SEIR Model to address the impact of face masks amid COVID-19 pandemic.

Early in the pandemic of coronavirus disease 2019 (COVID-19), face masks were used extensively by the general public in several Asian countries. The lower transmission rate of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Asian countries compared with Western countries suggested that the wider community use of face masks has the potential to decrease transmission of SARS-CoV-2. A risk assessment model named Susceptible, Exposed, Infectious, Recovered (SEIR) model is used to quantitatively evaluate the potential impact of community face masks on SARS-CoV-2 reproduction number (R0 ) and peak number of infectious persons. For a simulated population of one million, the model showed a reduction in R0 of 49% and 50% when 60% and 80% of the population wore masks, respectively. Moreover, we present a modified model that considers the effect of mask-wearing after community vaccination. Interestingly mask-wearing still provided a considerable benefit in lowering the number of infectious individuals. The results of this research are expected to help public health officials in making prompt decisions involving resource allocation and crafting legislation.

COVID-19 Trials: Who Participates and Who Benefits?

OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic has disproportionately afflicted vulnerable populations. Older adults, particularly residents of nursing facilities, represent a small percentage of the population but account for 40% of mortality from COVID-19 in the United States. Racial and ethnic minority individuals, particularly Black, Hispanic, and Indigenous Americans have experienced higher rates of infection and death than the White population. Although there has been an unprecedented explosion of clinical trials to examine potential therapies, participation by members of these vulnerable communities is crucial to obtaining data generalizable to those communities. METHODS: We undertook an open-label, factorial randomized clinical trial examining hydroxychloroquine and/or azithromycin for hospitalized patients. RESULTS: Of 53 screened patients, 11 (21%) were enrolled. Ten percent (3/31) of Black patients were enrolled, 33% (7/21) of White patients, and 50% (6/12) of Hispanic patients. Forty-seven percent (25/53) of patients declined participation despite eligibility; 58%(18/31) of Black patients declined participation. Forty percent (21/53) of screened patients were from a nursing facility and 10% (2/21) were enrolled. Enrolled patients had fewer comorbidities than nonenrolled patients: median modified Charlson comorbidity score 2.0 (interquartile range 0-2.5), versus 4.0 (interquartile range 2-6) for nonenrolled patients (P = 0.006). The limitations of the study were the low participation rate and the multiple treatment trials concurrently recruiting at our institution. CONCLUSIONS: The high rate of nonparticipation in our trial of nursing facility residents and Black people emphasizes the concern that clinical trials for therapeutics may not target key populations with high mortality rates.

Social Disadvantage, Politics, and Severe Acute Respiratory Syndrome Coronavirus 2 Trends: A County-level Analysis of United States Data.

BACKGROUND: Understanding the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for public health control efforts. Social, demographic, and political characteristics at the United States (US) county level might be associated with changes in SARS-CoV-2 case incidence. METHODS: We conducted a retrospective analysis of the relationship between the change in reported SARS-CoV-2 case counts at the US county level during 1 June-30 June 2020 and social, demographic, and political characteristics of the county. RESULTS: Of 3142 US counties, 1023 were included in the analysis: 678 (66.3%) had increasing and 345 (33.7%) nonincreasing SARS-CoV-2 case counts between 1 June and 30 June 2020. In bivariate analysis, counties with increasing case counts had a significantly higher Social Deprivation Index (median, 48 [interquartile range {IQR}, 24-72]) than counties with nonincreasing case counts (median, 40 [IQR, 19-66]; P = .009). Counties with increasing case counts were significantly more likely to be metropolitan areas of 250 000-1 million population (P < .001), to have a higher percentage of black residents (9% vs 6%; P = .013), and to have voted for the Republican presidential candidate in 2016 by a ≥10-point margin (P = .044). In the multivariable model, metropolitan areas of 250 000-1 million population, higher percentage of black residents, and a ≥10-point Republican victory were independently associated with increasing case counts. CONCLUSIONS: Increasing case counts of SARS-CoV-2 in the US during June 2020 were associated with a combination of sociodemographic and political factors. Addressing social disadvantage and differential belief systems that may correspond with political alignment will play a critical role in pandemic control.

Mortality outcomes with hydroxychloroquine and chloroquine in COVID-19 from an international collaborative meta-analysis of randomized trials.

Substantial COVID-19 research investment has been allocated to randomized clinical trials (RCTs) on hydroxychloroquine/chloroquine, which currently face recruitment challenges or early discontinuation. We aim to estimate the effects of hydroxychloroquine and chloroquine on survival in COVID-19 from all currently available RCT evidence, published and unpublished. We present a rapid meta-analysis of ongoing, completed, or discontinued RCTs on hydroxychloroquine or chloroquine treatment for any COVID-19 patients (protocol: https://osf.io/QESV4/ ). We systematically identified unpublished RCTs (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, Cochrane COVID-registry up to June 11, 2020), and published RCTs (PubMed, medRxiv and bioRxiv up to October 16, 2020). All-cause mortality has been extracted (publications/preprints) or requested from investigators and combined in random-effects meta-analyses, calculating odds ratios (ORs) with 95% confidence intervals (CIs), separately for hydroxychloroquine and chloroquine. Prespecified subgroup analyses include patient setting, diagnostic confirmation, control type, and publication status. Sixty-three trials were potentially eligible. We included 14 unpublished trials (1308 patients) and 14 publications/preprints (9011 patients). Results for hydroxychloroquine are dominated by RECOVERY and WHO SOLIDARITY, two highly pragmatic trials, which employed relatively high doses and included 4716 and 1853 patients, respectively (67% of the total sample size). The combined OR on all-cause mortality for hydroxychloroquine is 1.11 (95% CI: 1.02, 1.20; I² = 0%; 26 trials; 10,012 patients) and for chloroquine 1.77 (95%CI: 0.15, 21.13, I² = 0%; 4 trials; 307 patients). We identified no subgroup effects. We found that treatment with hydroxychloroquine is associated with increased mortality in COVID-19 patients, and there is no benefit of chloroquine. Findings have unclear generalizability to outpatients, children, pregnant women, and people with comorbidities.

Monitoring scheme for early detection of coronavirus and other respiratory virus outbreaks.

In December 2019, an outbreak of pneumonia caused by a novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) began in Wuhan, China. SARS-CoV-2 exhibited efficient person-to-person transmission of what became labeled as COVID-19. It has spread worldwide with over 83,000,000 infected cases and more than 1,800,000 deaths to date (December 31, 2020). This research proposes a statistical monitoring scheme in which an optimized np control chart is utilized by sentinel metropolitan airports worldwide for early detection of coronavirus and other respiratory virus outbreaks. The sample size of this chart is optimized to ensure the best overall performance for detecting a wide range of shifts in the infection rate, based on the available resources, such as the inspection rate and the allowable false alarm rate. The effectiveness of the proposed optimized np chart is compared with that of the traditional np chart with a predetermined sample size under both sampling inspection and 100% inspection. For a variety of scenarios including a real case, the optimized np control chart is found to substantially outperform its traditional counterpart in terms of the average number of infections. Therefore, this control chart has potential to be an effective tool for early detection of respiratory virus outbreaks, promoting early outbreak investigation and mitigation.