To what extent is alcohol consumption in social gatherings associated with observance of COVID-19 restrictions? A rapid review.

Background: Pre-pandemic research found a connection between alcohol consumption and reduced physical distancing among strangers. Understanding the association between alcohol consumption at social gatherings and observance of COVID-19 restrictions can help inform policy related to the safe operation of public spaces where alcohol is typically consumed, as well as guidance related to the safe conduct of social events in private spaces. Methods: We conducted a rapid review using adapted systematic review methods to explore the association between alcohol consumption in social gatherings and compliance with COVID-19 public health measures and produced a narrative synthesis of our findings. We ran searches in eleven health-related databases (MEDLINE, PubMed, CINAHL, Scopus, Embase (Ovid), ProQuest Public Health, ProQuest Coronavirus, Global Health (Ovid), WHO COVID-19 literature database, PsycInfo (Ovid) and ASSIA) between July 9, 2021, and July 31, 2021. We assessed methodological quality using the relevant Joanna Briggs Institute (JBI) checklists. This review was conducted and reported in accordance with PRISMA-P guidelines. Results: We identified 7936 studies from the searches. After title, abstract and full-text review, three cross-sectional studies were eligible for inclusion. One study found that people who adhered strongly to physical distancing rules were engaged in about 40% fewer weekly drinks and 60% fewer heavy episodic drinking occasions in a week than people who adhered poorly to physical distancing rules (P < 0.01). One study found that people who reported low-risk alcohol consumption patterns had a higher chance of adhering to hand hygiene measures than those who reported high-risk alcohol consumption (odds ratio (OR) = 4.24, 95% confidence interval (CI) = 1.08-16.64). No other statistically significant results on patterns of alcohol consumption and compliance with individual public health measures or with non-pharmaceutical interventions (NPIs) were found. The direction of effect between alcohol consumption and non-adherence to NPIs and the effect of confounding factors has not been established. The quality of studies found was low to moderate, with risk of recall bias and selection bias due to study design; and the extent to which those studies can be generalised beyond their original settings may be limited. Conclusions: Despite existing evidence suggesting an association between alcohol consumption, reduced physical distancing, and increased social interaction, we found few studies of variable quality exploring the relationship between alcohol consumption and compliance with public health measures. A possible association between higher-risk alcohol behaviours and lower compliance with certain NPIs was suggested, but the direction of effect is unknown, and further studies are required to confirm this finding.

Clinical features of COVID-19 for integration of COVID-19 into influenza surveillance: A systematic review.

Background: In November 2020, the World Health Organization (WHO) created interim guidance on how to integrate testing for SARS-CoV-2 into existing influenza surveillance systems. Influenza-like illness (ILI) and severe acute respiratory illness (SARI) case definitions have been used to specify the case definition of COVID-19 for surveillance purposes. This review aims to assess whether the common clinical features of COVID-19 have changed to the point that the criteria used to identify both COVID-19 and influenza in surveillance programs needs to be altered. Methods: A systematic review of reviews following PRISMA-P guidelines was conducted using the "COVID-19 evidence review" database from August 19, 2020, to August 19, 2021. Reviews providing pooled estimates of the prevalence of clinical features of COVID-19 within the general population, diagnosed by polymerase chain reaction or rapid diagnostic test, were included. These were critically appraised and sensitivity analysis was undertaken to examine potential causes of bias. Results: Fourteen reviews were identified, including three on adults only and three on children only. For all reviews, combined fever (median prevalence = 73.0%, IQR = 58.3-78.7) and cough (45.1%, IQR = 28.9-54.0) were the most common features. These were followed by loss of taste or smell (45.1%, IQR = 28.9-54.0), hypoxemia (33%, one review), fatigue (26.4%, IQR = 9.0-39.4) and expectoration (23.9%, IQR = 23.3-25.5). Fever and cough continued to be the most prevalent features for adults and children, with subsequent symptoms being similar for adults only. However, the pattern differed for children, with headache (34.3%, IQR = 18-50.7) and nasal congestion (20%, one review) being the third and fourth commonest symptoms. Conclusions: The prevalent features found in this recent review were the same as the ones identified at the beginning of the pandemic. Therefore, the current approach of using the ILI and SARI criteria which incorporate fever and cough will identify COVID-19 cases in addition to influenza. Interestingly, children may present with different features, as headaches and nasal congestion were more common in this group. Future research could examine this further and investigate whether symptomology changes with new variants of COVID-19.

Which factors influence the extent of indoor transmission of SARS-CoV-2? A rapid evidence review.

