Association of COVID-19 distribution with air quality, sociodemographic factors, and comorbidities: an ecological study of US states

Rain, rain, go away, come again another day: do climate variations enhance the spread of COVID-19?

The spread of infectious diseases was further promoted due to busy cities, increased travel, and climate change, which led to outbreaks, epidemics, and even pandemics. The world experienced the severity of the 125 nm virus called the coronavirus disease 2019 (COVID-19), a pandemic declared by the World Health Organization (WHO) in 2019. Many investigations revealed a strong correlation between humidity and temperature relative to the kinetics of the virus's spread into the hosts. This study aimed to solve the riddle of the correlation between environmental factors and COVID-19 by applying RepOrting standards for Systematic Evidence Syntheses (ROSES) with the designed research question. Five temperature and humidity-related themes were deduced via the review processes, namely 1) The link between solar activity and pandemic outbreaks, 2) Regional area, 3) Climate and weather, 4) Relationship between temperature and humidity, and 5) the Governmental disinfection actions and guidelines. A significant relationship between solar activities and pandemic outbreaks was reported throughout the review of past studies. The grand solar minima (1450-1830) and solar minima (1975-2020) coincided with the global pandemic. Meanwhile, the cooler, lower humidity, and low wind movement environment reported higher severity of cases. Moreover, COVID-19 confirmed cases and death cases were higher in countries located within the Northern Hemisphere. The Blackbox of COVID-19 was revealed through the work conducted in this paper that the virus thrives in cooler and low-humidity environments, with emphasis on potential treatments and government measures relative to temperature and humidity. HIGHLIGHTS: • The coronavirus disease 2019 (COIVD-19) is spreading faster in low temperatures and humid area. • Weather and climate serve as environmental drivers in propagating COVID-19. • Solar radiation influences the spreading of COVID-19. • The correlation between weather and population as the factor in spreading of COVID-19.

The effect of the urban exposome on COVID-19 health outcomes: A systematic review and meta-analysis

BACKGROUND

The global severity of SARS-CoV-2 illness has been associated with various urban characteristics, including exposure to ambient air pollutants. This systematic review and meta-analysis aims to synthesize findings from ecological and non-ecological studies to investigate the impact of multiple urban-related features on a variety of COVID-19 health outcomes.

METHODS

On December 5, 2022, PubMed was searched to identify all types of observational studies that examined one or more urban exposome characteristics in relation to various COVID-19 health outcomes such as infection severity, the need for hospitalization, ICU admission, COVID pneumonia, and mortality.

RESULTS

A total of 38 non-ecological and 241 ecological studies were included in this review. Non-ecological studies highlighted the significant effects of population density, urbanization, and exposure to ambient air pollutants, particularly PM2.5. The meta-analyses revealed that a 1 μg/m3 increase in PM2.5 was associated with a higher likelihood of COVID-19 hospitalization (pooled OR 1.08 (95% CI:1.02-1.14)) and death (pooled OR 1.06 (95% CI:1.03-1.09)). Ecological studies, in addition to confirming the findings of non-ecological studies, also indicated that higher exposure to nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), and carbon monoxide (CO), as well as lower ambient temperature, humidity, ultraviolet (UV) radiation, and less green and blue space exposure, were associated with increased COVID-19 morbidity and mortality.

CONCLUSION

This systematic review has identified several key vulnerability features related to urban areas in the context of the recent COVID-19 pandemic. The findings underscore the importance of improving policies related to urban exposures and implementing measures to protect individuals from these harmful environmental stressors.

Linkage between Airborne Particulate Matter and Viral Pandemic COVID-19 in Bucharest

The long-distance spreading and transport of airborne particulate matter (PM) of biogenic or chemical compounds, which are thought to be possible carriers of SARS-CoV-2 virions, can have a negative impact on the incidence and severity of COVID-19 viral disease. Considering the total Aerosol Optical Depth at 550 nm (AOD) as an atmospheric aerosol loading variable, inhalable fine PM with a diameter ≤2.5 µm (PM2.5) or coarse PM with a diameter ≤10 µm (PM10) during 26 February 2020-31 March 2022, and COVID-19's five waves in Romania, the current study investigates the impact of outdoor PM on the COVID-19 pandemic in Bucharest city. Through descriptive statistics analysis applied to average daily time series in situ and satellite data of PM2.5, PM10, and climate parameters, this study found decreased trends of PM2.5 and PM10 concentrations of 24.58% and 18.9%, respectively compared to the pre-pandemic period (2015-2019). Exposure to high levels of PM2.5 and PM10 particles was positively correlated with COVID-19 incidence and mortality. The derived average PM2.5/PM10 ratios during the entire pandemic period are relatively low (<0.44), indicating a dominance of coarse traffic-related particles' fraction. Significant reductions of the averaged AOD levels over Bucharest were recorded during the first and third waves of COVID-19 pandemic and their associated lockdowns (~28.2% and ~16.4%, respectively) compared to pre-pandemic period (2015-2019) average AOD levels. The findings of this research are important for decision-makers implementing COVID-19 safety controls and health measures during viral infections.

