COVID-19 and air pollution and meteorology-an intricate relationship: A review

Do Weather Conditions Still Have an Impact on the COVID-19 Pandemic? An Observation of the Mid-2022 COVID-19 Peak in Taiwan

Since the onset of the COVID-19 pandemic in 2019, the role of weather conditions in influencing transmission has been unclear, with results varying across different studies. Given the changes in border policies and the higher vaccination rates compared to earlier conditions, this study aimed to reassess the impact of weather on COVID-19, focusing on local climate effects. We analyzed daily COVID-19 case data and weather factors such as temperature, humidity, wind speed, and a diurnal temperature range from 1 March to 15 August 2022 across six regions in Taiwan. This study found a positive correlation between maximum daily temperature and relative humidity with new COVID-19 cases, whereas wind speed and diurnal temperature range were negatively correlated. Additionally, a significant positive correlation was identified between the unease environmental condition factor (UECF, calculated as RH*Tmax/WS), the kind of Climate Factor Complex (CFC), and confirmed cases. The findings highlight the influence of local weather conditions on COVID-19 transmission, suggesting that such factors can alter environmental comfort and human behavior, thereby affecting disease spread. We also introduced the Fire-Qi Period concept to explain the cyclic climatic variations influencing infectious disease outbreaks globally. This study emphasizes the necessity of considering both local and global climatic effects on infectious diseases.

Effect of Long-Distance Domestic Travel Ban Policies in Japan on COVID-19 Outbreak Dynamics During Dominance of the Ancestral Strain: Ex Post Facto Retrospective Observation Study

BACKGROUND

In Japan, long-distance domestic travel was banned while the ancestral SARS-CoV-2 strain was dominant under the first declared state of emergency from March 2020 until the end of May 2020. Subsequently, the "Go To Travel" campaign travel subsidy policy was activated, allowing long-distance domestic travel, until the second state of emergency as of January 7, 2021. The effects of this long-distance domestic travel ban on SARS-CoV-2 infectivity have not been adequately evaluated.

OBJECTIVE

We evaluated the effects of the long-distance domestic travel ban in Japan on SARS-CoV-2 infectivity, considering climate conditions, mobility, and countermeasures such as the "Go To Travel" campaign and emergency status.

METHODS

We calculated the effective reproduction number R(t), representing infectivity, using the epidemic curve in Kagoshima prefecture based on the empirical distribution of the incubation period and procedurally delayed reporting from an earlier study. Kagoshima prefecture, in southern Japan, has several resorts, with an airport commonly used for transportation to Tokyo or Osaka. We regressed R(t) on the number of long-distance domestic travelers (based on the number of airport limousine bus users provided by the operating company), temperature, humidity, mobility, and countermeasures such as state of emergency declarations and the "Go To Travel" campaign in Kagoshima. The study period was June 20, 2020, through February 2021, before variant strains became dominant. A second state of emergency was not declared in Kagoshima prefecture but was declared in major cities such as Tokyo and Osaka.

RESULTS

Estimation results indicated a pattern of declining infectivity with reduced long-distance domestic travel volumes as measured by the number of airport limousine bus users. Moreover, infectivity was lower during the "Go To Travel" campaign and the second state of emergency. Regarding mobility, going to restaurants, shopping malls, and amusement venues was associated with increased infectivity. However, going to grocery stores and pharmacies was associated with decreased infectivity. Climate conditions showed no significant association with infectivity patterns.

CONCLUSIONS

The results of this retrospective analysis suggest that the volume of long-distance domestic travel might reduce SARS-CoV-2 infectivity. Infectivity was lower during the "Go To Travel" campaign period, during which long-distance domestic travel was promoted, compared to that outside this campaign period. These findings suggest that policies banning long-distance domestic travel had little legitimacy or rationale. Long-distance domestic travel with appropriate infection control measures might not increase SARS-CoV-2 infectivity in tourist areas. Even though this analysis was performed much later than the study period, if we had performed this study focusing on the period of April or May 2021, it would likely yield the same results. These findings might be helpful for government decision-making in considering restarting a "Go To Travel" campaign in light of evidence-based policy.

A review of the influence of environmental pollutants (microplastics, pesticides, antibiotics, air pollutants, viruses, bacteria) on animal viruses

Microorganisms, especially viruses, cause disease in both humans and animals. Environmental chemical pollutants including microplastics, pesticides, antibiotics sand air pollutants arisen from human activities affect both animal and human health. This review assesses the impact of chemical and biological contaminants (virus and bacteria) on viruses including its life cycle, survival, mutations, loads and titers, shedding, transmission, infection, re-assortment, interference, abundance, viral transfer between cells, and the susceptibility of the host to viruses. It summarizes the sources of environmental contaminants, interactions between contaminants and viruses, and methods used to mitigate such interactions. Overall, this review provides a perspective of environmentally co-occurring contaminants on animal viruses that would be useful for future research on virus-animal-human-ecosystem harmony studies to safeguard human and animal health.

A study of the attenuation stage of a global infectious disease

Introduction

Differences in control measures and response speeds between regions may be responsible for the differences in the number of infections of global infectious diseases. Therefore, this article aims to examine the decay stage of global infectious diseases. We demonstrate our method by considering the first wave of the COVID-19 epidemic in 2020.

Methods

We introduce the concept of the attenuation rate into the varying coefficient SEIR model to measure the effect of different cities on epidemic control, and make inferences through the integrated adjusted Kalman filter algorithm.

Results

We applied the varying coefficient SEIR model to 136 cities in China where the total number of confirmed cases exceeded 20 after the implementation of control measures and analyzed the relationship between the estimated attenuation rate and local factors. Subsequent analysis and inference results show that the attenuation rate is significantly related to the local annual GDP and the longitude and latitude of a city or a region. We also apply the varying coefficient SEIR model to other regions outside China. We find that the fitting curve of the average daily number of new confirmed cases simulated by the variable coefficient SEIR model is consistent with the real data.

Discussion

The results show that the cities with better economic development are able to control the epidemic more effectively to a certain extent. On the other hand, geographical location also affected the effectiveness of regional epidemic control. In addition, through the results of attenuation rate analysis, we conclude that China and South Korea have achieved good results in controlling the epidemic in 2020.

The impact of ambient temperature and air pollution on SARS-CoV2 infection and Post COVID-19 condition in Belgium (2021-2022)

INTRODUCTION

The associations between non-optimal ambient temperature, air pollution and SARS-CoV-2 infection and post COVID-19 condition (PCC) remain constrained in current understanding. We conducted a retrospective analysis to explore how ambient temperature affected SARS-CoV-2 infection in individuals who later developed PCC compared to those who did not. We investigated if these associations were modified by air pollution.

METHODS

We conducted a bidirectional time-stratified case-crossover study among individuals who tested positive for SARS-CoV-2 between May 2021 and June 2022. We included 6302 infections, with 2850 PCC cases. We used conditional logistic regression and distributed lag non-linear models to obtain odds ratios (OR) and 95% confidence intervals (CI) for non-optimal temperatures relative to the period median temperature (10.6 °C) on lags 0 to 5. For effect modification, daily average PM2.5 concentrations were categorized using the period median concentration (8.8 μg/m3). Z-tests were used to compare the results by PCC status and PM2.5.

RESULTS

Non-optimal cold temperatures increased the cumulative odds of infection (OR = 1.93; 95%CI:1.67-2.23, OR = 3.53; 95%CI:2.72-4.58, for moderate and extreme cold, respectively), with the strongest associations observed for non-PCC cases. Non-optimal heat temperatures decreased the odds of infection except for moderate heat among PCC cases (OR = 1.32; 95%CI:0.89-1.96). When PM2.5 was >8.8 μg/m3, the associations with cold were stronger, and moderate heat doubled the odds of infection with later development of PCC (OR = 2.18; 95%CI:1.01-4.69). When PM2.5 was ≤8.8 μg/m3, exposure to non-optimal temperatures reduced the odds of infection.

CONCLUSION

Exposure to cold increases SARS-CoV2 risk, especially on days with moderate to high air pollution. Heated temperatures and moderate to high air pollution during infection may cause PCC. These findings stress the need for mitigation and adaptation strategies for climate change to reduce increasing trends in the frequency of weather extremes that have consequences on air pollution concentrations.

