Is temperature reducing the transmission of COVID-19 ?
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ABSTRACT:
SUBMITTER: Tobias A
PROVIDER: S-EPMC7165096 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:This study utilizes the non-linear least squares method to estimate the impact of temperature on COVID-19 cases per million in forty-three countries, divided into three groups as follows: the first group is composed of thirteen countries that announced the first COVID-19 cases in January 2020, while the second and third groups contain thirteen and seventeen countries, respectively, that witnessed the pandemic for the first time in February and March of the same year. This relationship was measured after four time periods from the date of reporting the first case until April 1, April 15, May 15, and July 8, 2020. The results show an inverse relationship between COVID-19 cases per million and the temperature in the studies of the four-time periods for the three-country groups. These results were only significant statistically (p < 0.1) after 110.8, 164.8 days on average from the beginning of the pandemic in the case of "January" countries.
| S-EPMC7793668 | biostudies-literature
Project description:The WHO characterized coronavirus disease 2019 (COVID-19) as a global pandemic. The influence of temperature on COVID-19 remains unclear. The objective of this study was to investigate the correlation between temperature and daily newly confirmed COVID-19 cases by different climate regions and temperature levels worldwide. Daily data on average temperature (AT), maximum temperature (MAXT), minimum temperature (MINT), and new COVID-19 cases were collected from 153 countries and 31 provinces of mainland China. We used the spline function method to preliminarily explore the relationship between R0 and temperature. The generalized additive model (GAM) was used to analyze the association between temperature and daily new cases of COVID-19, and a random effects meta-analysis was conducted to calculate the pooled results in different regions in the second stage. Our findings revealed that temperature was positively related to daily new cases at low temperature but negatively related to daily new cases at high temperature. When the temperature was below the smoothing plot peak, in the temperate zone or at a low temperature level (e.g., <25th percentiles), the RRs were 1.09 (95% CI: 1.04, 1.15), 1.10 (95% CI: 1.05, 1.15), and 1.14 (95% CI: 1.06, 1.23) associated with a 1°C increase in AT, respectively. Whereas temperature was above the smoothing plot peak, in a tropical zone or at a high temperature level (e.g., >75th percentiles), the RRs were 0.79 (95% CI: 0.68, 0.93), 0.60 (95% CI: 0.43, 0.83), and 0.48 (95% CI: 0.28, 0.81) associated with a 1°C increase in AT, respectively. The results were confirmed to be similar regarding MINT, MAXT, and sensitivity analysis. These findings provide preliminary evidence for the prevention and control of COVID-19 in different regions and temperature levels.
| S-EPMC8507510 | biostudies-literature
Project description:The COVID-19 outbreak has already become a global pandemic and containing this rapid worldwide transmission is of great challenge. The impacts of temperature and humidity on the COVID-19 transmission rate are still under discussion. Here, we elucidated these relationships by utilizing two unique scenarios, repeated measurement and natural experiment, using the COVID-19 cases reported from January 23 - February 21, 2020, in China. The modeling results revealed that higher temperature was most strongly associated with decreased COVID-19 transmission at a lag time of 8 days. Relative humidity (RH) appeared to have only a slight effect. These findings were verified by assessing SARS-CoV-2 infectivity under the relevant conditions of temperature (4°C-37°C) and RH (> 40%). We concluded that temperature increase made an important, but not determined, contribution to restrain the COVID-19 outbreak in China. It suggests that the emphasis of other effective controlling polices should be strictly implemented to restrain COVID-19 transmission in cold seasons.
| S-EPMC7834433 | biostudies-literature
Project description: Not available
| S-BSST1076 | biostudies-other
Project description:The coronavirus disease 2019 (COVID-19) pandemic is a major threat to global health. Relevant studies have shown that ambient temperature may influence the spread of novel coronavirus. However, the effect of ambient temperature on COVID-19 remains controversial. Human mobility is also closely related to the pandemic of COVID-19, which could be affected by temperature at the same time. The purpose of this study is to explore the underlying mechanism of the association of temperature with COVID-19 transmission rate by linking human mobility. The effective reproductive number, meteorological conditions and human mobility data in 47 countries are collected. Panel data models with fixed effects are used to analyze the association of ambient temperature with COVID-19 transmission rate, and the mediation by human mobility. Our results show that there is a negative relationship between temperature and COVID-19 transmission rate. We also observe that temperature is positively associated with human mobility and human mobility is positively related to COVID-19 transmission rate. Thus, the suppression effect (also known as the inconsistent mediation effect) of human mobility is confirmed, which remains robust when different lag structures are used. These findings provide evidence that temperature can influence the spread of COVID-19 by affecting human mobility. Therefore, although temperature is negatively related to COVID-19 transmission rate, governments and the public should pay more attention to control measures since people are more likely to go out when temperature rising. Our results could partially explain the reason why COVID-19 is not prevented by warm weather in some countries.
