Evidence map›Paper›PMID 38926448›Full record

ArticleScientific reports2024

Impact of vaccine coverage and disruption to health services on COVID-19 in Ukraine.

Valentina Costantino, Chandini R MacIntyre

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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

2 authors.

Valentina CostantinoThe Biosecurity Program, The Kirby Institute, University of New South Wales, High street, Kensington, Sydney, Australia. vale.cost@protonmail.com.
Chandini R MacIntyreThe Biosecurity Program, The Kirby Institute, University of New South Wales, High street, Kensington, Sydney, Australia.

Funding

National Health and Medical Research Council 1137582
6 · The paper itself

Abstract

COVID-19 surveillance in Ukraine ceased after the Russian invasion of the country in 2022, on a background of low vaccination rates of 34.5% for two doses at this time. We conducted a modelling study to estimate the epidemic trajectory of SARS-COV-2 in Ukraine after the start of the war. We use a COVID-19 deterministic Susceptible-Exposed-Infected-Recovered (SEIR) model for Ukraine to estimate the impact of increased vaccination coverage and masking as public health interventions. We fit the model output to case notification data between 6 January and 25 February 2022, then we forecast the COVID-19 epidemic trajectory in different scenarios of mask use and vaccine coverage. In the best-case scenario, 69% of the Ukrainian population would have been infected in the first half of 2022. Increasing mask use from 50 to 80% reduces cases and deaths by 17% and 30% respectively, while increasing vaccination rates to 60% and 9.6% for two and three doses respectively results in a 3% reduction in cases and 28% in deaths. However, if vaccination is increased to a higher coverage of 80% with two doses and 12.8% with three, or mask effectiveness is reduced to 40%, increasing vaccination coverage is more effective. The loss of health services, displacement, and destruction of infrastructure will amplify the risk of COVID-19 in Ukraine and make vaccine programs less feasible. Masks do not need the health infrastructure or cold-chain logistics required for vaccines and are more feasible for rapid epidemic control during war. However, increasing vaccine coverage will save more lives. Vaccination of refugees who have fled to other countries can be more feasibly achieved.

Indexed as

COVID-19COVID-19 VaccinesSARS-CoV-2Vaccination CoverageHumansMasksUkraineVaccinationCOVID-19 VaccinesCoronavirusInfectious diseasesModellingOutbreak responseUkraine, MasksVaccination

Identifiers

PMID38926448
PMCPMC11208616

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.