SARS-CoV-2 infection in animals: Patterns, transmission routes, and drivers

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is more widespread in animals than previously thought, and it may be able to infect a wider range of domestic and wild species. To effectively control the spread of the virus and protect animal health, it is crucial to understand the cross-species transmission mechanisms and risk factors of SARS-CoV-2. This article collects published literature on SARS-CoV-2 in animals and examines the distribution, transmission routes, biophysical, and anthropogenic drivers of infected animals. The reported cases of infection in animals are mainly concentrated in South America, North America, and Europe, and species affected include lions, white-tailed deer, pangolins, minks, and cats. Biophysical factors influencing infection of animals with SARS-CoV-2 include environmental determinants, high-risk landscapes, air quality, and susceptibility of different animal species, while anthropogenic factors comprise human behavior, intensive livestock farming, animal markets, and land management. Due to current research gaps and surveillance capacity shortcomings, future mitigation strategies need to be designed from a One Health perspective, with research focused on key regions with significant data gaps in Asia and Africa to understand the drivers, pathways, and spatiotemporal dynamics of interspecies transmission.

Causal effect of air pollution and meteorology on the COVID-19 pandemic: A convergent cross mapping approach

Environmental factors have been suspected to influence the propagation and lethality of COVID-19 in the global population. However, most of the studies have been limited to correlation analyses and did not use specific methods to address the dynamic of the causal relationship between the virus and its external drivers. This work focuses on inferring and understanding the causal effect of critical air pollutants and meteorological parameters on COVID-19 by using an Empirical Dynamic Modeling approach called Convergent Cross Mapping. This technique allowed us to identify the time-delayed causation and the sign of interactions. Considering its remarkable urban environment and mortality rate during the pandemic, Quito, Ecuador, was chosen as a case study. Our results show that both urban air pollution and meteorology have a causal impact on COVID-19. Even if the strength and the sign of the causality vary over time, a general trend can be drawn. NO2, SO2, CO and PM2.5 have a positive causation for COVID-19 infections (ρ > 0.35 and ∂ > 9.1). Contrary to current knowledge, this study shows a rapid effect of pollution on COVID-19 cases (1 < lag days <24) and a negative impact of O3 on COVID-19-related deaths (ρ = 0.53 and ∂ = -0.3). Regarding the meteorology, temperature (ρ = 0.24 and ∂ = -0.4) and wind speed (ρ = 0.34 and ∂ = -3.9) tend to mitigate the epidemiological consequences of SARS-CoV-2, whereas relative humidity seems to increase the excess deaths (ρ = 0.4 and ∂ = 0.05). A causal network is proposed to synthesize the interactions between the studied variables and to provide a simple model to support the management of coronavirus outbreaks.

Impact of short-term ambient air pollution exposure on the risk of severe COVID-19

Ecological studies suggested a link between air pollution and severe COVID-19 outcomes, while studies accounting for individual-level characteristics are limited. In the present study, we aimed to investigate the impact of short-term ambient air pollution exposure on disease severity among a cohort of 569 laboratory confirmed COVID-19 patients admitted to designated hospitals in Zhejiang province, China, from January 17 to March 3, 2020, and elucidate the possible biological processes involved using transcriptomics. Compared with mild cases, severe cases had higher proportion of medical conditions as well as unfavorable results in most of the laboratory tests, and manifested higher air pollution exposure levels. Higher exposure to air pollutants was associated with increased risk of severe COVID-19 with odds ratio (OR) of 1.89 (95% confidence interval (CI): 1.01, 3.53), 2.35 (95% CI: 1.20, 4.61), 2.87 (95% CI: 1.68, 4.91), and 2.01 (95% CI: 1.10, 3.69) for PM2.5, PM10, NO2 and CO, respectively. OR for NO2 remained significant in two-pollutant models after adjusting for other pollutants. Transcriptional analysis showed 884 differentially expressed genes which mainly were enriched in virus clearance related biological processes between patients with high and low NO2 exposure levels, indicating that compromised immune response might be a potential underlying mechanistic pathway. These findings highlight the impact of short-term air pollution exposure, particularly for NO2, on COVID-19 severity, and emphasize the significance in mitigating the COVID-19 burden of commitments to improve air quality.

Impact of Ambient Air Pollution Exposure on Long COVID-19 Symptoms: A Cohort Study within the Saudi Arabian Population

Evidence suggests that air pollution, specifically the particulate matters PM2.5 and PM10, plays a key role in exacerbating the risk of prolonged symptoms following COVID-19 infection.

AIM

This study endeavors to elucidate the potential interaction between chronic air pollution exposure and the manifestation of long COVID symptoms within a cohort based in Makkah, Saudi Arabia.

METHODS

Participants included residents from the Makkah region who had recovered from COVID-19 between 2022 and 2023. A comprehensive questionnaire was utilized to gather detailed demographic data and assess the persistent symptoms seen during the post-COVID period. To gauge the environmental exposure to potential risk factors, air sampling for PM10 and PM2.5 was systematically conducted in various locations in Makkah over a year.

RESULTS

Significant positive associations were found between PM2.5 and PM10 exposure and long COVID. Furthermore, specific symptom analysis revealed a significant association between air pollution and shortness of breath (for PM2.5). Only PM2.5 exposure remained statistically significant (RR = 1.32, 95% CI: 1.05, 1.67). In contrast, the association with PM10 remained on the cusp of significance, with an RR of 1.27 (95% CI: 1.00, 1.61).

CONCLUSION

This study highlights the importance of reducing air pollution levels to mitigate the long-term health consequences of COVID-19.

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.

Investigating changes in atmospheric aerosols properties over the Indo-Gangetic Plain during different phases of COVID-19-induced lockdowns

Impact of COrona VIrus Diseases 2019 (COVID-19) restrictive measures on aerosol optical depth (AOD) and black carbon (BC) concentration is investigated for the western, central, and eastern Indo-Gangetic Plain (IGP) using satellite-based observations. Due to COVID-19-induced lockdown measures, a noticeable decline in AOD and BC concentrations was observed across the IGP when compared to pre-lockdown period of 2020 and the lockdown concurrent period of 2015-2019. During the total lockdown period, a maximum drop in AOD and BC was observed in the central IGP (26.5 % and 10.1 %), followed by western IGP (24.9% and 5.2%) and eastern IGP (23.2 % and 4.9 %) with respect to the same period of 2015-2019. We have removed seasonal influences on aerosol properties during the COVID-19 lockdown, by taking average seasonal variations during the period of 2015-2019 as reference and projecting the hypothetical AOD and BC for the lockdown period under normal scenario. The difference between the hypothetical AOD and BC (under normal scenario) and the retrieved AOD and BC for the lockdown period is the absolute percentage change in AOD and BC concentration due to the lockdown alone. This elimination of seasonal influence is a novel approach. Central IGP showed an absolute decrease in AOD and BC of 38.5% and 18.2% during the lockdown period followed by western IGP (34.6% and 7.7%) and eastern IGP (25.9% and 11.5%). The observed absolute reduction in AOD, 26-39 %, is significantly higher than the global average reduction in AOD of 2-5%. CALIPSO-derived aerosol sub-types over major location of the western, central, and eastern IGP suggests prevalence of anthropogenic activities during pre- and post-lockdown periods. During the lockdown, IGP was influenced by aerosols from natural sources, with mineral dust and polluted dust in the western and central IGP, and aerosols from marine regions in the eastern IGP. Replenishment of aerosols within the boundary layer were far quicker when compared to total column during post-lockdown. Overall, the study reveals a reduction in anthropogenic emissions during the COVID-19-induced lockdowns, leading to temporary improvements in air quality over the IGP. Our study presents a comprehensive analysis of COVID-19 lockdown impact on aerosols properties over the IGP and highlights unprecedented reductions in AOD (~ 40 %) and BC (~ 20 %), due to imposition of lockdown and subsequent cessation of aerosol sources, by removing seasonal influences.

