Optimal temperature zone for the dispersal of COVID-19

Improvement of the global prediction system of the COVID-19 pandemic based on the ensemble empirical mode decomposition (EEMD) and autoregressive moving average (ARMA) model in a hybrid approach 基于集合经验模态分解和自回归-移动平均模型的 COVID-19 流行病全球预测系统预测结果改进

In 2020, the COVID-19 pandemic spreads rapidly around the world. To accurately predict the number of daily new cases in each country, Lanzhou University has established the Global Prediction System of the COVID-19 Pandemic (GPCP). In this article, the authors use the ensemble empirical mode decomposition (EEMD) model and autoregressive moving average (ARMA) model to improve the prediction results of GPCP. In addition, the authors also conduct direct predictions for those countries with a small number of confirmed cases or are in the early stage of the disease, whose development trends of the pandemic do not fully comply with the law of infectious diseases and cannot be predicted by the GPCP model. Judging from the results, the absolute values of the relative errors of predictions in countries such as Cuba have been reduced significantly and their prediction trends are closer to the real situations through the method mentioned above to revise the prediction results out of GPCP. For countries such as El Salvador with a small number of cases, the absolute values of the relative errors of prediction become smaller. Therefore, this article concludes that this method is more effective for improving prediction results and direct prediction.

摘要

2020年, 新型冠状病毒肺炎 (COVID-19) 在世界范围内迅速传播.为准确预测各国每日新增发病人数, 兰州大学开发了 COVID-19 流行病全球预测系统 (GPCP). 在本文的研究中, 我们使用集合经验模态分解 (EEMD) 模型和自回归-移动平均 (ARMA) 模型对 GPCP 的预测结果进行改进, 并对发病人数较少或处于发病初期, 不完全符合传染病规律, GPCP 模型无法预测的国家进行直接预测.从结果来看, 使用该方法修正预测结果, 古巴等国家预测误差均大幅下降, 且预测趋势更接近真实情况.对于萨尔瓦多等发病人数较少的国家直接进行预测, 相对误差较小, 预测结果较为准确.该方法对于改进预测结果和直接预测均较为有效.

Investigating connections between COVID-19 pandemic, air pollution and community interventions for Pakistan employing geoinformation technologies

Several major cities that witnessed heavy air pollution by particulate matter (PM2.5) concentration and nitrogen dioxide (NO2) have contributed to high rate of infection and severity of the coronavirus disease (COVID-19) pandemic. Owing to the negative impact of COVID-19 on health and economy, it is imperative to predict the pandemic trend of the COVID-19 outbreak. Pakistan is one of the mostly affected countries by recent COVID-19 pandemic in terms of COVID-cases and economic crises. Like other several Asian countries to combat the virus impacts, Pakistan implemented non-pharmacological interventions (NPI), such as national lockdowns. The current study investigates the effect of major interventions across three out of four provinces of Pakistan for the period from the start of the COVID-19 in March 22, 2020 until June 30, 2020, when lockdowns were started to be eased. High-resolution data on NO2 was recorded from Sentinel-5's Precursor spacecraft with TROPOspheric Monitoring Instrument (Sentinel-5P TROPOMI). Similarly, PM2.5 data were collected from sampling sties to investigate possible correlation among these pollutants and COVID-19. In addition, growth and susceptible-infected-recovered (SIR) models utilizing time-series data of COVID-19 from February 26 to December 31, 2020, with- and without NPI that encompass the predicted number of infected cases, peak time, impact on the healthcare system and mortality in Pakistan. Maximum mean PM2.5 concentration of 108 μgm-3 was recorded for Lahore with the range from 51 to 215 μgm-3, during strict lockdown (L), condition. This is three times higher than Pak-EPA and US-EPA and four times for WHO guidelines, followed by Peshawar (97.2 and 58 ± 130), Islamabad (83 and 158 ± 58), and Karachi (78 and 50 ± 140). The majority of sampling sites in Lahore showed NO2 levels higher than 8.75E-5 (mol/m2) in 2020 compared to 2019 during "L" period. The susceptible-infected-recovered (SIR) model depicted a strong correlation (r) between the predicted and reported cases for Punjab (r = 0.79), Sindh (r = 0.91), Khyber Pakhtunkhwa (KPK) (r = 94) and Islamabad (r = 0.85). Findings showed that major NPI and lockdowns especially have had a large effect on minimizing transmission. Continued community intervention should be undertaken to keep transmission of SARS-CoV-2 under control in cities where higher incidence of COVID-19 cases until the vaccine is available. This study provides a methodological framework that if adopted can assist epidemiologist and policy makers to be well-prepared in advance in cities where PM2.5 concentration and NO2 levels are already high in order to minimize the potential risk of further spread of COVID-19 cases.

Influence of population density, temperature, and absolute humidity on spread and decay durations of COVID-19: A comparative study of scenarios in China, England, Germany, and Japan

In this study, we analyzed the spread and decay durations of the COVID-19 pandemic in several cities of China, England, Germany, and Japan, where the first wave has undergone decay. Differences in medical and health insurance systems, as well as in regional policies incommoded the comparison of the spread and decay in different cities and countries. The spread and decay durations in the cities of the four studied countries were reordered and calculated based on an asymmetric bell-shaped model. We acquired the values of the ambient temperature, absolute humidity, and population density to perform multivariable analysis. We found a significant correlation (p < 0.05) of the spread and decay durations with population density in the four analyzed countries. Specifically, spread duration showed a high correlation with population density and absolute humidity (p < 0.05), whereas decay duration demonstrated the highest correlation with population density, absolute humidity, and maximum temperature (p < 0.05). The effect of population density was almost nonexistent in China because of the implemented strict lockdown. Our findings will be useful in policy setting and governmental actions in the next pandemic, as well as in the next waves of COVID-19.

A review of the impact of weather and climate variables to COVID-19: In the absence of public health measures high temperatures cannot probably mitigate outbreaks

The new severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) pandemic was first recognized at the end of 2019 and has caused one of the most serious global public health crises in the last years. In this paper, we review current literature on the effect of weather (temperature, humidity, precipitation, wind, etc.) and climate (temperature as an essential climate variable, solar radiation in the ultraviolet, sunshine duration) variables on SARS-CoV-2 and discuss their impact to the COVID-19 pandemic; the review also refers to respective effect of urban parameters and air pollution. Most studies suggest that a negative correlation exists between ambient temperature and humidity on the one hand and the number of COVID-19 cases on the other, while there have been studies which support the absence of any correlation or even a positive one. The urban environment and specifically the air ventilation rate, as well as air pollution, can probably affect, also, the transmission dynamics and the case fatality rate of COVID-19. Due to the inherent limitations in previously published studies, it remains unclear if the magnitude of the effect of temperature or humidity on COVID-19 is confounded by the public health measures implemented widely during the first pandemic wave. The effect of weather and climate variables, as suggested previously for other viruses, cannot be excluded, however, under the conditions of the first pandemic wave, it might be difficult to be uncovered. The increase in the number of cases observed during summertime in the Northern hemisphere, and especially in countries with high average ambient temperatures, demonstrates that weather and climate variables, in the absence of public health interventions, cannot mitigate the resurgence of COVID-19 outbreaks.

