Are We Essential, or Sacrificial? The Effects of Felt Public Gratitude on Essential Worker Recovery Activities During COVID-19.

COVID-19 has been characterized by unprecedented levels of public gratitude to some, but not all, essential workers. In this research, we integrate insights from the stigmatized occupations and gratitude literature to build theory on the positive and negative relationships between such displays of public gratitude and essential workers' recovery activities. We argue that felt public gratitude positively relates to adaptive recovery activities (e.g., exercise) and negatively relates to maladaptive recovery activities (e.g., overdrinking). We further explain how felt public gratitude impacts (mal)adaptive recovery activities through (a) felt invisibility and (b) negative/positive affect. We find support for our predictions in a two-wave survey of 186 corrections officers (Study 1) and an experiment with 379 essential workers across a variety of industries (Study 2).

Cross-sectional survey of compliance behaviour, knowledge and attitudes among cases and close contacts during COVID-19 pandemic.

Objectives: A key public health intervention is self-isolation for cases and restriction of movement for contacts. This study aimed to identify predictors of compliance behaviour and describe knowledge and attitudes among cases and contacts identified by the national Contact Management Programme to inform the global public health response. Study design: Secondary data analysis of anonymised cross-sectional survey data on national sample of cases and close contacts. Methods: A sample of 1000 cases and 1000 contacts was calculated to estimate compliance within a margin of error of 3% with 95% confidence. A telephone survey administered by trained interviewers collected information on socio-demographics, compliance behaviours, knowledge, and attitudes to COVID-19 from cases and close contacts. Data analysis included chi-squared statistics and multivariable logistic regression. Results: Most cases and contacts complied with public health guidance with similar characteristics in those who did and did not comply. Reasons for non-compliance included exercise, medical appointment, shopping, and work. Cases and contacts reported high levels of understanding about symptoms of COVID-19 and satisfaction with available information. Conclusion: Achieving high compliance with public health guidance is feasible and requires political leadership, policy changes and practical solutions.

Efficacy of Digital Health Tools for a Pediatric Patient Registry: Semistructured Interviews and Interface Usability Testing With Parents and Clinicians.

BACKGROUND: Acute respiratory infection (ARI) in childhood is common, but more knowledge on the burden and natural history of ARI in the community is required. A better understanding of ARI risk factors, treatment, and outcomes will help support parents to manage their sick child at home. Digital health tools are becoming more widely adopted in clinical care and research and may assist in understanding and managing common pediatric diseases, including ARI, in hospitals and in the community. We integrated 2 digital tools-a web-based discharge communication system and the REDCap (Research Electronic Data Capture) platform-into the Pragmatic Adaptive Trial for Acute Respiratory Infection in Children to enhance parent and physician engagement around ARI discharge communication and our patient registry. OBJECTIVE: The objective of this study is to determine the efficacy and usability of digital tools integrated into a pediatric patient registry for ARI. METHODS: Semistructured interviews and software interface usability testing were conducted with 11 parents and 8 emergency department physicians working at a tertiary pediatric hospital and research center in Perth, Western Australia, in 2019. Questions focused on experiences of discharge communication and clinical trial engagement. Responses were analyzed using the qualitative Framework Method. Participants were directly observed using digital interfaces as they attempted predetermined tasks that were then classified as success, failure, software failure, or not observed. Participants rated the interfaces using the System Usability Scale (SUS). RESULTS: Most parents (9/11, 82%) indicated that they usually received verbal discharge advice, with some (5/11, 45%) recalling receiving preprinted resources from their physician. Most (8/11, 73%) would also like to receive discharge advice electronically. Most of the physicians (7/8, 88%) described their usual practice as verbal discharge instructions, with some (3/8, 38%) reporting time pressures associated with providing discharge instructions. The digital technology option was preferred for engaging in research by most parents (8/11, 73%). For the discharge communication digital tool, parents gave a mean SUS score of 94/100 (SD 4.3; A grade) for the mobile interface and physicians gave a mean usability score of 93/100 (SD 4.7; A grade) for the desktop interface. For the research data management tool (REDCap), parents gave a mean usability score of 78/100 (SD 11.0; C grade) for the mobile interface. CONCLUSIONS: Semistructured interviews allowed us to better understand parent and physician experiences of discharge communication and clinical research engagement. Software interface usability testing methods and use of the SUS helped us gauge the efficacy of our digital tools with both parent and physician users. This study demonstrates the feasibility of combining qualitative research methods with software industry interface usability testing methods to help determine the efficacy of digital tools in a pediatric clinical research setting.

Transmission of SARS-CoV-2 arising from international flights arriving in Ireland in December 2020: a descriptive analysis using national surveillance data.