Combining aggregate and individual-level data to estimate individual-level associations between air pollution and COVID-19 mortality in the United States

Imposing stricter regulations for PM2.5 has the potential to mitigate damaging health and climate change effects. Recent evidence establishing a link between exposure to air pollution and COVID-19 outcomes is one of many arguments for the need to reduce the National Ambient Air Quality Standards (NAAQS) for PM2.5. However, many studies reporting a relationship between COVID-19 outcomes and PM2.5 have been criticized because they are based on ecological regression analyses, where area-level counts of COVID-19 outcomes are regressed on area-level exposure to air pollution and other covariates. It is well known that regression models solely based on area-level data are subject to ecological bias, i.e., they may provide a biased estimate of the association at the individual-level, due to within-area variability of the data. In this paper, we augment county-level COVID-19 mortality data with a nationally representative sample of individual-level covariate information from the American Community Survey along with high-resolution estimates of PM2.5 concentrations obtained from a validated model and aggregated to the census tract for the contiguous United States. We apply a Bayesian hierarchical modeling approach to combine county-, census tract-, and individual-level data to ultimately draw inference about individual-level associations between long-term exposure to PM2.5 and mortality for COVID-19. By analyzing data prior to the Emergency Use Authorization for the COVID-19 vaccines we found that an increase of 1 μg/m3 in long-term PM2.5 exposure, averaged over the 17-year period 2000-2016, is associated with a 3.3% (95% credible interval, 2.8 to 3.8%) increase in an individual's odds of COVID-19 mortality. Code to reproduce our study is publicly available at https://github.com/NSAPH/PM_COVID_ecoinference. The results confirm previous evidence of an association between long-term exposure to PM2.5 and COVID-19 mortality and strengthen the case for tighter regulations on harmful air pollution and greenhouse gas emissions.

Effects of fine particulate matter (PM2.5) and meteorological factors on the daily confirmed cases of COVID-19 in Bangkok during 2020-2021, Thailand

The ongoing global pandemic caused by the SARS-CoV-2 virus, known as COVID-19, has disrupted public health, businesses, and economies worldwide due to its widespread transmission. While previous research has suggested a possible link between environmental factors and increased COVID-19 cases, the evidence regarding this connection remains inconclusive. The purpose of this research is to determine whether or not there is a connection between the presence of fine particulate matter (PM2.5) and meteorological conditions and COVID-19 infection rates in Bangkok, Thailand. The study employs a statistical method called Generalized Additive Model (GAM) to find a positive and non-linear association between RH, AH, and R and the number of verified COVID-19 cases. The impacts of the seasons (especially summer) and rainfall on the trajectory of COVID-19 cases were also highlighted, with an adjusted R-square of 0.852 and a deviance explained of 85.60%, both of which were statistically significant (p < 0.05). The study results assist in preventing the future seasonal spread of COVID-19, and public health authorities may use these findings to make informed decisions and assess their policies.

How does the COVID-19-related restriction affect the spatiotemporal variability of ambient air quality in a tropical city?

The ambient air, a significant hazard to human health in most Indian cities, including Rourkela, is something we are strangely neglecting in the age of industrialization and urbanization. High levels of particulate matter released from various anthropogenic sources over the past decade have had a significant negative impact on the city. The COVID-19 lockdown situation brings understanding and realization towards the improvement of air quality and its subsequent effects. The present study investigates the impact of the COVID-19-related lockdown on the spatiotemporal variation of the ambient air quality in Rourkela City with a tropical climatic setup. The concentration and distribution of various pollutants are well explained by the wind rose and Pearson correlation. There is considerable spatiotemporal variation in the city's ambient air quality, as determined by a two-way ANOVA test comparing sampling sites and months. During the COVID-19 lockdown phases, the air quality of Rourkela witnessed an improvement in annual AQI ranging from 12.64 to 26.85% across the city. However, the air quality in the city deteriorated by 13.76-65.79% after the revocation of COVID-19 restrictions. The paired sample T-test justified that the air quality of Rourkela was significantly healthier in 2020 compared to both 2019 and 2021. Spatial interpolation reveals that the ambient air quality of Rourkela ranged from satisfactory to moderate categories throughout the entire study period. 31.93% area of the city has experienced an improvement in AQI from the Moderate to the satisfying category from 2019 to 2020, whereas about 68.78% area of the city has witnessed a decline in AQI from satisfactory to moderate category from 2020 to 2021.

Unraveling the socio-environmental drivers during the early COVID-19 pandemic in China

The effect of environmental and socioeconomic conditions on the global pandemic of COVID-19 had been widely studied, yet their influence during the early outbreak remains less explored. Unraveling these relationships represents a key knowledge to prevent potential outbreaks of similar pathogens in the future. This study aims to determine the influence of socioeconomic, infrastructure, air pollution, and weather variables on the relative risk of infection in the initial phase of the COVID-19 pandemic in China. A spatio-temporal Bayesian zero-inflated Poisson model is used to test for the effect of 13 socioeconomic, urban infrastructure, air pollution, and weather variables on the relative risk of COVID-19 disease in 122 cities of China. The results show that socioeconomic and urban infrastructure variables did not have a significant effect on the relative risk of COVID-19. Meanwhile, COVID-19 relative risk was negatively associated with temperature, wind speed, and carbon monoxide, while nitrous dioxide and the human modification index presented a positive effect. Pollution gases presented a marked variability during the study period, showing a decrease of CO. These findings suggest that controlling and monitoring urban emissions of pollutant gases is a key factor for the reduction of risk derived from COVID-19.

Explaining the higher COVID-19 mortality rates among disproportionately Black counties: A decomposition analysis

Background

Why is COVID-19 mortality higher in counties with a disproportionately large (>13.4%) share of Black residents (hereafter "Black counties") relative to others ("non-Black counties")? Existing literature points to six categories of determinants: (1) social distancing, (2) COVID-19 testing, (3) socioeconomic characteristics, (4) environmental characteristics, (5) prevalence of (pre-existing) chronic health conditions, and (6) demographic characteristics. The relative importance of these determinants has not yet been thoroughly examined.

Methods

We built a dataset consisting of 21 sub-indicators across the six categories of determinants for 3108 US counties and their COVID-19 mortality over the period of January 22, 2020-December 31, 2020. Applying the Gelbach's decomposition, we quantified which determinants were most (or least) associated with the COVID-19 mortality disparity between Black and non-Black counties.

Results

We find that COVID-19 death rates were 26 percent higher in Black counties compared to non-Black counties. This disparity was almost completely explained by the six categories of determinants included in our model. Decomposition analyses indicate that county-level demographic and population health characteristics explained most of this disparity. Among all sub-indicators considered, the greater proportion of females and smaller proportion of rural residents in Black counties were the two largest contributors to the COVID-19 mortality gap between Black and non-Black counties. Proportions of diabetic residents, uninsured residents, and the degree of income inequality also significantly contributed to the gap in COVID-19 mortality.

Conclusion

The COVID-19 mortality gap between Black and non-Black counties was largely explained by pre-pandemic differences in demographic and population health characteristics. Policies aiming to reduce the prevalence of chronic conditions and uninsured residents in Black counties would have helped narrow the COVID-19 mortality gap between Black and non-Black counties in 2020.

Animal experiments on respiratory viruses and analogous studies of infection factors for interpersonal transmission

Air pollution caused by SARS-CoV-2 and other viruses in human settlements will have a great impact on human health, but also a great risk of transmission. The transmission power of the virus can be represented by quanta number in the Wells-Riley model. In order to solve the problem of different dynamic transmission scenarios, only a single influencing factor is considered when predicting the infection rate, which leads to large differences in quanta calculated in the same space. In this paper, an analog model is established to define the indoor air cleaning index RL and the space ratio parameter. Based on infection data analysis and rule summary in animal experiments, factors affecting quanta in interpersonal communication were explored. Finally, by analogy, the factors affecting person-to-person transmission mainly include viral load of infected person, distance between individuals, etc., the more severe the symptoms, the closer the number of days of illness to the peak, and the closer the distance to the quanta. In summary, there are many factors that affect the infection rate of susceptible people in the human settlement environment. This study provides reference indicators for environmental governance under the COVID-19 epidemic, provides reference opinions for healthy interpersonal communication and human behavior, and provides some reference for accurately judging the trend of epidemic spread and responding to the epidemic.