A review of the impact of weather and climate variables to COVID-19: In the absence of public health measures high temperatures cannot probably mitigate outbreaks

The new severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) pandemic was first recognized at the end of 2019 and has caused one of the most serious global public health crises in the last years. In this paper, we review current literature on the effect of weather (temperature, humidity, precipitation, wind, etc.) and climate (temperature as an essential climate variable, solar radiation in the ultraviolet, sunshine duration) variables on SARS-CoV-2 and discuss their impact to the COVID-19 pandemic; the review also refers to respective effect of urban parameters and air pollution. Most studies suggest that a negative correlation exists between ambient temperature and humidity on the one hand and the number of COVID-19 cases on the other, while there have been studies which support the absence of any correlation or even a positive one. The urban environment and specifically the air ventilation rate, as well as air pollution, can probably affect, also, the transmission dynamics and the case fatality rate of COVID-19. Due to the inherent limitations in previously published studies, it remains unclear if the magnitude of the effect of temperature or humidity on COVID-19 is confounded by the public health measures implemented widely during the first pandemic wave. The effect of weather and climate variables, as suggested previously for other viruses, cannot be excluded, however, under the conditions of the first pandemic wave, it might be difficult to be uncovered. The increase in the number of cases observed during summertime in the Northern hemisphere, and especially in countries with high average ambient temperatures, demonstrates that weather and climate variables, in the absence of public health interventions, cannot mitigate the resurgence of COVID-19 outbreaks.

Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan

Information on the spatiotemporal variability of respirable suspended particulate pollutant matter concentrations, especially of particles having size of 2.5 μm and climate are the important factors in relation to emerging COVID-19 cases around the world. This study aims at examining the association between COVID-19 cases, air pollution, climatic and socioeconomic factors using geospatial techniques in three provincial capital cities and the federal capital city of Pakistan. A series of relevant data was acquired from 3 out of 4 provinces of Pakistan (Punjab, Sindh, Khyber Pakhtunkhwa (KPK) including the daily numbers of COVID-19 cases, PM2.5 concentration (μgm-3), a climatic factors including temperature (°F), wind speed (m/s), humidity (%), dew point (%), and pressure (Hg) from June 1 2020, to July 31 2020. Further, the possible relationships between population density and COVID-19 cases was determined. The generalized linear model (GLM) was employed to quantify the effect of PM2.5, temperature, dew point, humidity, wind speed, and pressure range on the daily COVID-19 cases. The grey relational analysis (GRA) was also implemented to examine the changes in COVID-19 cases with PM2.5 concentrations for the provincial city Lahore. About 1,92, 819 COVID-19 cases were reported in Punjab, Sindh, KPK, and Islamabad during the study period. Results indicated a significant relationship between COVID-19 cases and PM2.5 and climatic factors at p < 0.05 except for Lahore in case of humidity (r = 0.175). However, mixed correlations existed across Lahore, Karachi, Peshawar, and Islamabad. The R2 value indicates a moderate relationship between COVID-19 and population density. Findings of this study, although are preliminary, offers the first line of evidence for epidemiologists and may assist the local community to expedient for the growth of effective COVID-19 infection and health risk management guidelines. This remains to be seen.

Changes in the concentration of air pollutants before and after the COVID-19 blockade period and their correlation with vegetation coverage

In order to control the spread of COVID-19, China had implemented strict lockdown measures. The closure of cities had had a huge impact on human production and consumption activities, which had greatly reduced population mobility. This article used air pollutant data from 341 cities in mainland China and divided these cities into seven major regions based on geographic conditions and climatic environment. The impact of urban blockade on air quality during COVID-19 was studied from the perspectives of time, space, and season. In addition, this article used Normalized Difference Vegetation Index (NDVI) to systematically analyze the characteristics of air pollution in the country and used the Pearson correlation coefficient to explore the relationship between NDVI and the air pollutant concentrations during the COVID-19 period. Then, linear regression was used to find the quantitative relationship between NDVI and AQI, and the fitting effect of the model was found to be significant through t test. Finally, some countermeasures were proposed based on the analysis results, and suggestions were provided for improving air quality. This paper has drawn the following conclusions: (1) the concentration of pollutants varied greatly in different regions, and the causes of their pollution sources were also different. The region with the largest decline in AQI was the Northeast China (60.01%), while the AQI in the southwest China had the smallest change range, and its value had increased by 1.72%. In addition, after the implementation of the city blockade, the concentration of NO2 in different regions dropped the most, but the increase in O3 was more obvious. (2) Higher vegetation coverage would have a beneficial impact on the atmospheric environment. Areas with higher NDVI values have relatively low AQI. There is a negative correlation between NDVI and AQI, and an average increase of 0.1 in NDVI will reduce AQI by 3.75 (95% confidence interval). In the case of less human intervention, the higher the vegetation coverage, the lower the local pollutant concentration will be. Therefore, the degree of vegetation coverage would have a direct or indirect impact on air pollution.

Is coronavirus disease (COVID-19) seasonal? A critical analysis of empirical and epidemiological studies at global and local scales

Coronavirus disease (COVID-19) has infected more than 50 million people and killed more than one million, worldwide, during less than a year course. COVID-19, which has already become the worst pandemic in the last 100 years, is still spreading worldwide. Since the beginning of the outbreak, it has been of particular interest to understand whether COVID-19 is seasonal; the finding might help for better planning and preparation for the fight against the disease. Over the past 12 months, numerous empirical and epidemiological studies have been performed to define the distinct diffusion patterns of COVID-19. Thereby, a wealth of data has accumulated on the relationship between various seasonal meteorological factors and COVID-19 transmissibility at global and local scales. In this review, we aimed to discuss whether COVID-19 exhibits any seasonal features in a global and local perspective by collecting and providing summaries of the findings from empirical and epidemiological studies on the COVID-19 pandemic during its first seasonal cycle.

