The impact of ethnic segregation on neighbourhood-level social distancing in the United States amid the early outbreak of COVID-19.

The COVID-19 pandemic has been argued to be the 'great equaliser', but, in fact, ethnically and racially segregated communities are bearing a disproportionate burden from the disease. Although more people have been infected and died from the disease among these minority communities, still fewer people in these communities are complying with the suggested public health measures like social distancing. The factors contributing to these ramifications remain a long-lasting debate, in part due to the contested theories between ethnic stratification and ethnic community. To offer empirical evidence to this theoretical debate, we tracked public social-distancing behaviours from mobile phone devices across urban census tracts in the United States and employed a difference-in-difference model to examine the impact of racial/ethnic segregation on these behaviours. Specifically, we focussed on non-Hispanic Black and Hispanic communities at the neighbourhood level from three principal dimensions of ethnic segregation, namely, evenness, exposure, and concentration. Our results suggest that (1) the high ethnic diversity index can decrease social-distancing behaviours and (2) the high dissimilarity between ethnic minorities and non-Hispanic Whites can increase social-distancing behavior; (3) the high interaction index can decrease social-distancing behaviours; and (4) the high concentration of ethnic minorities can increase travel distance and non-home time but decrease work behaviours. The findings of this study shed new light on public health behaviours among minority communities and offer empirical knowledge for policymakers to better inform just and evidence-based public health orders.

Decline of onset-to-diagnosis interval and its impacts on clinical outcome of COVID-19 in China: a nation-wide observational study.

BACKGROUND: To quantitatively assess the impact of the onset-to-diagnosis interval (ODI) on severity and death for coronavirus disease 2019 (COVID-19) patients. METHODS: This retrospective study was conducted based on the data on COVID-19 cases of China over the age of 40 years reported through China's National Notifiable Infectious Disease Surveillance System from February 5, 2020 to October 8, 2020. The impacts of ODI on severe rate (SR) and case fatality rate (CFR) were evaluated at individual and population levels, which was further disaggregated by sex, age and geographic origin. RESULTS: As the rapid decline of ODI from around 40 days in early January to < 3 days in early March, both CFR and SR of COVID-19 largely dropped below 5% in China. After adjusting for age, sex, and region, an effect of ODI on SR was observed with the highest OR of 2.95 (95% CI 2.37‒3.66) at Day 10-11 and attributable fraction (AF) of 29.1% (95% CI 22.2‒36.1%) at Day 8-9. However, little effect of ODI on CFR was observed. Moreover, discrepancy of effect magnitude was found, showing a greater effect from ODI on SR among patients of male sex, younger age, and those cases in Wuhan. CONCLUSION: The ODI was significantly associated with the severity of COVID-19, highlighting the importance of timely diagnosis, especially for patients who were confirmed to gain increased benefit from early diagnosis to some extent.

Consistency of the relationship between air pollution and the urban form: Evidence from the COVID-19 natural experiment.

The lockdown measures enacted to control the COVID-19 pandemic in Wuhan, China, resulted in a suspension of nearly all non-essential human activities on January 23, 2020. Nevertheless, the lockdown provided a natural experiment to understand the consistency of the relationship between the urban form and air pollution with different compositions of locally or regionally transported sources. This study investigated the variations in six air pollutants (PM2.5, PM10, NO2, CO, O3, and SO2) in Wuhan before and during the lockdown and in the two same time spans in 2021. Moreover, a hierarchical agglomerative cluster analysis was conducted to differentiate the relative levels of pollutants and to detect the relationships between the air pollutants and the urban form during these four periods. Several features depicting the urban physical structures delivered consistent impacts. A lower building density and plot ratio, and a higher porosity always mitigated the concentrations of NO2 and PM2.5. However, they had inverse effects on O3 during the non-lockdown periods. PM10, CO, and SO2 concentrations have little correlation with the urban form. This study improves the comprehensive understanding of the effect of the urban form on ambient air pollution and suggests practical strategies for mitigating air pollution in Wuhan.