Thought Believability and Anxious Feelings about COVID-19: A Case-Control Study in Northeastern Iran

Background

Believability and thoughts are considered as the pillars of behaviors over time, and anxious feelings are a risk factor for mental disorders, especially during the coronavirus disease (COVID-19) pandemic. This study aimed to explore the thought believability and anxious feelings of COVID-19 among infected and healthy families.

Methods

In this hospital-based matched case-control study, health surveillance files of COVID-19 patients were collected from January to June 2021 and were analyzed statistically. In this study, two questionnaires of demographic characteristics and the Believability of Anxious Feelings and Thoughts (BAFT) were used. Data were analyzed using the One-way ANOVA.

Results

Of 600 participants, 300 (50%) were PCR-confirmed and 300 (50%) were non-infected. Overall, 163 (54.33%) of infected people were male, 146 (48.67%) single, and 156 (52.00%) government employees. The results showed that the mean scores of physical anxiety (PA) and negative evaluation (NE) in the case group is significantly higher than the control group (P = 0.001); while emotional regulation (ER) in the control group was significantly higher than the case group (P = 0.001).

Conclusion

Having high believability to the risks of COVID-19 may be a predictor of preventive behaviors in individuals. Worrying about COVID-19 can increase the perceived risk of a pandemic in societies and consequence, increase the general public health.

Environmental factors are associated to hospital outcomes in COVID-19 patients during lockdown and post-lockdown in 2020: A nationwide study

OBJECTIVE

This study analyzed, at a postcode detailed level, the relation-ship between short-term exposure to environmental factors and hospital ad-missions, in-hospital mortality, ICU admission, and ICU mortality due to COVID-19 during the lockdown and post-lockdown 2020 period in Spain.

METHODS

We performed a nationwide population-based retrospective study on 208,744 patients admitted to Spanish hospitals due to COVID-19 based on the Minimum Basic Data Set (MBDS) during the first two waves of the pandemic in 2020. Environmental data were obtained from Copernicus Atmosphere Monitoring Service. The association was assessed by a generalized additive model.

RESULTS

PM2.5 was the most critical environmental factor related to hospital admissions and hospital mortality due to COVID-19 during the lockdown in Spain, PM10, NO2, and SO2and also showed associations. The effect was considerably reduced during the post-lockdown period. ICU admissions in COVID-19 patients were mainly associated with PM2.5, PM10, NO2, and SO2 during the lockdown as well. During the lockdown, exposure to PM2.5 and PM10 were the most critical environmental factors related to ICU mortality in COVID-19.

CONCLUSION

Short-term exposure to air pollutants impacts COVID-19 out-comes during the lockdown, especially PM2.5, PM10, NO2, and SO2. These pollutants are associated with hospital admission, hospital mortality and ICU admission, while ICU mortality is mainly associated with PM2.5 and PM10. Our findings reveal the importance of monitoring air pollutants in respiratory infectious diseases.

Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States

Numerous studies have investigated the associations between COVID-19 risks and long-term exposure to air pollutants, revealing considerable heterogeneity and even contradictory regional results. Studying the spatial heterogeneity of the associations is essential for developing region-specific and cost-effective air-pollutant-related public health policies for the prevention and control of COVID-19. However, few studies have investigated this issue. Using the USA as an example, we constructed single/two-pollutant conditional autoregressions with random coefficients and random intercepts to map the associations between five air pollutants (PM_2.5, O₃, SO₂, NO₂, and CO) and two COVID-19 outcomes (incidence and mortality) at the state level. The attributed cases and deaths were then mapped at the county level. This study included 3108 counties from 49 states within the continental USA. The county-level air pollutant concentrations from 2017 to 2019 were used as long-term exposures, and the county-level cumulative COVID-19 cases and deaths through May 13, 2022, were used as outcomes. Results showed that considerably heterogeneous associations and attributable COVID-19 burdens were found in the USA. The COVID-19 outcomes in the western and northeastern states appeared to be unaffected by any of the five pollutants. The east of the USA bore the greatest COVID-19 burdens attributable to air pollution because of its high pollutant concentrations and significantly positive associations. PM_2.5 and CO were significantly positively associated with COVID-19 incidence in 49 states on average, whereas NO₂ and SO₂ were significantly positively associated with COVID-19 mortality. The remaining associations between air pollutants and COVID-19 outcomes were not statistically significant. Our study provided implications regarding where a major concern should be placed on a specific air pollutant for COVID-19 control and prevention, as well as where and how to conduct additional individual-based validation research in a cost-effective manner.