Social distancing enhanced automated optimal design of physical spaces in the wake of the COVID-19 pandemic

As the COVID-19 pandemic unfolds, manually enhanced ad-hoc solutions have helped the physical space designers and decision makers to cope with the dynamic nature of space planning. Due to the unpredictable nature by which the pandemic is unfolding, the standard operating procedures also change, and the protocols for physical interaction require continuous reconsideration. Consequently, the development of an appropriate technological solution to address the current challenge of reconfiguring common physical environments with prescribed physical distancing measures is much needed. To do this, we propose a design optimization methodology which takes the dimensions, as well as the constraints and other necessary requirements of a given physical space to yield optimal redesign solutions on the go. The methodology we propose here utilizes the solution to the well-known mathematical circle packing problem, which we define as a constrained mathematical optimization problem. The resulting optimization problem is solved subject to a given set of parameters and constraints - corresponding to the requirements on the social distancing criteria between people and the imposed constraints on the physical spaces such as the position of doors, windows, walkways and the variables related to the indoor airflow pattern. Thus, given the dimensions of a physical space and other essential requirements, the solution resulting from the automated optimization algorithm can suggest an optimal set of redesign solutions from which a user can pick the most feasible option. We demonstrate our automated optimal design methodology by way of a number of practical examples, and we discuss how this framework can be further taken forward as a design platform that can be implemented practically.

The first wave of the SARS-CoV-2 epidemic in Tuscany (Italy): A SI2R2D compartmental model with uncertainty evaluation

With the aim of studying the spread of the SARS-CoV-2 infection in the Tuscany region of Italy during the first epidemic wave (February-June 2020), we define a compartmental model that accounts for both detected and undetected infections and assumes that only notified cases can die. We estimate the infection fatality rate, the case fatality rate, and the basic reproduction number, modeled as a time-varying function, by calibrating on the cumulative daily number of observed deaths and notified infected, after fixing to plausible values the other model parameters to assure identifiability. The confidence intervals are estimated by a parametric bootstrap procedure and a Global Sensitivity Analysis is performed to assess the sensitivity of the estimates to changes in the values of the fixed parameters. According to our results, the basic reproduction number drops from an initial value of 6.055 to 0 at the end of the national lockdown, then it grows again, but remaining under 1. At the beginning of the epidemic, the case and the infection fatality rates are estimated to be 13.1% and 2.3%, respectively. Among the parameters considered as fixed, the average time from infection to recovery for the not notified infected appears to be the most impacting one on the model estimates. The probability for an infected to be notified has a relevant impact on the infection fatality rate and on the shape of the epidemic curve. This stresses the need of collecting information on these parameters to better understand the phenomenon and get reliable predictions.

Evaluating the Environmental Impacts of Personal Protective Equipment Use by the General Population during the COVID-19 Pandemic: A Case Study of Lombardy (Northern Italy)

The diffusion of Coronavirus disease (COVID-19) impacted the whole world, changing the life habits of billions of people. These changes caused an abundant increase in personal protective equipment (PPE, e.g., masks and gloves) use by the general population, which can become a concerning issue of plastic pollution. This study aims to evaluate the negative effects of the abundant PPE use following the COVID-19 diffusion using the test site of the Lombardy region, an area highly affected by the pandemic. Population data were retrieved from national databases, and the COVID-19 national guidelines were considered to estimate the total use of PPEs during 2020. Then, the quantity of waste derived from their use was evaluated based on the weight of PPEs. As well, possible scenarios for 2021 were proposed based on 2020 estimations. The results suggested different negative effects of the diffusion of PPEs both on waste management and on the environment: The abundant increase in PPEs-derived waste caused an increase in terms of costs for management, and the potential direct spreading in the environment of these materials (especially masks) poses a serious threat for an increase in microplastics in water bodies. Following this evaluation, a careful choice regarding COVID-19 measures of containment should be performed especially by the general population, avoiding contagion diffusion and reducing the possible environmental impact derived from disposable PPE use.

Observed and estimated prevalence of Covid-19 in Italy: How to estimate the total cases from medical swabs data

During the Covid-19 pandemic in Italy, official data are collected with medical swabs following a pure convenience criterion which, at least in an early phase, has privileged the exam of patients showing evident symptoms. However, there are evidences of a very high proportion of asymptomatic patients. In this situation, in order to estimate the real number of infected (and to estimate the lethality rate), it should be necessary to run a properly designed sample survey through which it would be possible to calculate the probability of inclusion and hence draw sound probabilistic inference. Unfortunately, the survey run by the Italian Statistical Institute encountered many field difficulties. Some researchers proposed estimates of the total prevalence based on various approaches, including epidemiologic models, time series and the analysis of data collected in countries that faced the epidemic in earlier times. In this paper, we propose to estimate the prevalence of Covid-19 in Italy by reweighting the available official data published by the Istituto Superiore di Sanità so as to obtain a more representative sample of the Italian population. Reweighting is a procedure commonly used to artificially modify the sample composition so as to obtain a distribution which is more similar to the population. In this paper, we will use post-stratification of the official data, in order to derive the weights necessary for reweighting the sample results, using age and gender as post-stratification variables, thus obtaining more reliable estimation of prevalence and lethality. Specifically, for Italy, we obtain a prevalence of 9%. The proposed methodology represents a reasonable approximation while waiting for more reliable data obtained with a properly designed national sample survey and that it could be further improved if more data were made available.

Estimating aerosol transmission risk of SARS-CoV-2 in New York City public schools during reopening

The objective of this study was to estimate the risk of SARS-CoV-2 transmission among students and teachers in New York City public schools, the largest school system in the US. Classroom measurements conducted from December 2017 to September 2018 were used to estimate risk of SARS-CoV-2 transmission using a modified Wells-Riley equation under a steady-state conditions and varying exposure scenarios (infectious student versus teacher, susceptible student versus teacher, with and without masks). We then used multivariable linear regression with GEE to identify school and classroom factors that impact transmission risk. Overall, 101 classrooms in 19 schools were assessed, 86 during the heating season, 69 during cooling season, and 54 during both. The mean probability of transmission was generally low but varied by scenario (range: 0.0015-0.81). Transmission rates were higher during the heating season (beta=0.108, p=0.010), in schools in higher income neighborhoods (>80K versus 20K-40K beta=0.196, p<0.001) and newer buildings (<50 years beta=0.237, p=<0.001; 50-99 years beta=0.230, p=0.013 versus 100+ years) and lower in schools with mechanical ventilation (beta=0.141, p=0.057). Surprisingly, schools located in older buildings and lower-income neighborhoods had lower transmission probabilities, likely due to the greater outdoor airflow associated with an older, non-renovated buildings that allow air to leak in (i.e. drafty buildings). Despite the generally low risk of school-based transmission found in this study, with SARS-CoV-2 prevalence rising in New York City this risk will increase and additional mitigation steps should be implemented in schools now.

