Are meteorological factors enhancing COVID-19 transmission in Bangladesh? Novel findings from a compound Poisson generalized linear modeling approach

Association metrological factors with Covid-19 mortality in Tehran, Iran (2020-2021)

The outbreak of the Coronavirus disease (COVID-19) has raised questions about the potential role of climate and environmental factors in disease transmission. This study examined meteorological and demographic factors to determine their impact on mortality and hospitalization rates in Tehran, Iran from January 1, 2021, to December 31, 2022. Notably, hospitalization cases were positively associated with temperature (P-value: 0.001 in spring, P-value: 0.045 in winter) and pressure (P-value: 0.004 in spring), while being negatively associated with wind speed (P-value: 0.03 in spring, P-value: 0.01 in autumn) and humidity (P-value: 0.001 in autumn) during the spring and autumn seasons. Conversely, mortality was associated with wind speed (P-value: 0.01) and pressure (P-value: 0.02) during winter and spring, respectively. Moreover, temperature was associated with mortality in both spring (P-value: 0.00) and winter (P-value: 0.04). The findings suggest that identifying the environmental factors that contribute to the spread of COVID-19 can help prevent future waves of the pandemic in Tehran.

What are the Effects of Climate Variables on COVID-19 Pandemic? A Systematic Review and Current Update

The climatological parameters can be different in various geographical locations. Moreover, they have possible impacts on COVID-19 incidence. Therefore, the purpose of this systematic review article was to describe the effects of climatic variables on COVID-19 pandemic in different countries. Systematic literature search was performed in Scopus, ISI Web of Science, and PubMed databases using ("Climate" OR "Climate Change" OR "Global Warming" OR "Global Climate Change" OR "Meteorological Parameters" OR "Temperature" OR "Precipitation" OR "Relative Humidity" OR "Wind Speed" OR "Sunshine" OR "Climate Extremes" OR "Weather Extremes") AND ("COVID" OR "Coronavirus disease 2019" OR "COVID-19" OR "SARS-CoV-2" OR "Novel Coronavirus") keywords. From 5229 articles, 424 were screened and 149 were selected for further analysis. The relationship between meteorological parameters is variable in different geographical locations. The results indicate that among the climatic indicators, the temperature is the most significant factor that influences on COVID-19 pandemic in most countries. Some studies were proved that warm and wet climates can decrease COVID-19 incidence; however, the other studies represented that warm location can be a high risk of COVID-19 incidence. It could be suggested that all climate variables such as temperature, humidity, rainfall, precipitation, solar radiation, ultraviolet index, and wind speed could cause spread of COVID-19. Thus, it is recommended that future studies will survey the role of all meteorological variables and interaction between them on COVID-19 spread in specific small areas such as cities of each country and comparison between them.

A review about COVID-19 in the MENA region: environmental concerns and machine learning applications

Coronavirus disease 2019 (COVID-19) has delayed global economic growth, which has affected the economic life globally. On the one hand, numerous elements in the environment impact the transmission of this new coronavirus. Every country in the Middle East and North Africa (MENA) area has a different population density, air quality and contaminants, and water- and land-related conditions, all of which influence coronavirus transmission. The World Health Organization (WHO) has advocated fast evaluations to guide policymakers with timely evidence to respond to the situation. This review makes four unique contributions. One, many data about the transmission of the new coronavirus in various sorts of settings to provide clear answers to the current dispute over the virus's transmission were reviewed. Two, highlight the most significant application of machine learning to forecast and diagnose severe acute respiratory syndrome coronavirus (SARS-CoV-2). Three, our insights provide timely and accurate information along with compelling suggestions and methodical directions for investigators. Four, the present study provides decision-makers and community leaders with information on the effectiveness of environmental controls for COVID-19 dissemination.

Understanding rural local government response during COVID-19-induced lockdown: perspective from Bangladesh

This study intends to explore the responses of local government during the COVID-19-induced lockdown in the rural areas, with particular emphasis on Bangladesh. By adopting a qualitative phenomenological research approach and employing multi-method data collection techniques (for instance, Key Informant Interview (KII), Focus Group Discussion (FGD), participant observation, and content analysis), this study found that the local governments managed the crisis of the pandemic relatively well with its limited manpower and funding through adequate preparedness and prevention strategies; effective emergency responses; and consolidated post-lockdown measures. The study revealed that the Bangladesh local government promptly took some essential actions, such as preparedness and prevention, arrangement of home quarantine and isolation, the training program for readiness, and disseminated crucial information to the local people during the pandemic, such as using masks, hand washing and sanitizing, and social distancing. Besides, the local government delivered relief, such as food and non-food items and financial support. Furthermore, the rural local government took post-lockdown responses to tackle pandemic in rural Bangladesh. Nevertheless, the service delivery individuals from local governance encountered numerous challenges, like scarcity of manpower, less support, and superstition, while providing services during the pandemic.