Effects of the built environment and human factors on the spread of COVID-19: A systematic literature review

Soon after its emergence, COVID-19 became a global problem. While different types of vaccines and treatments are now available, still non-pharmacological policies play a critical role in managing the pandemic. The literature is enriched enough to provide comprehensive, practical, and scientific insights to better deal with the pandemic. This research aims to find out how the built environment and human factors have affected the transmission of COVID-19 on different scales, including country, state, county, city, and urban district. This is done through a systematic literature review of papers indexed on the Web of Science and Scopus. Initially, these databases returned 4264 papers, and after different stages of screening, we found 166 relevant papers and reviewed them. The empirical papers that had at least one case study and analyzed the effects of at least one built environment factor on the spread of COVID-19 were selected. Results showed that the driving forces can be divided into seven main categories: density, land use, transportation and mobility, housing conditions, demographic factors, socio-economic factors, and health-related factors. We found that among other things, overcrowding, public transport use, proximity to public spaces, the share of health and services workers, levels of poverty, and the share of minorities and vulnerable populations are major predictors of the spread of the pandemic. As the most studied factor, density was associated with mixed results on different scales, but about 58 % of the papers reported that it is linked with a higher number of cases. This study provides insights for policymakers and academics to better understand the dynamic roles of the non-pharmacological driving forces of COVID-19 at different levels.

Comorbidities, sociodemographic factors, and determinants of health on COVID-19 fatalities in the United States

Previous studies have evaluated comorbidities and sociodemographic factors individually or by type but not comprehensively. This study aims to analyze the influence of a wide variety of factors in a single study to better understand the big picture of their effects on case-fatalities. This cross-sectional study used county-level comorbidities, social determinants of health such as income and race, measures of preventive healthcare, age, education level, average household size, population density, and political voting patterns were all evaluated on a national and regional basis. Analysis was performed through Generalized Additive Models and adjusted by the COVID-19 Community Vulnerability Index (CCVI). Effect estimates of COVID-19 fatality rates for risk factors such as comorbidities, sociodemographic factors and determinant of health. Factors associated with reducing COVID-19 fatality rates were mostly sociodemographic factors such as age, education and income, and preventive health measures. Obesity, minimal leisurely activity, binge drinking, and higher rates of individuals taking high blood pressure medication were associated with increased case fatality rate in a county. Political leaning influenced case case-fatality rates. Regional trends showed contrasting effects where larger household size was protective in the Midwest, yet harmful in Northeast. Notably, higher rates of respiratory comorbidities such as asthma and chronic obstructive pulmonary disease (COPD) diagnosis were associated with reduced case-fatality rates in the Northeast. Increased rates of chronic kidney disease (CKD) within counties were often the strongest predictor of increased case-fatality rates for several regions. Our findings highlight the importance of considering the full context when evaluating contributing factors to case-fatality rates. The spectrum of factors identified in this study must be analyzed in the context of one another and not in isolation.

Effects of meteorological factors and air pollutants on the incidence of COVID-19 in South Korea

Air pollution and meteorological factors can exacerbate susceptibility to respiratory viral infections. To establish appropriate prevention and intervention strategies, it is important to determine whether these factors affect the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Therefore, this study examined the effects of sunshine, temperature, wind, and air pollutants including sulfur dioxide (SO₂), carbon monoxide (CO), ozone (O₃), nitrogen dioxide (NO₂), particulate matter ≤2.5 μm (PM_2.5), and particulate matter ≤10 μm (PM₁₀) on the age-standardized incidence ratio of coronavirus disease (COVID-19) in South Korea between January 2020 and April 2020. Propensity score weighting was used to randomly select observations into groups according to whether the case was cluster-related, to reduce selection bias. Multivariable logistic regression analyses were used to identify factors associated with COVID-19 incidence. Age 60 years or over (odds ratio [OR], 1.29; 95% CI, 1.24-1.35), exposure to ambient air pollutants, especially SO₂ (OR, 5.19; 95% CI, 1.13-23.9) and CO (OR, 1.17; 95% CI, 1.07-1.27), and non-cluster infection (OR, 1.28; 95% CI, 1.24-1.32) were associated with SARS-CoV-2 infection. To manage and control COVID-19 effectively, further studies are warranted to confirm these findings and to develop appropriate guidelines to minimize SARS-CoV-2 transmission.

