Are environmental pollution and biodiversity levels associated to the spread and mortality of COVID-19? A four-month global analysis

Biodiversity and human health: A scoping review and examples of underrepresented linkages

Mounting evidence supports the connections between exposure to environmental typologies(such as green and blue spaces)and human health. However, the mechanistic links that connect biodiversity (the variety of life) and human health, and the extent of supporting evidence remain less clear. Here, we undertook a scoping review to map the links between biodiversity and human health and summarise the levels of associated evidence using an established weight of evidence framework. Distinct from other reviews, we provide additional context regarding the environment-microbiome-health axis, evaluate the environmental buffering pathway (e.g., biodiversity impacts on air pollution), and provide examples of three under- or minimally-represented linkages. The examples are (1) biodiversity and Indigenous Peoples' health, (2) biodiversity and urban social equity, and (3) biodiversity and COVID-19. We observed a moderate level of evidence to support the environmental microbiota-human health pathway and a moderate-high level of evidence to support broader nature pathways (e.g., greenspace) to various health outcomes, from stress reduction to enhanced wellbeing and improved social cohesion. However, studies of broader nature pathways did not typically include specific biodiversity metrics, indicating clear research gaps. Further research is required to understand the connections and causative pathways between biodiversity (e.g., using metrics such as taxonomy, diversity/richness, structure, and function) and health outcomes. There are well-established frameworks to assess the effects of broad classifications of nature on human health. These can assist future research in linking biodiversity metrics to human health outcomes. Our examples of underrepresented linkages highlight the roles of biodiversity and its loss on urban lived experiences, infectious diseases, and Indigenous Peoples' sovereignty and livelihoods. More research and awareness of these socioecological interconnections are needed.

Short-term exposure to air pollution and hospital admission after COVID-19 in Catalonia: the COVAIR-CAT study

BACKGROUND

A growing body of evidence has reported positive associations between long-term exposure to air pollution and poor COVID-19 outcomes. Inconsistent findings have been reported for short-term air pollution, mostly from ecological study designs. Using individual-level data, we studied the association between short-term variation in air pollutants [nitrogen dioxide (NO2), particulate matter with a diameter of <2.5 µm (PM2.5) and a diameter of <10 µm (PM10) and ozone (O3)] and hospital admission among individuals diagnosed with COVID-19.

METHODS

The COVAIR-CAT (Air pollution in relation to COVID-19 morbidity and mortality: a large population-based cohort study in Catalonia, Spain) cohort is a large population-based cohort in Catalonia, Spain including 240 902 individuals diagnosed with COVID-19 in the primary care system from 1 March until 31 December 2020. Our outcome was hospitalization within 30 days of COVID-19 diagnosis. We used individual residential address to assign daily air-pollution exposure, estimated using machine-learning methods for spatiotemporal prediction. For each pandemic wave, we fitted Cox proportional-hazards models accounting for non-linear-distributed lagged exposure over the previous 7 days.

RESULTS

Results differed considerably by pandemic wave. During the second wave, an interquartile-range increase in cumulative weekly exposure to air pollution (lag0_7) was associated with a 12% increase (95% CI: 4% to 20%) in COVID-19 hospitalizations for NO2, 8% (95% CI: 1% to 16%) for PM2.5 and 9% (95% CI: 3% to 15%) for PM10. We observed consistent positive associations for same-day (lag0) exposure, whereas lag-specific associations beyond lag0 were generally not statistically significant.

CONCLUSIONS

Our study suggests positive associations between NO2, PM2.5 and PM10 and hospitalization risk among individuals diagnosed with COVID-19 during the second wave. Cumulative hazard ratios were largely driven by exposure on the same day as hospitalization.

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.

Ecosystem degradation and the spread of Covid-19

The linkages between the emergence of zoonotic diseases and ecosystem degradation have been widely acknowledged by the scientific community and policy makers. In this paper we investigate the relationship between human overexploitation of natural resources, represented by the Human Appropriation of Net Primary Production Index (HANPP) and the spread of Covid-19 cases during the first pandemic wave in 730 regions of 63 countries worldwide. Using a Bayesian estimation technique, we highlight the significant role of HANPP as a driver of Covid-19 diffusion, besides confirming the well-known impact of population size and the effects of other socio-economic variables. We believe that these findings could be relevant for policy makers in their effort towards a more sustainable intensive agriculture and responsible urbanisation.