Correlation between COVID-19 and weather variables: A meta-analysis

Background

COVID-19 has significantly impacted humans worldwide in recent times. Weather variables have a remarkable effect on COVID-19 spread all over the universe.

Objectives

The aim of this study was to find the correlation between weather variables with COVID-19 cases and COVID-19 deaths.

Methods

Five electronic databases such as PubMed, Science Direct, Scopus, Ovid (Medline), and Ovid (Embase) were searched to conduct the literature survey from January 01, 2020, to February 03, 2022. Both fixed-effects and random-effects models were used to calculate pooled correlation and 95% confidence interval (CI) for both effect measures. Included studies heterogeneity was measured by Cochrane chi-square test statistic Q, I2 and τ2. Funnel plot was used to measure publication bias. A Sensitivity analysis was also carried out.

Results

Total 38 studies were analyzed in this study. The result of this analysis showed a significantly negative impact on COVID-19 fixed effect incidence and weather variables such as temperature (r = -0.113∗∗∗), relative humidity (r = -0.019∗∗∗), precipitation (r = -0.143∗∗∗), air pressure (r = -0.073∗), and sunlight (r = -0.277∗∗∗) and also found positive impact on wind speed (r = 0.076∗∗∗) and dew point (r = 0.115∗∗∗). From this analysis, significant negative impact was also found for COVID-19 fixed effect death and weather variables such as temperature (r = -0.094∗∗∗), wind speed (r = -0.048∗∗), rainfall (r = -0.158∗∗∗), sunlight (r = -0.271∗∗∗) and positive impact for relative humidity (r = 0.059∗∗∗).

Conclusion

This meta-analysis disclosed significant correlations between weather and COVID-19 cases and deaths. The findings of this analysis would help policymakers and the health professionals to reduce the cases and fatality rate depending on weather forecast techniques and fight this pandemic using restricted assets.

Decision-making framework for identifying regions vulnerable to transmission of COVID-19 pandemic

At the beginning of 2020, the World Health Organization (WHO) identified an unusual coronavirus and declared the associated COVID-19 disease as a global pandemic. We proposed a novel hybrid fuzzy decision-making framework to identify and analyze these transmission factors and conduct proactive decision-making in this context. We identified thirty factors from the extant literature and classified them into six major clusters (climate, hygiene and safety, responsiveness to decision-making, social and demographic, economic, and psychological) with the help of domain experts. We chose the most relevant twenty-five factors using the Fuzzy Delphi Method (FDM) screening from the initial thirty. We computed the weights of those clusters and their constituting factors and ranked them based on their criticality, applying the Fuzzy Analytic Hierarchy Process (FAHP). We found that the top five factors were global travel, delay in travel restriction, close contact, social cohesiveness, and asymptomatic. To evaluate our framework, we chose ten different geographically located cities and analyzed their exposure to COVID-19 pandemic by ranking them based on their vulnerability of transmission using Fuzzy Technique for Order of Preference by Similarity To Ideal Solution (FTOPSIS). Our study contributes to the disciplines of decision analytics and healthcare risk management during a pandemic through these novel findings. Policymakers and healthcare officials will benefit from our study by formulating and improving existing preventive measures to mitigate future global pandemics. Finally, we performed a sequence of sensitivity analyses to check for the robustness and generalizability of our proposed hybrid decision-making framework.

