Healthcare Workers' SARS-CoV-2 Infections in Four Hospital Outbreaks during Delta Variant Prevalence in Sydney, Australia.

Background: Healthcare workers (HCWs) are at risk of SARS-CoV-2 infections due to occupational exposure. The use of airborne personal protective equipment (PPE) significantly reduces this risk. In June 2021, an epidemic of the Delta variant began in New South Wales (NSW), Australia. Concurrent PPE guidelines, set by the Clinical Excellence Commission (CEC), restricted the use of respirators. Objective: To understand the relationship of PPE guidelines with workplace-acquired HCW SARS-CoV-2 infections in different clinical settings and to examine the relationship between rates of community transmission and workplace-acquired HCW infections during the Delta outbreak in NSW. Methods: Total SARS-CoV-2 HCW infections between 13 June and 30 October 2021 (first four months of the Delta wave) were estimated from the government COVID-19 surveillance reports and compared with the surveillance reports of community transmission. In the absence of a detailed reporting of HCW infections, open-source data including news articles, media releases, and epidemiological surveillance reports were also collected. Data were extracted on HCW cases of SARS-CoV-2 from four hospitals, including the number of HCW cases (per NSW Health definition), clinical setting, PPE guidelines, and evidence of increasing local transmission. Results: SARS-CoV-2 infections in HCW identified as workplace-acquired infections (n = 177) and those without a known transmission source (n = 532) increased during the period of increasing community transmission (n = 75,014) in NSW. Four hospital COVID-19 clusters affecting 20 HCWs were identified between June and October 2021. HCW clusters occurred in general wards where staff were recommended to wear surgical masks. No workplace-acquired HCW infections were reported in these hospitals from critical care wards, where respirators were recommended during the same outbreak weeks. Conclusions: Differences in PPE policy across different wards may leave healthcare staff at risk of SARS-CoV-2 infection. During periods of high community transmission, respirators should be provided to protect hospital staff. Formal reporting of HCW infections should occur.

Open-Source Intelligence for Detection of Radiological Events and Syndromes Following the Invasion of Ukraine in 2022: Observational Study.

BACKGROUND: On February 25, 2022, Russian forces took control of the Chernobyl power plant after continuous fighting within the Chernobyl exclusion zone. Continual events occurred in the month of March, which raised the risk of potential contamination of previously uncontaminated areas and the potential for impacts on human and environmental health. The disruption of war has caused interruptions to normal preventive activities, and radiation monitoring sensors have been nonfunctional. Open-source intelligence can be informative when formal reporting and data are unavailable. OBJECTIVE: This paper aimed to demonstrate the value of open-source intelligence in Ukraine to identify signals of potential radiological events of health significance during the Ukrainian conflict. METHODS: Data were collected from search terminology for radiobiological events and acute radiation syndrome detection between February 1 and March 20, 2022, using 2 open-source intelligence (OSINT) systems, EPIWATCH and Epitweetr. RESULTS: Both EPIWATCH and Epitweetr identified signals of potential radiobiological events throughout Ukraine, particularly on March 4 in Kyiv, Bucha, and Chernobyl. CONCLUSIONS: Open-source data can provide valuable intelligence and early warning about potential radiation hazards in conditions of war, where formal reporting and mitigation may be lacking, to enable timely emergency and public health responses.

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.

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.

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.

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.

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.

Distinct and sequential re-replication barriers ensure precise genome duplication.

Achieving complete and precise genome duplication requires that each genomic segment be replicated only once per cell division cycle. Protecting large eukaryotic genomes from re-replication requires an overlapping set of molecular mechanisms that prevent the first DNA replication step, the DNA loading of MCM helicase complexes to license replication origins, after S phase begins. Previous reports have defined many such origin licensing inhibition mechanisms, but the temporal relationships among them are not clear, particularly with respect to preventing re-replication in G2 and M phases. Using a combination of mutagenesis, biochemistry, and single cell analyses in human cells, we define a new mechanism that prevents re-replication through hyperphosphorylation of the essential MCM loading protein, Cdt1. We demonstrate that Cyclin A/CDK1 can hyperphosphorylate Cdt1 to inhibit MCM re-loading in G2 phase. The mechanism of inhibition is to block Cdt1 binding to MCM independently of other known Cdt1 inactivation mechanisms such as Cdt1 degradation during S phase or Geminin binding. Moreover, our findings suggest that Cdt1 dephosphorylation at the mitosis-to-G1 phase transition re-activates Cdt1. We propose that multiple distinct, non-redundant licensing inhibition mechanisms act in a series of sequential relays through each cell cycle phase to ensure precise genome duplication.