A Literature Review of the Effects of Air Pollution on COVID-19 Health Outcomes Worldwide: Statistical Challenges and Data Visualization

Several peer-reviewed papers and reviews have examined the relationship between exposure to air pollution and COVID-19 spread and severity. However, many of the existing reviews on this topic do not extensively present the statistical challenges associated with this field, do not provide comprehensive guidelines for future researchers, and review only the results of a relatively small number of papers. We reviewed 139 papers, 127 of which reported a statistically significant positive association between air pollution and adverse COVID-19 health outcomes. Here, we summarize the evidence, describe the statistical challenges, and make recommendations for future research. To summarize the 139 papers with data from geographical locations around the world, we also present anopen-source data visualization tool that summarizes these studies and allows the research community to contribute evidence as new research papers are published.

Climatic and Environmental Factors Influencing COVID-19 Transmission-An African Perspective

Since the outbreak of COVID-19 was decreed by the World Health Organization as a public health emergency of worldwide concern, the epidemic has drawn attention from all around the world. The disease has since spread globally in developed and developing countries. The African continent has not been spared from the pandemic; however, the low number of cases in Africa compared to developed countries has brought about more questions than answers. Africa is known to have a poor healthcare system that cannot sustain the emerging infectious disease pandemic. This study explored climatic and environmental elements influencing COVID-19 transmission in Africa. This study involved manuscripts and data that evaluated and investigated the climatic and environmental elements of COVID-19 in African countries. Only articles written in English were considered in the systematic review. Seventeen articles and one database were selected for manuscript write-ups after the review process. The findings indicated that there is evidence that suggests the influence of climatic and environmental elements on the spread of COVID-19 in the continent of Africa; however, the evidence needs more investigation in all six regions of Africa and at the country level to understand the role of weather patterns and environmental aspects in the transmission of COVID-19.

An overview and thematic analysis of research on cities and the COVID-19 pandemic: Toward just, resilient, and sustainable urban planning and design

Since early 2020, researchers have made efforts to study various issues related to cities and the pandemic. Despite the wealth of research on this topic, there are only a few review articles that explore multiple issues related to it. This is partly because of the rapid pace of publications that makes systematic literature review challenging. To address this issue, in the present study, we rely on bibliometric analysis techniques to gain an overview of the knowledge structure and map key themes and trends of research on cities and the pandemic. Results of the analysis of 2,799 articles show that research mainly focuses on six broad themes: air quality, meteorological factors, built environment factors, transportation, socio-economic disparities, and smart cities, with the first three being dominant. Based on the findings, we discuss major lessons that can be learned from the pandemic and highlight key areas that need further research.

Wealth, health, and beyond: Is COVID-19 less likely to spread in rich neighborhoods?

Since December 2019, the COVID-19 pandemic has quickly spread across the world. The traditional understanding of the relationship between wealth and the spread of contagious diseases is that similar to many precedent epidemics, the pandemic spread easily in poor neighborhoods in many countries. The environmental and socioeconomic implications of the COVID-19 pandemic are still poorly understood, thus this paper examines the relationship between neighborhood characteristics and the spread of the pandemic through a case study of Shenzhen, a Chinese megacity with many low-income rural migrants. The major finding is that wealthier and larger neighborhoods in Shenzhen were more likely to be infected in the first wave of the pandemic in 2020. This spread pattern is likely to result from China’s strict control to prevent the pandemic, human mobility, and demographic characteristics such as income. This finding reveals a new phenomenon that contrasts with the traditional understanding of the influence of wealth on the spread of epidemics. This paper enriches the understanding of the role of neighborhoods in the spread of the pandemic, and it has important public policy implications.

