SARS-CoV-2 infection and air pollutants: Correlation or causation?

Lessons learnt for air pollution mitigation policies from the COVID-19 pandemic: The Italian perspective

Policies to improve air quality need to be based on effective plans for reducing anthropogenic emissions. In 2020, the outbreak of COVID-19 pandemic resulted in significant reductions of anthropogenic pollutant emissions, offering an unexpected opportunity to observe their consequences on ambient concentrations. Taking the national lockdown occurred in Italy between March and May 2020 as a case study, this work tries to infer if and what lessons may be learnt concerning the impact of emission reduction policies on air quality. Variations of NO2, O3, PM10 and PM2.5 concentrations were calculated from numerical model simulations obtained with business as usual and lockdown specific emissions. Both simulations were performed at national level with a horizontal resolution of 4 km, and at local level on the capital city Rome at 1 km resolution. Simulated concentrations showed a good agreement with in-situ observations, confirming the modelling systems capability to reproduce the effects of emission reductions on ambient concentration variations, which differ according to the individual air pollutant. We found a general reduction of pollutant concentrations except for ozone, that experienced an increase in Rome and in the other urban areas, and a decrease elsewhere. The obtained results suggest that acting on precursor emissions, even with sharp reductions like those experienced during the lockdown, may lead to significant, albeit complex, reduction patterns for secondary pollutant concentrations. Therefore, to be more effective, reduction measures should be carefully selected, involving more sectors than those related to mobility, such as residential and agriculture, and integrated on different scales.

Analytic modeling and risk assessment of aerial transmission of SARS-CoV-2 virus through vaping expirations in shared micro-environments

It is well known that airborne transmission of COVID-19 in indoor spaces occurs through various respiratory activities: breathing, vocalizing, coughing, and sneezing. However, there is a complete lack of knowledge of its possible transmission through exhalations of e-cigarette aerosol (ECA), which is also a respiratory activity. E-cigarettes have become widely popular among smokers seeking a much safer way of nicotine consumption than smoking. Due to restrictive lockdown measures taken during the COVID-19 pandemic, many smokers and vapers (e-cigarette users) were confined to shared indoor spaces, making it necessary to assess the risk of SARS-CoV-2 virus aerial transmission through their exhalations. We summarize inferred knowledge of respiratory particles emission and transport through ECA, as well as a theoretical framework for explaining the visibility of exhaled ECA, which has safety implications and is absent in other respiratory activities (apart from smoking). We also summarize and briefly discuss the effects of new SARS-CoV-2 variants, vaccination rates, and environmental factors that may influence the spread of COVID-19. To estimate the risk of SARS-CoV-2 virus aerial transmission associated with vaping exhalations, we adapt a theoretical risk model that has been used to analyze the risks associated with other respiratory activities in shared indoor spaces. We consider home and restaurant scenarios, with natural and mechanical ventilation, with occupants wearing and not wearing face masks. We consider as "control case" or baseline risk scenario an indoor space (home and restaurant) where respiratory droplets and droplet nuclei are uniformly distributed and aerial contagion risk might originate exclusively from occupants exclusively rest breathing, assuming this to be the only (unavoidable) respiratory activity they all carry on. If an infected occupant uses an e-cigarette in a home or restaurant scenarios, bystanders not wearing face masks exposed to the resulting ECA expirations face a [Formula: see text] increase of risk of contagion with respect the control case. This relative added risk with respect to the control case becomes [Formula: see text] for high-intensity vaping, [Formula: see text], and over [Formula: see text] for speaking for various periods or coughing (all without vaping). Infectious emissions are significantly modified by mechanical ventilation, face mask usage, vaccination, and environmental factors, but given the lack of empiric evidence, we assume as a working hypothesis that all basic parameters of respiratory activities are equally (or roughly equally) affected by these factors. Hence, the relative risk percentages with respect to the control state should remain roughly the same under a wide range of varying conditions. By avoiding direct exposure to the visible exhaled vaping jet, wearers of commonly used face masks are well protected from respiratory droplets and droplet nuclei directly emitted by mask-less vapers. Compared to the control case of an already existing (unavoidable) risk from continuous breathing, vaping emissions in shared indoor spaces pose just a negligible additional risk of COVID-19 contagion. We consider that it is not necessary to take additional preventive measures beyond those already prescribed (1.5 m separation and wearing face masks) in order to protect bystanders from this contagion.

