ArticleMachine learning with applications2021
Estimating COVID-19
Article in Machine learning with applications, 2021. 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
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.
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
COVID-19 (SARS COV2 n-corona virus) is the newfangled virus of the coronavirus family. COVID-19 can cause serious illness with symptoms of fever, cold, cough, and respiratory blockage. COVID-19 is a contagious virus, which originated in Wuhan, China. After one month, WHO declared it as a Pandemic due to its rapid spreading. Presently, Indonesia is also facing a hard time controlling the spread. Hence, it is essential to understand the spread rate in Indonesia and to analyze the strategies to minimize the virus spread. The proposed study can be used to assess variations in virus spread both nationally, and sub-nationally. This allows public health officials and policy-makers to track the progress of the outbreak in near real-time using an epidemiologically valid measure.
Indexed as
Identifiers
What OpenQuestion holds
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.