Impacts of air pollution on COVID-19 case fatality rate: a global analysis

The coronavirus disease 2019 (COVID-19) pandemic is still rapidly spreading globally. To probe high-risk cities and the impacts of air pollution on public health, this study explores the relationship between the long-term average concentration of air pollution and the city-level case fatality rate (CFR) of COVID-19 globally. Then, geographically weighted regression (GWR) is applied to examine the spatial variability of the relationships. Six air pollution factors, including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), PM_2.5 (particles with diameter ≤2.5 μm), PM₁₀ (particles with diameter ≤10 μm), and air quality index (AQI), are positively associated with the city-level COVID-19 CFR. Our results indicate that a 1-unit increase in NO₂ (part per billion, PPB), SO₂ (PPB), O₃ (PPB), PM_2.5 (microgram per cubic meter, μg/m³), PM₁₀ (μg/m³), AQI (score), is related to a 1.450%, 1.005%, 0.992%, 0.860%, 0.568%, and 0.776% increase in the city-level COVID-19 CFR, respectively. Additionally, the effects of NO₂, O₃, PM_2.5, AQI, and probability of living with poor AQI on COVID-19 spatially vary in view of the estimation of the GWR. In other words, the adverse impacts of air pollution on health are different among the cities. In summary, long-term exposure to air pollution is negatively related to the COVID-19 health outcome, and the relationship is spatially non-stationary. Our research sheds light on the impacts of slashing air pollution on public health in the COVID-19 pandemic to help governments formulate air pollution policies in light of the local situations.

Effects of country success on COVID-19 cumulative cases and excess deaths in 169 countries

COVID-19 has caused over 260 million confirmed cases and over 5 million deaths globally. The results of statistical and multiple criteria analyses on the success of 169 countries and on COVID-19 cumulative cases and excess deaths show that the prosperity of a country relates directly to the consequences due to the pandemic. The topic of this article is the Country Success and COVID-19 (CSC) Map of the World. As a country's success grows, this map shows how cumulative cases of COVID-19 increase; at the same time, excess deaths decrease. The indicators in the system of criteria regarding country success and sustainability are interrelated. Conditional country successes remain quite similar, despite changes to the numbers of countries and their indicators. Likewise, the seven clusters of countries under consideration group together independently of which system of indicators had been applied for their analysis. The 2020 Inglehart-Welzel Cultural Map of the World, which is grounded on surveys, and the CSC Map, which is grounded on statistical indicators, have axes that correlate with one another significantly. The CSC Map Model explains over 63% of the dispersions pertinent to COVID-19 cumulative cases, over 52% of COVID-19 excess deaths, and over 95% of country success variables. The layout of the clusters on the CSC Map changes little over time. Upon performance of the correlation analysis, it was established that strong and statistically significant relationships exist between 169 countries success and sustainability linked with their current air quality score (r = 0.602, p < 0.01) and the environmental performance index (EPI) score (r = 0.931, p < 0.01). The results obtained show that when a country's EPI score and current air quality improve by 1%, excess deaths decrease, respectively, by 2.33 and 1.55%. Global integrated analysis on country successes, COVID-19 cumulative cases, and excess deaths comprise this study.

Local environmental quality and heterogeneity in an OLG agent-based model with spatial externalities

Most of the theoretical contributions on the relationship between economy and environment assume the environment as a good distributed homogeneously among agents. The aim of this work is to relax this hypothesis and to consider that the environment can have a local character even if conditioned through externalities by the choices made at the global level. In this article, we adapt the classical framework introduced in John and Pecchenino (Econ J 104(427):1393-1410, 1994) to analyze the dynamic relationship between environment and economic process, and we propose an OLG agent-based model where each agent perceives her own level of environmental quality determined by her own decisions, and by the decisions of those living around her. Despite the attention devoted to local environmental aspects, network externalities (determined through the scheme of Moore neighborhoods) play a fundamental role in defining environmental dynamics and they may induce the emergence of cyclical dynamics. The occurrence of oscillations in the local environmental quality is partially mitigated by the presence of heterogeneity in individuals' preferences. Finally, when a centralized planner is introduced, the dynamics converge to stationary values regardless of the assumption on heterogeneity of agents.