Did unprecedented air pollution levels cause spike in Delhi's COVID cases during second wave?

The onset of the second wave of COVID-19 devastated many countries worldwide. Compared with the first wave, the second wave was more aggressive regarding infections and deaths. Numerous studies were conducted on the association of air pollutants and meteorological parameters during the first wave of COVID-19. However, little is known about their associations during the severe second wave of COVID-19. The present study is based on the air quality in Delhi during the second wave. Pollutant concentrations decreased during the lockdown period compared to pre-lockdown period (PM2.5: 67 µg m-3 (lockdown) versus 81 µg m-3 (pre-lockdown); PM10: 171 µg m-3 versus 235 µg m-3; CO: 0.9 mg m-3 versus 1.1 mg m-3) except ozone which increased during the lockdown period (57 µg m-3 versus 39 µg m-3). The variation in pollutant concentrations revealed that PM2.5, PM10 and CO were higher during the pre-COVID-19 period, followed by the second wave lockdown and the lowest in the first wave lockdown. These variations are corroborated by the spatiotemporal variability of the pollutants mapped using ArcGIS. During the lockdown period, the pollutants and meteorological variables explained 85% and 52% variability in COVID-19 confirmed cases and deaths (determined by General Linear Model). The results suggests that air pollution combined with meteorology acted as a driving force for the phenomenal growth of COVID-19 during the second wave. In addition to developing new drugs and vaccines, governments should focus on prediction models to better understand the effect of air pollution levels on COVID-19 cases. Policy and decision-makers can use the results from this study to implement the necessary guidelines for reducing air pollution. Also, the information presented here can help the public make informed decisions to improve the environment and human health significantly.

Pre-COVID-19 pandemic: effects on air quality in the three cities of India using fuzzy MCDM model

Due to urbanization and industrialization pollution level increases. Air pollution directly affects to human health. Air Quality Indices (AQI) method is related to measuring the concentration of different pollutants PM₁₀, NO₂, SO₂ and other pollutants. The fuzzy Logic air quality index calculates in single value of AQI defines limits 0 to 1. In this study, a comparison of air quality data of three cities was conducted with the help of fuzzy logic algorithm. It used to evaluating Indices through fuzzy multi criteria decision making (MCDM) framework in which linguistic terms of experts opinion and perception, accordingly computing matrix is constructed for sub criteria. There are five linguistic terms used in this framework to create membership functions such as high significant, significant, average significant, low significant and not significant. The three cities, Bangalore, Mysore, and Hubli-Dharwad air quality datas was taken for analysis and evaluating indices during pre-COVID years (2017, 2018, and 2019). The AQI value shows that Bangalore has the highest pollution level while Mysore has the lowest. Using the fuzzy theory, results show that Bangalore and Hubli-Dharwad decrease in pollution level by -0.074921% and -0.04797%. Negative sign shows the decrease pollution level while Mysore increase pollution level by 0.011792%. Overall the results show that AQI of Mysore city is low compared to Bangalore and Hubli-Dharwad. Also, this study reveals air quality disseminated through industrial processes and automobile emissions in India cities during pre-COVID pandemic years.