The role of seasonality in the spread of COVID-19 pandemic

It has been reported that the transmission of COVID-19 can be influenced by the variation of environmental factors due to the seasonal cycle. However, its underlying mechanism in the current and onward transmission pattern remains unclear owing to the limited data and difficulties in separating the impacts of social distancing. Understanding the role of seasonality in the spread of the COVID-19 pandemic is imperative in formulating public health interventions. Here, the seasonal signals of the COVID-19 time series are extracted using the EEMD method, and a modified Susceptible, Exposed, Infectious, Recovered (SEIR) model incorporated with seasonal factors is introduced to quantify its impact on the current COVID-19 pandemic. Seasonal signals decomposed via the EEMD method indicate that infectivity and mortality of SARS-CoV-2 are both higher in colder climates. The quantitative simulation shows that the cold season in the Southern Hemisphere countries caused a 59.71 ± 8.72% increase of the total infections, while the warm season in the Northern Hemisphere countries contributed to a 46.38 ± 29.10% reduction. COVID-19 seasonality is more pronounced at higher latitudes, where larger seasonal amplitudes of environmental indicators are observed. Seasonality alone is not sufficient to curb the virus transmission to an extent that intervention measures are no longer needed, but health care capacity should be scaled up in preparation for new surges in COVID-19 cases in the upcoming cold season. Our study highlights the necessity of considering seasonal factors when formulating intervention strategies.

Temperature dependence of COVID-19 transmission

The recent COVID-19 pandemic follows in its early stages an almost exponential expansion, with the number of cases as a function of time reasonably well fit by N(t) ∝ eαt, in many countries. We analyze the rate α in different countries, starting in each country from a threshold of 30 total cases and fitting for the following 12 days, capturing thus the early exponential growth in a rather homogeneous way. We look for a link between the rate α and the average temperature T of each country, in the month of the initial epidemic growth. We analyze a base set of 42 countries, which developed the epidemic at an earlier stage, an intermediate set of 88 countries and an extended set of 125 countries, which developed the epidemic more recently. Fitting with a linear behavior α(T), we find increasing evidence in the three datasets for a slower spread at high T, at 99.66% C.L., 99.86% C.L. and 99.99995% C.L. (p-value 5⋅10-7, or 5σ detection) in the base, intermediate and extended dataset, respectively. The doubling time at 25 °C is 40% ~ 50% longer than at 5 °C. Moreover we analyzed the possible existence of a bias: poor countries, typically located in warm regions, might have less intense testing. By excluding countries below a given GDP per capita from the dataset, we find that this affects our conclusions only slightly and only for the extended dataset. The significance always remains high, with a p-value of about 10-3 - 10-4 or less. Our findings give hope that, for northern hemisphere countries, the growth rate should significantly decrease as a result of both warmer weather and lockdown policies. In general, policy measures should be taken to prevent a second wave, such as safe ventilation in public buildings, social distancing, use of masks, testing and tracking policies, before the arrival of the next cold season.

Airborne dispersion of droplets during coughing: a physical model of viral transmission

The Covid-19 pandemic has focused attention on airborne transmission of viruses. Using realistic air flow simulation, we model droplet dispersion from coughing and study the transmission risk related to SARS-CoV-2. Although this model defines most airborne droplets as 8-16 µm in diameter, we infer that larger droplets of 32-40 µm in diameter may potentially be more infectious due to higher viral content. Use of face masks is therefore recommended for both personal and social protection. We found social distancing effective at reducing transmission potential across all droplet sizes. However, the presence of a human body 1 m away modifies the aerodynamics so that downstream droplet dispersion is enhanced, which has implications on safe distancing in queues. At 1 m distance, we found that an average of 0.55 viral copies is inhaled for a cough at median loading, scalable up to 340 copies at peak loading. Droplet evaporation results in significant reduction in droplet counts, but airborne transmission remains possible even under low humidity conditions.

Unconditional and conditional analysis between covid-19 cases, temperature, exchange rate and stock markets using wavelet coherence and wavelet partial coherence approaches

This paper examines the time-frequency relationship between the number of confirmed COVID-19 cases, temperature, exchange rates and stock market return in the top-15 most affected countries by the COVID-19 pandemic. We employ Wavelet Coherence and Partial Wavelet Coherence on the daily data from 1st February, 2020 to 13th May, 2020. This study adds to the literature by implementing the Wavelet Coherence technique to explore the unexpected outbreak effects of the global pandemic on temperature, exchange rates and stock market returns. Our results reveal (i) there is evidence of cyclicality between temperature and COVID-19 cases, implying that average daily temperature has a significant impact on the spread of the COVID-19 disease in most of the countries; (ii) strong connectedness at low frequencies display that COVID-19 cases have a significant long-term impact on the exchange rate returns and stock markets returns of the most affected countries under study; (iii) after controlling for the effect of stock market returns and temperature, the co-movements between the confirmed COVID-19 cases and exchange rate returns becomes stronger; (iv) after controlling for the effect of exchange rate returns and temperature, the co-movements between the confirmed COVID-19 cases and stock market returns become stronger. Apart from theoretical contribution, this paper offers value to investors and policymakers as they attempt to combat the coronavirus risk and shape the economy and stock market behavior.

Environmental Indicator for COVID-19 Non-Pharmaceutical Interventions

A novel coronavirus (COVID-19) has caused viral pneumonia worldwide, posing a major threat to international health. Our study reports that city lockdown is an effective way to reduce the number of new cases and the nitrogen dioxide (NO2) concentration can be used as an environmental lockdown indicator to evaluate the effectiveness of lockdown measures. The airborne NO2 concentration steeply decreased over the vast majority of COVID-19-hit areas since the lockdown. The total number of newly confirmed cases reached an inflection point about two weeks since the lockdown and could be reduced by about 50% within 30 days of the lockdown. The stricter lockdown will help newly confirmed cases to decline earlier and more rapidly, and at the same time, the reduction rate of NO2 concentration will increase. Our research results show that NO2 satellite observations can help decision makers effectively monitor and manage non-pharmaceutical interventions in the epidemic.