Sustainable development goals under threat? Multidimensional impact of COVID-19 on our planet and society outweigh short term global pollution reduction.

The Sustainable Development Goals (SDGs) call on all nations to accomplish 17 broad global development goals by 2030. However, the COVID-19 pandemic presents a challenging period in human history, causing large-scale impacts on society and the environment as governments shift priorities and divert funding in response to this pandemic. Through a literature survey and data acquirement from various international organizations (e.g. United Nations and European Space Agency), this manuscript is intended to provide critical insights into the impacts of the COVID-19 pandemic on the SDGs. We briefly describe this pandemic's positive and short-term effects on the environment, followed by a critical evaluation of its potential long-term impacts on the environment, society, and the SDGs. On the basis of COVID-19 effects, the SDGs are classified into three categories: directly-affected SDGs, indirectly-affected SDGs, and a stand-alone category. The COVID-19-induced lockdowns and restrictions resulted in a short-term decline in environmental pollution and greenhouse gases (GHG) emissions, providing valuable data for climate advocates and researchers. These positive impacts were essentially temporary due to the synchronized global response to the pandemic. The halted focus on the progress of the SDGs greatly impacts the global green transition to a healthy and sustainable world. COVID-19 threatens to impede the progress toward a prosperous, environment-friendly, and sustainable global development in multiple ways. These multi-dimensional threats have been critically evaluated, along with a description of potential solutions to curtail the adverse effects of COVID-19 on the SDGs. Considering the limited data regarding the impacts of the pandemic on the SDGs, diverse collaborative studies at the regional and global levels are recommended.

The Effect of the COVID-19 Vaccine on Daily Cases and Deaths Based on Global Vaccine Data.

BACKGROUND: Coronavirus disease 2019 (COVID-19), a global pandemic, has caused over 216 million cases and 4.50 million deaths as of 30 August 2021. Vaccines can be regarded as one of the most powerful weapons to eliminate the pandemic, but the impact of vaccines on daily COVID-19 cases and deaths by country is unclear. This study aimed to investigate the correlation between vaccines and daily newly confirmed cases and deaths of COVID-19 in each country worldwide. METHODS: Daily data on firstly vaccinated people, fully vaccinated people, new cases and new deaths of COVID-19 were collected from 187 countries. First, we used a generalized additive model (GAM) to analyze the association between daily vaccinated people and daily new cases and deaths of COVID-19. Second, a random effects meta-analysis was conducted to calculate the global pooled results. RESULTS: In total, 187 countries and regions were included in the study. During the study period, 1,011,918,763 doses of vaccine were administered, 540,623,907 people received at least one dose of vaccine, and 230,501,824 people received two doses. For the relationship between vaccination and daily increasing cases of COVID-19, the results showed that daily increasing cases of COVID-19 would be reduced by 24.43% [95% CI: 18.89, 29.59] and 7.50% [95% CI: 6.18, 8.80] with 10,000 fully vaccinated people per day and at least one dose of vaccine, respectively. Daily increasing deaths of COVID-19 would be reduced by 13.32% [95% CI: 3.81, 21.89] and 2.02% [95% CI: 0.18, 4.16] with 10,000 fully vaccinated people per day and at least one dose of vaccine, respectively. CONCLUSIONS: These findings showed that vaccination can effectively reduce the new cases and deaths of COVID-19, but vaccines are not distributed fairly worldwide. There is an urgent need to accelerate the speed of vaccination and promote its fair distribution across countries.

Association between temperature and COVID-19 transmission in 153 countries.