Association between air pollution and COVID-19 mortality and morbidity

Coronavirus disease (COVID-19) pandemic is affecting the world unevenly. One of the highest numbers of cases were recorded in the most polluted regions worldwide. The risk factors for severe COVID-19 include diabetes, cardiovascular, and respiratory diseases. It has been known that the same disease might be worsened by chronic exposure to air pollution. The study aimed to determine whether long-term average exposure to air pollution is associated with an increased risk of COVID-19 cases and deaths in Poland. The cumulative number of COVID-19 cases and deaths for each voivodeship (the main administrative level of jurisdictions) in Poland were collected from March 4, 2020, to May 15, 2020. Based on the official data published by Chief Inspectorate of Environmental Protection voivodeship-level long-term exposure to main air pollution: PM2.5, PM10, NO2, SO2, O3 (averaged from 2013 to 2018) was established. There were statistically significant correlation between COVID-19 cases (per 100,000 population) and annual average concentration of PM2.5 (R2 = 0.367, p = 0.016), PM10 (R2 = 0.415, p = 0.009), SO2 (R2 = 0.489, p = 0.003), and O3 (R2 = 0.537, p = 0.0018). Moreover, COVID-19 deaths (per 100,000 population) were associated with annual average concentration of PM2.5 (R2 = 0.290, p = 0.038), NO2 (R2 = 0.319, p = 0.028), O3 (R2 = 0.452, p = 0.006). The long-term exposure to air pollution, especially PM2.5, PM10, SO2, NO2, O3 seems to play an essential role in COVID-19 prevalence and mortality. Long-term exposure to air pollution might increase the susceptibility to the infection, exacerbates the severity of SARS-CoV-2 infections, and worsens the patients' prognosis. The study provides generalized and possible universal trends. Detailed analyzes of the phenomenon dedicated to a given region require taking into account data on comorbidities and socioeconomic variables as well as information about the long-term exposure to air pollution and COVID-19 cases and deaths at smaller administrative level of jurisdictions (community or at least district level).

Excess mortality in Mountain Areas of Emilia Romagna Region during the first months of SARS-CoV-2 pandemic: a "canary in the coal mine"?

BACKGROUND

Because of their remoteness, Mountain Communities (MC) have been considered at advantage when dealing with infectious diseases. However, earlier reports have identified MC among the hotspots for early spreading of COVID-19 pandemic.

METHODS

Crude mortality rates (CMR) and Excess mortality rates (EMR) were calculated for 97 municipalities from MC in the Emilia Romagna Region, and resulting estimates were compared to the Parent Provinces. Notification and mortality rates for COVID-19 were also retrieved, and correlated with EMR estimates.

RESULTS

During 2020, a CMR of 150.3/100,000 (95% Confidence Interval [95%CI] 117-185.4) was identified, with substantial heterogeneities between the 8 provinces of Emilia Romagna Region that were included in the analyses. A pooled EMR of +20.3% (95%CI 10.6-30.1) for MC and 19.9% (95%CI 9.5-30.3) was identified. The monthly estimates were quite heterogenous across the various provinces, ranging between -79.7% and +307.4% during the assessed timeframe. Higher estimates were identified in the months of March and April in MC, and during the months of April and May for Parent Provinces. In bivariate analysis, EM in MC was positively correlated with estimates in the parent province (Spearman's r = 0.201, p = 0.049), and also with notification rates for COVID- (i.e. Piacenza, Parma, Reggio Emilia, Modena, Bologna, Ravenna, Rimini, and Forlì Cesena) (r = 0.225, p = 0.045), and particularly with mortality rates for COVID-19 at provincial level (r = 0.372, p < 0.001).

CONCLUSIONS

In summary, the study highlights that small geographical and population size, along with remoteness, did not play a substantial advantage for MC against the spread and mortality rate of COVID-19. On the other hand, as the surge of EM in MC anticipated a similar habit in Parent Provinces of several weeks, improved surveillance interventions are also urgently in need. (www.actabiomedica.it).

