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.

Early pandemic use of face masks in Papua New Guinea under a mask mandate.

Objective: During the coronavirus disease (COVID-19) pandemic, face mask wearing was mandated in Port Moresby, Papua New Guinea in July 2020, but compliance was observed to be low. We aimed to determine the frequency of face mask wearing by the general public in Papua New Guinea under the mask mandate. Methods: To estimate compliance with the mandate, we analysed photographs of people gathering in Port Moresby published between 29 September and 29 October 2020. Photo-epidemiology was performed on the 40 photographs that met pre-defined selection criteria for inclusion in our study. Results: Among the total of 445 fully visible photographed faces, 53 (11.9%) were observed wearing a face mask over mouth and nose. Complete non-compliance (no faces wearing masks) was observed in 19 (4.3%) photographs. Physical distancing was observed in 10% of the 40 photographs. Mask compliance in indoor settings (16.4%) was higher than that observed in outdoor settings (9.8%), and this difference was statistically significant (P < 0.05). Mask compliance was observed in 8.9% of large-sized gatherings (> 30 people), 12.7% of medium-sized gatherings (11-30 people) and 25.0% of small-sized gatherings (4-10 people; photographs with < 4 people were excluded from analysis). Discussion: We found very low population compliance with face mask mandates in Papua New Guinea during the pre-vaccine pandemic period. Individuals without face coverings and non-compliant with physical distancing guidelines are considered to be in a high-risk category for COVID-19 transmission particularly in medium- and large-sized gatherings. A new strategy to enforce public health mandates is required and should be clearly promoted to the public.

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.

Influenza cases in nine aged care facilities in Sydney, Australia over a three-year surveillance period, 2018-2020.

BACKGROUND: Influenza outbreaks in aged care facilities are a major public health concern. In response to the severe 2017 influenza season in Australia, enhanced influenza vaccines were introduced from 2018 onwards for those over 65 and more emphasis was placed on improving vaccination rates among aged care staff. During the COVID-19 pandemic, these efforts were then further escalated to reduce the additional burden that influenza could pose to facilities. METHODS: An observational epidemiological study was conducted from 2018 to 2020 in nine Sydney (Australia) aged care facilities of the same provider. De-identified vaccination data and physical layout data were collected from participating facility managers from 2018 to 2020. Active surveillance of influenza-like illness was carried out from 2018 to 2020 influenza seasons. Correlation and Poisson regression analyses were carried out to explore the relationship between physical layout variables to occurrence of influenza cases. RESULTS: Influenza cases were low in 2018 and 2019, and there were no confirmed influenza cases identified in 2020. Vaccination rates increased among staff by 50.5% and residents by 16.8% over the three-year period of surveillance from 2018 to 2020. For each unit increase in total number of beds, common areas, single rooms, all types of rooms (including double occupancy rooms), the influenza cases increased by 1.02 (95% confidence interval:1.018-1.025), 1.04 (95% confidence interval: 1.019-1.073), 1.03 (95% confidence interval: 1.016-1 0.038) and 1.02 (95% confidence interval:1.005-1.026) times which were found to be statistically significant. For each unit increase in the proportion of shared rooms, influenza cases increased by 1.004 (95% confidence interval:1.0001-1.207) which was found to be statistically significant. CONCLUSIONS: There is a relationship between influenza case counts and aspects of the physical layout such as facility size, and this should be considered in assessing risk of outbreaks in aged care facilities. Increased vaccination rates in staff and COVID-19 prevention and control measures may have eliminated influenza in the studied facilities in 2020.

Factors associated with repeated influenza vaccine uptake among aged care staff in an Australian sample from 2017 to 2019.

BACKGROUND/AIM: Influenza vaccination is strongly recommended every year for aged care staff to protect themselves and minimise risk of transmission to residents. This study aimed to determine the factors associated with repeated annual influenza vaccine uptake among Australian aged care staff from 2017 to 2019. METHODS: Demographic, medical and vaccination data collected from the staff, who participated in an observational study from nine aged care facilities under a single provider in Sydney Australia, were analysed retrospectively. Based on the pattern of repeated influenza vaccination from 2017 to 2019, three groups were identified: (1) unvaccinated all three years; (2) vaccinated occasionally(once or twice) over three years; and (3)vaccinated all threeyears. Multinomial logistic regression analysis was performed to better understand the factors associated with the pattern of repeated influenza vaccination. RESULTS: From a total of 138 staff, between 2017 and 2019, 28.9 % (n = 40) never had a vaccination, while 44.2 % (n = 61) had vaccination occasionally and 26.8 % (n = 37) had vaccination all three years. In the multinomial logistic regression model, those who were<40 years old (OR = 0.57, 95 % CI: 0.19-0.90, p < 0.05) and those who were current smokers (OR = 0.20; 95 % CI: 0.03-0.76, p < 0.05) were less likely to have repeated vaccination for all three years compared to the unvaccinated group. Those who were<40 years old (OR = 0.61; 95 % CI: 0.22-0.68, p < 0.05) and those who were born overseas (OR = 0.50; 95 % CI:0.27-0.69, p < 0.05) were more likely to be vaccinated occasionally compared to the unvaccinated group. CONCLUSION: The significant predictors of repeated vaccine uptake across the three-year study period among aged care staff were age, smoking status and country of birth (Other vs Australia). Targeted interventions towards the younger age group (<40 years old), smokers and those who were born overseas could improve repeated influenza vaccination uptake in the aged care workforce.

