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Objective: To investigate the epidemiological characteristics of human infection with corona virus disease 2019 (COVID-19) in Moscow, Lima, Kuwait, and Singapore to analyze the effects of climate factors on the incidence of COVID-19. Methods: Collect the daily incidence of COVID-19 and related climate data in four areas, construct a negative binomial regression model, and analyze the correlation between the incidence of COVID-19 and meteorological factors. Results: AH was the climate factor affecting the incidence of COVID-19 in Moscow, Lima, and Singapore; Ta and RH were the climate factors affecting the incidence of COVID-19 in Kuwait. Conclusions: The incidence of COVID-19 in four areas were all associated with the humidity, and climate factors should be taken into consideration when epidemic prevention measures are taken, and environment humidification may be a feasible approach to decrease COVID-19 virus transmission.

We modelled the impact of selected meteorological factors on the daily number of new cases of the coronavirus disease 2019 (COVID-19) at the Hospital District of Helsinki and Uusimaa in southern Finland from August 2020 until May 2021. We applied a DLNM (distributed lag non-linear model) with and without various environmental and non-environmental confounding factors. The relationship between the daily mean temperature or absolute humidity and COVID-19 morbidity shows a non-linear dependency, with increased incidence of COVID-19 at low temperatures between 0 to −10 °C or at low absolute humidity (AH) values below 6 g/m3. However, the outcomes need to be interpreted with caution, because the associations found may be valid only for the study period in 2020–2021. Longer study periods are needed to investigate whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a seasonal pattern similar such as influenza and other viral respiratory infections. The influence of other non-environmental factors such as various mitigation measures are important to consider in future studies. Knowledge about associations between meteorological factors and COVID-19 can be useful information for policy makers and the education and health sector to predict and prepare for epidemic waves in the coming winters.

This study aims to analyze the correlation between environmental factors and confirmed cases of COVID-19 pandemic in Victoria, Mexico. The analysis is performed at the micro-level, filtering only confirmed cases of COVID-19 that are located near air quality monitoring stations, within an approximate coverage of 2.5 km, in order to identify a possible specific association between PM2.5, PM10, carbon monoxide (CO), relative humidity, temperature, absolute humidity, and total confirmed cases of COVID-19. The results evidenced that the cases of COVID-19 were very strongly associated with CO concentration. Our results also suggested that particulate matter pollution (PM2.5 and PM10) exposure have a significant correlation for confirmed cases of COVID-19. Furthermore, we studied the changes in air quality during the COVID-19 outbreak by comparing the average concentration of the four weeks before lockdown (February 16 to March 14, 2020) and the following twelve weeks during the partial lockdown (March 15 to June 06, 2020), revealing a very significant decrease of pollutants., Highlights • The first study on the effects of environmental and meteorological factors on COVID-19 cases in Mexico. • A decrease of more than 44% was found in the concentration levels of PM2.5, PM10 and CO during the lockdown period. • A strong positive correlation between confirmed COVID-19 cases with carbon monoxide. • PM2.5 and PM10 show a positive association with confirmed cases of COVID-19. • Temperature is negatively correlated to the spread of COVID-19.

Environmental factors are well known to affect spatio-temporal patterns of infectious disease outbreaks, but whether the recent rapid spread of COVID-19 across the globe is related to local environmental conditions is highly debated. We assessed the impact of environmental factors (temperature, humidity and air pollution) on the global patterns of COVID-19 early outbreak dynamics during January-May 2020, controlling for several key socio-economic factors and airport connections. We showed that during the earliest phase of the global outbreak (January-March), COVID-19 growth rates were non-linearly related to climate, with fastest spread in regions with a mean temperature of ca. 5°C, and in the most polluted regions. However, environmental effects faded almost completely when considering later outbreaks, in keeping with the progressive enforcement of containment actions. Accordingly, COVID-19 growth rates consistently decreased with stringent containment actions during both early and late outbreaks. Our findings indicate that environmental drivers may have played a role in explaining the early variation among regions in disease spread. With limited policy interventions, seasonal patterns of disease spread might emerge, with temperate regions of both hemispheres being most at risk of severe outbreaks during colder months. Nevertheless, containment measures play a much stronger role and overwhelm impacts of environmental variation, highlighting the key role for policy interventions in curbing COVID-19 diffusion within a given region. If the disease will become seasonal in the next years, information on environmental drivers of COVID-19 can be integrated with epidemiological models to inform forecasting of future outbreak risks and improve management plans., Graphical abstract Unlabelled Image, Highlights • The role of environmental conditions on COVID-19 transmission is controversial • In earliest outbreaks, COVID-19 growth rate was related to climate and PM2.5 • Early growth rates were faster in cold, dry climates and in polluted regions • Environmental effects faded almost completely when considering later outbreaks • Containment measures overwhelm impacts of environmental variation on COVID-19