Geospatial Correlation Analysis between Air Pollution Indicators and Estimated Speed of COVID-19 Diffusion in the Lombardy Region (Italy)

Background: the Lombardy region in Italy was the first area in Europe to record an outbreak of COVID-19 and one of the most affected worldwide. As this territory is strongly polluted, it was hypothesized that pollution had a role in facilitating the diffusion of the epidemic, but results are uncertain. Aim: the paper explores the effect of air pollutants in the first spread of COVID-19 in Lombardy, with a novel geomatics approach addressing the possible confounding factors, the reliability of data, the measurement of diffusion speed, and the biasing effect of the lockdown measures. Methods and results: all municipalities were assigned to one of five possible territorial classes (TC) according to land-use and socio-economic status, and they were grouped into districts of 100,000 residents. For each district, the speed of COVID-19 diffusion was estimated from the ambulance dispatches and related to indicators of mean concentration of air pollutants over 1, 6, and 12 months, grouping districts in the same TC. Significant exponential correlations were found for ammonia (NH₃) in both prevalently agricultural (R² = 0.565) and mildly urbanized (R² = 0.688) areas. Conclusions: this is the first study relating COVID-19 estimated speed of diffusion with indicators of exposure to NH₃. As NH₃ could induce oxidative stress, its role in creating a pre-existing fragility that could have facilitated SARS-CoV-2 replication and worsening of patient conditions could be speculated.

COVID-19 and environment: a poignant reminder of sustainability in the new normal

The nexus of COVID-19 and environment is conspicuously deep-rooted. The roles of environmental factors in the origin, transmission and spread of COVID-19 and the mutual impact of the pandemic on the global environment have been the two perspectives to view this nexus. The present paper attempts to systematically review the existing literature to understand and explore the linkages of COVID-19 with environment and proposes conceptual frameworks to underline this nexus. Our study indicates a critical role of meteorological factors, ambient air pollutants and wastewater in severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) transmission-spread dynamics. The study also focuses on the direct and indirect impacts of COVID-19 on the regional and global environment. Most of the indirect environmental effects of COVID-19 were attributed to global human confinement that resulted from the implementation of the pandemic containment measures. This worldwide anthropogenic 'pause' sent ripples to all environmental compartments and presented a unique test bed to identify anthropogenic impacts on the earth's natural systems. The review further addresses emerging sustainability challenges in the new normal and their potential solutions. The situation warrants critical attention to the environment-COVID-19 nexus and innovative sustainable practices to address the ramifications of short- and long-term environmental impacts of the COVID-19 pandemic.

Graphical abstract

Simultaneous monitoring of SARS-CoV-2, bacteria, and fungi in indoor air of hospital: a study on Hajar Hospital in Shahrekord, Iran

The novel SARS-CoV-2 outbreak was declared as pandemic by the World Health Organization (WHO) on March 11, 2020. Understanding the airborne route of SARS-CoV-2 transmission is essential for infection prevention and control. In this study, a total of 107 indoor air samples (45 SARS-CoV-2, 62 bacteria, and fungi) were collected from different wards of the Hajar Hospital in Shahrekord, Iran. Simultaneously, bacterial and fungal samples were also collected from the ambient air of hospital yard. Overall, 6 positive air samples were detected in the infectious 1 and infectious 2 wards, intensive care unit (ICU), computed tomography (CT) scan, respiratory patients' clinic, and personal protective equipment (PPE) room. Also, airborne bacteria and fungi were simultaneously detected in the various wards of the hospital with concentrations ranging from 14 to 106 CFU m-3 and 18 to 141 CFU m-3, respectively. The highest mean concentrations of bacteria and fungi were observed in respiratory patients' clinics and ICU wards, respectively. Significant correlation (p < 0.05) was found between airborne bacterial concentration and the presence of SARS-CoV-2, while no significant correlation was found between fungi concentration and the virus presence. This study provided an additional evidence about the presence of SARS-CoV-2 in the indoor air of a hospital that admitted COVID-19 patients. Moreover, it was revealed that the monitoring of microbial quality of indoor air in such hospitals is very important, especially during the COVID-19 pandemic, for controlling the nosocomial infections.

