Evidence map›Paper›PMID 36740623›Full record

ArticleJournal of epidemiology and global health2023

Tuberculosis in the Russian Federation: Prognosis and Epidemiological Models in a Situation After the COVID-19 Pandemic.

Anna Starshinova, Ekaterina Belyaeva, Natalia Doktorova, Ilya Korotkevich, Dmitry Kudlay

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.9field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Anna StarshinovaAlmazov National Medical Research Centre, 197341, St. Petersburg, Russia. starshinova_aa@almazovcentre.ru.ORCID 0000-0002-9023-6986
Ekaterina BelyaevaThe Republic of Karelia "The Republic TB Healthcare Dispensary", 185032, Petrozavodsk, Russia.
Natalia DoktorovaGSC «GENERIUM», 123112, Moscow, Russia.ORCID 0000-0002-8890-8958
Ilya KorotkevichGSC «GENERIUM», 123112, Moscow, Russia.
Dmitry KudlayFirst Moscow State Medical University (Sechenov University), 119991, Moscow, Russia.ORCID 0000-0003-1878-4467
Genetika · RUFederal Almazov North-West Medical Research Centre · RUSechenov University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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).

Indexed as

COVID-19TuberculosisTuberculosis, Multidrug-ResistantAdultChildEpidemiological ModelsHumansIncidencePandemicsPrognosisRussiaCOVID-19Epidemiological modelsIncidenceMortalityScreeningTuberculosis

Identifiers

PMID36740623
PMCPMC9900203
OpenAlexW4319263893

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.