COVID-19 Mortality in Europe, by Latitude and Obesity Status: A Geo-Spatial Analysis in 40 Countries

On 30 January 2020, the World Health Organization (WHO) declared the current novel coronavirus disease 2019 (COVID-19) as a public health emergency of international concern and later characterized it as a pandemic. New data show that excess body mass and vitamin D deficiency might be related to the disease severity and mortality. The aim of this study was to evaluate whether latitude, as a proxy of sunlight exposure and Vitamin D synthesis, and prevalent obesity among European populations, is related to COVID-19 spread and severity. European COVID-19 data (incidence and fatality), including information on the prevalence of obesity, social distancing, and others were obtained by the "Our World in Data" website on 17 April 2021. Adjusted analysis showed that higher COVID-19 incidence and fatality were pictured in countries being in higher latitude, both during the whole period, as well as, during the time period 1 November 2020-31 March 2021. Higher incidence and fatality of COVID-19 were observed where the prevalence of overweight/obesity was higher during the whole time period, whereas during the time period 1 November 2020-31 March 2021, only COVID-19 incidence was higher but not a fatality. The present results provide insights for targeted interventions and preventive strategies against COVID-19.

COVID-19 Propagation Model Based on Economic Development and Interventions

In order to understand the influencing factors affecting the COVID-19 propagation, and analyze the development trend of the epidemic situation in the world, COVID-19 propagation model to simulate the COVID-19 propagation in the population is proposed in this paper. First of all, this paper analyzes the economic factors and interventions affecting the COVID-19 propagation in various different countries. Then, the touch number for COVID-19 High-risk Population Dynamic Network in this paper was redefined, and it predicts and analyzes the development trend of the epidemic situation in different countries. The simulation data and the published confirmed data by the world health organization could fit well, which also verified the reliability of the model. Finally, this paper also analyzes the impact of public awareness of prevention on the control of the epidemic. The analysis shows that increasing the awareness of prevention, timely and early adoption of protective measures such as wearing masks, and reducing travel can greatly reduce the risk of infection and the outbreak scale.

Positive association between outdoor air pollution and the incidence and severity of COVID-19. A review of the recent scientific evidences

In June 2020, we published a review focused on assessing the influence of various air pollutants on the transmission of SARS-CoV-2, and the severity of COVID-19 in patients infected by the coronavirus. The results of most of those reviewed studies suggested that chronic exposure to certain air pollutants might lead to more severe and lethal forms of COVID-19, as well as delays/complications in the recovery of the patients. Since then, a notable number of studies on this topic have been published, including also various reviews. Given the importance of this issue, we have updated the information published since our previous review. Taking together the previous results and those of most investigations now reviewed, we have concluded that there is a significant association between chronic exposure to various outdoor air pollutants: PM_2.5, PM₁₀, O₃, NO₂, SO₂ and CO, and the incidence/risk of COVID-19 cases, as well as the severity/mortality of the disease. Unfortunately, studies on the potential influence of other important air pollutants such as VOCs, dioxins and furans, or metals, are not available in the scientific literature. In relation to the influence of outdoor air pollutants on the transmission of SARS-CoV-2, although the scientific evidence is much more limited, some studies point to PM_2.5 and PM₁₀ as potential airborne transmitters of the virus. Anyhow, it is clear that environmental air pollution plays an important negative role in COVID-19, increasing its incidence and mortality.

Heterogeneity in the Effectiveness of Non-pharmaceutical Interventions During the First SARS-CoV2 Wave in the United States

Background: Attempts to quantify effect sizes of non-pharmaceutical interventions (NPI) to control COVID-19 in the US have not accounted for heterogeneity in social or environmental factors that may influence NPI effectiveness. This study quantifies national and sub-national effect sizes of NPIs during the early months of the pandemic in the US.

Methods: Daily county-level COVID-19 cases and deaths during the first wave (January 2020 through phased removal of interventions) were obtained. County-level cases, doubling times, and death rates were compared to four increasingly restrictive NPI levels. Socio-demographic, climate and mobility factors were analyzed to explain and evaluate NPI heterogeneity, with mobility used to approximate NPI compliance. Analyses were conducted separately for the US and for each Census regions (Pacific, Mountain, east/West North Central, East/West South Central, South Atlantic, Middle Atlantic and New England). A stepped-wedge cluster-randomized trial analysis was used, leveraging the phased implementation of policies.