COVID-19 false dichotomies and a comprehensive review of the evidence regarding public health, COVID-19 symptomatology, SARS-CoV-2 transmission, mask wearing, and reinfection

Scientists across disciplines, policymakers, and journalists have voiced frustration at the unprecedented polarization and misinformation around coronavirus disease 2019 (COVID-19) pandemic. Several false dichotomies have been used to polarize debates while oversimplifying complex issues. In this comprehensive narrative review, we deconstruct six common COVID-19 false dichotomies, address the evidence on these topics, identify insights relevant to effective pandemic responses, and highlight knowledge gaps and uncertainties. The topics of this review are: 1) Health and lives vs. economy and livelihoods, 2) Indefinite lockdown vs. unlimited reopening, 3) Symptomatic vs. asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, 4) Droplet vs. aerosol transmission of SARS-CoV-2, 5) Masks for all vs. no masking, and 6) SARS-CoV-2 reinfection vs. no reinfection. We discuss the importance of multidisciplinary integration (health, social, and physical sciences), multilayered approaches to reducing risk ("Emmentaler cheese model"), harm reduction, smart masking, relaxation of interventions, and context-sensitive policymaking for COVID-19 response plans. We also address the challenges in understanding the broad clinical presentation of COVID-19, SARS-CoV-2 transmission, and SARS-CoV-2 reinfection. These key issues of science and public health policy have been presented as false dichotomies during the pandemic. However, they are hardly binary, simple, or uniform, and therefore should not be framed as polar extremes. We urge a nuanced understanding of the science and caution against black-or-white messaging, all-or-nothing guidance, and one-size-fits-all approaches. There is a need for meaningful public health communication and science-informed policies that recognize shades of gray, uncertainties, local context, and social determinants of health.

COVID19 outbreak in Lombardy, Italy: An analysis on the short-term relationship between air pollution, climatic factors and the susceptibility to SARS-CoV-2 infection

Short-term exposure to air pollution, as well as to climate variables have been linked to a higher incidence of respiratory viral diseases. The study aims to assess the short-term influence of air pollution and climate on COVID19 incidence in Lombardy (Italy), during the early stage of the outbreak, before the implementation of the lockdown measures. The daily number of COVID19 cases in Lombardy from February 25th to March 10th, 2020, and the daily average concentrations up to 15 days before the study period of particulate matter (PM10, PM2.5), O3, SO2, and NO2 together with climate variables (temperature, relative humidity - RH%, wind speed, precipitation), were analyzed. A univariable mixed model with a logarithm transformation as link function was applied for each day, from 15 days (lag15) to one day (lag1) before the day of detected cases, to evaluate the effect of each variable. Additionally, change points (Break Points-BP) in the relationship between incident cases and air pollution or climatic factors were estimated. The results did not show a univocal relationship between air quality or climate factors and COVID19 incidence. PM10, PM2.5 and O3 concentrations in the last lags seem to be related to an increased COVID19 incidence, probably due to an increased susceptibility of the host. In addition, low temperature and low wind speed in some lags resulted associated with increased daily COVID19 incidence. The findings observed suggest that these factors, in particular conditions and lags, may increase individual susceptibility to the development of viral infections such as SARS-CoV-2.

Why airborne transmission hasn't been conclusive in case of COVID-19? An atmospheric science perspective

Airborne transmission is one of the routes for the spread of COVID-19 which is caused by inhalation of smaller droplets1 containing SARS-CoV-2 (i.e., either virus-laden particulate matter: PM and/or droplet nuclei) in an indoor environment. Notably, a significant fraction of the small droplets, along with respiratory droplets, is produced by both symptomatic and asymptomatic individuals during expiratory events such as breathing, sneezing, coughing and speaking. When these small droplets are exposed to the ambient environment, they may interact with PM and may remain suspended in the atmosphere even for several hours. Therefore, it is important to know the fate of these droplets and processes (e.g., physical and chemical) in the atmosphere to better understand airborne transmission. Therefore, we reviewed existing literature focussed on the transmission of SARS-CoV-2 in the spread of COVID-19 and present an environmental perspective on why airborne transmission hasn't been very conclusive so far. In addition, we discuss various environmental factors (e.g., temperature, humidity, etc.) and sampling difficulties, which affect the conclusions of the studies focussed on airborne transmission. One of the reasons for reduced emphasis on airborne transmission could be that the smaller droplets have less number of viruses as compared to larger droplets. Further, smaller droplets can evaporate faster, exposing SARS-CoV-2 within the small droplets to the environment, whose viability may further reduce. For example, these small droplets containing SARS-CoV-2 might also physically combine with or attach to pre-existing PM so that their behaviour and fate may be governed by PM composition. Thus, the measurement of their infectivity and viability is highly uncertain due to a lack of robust sampling system to separately collect virions in the atmosphere. We believe that the present review will help to minimize the gap in our understanding of the current pandemic and develop a robust epidemiological method for mortality assessment.

