The origins of COVID-19 pandemic: A brief overview.

The novel coronavirus disease (COVID-19) outbreak that emerged at the end of 2019 has now swept the world for more than 2 years, causing immeasurable damage to the lives and economies of the world. It has drawn so much attention to discovering how the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated and entered the human body. The current argument revolves around two contradictory theories: a scenario of laboratory spillover events and human contact with zoonotic diseases. Here, we reviewed the transmission, pathogenesis, possible hosts, as well as the genome and protein structure of SARS-CoV-2, which play key roles in the COVID-19 pandemic. We believe the coronavirus was originally transmitted to human by animals rather than by a laboratory leak. However, there still needs more investigations to determine the source of the pandemic. Understanding how COVID-19 emerged is vital to developing global strategies for mitigating future outbreaks.

Trends in Illness Severity, Hospitalization, and Mortality for Community-Onset Pneumonia at 118 US Veterans Affairs Medical Centers.

BACKGROUND: Deaths from pneumonia were decreasing globally prior to the COVID-19 pandemic, but it is unclear whether this was due to changes in patient populations, illness severity, diagnosis, hospitalization thresholds, or treatment. Using clinical data from the electronic health record among a national cohort of patients initially diagnosed with pneumonia, we examined temporal trends in severity of illness, hospitalization, and short- and long-term deaths. DESIGN: Retrospective cohort PARTICIPANTS: All patients >18 years presenting to emergency departments (EDs) at 118 VA Medical Centers between 1/1/2006 and 12/31/2016 with an initial clinical diagnosis of pneumonia and confirmed by chest imaging report. EXPOSURES: Year of encounter. MAIN MEASURES: Hospitalization and 30-day and 90-day mortality. Illness severity was defined as the probability of each outcome predicted by machine learning predictive models using age, sex, comorbidities, vital signs, and laboratory data from encounters during years 2006-2007, and similar models trained on encounters from years 2015 to 2016. We estimated the changes in hospitalizations and 30-day and 90-day mortality between the first and the last 2 years of the study period accounted for by illness severity using time covariate decompositions with model estimates. RESULTS: Among 196,899 encounters across the study period, hospitalization decreased from 71 to 63%, 30-day mortality 10 to 7%, 90-day mortality 16 to 12%, and 1-year mortality 29 to 24%. Comorbidity risk increased, but illness severity decreased. Decreases in illness severity accounted for 21-31% of the decrease in hospitalizations, and 45-47%, 32-24%, and 17-19% of the decrease in 30-day, 90-day, and 1-year mortality. Findings were similar among underrepresented patients and those with only hospital discharge diagnosis codes. CONCLUSIONS: Outcomes for community-onset pneumonia have improved across the VA healthcare system after accounting for illness severity, despite an increase in cases and comorbidity burden.

A systematic review and meta-analysis on the prevalence of stigma in infectious diseases, including COVID-19: a call to action.

Infectious diseases, including COVID-19, are crucial public health issues and may lead to considerable fear among the general public and stigmatization of, and discrimination against, specific populations. This meta-analysis aimed to estimate the pooled prevalence of stigma in infectious disease epidemics. We systematically searched PubMed, PsycINFO, Embase, MEDLINE, Web of Science, and Cochrane databases since inception to June 08, 2021, and reported the prevalence of stigma towards people with infectious diseases including SARS, H1N1, MERS, Zika, Ebola, and COVID-19. A total of 50 eligible articles were included that contributed 51 estimates of prevalence in 92722 participants. The overall pooled prevalence of stigma across all populations was 34% [95% CI: 28-40%], including enacted stigma (36% [95% CI: 28-44%]) and perceived stigma (31% [95% CI: 22-40%]). The prevalence of stigma in patients, community population, and health care workers, was 38% [95% CI: 12- 65%], 36% [95% CI: 28-45%], and 30% [95% CI: 20-40%], respectively. The prevalence of stigma in participants from low- and middle-income countries was 37% [95% CI: 29-45%], which is higher than that from high-income countries (27% [95% CI: 18-36%]) though this difference was not statistically significant. A similar trend of prevalence of stigma was also observed in individuals with lower education (47% [95% CI: 23-71%]) compared to higher education level (33% [95% CI: 23-4%]). These findings indicate that stigma is a significant public health concern, and effective and comprehensive interventions are needed to counteract the damaging effects of the infodemics during infectious disease epidemics, including COVID-19, and reduce infectious disease-related stigma.