Pareto-based evaluation of national responses to COVID-19 pandemic shows that saving lives and protecting economy are non-trade-off objectives

Countries worldwide have adopted various strategies to minimize the socio-economic impact of the ongoing COVID-19 pandemic. Stringency of imposed measures universally reflects the standpoint from which protecting public health and avoiding damage to economy are seen as contradictory objectives. Based on epidemic trajectories of 25 highly developed countries and 10 US states in the (mobility reduction)–(reproduction number) plane we showed that delay in imposition of nation-wide quarantine elevates the number of infections and deaths, surge of which inevitably has to be suppressed by stringent and sustained lockdown. As a consequence, cumulative mobility reduction and population-normalized cumulative number of COVID-19-associated deaths are significantly correlated and this correlation increases with time. Overall, we demonstrated that, as long as epidemic suppression is the aim, the trade-off between the death toll and economic loss is illusory: high death toll correlates with deep and long-lasting lockdown causing a severe economic downturn.

Weather Variability and COVID-19 Transmission: A Review of Recent Research

Weather and climate play a significant role in infectious disease transmission, through changes to transmission dynamics, host susceptibility and virus survival in the environment. Exploring the association of weather variables and COVID-19 transmission is vital in understanding the potential for seasonality and future outbreaks and developing early warning systems. Previous research examined the effects of weather on COVID-19, but the findings appeared inconsistent. This review aims to summarize the currently available literature on the association between weather and COVID-19 incidence and provide possible suggestions for developing weather-based early warning system for COVID-19 transmission. Studies eligible for inclusion used ecological methods to evaluate associations between weather (i.e., temperature, humidity, wind speed and rainfall) and COVID-19 transmission. The review showed that temperature was reported as significant in the greatest number of studies, with COVID-19 incidence increasing as temperature decreased and the highest incidence reported in the temperature range of 0–17 °C. Humidity was also significantly associated with COVID-19 incidence, though the reported results were mixed, with studies reporting positive and negative correlation. A significant interaction between humidity and temperature was also reported. Wind speed and rainfall results were not consistent across studies. Weather variables including temperature and humidity can contribute to increased transmission of COVID-19, particularly in winter conditions through increased host susceptibility and viability of the virus. While there is less indication of an association with wind speed and rainfall, these may contribute to behavioral changes that decrease exposure and risk of infection. Understanding the implications of associations with weather variables and seasonal variations for monitoring and control of future outbreaks is essential for early warning systems.

Meteorological parameters and COVID-19 spread-Russia a case study

An attempt was made in this chaper to understand the meteorological controls on SARS-CoV-2 (COVID-19) spread in Russia. Russia is one of the most affected country for COVID-19 and significant death cases were recorded. A continuous seven-month data from 31 January to 23 August 2020 from different locations in the country was collected through the commonly available websites. COVID data (total cases (966189), daily new cases (11656), daily deaths (232), and total recovered (777960)) and meteorological parameters (temperature, dew, precipitation, humidity, and wind speed) were used for this analysis. The results show an increasing trend of daily new cases and daily deaths during lock down period, and it gradually decreased or stabilized in the post lock down period. It infers the effectiveness of movement control during the lock down period, that stops further spreading. The positive correlation between COVID cases and temperature indicate that the increase of temperature increases the spreading and vice versa. The negative relationship of humidity with death cases also facilitates the pandemic spread. Thus, the outcome of this study may help to address concerns about the COVID-19 pandemic among the public and policymakers.

Lessons learned and questions raised during and post-COVID-19 anthropopause period in relation to the environment and climate

In the first part, this work reports that during the global "anthropopause" period, that was imposed in March and April 2020 for limiting the spread of COVID-19, the concentrations of basic air pollutants over Europe were reduced by up to 70%. During May and June, the gradual lift of the stringent measures resulted in the recovery of these reductions with pollution concentrations approaching the levels before the lockdown by the end of June 2020. In the second part, this work examines the alleged correlations between the reported cases of COVID-19 and temperature, humidity and particulate matter for March and April 2020 in Europe. It was found that decreasing temperatures and relative humidity with increasing concentrations of particulate matter are correlated with an increase in the number of reported cases during these 2 months. However, when these calculations were repeated for May and June, we found a remarkable drop in the significance of the correlations which leads us to question the generally accepted inverse relation between pandemics and air temperature at least during the warmer months. Such a relationship could not be supported in our study for SARS-CoV-2 virus and the question remains open. In the third and last part of this work, we examine the question referring to the origin of pandemics. In this context we have examined the hypothesis that the observed climate warming in Siberia and the Arctic and the thawing of permafrost could result to the release of trapped in the permafrost pathogens in the atmosphere. We find that although such relations cannot be directly justified, they present a possible horrifying mechanism for the origin of viruses in the future during the developing global warming of our planet in the decades to come. Overall the findings of our study indicate that: (1) the reduction of anthropogenic emissions in Europe during the "anthropopause" period of March and April 2020 was significant, but when the lockdown measures were raised the concentrations of atmospheric pollutants quickly recovered to pre-pandemic levels and therefore any possible climatic feedbacks were negligible; (2) no robust relationship between atmospheric parameters and the spread of COVID-19 cases can be justified in the warmer part of the year and (3) more research needs to be done regarding the possible links between climate change and the release of new pathogens from thawing of permafrost areas.

SARS-CoV-2 viability under different meteorological conditions, surfaces, fluids and transmission between animals

Since the COVID-19 outbreak, researchers have tried to characterise the novel coronavirus SARS-CoV-2 to better understand the pathogenic mechanisms of the virus and prevent further dissemination. As a consequence, there has been a bloom in scientific research papers focused on the behaviour of the virus in different environmental contexts. Nevertheless, despite these efforts and due to its novelty, available information about this coronavirus is limited, as several research studies are still ongoing. This review aims to shed light on this issue. To that end, we have examined the scientific literature to date regarding the viability of SARS-CoV-2 on surfaces and fluids or under different environmental conditions (temperature, precipitation and UV radiation). We have also addressed the role of animals in the transmission of this coronavirus.

Physical distancing and risk of COVID-19 in small-scale fisheries: a remote sensing assessment in coastal Ghana

The novel coronavirus is predicted to have dire implications on global food systems including fisheries value chains due to restrictions imposed on human movements in many countries. In Ghana, food production, both agriculture and fisheries, is exempted from restrictions as an essential service. The enforcement of COVID-19 prevention protocols, particularly social distancing, has been widely reported in Ghana's agricultural markets whereas casual observations and media reports on fish landing sites suggest no such enforcements are in place. This study aimed to provide sound scientific evidence as a basis for informed policy direction and intervention for the artisanal fishing sector in these challenging times. We employed an unmanned aerial vehicle in assessing the risk of artisanal fishers to the pandemic using physical distancing as a proxy. From analysis of cumulative distribution function (G-function) of the nearest-neighbour distances, this study underscored crowding at all surveyed fish landing beaches, and identified potential "hotspots" for disease transmission. Aerial measurements taken at times of peak landing beach activity indicated that the highest proportion of people, representing 56%, 48%, 39% and 78% in Elmina, Winneba, Apam and Mumford respectively, were located at distances of less than one metre from their nearest neighbour. Risk of crowding was independent of the population at the landing beaches, suggesting that all categories of fish landing sites along the coast would require equal urgency and measured attention towards preventing and mitigating the spread of the disease.