Mitigation of Airborne Contaminant Spread through Simple Interventions in an Occupied Single-Family Home

Historically, reducing aerosol-based transmission of respired viruses in indoor environments has been of importance for controlling influenza viruses and common-cold rhinoviruses. The present public health emergency associated with SARS-CoV-2 makes this topic critically important. Yet to be tested is the potential effectiveness of simple interventions that create an isolation zone (IZ) for a suspected/confirmed sick or sensitive person requiring quarantine. The intent in existing homes is to find a practical means to mitigate exposure to airborne contaminants. In creating an IZ in an occupied single-family home in the study, four simple strategies were tested. The test configurations were: (1) IZ windows closed with IZ bathroom exhaust ventilation fan off, (2) IZ windows closed with IZ exhaust fan on, (3) IZ window open with IZ exhaust fan off, and (4) IZ window open with IZ exhaust fan on. Incense-generated fine particulate matter (PM2.5) was used as a marker for virus transmission. The measured transfer of PM2.5 from the IZ into the main zone (MZ) of the house enabled us to determine the relative effectiveness of four containment strategies. Collectively, the data from pressure differential (across zones) and PM2.5 measurements suggested that the best containment strategy was achieved through continuously operating the bathroom exhaust fan while keeping the windows closed in the IZ (configuration 2). Interventions using open windows were found to be less reliable, due to variability in wind speed and direction, resulting in an unpredictable and sometimes detrimental pressure differential in the IZ with reference to MZ. Our findings strongly suggest a simple IZ exhaust ventilation strategy has the potential for mitigating the risk from the airborne spread of contaminants, such as SARS-CoV-2.

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.

The impact of non-pharmaceutical interventions, demographic, social, and climatic factors on the initial growth rate of COVID-19: A cross-country study

On March 11, 2020 the World Health Organization announced that the COVID-19 disease developed into a global pandemic. In the present paper, we aimed at analysing how the implementation of Non-Pharmaceutical Interventions (NPI) as well as climatic, social, and demographic variables affected the initial growth rate of COVID-19. In more detail, we aimed at identifying and assessing all the predictors in a whole picture of the COVID-19 outbreak and the effectiveness of the response of the countries to the pandemic. It can be expected, indeed, that there is a subtle and complex interplay among the various parameters. As such, we estimated the initial growth rate of COVID-19 for countries across the globe, and used a multiple linear regression model to study the association between the initial growth rate and NPI as well as pre-existing country characteristics (climatic, social and demographic variables measured before the current epidemic began). We obtained a mean initial growth rate of 0.120 (SD 0.076), in the range 0.023-0.315. Ten (8 pre-existing country characteristics and 2 NPI) out of 29 factors considered (21 pre-existing country characteristics and 8 NPI) were associated with the initial growth of COVID-19. Population in urban agglomerations of more than 1 million, PM2.5 air pollution mean annual exposure, life expectancy, hospital beds available, urban population, Global Health Security detection index and restrictions on international movement had the most significant effects on the initial growth of COVID-19. Based on available data and the results we obtained, NPI put in place by governments around the world alone may not have had a significant impact on the initial growth of COVID-19. Only restrictions on international movements had a relative significance with respect to the initial growth rate, whereas demographic, climatic, and social variables seemed to play a greater role in the initial growth rate of COVID-19.

