ArticleJournal of epidemiology and global health2023
Tuberculosis in the Russian Federation: Prognosis and Epidemiological Models in a Situation After the COVID-19 Pandemic.
Article in Journal of epidemiology and global health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 10 citations in OpenAlex.
- Declining prevalence of multidrug-resistant but comparatively high quinolone-resistant tuberculosis in Heilongjiang Province, China: 2013-2022 trend.BMC infectious diseases · 2026Article
- Trends and spatial distribution of pulmonary tuberculosis in China: a surveillance study.Frontiers in public health · 2026Article
- Analysis of factors influencing high infectivity in patients with tuberculosis using clinical and imaging methods.BMC infectious diseases · 2025Article
- Tuberculosis in Pregnant Women After COVID-19: Features of Prevention, Diagnosis, and Treatment (Narrative Review).Journal of clinical medicine · 2025Review
- Immune-neuroendocrine reactivity and features of tuberculosis in pregnancy.Frontiers in medicine · 2025Review
- Differential Diagnosis of Tuberculosis and Sarcoidosis by Immunological Features Using Machine Learning.Diagnostics (Basel, Switzerland) · 2024Article
- COVID-19 and Tuberculosis: Mathematical Modeling of Infection Spread Taking into Account Reduced Screening.Diagnostics (Basel, Switzerland) · 2024Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimBecause of the COVID-19 pandemic, many support programs for tuberculosis (TB) patients have been discontinued and TB mass screening activities decreased worldwide, resulting in a decrease in new case detection and an increase in TB deaths (WHO, WHO global lists of high burden countries for TB, multidrug/rifampicin-resistant TB (MDR/RR-TB) and TB/HIV, 2021-2025, 2021). The study aimed to assess changes in epidemiological indicators of tuberculosis in the Russian Federation and to simulate these indicators in the post-COVID-19 period. MATERIALS AND
methodsThe main epidemiological indicators of tuberculosis were analyzed with the use of government statistical data for the period from 2009 to 2021. Further mathematical modeling of epidemiological indicators for the coming years was carried out, taking into account the TB screening by chest X-ray. Statistical analysis was carried out using the software environment R (v.3.5.1) for statistical computing and the commercial software Statistical Package for the Social Sciences (SPSS Statistics for Windows, version 24.0, IBM Corp., 2016). Time series forecasting was performed using the programming language for statistical calculations R, version 4.1.2 and the bsts package, version 0.9.8. STUDY
resultsThe study has found that the mean regression coefficient of a single predictor differs in the model for TB incidence and mortality (0.0098 and 0.0002, respectively). Forecast of overall incidence, the incidence of children and the forecast for mortality using the basic scenario (screening 75-78%) for the period from 2022 to 2026 was characterized by a mean decrease rate of 23.1%, 15.6% and 6.0% per year, respectively. A conservative scenario (screening 47-63%) of overall incidence indicates that the incidence of children and the forecast for mortality will continue to decrease with a mean decrease rate of 23.2%, 15.6% and 6.0% per year, respectively. Comparable data were obtained from the forecast of overall incidence, the incidence of children and the forecast for mortality using the optimistic scenario (screening 82-89%) with a mean decrease rate of 22.9%, 15.4% and 6.0% per year, respectively.
conclusionsIt has been proven that the significance of screening with chest X-ray as a predictor of mortality is minimal. However, TB screening at least 60% of the population (chest X-ray in adults and immunological tests in children) have provided relationship between the TB screening rate and TB mortality rate (TB mortality rate increases with an increase in the population coverage and, conversely, decreases with a decrease in the population coverage).
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