A review of the impact of environmental factors and pollutants on covid-19 transmission

The coronavirus disease (COVID-19) caused an unprecedented loss of life with colossal social and economic fallout over 237 countries and territories worldwide. Environmental conditions played a significant role in spreading the virus. Despite the availability of literature, the consecutive waves of COVID-19 in all geographical conditions create the necessity of reviewing the impact of environmental factors on it. This study synthesized and reviewed the findings of 110 previously published articles on meteorological factors and COVID-19 transmission. This study aimed to identify the diversified impacts of meteorological factors on the spread of infection and suggests future research. Temperature, rainfall, air quality, sunshine, wind speed, air pollution, and humidity were found as investigated frequently. Correlation and regression analysis have been widely used in previous studies. Most of the literature showed that temperature and humidity have a favorable relationship with the spread of COVID-19. On the other hand, 20 articles stated no relationship with humidity, and nine were revealed the negative effect of temperature. The daily number of COVID-19 confirmed cases increased by 4.86% for every 1 °C increase in temperature. Sunlight was also found as a significant factor in 10 studies. Moreover, increasing COVID-19 incidence appeared to be associated with increased air pollution, particularly PM10, PM2.5, and O₃ concentrations. Studies also indicated a negative relation between the air quality index and the COVID-19 cases. This review determined environmental variables' complex and contradictory effects on COVID-19 transmission. Hence it becomes essential to include environmental parameters into epidemiological models and controlled laboratory experiments to draw more precious results.

Hierarchical Bayesian spatio-temporal modeling of COVID-19 in the United States

We examine the impact of economic, demographic, and mobility-related factors have had on the transmission of COVID-19 in 2020. While many models in the academic literature employ linear/generalized linear models, few contributions exist that incorporate spatial analysis, which is useful for understanding factors influencing the proliferation of the disease before the introduction of vaccines. We utilize a Poisson generalized linear model coupled with a spatial autoregressive structure to do so. Our analysis yields a number of insights including that, in some areas of the country, the counterintuitive result that staying at home can lead to increased disease proliferation. Additionally, we find some positive effects from increased gathering at grocery stores, negative effects of visiting retail stores and workplaces, and even small effects on visiting parks highlighting the complexities travel and migration have on the transmission of diseases.

Relationship between Meteorological and Air Quality Parameters and COVID-19 in Casablanca Region, Morocco

The aim of this study was to investigate the relationship between meteorological parameters, air quality and daily COVID-19 transmission in Morocco. We collected daily data of confirmed COVID-19 cases in the Casablanca region, as well as meteorological parameters (average temperature, wind, relative humidity, precipitation, duration of insolation) and air quality parameters (CO, NO₂, 03, SO₂, PM10) during the period of 2 March 2020, to 31 December 2020. The General Additive Model (GAM) was used to assess the impact of these parameters on daily cases of COVID-19. A total of 172,746 confirmed cases were reported in the study period. Positive associations were observed between COVID-19 and wind above 20 m/s and humidity above 80%. However, temperatures above 25° were negatively associated with daily cases of COVID-19. PM10 and O₃ had a positive effect on the increase in the number of daily confirmed COVID-19 cases, while precipitation had a borderline effect below 25 mm and a negative effect above this value. The findings in this study suggest that significant associations exist between meteorological factors, air quality pollution (PM10) and the transmission of COVID-19. Our findings may help public health authorities better control the spread of COVID-19.

Stochastic analysis of the relationship between atmospheric variables and coronavirus disease (COVID-19) in a hot, arid climate

The rapid outbreak of the coronavirus disease (COVID-19) has affected millions of people all over the world and killed hundreds of thousands. Atmospheric conditions can play a fundamental role in the transmission of a virus. The relationship between several atmospheric variables and the transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are therefore investigated in this study, in which the State of Kuwait, which has a hot, arid climate, is considered during free movement (without restriction), partial lockdown (partial restrictions), and full lockdown (full restriction). The relationship between the infection rate, growth rate, and doubling time for SARS-CoV-2 and atmospheric variables are also investigated in this study. Daily data describing the number of COVID-19 cases and atmospheric variables, such as temperature, relative humidity, wind speed, visibility, and solar radiation, were collected for the period February 24 to May 30, 2020. Stochastic models were employed to analyze how atmospheric variables can affect the transmission of SARS-CoV-2. The normal and lognormal probability and cumulative density functions (PDF and CDF) were applied to analyze the relationship between atmospheric variables and COVID-19 cases. The Spearman's rank correlation test and multiple regression model were used to investigate the correlation of the studied variables with the transmission of SARS-CoV-2 and to confirm the findings obtained from the stochastic models. The results indicate that relative humidity had a significant negative correlation with the number of COVID-19 cases, whereas positive correlations were observed for cases of infection and temperature, wind speed, and visibility. The infection rate for SARS-CoV-2 is directly proportional to the air temperature, wind speed, and visibility, whereas inversely related to the humidity. The lowest growth rate and longest doubling time of the COVID-19 infection occurred during the full lockdown period. The results in this study may help the World Health Organization (WHO) make specific recommendations about the outbreak of COVID-19 for decision-makers around the world. Integr Environ Assess Manag 2022;18:500-516. © 2021 SETAC.