DatAC: A visual analytics platform to explore climate and air quality indicators associated with the COVID-19 pandemic in Spain

The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented global health crisis, with several countries imposing lockdowns to control the coronavirus spread. Important research efforts are focused on evaluating the association of environmental factors with the survival and spread of the virus and different works have been published, with contradictory results in some cases. Data with spatial and temporal information is a key factor to get reliable results and, although there are some data repositories for monitoring the disease both globally and locally, an application that integrates and aggregates data from meteorological and air quality variables with COVID-19 information has not been described so far to the best of our knowledge. Here, we present DatAC (Data Against COVID-19), a data fusion project with an interactive web frontend that integrates COVID-19 and environmental data in Spain. DatAC is provided with powerful data analysis and statistical capabilities that allow users to explore and analyze individual trends and associations among the provided data. Using the application, we have evaluated the impact of the Spanish lockdown on the air quality, observing that NO2, CO, PM2.5, PM10 and SO2 levels decreased drastically in the entire territory, while O3 levels increased. We observed similar trends in urban and rural areas, although the impact has been more important in the former. Moreover, the application allowed us to analyze correlations among climate factors, such as ambient temperature, and the incidence of COVID-19 in Spain. Our results indicate that temperature is not the driving factor and without effective control actions, outbreaks will appear and warm weather will not substantially limit the growth of the pandemic. DatAC is available at https://covid19.genyo.es.

Electrostatic fine particles emitted from laser printers as potential vectors for airborne transmission of COVID-19

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 14 million people globally. Recently, airborne transmission has been postulated to be a major contributor to the spread of the novel coronavirus, especially in enclosed public spaces. While many studies have demonstrated positive correlations between atmospheric pollutants and SARS-CoV-2 infection, the impact of indoor air pollutants on airborne transmission has been largely overlooked. In particular, laser printers are a primary source of particle emission that increases the concentrations of particulate matter in indoor atmosphere by releasing substantial quantities of electrostatic fine particles, at rates comparable with tobacco smoking and incense burning. We hypothesized that particles emitted from laser printers present a potential risk factor for the transmission of SARS-CoV-2 in offices and other indoor environments with high user occupancy. To test this hypothesis, we reviewed recent knowledge on the characteristics of particles emitted by laser printing, including their emission rates and accumulation in indoor air, electrostatic charges, localized emission and subsequent particle diffusion in relation to the human breathing zone. We then discuss the potential impact on the transmission of SAR-CoV-2 in indoor spaces. We found that emission rates from laser printers ranged from 10⁸ to 10¹² particles min^-1, and these fine particles typically remain suspended for prolonged periods in indoor air. Electrostatic charges carried by these particles can reach 260-379 e per particle, thus enhancing their surface adsorption and deposition in human airways. Localized emission by laser printers and subsequent diffusion highly increase particle concentrations near the human breathing zone.

Assessing correlations between short-term exposure to atmospheric pollutants and COVID-19 spread in all Italian territorial areas

The spread of SARS-CoV-2, the beta coronavirus responsible for the current pneumonia pandemic outbreak, has been speculated to be linked to short-term and long-term atmospheric pollutants exposure. The present work has been aimed at analyzing the atmospheric pollutants concentrations (PM10, PM2.5, NO2) and spatio-temporal distribution of cases and deaths (specifically incidence, mortality and lethality rates) across the whole Italian national territory, down to the level of each individual territorial area, with the goal of checking any potential short-term correlation between these two phenomena. The data analysis has been limited to the first quarter of 2020 to reduce the lockdown-dependent biased effects on the atmospheric pollutant levels as much as possible. The analysis looked at non-linear, monotonic correlations using the Spearman non-parametric correlation index. The statistical significance of the Spearman correlations has also been evaluated. The results of the statistical analysis suggest the hypothesis of a moderate-to-strong correlation between the number of days exceeding the annual regulatory limits of PM10, PM2.5 and NO2 atmospheric pollutants and COVID-19 incidence, mortality and lethality rates for all the 107 territorial areas in Italy. A weak-to-moderate correlation seems to exist when considering the 36 territorial areas in four of the most affected regions (Lombardy, Piedmont, Emilia-Romagna and Veneto). Overall, PM10 and PM2.5 showed a higher non-linear correlation than NO2 with incidence, mortality and lethality rates. As to particulate matters, PM10 profile has been compared with the incidence rate variation that occurred in three of the most affected territorial areas in Northern Italy (i.e., Milan, Brescia, and Bergamo). All areas showed a similar PM10 time trend but a different incidence rate variation, that was less severe in Milan compared with Brescia and Bergamo.