Elucidating the role of environmental management of forests, air quality, solid waste and wastewater on the dissemination of SARS-CoV-2

The increasing frequency of zoonotic diseases is amongst several catastrophic repercussions of inadequate environmental management. Emergence, prevalence, and lethality of zoonotic diseases is intrinsically linked to environmental management which are currently at a destructive level globally. The effects of these links are complicated and interdependent, creating an urgent need of elucidating the role of environmental mismanagement to improve our resilience to future pandemics. This review focused on the pertinent role of forests, outdoor air, indoor air, solid waste and wastewater management in COVID-19 dissemination to analyze the opportunities prevailing to control infectious diseases considering relevant data from previous disease outbreaks. Global forest management is currently detrimental and hotspots of forest fragmentation have demonstrated to result in zoonotic disease emergences. Deforestation is reported to increase susceptibility to COVID-19 due to wildfire induced pollution and loss of forest ecosystem services. Detection of SARS-CoV-2 like viruses in multiple animal species also point to the impacts of biodiversity loss and forest fragmentation in relation to COVID-19. Available literature on air quality and COVID-19 have provided insights into the potential of air pollutants acting as plausible virus carrier and aggravating immune responses and expression of ACE2 receptors. SARS-CoV-2 is detected in outdoor air, indoor air, solid waste, wastewater and shown to prevail on solid surfaces and aerosols for prolonged hours. Furthermore, lack of protection measures and safe disposal options in waste management are evoking concerns especially in underdeveloped countries due to high infectivity of SARS-CoV-2. Inadequate legal framework and non-adherence to environmental regulations were observed to aggravate the postulated risks and vulnerability to future waves of pandemics. Our understanding underlines the urgent need to reinforce the fragile status of global environmental management systems through the development of strict legislative frameworks and enforcement by providing institutional, financial and technical supports.

Impacts of exposure to air pollution, radon and climate drivers on the COVID-19 pandemic in Bucharest, Romania: A time series study

During the ongoing global COVID-19 pandemic disease, like several countries, Romania experienced a multiwaves pattern over more than two years. The spreading pattern of SARS-CoV-2 pathogens in the Bucharest, capital of Romania is a multi-factorial process involving among other factors outdoor environmental variables and viral inactivation. Through descriptive statistics and cross-correlation analysis applied to daily time series of observational and geospatial data, this study aims to evaluate the synergy of COVID-19 incidence and lethality with air pollution and radon under different climate conditions, which may exacerbate the coronavirus' effect on human health. During the entire analyzed period 1 January 2020-21 December 2021, for each of the four COVID-19 waves were recorded different anomalous anticyclonic synoptic meteorological patterns in the mid-troposphere, and favorable stability conditions during fall-early winter seasons for COVID-19 disease fast-spreading, mostly during the second, and the fourth waves. As the temporal pattern of airborne SARS-CoV-2 and its mutagen variants is affected by seasonal variability of the main air pollutants and climate parameters, this paper found: 1) the daily outdoor exposures to air pollutants (particulate matter PM2.5 and PM10, nitrogen dioxide-NO₂, sulfur dioxide-SO₂, carbon monoxide-CO) and radon - ²²²Rn, are directly correlated with the daily COVID-19 incidence and mortality, and may contribute to the spread and the severity of the pandemic; 2) the daily ground ozone-O₃ levels, air temperature, Planetary Boundary Layer height, and surface solar irradiance are anticorrelated with the daily new COVID-19 incidence and deaths, averageingful for spring-summer periods. Outdoor exposure to ambient air pollution associated with radon is a non-negligible driver of COVID-19 transmission in large metropolitan areas, and climate variables are risk factors in spreading the viral infection. The findings of this study provide useful information for public health authorities and decision-makers to develop future pandemic diseases strategies in high polluted metropolitan environments.

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.

Long-term exposure to fine particulate matter air pollution: An ecological study of its effect on COVID-19 cases and fatality in Germany

BACKGROUND

COVID-19 is a lung disease, and there is medical evidence that air pollution is one of the external causes of lung diseases. Fine particulate matter is one of the air pollutants that damages pulmonary tissue. The combination of the coronavirus and fine particulate matter air pollution may exacerbate the coronavirus' effect on human health.

RESEARCH QUESTION

This paper considers whether the long-term concentration of fine particulate matter of different sizes changes the number of detected coronavirus infections and the number of COVID-19 fatalities in Germany.

STUDY DESIGN

Data from 400 German counties for fine particulate air pollution from 2002 to 2020 are used to measure the long-term impact of air pollution. Kriging interpolation is applied to complement data gaps. With an ecological study, the correlation between average particulate matter air pollution and COVID-19 cases, as well as fatalities, are estimated with OLS regressions. Thereby, socioeconomic and demographic covariates are included.

