Predicting the local COVID-19 outbreak around the world with meteorological conditions: a model-based qualitative study

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 analysisWe 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.

Impact of climatic, demographic and disease control factors on the transmission dynamics of COVID-19 in large cities worldwide

“…The review also said 13 of 14 studies (e.g. [ 15 , 16 ]) reported decreased transmission in more humid conditions, though we find only tentative evidence supporting this. However, according to the review the overall quality of existing evidence for climatic associations was low.…”

“…Early attempts to capture relationships between climate and case numbers or transmission rate have produced disparate and inconclusive results. Analyses have conflictingly reported positive [ [11] , [12] , [13] ], negative [ 14 , 15 ], or nonlinear [ 16 ] effects of humidity. Reported effects of temperature appear more consistent, suggesting a consensus negative relationship [ [11] , [12] , [13] , 15 ], or curvilinear patterns, with cases or transmission rate peaking between ~0 °C and ~ 10 °C [ [16] , [17] , [18] ].…”

“…Analyses have conflictingly reported positive [ [11] , [12] , [13] ], negative [ 14 , 15 ], or nonlinear [ 16 ] effects of humidity. Reported effects of temperature appear more consistent, suggesting a consensus negative relationship [ [11] , [12] , [13] , 15 ], or curvilinear patterns, with cases or transmission rate peaking between ~0 °C and ~ 10 °C [ [16] , [17] , [18] ]. However, these initial modelling efforts often achieved relatively poor model fits to data, either because of data specified at country or administrative division-level, ignoring heterogeneity in local climatic conditions and epidemic spread, or failure to account for additional confounding variables.…”

Severe acute respiratory syndrome coronavirus-2 medical solid waste treatment: A need for efficient and effective strategies in low-resourced settings

“…As per the literature, several viral respiratory diseases such as influenza and SARS coronavirus-2 itself benefit from high RH to spread, suggesting that suspension of a sufficient quantity of droplets in the air is more important in terms of infectivity when compared to the adverse effect of dry air on the human immune system ( Chen et al, 2020 ).…”

Statistical analysis of COVID-19 infection caused by environmental factors: Evidence from Pakistan

“…Another study has also demonstrated the impact of humidity and temperature cause variations on COVID-19 mortality [ 15 ]. Chen and coworkers also explained the role of temperature, wind speed and relative humidity in COVID-19 severity and spread [ 19 ].…”