The WHO characterized coronavirus disease 2019 (COVID-19) as a global pandemic. The influence of temperature on COVID-19 remains unclear. The objective of this study was to investigate the correlation between temperature and daily newly confirmed COVID-19 cases by different climate regions and temperature levels worldwide. Daily data on average temperature (AT), maximum temperature (MAXT), minimum temperature (MINT), and new COVID-19 cases were collected from 153 countries and 31 provinces of mainland China. We used the spline function method to preliminarily explore the relationship between R0 and temperature. The generalized additive model (GAM) was used to analyze the association between temperature and daily new cases of COVID-19, and a random effects meta-analysis was conducted to calculate the pooled results in different regions in the second stage. Our findings revealed that temperature was positively related to daily new cases at low temperature but negatively related to daily new cases at high temperature. When the temperature was below the smoothing plot peak, in the temperate zone or at a low temperature level (e.g., <25th percentiles), the RRs were 1.09 (95% CI: 1.04, 1.15), 1.10 (95% CI: 1.05, 1.15), and 1.14 (95% CI: 1.06, 1.23) associated with a 1°C increase in AT, respectively. Whereas temperature was above the smoothing plot peak, in a tropical zone or at a high temperature level (e.g., >75th percentiles), the RRs were 0.79 (95% CI: 0.68, 0.93), 0.60 (95% CI: 0.43, 0.83), and 0.48 (95% CI: 0.28, 0.81) associated with a 1°C increase in AT, respectively. The results were confirmed to be similar regarding MINT, MAXT, and sensitivity analysis. These findings provide preliminary evidence for the prevention and control of COVID-19 in different regions and temperature levels.

Etiological and epidemiological features of acute respiratory infections in China.

Nationwide prospective surveillance of all-age patients with acute respiratory infections was conducted in China between 2009‒2019. Here we report the etiological and epidemiological features of the 231,107 eligible patients enrolled in this analysis. Children <5 years old and school-age children have the highest viral positivity rate (46.9%) and bacterial positivity rate (30.9%). Influenza virus, respiratory syncytial virus and human rhinovirus are the three leading viral pathogens with proportions of 28.5%, 16.8% and 16.7%, and Streptococcus pneumoniae, Mycoplasma pneumoniae and Klebsiella pneumoniae are the three leading bacterial pathogens (29.9%, 18.6% and 15.8%). Negative interactions between viruses and positive interactions between viral and bacterial pathogens are common. A Join-Point analysis reveals the age-specific positivity rate and how this varied for individual pathogens. These data indicate that differential priorities for diagnosis, prevention and control should be highlighted in terms of acute respiratory tract infection patients' demography, geographic locations and season of illness in China.

Self-Perpetuating Carbon Foam Microwave Plasma Conversion of Hydrocarbon Wastes into Useful Fuels and Chemicals.

White wastes (unseparated plastics, face masks, textiles, etc.) pose a serious challenge to sustainable human development and the ecosystem and have recently been exacerbated due to the surge in plastic usage and medical wastes from COVID-19. Current recycling methods such as chemical recycling, mechanical recycling, and incineration require either pre-sorting and washing or releasing CO2. In this work, a carbon foam microwave plasma process is developed, utilizing plasma discharge to generate surface temperatures exceeding ∼3000 K in a N2 atmosphere, to convert unsorted white wastes into gases (H2, CO, C2H4, C3H6, CH4, etc.) and small amounts of inorganic minerals and solid carbon, which can be buried as artificial "coal". This process is self-perpetuating, as the new solid carbon asperities grafted onto the foam's surface actually increase the plasma discharge efficiency over time. This process has been characterized by in situ optical probes and infrared sensors and optimized to handle most of the forms of white waste without the need for pre-sorting or washing. Thermal measurement and modeling show that in a flowing reactor, the device can achieve locally extremely high temperatures, but the container wall will still be cold and can be made with cheap materials, and thus, a miniaturized waste incinerator is possible that also takes advantage of intermittent renewable electricity.