| S-EPMC7832246 | biostudies-literature
Project description:Environmental parameters have a significant impact on the spread of respiratory viral diseases (temperature (T), relative humidity (RH), and air saturation state). T and RH are strongly correlated with viral inactivation in the air, whereas supersaturated air can promote droplet deposition in the respiratory tract. This study introduces a new concept, the dynamic virus deposition ratio (α), that reflects the dynamic changes in viral inactivation and droplet deposition under varying ambient environments. A non-steady-state-modified Wells-Riley model is established to predict the infection risk of shared air space and highlight the high-risk environmental conditions. Findings reveal that a rise in T would significantly reduce the transmission of COVID-19 in the cold season, while the effect is not significant in the hot season. The infection risk under low-T and high-RH conditions, such as the frozen seafood market, is substantially underestimated, which should be taken seriously. The study encourages selected containment measures against high-risk environmental conditions and cross-discipline management in the public health crisis based on meteorology, government, and medical research.
| S-EPMC9366825 | biostudies-literature
Project description: Not available
| S-BSST563 | biostudies-other
Project description:Oral and maxillofacial surgery in patients with suspected or confirmed COVID-19, presents a high risk of exposure and cross contamination to the operative room personnel. We designed, simulated and implemented a continue negative pressure operative field barrier to provide an additional layer of protection, using standard equipment readily available in most operative rooms during oral and maxillofacial procedures.
| S-EPMC7260501 | biostudies-literature
Project description:ObjectiveTo review the evidence on the effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality.DesignSystematic review and meta-analysis.Data sourcesMedline, Embase, CINAHL, Biosis, Joanna Briggs, Global Health, and World Health Organization COVID-19 database (preprints).Eligibility criteria for study selectionObservational and interventional studies that assessed the effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality.Main outcome measuresThe main outcome measure was incidence of covid-19. Secondary outcomes included SARS-CoV-2 transmission and covid-19 mortality.Data synthesisDerSimonian Laird random effects meta-analysis was performed to investigate the effect of mask wearing, handwashing, and physical distancing measures on incidence of covid-19. Pooled effect estimates with corresponding 95% confidence intervals were computed, and heterogeneity among studies was assessed using Cochran's Q test and the I2 metrics, with two tailed P values.Results72 studies met the inclusion criteria, of which 35 evaluated individual public health measures and 37 assessed multiple public health measures as a "package of interventions." Eight of 35 studies were included in the meta-analysis, which indicated a reduction in incidence of covid-19 associated with handwashing (relative risk 0.47, 95% confidence interval 0.19 to 1.12, I2=12%), mask wearing (0.47, 0.29 to 0.75, I2=84%), and physical distancing (0.75, 0.59 to 0.95, I2=87%). Owing to heterogeneity of the studies, meta-analysis was not possible for the outcomes of quarantine and isolation, universal lockdowns, and closures of borders, schools, and workplaces. The effects of these interventions were synthesised descriptively.ConclusionsThis systematic review and meta-analysis suggests that several personal protective and social measures, including handwashing, mask wearing, and physical distancing are associated with reductions in the incidence covid-19. Public health efforts to implement public health measures should consider community health and sociocultural needs, and future research is needed to better understand the effectiveness of public health measures in the context of covid-19 vaccination.Systematic review registrationPROSPERO CRD42020178692.
| S-EPMC9423125 | biostudies-literature
Project description:COVID-19 has become a pandemic. The influence of meteorological factors on the transmission and spread of COVID-19 is of interest. This study sought to examine the associations of daily average temperature (AT) and relative humidity (ARH) with the daily counts of COVID-19 cases in 30 Chinese provinces (in Hubei from December 1, 2019 to February 11, 2020 and in other provinces from January 20, 2020 to Februarys 11, 2020). A Generalized Additive Model (GAM) was fitted to quantify the province-specific associations between meteorological variables and the daily cases of COVID-19 during the study periods. In the model, the 14-day exponential moving averages (EMAs) of AT and ARH, and their interaction were included with time trend and health-seeking behavior adjusted. Their spatial distributions were visualized. AT and ARH showed significantly negative associations with COVID-19 with a significant interaction between them (0.04, 95% confidence interval: 0.004-0.07) in Hubei. Every 1 °C increase in the AT led to a decrease in the daily confirmed cases by 36% to 57% when ARH was in the range from 67% to 85.5%. Every 1% increase in ARH led to a decrease in the daily confirmed cases by 11% to 22% when AT was in the range from 5.04 °C to 8.2 °C. However, these associations were not consistent throughout Mainland China.
| S-EPMC7167225 | biostudies-literature