Peculiar weather patterns effects on air pollution and COVID-19 spread in Tokyo metropolis

As a pandemic hotspot in Japan, between March 1, 2020-October 1, 2022, Tokyo metropolis experienced seven COVID-19 waves. Motivated by the high rate of COVID-19 incidence and mortality during the seventh wave, and environmental/health challenges we conducted a time-series analysis to investigate the long-term interaction of air quality and climate variability with viral pandemic in Tokyo. Through daily time series geospatial and observational air pollution/climate data, and COVID-19 incidence and death cases, this study compared the environmental conditions during COVID-19 multiwaves. In spite of five State of Emergency (SOEs) restrictions associated with COVID-19 pandemic, during (2020-2022) period air quality recorded low improvements relative to (2015-2019) average annual values, namely: Aerosol Optical Depth increased by 9.13% in 2020 year, and declined by 6.64% in 2021, and 12.03% in 2022; particulate matter PM2.5 and PM10 decreased during 2020, 2021, and 2022 years by 10.22%, 62.26%, 0.39%, and respectively by 4.42%, 3.95%, 5.76%. For (2021-2022) period the average ratio of PM2.5/PM10 was (0.319 ± 0.1640), showing a higher contribution to aerosol loading of traffic-related coarse particles in comparison with fine particles. The highest rates of the daily recorded COVID-19 incidence and death cases in Tokyo during the seventh COVID-19 wave (1 July 2022-1 October 2022) may be attributed to accumulation near the ground of high levels of air pollutants and viral pathogens due to: 1) peculiar persistent atmospheric anticyclonic circulation with strong positive anomalies of geopotential height at 500 hPa; 2) lower levels of Planetary Boundary Layer (PBL) heights; 3) high daily maximum air temperature and land surface temperature due to the prolonged heat waves (HWs) in summer 2022; 4) no imposed restrictions. Such findings can guide public decision-makers to design proper strategies to curb pandemics under persistent stable anticyclonic weather conditions and summer HWs in large metropolitan areas.

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

PM_2.5 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 PM_2.5, PM₁₀, NO₂, and SO2 during the lockdown as well. During the lockdown, exposure to PM_2.5 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 PM_2.5, PM₁₀, NO₂, and SO2. These pollutants are associated with hospital admission, hospital mortality and ICU admission, while ICU mortality is mainly associated with PM_2.5 and PM₁₀. Our findings reveal the importance of monitoring air pollutants in respiratory infectious diseases.

Association of the corona virus (Covid-19) epidemic with environmental risk factors

The current outbreak of the novel coronavirus SARS-CoV-2 (coronavirus disease 2019; previously 2019-nCoV), epicenter in Hubei Province (Wuhan), People's Republic of China, has spread too many other countries. The transmission of the corona virus occurs when people are in the incubation stage and do not have any symptoms. Therefore, the role of environmental factors such as temperature and wind speed becomes very important. The study of Acute Respiratory Syndrome (SARS) indicates that there is a significant relationship between temperature and virus transmission and three important factors, namely temperature, humidity and wind speed, cause SARS transmission. Daily data on the incidence and mortality of Covid-19 disease were collected from World Health Organization (WHO) website and World Meter website (WMW) for several major cities in Iran and the world. Data were collected from February 2020 to September 2021. Meteorological data including temperature, air pressure, wind speed, dew point and air quality index (AQI) index are extracted from the website of the World Meteorological Organization (WMO), The National Aeronautics and Space Administration (NASA) and the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Statistical analysis carried out for significance relationships. The correlation coefficient between the number of infected people in one day and the environmental variables in the countries was different from each other. The relationship between AQI and number of infected was significant in all cities. In Canberra, Madrid and Paris, a significant inverse relationship was observed between the number of infected people in one day and wind speed. There is a significant positive relationship between the number of infected people in a day and the dew point in the cities of Canberra, Wellington and Washington. The relationship between the number of infected people in one day and Pressure was significantly reversed in Madrid and Washington, but positive in Canberra, Brasilia, Paris and Wuhan. There was significant relationship between Dew point and prevalence. Wind speed showed a significant relationship in USA, Madrid and Paris. AQI was strongly associated with the prevalence of covid19. The purpose of this study is to investigate some environmental factors in the transmission of the corona virus.

Meteorological, PM2.5 and PM10 factors on SARS-COV-2 transmission: The case of southern regions in Chile

There are several determinants of a population's health, including meteorological factors and air pollution. For example, it is well known that low temperatures and air pollution increase mortality rates in infant and elderly populations. With the emergence of SARS-COV-2, it is important to understand what factors contribute to its mitigation and control. There is some research in this area which shows scientific evidence on the virus's behavior in the face of these variables. This research aims to quantify the impact of climatic factors and environmental pollution on SARS-COV-2 specifically the effect on the number of new infections in different areas of Chile. At the local level, historical information available from the Department of Statistics and Health Information, the Chilean National Air Quality Information System, the Chilean Meteorological Directorate, and other databases will allow the generation of panel data suitable for the analysis. The results show the significant effect of pollution and climate variables measured in lags and will allow us to explain the behavior of the pandemic by identifying the relevant factors affecting health, using heteroskedastic models, which in turn will serve as a contribution to the generation of more effective and timely public policies for the control of the pandemic.

Impact of COVID-19 lockdown on air quality analyzed through machine learning techniques

After February 2020, the majority of the world's governments decided to implement a lockdown in order to limit the spread of the deadly COVID-19 virus. This restriction improved air quality by reducing emissions of particular atmospheric pollutants from industrial and vehicular traffic. In this study, we look at how the COVID-19 shutdown influenced the air quality in Lahore, Pakistan. HAC Agri Limited, Dawn Food Head Office, Phase 8-DHA, and Zeenat Block in Lahore were chosen to give historical data on the concentrations of many pollutants, including PM2.5, PM10 (particulate matter), NO2 (nitrogen dioxide), and O3 (ozone). We use a variety of models, including decision tree, SVR, random forest, ARIMA, CNN, N-BEATS, and LSTM, to compare and forecast air quality. Using machine learning methods, we looked at how each pollutant's levels changed during the lockdown. It has been shown that LSTM estimates the amounts of each pollutant during the lockout more precisely than other models. The results show that during the lockdown, the concentration of atmospheric pollutants decreased, and the air quality index improved by around 20%. The results also show a 42% drop in PM2.5 concentration, a 72% drop in PM10 concentration, a 29% drop in NO2 concentration, and an increase of 20% in O3 concentration. The machine learning models are assessed using the RMSE, MAE, and R-SQUARE values. The LSTM measures NO2 at 4.35%, O3 at 8.2%, PM2.5 at 4.46%, and PM10 at 8.58% in terms of MAE. It is observed that the LSTM model outperformed with the fewest errors when the projected values are compared with the actual values.

The effect of air quality parameters on new COVID-19 cases between two different climatic and geographical regions in Turkey

Different health management strategies may need to be implemented in different regions to cope with diseases. The current work aims to evaluate the relationship between air quality parameters and the number of new COVID-19 cases in two different geographical locations, namely Western Anatolia and Western Black Sea in Turkey. Principal component analysis (PCA) and regression model were utilized to describe the effect of environmental parameters (air quality and meteorological parameters) on the number of new COVID-19 cases. A big difference in the mean values for all air quality parameters has appeared between the two areas. Two regression models were developed and showed a significant relationship between the number of new cases and the selected environmental parameters. The results showed that wind speed, SO₂, CO, NO_X, and O₃ are not influential variable and does not affect the number of new cases of COVID-19 in the Western Black Sea area, while only wind speed, SO₂, CO, NO_X, and O₃ are influential parameters on the number of new cases in Western Anatolia. Although the environmental parameters behave differently in each region, these results revealed that the relationship between the air quality parameters and the number of new cases is significant.

Ambient air pollution exposure linked to long COVID among young adults: a nested survey in a population-based cohort in Sweden

Background

Post COVID-19 conditions, also known as long COVID, are of public health concern, but little is known about their underlying risk factors. We aimed to investigate associations of air pollution exposure with long COVID among Swedish young adults.

Methods

We used data from the BAMSE (Children, Allergy, Environment, Stockholm, Epidemiology [in Swedish]) cohort. From October 2021 to February 2022 participants answered a web-questionnaire focusing on persistent symptoms following acute SARS-CoV-2 infection. Long COVID was defined as symptoms after confirmed infection with SARS-CoV-2 lasting for two months or longer. Ambient air pollution levels (particulate matter ≤2.5 μm [PM_2.5], ≤10 μm [PM₁₀], black carbon [BC] and nitrogen oxides [NO_x]) at individual-level addresses were estimated using dispersion modelling.

