Ambient temperature and subsequent COVID-19 mortality in the OECD countries and individual United States (original) (raw)
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2020
Background With the aim of providing a dynamic evaluation of the effects of basic environmental parameters on COVID-19-related death rate, we assessed the correlation between average monthly high temperatures and population density, with death/rate (monthly number of deaths/1M people) for the months of March (start of the analysis and beginning of local epidemic in most of the Western World, except in Italy where it started in February) and April 2020 (continuation of the epidemic). Different geographical areas of the Northern Hemisphere in the United States and in Europe were selected in order to provide a wide range among the different parameters. The death rates were gathered from an available dataset. As a further control, we also included latitude, as a proxy for temperature. Methods Utilizing a publicly available dataset, we retrieved data for the months of March and April 2020 for 25 areas in Europe and in the US. We computed the monthly number of deaths/1M people of confirme...
Spring Weather and COVID-19 Deaths in the U.S
2020
This study used statistically robust regression models to control for a large set of confounders (including county-level time-invariant factors and time trends, regional-level daily variation, state-level social distancing measures, ultraviolet light, and levels of ozone and fine particulate matter, PM2.5) to estimate a reliable rather than simple regression for the impact of weather on the most accurately measured outcome of COVID-19, death. When the average minimum temperature within a five-day window increased by one degree Fahrenheit in spring 2020, daily death rates in northern U.S. counties increased by an estimated 5.1%. When ozone concentration over a five-day window rose by one part per billion, daily death rates in southern U.S. counties declined by approximately 2.0%. Maximum temperature, precipitation, PM2.5, and ultraviolet light did not significantly associate with COVID-19 mortality. The mechanism that may drive the observed association of minimum temperature on COVID...
2020
We performed a global analysis with data from 149 countries to test whether temperature can explain the spatial variability of the spread rate and mortality of COVID-19 at the global scale. We performed partial correlation analysis and linear mixed effect modelling to evaluate the association of the spread rate and motility of COVID-19 with maximum, minimum, average temperatures and temperature extreme (difference between maximum and minimum temperature) and other environmental and socioeconomic parameters. After controlling the effect of the duration after the first positive case, partial correlation analysis revealed that temperature was not related with the spatial variability of the spread rate of COVID-19. Mortality was negatively related with temperature in the countries with high-income economies. In contrast, temperature extreme was significantly and positively correlated with mortality in the low-and middle-income countries. Taking the country heterogeneity into account, mi...
The American Journal of Tropical Medicine and Hygiene, 2022
The complexity of transmission of COVID-19 in the human population cannot be overstated. Although major transmission routes of COVID-19 remain as human-to-human interactions, understanding the possible role of climatic and weather processes in accelerating such interactions is still a challenge. The majority of studies on the transmission of this disease have suggested a positive association between a decrease in ambient air temperature and an increase in human cases. Using data from 19 early epicenters, we show that the relationship between the incidence of COVID-19 and temperature is a complex function of prevailing climatic conditions influencing human behavior that govern virus transmission dynamics. We note that under a dry (low-moisture) environment, notably at dew point temperatures below 0°C, the incidence of the disease was highest. Prevalence of the virus in the human population, when ambient air temperatures were higher than 24°C or lower than 17°C, was hypothesized to be...
Effects of Air Temperature on COVID-19 Case Fatality Rate
Contemporary Economics, 2021
The aim of this study was to assess the case fatality rate (CFR) of COVID-19 by performing a meta-analysis according to the air temperature and to determine if the temperature modifies the pandemic duration to the peak day for CFR of the COVID-19. A novel coronavirus spread began in December 2019 in Wuhan, China, and half a year after, more than 9 million total cases were confirmed worldwide. Therefore, knowing the conditions favorable for the spread of the virus (including weather conditions) is crucial from the perspective of the entire population. Using information from the World Health Organization, subgroup meta-analysis by temperature was performed. Survival analysis using the Kaplan-Meier estimates and the Cox proportional hazards models was conducted. Based on the conducted analysis we can conclude that in countries with temperature equal or lower than 14.8°C the pooled CFR of COVID-19 is higher than in countries with temperature greater than 14.8°C. Besides, in countries with lower temperature the peak of the CFR appears after a longer time from the first case of the novel coronavirus than in countries with higher temperature.