Results: Aggressive (level 4) NPIs were associated with slower COVID-19 propagation, particularly in high compliance counties. Longer duration of level 4 NPIs was associated with lower case rates (log beta −0.028, 95% CI −0.04 to −0.02) and longer doubling times (log beta 0.02, 95% CI 0.01–0.03). Effects varied by Census region, for example, level 4 effects on doubling time in Pacific states were opposite to those in Middle Atlantic and New England states. NPI heterogeneity can be explained by differential timing of policy initiation and by variable socio-demographic county characteristics that predict compliance, particularly poverty and racial/ethnic population. Climate exhibits relatively consistent relationships across Census regions, for example, higher minimum temperature and specific humidity were associated with lower doubling times and higher death rates for this period of analysis in South Central, South Atlantic, Middle Atlantic, and New England states.

Conclusion and Relevance: Heterogeneity exists in both the effectiveness of NPIs across US Census regions and policy compliance. This county-level variability indicates that control strategies are best designed at community-levels where policies can be tuned based on knowledge of local disparities and compliance with public health ordinances.

Dilution effects in disease ecology

For decades, people have reduced the transmission of pathogens by adding low‐quality hosts to managed environments like agricultural fields. More recently, there has been interest in whether similar ‘dilution effects’ occur in natural disease systems, and whether these effects are eroded as diversity declines. For some pathogens of plants, humans and other animals, the highest‐quality hosts persist when diversity is lost, so that high‐quality hosts dominate low‐diversity communities, resulting in greater pathogen transmission. Meta‐analyses reveal that these natural dilution effects are common. However, studying them remains challenging due to limitations on the ability of researchers to manipulate many disease systems experimentally, difficulties of acquiring data on host quality and confusion about what should and should not be considered a dilution effect. Because dilution effects are widely used in managed disease systems and have been documented in a variety of natural disease systems, their existence should not be considered controversial. Important questions remain about how frequently they occur and under what conditions to expect them. There is also ongoing confusion about their relationships to both pathogen spillover and general biogeographical correlations between diversity and disease, which has resulted in an inconsistent and confusing literature. Progress will require rigorous and creative research.

Multivariate Analysis of Risk Factors of the COVID-19 Pandemic in the Community of Madrid, Spain

It has been more than one year since Chinese authorities identified a deadly new strain of coronavirus, SARS-CoV-2. Since then, the scientific work regarding the transmission risk factors of COVID-19 has been intense. The relationship between COVID-19 and environmental conditions is becoming an increasingly popular research topic. Based on the findings of the early research, we focused on the community of Madrid, Spain, which is one of the world's most significant pandemic hotspots. We employed different multivariate statistical analyses, including principal component analysis, analysis of variance, clustering, and linear regression models. Principal component analysis was employed in order to reduce the number of risk factors down to three new components that explained 71% of the original variance. Cluster analysis was used to delimit the territory of Madrid according to these new risk components. An ANOVA test revealed different incidence rates between the territories delimited by the previously identified components. Finally, a set of linear models was applied to demonstrate how environmental factors present a greater influence on COVID-19 infections than socioeconomic dimensions. This type of local research provides valuable information that could help societies become more resilient in the face of future pandemics.

Comparison of positive SARS-CoV-2 incidence rate with environmental and socioeconomic factors in northern Illinois

Early studies showed positive associations fine particulate matter (PM2.5), course particulate matter PM10, nitrogen dioxide (NO2) and Ozone (O3) concentrations with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) confirmed cases in the United States. One study showed that a1 μg/m3 increase in PM2.5 is associated with an 8% increase in the COVID-19 death rate. Specifically, Chicago and surrounding suburbs have been labeled hot spots in the United States and correlation with air pollutants concentration will help identify specific communities most at risk. A number of studies have identified demographic variables associated with increased positive SARS-CoV-2 and the importance of air quality and socioeconomic factors must be further understood for more targeted public health responses. The results of this analysis noted positive relationships between zip code SARS-CoV-2 incidence rate and environmental and demographic EJ indicators. Evaluation of race and SARS-CoV-2 incidence rate at the zip code level found positive moderate correlations for ethnic minority individuals.