The transmission of coronaviruses can be affected by several factors, including the climate. Due to the rapid spread of COVID-19 and the urgent need for rapid responses to contain the pandemic, it is essential to understand the role that weather conditions on the transmission of SARS-CoV-2. We evaluate the influence of meteorological factors on the incidence of COVID-19 during the first wave of the epidemic in Catalonia. We conducted a geographical analysis at the county level to evaluate the association between mean temperature, absolute humidity, solar radiation, and the cumulative incidence of COVID-19. Next, we used a time-series design to assess the short-term effects of meteorological factors on the daily incidence of COVID-19. We found a geographical association between meteorological factors and the cumulative incidence of COVID-19, from the end of March to June 2020, and a lesser extent in the short-term on the daily incidence during the first wave of the epidemic in Spain. Our findings suggest that warm and wet climates may reduce the incidence of COVID-19 in Catalonia. However, policy makers must interpret with caution any COVID-19 risk predictions based on climate information alone., MS appreciates the funding from SUPERA COVID19 Fund, from SAUN (Santander Universidades), CRUE and CSIC; as well as from Pfizer Global Medical Grants. The funding sources did not participate in the design or conduct of the study, the collection, management, analysis, or interpretation of the data, or the preparation, review, or approval of the manuscript.

The Severe Acute Respiratory Syndrome-Coronavirus Disease 2019 (COVID-19) pandemic caused by a novel coronavirus known as SARS-CoV-2 has caused tremendous suffering and huge economic losses. We hypothesized that extreme measures of partial-to-total shutdown might have influenced the quality of the global environment because of decreased emissions of atmospheric pollutants. We tested this hypothesis using satellite imagery, climatic datasets (temperature, and absolute humidity), and COVID-19 cases available in the public domain. While the majority of the cases were recorded from Western countries, where mortality rates were strongly positively correlated with age, the number of cases in tropical regions was relatively lower than European and North American regions, possibly attributed to faster human-to-human transmission. There was a substantial reduction in the level of nitrogen dioxide (NO2: 0.00002 mol m−2), a low reduction in CO (, Graphical abstract Unlabelled Image, Highlights • COVID-19 cases in the tropical regions were relatively lower than the European & American regions. • Observed a substantial reduction in NO2, low reduction in CO, and low to moderate reduction in AOD • High COVID-19 hazard (AH: 4 to 9 g m−3) in major of the globe during April–July 2020 • Northern Hemisphere may be more susceptible compared to tropical regions in May–July 2020. • Tropical regions may be comparatively more prone to outbreaks in October–November 2020.

This study analyzed the morbidity and mortality rates of the coronavirus disease (COVID-19) pandemic in different prefectures of Japan. Under the constraint that daily maximum confirmed deaths and daily maximum cases should exceed 4 and 10, respectively, 14 prefectures were included, and cofactors affecting the morbidity and mortality rates were evaluated. In particular, the number of confirmed deaths was assessed, excluding cases of nosocomial infections and nursing home patients. The correlations between the morbidity and mortality rates and population density were statistically significant (p-value &lt, 0.05). In addition, the percentage of elderly population was also found to be non-negligible. Among weather parameters, the maximum temperature and absolute humidity averaged over the duration were found to be in modest correlation with the morbidity and mortality rates. Lower morbidity and mortality rates were observed for higher temperature and absolute humidity. Multivariate linear regression considering these factors showed that the adjusted determination coefficient for the confirmed cases was 0.693 in terms of population density, elderly percentage, and maximum absolute humidity (p-value &lt, 0.01). These findings could be useful for intervention planning during future pandemics, including a potential second COVID-19 outbreak.