MAIN FINDINGS

An increase in the average long-term air pollution of 1 μg/m3 particulate matter PM2.5 is correlated with 199.46 (SD = 29.66) more COVID-19 cases per 100,000 inhabitants in Germany. For PM10 the respective increase is 52.38 (SD = 12.99) more cases per 100,000 inhabitants. The number of COVID-19 deaths were also positively correlated with PM2.5 and PM10 (6.18, SD = 1.44, respectively 2.11, SD = 0.71, additional COVID-19 deaths per 100,000 inhabitants).

CONCLUSION

Long-term fine particulate air pollution is suspected as causing higher numbers of COVID-19 cases. Higher long-term air pollution may even increase COVID-19 death rates. We find that the results of the correlation analysis without controls are retained in a regression analysis with controls for relevant confounding factors. Nevertheless, additional epidemiological investigations are required to test the causality of particulate matter air pollution for COVID-19 cases and the severity.

Correlation between environmental factors and COVID-19 indices: a global level ecological study

This global level ecological study aimed to investigate the correlation between environmental factors and the COVID-19 indices. This survey is an ecological study, so all studied variables are aggregate variables. To collect the variables in the study, a data set was provided, which includes the information of each country based on the cumulative deaths, case fatality rate, recovery rate, and the number of performed COVID-19 tests. Scatter plots of environmental factors for the studied countries were drawn based on cumulative incidence rate of cases, cumulative incidence rate of death, tests, recovery rate, and case fatality rate of COVID-19. Furthermore, Spearman correlation coefficient was also used to verify the correlation between environmental factors and indicators related to COVID-19. The results of this ecological study showed that among all countries surveyed, Montenegro (60,310.56 per million) and Luxembourg (54,807.89 per million) had the highest cumulative incidence rates of COVID-19 cases, when Tanzania (8.42 per million) and Vietnam (13.78 per million) had the lowest cumulative incidence rates of COVID-19. In addition, in this study, it was shown that the cumulative incidence rate of cases, the cumulative incidence rate of deaths, and performed COVID-19 tests had significant direct correlations with the access to drinking water and the access to sanitation services (p < 0.001). The findings of the present study showed an inverse correlation between the mortality rate due to unhealthy water consumption, poor health status, and a positive correlation between access to drinking water and health services with the cumulative incidence and mortality rates of COVID-19. The differences between our findings and many other studies could be due to the ecological nature of the study. Nevertheless, our findings will help health policymakers to develop timely strategies to reduce the mortality and incidence rate of COVID-19.

The impact of the COVID-19 lockdown on global air quality: A review

The coronavirus disease 2019 (COVID-19) was declared a pandemic by the World Health Organization (WHO) on March 11, 2020. As a preventive measure, the majority of countries adopted partial or complete lockdown to fight the novel coronavirus. The lockdown was considered the most effective tool to break the spread of the coronavirus infection worldwide. Although lockdown damaged national economies, it has given a new dimension and opportunity to reduce environmental contamination, especially air pollution. In this study, we reviewed, analyzed and discussed the available recent literature and highlighted the impact of lockdown on the level of prominent air pollutants and consequent effects on air quality. The levels of air contaminants like nitrogen dioxide (NO2), sulphur dioxide (SO2), carbon monoxide (CO), and particulate matter (PM) decreased globally compared to levels in the past few decades. In many megacities of the world, the concentration of PM and NO2 declined by > 60% during the lockdown period. The air quality index (AQI) also improved substantially throughout the world during the lockdown. Overall, the air quality of many urban areas improved slightly to significantly during the lockdown period. It has been observed that COVID-19 transmission and mortality rate also decreased in correlation to reduced pollution level in many cities.

Air quality index variation before and after the onset of COVID-19 pandemic: a comprehensive study on 87 capital, industrial and polluted cities of the world

BACKGROUND

Coronavirus disease 2019 (COVID-19) pandemic provided an opportunity for the environment to reduce ambient pollution despite the economic, social and health disruption to the world. The purpose of this study was to investigate the changes in the air quality indexes (AQI) in industrial, densely populated and capital cities in different countries of the world before and after 2020. In this ecological study, we used AQI obtained from the free available databases such as the World Air Quality Index (WAQI). Bivariate correlation analysis was used to explore the correlations between meteorological and AQI variables. Mean differences (standard deviation: SD) of AQI parameters of different years were tested using paired-sample t-test or Wilcoxon signed-rank test as appropriate. Multivariable linear regression analysis was conducted to recognize meteorological variables affecting the AQI parameters.