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.

Estimating the COVID-19 Spread Through Real-time Population Mobility Patterns: Surveillance in Low- and Middle-Income Countries

Background

On January 21, 2020, the World Health Organization reported the first case of severe acute respiratory syndrome coronavirus 2, which rapidly evolved to the COVID-19 pandemic. Since then, the virus has also rapidly spread among Latin American, Caribbean, and African countries.

Objective

The first aim of this study is to identify new emerging COVID-19 clusters over time and space (from January 21 to mid-May 2020) in Latin American, Caribbean, and African regions, using a prospective space–time scan measurement approach. The second aim is to assess the impact of real-time population mobility patterns between January 21 and May 18, 2020, under the implemented government interventions, measurements, and policy restrictions on COVID-19 spread among those regions and worldwide.

Methods

We created a global COVID-19 database, of 218 countries and territories, merging the World Health Organization daily case reports with other measures such as population density and country income levels for January 21 to May 18, 2020. A score of government policy interventions was created for low, intermediate, high, and very high interventions. The population’s mobility patterns at the country level were obtained from Google community mobility reports. The prospective space–time scan statistic method was applied in five time periods between January and May 2020, and a regression mixed model analysis was used.

Results

We found that COVID-19 emerging clusters within these five periods of time increased from 7 emerging clusters to 28 by mid-May 2020. We also detected various increasing and decreasing relative risk estimates of COVID-19 spread among Latin American, Caribbean, and African countries within the period of analysis. Globally, population mobility to parks and similar leisure areas during at least a minimum of implemented intermediate-level control policies (when compared to low-level control policies) was related to accelerated COVID-19 spread. Results were almost consistent when regional stratified analysis was applied. In addition, worldwide population mobility due to working during high implemented control policies and very high implemented control policies, when compared to low-level control policies, was related to positive COVID-19 spread.

Conclusions

The prospective space–time scan is an approach that low-income and middle-income countries could use to detect emerging clusters in a timely manner and implement specific control policies and interventions to slow down COVID-19 transmission. In addition, real-time population mobility obtained from crowdsourced digital data could be useful for current and future targeted public health and mitigation policies at a global and regional level.

SARS-CoV-2 and other main pathogenic microorganisms in the environment: Situation in Galicia and Spain

In the context of the current COVID-19 pandemic, and mostly taking a broad perspective, it is clearly relevant to study environmental factors that could affect eventual future outbreaks due to coronaviruses and/or other pathogenic microorganisms. In view of that, the authors of this manuscript review the situation of SARS-CoV-2 and other main pathogenic microorganisms in the environment, focusing on Galicia and Spain. Overall, in addition to showing local data, it is put in evidence that, summed to all efforts being carried out to treat/control this and any other eventual future epidemic diseases, both at local and global levels, a deep attention should be paid to ecological/environmental aspects that have effects on the planet, its ecosystems and their relations/associations with the probability of spreading of eventual future pandemics.

An Italian individual-level data study investigating on the association between air pollution exposure and Covid-19 severity in primary-care setting

BACKGROUND

Several studies have been focusing on the potential role of atmospheric pollutants in the diffusion and impact on health of Covid-19. This study's objective was to estimate the association between ≤10 μm diameter particulate matter (PM10) exposure and the likelihood of experiencing pneumonia due to Covid-19 using individual-level data in Italy.

METHODS

Information on Covid-19 patients was retrieved from the Italian IQVIA® Longitudinal Patient Database (LPD), a computerized network of general practitioners (GPs) including anonymous data on patients' consultations and treatments. All patients with a Covid-19 diagnosis during March 18th, 2020 - June 30th, 2020 were included in the study. The date of first Covid-19 registration was the starting point of the 3-month follow-up (Index Date). Patients were classified based on Covid-19-related pneumonia registrations on the Index date and/or during follow-up presence/absence. Each patient was assigned individual exposure by calculating average PM10 during the 30-day period preceding the Index Date, and according to GP's office province. A multiple generalized linear mixed model, mixed-effects logistic regression, was used to assess the association between PM10 exposure tertiles and the likelihood of experiencing pneumonia.

