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Record W4411508502 · doi:10.15407/scine21.03.099

Epidemiological Monitoring of Tuberculosis Among Military Personnel in Ukraine: the Impact of the War and Key Priorities for the Development of the National Tuberculosis Prevention Program

2025· article· en· W4411508502 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience and innovation · 2025
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsCanadian Armed Forces
Fundersnot available
KeywordsTuberculosisEpidemiologyMedicineIncidence (geometry)PandemicEnvironmental healthPeacetimePublic healthEconomic growthPolitical scienceDiseaseCoronavirus disease 2019 (COVID-19)PathologyInfectious disease (medical specialty)Law

Abstract

fetched live from OpenAlex

Introduction. The war in Ukraine has exacerbated the humanitarian crisis and severely damaged the healthcare infrastructure, which had already been weakened in recent years by the COVID-19 pandemic, creating a new threat to the fight against tuberculosis. The incidence of tuberculosis within the Armed Forces has increased, mirroring the broader trends of rising tuberculosis rates across Ukraine.Problem Statement. In light of the difficult epidemic situation with tuberculosis globally, in Ukraine, and within its Armed Forces, the issues of diagnosis, treatment, and prevention of tuberculosis have become extremely urgent.Purpose. The aim of this study is to analyze the specific developments in tuberculosis infection among military personnel and the need for the implementation of innovative measures for its prevention, early diagnosis, and treatment. Materials and Methods. The materials for this study included reports on tuberculosis incidence from 2017 to 2023 among servicemen within the administrative territorial zones of responsibility, as determined by the Regional Sanitary and Epidemiological Department of the Command of the Medical Forces of the Armed Forces of Ukraine. Analytical and epidemiological methods, as well as mathematical modeling techniques, have been applied.Results. The relationship between the increase in tuberculosis incidence among the servicemen of the Armed Forces of Ukraine and the armed aggression by the Russian Federation was highlighted. From 2021 to 2023, a sharp increase in military personnel illness rates was observed, rising from 0.2‰ to 1.82‰. The morbidity ratio in 2023 compared to 2022 was 170.09%. The predicted incidence rate for 2024 is 1.42‰ (unfavorable).Conclusions. Ensuring effective treatment for tuberculosis, particularly multi-drug resistant forms, through the use of innovative early diagnosis methods, is one of the primary objectives for domestic medicine. Additionally, identifying cofactors contributing to tuberculosis development remains a crucial task.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.064
GPT teacher head0.406
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it