the disease while minimizing costs.

The research was not funded by any sources. No third parties had any role in the design of the study, analyzes, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.
The authors declare no conflict of interest.
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