ArticleCureus2024
Predicting the Airborne Transmission of Measles: Impact of Indoor Carbon Dioxide (CO2) Levels and Mitigation Strategies.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMeasles is a highly contagious cause of febrile illness typically seen in young children. It is transmitted primarily through respiratory droplets and small-particle aerosols and can remain viable in the air. Despite the availability of an effective vaccine, measles remains a major global issue, particularly in regions with low vaccination rates.
aimThis study aimed to quantify the airborne transmission risk of the measles virus in various indoor environments.
methodsUsing indoor carbon dioxide (CO
resultsThe relationship between airborne transmission rates and indoor CO DISCUSSION AND
conclusionIn all indoor environmental scenarios, a positive linear relationship was found between the risk of airborne transmission and indoor CO
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Registered trials
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.