The effects of air pollution, meteorological parameters, and climate change on COVID-19 comorbidity and health disparities: A systematic review

Air pollutants, especially particulate matter, and other meteorological factors serve as important carriers of infectious microbes and play a critical role in the spread of disease. However, there remains uncertainty about the relationship among particulate matter, other air pollutants, meteorological conditions and climate change and the spread of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), hereafter referred to as COVID-19. A systematic review was conducted using PRISMA guidelines to identify the relationship between air quality, meteorological conditions and climate change, and COVID-19 risk and outcomes, host related factors, co-morbidities and disparities. Out of a total of 170,296 scientific publications screened, 63 studies were identified that focused on the relationship between air pollutants and COVID-19. Additionally, the contribution of host related-factors, co-morbidities, and health disparities was discussed. This review found a preponderance of evidence of a positive relationship between PM_2.5, other air pollutants, and meteorological conditions and climate change on COVID-19 risk and outcomes. The effects of PM_2.5, air pollutants, and meteorological conditions on COVID-19 mortalities were most commonly experienced by socially disadvantaged and vulnerable populations. Results however, were not entirely consistent, and varied by geographic region and study. Opportunities for using data to guide local response to COVID-19 are identified.

Prediction of COVID-19 Cases from the Nexus of Air Quality and Meteorological Phenomena: Bangladesh Perspective

An integrated approach was used to estimate the number of COVID-19 patients related to air quality and meteorological phenomena. Additionally, the air quality during pre-lockdown, lockdown, and post-lockdown stages of the COVID-19 pandemic was assessed to determine the effect of the infection containment measures taken in Bangladesh during the pandemic. The air quality was assessed based on measurements of nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), carbon monoxide (CO), black carbon, particulate matter (PM_2.5 and PM₁₀), and aerosol optical depth. Time-averaged maps of these parameters have been generated from NASA's (National Aeronautics and Space Administration) website. Values of these parameters have also been collected from a continuous air monitoring station (CAMS) located in Bangladesh's north-western city Rajshahi. The comparison shows that lockdown during the pandemic has brought significant improvements in air quality. However, the improvement was not sustained, since rapid increases in the air pollutant concentrations were observed in the post-lockdown period. Furthermore, Pearson correlation coefficients between each air quality variable and the daily new COVID-19 case rates were calculated. Different meteorological variables during the same time periods were determined to observe the variation in Rajshahi city. Relationships of these variables with the case rates were also established. Additionally, statistical analyses of the obtained data have been conducted for the measured variables using the Kruskal-Wallis test to assess the differences in the observed data among the pre-lockdown, lockdown, and post-lockdown periods. Dunn's "Q" test was employed to test if the variables showed significance statistical difference during the Kruskal-Wallis test for pairwise comparisons. From the study, it has been observed that both meteorological variables and air quality parameters have significant relationship with daily new COVID-19 case rates. Both positive and negative associations of these parameters with the COVID-19 case rates have been observed. Very high air pollution has been observed in the post-lockdown period. Thus, it is recommended that appropriate authorities undertake corrective measures to protect the environment in cities with large populations. This study provides guidance for decision makers and health officials for future research and potentially reducing the spread of COVID-19.

Statistical study on the impact of different meteorological changes on the spread of COVID-19 pandemic in Egypt and its latitude

Abstract

More than 1 million illnesses and 70,000 deaths were reported due to novel COVID-19 by the end of the first quarter of 2020. In April 2020, the World Health Organization declared COVID-19 a pandemic. The striking resemblance between COVID-19 and its forerunners SARS and MERS, as well as earlier findings on the impact of meteorological conditions on the spread of SARS and MERS, prompted researchers to investigate the relationship between meteorological conditions and the spread of COVID-19. In this work, we statistically studied the effect of different meteorological parameters such as average temperature, humidity, dew point, and wind speed on the spread of COVID-19 pandemic in Egypt and its latitude (Algeria, Egypt, Iran, Saudi Arabia, Turkey). Our findings revealed that there is a correlation between several meteorological parameters and the spread of COVID-19, but that, contrary to popular belief, the virus does not disappear when the temperature rises. Our theory is that either the virus became active in Egypt and its latitude as the temperature rose, or the humidity became unstable when the temperature rose during the summer season. A log-linear quasi-Poisson regression model was used to estimate the relationship between the studied metrological parameters and the spread of COVID-19. The findings of the study will have ramifications for future control and prevention efforts in Egypt and its latitude.