This study investigated the effects of weather conditions, air pollutants, and the air quality index (AQI) on daily cases of COVID-19 in the Bangkok Metropolitan Region (BMR). In this research, we collected data from January 1 to March 30, 2020 (90 days). This study used secondary data of meteorological and air pollutant parameters obtained from the Pollution Control Department of the Ministry of Natural Resources and Environment as well as daily confirmed COVID-19 case data in the BMR obtained from the official webpage of the Department of Disease Control, Ministry of Public Health, Thailand. We employed descriptive statistics, and Spearman and Kendall rank correlation tests were used to investigate the associations of weather variables, air pollutants, AQI with daily confirmed COVID-19 cases. Our findings indicate that CO, NO2, SO2, O3 PM10, PM2.5, AQI have a significantly negative association with daily confirmed COVID-19 cases in the BMR, whereas meteorological parameters such as temperature, relative humidity (RH), absolute humidity (AH) and wind speed (WS) showed significant positive associations with daily confirmed COVID-19 cases in the BMR. Our study is a useful supplement to encourage regulatory bodies to promote environmental strategies, as air pollution regulation could be a sustainable policy for mitigating the harmful effects of air pollutants. Furthermore, this study provides new insights into the relationship between daily meteorological factors, AQI, and air pollutants and daily confirmed COVID-19 cases in the BMR. These data may provide useful information to the public health authorities and decision makers in Thailand, as well as to the World Health Organization (WHO), in order to set proper strategic aimed at reducing the impact of the COVID-19. Future studies concerning SARS-CoV-2 and other viruses should investigate the possibility of infectious droplet dispersion in indoor and outdoor air during and after the epidemic outbreak.

The novel Coronavirus (COVID-19) was identified in Wuhan, Hubei Province, China, in December 2019 and has created a medical emergency worldwide. In India, it is already reported more than 855 thousand cases and more than 22 thousands deaths due to COVID-19 till July 12, 2020. The role of temperature, humidity, and absolute humidity in the transmission of COVID-19 has not yet been well established. In contrast, for the previous many viral infections like influenza, it is well established. Therefore the study to investigate the meteorological condition for incidence and spread of COVID-19 infection and to provide a scientific basis for prevention and control measures against the new disease is required for India. In this work, we analyze daily averaged meteorological data for the last three years (2017–2019) for March, April and May months and the same for the year 2020 for March 1 to May 31. We found a positive association between daily COVID-19 cases and temperature and a mixed association with relative and absolute humidity over India. We have investigated the association of aerosols (AOD) and other pollutions (NO2) with COVID-19 cases during the study period and also during the lockdown period (25 March-31 May) in India. During the lockdown period, aerosols (AOD) and NO2 reduced sharply with a maximum percentage drop of about 60 and 45, respectively. We have also found the reduction in surface PM2.5 PM10 and NO2 for the six mega cities of India during the lockdown period. Our results suggest that COVID-19 still may spread in warm, humid regions or during summer/monsoon, therefore an effective public health intervention should be implemented across India to slow down the transmission of COVID-19., Graphical abstract Variability of surface PM2.5, PM10 and NO2 at six mega cities of India during lockdown (1 March-31 May 2020).Unlabelled Image, Highlights • First study on the effects of meteorological factors on COVID-19 cases in India • A positive association between daily new cases of COVID-19 with temperature • RH and AH show mixed association with daily new cases of COVID-19. • Early lockdown in India slows down the spread of contagious disease COVID-19. • More than 45% fall was found in AOD and NO2 values during the lockdown period.

The purpose of the present study is to explore the associations between novel coronavirus disease 2019 (COVID-19) case counts and meteorological factors in 30 provincial capital cities of China. We compiled a daily dataset including confirmed case counts, ambient temperature (AT), diurnal temperature range (DTR), absolute humidity (AH) and migration scale index (MSI) for each city during the period of January 20th to March 2nd, 2020. First, we explored the associations between COVID-19 confirmed case counts, meteorological factors, and MSI using non-linear regression. Then, we conducted a two-stage analysis for 17 cities with more than 50 confirmed cases. In the first stage, generalized linear models with negative binomial distribution were fitted to estimate city-specific effects of meteorological factors on confirmed case counts. In the second stage, the meta-analysis was conducted to estimate the pooled effects. Our results showed that among 13 cities that have less than 50 confirmed cases, 9 cities locate in the Northern China with average AT below 0 °C, 12 cities had average AH below 4 g/m3, and one city (Haikou) had the highest AH (14.05 g/m3). Those 17 cities with 50 and more cases accounted for 90.6% of all cases in our study. Each 1 °C increase in AT and DTR was related to the decline of daily confirmed case counts, and the corresponding pooled RRs were 0.80 (95% CI: 0.75, 0.85) and 0.90 (95% CI: 0.86, 0.95), respectively. For AH, the association with COVID-19 case counts were statistically significant in lag 07 and lag 014. In addition, we found the all these associations increased with accumulated time duration up to 14 days. In conclusions, meteorological factors play an independent role in the COVID-19 transmission after controlling population migration. Local weather condition with low temperature, mild diurnal temperature range and low humidity likely favor the transmission., Graphical abstract Unlabelled Image, Highlights • The impacts of meteorological factors on COVID-19 case counts were assessed after controlling population migration. • The weather with low temperature, mild diurnal temperature range and low humidity likely favor the transmission of COVID-19. • The epidemic might gradually ease partially due to rising temperatures in coming months.