Pacific Eclipse - A tabletop exercise on smallpox pandemic response.

BACKGROUND: In December 2019, we ran Pacific Eclipse, a pandemic tabletop exercise using smallpox originating in Fiji as a case study. Pacific Eclipse brought together international stakeholders from health, defence, law enforcement, emergency management and a range of other organisations. AIM: To review potential gaps in preparedness and identify modifiable factors which could prevent a pandemic or mitigate the impact of a pandemic. METHODS: Pacific Eclipse was held on December 9-10 in Washington DC, Phoenix and Honolulu simultaneously. The scenario began in Fiji and becomes a pandemic. Mathematical modelling of smallpox transmission was used to simulate the epidemic under different conditions and to test the effect of interventions. Live polling, using Poll Everywhere software that participants downloaded onto their smart phones, was used to gather participant decisions as the scenario unfolded. Stakeholders from state and federal government and non-government organisations from The United States, The United Kingdom, Australia, New Zealand, Canada, as well as industry and non-government organisations attended. RESULTS: The scenario progressed in three phases and participants were able to make decisions during each phase using live polling. The polling showed very diverse and sometimes conflicting decision making. Factors influential to pandemic severity were identified and categorised as modifiable or unmodifiable. A series of recommendations were made on the modifiable determinants of pandemic severity and how these can be incorporated into pandemic planning. These included preventing an attack through intelligence, law enforcement and legislation, improved speed of diagnosis, speed and completeness of case finding and case isolation, speed and security of vaccination response (including stockpiling), speed and completeness of contact tracing, protecting critical infrastructure and business continuity, non-pharmaceutical interventions (social distancing, PPE, border control) and protecting first responders. DISCUSSION: Pacific Eclipse illustrated the impact of a pandemic of smallpox under different response scenarios, which were validated to some extent by the COVID-19 pandemic. The framework developed from the scenario draws out modifiable determinants of pandemic severity which can inform pandemic planning for the ongoing COVID-19 pandemic and for future pandemics.

Factors Associated With SARS-CoV-2 Attack Rates in Aged Care-A Meta-analysis.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has resulted in significant morbidity and mortality in aged-care facilities worldwide. The attention of infection control in aged care needs to shift towards the built environment, especially in relation to using the existing space to allow social distancing and isolation. Physical infrastructure of aged care facilities has been shown to present challenges to the implementation of isolation procedures. To explore the relationship of the physical layout of aged care facilities with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) attack rates among residents, a meta-analysis was conducted. METHODS: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocol (PRISMA-P), studies were identified from 5 databases using a registered search strategy with PROSPERO. Meta-analysis for pooled attack rates of SARS-CoV-2 in residents and staff was conducted, with subgroup analysis for physical layout variables such as total number of beds, single rooms, number of floors, number of buildings in the facility, and staff per 100 beds. RESULTS: We included 41 articles across 11 countries, reporting on 90 657 residents and 6521 staff in 757 facilities. The overall pooled attack rate was 42.0% among residents (95% CI, 38.0%-47.0%) and 21.7% in staff (95% CI, 15.0%-28.4%). Attack rates in residents were significantly higher in single-site facilities with standalone buildings than facilities with smaller, detached buildings. Staff-to-bed ratio significantly explains some of the heterogeneity of the attack rate between studies. CONCLUSIONS: The design of aged care facilities should be smaller in size, with adequate space for social distancing.