Graphic abstract

The Effect of Ambient Environmental Conditions on COVID-19 Mortality: A Systematic Review

Weather conditions may have an impact on SARS-CoV-2 virus transmission, as has been shown for seasonal influenza. Virus transmission most likely favors low temperature and low humidity conditions. This systematic review aimed to collect evidence on the impact of temperature and humidity on COVID-19 mortality. This review was registered with PROSPERO (registration no. CRD42020196055). We searched the Pubmed, Embase, and Cochrane COVID-19 databases for observational epidemiological studies. Two independent reviewers screened the title/abstracts and full texts of the studies. Two reviewers also performed data extraction and quality assessment. From 5051 identified studies, 11 were included in the review. Although the results were inconsistent, most studies imply that a decrease in temperature and humidity contributes to an increase in mortality. To establish the association with greater certainty, future studies should consider accurate exposure measurements and important covariates, such as government lockdowns and population density, sufficient lag times, and non-linear associations.

Meteorological factors, COVID-19 cases, and deaths in top 10 most affected countries: an econometric investigation

This paper examines the nexus between the Covid-19 confirmed cases, deaths, meteorological factors, including an air pollutant among the world's top 10 infected countries, from 1 February 2020 through 30 June 2020, using advanced econometric techniques to address heterogeneity across the nations. The findings of the study suggest that there exists a strong cross-sectional dependence between Covid-19 cases, deaths, and all the meteorological factors for the countries under study. The findings also reveal that a long-term relationship exists between all the meteorological factors. There exists a bi-directional causality running between the Covid-19 cases and all the meteorological factors. With Covid-19 death cases as the dependent variable, there exists bi-directional causality running between the Covid-19 death cases and Covid-19 confirmed cases, air pressure, humidity, and temperature. Temperature and air pressure exhibit a statistically significant and negative impact on the Covid-19 confirmed cases. Air pollutant PM2.5 also exhibits a significant but positive impact on the Covid-19 confirmed cases. Temperature indicates a statistically significant and negative impact on the Covid-19 death cases. At the same time, Covid-19 confirmed cases and air pollutant PM2.5 exhibit a statistically significant and positive impact on the Covid-19 death cases across the ten countries under study. Hence, it is possible to postulate that cool and dry weather conditions with lower temperatures may promote indoor activities and human gatherings (assembling), leading to virus transmission. This study contributes both practically and theoretically to the concerned field of pandemic management. Our results assist in taking appropriate measures in implementing intersectoral policies and actions as necessary in a timely and efficient manner. Causal relations of Meteorological factors and Covid-19 (2 models used in the study).

Econometric analysis of COVID-19 cases, deaths, and meteorological factors in South Asia

The pandemic has affected almost 74 million people worldwide as of 17 December 2020. This is the first study that attempts to examine the nexus between the confirmed COVID-19 cases, deaths, meteorological factors, and the air pollutant namely PM2.5 in six South Asian countries, from 1 March 2020 to 30 June 2020, using the advanced econometric techniques that are robust to heterogeneity across nations. Our findings confirm (1) a strong cross-sectional dependence and significant correlation between COVID-19 cases, deaths, meteorological factors, and air pollutant; (2) long-term relationship between all the meteorological variables, air pollutant, and COVID-19 death cases; (3) temperature, air pressure, and humidity exhibit a significant impact on the COVID-19 confirmed cases, while COVID-19 confirmed cases and air pollutant PM2.5 have a statistically significant impact on the COVID-19 death cases. In this way, the conclusion that high temperature and high humidity increase the transmission of the COVID-19 infections can also be applied to the regions with greater transmission rates, where the minimum temperature is mostly over 21 °C and humidity ranges around 80% for months. From the findings, it is evident that majority of the meteorological factors and air pollutant PM2.5 exhibit significant negative and positive effects on the number of COVID-19 confirmed cases and death cases in the six countries under study. Air pollutant PM 2.5 provides more particle surface for the virus to stick and get transported longer distances. Hence, higher particulate pollution levels in the air increase COVID-19 transmission in these six South Asian countries. This information is vital for the government and public health authorities in formulating relevant policies. The study contributes both practically and theoretically to the concerned field of pandemic management.