RESULTS

AQI-PM2.5, AQI-PM10 and AQI-NO2 changes were significantly higher before and after 2020, simultaneously with COVID-19 restrictions in different cities of the world. The overall changes of AQI-PM2.5, AQI-PM10 and AQI-NO2 in 2020 were - 7.36%, - 17.52% and - 20.54% compared to 2019. On the other hand, these results became reversed in 2021 (+ 4.25%, + 9.08% and + 7.48%). In general, the temperature and relative humidity were inversely correlated with AQI-PM2.5, AQI-PM10 and AQI-NO2. Also, after adjusting for other meteorological factors, the relative humidity was inversely associated with AQI-PM2.5, AQI-PM10 and AQI-NO2 (β = - 1.55, β = - 0.88 and β = - 0.10, P < 0.01, respectively).

CONCLUSIONS

The results indicated that air quality generally improved for all pollutants except carbon monoxide and ozone in 2020; however, changes in 2021 have been reversed, which may be due to the reduction of some countries' restrictions. Although this quality improvement was temporary, it is an important result for planning to control environmental pollutants.

The lost productivity cost of absenteeism due to COVID-19 in health care workers in Iran: a case study in the hospitals of Mashhad University of Medical Sciences

Background

Human resources management plays an important role in social development and economic growth. Absence from work due to health problems can make obstacles to the growth of economy. This study conducted aimed to estimate the absenteeism costs of COVID-19 among the personnel of hospitals affiliated to Mashhad University of Medical Sciences in Mashhad, Iran.

Methods

This cross-sectional study was conducted between February 19, 2020, and September 21, 2020. The absenteeism costs were calculated using the human capital approach. Finally, we applied the linear regression to assess the impact of variables on the lost productivity of absenteeism due to COVID-19 among the personnel of hospitals affiliated to Mashhad University of Medical Sciences.

Results

The results of this study showed that 1958 personnel had COVID-19. The total of absenteeism days in our study were 32,209 days, with an average of 16.44 absenteeism days. Total costs due to absenteeism were estimated to be nearly $1.3 million, with an average of $671.4 per patient. The results of regression model showed that gender (male), age (> 50 years), employment Type (non-permanent) and monthly income had a positive relationship with the absenteeism cost. Also, there are a negative significant relationship between absenteeism cost with job (physicians) and work experience.

Conclusions

Absenteeism costs of COVID-19 in the hospitals of Mashhad University of Medical Sciences represent a significant economic burden. The findings of our study emphasize the emergency strategies to prevent and control COVID-19 among the healthcare workers. It can decrease the economic impacts of COVID-19 and improve human resources management during the COVID-19 pandemic.

COVID-19, body mass index and cholesterol: an ecological study using global data

Background

Coronavirus disease 2019 (COVID-19) is now globally considered a serious economic, social and health threat. A wide range of health related factors including Body Mass Index (BMI) is reported to be associated with the disease. In the present study, we analyzed global databases to assess the correlation of BMI and cholesterol with the risk of COVID-19.

Methods

In this ecological study, we used age-standardized BMI and cholesterol levels as well as the incidence and mortality ratio of COVID-19 at the national-levels obtained from the publicly available databases such as the World Health Organization (WHO) and NCD Risk Factor Collaboration (NCD-RisC). Bivariate correlation analysis was applied to assess the correlations between the study variables. Mean differences (standard deviation: SD) of BMI and cholesterol levels of different groups were tested using independent sample t-test or Mann–Whitney rank test as appropriate. Multivariable linear regression analysis was performed to identify variables affecting the incidence and mortality ratio of COVID-19.

Results

Incidence and mortality ratio of COVID-19 were significantly higher in developed (29,639.85 ± 20,210.79 for cases and 503.24 ± 414.65 for deaths) rather than developing (8153.76 ± 11,626.36 for cases and 169.95 ± 265.78 for deaths) countries (P < 0.01). Results indicated that the correlations of BMI and cholesterol level with COVID-19 are stronger in countries with younger population. In general, the BMI and cholesterol level were positively correlated with COVID-19 incidence ratio (β = 2396.81 and β = 30,932.80, p < 0.01,‌ respectively) and mortality ratio (β = 38.18 and β = 417.52, p < 0.05,‌ respectively) after adjusting for socioeconomic and demographic factors.

Conclusion

Countries with higher BMI or cholesterol at aggregate levels had a higher ratios of COVID-19 incidence and mortality. The aggregated level of cholesterol and BMI are important risk factors for COVID-19 major outcomes, especially in developing countries with younger populations. We recommend monitoring and promotion of health indicices to better prevent morbidity and mortality of COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11715-7.