Findings

A total of 753 participants with SARS-CoV-2 infection were included of whom 116 (15.4%) reported having long COVID. The most common symptoms were altered smell/taste (n = 80, 10.6%), dyspnea (n = 36, 4.8%) and fatigue (n = 34, 4.5%). Median annual PM_2.5 exposure in 2019 (pre-pandemic) was 6.39 (interquartile range [IQR] 6.06-6.71) μg/m³. Adjusted Odds Ratios (95% confidence intervals) of PM_2.5 per IQR increase were 1.28 (1.02-1.60) for long COVID, 1.65 (1.09-2.50) for dyspnea symptoms and 1.29 (0.97-1.70) for altered smell/taste. Positive associations were found for the other air pollutants and remained consistent across sensitivity analyses. Associations tended to be stronger among participants with asthma, and those having had COVID during 2020 (versus 2021).

Interpretation

Ambient long-term PM_2.5 exposure may affect the risk of long COVID in young adults, supporting efforts for continuously improving air quality.

Funding

The study received funding from the Swedish Research Council (grant no. 2020-01886, 2022-06340), the Swedish Research Council for Health, Working life and Welfare (FORTE grant no. 2017-01146), the Swedish Heart-Lung Foundation, Karolinska Institute (no. 2022-01807) and Region Stockholm (ALF project for cohort and database maintenance).

Environment and COVID-19 incidence: A critical review

The coronavirus disease 2019 (COVID-19) pandemic is an unprecedented worldwide health crisis. Many previous research studies have found and investigated its links with one or some natural or human environmental factors. However, a review on the relationship between COVID-19 incidence and both the natural and human environment is still lacking. This review summarizes the inter-correlation between COVID-19 incidence and environmental factors. Based on keyword searching, we reviewed 100 relevant peer-reviewed articles and other research literature published since January 2020. This review is focused on three main findings. One, we found that individual environmental factors have impacts on COVID-19 incidence, but with spatial heterogeneity and uncertainty. Two, environmental factors exert interactive effects on COVID-19 incidence. In particular, the interactions of natural factors can affect COVID-19 transmission in micro- and macro- ways by impacting SARS-CoV-2 survival, as well as human mobility and behaviors. Three, the impact of COVID-19 incidence on the environment lies in the fact that COVID-19-induced lockdowns caused air quality improvement, wildlife shifts and socio-economic depression. The additional value of this review is that we recommend future research perspectives and adaptation strategies regarding the interactions of the environment and COVID-19. Future research should be extended to cover both the effects of the environment on the COVID-19 pandemic and COVID-19-induced impacts on the environment. Future adaptation strategies should focus on sustainable environmental and public policy responses.

The COVID-19 Mortality Rate Is Associated with Illiteracy, Age, and Air Pollution in Urban Neighborhoods: A Spatiotemporal Cross-Sectional Analysis

There are different area-based factors affecting the COVID-19 mortality rate in urban areas. This research aims to examine COVID-19 mortality rates and their geographical association with various socioeconomic and ecological determinants in 350 of Tehran's neighborhoods as a big city. All deaths related to COVID-19 are included from December 2019 to July 2021. Spatial techniques, such as Kulldorff's SatScan, geographically weighted regression (GWR), and multi-scale GWR (MGWR), were used to investigate the spatially varying correlations between COVID-19 mortality rates and predictors, including air pollutant factors, socioeconomic status, built environment factors, and public transportation infrastructure. The city's downtown and northern areas were found to be significantly clustered in terms of spatial and temporal high-risk areas for COVID-19 mortality. The MGWR regression model outperformed the OLS and GWR regression models with an adjusted R² of 0.67. Furthermore, the mortality rate was found to be associated with air quality (e.g., NO₂, PM₁₀, and O₃); as air pollution increased, so did mortality. Additionally, the aging and illiteracy rates of urban neighborhoods were positively associated with COVID-19 mortality rates. Our approach in this study could be implemented to study potential associations of area-based factors with other emerging infectious diseases worldwide.

Unanswered questions on the airborne transmission of COVID-19

Policies and measures to control pandemics are often failing. While biological factors controlling transmission are usually well explored, little is known about the environmental drivers of transmission and infection. For instance, respiratory droplets and aerosol particles are crucial vectors for the airborne transmission of the severe acute respiratory syndrome coronavirus 2, the causation agent of the coronavirus 2019 pandemic (COVID-19). Once expectorated, respiratory droplets interact with atmospheric particulates that influence the viability and transmission of the novel coronavirus, yet there is little knowledge on this process or its consequences on virus transmission and infection. Here we review the effects of atmospheric particulate properties, vortex zones, and air pollution on virus survivability and transmission. We found that particle size, chemical constituents, electrostatic charges, and the moisture content of airborne particles can have notable effects on virus transmission, with higher survival generally associated with larger particles, yet some viruses are better preserved on small particles. Some chemical constituents and surface-adsorbed chemical species may damage peptide bonds in viral proteins and impair virus stability. Electrostatic charges and water content of atmospheric particulates may affect the adherence of virion particles and possibly their viability. In addition, vortex zones and human thermal plumes are major environmental factors altering the aerodynamics of buoyant particles in air, which can strongly influence the transport of airborne particles and the transmission of associated viruses. Insights into these factors may provide explanations for the widely observed positive correlations between COVID-19 infection and mortality with air pollution, of which particulate matter is a common constituent that may have a central role in the airborne transmission of the novel coronavirus.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10311-022-01557-z.

Effects of air pollution and weather on the initial COVID-19 outbreaks in United States, Italy, Spain, and China: A comparative study

Contrasting effects have been identified in association of weather (temperature and humidity) and pollutant gases with COVID-19 infection, which could be derived from the influence of lockdowns and season change. The influence of pollutant gases and climate during the initial phases of the pandemic, before the closures and the change of season in the northern hemisphere, is unknown. Here, we used a spatial-temporal Bayesian zero-inflated-Poisson model to test for short-term associations of weather and pollutant gases with the relative risk of COVID-19 disease in China (first outbreak) and the countries with more cases during the initial pandemic (the United States, Spain and Italy), considering also the effects of season and lockdown. We found contrasting association between pollutant gases and COVID-19 risk in the United States, Italy, and Spain, while in China it was negatively associated (except for SO₂ ). COVID-19 risk was positively associated with specific humidity in all countries, while temperature presented a negative effect. Our findings showed that short-term associations of air pollutants with COVID-19 infection vary strongly between countries, while generalized effects of temperature (negative) and humidity (positive) with COVID-19 was found. Our results show novel information about the influence of pollution and weather on the initial outbreaks, which contribute to unravel the mechanisms during the beginning of the pandemic.

Relation of pandemics with solar cycles through ozone, cloud seeds, and vitamin D

The global records of infectious diseases, including Western and Eastern documents from 1825 to 2020, during which sunspot observations are considered reliable, show that 27 of the 34 pandemic outbreaks were coincident with sunspot number maxima or minima. There is evidence that the intensity of galactic cosmic rays is anti-correlated with solar activity and that cloud seed formation is accelerated by galactic cosmic rays. There are a substantial number of research papers showing the relationship between COVID-19 and vitamin D deficiency. The data analysis of ozone thickness measured based on NASA satellite observations revealed that ozone thickness has 11-year and 28-month cycles. Because the 11-year cycles of ozone thickness and cloud seed attenuation are anti-correlated, when either one becomes extremely thick, such as at the maximum or minimum point of solar activity, UV radiation is over-attenuated, and human vitamin D deficiency is globally increased. This finding explains the coincidence of pandemic outbreaks with the extrema of the sunspot numbers. Vitamin D supplementation can be an effective countermeasure against the spread of infectious diseases, which is a paramount importance to global society. Future pandemic forecasting should include the 11-year and 28-month cycles of UV radiation. This founding completes the relationship between solar activity and human health through the earth's environment.

How do temperature, humidity, and air saturation state affect the COVID-19 transmission risk?

Environmental parameters have a significant impact on the spread of respiratory viral diseases (temperature (T), relative humidity (RH), and air saturation state). T and RH are strongly correlated with viral inactivation in the air, whereas supersaturated air can promote droplet deposition in the respiratory tract. This study introduces a new concept, the dynamic virus deposition ratio (α), that reflects the dynamic changes in viral inactivation and droplet deposition under varying ambient environments. A non-steady-state-modified Wells-Riley model is established to predict the infection risk of shared air space and highlight the high-risk environmental conditions. Findings reveal that a rise in T would significantly reduce the transmission of COVID-19 in the cold season, while the effect is not significant in the hot season. The infection risk under low-T and high-RH conditions, such as the frozen seafood market, is substantially underestimated, which should be taken seriously. The study encourages selected containment measures against high-risk environmental conditions and cross-discipline management in the public health crisis based on meteorology, government, and medical research.

