Evidence map›Paper›PMID 37224511›Full record

ArticleJournal of global health2023

Identification of growing tuberculosis incidence clusters in a region with a decrease in tuberculosis prevalence in Moscow (2000-2019).

Alexei A Romanyukha, Arseny S Karkach, Sergey E Borisov, Evgeny M Belilovsky, Tatiana E Sannikova

Open access · goldAbstract read
In one paragraph

Article in Journal of global health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 42% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Review
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 2 institutions in 1 country.

Alexei A Romanyukha *Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow, Russia.
Arseny S Karkach *Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow, Russia.
Sergey E BorisovMoscow Research and Clinical Center for Tuberculosis Control, Moscow Department of Public Health, Moscow, Russia.
Evgeny M BelilovskyMoscow Research and Clinical Center for Tuberculosis Control, Moscow Department of Public Health, Moscow, Russia.
Tatiana E SannikovaMarchuk Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow, Russia.
Russian Academy of Sciences · RUInstitute of Numerical Mathematics · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The control of tuberculosis (TB) may benefit from a prospective identification of areas where the incidence may increase in addition to the traditionally identified foci of high incidence. We aimed to identify residential areas with growing tuberculosis incidence rates and assess their significance and stability. Methods: We analysed the changes in TB incidence rates using case data georeferenced with spatial granularity to apartment buildings in the territory of Moscow from 2000 to 2019. We identified sparsely distributed areas with significant increases in the incidence rate inside residential areas. We tested the stability of found growth areas to case underreporting via stochastic modelling. Results: For 21 350 cases with smear- or culture-positive pulmonary TB among residents from 2000 to 2019, we identified 52 small-scale clusters of growing incidence rate responsible for 1% of all registered cases. We tested clusters of disease growth for underreporting and found them to be relatively unstable to resampling with case drop-out, but their spatial displacement was small. Territories with a stable increase in TB incidence rate were identified and compared to the rest of the city, which is characterised by a significant decrease in incidence. Conclusions: Identified areas with a tendency for an increase in the TB incidence rate may be important targets for disease control services.

Indexed as

TuberculosisHumansIncidenceMoscowPrevalenceProspective Studies

Identifiers

PMID37224511
PMCPMC10209626
OpenAlexW4377981725

What OpenQuestion holds

Textmetadata
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.