COVID-19 and environmental concerns: A rapid review

COVID-19 has slowed global economic growth and consequently impacted the environment as well. Parallelly, the environment also influences the transmission of this novel coronavirus through various factors. Every nation deals with varied population density and size; air quality and pollutants; the nature of land and water, which significantly impact the transmission of coronavirus. The WHO (Ziaeepour et al., 2008) [1] has recommended rapid reviews to provide timely evidence to the policymakers to respond to the emergency. The present study follows a rapid review along with a brief bibliometric analysis of 328 research papers, which synthesizes the evidence regarding the environmental concerns of COVID-19. The novel contribution of this rapid review is threefold. One, we take stock of the diverse findings as regards the transmission of the novel coronavirus in different types of environments for providing conclusive directions to the ongoing debate regarding the transmission of the virus. Two, our findings provide topical insights as well as methodological guidance for future researchers in the field. Three, we inform the policymakers on the efficacy of environmental measures for controlling the spread of COVID-19.

COVID-19 Reveals Vulnerabilities of the Food-Energy-Water Nexus to Viral Pandemics

Food, energy, and water (FEW) sectors are inextricably linked, making one sector vulnerable to disruptions in another. Interactions between FEW systems, viral pandemics, and human health have not been widely studied. We mined scientific and news/media articles for causal relations among FEW and COVID-19 variables and qualitatively characterized system dynamics. Food systems promoted the emergence and spread of COVID-19, leading to illness and death. Major supply-side breakdowns were avoided (likely due to low morbidity/mortality among working-age people). However, COVID-19 and physical distancing disrupted labor and capital inputs and stressed supply chains, while creating economic insecurity among the already vulnerable poor. This led to demand-side FEW insecurities, in turn increasing susceptibility to COVID-19 among people with many comorbidities. COVID-19 revealed trade-offs such as allocation of water to hygiene versus to food production and disease burden avoided by physical distancing versus disease burden from increased FEW insecurities. News/media articles suggest great public interest in FEW insecurities triggered by COVID-19 interventions among individuals with low COVID-19 case-fatality rates. There is virtually no quantitative analysis of any of these trade-offs or feedbacks. Enhanced quantitative FEW and health models are urgently needed as future pandemics are likely and may have greater morbidity and mortality than COVID-19.

Effects of air pollution and climatology on COVID-19 mortality in Spain

The health, economic, and social impact of COVID-19 has been significant across the world. Our objective was to evaluate the association between air pollution (through NO2 and PM2.5 levels) and COVID-19 mortality in Spanish provinces from February 3, 2020, to July 14, 2020, adjusting for climatic parameters. An observational and ecological study was conducted with information extracted from Datadista repository (Datadista, 2020). Air pollutants (NO2 and PM2.5 levels) were analyzed as potential determinants of COVID-19 mortality. Multilevel Poisson regression models were used to analyze the risk of mortality after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Models were adjusted by four climatic variables (hours of solar radiation, precipitation, daily temperature and wind speed) and population size. The mean levels of PM2.5 and NO2 across all provinces and time in Spain were 8.7 μg/m3 (SD 9.7) and 8.7 μg/m3 (SD 6.2), respectively. High levels of PM2.5 (IRR = 1.016, 95% CI: 1.007-1.026), NO2 (IRR = 1.066, 95% CI: 1.058-1.075) and precipitation (IRRNO2 = 0.989, 95% CI: 0.981-0.997) were positively associated with COVID-19 mortality, whereas temperature (IRRPM2.5 = 0.988, 95% CI: 0.976-1.000; and IRRNO2 = 0.771, 95% CI: 0.761-0.782, respectively) and wind speed (IRRNO2 = 1.095, 95% CI: 1.061-1.131) were negatively associated with COVID-19 mortality. Air pollution can be a key factor to understand the mortality rate for COVID-19 in Spain. Furthermore, climatic variables could be influencing COVID-19 progression. Thus, air pollution and climatology ought to be taken into consideration in order to control the pandemic.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11869-021-01062-2.

Impact of COVID-19 lockdown on NO2 and PM2.5 exposure inequalities in London, UK

Amid the COVID-19 pandemic, a nationwide lockdown was imposed in the United Kingdom (UK) on March 23, 2020. These sudden control measures led to radical changes in human activities in the Greater London Area (GLA). During this lockdown, transportation use was significantly reduced and non-key workers were required to work from home. This study aims to understand how population exposure to PM2.5 and NO2 changed spatially and temporally across London, in different microenvironments, following the lockdown period relative to the previous three-year average in the same calendar period. Our research shows that population exposure to NO2 declined significantly (52.3% ± 6.1%), while population exposure to PM2.5 showed a smaller relative reduction (15.7% ± 4.1%). Changes in population activity had the strongest relative influence on exposure levels during morning rush hours, when prior to the lockdown a large percentage of people would normally commute or be at the workplace. In particular, a very high exposure decrease was observed for both pollutants (approximately 66% for NO2 and 19% for PM2.5) at 08:00am, consistent with the radical changes in population commuting. The infiltration of outdoor air pollution into housing modifies the degree of exposure change both temporally and spatially. Moreover, this study shows that the impacts on air pollution exposure vary across groups with different socioeconomic status (SES), with a disproportionate positive effect on the areas of the city home to more economically deprived communities.