RESULTS

Among 6483 Covid-19 patients included, 1079 (16.6%) had a diagnosis of pneumonia. Pneumonia patients were older, more frequently men, more health-impaired, and had a higher individual-level exposure to PM10 during the month preceding Covid-19 diagnosis. The mixed-effects model showed that patients whose PM10 exposure level fell in the second tertile had a 30% higher likelihood of having pneumonia than that of first tertile patients, and the risk for those who were in the third tertile was almost doubled.

CONCLUSION

The consistent findings toward a positive association between PM10 levels and the likelihood of experiencing pneumonia due to Covid-19 make the implementation of new strategies to reduce air pollution more and more urgent.

COVID-19 and air pollution in Vienna-a time series approach

We performed a time series analysis in Vienna, Austria, investigating the temporal association between daily air pollution (nitrogen dioxide, NO₂ and particulate matter smaller than 10 µm, PM10) concentration and risk of coronavirus disease 2019 (COVID-19) infection and death. Data covering about 2 months (March–April 2020) were retrieved from public databases. Infection risk was defined as the ratio between infected and infectious. In a separate sensitivity analysis different models were applied to estimate the number of infectious people per day. The impact of air pollution was assessed through a linear regression on the natural logarithm of infection risk. Risk of COVID-19 mortality was estimated by Poisson regression. Both pollutants were positively correlated with the risk of infection with the coefficient for NO₂ being 0.032 and for PM10 0.014. That association was significant for the irritant gas (p = 0.012) but not for particles (p = 0.22). Pollutants did not affect COVID-19-related mortality. The study findings might have wider implications on an interaction between air pollution and infectious agents.

Effectiveness of Face Coverings in Mitigating the COVID-19 Pandemic in the United States

The COVID-19 pandemic has been one of the biggest public health challenges of the 21st century. Many prevalent measures have been taken to prevent its spread and protect the public. However, the use of face coverings as an effective preventive measure remains contentious. The goal of the current study is to evaluate the effectiveness of face coverings as a protective measure. We examined the effectiveness of face coverings between 1 April and 31 December 2020. This was accomplished by analyzing trends of daily new COVID-19 cases, cumulative confirmed cases, and cases per 100,000 people in different U.S. states, including the District of Columbia. The results indicated a sharp change in trends after face covering mandates. For the 32 states with face covering mandates, 63% and 66% exhibited a downward trend in confirmed cases within 21 and 28 days of implementation, respectively. We estimated that face covering mandates in the 32 states prevented approximately 78,571 and 109,703 cases within 21- and 28-day periods post face covering mandate, respectively. A statistically significant (p = 0.001) negative correlation (-0.54) was observed between the rate of cases and days since the adoption of a face covering mandate. We concluded that the use of face coverings can provide necessary protection if they are properly used.

Next City: Learning from Cities during COVID-19 to Tackle Climate Change

Fundamental principles of modern cities and urban planning are challenged during the COVID-19 pandemic, such as the advantages of large city size, high density, mass transport, free use of public space, unrestricted individual mobility in cities. These principles shaped the development of cities and metropolitan areas for more than a century, but currently, there are signs that they have turned from advantage to liability. Cities Public authorities and private organisations responded to the COVID-19 crisis with a variety of policies and business practices. These countermeasures codify a valuable experience and can offer lessons about how cities can tackle another grand challenge, this of climate change. Do the measures taken during the COVID-19 crisis represent a temporal adjustment to the current health crisis? Or do they open new ways towards a new type of urban development more effective in times of environmental and health crises? We address these questions through literature review and three case studies that review policies and practices for the transformation of city ecosystems mostly affected by the COVID-19 pandemic: (a) the central business district, (b) the transport ecosystem, and (c) the tourism–hospitality ecosystem. We assess whether the measures implemented in these ecosystems shape new policy and planning models for higher readiness of cities towards grand challenges, and how, based on this experience, cities should be organized to tackle the grand challenge of environmental sustainability and climate change.