Are People Optimistically Biased about the Risk of COVID-19 Infection? Lessons from the First Wave of the Pandemic in Europe

Unrealistic optimism, the underestimation of one’s risk of experiencing harm, has been investigated extensively to understand better and predict behavioural responses to health threats. Prior to the COVID-19 pandemic, a relative dearth of research existed in this domain regarding epidemics, which is surprising considering that this optimistic bias has been associated with a lack of engagement in protective behaviours critical in fighting twenty-first-century, emergent, infectious diseases. The current study addresses this gap in the literature by investigating whether people demonstrated optimism bias during the first wave of the COVID-19 pandemic in Europe, how this changed over time, and whether unrealistic optimism was negatively associated with protective measures. Taking advantage of a pre-existing international participative influenza surveillance network (n = 12,378), absolute and comparative unrealistic optimism were measured at three epidemic stages (pre-, early, peak), and across four countries—France, Italy, Switzerland and the United Kingdom. Despite differences in culture and health response, similar patterns were observed across all four countries. The prevalence of unrealistic optimism appears to be influenced by the particular epidemic context. Paradoxically, whereas absolute unrealistic optimism decreased over time, comparative unrealistic optimism increased, suggesting that whilst people became increasingly accurate in assessing their personal risk, they nonetheless overestimated that for others. Comparative unrealistic optimism was negatively associated with the adoption of protective behaviours, which is worrying, given that these preventive measures are critical in tackling the spread and health burden of COVID-19. It is hoped these findings will inspire further research into sociocognitive mechanisms involved in risk appraisal.

Influenza A and D Viruses in Non-Human Mammalian Hosts in Africa: A Systematic Review and Meta-Analysis

We conducted a systematic review and meta-analysis to investigate the prevalence and current knowledge of influenza A virus (IAV) and influenza D virus (IDV) in non-human mammalian hosts in Africa. PubMed, Google Scholar, Wiley Online Library and World Organisation for Animal Health (OIE-WAHIS) were searched for studies on IAV and IDV from 2000 to 2020. Pooled prevalence and seroprevalences were estimated using the quality effects meta-analysis model. The estimated pooled prevalence and seroprevalence of IAV in pigs in Africa was 1.6% (95% CI: 0–5%) and 14.9% (95% CI: 5–28%), respectively. The seroprevalence of IDV was 87.2% (95% CI: 24–100%) in camels, 9.3% (95% CI: 0–24%) in cattle, 2.2% (95% CI: 0–4%) in small ruminants and 0.0% (95% CI: 0–2%) in pigs. In pigs, H1N1 and H1N1pdm09 IAVs were commonly detected. Notably, the highly pathogenic H5N1 virus was also detected in pigs. Other subtypes detected serologically and/or virologically included H3N8 and H7N7 in equids, H1N1, and H3N8 and H5N1 in dogs and cats. Furthermore, various wildlife animals were exposed to different IAV subtypes. For prudent mitigation of influenza epizootics and possible human infections, influenza surveillance efforts in Africa should not neglect non-human mammalian hosts. The impact of IAV and IDV in non-human mammalian hosts in Africa deserves further investigation.

Respiratory Syncytial Virus: New Challenges for Molecular Epidemiology Surveillance and Vaccination Strategy in Patients with ILI/SARI

Several respiratory pathogens are responsible for influenza-like illness (ILI) and severe respiratory infections (SARI), among which human respiratory syncytial virus (hRSV) represents one of the most common aetiologies. We analysed the hRSV prevalence among subjects with ILI or SARI during the five influenza seasons before the emergence of SARS-CoV-2 epidemic in Sicily (Italy). Respiratory specimens from ILI outpatients and SARI inpatients were collected in the framework of the Italian Network for the Influenza Surveillance and molecularly tested for hRSV-A and hRSV-B. Overall, 8.1% of patients resulted positive for hRSV. Prevalence peaked in the age-groups <5 years old (range: 17.6–19.1%) and ≥50 years old (range: 4.8–5.1%). While the two subgroups co-circulated throughout the study period, hRSV-B was slightly predominant over hRSV-A, except for the season 2019–2020 when hRSV-A strongly prevailed (82.9%). In the community setting, the distribution of hRSV subgroups was balanced (47.8% vs. 49.7% for hRSV-A and hRSV-B, respectively), while most infections identified in the hospital setting were caused by hRSV-B (69.5%); also, this latter one was more represented among hRSV cases with underlying diseases, as well as among those who developed a respiratory complication. The molecular surveillance of hRSV infections may provide a valuable insight into the epidemiological features of ILI/SARI. Our findings add new evidence to the existing knowledge on viral aetiology of ILI and SARI in support of public health strategies and may help to define high-risk categories that could benefit from currently available and future vaccines.