Physical distancing and risk of COVID-19 in small-scale fisheries: a remote sensing assessment in coastal Ghana

The novel coronavirus is predicted to have dire implications on global food systems including fisheries value chains due to restrictions imposed on human movements in many countries. In Ghana, food production, both agriculture and fisheries, is exempted from restrictions as an essential service. The enforcement of COVID-19 prevention protocols, particularly social distancing, has been widely reported in Ghana’s agricultural markets whereas casual observations and media reports on fish landing sites suggest no such enforcements are in place. This study aimed to provide sound scientific evidence as a basis for informed policy direction and intervention for the artisanal fishing sector in these challenging times. We employed an unmanned aerial vehicle in assessing the risk of artisanal fishers to the pandemic using physical distancing as a proxy. From analysis of cumulative distribution function (G-function) of the nearest-neighbour distances, this study underscored crowding at all surveyed fish landing beaches, and identified potential “hotspots” for disease transmission. Aerial measurements taken at times of peak landing beach activity indicated that the highest proportion of people, representing 56%, 48%, 39% and 78% in Elmina, Winneba, Apam and Mumford respectively, were located at distances of less than one metre from their nearest neighbour. Risk of crowding was independent of the population at the landing beaches, suggesting that all categories of fish landing sites along the coast would require equal urgency and measured attention towards preventing and mitigating the spread of the disease.

The COVID-19 pandemic: Impacts on cities and major lessons for urban planning, design, and management

Since the early days of the COVID-19 crisis the scientific community has constantly been striving to shed light on various issues such as the mechanisms driving the spread of the virus, its environmental and socio-economic impacts, and necessary recovery and adaptation plans and policies. Given the high concentration of population and economic activities in cities, they are often hotspots of COVID-19 infections. Accordingly, many researchers are struggling to explore the dynamics of the pandemic in urban areas to understand impacts of COVID-19 on cities. In this study we seek to provide an overview of COVID-19 research related to cities by reviewing literature published during the first eight months after the first confirmed cases were reported in Wuhan, China. The main aims are to understand impacts of the pandemic on cities and to highlight major lessons that can be learned for post-COVID urban planning and design. Results show that, in terms of thematic focus, early research on the impacts of COVID-19 on cities is mainly related to four major themes, namely, (1) environmental quality, (2) socio-economic impacts, (3) management and governance, and (4) transportation and urban design. While this indicates a diverse research agenda, the first theme that covers issues related to air quality, meteorological parameters, and water quality is dominant, and the others are still relatively underexplored. Improvements in air and water quality in cities during lockdown periods highlight the significant environmental impacts of anthropogenic activities and provide a wake-up call to adopt environmentally friendly development pathways. The paper also provides other recommendations related to the socio-economic factors, urban management and governance, and transportation and urban design that can be used for post-COVID urban planning and design. Overall, existing knowledge shows that the COVID-19 crisis entails an excellent opportunity for planners and policy makers to take transformative actions towards creating cities that are more just, resilient, and sustainable.

Potential sources, modes of transmission and effectiveness of prevention measures against SARS-CoV-2

During the current SARS-CoV-2 pandemic new studies are emerging daily providing novel information about sources, transmission risks and possible prevention measures. In this review, we aimed to comprehensively summarize the current evidence on possible sources for SARS-CoV-2, including evaluation of transmission risks and effectiveness of applied prevention measures. Next to symptomatic patients, asymptomatic or pre-symptomatic carriers are a possible source with respiratory secretions as the most likely cause for viral transmission. Air and inanimate surfaces may be sources; however, viral RNA has been inconsistently detected. Similarly, even though SARS-CoV-2 RNA has been detected on or in personal protective equipment (PPE), blood, urine, eyes, the gastrointestinal tract and pets, these sources are currently thought to play a negligible role for transmission. Finally, various prevention measures such as handwashing, hand disinfection, face masks, gloves, surface disinfection or physical distancing for the healthcare setting and in public are analysed for their expected protective effect.

What could explain the late emergence of COVID-19 in Africa?

At the end of November 2019, a novel coronavirus responsible for respiratory tract infections emerged in China. Despite drastic containment measures, this virus, known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), spread in Asia and Europe. The pandemic is ongoing with a particular hotspot in southern Europe and America in spring 2020. Many studies predicted an epidemic in Africa similar to that currently seen in Europe and the USA. However, reported data do not confirm these predictions. Several hypotheses that could explain the later emergence and spread of the coronavirus disease 2019 (COVID-19) pandemic in African countries are being discussed, including the lack of health-care infrastructure capable of clinically detecting and confirming COVID-19 cases, the implementation of social distancing and hygiene, international air traffic flows, the climate, the relatively young and rural population, the genetic polymorphism of the angiotensin-converting enzyme 2 receptor, cross-immunity and the use of antimalarial drugs.

Global impact of environmental temperature and BCG vaccination coverage on the transmissibility and fatality rate of COVID-19

The 2019-Coronavirus (COVID-19) pandemic has had a global impact. The effect of environmental temperature on transmissibility and fatality rate of COVID-19 and protective efficacy of Bacillus Calmette-Guérin (BCG) vaccination towards COVID-19 remains ambiguous. Therefore, we explored the global impact of environmental temperature and neonatal BCG vaccination coverage on transmissibility and fatality rate of COVID-19. The COVID-19 data for reported cases, deaths and global temperature were collected from 31^st December 2020 to 3^rd April 2020 for 67 countries. Temperature data were split into quartiles for all three categories (minimum temperature, maximum temperature and mean temperature). The impact of three types of temperature data and policy of BCG vaccination on COVID-19 infection was determined by applying the multivariable two-level negative binomial regression analysis keeping daily new cases and daily mortality as outcome. The highest number of cases fell in the temperature categories as following: mean temperature in the second quartile (6°C to 10.5°C), median 26, interquartile range (IQR) 237; minimum temperature in the first quartile (-26°C to 1°C), median 23, IQR 173; maximum temperature in the second quartile (10°C to 16°C), median 27.5, IQR 219. For the minimum temperature category, 28% statistically significant lower incidence was noted for new cases from the countries falling in the second quartile (2°C to 6°C) compared with countries falling in the first quartile (-26°C to 1°C) (incidence rate ratio [IRR] 0.72, 95% confidence interval [CI] 0.57 to 0.93). However, no statistically significant difference in incidence rate was observed for mean temperature categories in comparison to the first quartile. Countries with BCG vaccination policy had 58% less mortality as compared with countries without BCG coverage (IRR 0.42; 95% CI 0.18 to 0.95). Our exploratory study provides evidence that high temperature might not be associated with low transmissibility and countries having neonatal BCG vaccination policy had a low fatality rate of COVID-19.