Investigating the drivers of the spatio-temporal heterogeneity in COVID-19 hospital incidence-Belgium as a study case

BACKGROUND

The COVID-19 pandemic is affecting nations globally, but with an impact exhibiting significant spatial and temporal variation at the sub-national level. Identifying and disentangling the drivers of resulting hospitalisation incidence at the local scale is key to predict, mitigate and manage epidemic surges, but also to develop targeted measures. However, this type of analysis is often not possible because of the lack of spatially-explicit health data and spatial uncertainties associated with infection.

METHODS

To overcome these limitations, we propose an analytical framework to investigate potential drivers of the spatio-temporal heterogeneity in COVID-19 hospitalisation incidence when data are only available at the hospital level. Specifically, the approach is based on the delimitation of hospital catchment areas, which allows analysing associations between hospitalisation incidence and spatial or temporal covariates. We illustrate and apply our analytical framework to Belgium, a country heavily impacted by two COVID-19 epidemic waves in 2020, both in terms of mortality and hospitalisation incidence.

RESULTS

Our spatial analyses reveal an association between the hospitalisation incidence and the local density of nursing home residents, which confirms the important impact of COVID-19 in elderly communities of Belgium. Our temporal analyses further indicate a pronounced seasonality in hospitalisation incidence associated with the seasonality of weather variables. Taking advantage of these associations, we discuss the feasibility of predictive models based on machine learning to predict future hospitalisation incidence.

CONCLUSION

Our reproducible analytical workflow allows performing spatially-explicit analyses of data aggregated at the hospital level and can be used to explore potential drivers and dynamic of COVID-19 hospitalisation incidence at regional or national scales.

Spatial temporal distribution of COVID-19 risk during the early phase of the pandemic in Malawi

BACKGROUND

COVID-19 has been one of the greatest challenges the world has faced since the second world war. This study aimed at investigating the distribution of COVID-19 in both space and time in Malawi.

METHODS

The study used publicly available data of COVID-19 cases for the period from 2 April 2020 to 28 October 2020. Semiparametric spatial temporal models were fitted to the number of monthly confirmed cases as an outcome data, with time and district as independent variables, where district was the spatial unit, while accounting for sociodemographic factors.

RESULTS

The study found significant effects of location and time, with the two interacting. The spatial distribution of COVID-19 risk showed major cities being at greater risk than rural areas. Over time, the COVID-19 risk was increasing then decreasing in most districts with the rural districts being consistently at lower risk. High proportion of elderly people was positively associated with COVID-19 risk (β = 1.272, 95% CI [0.171, 2.370]) than low proportion of elderly people. There was negative association between poverty incidence and COVID-19 risk (β = -0.100, 95% CI [-0.136, -0.065]).

CONCLUSION

Future or present strategies to limit the spread of COVID-19 should target major cities and the focus should be on time periods that had shown high risk. Furthermore, the focus should be on elderly and rich people.

Macrolevel association of COVID-19 with non-communicable disease risk factors in India

BACKGROUND & AIMS

Greater COVID-19 related mortality has been reported among persons with various non-communicable diseases (NCDs). We performed an ecological study to determine the association of state-level cases and deaths with NCD risk factors and healthcare and social indices.

METHODS

We obtained cumulative national and state-level data on COVID-19 cases and deaths from publicly available database www.covid19india.org from February to end November 2020. To identify association with major NCD risk factors, NCDs, healthcare related and social variables we obtained data from public sources. Association was determined using univariate and multivariate statistics.

RESULTS

More than 9.5 million COVID-19 cases and 135,000 deaths have been reported in India towards end of November 2020. There is significant positive correlation (Pearson r) of state-level COVID-19 cases and deaths per million, respectively, with NCD risk factors- obesity (0.64, 0.52), hypertension (0.28, 0.16), diabetes (0.66, 0.46), NCD epidemiological transition index (0.58, 0.54) and ischemic heart disease mortality (0.22, 0.33). Correlation is also observed with indices of healthcare access and quality (0.71, 0.61), urbanization (0.75, 0.73) and human (0.61, 0.56) and sociodemographic (0.70, 0.69) development. Multivariate adjusted analyses shows strong correlation of COVID-19 burden and deaths with NCD risk factors (r² = 0.51, 0.43), NCDs (r² = 0.32, 0.16) and healthcare (r² = 0.52, 0.38).

CONCLUSIONS

COVID-19 disease burden and mortality in India is ecologically associated with greater state-level burden of NCDs and risk factors, especially obesity and diabetes.