Estimated Mask Use and Temporal Relationship to COVID-19 Epidemiology of Black Lives Matter Protests in 12 Cities.

BACKGROUND: There is an increased risk of SARS-CoV-2 transmission during mass gatherings and a risk of asymptomatic infection. We aimed to estimate the use of masks during Black Lives Matter (BLM) protests and whether these protests increased the risk of COVID-19. Two reviewers screened 496 protest images for mask use, with high inter-rater reliability. Protest intensity, use of tear gas, government control measures, and testing rates were estimated in 12 cities. A correlation analysis was conducted to assess the potential effect of mask use and other measures, adjusting for testing rates, on COVID-19 epidemiology 4 weeks (two incubation periods) post-protests. Mask use ranged from 69 to 96% across protests. There was no increase in the incidence of COVID-19 post-protest in 11 cities. After adjusting for testing rates, only Miami, which involved use of tear gas and had high protest intensity, showed a clear increase in COVID-19 after one incubation period post-protest. No significant correlation was found between incidence and protest factors. Our study showed that protests in most cities studied did not increase COVID-19 incidence in 2020, and a high level of mask use was seen. The absence of an epidemic surge within two incubation periods of a protest is indicative that the protests did not have a major influence on epidemic activity, except in Miami. With the globally circulating highly transmissible Alpha, Delta, and Omicron variants, layered interventions such as mandated mask use, physical distancing, testing, and vaccination should be applied for mass gatherings in the future.

Artificial intelligence in public health: the potential of epidemic early warning systems.

The use of artificial intelligence (AI) to generate automated early warnings in epidemic surveillance by harnessing vast open-source data with minimal human intervention has the potential to be both revolutionary and highly sustainable. AI can overcome the challenges faced by weak health systems by detecting epidemic signals much earlier than traditional surveillance. AI-based digital surveillance is an adjunct to-not a replacement of-traditional surveillance and can trigger early investigation, diagnostics and responses at the regional level. This narrative review focuses on the role of AI in epidemic surveillance and summarises several current epidemic intelligence systems including ProMED-mail, HealthMap, Epidemic Intelligence from Open Sources, BlueDot, Metabiota, the Global Biosurveillance Portal, Epitweetr and EPIWATCH. Not all of these systems are AI-based, and some are only accessible to paid users. Most systems have large volumes of unfiltered data; only a few can sort and filter data to provide users with curated intelligence. However, uptake of these systems by public health authorities, who have been slower to embrace AI than their clinical counterparts, is low. The widespread adoption of digital open-source surveillance and AI technology is needed for the prevention of serious epidemics.

COVID-19 outbreaks in aged-care facilities in Australia.

BACKGROUND: Aged-care facilities (ACF's) provide unique challenges when implementing infection control methods for respiratory outbreaks such as COVID-19. Research on this highly vulnerable setting is lacking and there was no national reporting data of COVID-19 cases in ACFs in Australia early in the pandemic. We aimed to estimate the burden of aged-care worker (ACW) infections and outbreaks of COVID-19 in Australian aged-care. METHODS: A line list of publicly available aged-care related COVID-19 reported cases from January 25 to June 10, 2020 was created and was enhanced by matching data extracted from media reports of aged-care related COVID-19 relevant outbreaks and reports. Rate ratios (RR) were used to predict risk of infection in ACW and aged-care residents, and were calculated independently, by comparing overall cases to ACW and aged-care residents' cases. RESULTS: A total of 14 ACFs with COVID-19 cases were recorded by June 2020 nationwide, with a high case fatality rate (CFR) of 50% (n = 34) and 100% (n = 3) seen in two ACFs. Analysis on the resident risk found that the COVID-19 risk is 1.27 times higher (unadjusted RR 1.27 95% confidence interval [CI] 1.00 to1.61; P = 0.047) as compared with the risk of infection in the general population. In over 60% of cases identified in ACFs, the source of infection in the index case was unknown. A total of 28 deaths associated within ACFs were reported, accounting for 54.9% of total deaths in New South Wales and 26.9% of total deaths in Australia. CONCLUSIONS: This high-risk population requires additional prevention and control measures, such as routine testing of all staff and patients regardless of symptoms. Prompt isolation and quarantine as soon as a case is confirmed within a facility is essential.

Droplets and Aerosols Generated by Singing and the Risk of Coronavirus Disease 2019 for Choirs.

Choral singing has become a major risk during the coronavirus disease 2019 (COVID-19) pandemic due to high infection rates. Our visualization and velocimetry results reveal that the majority of droplets expelled during singing follow the ambient airflow pattern. These results point toward the possibility of COVID-19 spread by small airborne droplets during singing.

Estimating the burden of COVID-19 on the Australian healthcare workers and health system during the first six months of the pandemic.

INTRODUCTION: There are no publicly available national data on healthcare worker infections in Australia. It has been documented in many countries that healthcare workers (HCW) are at increased occupational risk of COVID-19. We aimed to estimate the burden of COVID-19 on Australia HCW and the health system by obtaining and organizing data on HCW infections, analyzing national HCW cases in regards to occupational risk and analyzing healthcare outbreak. METHODS: We searched government reports and websites and media reports to create a comprehensive line listing of Australian HCW infections and nosocomial outbreaks between January 25th and July 8th, 2020. A line list of HCW related COVID-19 reported cases was created and enhanced by matching data extracted from media reports of healthcare related COVID-19 relevant outbreaks and reports, using matching criteria. Rates of infections and odds ratios (ORs) for HCW were calculated per state, by comparing overall cases to HCW cases. To investigate the sources of infection amongst HCW, transmission data were collated and graphed to show distribution of sources. RESULTS: We identified 36 hospital outbreaks or HCW infection reports between January 25th and July 8th, 2020. According to our estimates, at least 536 HCW in Australia had been infected with COVID-19, comprising 6.03% of all reported infections. The rate of HCW infection was 90/100000 and of community infection 34/100,000. HCW were 2.69 times more likely to contract COVID-19 (95% CI 2.48 to 2.93; P < 0.001). The timing of hospital outbreaks did not always correspond to community peaks. Where data were available, a total of 131 HCW across 21 outbreaks led to 1656 HCW being furloughed for quarantine. In one outbreak, one hospital was closed and 1200 HCW quarantined. CONCLUSION: The study shows that HCW were at nearly 3 times the risk of infection. Of concern, this nearly tripling of risk occurred during a period of low community prevalence suggesting failures at multiple hazard levels including PPE policies within the work environment. Even in a country with relatively good control of COVID-19, HCW are at greater risk of infection than the general community and nosocomial outbreaks can have substantial effects on workforce capacity by the quarantine of numerous HCW during an outbreak. The occurrence of hospital outbreaks even when community incidence was low highlights the high risk setting that hospitals present. Australia faced a resurgence of COVID-19 after the study period, with multiple hospital outbreaks. We recommend formal reporting of HCW infections, testing protocols for nosocomial outbreaks, cohorting of workforce to minimize the impact, and improved PPE guidelines to provide precautionary and optimal protection for HCW.