Impact of meteorological conditions and air pollution on COVID-19 pandemic transmission in Italy

Italy was the first, among all the European countries, to be strongly hit by the COVID-19 pandemic outbreak caused by the severe acute respiratory syndrome coronavirus 2 (Sars-CoV-2). The virus, proven to be very contagious, infected more than 9 million people worldwide (in June 2020). Nevertheless, it is not clear the role of air pollution and meteorological conditions on virus transmission. In this study, we quantitatively assessed how the meteorological and air quality parameters are correlated to the COVID-19 transmission in two large metropolitan areas in Northern Italy as Milan and Florence and in the autonomous province of Trento. Milan, capital of Lombardy region, it is considered the epicenter of the virus outbreak in Italy. Our main findings highlight that temperature and humidity related variables are negatively correlated to the virus transmission, whereas air pollution (PM2.5) shows a positive correlation (at lesser degree). In other words, COVID-19 pandemic transmission prefers dry and cool environmental conditions, as well as polluted air. For those reasons, the virus might easier spread in unfiltered air-conditioned indoor environments. Those results will be supporting decision makers to contain new possible outbreaks.

Environmental concern regarding the effect of humidity and temperature on 2019-nCoV survival: fact or fiction

The new coronavirus, called 2019-nCoV, is a new type of virus that was first identified in Wuhan, China, in December 2019. Environmental conditions necessary for survival and spread of 2019-nCoV are somewhat transparent but unlike animal coronaviruses. We are poorly aware of their survival in environment and precise factors of their transmission. Countries located in east and west of globe did not have a significant impact on prevalence of disease among communities, and on the other hand, north and south have provided a model for relative prediction of disease outbreaks. The 2019-nCoV can survive for up to 9 days at 25 °C, and if this temperature rises to 30 °C, its lifespan will be shorter. The 2019-nCoV is sensitive to humidity, and lifespan of viruses in 50% humidity is longer than that of 30%. Also, temperature and humidity are important factors influencing the COVID-19 mortality rate and may facilitate 2019-nCoV transmission. Thus, considering the available and recent evidence, it seems that low temperatures, as well as dry and unventilated air, may affect stability and transmissibility of 2019-nCoV.

Antimalarial artemisinin-based combination therapies (ACT) and COVID-19 in Africa: In vitro inhibition of SARS-CoV-2 replication by mefloquine-artesunate

OBJECTIVES

At the end of November 2019, a novel coronavirus responsible for respiratory tract infections (COVID-19) emerged in China. Despite drastic containment measures, this virus, known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), spread in Asia and Europe. The pandemic is ongoing with a particular hotspot in Southern Europe and America; many studies predicted a similar epidemic in Africa, as is currently seen in Europe and the United States of America. However, reported data have not confirmed these predictions. One of the hypotheses that could explain the later emergence and spread of COVID-19 pandemic in African countries is the use of antimalarial drugs to treat malaria, and specifically, artemisinin-based combination therapy (ACT).

METHODS

The antiviral activity of fixed concentrations of ACT at concentrations consistent with those observed in human plasma when ACT is administered at oral doses for uncomplicated malaria treatment was evaluatedin vitro against a clinically isolated SARS-CoV-2 strain (IHUMI-3) in Vero E6 cells.

RESULTS

Mefloquine-artesunate exerted the highest antiviral activity with % inhibition of 72.1 ± 18.3 % at expected maximum blood concentration (Cmax) for each ACT drug at doses commonly administered in malaria treatment. All the other combinations, artesunate-amodiaquine, artemether-lumefantrine, artesunate-pyronaridine, or dihydroartemisinin-piperaquine, showed antiviral inhibition in the same ranges (27.1 to 34.1 %).

CONCLUSIONS

Antimalarial drugs for which concentration data in the lungs are available are concentrated from 10 to 160 fold more in the lungs than in blood. Thesein vitro results reinforce the hypothesis that antimalarial drugs could be effective as an anti-COVID-19 treatment.

May SARS-CoV-2 Diffusion Be Favored by Alkaline Aerosols and Ammonia Emissions?

Ammonia is a common factor linking air in bat caves and air pollution in the proximity of agricultural fields treated with livestock farming sewage and slaughterhouses, where important clusters of COVID-19 have recently been reported all over the world. Such a commonality has a further connection with the known behavior of some viruses of the coronavirus family, such as the murine hepatitis virus, whose spike glycoprotein (S) can be triggered to a membrane-binding conformation at pH 8.0. Within the airborne route of virus transmission, with particular relevance for crowded and enclosed environments, these observations have prompted a hypothesis that may represent a contributing cause to interpret the geographical variability of the virus diffusion and the surging rise of COVID-19 cases in slaughterhouses all over the world. The hypothesis is that, in these environments, the SARS-CoV-2 S protein may find on a fraction of the airborne particles an alkaline pH, favorable to trigger the conformational changes, needed to induce the fusion of the viral envelope with the plasma membrane of the target cells.

Prevention and Control Strategies for Coronavirus Disease-2019 in a Tertiary Hospital in the Middle East of China

BACKGROUND

Coronavirus disease-2019 (COVID-19) is a new infectious disease. The COVID-19 outbreak has quickly spread globally and now is having remarkable effects on public health and national economies.

PURPOSE

Effective measures for prevention and control of nosocomial infection are urgently needed to control COVID-19 infection among medical staff.

METHODS

Herein, we described COVID-19 prevention and control strategies that have been implemented in a tertiary hospital in the middle east of China. Hospital layout was adjusted to prevent and control transmission. Other procedures were then implemented to prevent the spread of the virus, including specialized training and evaluation of medical staff, pre-testing and triage, measures to promote early identification of patients, environmental cleaning and disinfection, new medical waste processing procedures, new patient management procedures, timely disinfection of potential sources of nosocomial infection, and strict protective measures.

RESULTS

Since the new measures were implemented, to date there have only been three new confirmed cases of COVID-19 infection, no cases of medical staff infection, and no COVID-19-related deaths at the hospital.

CONCLUSION

The current report provides a protocol that could be implemented in medical departments in similar cities worldwide.