Probability-Based Estimates of Severe Acute Respiratory Syndrome Coronavirus 2 Seroprevalence and Detection Fraction, Utah, USA.

We aimed to generate an unbiased estimate of the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in 4 urban counties in Utah, USA. We used a multistage sampling design to randomly select community-representative participants >12 years of age. During May 4-June 30, 2020, we collected serum samples and survey responses from 8,108 persons belonging to 5,125 households. We used a qualitative chemiluminescent microparticle immunoassay to detect SARS-CoV-2 IgG in serum samples. We estimated the overall seroprevalence to be 0.8%. The estimated seroprevalence-to-case count ratio was 2.5, corresponding to a detection fraction of 40%. Only 0.2% of participants from whom we collected nasopharyngeal swab samples had SARS-CoV-2-positive reverse transcription PCR results. SARS-CoV-2 antibody prevalence during the study was low, and prevalence of PCR-positive cases was even lower. The comparatively high SARS-CoV-2 detection rate (40%) demonstrates the effectiveness of Utah's testing strategy and public health response.

An analysis of COVID-19 impacts on S&P 500 and FinTech index

COVID-19 developed into an extremely serious pandemic by the middle of 2020. It has caused enormous negative impacts such as a crush to the global market. In this study, we tested the correlation between COVID-19 and stock market in a more intuitive way with the COVID-19 transmission rate and recovery rate. They were generated by using Unscented Kalman Filter method incorporated with SEIR model. Since the Unscented Kalman Filter method analyzes data at daily intervals, we can study the trend of COVID-19 development and the fund index rate change in detail.

Angiotensin II receptor blocker or angiotensin-converting enzyme inhibitor use and COVID-19-related outcomes among US Veterans.

BACKGROUND: Angiotensin II receptor blockers (ARBs) and angiotensin-converting enzyme inhibitors (ACEIs) may positively or negatively impact outcomes in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We investigated the association of ARB or ACEI use with coronavirus disease 2019 (COVID-19)-related outcomes in US Veterans with treated hypertension using an active comparator design, appropriate covariate adjustment, and negative control analyses. METHODS AND FINDINGS: In this retrospective cohort study of Veterans with treated hypertension in the Veterans Health Administration (01/19/2020-08/28/2020), we compared users of (A) ARB/ACEI vs. non-ARB/ACEI (excluding Veterans with compelling indications to reduce confounding by indication) and (B) ARB vs. ACEI among (1) SARS-CoV-2+ outpatients and (2) COVID-19 hospitalized inpatients. The primary outcome was all-cause hospitalization or mortality (outpatients) and all-cause mortality (inpatients). We estimated hazard ratios (HR) using propensity score-weighted Cox regression. Baseline characteristics were well-balanced between exposure groups after weighting. Among outpatients, there were 5.0 and 6.0 primary outcomes per 100 person-months for ARB/ACEI (n = 2,482) vs. non-ARB/ACEI (n = 2,487) users (HR 0.85, 95% confidence interval [CI] 0.73-0.99, median follow-up 87 days). Among outpatients who were ARB (n = 4,877) vs. ACEI (n = 8,704) users, there were 13.2 and 14.8 primary outcomes per 100 person-months (HR 0.91, 95%CI 0.86-0.97, median follow-up 85 days). Among inpatients who were ARB/ACEI (n = 210) vs. non-ARB/ACEI (n = 275) users, there were 3.4 and 2.0 all-cause deaths per 100 person months (HR 1.25, 95%CI 0.30-5.13, median follow-up 30 days). Among inpatients, ARB (n = 1,164) and ACEI (n = 2,014) users had 21.0 vs. 17.7 all-cause deaths, per 100 person-months (HR 1.13, 95%CI 0.93-1.38, median follow-up 30 days). CONCLUSIONS: This observational analysis supports continued ARB or ACEI use for patients already using these medications before SARS-CoV-2 infection. The novel beneficial association observed among outpatients between users of ARBs vs. ACEIs on hospitalization or mortality should be confirmed with randomized trials.