OBJECTIVES: There is limited evidence on the risk of in-flight transmission of SARS-CoV-2. This study estimated the extent of in-flight SARS-CoV-2 transmission on international flights arriving in Ireland during December 2020. STUDY DESIGN: This was a cross-sectional analysis. METHODS: National surveillance data identified all notified cases of COVID-19 who were infectious while travelling on international flights to Ireland during December 2020. Close contacts of cases were tested for SARS-CoV-2, and the results were collated to estimate the pooled secondary attack rate across all flights. Laboratory and epidemiological data were obtained from the Health Service Executive Covid Care Tracker, a national database of COVID-19 cases in Ireland. RESULTS: A total of 165 infectious cases of COVID-19 were identified on 134 incoming flights; 40.0% were symptomatic on board. There were 2099 flight close contacts identified, of whom 40.9% had results of a SARS-CoV-2 polymerase chain reaction test within 14 days of arrival. The pooled secondary attack rate for these contacts was 7.0% and was higher among those on flights of ≥5-hour duration (P = 0.008). More than half (59.1%) of close contacts had no SARS-CoV-2 test result recorded; the reasons included incorrect or absent contact details (26.5%) and no response when contacted (17.8%). CONCLUSIONS: In this national study investigating transmission of SARS-CoV-2 from international flights arriving into Ireland, the pooled secondary attack rate was 7.0%. International travel is likely to have contributed to the third wave of SARS-CoV-2 infections in Ireland in early 2021. Application of non-pharmaceutical interventions remains central to mitigating the risk of in-flight transmission.

Numbers of close contacts of individuals infected with SARS-CoV-2 and their association with government intervention strategies.

BACKGROUND: Contact tracing is conducted with the primary purpose of interrupting transmission from individuals who are likely to be infectious to others. Secondary analyses of data on the numbers of close contacts of confirmed cases could also: provide an early signal of increases in contact patterns that might precede larger than expected case numbers; evaluate the impact of government interventions on the number of contacts of confirmed cases; or provide data information on contact rates between age cohorts for the purpose of epidemiological modelling. We analysed data from 140,204 close contacts of 39,861 cases in Ireland from 1st May to 1st December 2020. RESULTS: Negative binomial regression models highlighted greater numbers of contacts within specific population demographics, after correcting for temporal associations. Separate segmented regression models of the number of cases over time and the average number of contacts per case indicated that a breakpoint indicating a rapid decrease in the number of contacts per case in October 2020 preceded a breakpoint indicating a reduction in the number of cases by 11 days. CONCLUSIONS: We found that the number of contacts per infected case was overdispersed, the mean varied considerable over time and was temporally associated with government interventions. Analysis of the reported number of contacts per individual in contact tracing data may be a useful early indicator of changes in behaviour in response to, or indeed despite, government restrictions. This study provides useful information for triangulating assumptions regarding the contact mixing rates between different age cohorts for epidemiological modelling.

Estimation of the serial interval and proportion of pre-symptomatic transmission events of COVID- 19 in Ireland using contact tracing data.

BACKGROUND: The serial interval is the period of time between the onset of symptoms in an infector and an infectee and is an important parameter which can impact on the estimation of the reproduction number. Whilst several parameters influencing infection transmission are expected to be consistent across populations, the serial interval can vary across and within populations over time. Therefore, local estimates are preferable for use in epidemiological models developed at a regional level. We used data collected as part of the national contact tracing process in Ireland to estimate the serial interval of SARS-CoV-2 infection in the Irish population, and to estimate the proportion of transmission events that occurred prior to the onset of symptoms. RESULTS: After data cleaning, the final dataset consisted of 471 infected close contacts from 471 primary cases. The median serial interval was 4 days, mean serial interval was 4.0 (95% confidence intervals 3.7, 4.3) days, whilst the 25th and 75th percentiles were 2 and 6 days respectively. We found that intervals were lower when the primary or secondary case were in the older age cohort (greater than 64 years). Simulating from an incubation period distribution from international literature, we estimated that 67% of transmission events had greater than 50% probability of occurring prior to the onset of symptoms in the infector. CONCLUSIONS: Whilst our analysis was based on a large sample size, data were collected for the primary purpose of interrupting transmission chains. Similar to other studies estimating the serial interval, our analysis is restricted to transmission pairs where the infector is known with some degree of certainty. Such pairs may represent more intense contacts with infected individuals than might occur in the overall population. It is therefore possible that our analysis is biased towards shorter serial intervals than the overall population.

Epidemiology of COVID-19 and public health restrictions during the first wave of the pandemic in Ireland in 2020.

BACKGROUND: We describe the epidemiological trends and report and review the public health restrictions implemented during the first wave of the COVID-19 pandemic in Ireland. METHODS: The study reviewed confirmed cases of COVID-19 notified from 1 March to 18 July 2020. Data were obtained from the national COVID-19 Data Hub, the National Health Protection Surveillance Centre, the National Contact Management Programme and the European Centre for Disease Prevention and Control. RESULTS: A total of 25 617 cases were notified during the study period. Weekly cases and deaths peaked in mid-April 2020 at 5701 and 316, respectively. Mean number of close contacts per case was lowest at 0.7 in April, rising to 6.6 by July. Outbreak settings shifted from travel and workplace in March, to healthcare in April. Restrictions implemented on 12 March extended to full lockdown on 27 March. Phased relaxation of restrictions commenced 18 May. Effective suppression of community transmission of COVID-19 was achieved by June 2020. CONCLUSION: Lockdown is a crude population-level restriction effective in controlling COVID-19. Phased relaxation of restrictions in Ireland, however, led to an immediate increase in mean number of contacts per case, which facilitates viral transmission unless individual-level restrictions are adhered to. This demonstrates a limitation of lockdown as a long-term mechanism of pandemic control.