ArticleJournal of public affairs2021
COVID-19 pandemic and transmission factors: An empirical investigation of different countries.
Article in Journal of public affairs, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed, 10 citations in OpenAlex.
- What are the Effects of Climate Variables on COVID-19 Pandemic? A Systematic Review and Current Update.Advanced biomedical research · 2023Review
- Implementation of the SutteARIMA method to predict short-term cases of stock market and COVID-19 pandemic in USA.Quality & quantity · 2022Article
- COVID-19 pandemic and transmission factors: An empirical investigation of different countries.Journal of public affairs · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present work evaluates the impact of age, population density, total population, rural population, annual average temperature, basic sanitation facilities, and diabetes prevalence on the transmission of COVID-19. This research is an effort to identify the major predictors that have a significant impact on the number of COVID-19 cases per million population for 83 countries. The findings highlight that a population with a greater share of old people (aged above 65) shows a higher number of COVID-19 positive cases and a population with a lower median age has fewer cases. This can be explained in terms of higher co-morbidities and the lower general immunity in the older age group. The analysis restates the widely seen results that a higher median age and greater prevalence of co-morbidities leads to higher cases per million and lesser population density and interpersonal contact helps in containing the spread of the virus. The study finds foundation in the assertion that a higher temperature might lower the number of cases, or that temperature in general can affect the infectivity. The study suggests that better access to sanitation is a certain measure to contain the spread of the virus. The outcome of this study will be helpful in ascertaining the impact of these indicators in this pandemic, and help in policy formation and decision-making strategies to fight against it.
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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.