A comparison of coronavirus disease 2019 and seasonal influenza surveillance in five European countries: France, Germany, Italy, Spain and the United Kingdom

Background: In response to the coronavirus disease (COVID-19) outbreak that unfolded across Europe in 2020, the World Health Organisation called for repurposing existing influenza surveillance systems to monitor COVID-19. This analysis aimed to compare descriptively the extent to which influenza surveillance systems were adapted and enhanced, and how COVID-19 surveillance could ultimately benefit or disrupt routine influenza surveillance. Methods: We used a previously developed framework in France, Germany, Italy, Spain and the United Kingdom to describe COVID-19 surveillance and its impact on influenza surveillance. The framework divides surveillance systems into 7 sub-systems and 20 comparable outcomes of interest, and uses 5 evaluation criteria based on WHO guidance. Information on influenza and COVID-19 surveillance systems were collected from publicly available resources shared by European and national public health agencies. Results: Overall, non-medically attended, virological, primary care and mortality surveillance were adapted in most countries to monitor COVID-19, whilst community, outbreak, and hospital surveillance were reinforced in all countries. Data granularity improved, with more detailed demographic and medical information recorded. A shift to systematic notification for cases and deaths enhanced both geographic and population representativeness whilst the sampling strategy benefited from the roll out of widespread molecular testing. Data communication was greatly enhanced, contributing to improved public awareness. Conclusions: Well-established influenza surveillance systems are a key component of pandemic preparedness and their upgrade allowed European countries to respond to the COVID-19 pandemic. However, uncertainties remain on how both influenza and COVID-19 surveillance can be jointly and durably implemented.

Front-Line Emergency Department Clinician Acceptability and Use of a Prototype Real-Time Cloud-Based Influenza Surveillance System

Objectives: To assess emergency department (ED) clinicians' perceptions of a novel real-time influenza surveillance system using a pre- and post-implementation structured survey.Methods: We created and implemented a laboratory-based real-time influenza surveillance system at two EDs at the beginning of the 2013-2014 influenza season. Patients with acute respiratory illness were tested for influenza using rapid PCR-based Cepheid Xpert Flu assay. Results were instantaneously uploaded to a cloud-based data aggregation system made available to clinicians via a web-based dashboard. Clinicians received bimonthly email updates summating year-to-date results. Clinicians were surveyed prior to, and after the influenza season, to assess their views regarding acceptability and utility of the surveillance system data which were shared via dashboard and email updates.Results: The pre-implementation survey revealed that the majority (82%) of the 151 ED clinicians responded that they “sporadically” or “don't,” actively seek influenza-related information during the season. However, most (75%) reported that they would find additional information regarding influenza prevalence useful. Following implementation, there was an overall increase in the frequency of clinician self-reporting increased access to surveillance information from 50 to 63%, with the majority (75%) indicating that the surveillance emails impacted their general awareness of influenza. Clinicians reported that the additional real-time surveillance data impacted their testing (65%) and treatment (51%) practices.Conclusions: The majority of ED clinicians found surveillance data useful and indicated the additional information impacted their clinical practice. Accurate and timely surveillance information, distributed in a provider-friendly format could impact ED clinician management of patients with suspected influenza.

Training the domestic ferret to discriminate odors associated with wildlife disease

Recent avian influenza infection outbreaks have resulted in global biosecurity and economic concerns. Mallards are asymptomatic for the disease and can potentially spread AI along migratory bird flyways. In a previous study, trained mice correctly discriminated the health status of individual ducks on the basis of fecal odors when feces from post-infection periods were paired with feces from pre-infection periods. Chemical analyses indicated that avian influenza infection was associated with a marked increase of acetoin (3-hydroxy-2-butanone) in feces. In the current study, domesticated male ferrets (Mustela putorius furo) were trained to display a specific conditioned response (i.e. active scratch alert) in response to a marked increase of acetoin in a presentation of an acetoin:1-octen-3-ol solution. Ferrets rapidly generalized this learned response to the odor of irradiated feces from avian influenza infected mallards. These results suggest that a trained mammalian biosensor could be employed in an avian influenza surveillance program.