Influence of air pollution and meteorological factors on the spread of COVID-19 in the Bangkok Metropolitan Region and air quality during the 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, PM_2.5, 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.

Containment measures limit environmental effects on COVID-19 early outbreak dynamics

Environmental factors are well known to affect spatio-temporal patterns of infectious disease outbreaks, but whether the 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.

Impact of meteorological parameters on COVID-19 transmission in Bangladesh: a spatiotemporal approach

It has been more than 10 months since the first COVID-19 case was reported in Wuhan, China, still menacing the world with a possible second wave. This study aimed to analyze how meteorological variables can affect the spread of local COVID-19 transmission in Bangladesh. Nine spatial units were considered from a meteorological standpoint to characterize COVID-19 transmission in Bangladesh. The daily COVID-19 incidence and meteorological variable (e.g., mean temperature, relative humidity, precipitation, and wind speed) data from April 5 to September 20, 2020, were collected. The Spearman rank correlation, heat maps, and multivariate quasi-Poisson regression were employed to understand their association. The effect of meteorological variables on COVID-19 transmission was modeled using a lag period of 10 days. Results showed that mean temperature, relative humidity, and wind speed are substantially associated with an increased risk of COVID-19. On the other hand, daily precipitation is significantly associated with a decreased risk of COVID-19 incidence. The relative risks (RR) of mean temperature for daily COVID-19 incidences were 1.222 (95% confidence interval [CI], 1.214-1.232). For wind speed, the RR was 1.087 (95% CI, 1.083-1.090). For relative humidity, the RR was 1.027 (95% CI, 1.025-1.029). Overall, this study found the profound effect of meteorological parameters on COVID-19 incidence across selected nine areas in Bangladesh. This study is probably the first study to explore the impact of region-specific meteorological conditions on COVID-19 incidence in Bangladesh. Moreover, adjustments on the areal-aggregated and regional levels were made for three confounding factors, including lockdown, population density, and potential seasonal effects. The study's findings suggest that SARS-CoV-2 can be transmitted in high temperatures and humidity conditions, which contradicts many other countries' prior studies. The research outcomes will provide implications for future control and prevention measures in Bangladesh and other countries with similar climate conditions and population density.

Associations of Ambient Air Pollutants and Meteorological Factors With COVID-19 Transmission in 31 Chinese Provinces: A Time Series Study

Evidence regarding the effects of environmental factors on COVID-19 transmission is mixed. We aimed to explore the associations of air pollutants and meteorological factors with COVID-19 confirmed cases during the outbreak period throughout China. The number of COVID-19 confirmed cases, air pollutant concentrations, and meteorological factors in China from January 25 to February 29, 2020, (36 days) were extracted from authoritative electronic databases. The associations were estimated for a single-day lag as well as moving averages lag using generalized additive mixed models. Region-specific analyses and meta-analysis were conducted in 5 selected regions from the north to south of China with diverse air pollution levels and weather conditions and sufficient sample size. Nonlinear concentration-response analyses were performed. An increase of each interquartile range in PM2.5, PM10, SO2, NO2, O3, and CO at lag4 corresponded to 1.40 (1.37-1.43), 1.35 (1.32-1.37), 1.01 (1.00-1.02), 1.08 (1.07-1.10), 1.28 (1.27-1.29), and 1.26 (1.24-1.28) ORs of daily new cases, respectively. For 1°C, 1%, and 1 m/s increase in temperature, relative humidity, and wind velocity, the ORs were 0.97 (0.97-0.98), 0.96 (0.96-0.97), and 0.94 (0.92-0.95), respectively. The estimates of PM2.5, PM10, NO2, and all meteorological factors remained significantly after meta-analysis for the five selected regions. The concentration-response relationships showed that higher concentrations of air pollutants and lower meteorological factors were associated with daily new cases increasing. Higher air pollutant concentrations and lower temperature, relative humidity and wind velocity may favor COVID-19 transmission. Controlling ambient air pollution, especially for PM2.5, PM10, NO2, may be an important component of reducing risk of COVID-19 infection. In addition, as winter months are arriving in China, the meteorological factors may play a negative role in prevention. Therefore, it is significant to implement the public health control measures persistently in case another possible pandemic.