A. Starshinova, I. Dovgalyuk, N. N. Osipov, D. Kudlay
{"title":"Lessons Learned from the COVID-19 Pandemic: Simulation of the Tuberculosis Epidemic as a Function of Population Coverage with Screening","authors":"A. Starshinova, I. Dovgalyuk, N. N. Osipov, D. Kudlay","doi":"10.58838/2075-1230-2023-101-6-56-65","DOIUrl":null,"url":null,"abstract":"The COVID-19 pandemic has led to the discontinuation of many support programs for tuberculosis patients worldwide, and lower coverage of population with screening for tuberculosis.The objective: To build a model describing the spread of tuberculosis depending on the population coverage with preventive screening, and to obtain a long-term forecast of the infection spread using this model.Subjects and Methods. We analyzed official statistical data on incidence, mortality, preventive screening coverage (PSC), and revalence of sputum smear-positive tuberculosis in the Russian Federation from 2008 to 2021. The model was built up based on fluctuations in those rates in 2020, when there was a sharp reduction in tuberculosis control interventions due to the COVID-19 pandemic. Statistical analysis was performed using the R Software (v.4.2.1).Results. A simple mathematical model describing the dependence of incidence and sputum smear-positive tuberculosis in the current year on sputum smear-positive tuberculosis in the past year and population coverage with preventive screening in the current and past years was built up. The adjusted coefficient of determination of the model (adjusted R-squared) was 0.9969, which meant that the model contained almost no random components. It showed that tuberculosis cases missed due to low population coverage with preventive screening lead to future spread of tuberculous infection and a significant increase in the number of new tuberculosis cases. Comparison of projected rates and data for 2022 demontrated correct formation of models. However, the projected rates were slightly higher than the actual rates for 2022 due to the influence of factors other than the population coverage with preventive screening for tuberculosis.Conclusions. The findings demonstrate the need for mass screening of the population in the context of significant spread of tuberculosis infection for timely detection of patients with sputum smear-positive tuberculosis.","PeriodicalId":37828,"journal":{"name":"Tuberculosis and Lung Diseases","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tuberculosis and Lung Diseases","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.58838/2075-1230-2023-101-6-56-65","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
The COVID-19 pandemic has led to the discontinuation of many support programs for tuberculosis patients worldwide, and lower coverage of population with screening for tuberculosis.The objective: To build a model describing the spread of tuberculosis depending on the population coverage with preventive screening, and to obtain a long-term forecast of the infection spread using this model.Subjects and Methods. We analyzed official statistical data on incidence, mortality, preventive screening coverage (PSC), and revalence of sputum smear-positive tuberculosis in the Russian Federation from 2008 to 2021. The model was built up based on fluctuations in those rates in 2020, when there was a sharp reduction in tuberculosis control interventions due to the COVID-19 pandemic. Statistical analysis was performed using the R Software (v.4.2.1).Results. A simple mathematical model describing the dependence of incidence and sputum smear-positive tuberculosis in the current year on sputum smear-positive tuberculosis in the past year and population coverage with preventive screening in the current and past years was built up. The adjusted coefficient of determination of the model (adjusted R-squared) was 0.9969, which meant that the model contained almost no random components. It showed that tuberculosis cases missed due to low population coverage with preventive screening lead to future spread of tuberculous infection and a significant increase in the number of new tuberculosis cases. Comparison of projected rates and data for 2022 demontrated correct formation of models. However, the projected rates were slightly higher than the actual rates for 2022 due to the influence of factors other than the population coverage with preventive screening for tuberculosis.Conclusions. The findings demonstrate the need for mass screening of the population in the context of significant spread of tuberculosis infection for timely detection of patients with sputum smear-positive tuberculosis.
期刊介绍:
The Journal is aimed for professional development of researchers, doctors, teachers of medical universities and training institutions. The Journal focuses on the presentation of results of research, case studies, issues of differential diagnostics and treatment in the phthisiologist’s practice, national programs on tuberculosis control in the Russian Federation, WHO strategies, discussion of prevention issues to stop transmission of TB/HIVco-infection, and extrapulmonary tuberculosis.