SARS-CoV-2 airborne transmission: a review of risk factors and possible preventative measures using air purifiers

The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the resulting worldwide death toll have prompted worries regarding its transmission mechanisms. Direct, indirect, and droplet modes are the basic mechanisms of transmission. SARS-CoV-2 spreads by respiratory droplets (size range >10 μm size ranges), aerosols (5 μm), airborne, and particulate matter. The rapid transmission of SARS-CoV-2 is due to the involvement of tiny indoor air particulate matter (PM_2.5), which functions as a vector. SARS-CoV-2 is more contagious in the indoor environment where particulate matter floats for a longer period and greater distances. Extended residence time in the environment raises the risk of SARS-CoV-2 entering the lower respiratory tract, which may cause serious infection and possibly death. To decrease viral transmission in the indoor environment, it is essential to catch and kill the SARS-CoV-2 virus and maintain virus-free air, which will significantly reduce viral exposure concerns. Therefore, effective air filters with anti-viral, anti-bacterial, and anti-air-pollutant characteristics are gaining popularity recently. It is essential to develop cost-effective materials based on nanoparticles and metal-organic frameworks in order to lower the risk of airborne transmission in developing countries. A diverse range of materials play an important role in the manufacturing of effective air filters. We have summarized in this review article the basic concepts of the transmission routes of SARS-CoV-2 virus and precautionary measures using air purifiers with efficient materials-based air filters for the indoor environment. The performance of air-filter materials, challenges and alternative approaches, and future perspectives are also presented. We believe that air purifiers fabricated with highly efficient materials can control various air pollutants and prevent upcoming pandemics.

Relation between PM2.5 pollution and Covid-19 mortality in Western Europe for the 2020-2022 period

The ambient air pollution by particulate matter (PM) has strong negative effects on human health. Recent studies have found correlations between pollution and mortality due to Covid-19. We present here an analysis of such correlation for 32 locations in 6 countries of the Western Europe (France, Germany, Italy, Netherlands, Spain, United Kingdom), for the 2020-2022 period. The data are weekly averaged, and the mortality values were normalized considering the population of the locations. A correlation is qualitatively found for the time-series of PM2.5 pollution and Covid-19 mortality. The higher mortality values occurred during the pollutions peaks, as presented for the city of Paris (France) and the Lombardy regions (Italia), one of the more polluted locations in Western Europe. An almost linear trend with a factor 5.5 ± 1.0 increase in mortality when the pollution increases to ~45 μg.m^-3 is found when considering all data. This leads to an increase of 10.5 ± 2.5 % of mortality per 1 μg.m^-3. More precisely, the trend depends on the period of the analysis and decreases with time (first spread of the pandemic in Spring 2020, mid-2020 - mid 2021 period where the pandemic was better managed, and vaccinal race after mid-2021). Finally, although the initial conditions could differ from one country to another, the relative trend of increase was similar for the countries here considered. Such results can have some implication on the management of the Covid-19 pandemic and other cardiopulmonary diseases during PM pollution events. They also show the importance of reducing the PM pollution in the major cities.

Association Between Weather Parameters and SARS-CoV-2 Confirmed Cases in Two South African Cities

Several approaches have been used in the race against time to mitigate the spread and impact of COVID-19. In this study, we investigated the role of temperature, relative humidity, and particulate matter in the spread of COVID-19 cases within two densely populated cities of South Africa-Pretoria and Cape Town. The role of different levels of COVID-19 restrictions in the air pollution levels, obtained from the Purple Air Network, of the two cities were also considered. Our results suggest that 26.73% and 43.66% reduction in PM2.5 levels were observed in Cape Town and Pretoria respectively for no lockdown (Level 0) to the strictest lockdown level (Level 5). Furthermore, our results showed a significant relationship between particulate matter and COVID-19 in the two cities. Particulate matter was found to be a good predictor, based on the significance of causality test, of COVID-19 cases in Pretoria with a lag of 7 days and more. This suggests that the effect of particulate matter on the number of cases can be felt after 7 days and beyond in Pretoria.

Analysis of airborne sputum droplets flow dynamic behaviors under different ambient conditions and aerosol size effects

The coronavirus (COVID-19) is becoming more threatening with the emergence of new mutations. New virus transmission and infection processes remain challenging and re-examinations of proper protection methods are urgently needed. From fluid dynamic viewpoint, the transmission of virus-carrying droplets and aerosols is one key to understanding the virus-transmission mechanisms. This study shows virus transmission by incorporating flow-evaporation model into the Navier-Stokes equation to describe the group of airborne sputum droplets exhaled under Rosin-Rammler distribution. Solid components and humidity field evolution are incorporated in describing droplet and ambient conditions. The numerical model is solved by an inhouse code using advection-diffusion equation for the temperature field and the humidity field, discretized by applying the total-variation diminishing Runge-Kutta method. The results of this study are presented in detail to show the different trends under various ambient conditions and to reveal the major viral-transmission routes as a function of droplet size.

Risk management and communication plans from SARS to COVID-19 and beyond

OBJECTIVE

Nowadays, due to globalisation, the likelihood that infectious diseases spread rapidly is extraordinarily high. SARS and COVID-19 are two diseases of the Coronavirus family, which developed in China and then spread internationally, causing global public health emergencies. This study investigates the role that risk management and communication systems played in mitigating these emergencies, to establish how they should be improved in the future.

METHODS

A narrative review was carried out to investigate different knowledge domains, such as risk management and communication, risk assessment and indicators, epidemiological and clinical data, diagnostic methods, vaccines, public health and social measures.

RESULTS

On one side, risk management systems assess the main data, knowledge, and indicators on epidemiology, diagnostics, and vaccines (science-based); on the other side, they apply public health and social measures (socially-based). Decision-makers, in fact, implement their actions by constantly balancing these two sides (policy-based).

CONCLUSIONS

A correct crisis management approach should support the governance of pandemics, by harmonising the actual risks assessed by experts with those perceived by the general population. It should incorporate not only the biological, but even the environmental, social and economic aspects of virus emergencies, towards establishing a suitable framework to deal with possible future pandemics.

Association Between Air Pollution, Climate Change, and COVID-19 Pandemic: A Review of the Recent Scientific Evidence

Background: Recent studies indicated the possible relationship between climate change, environmental pollution, and Coronavirus Disease 2019 (COVID-19) pandemic. This study reviewed the effects of air pollution, climate parameters, and lockdown on the number of cases and deaths related to COVID-19. Methods: The present review was performed to determine the effects of weather and air pollution on the number of cases and deaths related to COVID-19 during the lockdown. Articles were collected by searching the existing online databases, such as PubMed, Science Direct, and Google Scholar, with no limitations on publication dates. Afterwards, this review focused on outdoor air pollution, including PM2.5, PM10, NO2, SO2, and O3, and weather conditions affecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/COVID-19. Results: Most reviewed investigations in the present study showed that exposure to air pollutants, particularly PM2.5 and NO2, is positively related to COVID-19 patients and mortality. Moreover, these studies showed that air pollution could be essential in transmitting COVID-19. Local meteorology plays a vital role in coronavirus spread and mortality. Temperature and humidity variables are negatively correlated with virus transmission. The evidence demonstrated that air pollution could lead to COVID-19 transmission. These results support decision-makers in curbing potential new outbreaks. Conclusions: Overall, in environmental perspective-based COVID-19 studies, efforts should be accelerated regarding effective policies for reducing human emissions, bringing about air pollution and weather change. Therefore, using clean and renewable energy sources will increase public health and environmental quality by improving global air quality.