Hydroxychloroquine vs. Azithromycin for Hospitalized Patients with COVID-19 (HAHPS): Results of a Randomized, Active Comparator Trial.

RATIONALE: The COVID-19 pandemic struck an immunologically naïve, globally interconnected population. In the face of a new infectious agent causing acute respiratory failure for which there were no known effective therapies, rapid, often pragmatic trials were necessary to evaluate potential treatments, frequently starting with medications that are already marketed for other indications. Early in the pandemic, hydroxychloroquine and azithromycin were two such candidates. OBJECTIVE: Assess the relative efficacy of hydroxychloroquine and azithromycin among hospitalized patients with COVID-19. METHODS: We performed a randomized clinical trial of hydroxychloroquine vs. azithromycin among hospitalized patients with COVID-19. Treatment was 5 days of study medication. The primary endpoint was the COVID Ordinal Outcomes scale at day 14. Secondary endpoints included hospital-, ICU-, and ventilator-free days at day 28. The trial was stopped early after enrollment of 85 patients when a separate clinical trial concluded that a clinically important effect of hydroxychloroquine over placebo was definitively excluded. Comparisons were made a priori using a proportional odds model from a Bayesian perspective. RESULTS: We enrolled 85 patients at 13 hospitals over 11 weeks. Adherence to study medication was high. The estimated odds ratio for less favorable status on the ordinal scale for hydroxychloroquine vs. azithromycin from the primary analysis was 1.07, with a 95% credible interval from 0.63 to 1.83 with a posterior probability of 60% that hydroxychloroquine was worse than azithryomycin. Secondary outcomes displayed a similar, slight preference for azithromycin over hydroxychloroquine. QTc prolongation was rare and did not differ between groups. The twenty safety outcomes were similar between arms with the possible exception of post-randomization onset acute kidney injury, which was more common with hydroxychloroquine (15% vs. 0%). Patients in the hydroxychloroquine arm received remdesivir more often than in the azithromycin arm (19% vs. 2%). There was no apparent association between remdesivir use and acute kidney injury. CONCLUSIONS: While early termination limits the precision of our results, we found no suggestion of substantial efficacy for hydroxychloroquine over azithromycin. Acute kidney injury may be more common with hydroxychloroquine than azithromycin, although this may be due to the play of chance. Differential use of remdesivir may have biased our results in favor of hydroxychloroquine. Our results are consistent with conclusions from other trials that hydroxychloroquine cannot be recommended for inpatients with COVID-19; azithromycin may merit additional investigation. CLINICAL TRIAL REGISTRATION: This trial was prospectively registered (NCT04329832) before enrollment of the first patient.

Preliminary analysis on the incidence trend of novel coronavirus pneumonia in Shanghai / 上海预防医学

Objective To investigate the epidemical characteristics and analyze the incidence trend of novel coronavirus pneumonia (NCP) in Shanghai. Methods The epidemical data on NCP in Shanghai from January 20 to February 3, 2020 were collected for epidemiological descriptive analysis. Results The number of cumulative confirmed and suspected cases increased first and then decreased from January 20 to February 3, with the peak date being January 30 and January 29 respectively. The day-on-day growth rate of the suspected cases and the cumulative confirmed cases declined after January 27. Among the confirmed cases, the proportion of the exposure history of relevant confirmed cases was on the rise. The total number of confirmed cases of the resident population exceeded that of the population from other places to Shanghai, and Pudong new area had the largest number of confirmed cases. Conclusion The incidence of NCP showed a slowdown trend in shanghai, but it also faces the pressure of the peak of population returning to city, which should be paid enough attention to.