Factors associated with SARS-COV-2 attack rates in aged care– a meta-analysis

Background The COVID-19 pandemic has resulted in significant morbidity and mortality in aged care facilities worldwide. The attention of infection control in aged care needs to shift towards the built environment, especially with relation to using the existing space to allow social distancing and isolation. Physical infrastructure of aged care facilities has been shown to present challenges to implementation of isolation procedures. To explore the relationship of the physical layout of aged care facilities on SARS-CoV-2 attack rates among residents, a meta-analysis was conducted. Methods Using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocol (PRISMA-P), studies were identified from five databases using a registered search strategy with PROSPERO. Meta-regression analysis for pooled attack rates of SARS-CoV-2 in residents and staff was conducted, with subgroup analysis for physical layout variables such as total number of beds, single rooms, number of floors, number of buildings in facility and staff per 100 beds Results We included 41 articles across 11 countries, reporting on 90 657 residents and 6521 staff in 757 facilities. The overall pooled attack rate among residents was 42.0% (95% CI: 38.0-47.0%) and 21.7% (95% CI: 15.0-28.4%) in staff. Attack rates in residents were significantly higher in single-site facilities with standalone buildings than facilities with smaller, detached buildings. Staff-to-bed ratio significantly explains some of the heterogeneity of the attack rate between studies. Conclusion The design of aged care facilities should have smaller-sized facilities with adequate space for social distancing.

Experimental Evidence for the Optimal Design of a High-Performing Cloth Mask.

Cloth masks can be an alternative to medical masks during pandemics. Recent studies have examined the performance of fabrics under various conditions; however, the performance against violent respiratory events such as human sneezes is yet to be explored. Accordingly, we present a comprehensive experimental study using sneezes by a healthy adult and a tailored image-based flow measurement diagnostic system evaluating all dimensions of protection of commonly available fabrics and their layered combinations: the respiratory droplet blocking efficiency, water resistance, and breathing resistance. Our results reveal that a well-designed cloth mask can outperform a three-layered surgical mask for such violent respiratory events. Specifically, increasing the number of layers significantly increases the droplet blocking efficiency, on average by ∼20 times per additional fabric layer. A minimum of three layers is necessary to resemble the droplet blocking performance of surgical masks, and a combination of cotton/linen (hydrophilic inner layer)-blends (middle layer)-polyester/nylon (hydrophobic outer layer) exhibited the best performance among overall indicators tested. In an optimum three-layered design, the average thread count should be greater than 200, and the porosity should be less than 2%. Furthermore, machine washing at 60 °C did not significantly impact the performance of cloth masks. These findings inform the design of high-performing homemade cloth masks.

The potential impact of a recent measles epidemic on COVID-19 in Samoa.

BACKGROUND: The pandemic of COVID-19 has occurred close on the heels of a global resurgence of measles. In 2019, an unprecedented epidemic of measles affected Samoa, requiring a state of emergency to be declared. Measles causes an immune amnesia which can persist for over 2 years after acute infection and increases the risk of a range of other infections. METHODS: We modelled the potential impact of measles-induced immune amnesia on a COVID-19 epidemic in Samoa using data on measles incidence in 2018-2019, population data and a hypothetical COVID-19 epidemic. RESULTS: The young population structure and contact matrix in Samoa results in the most transmission occurring in young people < 20 years old. The highest rate of death is the 60+ years old, but a smaller peak in death may occur in younger people, with more than 15% of total deaths in the age group under 20 years old. Measles induced immune amnesia could increase the total number of cases by 8% and deaths by more than 2%. CONCLUSIONS: Samoa, which had large measles epidemics in 2019-2020 should focus on rapidly achieving high rates of measles vaccination and enhanced surveillance for COVID-19, as the impact may be more severe due to measles-induced immune paresis. This applies to other severely measles-affected countries in the Pacific, Europe and elsewhere.

The effectiveness of full and partial travel bans against COVID-19 spread in Australia for travellers from China during and after the epidemic peak in China.

BACKGROUND: Australia implemented a travel ban on China on 1 February 2020, while COVID-19 was largely localized to China. We modelled three scenarios to test the impact of travel bans on epidemic control. Scenario one was no ban; scenario two and three were the current ban followed by a full or partial lifting (allow over 100 000 university students to enter Australia, but not tourists) from the 8th of March 2020. METHODS: We used disease incidence data from China and air travel passenger movements between China and Australia during and after the epidemic peak in China, derived from incoming passenger arrival cards. We used the estimated incidence of disease in China, using data on expected proportion of under-ascertainment of cases and an age-specific deterministic model to model the epidemic in each scenario. RESULTS: The modelled epidemic with the full ban fitted the observed incidence of cases well, predicting 57 cases on March 6th in Australia, compared to 66 observed on this date; however, we did not account for imported cases from other countries. The modelled impact without a travel ban results in more than 2000 cases and about 400 deaths, if the epidemic remained localized to China and no importations from other countries occurred. The full travel ban reduced cases by about 86%, while the impact of a partial lifting of the ban is minimal and may be a policy option. CONCLUSIONS: Travel restrictions were highly effective for containing the COVID-19 epidemic in Australia during the epidemic peak in China and averted a much larger epidemic at a time when COVID-19 was largely localized to China. This research demonstrates the effectiveness of travel bans applied to countries with high disease incidence. This research can inform decisions on placing or lifting travel bans as a control measure for the COVID-19 epidemic.