The spatial clustering analysis of COVID-19 and its associated factors in mainland China at the prefecture level

Coronavirus disease 2019 (COVID-19) has become a worldwide public health threat. Many associated factors including population movement, meteorological parameters, air quality and socioeconomic conditions can affect COVID-19 transmission. However, no study has combined these various factors in a comprehensive analysis. We collected data on COVID-19 cases and the factors of interest in 340 prefectures of mainland China from 1 December 2019 to 30 April 2020. Moran's I statistic, Getis-Ord Gi⁎ statistic and Kulldorff's space-time scan statistics were used to identify spatial clusters of COVID-19, and the geographically weighted regression (GWR) model was applied to investigate the effects of the associated factors on COVID-19 incidence. A total of 67,449 laboratory-confirmed cases were reported during the study period. Wuhan city as well as its surrounding areas were the cluster areas, and January 25 to February 21, 2020, was the clustering time of COVID-19. The population outflow from Wuhan played a significant role in COVID-19 transmission, with the local coefficients varying from 14.87 to 15.02 in the 340 prefectures. Among the meteorological parameters, relative humidity and precipitation were positively associated with COVID-19 incidence, while the average wind speed showed a negative correlation, but the relationship of average temperature with COVID-19 incidence inconsistent between northern and southern China. NO2 was positively associated, and O3 was negatively associated, with COVID-19 incidence. Environment with high levels of inbound migration or travel, poor ventilation, high humidity or heavy rainfall, low temperature, and high air pollution may be favorable for the growth, reproduction and spread of SARS-CoV-2. Therefore, applying appropriate lockdown measures and travel restrictions, strengthening the ventilation of living and working environments, controlling air pollution and making sufficient preparations for a possible second wave in the relatively cold autumn and winter months may be helpful for the control and prevention of COVID-19.

Fast automated detection of COVID-19 from medical images using convolutional neural networks.

Coronavirus disease 2019 (COVID-19) is a global pandemic posing significant health risks. The diagnostic test sensitivity of COVID-19 is limited due to irregularities in specimen handling. We propose a deep learning framework that identifies COVID-19 from medical images as an auxiliary testing method to improve diagnostic sensitivity. We use pseudo-coloring methods and a platform for annotating X-ray and computed tomography images to train the convolutional neural network, which achieves a performance similar to that of experts and provides high scores for multiple statistical indices (F1 scores > 96.72% (0.9307, 0.9890) and specificity >99.33% (0.9792, 1.0000)). Heatmaps are used to visualize the salient features extracted by the neural network. The neural network-based regression provides strong correlations between the lesion areas in the images and five clinical indicators, resulting in high accuracy of the classification framework. The proposed method represents a potential computer-aided diagnosis method for COVID-19 in clinical practice.

Social distancing and inequality in the United States amid COVID-19 outbreak

Amid sweeping efforts to get Americans to stay at home to slow the spread of the coronavirus disease, we geovisualized how foot traffic has increased or declined in relation to six types of trips across the United States: homes, workplaces, retail and recreation establishments, parks, grocery stores and pharmacies, and transit stations. The geovisualization shows that most West and East Coast cities have reduced extensive movements while many Middle American cities even increased their movements, such as trips to grocery stores and parks. We further found that the poorest communities reduced fewer movements than the wealthiest communities, except for the trips to parks.

Risk factors for prolonged viral clearance in adult patients with COVID-19 in Beijing, China: A prospective observational study.

Clearance of COVID-19 from the human body has not been established. Our study collected the laboratory test results from patients and analyzed the correlation between early changes in serum indices and the virus clearance by univariable and multivariable COX regression models, with an aim to explore the risk factors for prolonged viral clearance. The study included 61 patients with COVID-19 treated at the Fifth Medical Center of PLA General Hospital in Beijing from 20 January 2020 to 20 February 2020. We set the total observation of the disease course to 20 days and the patients were divided into two groups (prolonged group, > 20d vs. normal group, ≤ 20d). The 48 patients with COVID-19 included in this study, 13 remained positive for viral nucleic acid monitoring 20 days after onset. The median for virus clearance was 16 days (range, 6-35 days). The results showed that hypertension, a lactate dehydrogenase level > 211.5 U/L, an interleukin 6 (IL-6) level > 12.5 pg/ml, and a NK lymphocyte percentage > 0.5% were associated with prolonged viral clearance. Therefore, we showed that a history of hypertension, an elevated IL-6 level, and an elevated percentage of NK cells were risk factors for prolonged viral clearance.