ReviewFrontiers in public health2021
The Association Between COVID-19, Air Pollution, and Climate Change.
Review in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled 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.
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
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Review of an intelligent indoor environment monitoring and management system for COVID-19 risk mitigation.Frontiers in public health · 2022Pooled it
- Social inequalities in SARS-CoV-2 infection in high income countries: highlighting the need for an intersectional perspective in quantitative research.Frontiers in public health · 2025Review
- Short-term effects of air pollutants on hospitalization for childhood respiratory diseases in Suzhou City: a time-stratified case-crossover study.Journal of health, population, and nutrition · 2024Article
- Pathogen inhibition and indication by gelatin nonwoven mats with incorporation of polyphenol derivatives.RSC advances · 2023Article
- Research Progress and Hotspot Analysis of Residential Carbon Emissions Based on CiteSpace Software.International journal of environmental research and public health · 2023Review
- The COVID-19 pandemic, an environmental neurology perspective.Revue neurologique · 2022Review
- Early prediction of SARS-CoV-2 reproductive number from environmental, atmospheric and mobility data: A supervised machine learning approach.International journal of medical informatics · 2022Article
- Tobacco control measures in COVID-19 recovery: an opportune time to restore equity and planetary health.Environmental health and preventive medicine · 2022Article
- COVID-19 Impact on Public Health, Environment, Human Psychology, Global Socioeconomy, and Education.TheScientificWorldJournal · 2022Review
- The concept, approach, and future research of hydrological connectivity and its assessment at multiscales.Environmental science and pollution research international · 2021Review
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
This mini-review aims to highlight both the positive and negative relationship between COVID-19 and air pollution and climate change based on current studies. Since, COVID-19 opened a bibliographic door to scientific production, so there was a limit to research at the moment. There were two sides to the relationship between COVID-19 and both air pollution and climate change. The associated with climate change, in particular, defines the relationship very loosely. Many studies have revealed a positive correlation between COVID-19 and each air pollutants, while some studies shown a negative correlation. There were a few studies that focused on the relationship between COVID-19 in terms of climate. Meanwhile, there were many studies explained the relationship with meteorological factors instead.
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.