A comparative analysis of SARS-CoV-2 viral load across different altitudes

SARS-CoV-2 has spread throughout the world, including areas located at high or very high altitudes. There is a debate about the role of high altitude hypoxia on viral transmission, incidence, and COVID-19 related mortality. This is the first comparison of SARS-CoV-2 viral load across elevations ranging from 0 to 4300 m. To describe the SARS-CoV-2 viral load across samples coming from 62 cities located at low, moderate, high, and very high altitudes in Ecuador. An observational analysis of viral loads among nasopharyngeal swap samples coming from a cohort of 4929 patients with a RT-qPCR test positive for SARS-CoV-2. The relationship between high and low altitude only considering our sample of 4929 persons is equal in both cases and not significative (p-value 0.19). In the case of low altitude, adding the sex variable to the analysis, it was possible to find a significative difference between men and women (p-value < 0.05). Considering initially sex and then altitude, it was possible to find a significative difference between high and low altitude for men (p-value 0.05). There is not enough evidence to state that viral load is affected directly by altitude range but adding a new variable as sex in the analysis shows that the presence of new variables influences the relationship of altitude range and viral load. There is no evidence that viral loads (Ct and copies/ml) differ at low or high altitude. Using sex as a co-factor, we found that men have higher viral loads than women at low and moderate altitude locations, while living at high altitude, no differences were found. When Ct values were aggregated by low, moderate, and high viral load, we found no significant differences when sex was excluded from the analysis. We conclude that viral load is not directly affected by altitude, but COVID-19 incidence and mortality are rather affected by socio-demographic and idiosyncratic dynamics.

Cumulative effects of air pollution and climate drivers on COVID-19 multiwaves in Bucharest, Romania

Over more than two years of global health crisis due to ongoing COVID-19 pandemic, Romania experienced a five-wave pattern. This study aims to assess the potential impact of environmental drivers on COVID-19 transmission in Bucharest, capital of Romania during the analyzed epidemic period. Through descriptive statistics and cross-correlation tests applied to time series of daily observational and geospatial data of major outdoor inhalable particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) or ≤ 10 µm (PM10), nitrogen dioxide (NO₂), ozone (O₃), sulfur dioxide (SO₂), carbon monoxide (CO), Aerosol Optical Depth at 550 nm (AOD) and radon (²²²Rn), we investigated the COVID-19 waves patterns under different meteorological conditions. This study examined the contribution of individual climate variables on the ground level air pollutants concentrations and COVID-19 disease severity. As compared to the long-term average AOD over Bucharest from 2015 to 2019, for the same year periods, this study revealed major AOD level reduction by ~28 % during the spring lockdown of the first COVID-19 wave (15 March 2020-15 May 2020), and ~16 % during the third COVID-19 wave (1 February 2021-1 June 2021). This study found positive correlations between exposure to air pollutants PM2.5, PM10, NO₂, SO₂, CO and ²²²Rn, and significant negative correlations, especially for spring-summer periods between ground O₃ levels, air temperature, Planetary Boundary Layer height, and surface solar irradiance with COVID-19 incidence and deaths. For the analyzed time period 1 January 2020-1 April 2022, before and during each COVID-19 wave were recorded stagnant synoptic anticyclonic conditions favorable for SARS-CoV-2 virus spreading, with positive Omega surface charts composite average (Pa/s) at 850 mb during fall- winter seasons, clearly evidenced for the second, the fourth and the fifth waves. These findings are relevant for viral infections controls and health safety strategies design in highly polluted urban environments.

Interactions between climate and COVID-19

In this Personal View, we explain the ways that climatic risks affect the transmission, perception, response, and lived experience of COVID-19. First, temperature, wind, and humidity influence the transmission of COVID-19 in ways not fully understood, although non-climatic factors appear more important than climatic factors in explaining disease transmission. Second, climatic extremes coinciding with COVID-19 have affected disease exposure, increased susceptibility of people to COVID-19, compromised emergency responses, and reduced health system resilience to multiple stresses. Third, long-term climate change and prepandemic vulnerabilities have increased COVID-19 risk for some populations (eg, marginalised communities). The ways climate and COVID-19 interact vary considerably between and within populations and regions, and are affected by dynamic and complex interactions with underlying socioeconomic, political, demographic, and cultural conditions. These conditions can lead to vulnerability, resilience, transformation, or collapse of health systems, communities, and livelihoods throughout varying timescales. It is important that COVID-19 response and recovery measures consider climatic risks, particularly in locations that are susceptible to climate extremes, through integrated planning that includes public health, disaster preparedness, emergency management, sustainable development, and humanitarian response.

The effects of COVID-19 transmission on environmental sustainability and human health: Paving the way to ensure its sustainable management

The transmission dynamics and health risks of coronavirus disease 2019 (COVID-19) pandemic are inextricably linked to ineract with environment, climate, air pollution, and meteorological conditions. The spread of COVID-19 infection can thus perturb the 'planetary health' and livelihood by exerting impacts on the temporal and spatial variabilities of environmental pollution. Prioritization of COVID-19 by the health-care sector has been posing a serious threat to economic progress while undermining the efforts to meet the United Nations' Sustainable Development Goals (SDGs) for environmental sustainability. Here, we review the multifaceted effects of COVID-19 with respect to environmental quality, climatic variables, SDGs, energy resilience, and sustainability programs. It is well perceived that COVID-19 may have long-lasting and profound effects on socio-economic systems, food security, livelihoods, and the 'nexus' indicators. To seek for the solution of these problems, consensus can be drawn to establish and ensure a sound health-care system, a sustainable environment, and a circular bioeconomy. A holistic analysis of COVID-19's effects on multiple sectors should help develop nature-based solutions, cleaner technologies, and green economic recovery plans to help maintain environmental sustainability, ecosystem resilience, and planetary health.

Human Responses in Public Health Emergencies for Infectious Disease Control: An Overview of Controlled Topologies for Biomedical Applications

COVID-19 originated in Wuhan city of Hubei Province in China in December three years ago. Since then, it has spread to more than 210 countries and territories. This disease is caused by Severe Acute Respiratory Syndrome Coronavirus 2. The virus has a size of one to two nanometers and a single-stranded positive RNA. Droplets spread the virus from coughing and sneezing. This condition causes coughing, fever, acute respiratory problems, and even death. According to the WHO, the virus can survive outside the body for several hours. This research aimed to determine how environmental factors influenced the COVID-19 virus's survival and behavior, as well as its transmission, in a complex environment. Based on the results, virus transmissions are influenced by various human and environmental factors such as population distribution, travel, social behavior, and climate change. Environmental factors have not been adequately examined concerning the transmission of this epidemic. Thus, it is necessary to examine various aspects of prevention and control of this disease, including its effects on climate and other environmental factors.

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.

Autoantibodies and autoimmune disorders in SARS-CoV-2 infection: pathogenicity and immune regulation

Coronavirus disease 2019 (COVID-19) is an infectious disease associated with the respiratory system caused by the SARS-CoV-2 virus. The aim of this review article is to establish an understanding about the relationship between autoimmune conditions and COVID-19 infections. Although majority of the population have been protected with vaccines against this virus, there is yet a successful curative medication for this disease. The use of autoimmune medications has been widely considered to control the infection, thus postulating possible relationships between COVID-19 and autoimmune diseases. Several studies have suggested the correlation between autoantibodies detected in patients and the severity of the COVID-19 disease. Studies have indicated that the SARS-CoV-2 virus can disrupt the self-tolerance mechanism of the immune system, thus triggering autoimmune conditions. This review discusses the current scenario and future prospects of promising therapeutic strategies that may be employed to regulate such autoimmune conditions.

Modelling the persistence of Covid-19 positivity rate in Italy

The current Covid-19 pandemic is severely affecting public health and global economies. In this context, accurately predicting its evolution is essential for planning and providing resources effectively. This paper aims at capturing the dynamics of the positivity rate (PPR) of the novel coronavirus using the Heterogeneous Autoregressive (HAR) model. The use of this model is motivated by two main empirical features arising from the analysis of PPR time series: the changing long-run level and the persistent autocorrelation structure. Compared to the most frequently used Autoregressive Integrated Moving Average (ARIMA) models, the HAR is able to reproduce the strong persistence of the data by using components aggregated at different interval sizes, remaining parsimonious and easy to estimate. The relative merits of the proposed approach are assessed by performing a forecasting study on the Italian dataset. As a robustness check, the analysis of the positivity rate is also conducted by considering the case of the United States. The ability of the HAR-type models to predict the PPR at different horizons is evaluated through several loss functions, comparing the results with those generated by ARIMA models. The Model Confidence Set is used to test the significance of differences in the predictive performances of the models under analysis. Our findings suggest that HAR-type models significantly outperform ARIMA specifications in terms of forecasting accuracy. We also find that the PPR could represent an important metric for monitoring the evolution of hospitalizations, as the peak of patients in intensive care units occurs within 12-16 days after the peak in the positivity rate. This can help governments in planning socio-economic and health policies in advance.

