ArticleBMJ open2020
Predicting the local COVID-19 outbreak around the world with meteorological conditions: a model-based qualitative study.
Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The impact of geo-environmental factors on global COVID-19 transmission: A review of evidence and methodology.The Science of the total environment · 2022Pooled it
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- Forecasting COVID-19 spreading through an ensemble of classical and machine learning models: Spain's case study.Scientific reports · 2023Article
- Association of government effectiveness, logistics performance, IT systems and income with COVID-19 mortality.Heliyon · 2023Article
- Single-cell transcriptomics reveals immune infiltrate in sepsis.Frontiers in pharmacology · 2023Article
- The effects of COVID-19 transmission on environmental sustainability and human health: Paving the way to ensure its sustainable management.The Science of the total environment · 2022Review
- Weather Conditions and COVID-19 Cases: Insights from the GCC Countries.Intelligent systems with applications · 2022Article
- Article
- Assessment of Meteorological Variables and Air Pollution Affecting COVID-19 Cases in Urban Agglomerations: Evidence from China.International journal of environmental research and public health · 2022Article
- Predicting COVID-19 Cases in South Korea Using Stringency and Niño Sea Surface Temperature Indices.Frontiers in public health · 2022Article
- COVID-19 and environmental concerns: A rapid review.Renewable & sustainable energy reviews · 2021Review
- Evolutionary trajectory of SARS-CoV-2 and emerging variants.Virology journal · 2021Review
- Climate change, environment pollution, COVID-19 pandemic and mental health.The Science of the total environment · 2021Review
- Impact of outdoor and indoor meteorological conditions on the COVID-19 transmission in the western region of Saudi Arabia.Journal of environmental management · 2021Article
- Impact of climatic, demographic and disease control factors on the transmission dynamics of COVID-19 in large cities worldwide.One health (Amsterdam, Netherlands) · 2021Article
- Severe acute respiratory syndrome coronavirus-2 medical solid waste treatment: A need for efficient and effective strategies in low-resourced settings.Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA · 2021Article
- SARS-CoV-2 biology and variants: anticipation of viral evolution and what needs to be done.Environmental microbiology · 2021Article
- Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan.Chemosphere · 2021Article
- Ambient temperature and subsequent COVID-19 mortality in the OECD countries and individual United States.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThis study aims to investigate the relationship between daily weather and transmission rate of SARS-CoV-2, and to develop a generalised model for future prediction of the COVID-19 spreading rate for a certain area with meteorological factors.
designA retrospective, qualitative study. METHODS AND ANALYSIS: We collected 382 596 records of weather data with four meteorological factors, namely, average temperature, relative humidity, wind speed, and air visibility, and 15 192 records of epidemic data with daily new confirmed case counts (1 587 209 confirmed cases in total) in nearly 500 areas worldwide from 20 January 2020 to 9 April 2020. Epidemic data were modelled against weather data to find a model that could best predict the future outbreak.
resultsSignificant correlation of the daily new confirmed case count with the weather 3 to 7 days ago were found. SARS-CoV-2 is easy to spread under weather conditions of average temperature at 5 to 15°C, relative humidity at 70% to 80%, wind speed at 1.5 to 4.5 m/s and air visibility less than 10 statute miles. A short-term model with these four meteorological variables was derived to predict the daily increase in COVID-19 cases; and a long-term model using temperature to predict the pandemic in the next week to month was derived. Taken China as a discovery dataset, it was well validated with worldwide data. According to this model, there are five viral transmission patterns, 'restricted', 'controlled', 'natural', 'tropical' and 'southern'. This model's prediction performance correlates with actual observations best (over 0.9 correlation coefficient) under natural spread mode of SARS-CoV-2 when there is not much human interference such as epidemic control.
conclusionsThis model can be used for prediction of the future outbreak, and illustrating the effect of epidemic control for a certain area.
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