Effects of meteorological conditions and air pollution on COVID-19 transmission: Evidence from 219 Chinese cities

The spatial distribution of the COVID-19 infection in China cannot be explained solely by geographical distance and regulatory stringency. In this research we investigate how meteorological conditions and air pollution, as concurring factors, impact COVID-19 transmission, using data on new confirmed cases from 219 prefecture cities from January 24 to February 29, 2020. Results revealed a kind of nonlinear dose-response relationship between temperature and coronavirus transmission. We also found that air pollution indicators are positively correlated with new confirmed cases, and the coronavirus further spreads by 5-7% as the AQI increases by 10 units. Further analysis based on regional divisions revealed that in northern China the negative effects of rising temperature on COVID-19 is counteracted by aggravated air pollution. In the southern cities, the ambient temperature and air pollution have a negative interactive effect on COVID-19 transmission, implying that rising temperature restrains the facilitating effects of air pollution and that they jointly lead to a decrease in new confirmed cases. These results provide implications for the control and prevention of this disease and for the anticipation of another possible pandemic.

No small matter: a perspective on nanotechnology-enabled solutions to fight COVID-19

There is an urgent need for safe and effective approaches to combat COVID-19. Here, we asked whether lessons learned from nanotoxicology and nanomedicine could shed light on the current pandemic. SARS-CoV-2, the causative agent, may trigger a mild, self-limiting disease with respiratory symptoms, but patients may also succumb to a life-threatening systemic disease. The host response to the virus is equally complex and studies are now beginning to unravel the immunological correlates of COVID-19. Nanotechnology can be applied for the delivery of antiviral drugs or other repurposed drugs. Moreover, recent work has shown that synthetic nanoparticles wrapped with host-derived cellular membranes may prevent virus infection. We posit that nanoparticles decorated with ACE2, the receptor for SARS-CoV-2, could be exploited as decoys to intercept the virus before it infects cells in the respiratory tract. However, close attention should be paid to biocompatibility before such nano-decoys are deployed in the clinic.

Initial COVID-19 Transmissibility and Three Gaseous Air Pollutants (NO2, SO2, and CO): A Nationwide Ecological Study in China

In this study, we conducted an ecological study to examine their effects in the early phase of the pandemic (from December 2019 to February 2020) in China. We found that the associations between the average concentrations of NO₂, SO₂, and CO and the COVID-19 transmissibility are not statistically clear.

Influence of airborne transmission of SARS-CoV-2 on COVID-19 pandemic. A review

In recent years, a number of epidemiological studies have demonstrated that exposure to air pollution is associated with several adverse outcomes, such as acute lower respiratory infections, chronic obstructive pulmonary disease, asthma, cardiovascular diseases, and lung cancer among other serious diseases. Air pollutants such as sulfur oxides, nitrogen oxides, carbon monoxide and dioxide, particulate matter (PM), ozone and volatile organic compounds (VOCs) are commonly found at high levels in big cities and/or in the vicinity of different chemical industries. An association between air concentrations of these pollutants and human respiratory viruses interacting to adversely affect the respiratory system has been also reported. The present review was aimed at assessing the potential relationship between the concentrations of air pollutants on the airborne transmission of SARS-CoV-2 and the severity of COVID-19 in patients infected by this coronavirus. The results of most studies here reviewed suggest that chronic exposure to certain air pollutants leads to more severe and lethal forms of COVID-19 and delays/complicates the recovery of patients of this disease.