Effects of environmental parameters and their interactions on the spreading of SARS-CoV-2 in North Italy under different social restrictions. A new approach based on multivariate analysis

In 2020 North Italy suffered the SARS-CoV-2-related pandemic with a high number of deaths and hospitalization. The effect of atmospheric parameters on the amount of hospital admissions (temperature, solar radiation, particulate matter, relative humidity and wind speed) is studied through about 8 months (May-December). Two periods are considered depending on different conditions: a) low incidence of COVID-19 and very few regulations concerning personal mobility and protection ("free/summer period"); b) increasing incidence of disease, social restrictions and use of personal protections ("confined/autumn period"). The "hospitalized people in medical area wards/100000 residents" was used as a reliable measure of COVID-19 spreading and load on the sanitary system. We developed a chemometric approach (multiple linear regression analysis) using the daily incidence of hospitalizations as a function of the single independent variables and of their products (interactions). Eight administrative domains were considered (altogether 26 million inhabitants) to account for relatively homogeneous territorial and social conditions. The obtained models very significantly match the daily variation of hospitalizations, during the two periods. Under the confined/autumn period, the effect of non-pharmacologic measures (social distances, personal protection, etc.) possibly attenuates the virus diffusion despite environmental factors. On the contrary, in the free/summer conditions the effects of atmospheric parameters are very significant through all the areas. Particulate matter matches the growth of hospitalizations in areas with low chronic particulate pollution. Fewer hospitalizations strongly correspond to higher temperature and solar radiation. Relative humidity plays the same role, but with a lesser extent. The interaction between solar radiation and high temperature is also highly significant and represents surprising evidence. The solar radiation alone and combined with high temperature exert an anti-SARS-CoV-2 effect, via both the direct inactivation of virions and the stimulation of vitamin D synthesis, improving immune system function.

Short-term influence of environmental factors and social variables COVID-19 disease in Spain during first wave (Feb-May 2020)

This study aims to identify the combined role of environmental pollutants and atmospheric variables at short term on the rate of incidence (TIC) and on the hospital admission rate (TIHC) due to COVID-19 disease in Spain. This study used information from 41 of the 52 provinces of Spain (from Feb. 1, 2021 to May 31, 2021). Using TIC and TIHC as dependent variables, and average daily concentrations of PM₁₀ and NO₂ as independent variables. Meteorological variables included maximum daily temperature (Tmax) and average daily absolute humidity (HA). Generalized linear models (GLM) with Poisson link were carried out for each provinces The GLM model controlled for trend, seasonalities, and the autoregressive character of the series. Days with lags were established. The relative risk (RR) was calculated by increases of 10 μg/m³ in PM₁₀ and NO₂ and by 1 °C in the case of Tmax and 1 g/m³ in the case of HA. Later, a linear regression was carried out that included the social determinants of health. Statistically significant associations were found between PM₁₀, NO₂, and the rate of COVID-19 incidence. NO₂ was the variable that showed greater association, both for TIC as well as for TIHC in the majority of provinces. Temperature and HA do not seem to have played an important role. The geographic distribution of RR in the studied provinces was very much heterogeneous. Some of the health determinants considered, including income per capita, presence of airports, average number of diesel cars per inhabitant, average number of nursing personnel, and homes under 30 m² could explain the differential geographic behavior. As findings indicates, environmental factors only could modulate the incidence and severity of COVID-19. Moreover, the social determinants and public health measures could explain some patterns of geographically distribution founded.

SARS-CoV-2 Viral Load Analysis at Low and High Altitude: A Case Study from Ecuador

SARS-CoV-2 has spread throughout the world, including remote areas such as those located at high altitudes. There is a debate about the role of hypobaric hypoxia on viral transmission and COVID-19 incidence. A descriptive cross-sectional analysis of SARS-CoV-2 infection and viral load among patients living at low (230 m) and high altitude (3800 m) in Ecuador was completed. Within these two communities, the total number of infected people at the time of the study was 108 cases (40.3%). The COVID-19 incidence proportion at low altitude was 64% while at high altitude was 30.3%. The mean viral load from those patients who tested positive was 3,499,184 copies/mL (SD = 23,931,479 copies/mL). At low altitude (Limoncocha), the average viral load was 140,223.8 copies/mL (SD = 990,840.9 copies/mL), while for the high altitude group (Oyacachi), the mean viral load was 6,394,789 copies/mL (SD = 32,493,469 copies/mL). We found no statistically significant differences when both results were compared (p = 0.056). We found no significant differences across people living at low or high altitude; however, men and younger populations had higher viral load than women older populations, respectively.

Spatial epidemiology and meteorological risk factors of COVID-19 in Fars Province, Iran

This study aimed at detecting space-time clusters of COVID-19 cases in Fars Province, Iran and at investigating their potential association with meteorological factors, such as temperature, precipitation and wind velocity. Time-series data including 53,554 infected people recorded in 26 cities from 18 February to 30 September 2020 together with 5876 meteorological records were subjected to the analysis. Applying a significance level of P<0.05, the analysis of space-time distribution of COVID-19 resulted in nine significant outbreaks within the study period. The most likely cluster occurred from 27 March to 13 July 2020 and contained 11% of the total cases with eight additional, secondary clusters. We found that the COVID-19 incidence rate was affected by high temperature (OR=1.64; 95% CI: 1.44-1.87), while precipitation and wind velocity had less effect (OR=0.84; 95% CI: 0.75-0.89 and OR=0.27; 95% CI: 0.14-0.51), respectively.

Transmission of COVID-19 pandemic (Turkey) associated with short-term exposure of air quality and climatological parameters

The study aims to investigate associations between air pollution, climate parameters, and the diffusion of COVID-19-confirmed cases in Turkey using Spearman's correlation test as an empirical methodology by Statgraphics Centurion XVI (version 16.1) and to determine the risk factors accelerating the spread of SARS-CoV-2 virus. The present study demonstrates the strong impacts of air pollutants and weather conditions on the transmission of COVID-19 morbidity. Particularly, O3 and PM10 from air quality parameters exhibited the strongest correlation with the number of daily cases in Kütahya (rs = -0.62; p < 0.05) and Sivas (rs = -0.62; p < 0.05) provinces, respectively. In meteorological parameters, rainfall showed the highest impact (rs = 0.76; p < 0.05) on the number of daily COVID-19 cases in Denizli distinct. Moreover, this study suggested that the diffusion of the novel coronavirus SARS-CoV-2 in regions with high levels of air pollution and low wind speed is dominant. To prevent the negative effects of the future pandemic crisis on public health and economic systems, manifold implications to encourage strategies to reduce air pollution in the polluted region such as being prevalent the usage of renewable energy technologies in particular electricity generation and sustainable policies such as improving the health system should be implemented by decision-makers.

Dynamics of SARS-CoV-2 spreading under the influence of environmental factors and strategies to tackle the pandemic: A systematic review

COVID-19 is deemed as the most critical world health calamity of the 21st century, leading to dramatic life loss. There is a pressing need to understand the multi-stage dynamics, including transmission routes of the virus and environmental conditions due to the possibility of multiple waves of COVID-19 in the future. In this paper, a systematic examination of the literature is conducted associating the virus-laden-aerosol and transmission of these microparticles into the multimedia environment, including built environments. Particularly, this paper provides a critical review of state-of-the-art modelling tools apt for COVID-19 spread and transmission pathways. GIS-based, risk-based, and artificial intelligence-based tools are discussed for their application in the surveillance and forecasting of COVID-19. Primary environmental factors that act as simulators for the spread of the virus include meteorological variation, low air quality, pollen abundance, and spatial-temporal variation. However, the influence of these environmental factors on COVID-19 spread is still equivocal because of other non-pharmaceutical factors. The limitations of different modelling methods suggest the need for a multidisciplinary approach, including the 'One-Health' concept. Extended One-Health-based decision tools would assist policymakers in making informed decisions such as social gatherings, indoor environment improvement, and COVID-19 risk mitigation by adapting the control measurements.