Players' physical performance in LaLiga across the season: insights for competition continuation after COVID-19

Due to the COVID-19 outbreak, professional football players competing in LaLiga were confined at home for ~8 weeks and then they were allowed to train to prepare the first competitive match for 4 weeks. As the duration of summer break in the prior four seasons of LaLiga (from 2015-2016 to 2018-2019) was of similar length to the suspension of the championship due to COVID-19 (~12 weeks), we have analysed the running performance of teams competing in LaLiga in these four seasons to anticipate players’ physical performance after the resumption of the competition. The analysis includes the average running distance per game for each of the 38 matchdays that compose LaLiga. One-way ANOVA revealed that there was a main effect of the matchday on total running distance per match (p = 0.001), and in the distance covered between 14.0 and 20.9 km/h (p < 0.001), between 21.0 and 23.9 km/h (p < 0.001) and at above 24.0 km/h (p < 0.001). Overall, the post-hoc analysis revealed that the running patterns progressively increased during the first 8-10 matchdays and then reached a plateau which was significantly different to matchday-1 (p < 0.05). This analysis reveals that, in the prior four competitive seasons of LaLiga, players’ physical performance was lower at the beginning of the season and the teams needed approximately 8-10 matchdays to reach a steady state running performance. These data suggest that football players will progressively increase their performance across the 11 matchdays remaining to complete LaLiga.

Correlation between COVID-19 Morbidity and Mortality Rates in Japan and Local Population Density, Temperature, and Absolute Humidity

This study analyzed the morbidity and mortality rates of the coronavirus disease (COVID-19) pandemic in different prefectures of Japan. Under the constraint that daily maximum confirmed deaths and daily maximum cases should exceed 4 and 10, respectively, 14 prefectures were included, and cofactors affecting the morbidity and mortality rates were evaluated. In particular, the number of confirmed deaths was assessed, excluding cases of nosocomial infections and nursing home patients. The correlations between the morbidity and mortality rates and population density were statistically significant (p-value < 0.05). In addition, the percentage of elderly population was also found to be non-negligible. Among weather parameters, the maximum temperature and absolute humidity averaged over the duration were found to be in modest correlation with the morbidity and mortality rates. Lower morbidity and mortality rates were observed for higher temperature and absolute humidity. Multivariate linear regression considering these factors showed that the adjusted determination coefficient for the confirmed cases was 0.693 in terms of population density, elderly percentage, and maximum absolute humidity (p-value < 0.01). These findings could be useful for intervention planning during future pandemics, including a potential second COVID-19 outbreak.

Influence of Absolute Humidity, Temperature and Population Density on COVID-19 Spread and Decay Durations: Multi-Prefecture Study in Japan

This study analyzed the spread and decay durations of the COVID-19 pandemic in different prefectures of Japan. During the pandemic, affordable healthcare was widely available in Japan and the medical system did not suffer a collapse, making accurate comparisons between prefectures possible. For the 16 prefectures included in this study that had daily maximum confirmed cases exceeding ten, the number of daily confirmed cases follow bell-shape or log-normal distribution in most prefectures. A good correlation was observed between the spread and decay durations. However, some exceptions were observed in areas where travelers returned from foreign countries, which were defined as the origins of infection clusters. Excluding these prefectures, the population density was shown to be a major factor, affecting the spread and decay patterns, with R² = 0.39 (p < 0.05) and 0.42 (p < 0.05), respectively, approximately corresponding to social distancing. The maximum absolute humidity was found to affect the decay duration normalized by the population density (R² > 0.36, p < 0.05). Our findings indicate that the estimated pandemic spread duration, based on the multivariate analysis of maximum absolute humidity, ambient temperature, and population density (adjusted R² = 0.53, p-value < 0.05), could prove useful for intervention planning during potential future pandemics, including a second COVID-19 outbreak.

Lower Incidence of COVID-19 at High Altitude: Facts and Confounders

Pun, Matiram, Rachel Turner, Giacomo Strapazzon, Hermann Brugger, and Erik R. Swenson. Lower incidence of COVID-19 at high altitude: Facts and confounders. High Alt Med Biol. 21:217-222, 2020.-The rapid transmission, increased morbidity, and mortality of coronavirus disease 2019 (COVID-19) has exhausted many health care systems and the global economy. Large variations in COVID-19 prevalence and incidence have been reported across and within many countries worldwide; however, this remains poorly understood. The variability and susceptibility across the world have been mainly attributed to differing socioeconomic status, burden of chronic diseases, access to health care, strength of health care systems, and early or late adoption of control measures. Environmental factors such as pollution, ambient temperature, humidity, and seasonal weather patterns at different latitudes may influence how severe the pandemic is and the incidence of infection in any part of the world. In addition, recent epidemiological data have been used to propose that altitude of residence may not only influence those environmental features considered key to lesser viral transmission, but also susceptibility to more severe forms of COVID-19 through hypoxic-hypobaria driven genomic or nongenomic adaptations specific to high-altitude populations. In this review, we critically examine these factors and attempt to determine based upon available scientific and epidemiological data whether living in high-altitude regions might be protective against COVID-19 as recent publications have claimed.

Epidemiological Peculiarities of New Coronavirus Infection (COVID-2019). Communication 2: Peculiarities of epidemic process development in conjunction with performed anti-epidemic measures around the world and in the Russian Federation

The review presents the analysis of the data on the spread of COVID-19 around the world and in Russia available as of June 15, 2020. Dynamics and geographical dissemination of COVID-19 in the Russian Federation is considered. The structure of incidence by gender and age is presented. Assessment of the key epidemiological parameters (morbidity rates and lethality) is provided. The effectiveness of the response measures conducted to control COVID-19 is discussed.

COVID-19 from mysterious enemy to an environmental detection process: a critical review

The recent global emergence of an unusual viral pneumonia of COVID-19 epidemic was firstly started in Wuhan city, Hubei province in China in December 2019. Regrettably, it is still sweeping the planet, and it cannot be controlled up till now. By May 2020, the unexpected spread of this disaster had caused more than 3,759,967 cases and 259,474 deaths in 114 countries from Asia to the Middle East, Europe, and the USA. Considering its fatal nature, it has evolved as a major challenge for the world. This is necessitating a quick and steep intervention in order to save millions of people’s lives across the globe. The knowledge about the nature and evolution of the COVID-19 virus in water, soils, and other environmental compartments can be addressed through wastewater and sewage. Wastewater-based epidemiology approach can be used as an early indicator of the infection within a specific population. The basic aim of this review article is trying to provide a prompt, and valuable reference guides about COVID-19. Some important questions were addressed, such as, its origin, transmission, clinical symptoms, diagnosis, environmental aspects, and the possible indoors and outdoors airborne transmission minimization strategies that may benefit specialists.