1338. Before and After: The Impact of the COVID-19 Pandemic on Influenza-Like Illness Trends in PAIVED

Background The Pragmatic Assessment of Influenza Vaccine Effectiveness in the DoD (PAIVED) is a multicenter study assessing influenza vaccine effectiveness in active duty service members, retirees, and dependents. PAIVED recently completed its third year and offers a unique opportunity to examine influenza-like illness (ILI) trends prior to and during the COVID-19 pandemic in a prospective, well-defined cohort. Methods During the 2018-19, 2019-20, and 2020-21 influenza seasons, PAIVED enrolled DoD beneficiaries presenting for annual influenza vaccination. After collecting baseline demographic data, participants were randomized to receive egg-based, cell-based, or recombinant-derived influenza vaccine. Weekly throughout the influenza season of enrollment, participants were surveyed electronically for ILI, defined as (1) having cough or sore throat, plus (2) feeling feverish/having chills or having body aches/fatigue. Participants with ILI completed a daily symptom diary for seven days and submitted a nasal swab for pathogen detection. Results Over the three seasons, there were 10,656 PAIVED participants: 1514 (14.2%) in 2018-19, 5876 (55.1%) in 2019-20, and 3266 (30.6%) in 2020-21. The majority were male (68-73% per year) with a mean age of 34±14.8 years at enrollment. 2266 participants reported a total of 2673 unique ILIs. The highest percentage of participants with ILI was in 2019-20 (28.2%), versus 19.6% in 2018-19 and 9.6% in 2020-21. Figure 1 depicts the percent of individuals reporting ILI by week of the season for each of the PAIVED seasons. Notably, after March 21, 2020, the weekly incidence of participants reporting ILI never exceeded 1%. Figure 1. Percent of PAIVED participants reporting ILI by week of season. Conclusion The low incidence of reported ILI in PAIVED participants during the COVID-19 pandemic is consistent with national influenza surveillance reports of influenza and outpatient ILI activity, suggesting that mitigation measures taken to reduce transmission of SARS-CoV-2 reduced the spread of other respiratory viruses. Disclaimer Disclosures Ryan C. Maves, MD, EMD Serono (Advisor or Review Panel member)Heron Therapeutics (Advisor or Review Panel member) Jitu Modi, MD, GSK (Speaker’s Bureau)

Respiratory syncytial virus (RSV) in pediatric influenza-like illness (ILI) cases in Lombardy, Northern Italy, during seven consecutive winter seasons (from 2014-2015 to 2020-2021)

INTRODUCTION. Respiratory syncytial virus (RSV) is the major cause of lower respiratory tract illness in young children and can also cause influenza-like illness (ILI). Here we investigated the epidemiological features of RSV infection in pediatric ILI cases in Lombardy (a region in Northern Italy accounting nearly 10-million inhabitants) from 2014-2015 to 2020-2021 winter seasons. MATERIAL AND METHODS. Data for this study were retrieved and statistically analyzed from the database of virological influenza surveillance of the regional reference laboratory for Lombardy within the Italian influenza surveillance network (InfluNet). RESULTS. RSV accounting for nearly 19% of pediatric ILI with a risk of infection nearly 2-fold greater than that of individuals ≥15 years. The RSV positivity rate increased to 28% considering 0-5 years old children. Although in children ≤5 years the risk of infection from influenza viruses resulted nearly 2-fold higher than the risk of RSV infection, the age group 4-6 months and 7-12 months showed 5-fold greater risk of infection from RSV than from influenza. Children ≤5 years of age with presence of one or more comorbidities had a nearly 5-fold greater risk of getting RSV infection than otherwise healthy 0-5 years old children. DISCUSSION. The use of the ILI sentinel surveillance allowed us to identify groups at higher risk of RSV and influenza infection and to define the start, duration, timing and intensity of the RSV and influenza community circulation, determining thresholds based on historical data. This surveillance approach can be implemented to assess the nearly real-time RSV circulation and impact.