BACKGROUND: This rapid evidence review identifies and integrates evidence from epidemiology, microbiology and fluid dynamics on the transmission of SARS-CoV-2 in indoor environments. METHODS: Searches were conducted in May 2020 in PubMed, medRxiv, arXiv, Scopus, WHO COVID-19 database, Compendex & Inspec. We included studies reporting data on any indoor setting except schools, any indoor activities and any potential means of transmission. Articles were screened by a single reviewer, with rejections assessed by a second reviewer. We used Joanna Briggs Institute and Critical Appraisal Skills Programme tools for evaluating epidemiological studies and developed bespoke tools for the evaluation of study types not covered by these instruments. Data extraction and quality assessment were conducted by a single reviewer. We conducted a meta-analysis of secondary attack rates in household transmission. Otherwise, data were synthesised narratively. RESULTS: We identified 1573 unique articles. After screening and quality assessment, fifty-eight articles were retained for analysis. Experimental evidence from fluid mechanics and microbiological studies demonstrates that aerosolised transmission is theoretically possible; however, we found no conclusive epidemiological evidence of this occurring. The evidence suggests that ventilation systems have the potential to decrease virus transmission near the source through dilution but to increase transmission further away from the source through dispersal. We found no evidence for faecal-oral transmission. Laboratory studies suggest that the virus survives for longer on smooth surfaces and at lower temperatures. Environmental sampling studies have recovered small amounts of viral RNA from a wide range of frequently touched objects and surfaces; however, epidemiological studies are inconclusive on the extent of fomite transmission. We found many examples of transmission in settings characterised by close and prolonged indoor contact. We estimate a pooled secondary attack rate within households of 11% (95% confidence interval (CI) = 9, 13). There were insufficient data to evaluate the transmission risks associated with specific activities. Workplace challenges related to poverty warrant further investigation as potential risk factors for workplace transmission. Fluid mechanics evidence on the physical properties of droplets generated by coughing, speaking and breathing reinforce the importance of maintaining 2 m social distance to reduce droplet transmission. CONCLUSIONS: This review provides a snap-shot of evidence on the transmission of SARS-CoV-2 in indoor environments from the early months of the pandemic. The overall quality of the evidence was low. As the quality and quantity of available evidence grows, it will be possible to reach firmer conclusions on the risk factors for and mechanisms of indoor transmission.

The temporal association of introducing and lifting non-pharmaceutical interventions with the time-varying reproduction number (R) of SARS-CoV-2: a modelling study across 131 countries.

BACKGROUND: Non-pharmaceutical interventions (NPIs) were implemented by many countries to reduce the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of COVID-19. A resurgence in COVID-19 cases has been reported in some countries that lifted some of these NPIs. We aimed to understand the association of introducing and lifting NPIs with the level of transmission of SARS-CoV-2, as measured by the time-varying reproduction number (R), from a broad perspective across 131 countries. METHODS: In this modelling study, we linked data on daily country-level estimates of R from the London School of Hygiene & Tropical Medicine (London, UK) with data on country-specific policies on NPIs from the Oxford COVID-19 Government Response Tracker, available between Jan 1 and July 20, 2020. We defined a phase as a time period when all NPIs remained the same, and we divided the timeline of each country into individual phases based on the status of NPIs. We calculated the R ratio as the ratio between the daily R of each phase and the R from the last day of the previous phase (ie, before the NPI status changed) as a measure of the association between NPI status and transmission of SARS-CoV-2. We then modelled the R ratio using a log-linear regression with introduction and relaxation of each NPI as independent variables for each day of the first 28 days after the change in the corresponding NPI. In an ad-hoc analysis, we estimated the effect of reintroducing multiple NPIs with the greatest effects, and in the observed sequence, to tackle the possible resurgence of SARS-CoV-2. FINDINGS: 790 phases from 131 countries were included in the analysis. A decreasing trend over time in the R ratio was found following the introduction of school closure, workplace closure, public events ban, requirements to stay at home, and internal movement limits; the reduction in R ranged from 3% to 24% on day 28 following the introduction compared with the last day before introduction, although the reduction was significant only for public events ban (R ratio 0·76, 95% CI 0·58-1·00); for all other NPIs, the upper bound of the 95% CI was above 1. An increasing trend over time in the R ratio was found following the relaxation of school closure, bans on public events, bans on public gatherings of more than ten people, requirements to stay at home, and internal movement limits; the increase in R ranged from 11% to 25% on day 28 following the relaxation compared with the last day before relaxation, although the increase was significant only for school reopening (R ratio 1·24, 95% CI 1·00-1·52) and lifting bans on public gatherings of more than ten people (1·25, 1·03-1·51); for all other NPIs, the lower bound of the 95% CI was below 1. It took a median of 8 days (IQR 6-9) following the introduction of an NPI to observe 60% of the maximum reduction in R and even longer (17 days [14-20]) following relaxation to observe 60% of the maximum increase in R. In response to a possible resurgence of COVID-19, a control strategy of banning public events and public gatherings of more than ten people was estimated to reduce R, with an R ratio of 0·71 (95% CI 0·55-0·93) on day 28, decreasing to 0·62 (0·47-0·82) on day 28 if measures to close workplaces were added, 0·58 (0·41-0·81) if measures to close workplaces and internal movement restrictions were added, and 0·48 (0·32-0·71) if measures to close workplaces, internal movement restrictions, and requirements to stay at home were added. INTERPRETATION: Individual NPIs, including school closure, workplace closure, public events ban, ban on gatherings of more than ten people, requirements to stay at home, and internal movement limits, are associated with reduced transmission of SARS-CoV-2, but the effect of introducing and lifting these NPIs is delayed by 1-3 weeks, with this delay being longer when lifting NPIs. These findings provide additional evidence that can inform policy-maker decisions on the timing of introducing and lifting different NPIs, although R should be interpreted in the context of its known limitations. FUNDING: Wellcome Trust Institutional Strategic Support Fund and Data-Driven Innovation initiative.