Correlation of Climate Factors with the COVID-19 Pandemic in USA
Biomedical statistics and informatics, 2020
The coronavirus diseases 2019 (COVID-19) caused by a novel coronavirus which was first identified in Wuhan, a city of Eastern China. What began as an epidemic mostly constrained to China has now become a worldwide pandemic. Previous studies on airborne viruses comparable to coronavirus show that there is a notable relationship between the climate indicators and transmission of viruses. This study was conducted to observe the relationships of climate factors on the number of cases and the number of deaths by Coronavirus Disease -19 (COVID-19) and the spread of it in the USA. The datasets for this research have been collected from the regular updates of The New York Times, weather2visit, Current results (weather and science fact), and Americas Health Rankings from 1 April 2020 to 30 April 2020. Findings of our study observed that the highest number of infected people and death was found in New York in April 2020. Kendall's tau-b and Spearman test of correlation reveals that minimum temperature, average temperature, absolute humidity, and air pollution are significantly correlated with the transmission of this virus and the sum of deaths by COVID-19. The verdict of this article will boost the native and international health organizations to understand the spread of COVID-19 in different environmental situations.
Impact Of Temperature and Sunshine Duration on Daily New Cases and Death due to COVID-19
2020
Background: The coronavirus pandemic (COVID-19) control has now become a critical issue for public health. Many ecological factors are proven to influence the transmission and survival of the virus. In this study, we aim to determine the association of different climate factors with the spread and mortality due to COVID-19. Methods: The climate indicators included in the study were duration of sunshine, average minimum temperature and average maximum temperature, with cumulative confirmed cases, deceased and recovered cases. The data was performed for 138 different countries of the world, between January 2020 to May 2020. Both univariate and multivariate was performed for cumulative and month-wise analysis using SPSS software. Results: The average maximum temperature, and sunshine duration was significantly associated with COVID-19 confirmed cases, deceased and recovered. For every one degree increase in mean average temperature, the confirmed, deceased and recovered cases decreased...
Effects of environmental factors on severity and mortality of COVID-19
2020
ABSTRACTBackgroundMost respiratory viruses show pronounced seasonality, but for SARS-CoV-2 this still needs to be documented.MethodsWe examined the disease progression of COVID-19 in 6,914 patients admitted to hospitals in Europe and China. In addition, we evaluated progress of disease symptoms in 37,187 individuals reporting symptoms into the COVID Symptom Study application.FindingsMeta-analysis of the mortality risk in seven European hospitals estimated odds ratios per one day increase in the admission date to be 0.981 (0.973-0.988, p<0.001) and per increase in ambient temperature of one degree Celsius to be 0.854 (0.773-0.944, p=0.007). Statistically significant decreases of comparable magnitude in median hospital stay, probability of transfer to Intensive Care Unit and need for mechanical ventilation were also observed in most, but not all hospitals. The analysis of individually reported symptoms of 37,187 individuals in the UK also showed the decrease in symptom duration and...
Environment, Development and Sustainability
We performed a global analysis with data from 149 countries to test whether temperature can explain the spatial variability of the spread rate and mortality of COVID-19 at the global scale. We performed partial correlation analysis and linear mixed effect modelling to evaluate the association of the spread rate and motility of COVID-19 with maximum, minimum, average temperatures and diurnal temperature variation (difference between daytime maximum and night-time minimum temperature) and other environmental and socioeconomic parameters. After controlling the effect of the duration since the first positive case, partial correlation analysis revealed that temperature was not related with the spatial variability of the spread rate of COVID-19 at the global scale. Mortality was negatively related with temperature in the countries with high-income economies. In contrast, diurnal temperature variation was significantly and positively correlated with mortality in the lowand middle-income countries. Taking the country heterogeneity into account, mixed effect modelling revealed that inclusion of temperature as a fixed factor in the model significantly improved model skill predicting mortality in the low-and middle-income countries. Our analysis suggests that warm climate may reduce the mortality rate in high-income economies, but in low-and middle-income countries, high diurnal temperature variation may increase the mortality risk.