Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

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

Spatial analysis and GIS in the study of COVID-19. A review.

Temperature significantly changes COVID-19 transmission in (sub)tropical cities of Brazil.

A spatio-temporal analysis for exploring the effect of temperature on COVID-19 early evolution in Spain.

https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1293&context=sph_pubs

Impact of meteorological factors on the COVID-19 transmission: A multi-city study in China.

Objective Coronavirus disease 2019 (COVID-19) is a serious infectious disease, which has caused great number of deaths and health problems worldwide. This study aims to examine the effects of airborne particulate matter (PM) pollution on COVID-19 across China. Methods In this study, we obtained confirmed cases of COVID-19, the data of airborne ambient PM with aerodynamic diameter ≤ 2.5 μm (PM2.5) and ≤ 10 μm (PM10), ambient temperature (AT), absolute humidity (AH) and migration scale index (MSI) in 72 cities of China (excluded Wuhan city) on a daily basis, each of which confirmed more than 50 cases from January 20th to March 2nd, 2020. We applied a two-stage analysis. Generalized additive models with quasi-Poisson distribution was first fitted to estimate city-specific effects of PM10 and PM2.5 on daily confirmed COVID-19 cases while controlling AT, AH and MSI. Then, we used meta-analysis to generate the pooled effect estimates from city-specific results. Results During the study period, there were a total of 24 939 COVID-19 cases, most of which were reported in Hubei Province. In our meta-analysis, we found each 10 μg/m3 increase in concentration of PM2.5 and PM10 in single day lag (from lag 0 to lag 7 and lag 14) were positively associated with confirmed cases of COVID-19, not including PM10 at lag 5, lag 6 and lag 7, and PM2.5 at lag 5, lag 6. Similar trend was also found in different cumulative lag days (from lag 01 to lag 07 and lag 014). The effects of PM2.5 and PM10 on daily COVID-19 confirmed cases are statistically significant for three cumulative lag periods over 3, 7 and 14 days with the greatest effect over 14 days. The estimated RRs of which were 1.64 (95% CIs: 1.47, 1.82) and 1.47 (95% CIs: 1.34, 1.61) with each 10 μg/m3 increase in concentrations of PM2.5 and PM10, respectively. In addition, we found that the effects of PM2.5 on daily confirmed cases were greater than PM10 in all included lag days. Conclusions This nationwide study suggests that airborne PM pollution likely increases the risk of getting COVID-19 in China.

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An effect assessment of Airborne particulate matter pollution on COVID-19: A multi-city Study in China


 
 Novel coronavirus disease (SARS COV-2 infection or COVID-19) is a respiratory tract infection which has been linked with severe acute respiratory syndrome transmitted particularly through touching and respiration. The purpose of this study is to understand the epidemiological characteristics of the COVID-19 cases in a typical tourist-related outbreak and explore the possible route for its transmission.
 
 
 
 All data and epidemiological survey reports of COVID-19 cases in the outbreak were reported by provincial and urban (county) Centers for Disease Control and Prevention and Health Commissions nationwide from October 16 to November 5, 2021. The epidemiological survey reports included information on gender, age, source of infection (imported from other provinces or locally acquired), daily life track and itinerary, date of symptom onset and date of diagnosis. The data were analyzed using descriptive statistical methods, one-way analysis of variance, independent t-test, and Chi-square tests. Histograms and percentage stacked area plots were used to describe the epidemiological characteristics of the outbreaks.
 
 
 
 The COVID-19 outbreak associated with the tourist groups has involved 551 COVID-19 cases, with a median age of 44 years (interquartile range: 30-59 years), gradually spreading from the northwestern region to the national level across 15 provinces of China. Fifth cases (16.0%) had traveled to ejin banner, resulting in 68 second-generation cases. The outbreak involved 11 flights and 19 trains, with a total of 27 confirmed cases. An amount of 42 related outbreaks were clustered, of which 21 outbreaks (50.0%) occurred in households and 10 outbreaks (23.81%) in restaurants. About 106 confirmed cases were related to the restaurant gathering. The median incubation period for this COVID-19 outbreak was 7 days (inter-quartile range: 5-10 days).
 
 
 
 The survey results indicated that this COVID-19 outbreak originated in Ejina Banner and spread by tourist groups, which was a typical infection outbreak promoted by travel. Our results further confirmed that travel need to be more strictly weighed in pandemic like COVID-19, and people need to pay more attention to the prevention against infectious diseases particularly when traveling in a tourist group.


Analysis on a Typical COVID-19 Outbreak Spread by Tourist Groups

Objective: To systematically evaluate the incidence of adverse reactions to coronavirus disease 2019 (COVID-19) vaccination. Methods: We systematically searched PubMed, Embase, The Cochrane Library, Web of Science, CNKI, WanFang Data, and VIP Database from the inception of each database to August 31, 2021. Randomized controlled clinical trials (RCTs) on the safety of different types of COVID-19 vaccines were retrieved and analyzed. A random or fixed-effects model was used with an odds ratio as the effect size. The quality of each reference was evaluated. The incidence of the adverse reactions of the placebo group and the vaccination group was compared. Heterogeneity and publication bias were taken care of by meta-regression and sub-group analyses. Results: A total of 13 articles were included, with 81 287 subjects. Compared with the placebo group, the vaccination group showed a higher combined risk ratio (RR) of total adverse reactions (RR=1.67, 95% CI: 1.46-1.91, P<0.01), local adverse reactions (RR=2.86, 95% CI: 2.11-3.87, P<0.01), systemic adverse reactions (RR=1.25, 95% CI: 0.92-1.72, P=0.16), pain (RR=2.55, 95% CI: 1.75-3.70, P<0.01), swelling (RR=4.16, 95% CI: 1.71-10.17, P=0.002, fever (RR=2.34, 95% CI: 1.84-2.97, P<0.01), fatigue (RR=1.36, 95% CI: 1.32-1.41, P<0.01) and headache (RR=1.22, 95% CI: 1.18-1.26, P<0.01). The subgroup analysis showed the incidence of adverse reactions of the vaccination group after injection of the three COVID-19 vaccines (inactivated viral vaccines, mRNA vaccines and adenovirus vector vaccines) was higher than that of the placebo group, and the difference between the placebo group and the vaccination group in the mRNA vaccine subgroup and the adenovirus vector vaccine subgroup was statistically significant (P<0.01). The incidence of adverse reactions after injection of COVID-19 vaccine in subgroups of different ages was significantly higher than that in the placebo group (P<0.01). Conclusions: COVID-19 vaccines have a good safety, among which adenovirus vector vaccine has the highest incidence of adverse reactions. Both adolescents and adults vaccinated with novel coronavirus vaccine have a certain proportion of adverse reactions, but the symptoms are mild and can be relieved by themselves. Our meta-analysis can help boost global awareness of vaccine safety, promote mass vaccination, help build regional and global immune barriers and effectively curb the recurrency of COVID-19.

Jinxi Yao

Papers

Impact of meteorological factors on the COVID-19 transmission: A multi-city study in China.

An effect assessment of Airborne particulate matter pollution on COVID-19: A multi-city Study in China

Analysis on a Typical COVID-19 Outbreak Spread by Tourist Groups

Incidence of adverse reactions to COVID-19 vaccination: A meta-analysis of randomized controlled trials