Coronavirus disease (COVID-19)

During the COVID-19 pandemic, public perceptions and behaviours have had to adapt rapidly to new risk scenarios and radical behavioural restrictions.

To identify major drivers of acceptance of protective behaviours during the 4-week transition from virtually no COVID-19 cases to the nationwide lockdown in Germany (3–25 March 2020).

A serial cross-sectional online survey was administered weekly to ca 1,000 unique individuals for four data collection rounds in March 2020 using non-probability quota samples, representative of the German adult population between 18 and 74 years in terms of age × sex and federal state (n = 3,910). Acceptance of restrictions was regressed on sociodemographic variables, time and psychological variables, e.g. trust, risk perceptions, self-efficacy. Extraction of homogenous clusters was based on knowledge and behaviour.

Acceptance of restrictive policies increased with participants’ age and employment in the healthcare sector; cognitive and particularly affective risk perceptions were further significant predictors. Acceptance increased over time, as trust in institutions became more relevant and trust in media became less relevant. The cluster analysis further indicated that having a higher education increased the gap between knowledge and behaviour. Trust in institutions was related to conversion of knowledge into action.

Identifying relevant principles that increase acceptance will remain crucial to the development of strategies that help adjust behaviour to control the pandemic, possibly for years to come. Based on our findings, we provide operational recommendations for health authorities regarding data collection, health communication and outreach.

The occupational risk of COVID-19 may be different in the first versus second epidemic wave.

To study whether employees in occupations that typically entail close contact with others were at higher risk of SARS-CoV-2 infection and COVID-19-related hospitalisation during the first and second epidemic wave before and after 18 July 2020, in Norway.

We included individuals in occupations working with patients, children, students, or customers using Standard Classification of Occupations (ISCO-08) codes. We compared residents (3,559,694 on 1 January 2020) in such occupations aged 20–70 years (mean: 44.1; standard deviation: 14.3 years; 51% men) to age-matched individuals in other professions using logistic regression adjusted for age, sex, birth country and marital status.

Nurses, physicians, dentists and physiotherapists had 2–3.5 times the odds of COVID-19 during the first wave when compared with others of working age. In the second wave, bartenders, waiters, food counter attendants, transport conductors, travel stewards, childcare workers, preschool and primary school teachers had ca 1.25–2 times the odds of infection. Bus, tram and taxi drivers had an increased odds of infection in both waves (odds ratio: 1.2–2.1). Occupation was of limited relevance for the odds of severe infection, here studied as hospitalisation with the disease.

Our findings from the entire Norwegian population may be of relevance to national and regional authorities in handling the epidemic. Also, we provide a knowledge foundation for more targeted future studies of lockdowns and disease control measures.

To mitigate SARS-CoV-2 transmission risks from international air travellers, many countries implemented a combination of up to 14 days of self-quarantine upon arrival plus PCR testing in the early stages of the COVID-19 pandemic in 2020.

To assess the effectiveness of quarantine and testing of international travellers to reduce risk of onward SARS-CoV-2 transmission into a destination country in the pre-COVID-19 vaccination era.

We used a simulation model of air travellers arriving in the United Kingdom from the European Union or the United States, incorporating timing of infection stages while varying quarantine duration and timing and number of PCR tests.

Quarantine upon arrival with a PCR test on day 7 plus a 1-day delay for results can reduce the number of infectious arriving travellers released into the community by a median 94% (95% uncertainty interval (UI): 89–98) compared with a no quarantine/no test scenario. This reduction is similar to that achieved by a 14-day quarantine period (median > 99%; 95% UI: 98–100). Even shorter quarantine periods can prevent a substantial amount of transmission; all strategies in which travellers spend at least 5 days (mean incubation period) in quarantine and have at least one negative test before release are highly effective (median reduction 89%; 95% UI: 83–95)).

The effect of different screening strategies impacts asymptomatic and symptomatic individuals differently. The choice of an optimal quarantine and testing strategy for unvaccinated air travellers may vary based on the number of possible imported infections relative to domestic incidence.

School attendance during the COVID-19 pandemic is intensely debated.

In November 2020, we assessed SARS-CoV-2 infections and seroreactivity in 24 randomly selected school classes and connected households in Berlin, Germany.

We collected oro-nasopharyngeal swabs and blood samples, examining SARS-CoV-2 infection and IgG antibodies by RT-PCR and ELISA. Household members self-swabbed. We assessed individual and institutional prevention measures. Classes with SARS-CoV-2 infection and connected households were retested after 1 week.

We examined 1,119 participants, including 177 primary and 175 secondary school students, 142 staff and 625 household members. SARS-CoV-2 infection occurred in eight classes, affecting each 1–2 individuals. Infection prevalence was 2.7% (95% confidence interval (CI): 1.2–5.0; 9/338), 1.4% (95% CI: 0.2–5.1; 2/140), and 2.3% (95% CI: 1.3–3.8; 14/611) among students, staff and household members. Six of nine infected students were asymptomatic at testing. We detected IgG antibodies in 2.0% (95%CI: 0.8–4.1; 7/347), 1.4% (95% CI: 0.2–5.0; 2/141) and 1.4% (95% CI: 0.6–2.7; 8/576). Prevalence increased with inconsistent facemask-use in school, walking to school, and case-contacts outside school. For three of nine households with infection(s), origin in school seemed possible. After 1 week, no school-related secondary infections appeared in affected classes; the attack rate in connected households was 1.1%.

School attendance under rigorously implemented preventive measures seems reasonable. Balancing risks and benefits of school closures need to consider possible spill-over infection into households. Deeper insight is required into the infection risks due to being a schoolchild vs attending school.

Determinants of hospitalisation, intensive care unit (ICU) admission and death are still unclear for COVID-19. Few studies have adjusted for confounding for different clinical outcomes including all reported cases within a country.

We used routine surveillance data from Portugal to identify risk factors for severe COVID-19 outcomes, and to support risk stratification, public health interventions, and planning of healthcare resources.

We conducted a retrospective cohort study including 20,293 laboratory-confirmed cases of COVID-19 reported between 1 March and 28 April 2020 through the national epidemiological surveillance system. We calculated absolute risk, relative risk (RR) and adjusted relative risk (aRR) to identify demographic and clinical factors associated with hospitalisation, ICU admission and death using Poisson regressions.

Increasing age (≥ 60 years) was the major determinant for all outcomes. Age ≥ 90 years was the strongest determinant of hospital admission (aRR: 6.1), and 70–79 years for ICU (aRR: 10.4). Comorbidities of cardiovascular, immunodeficiency, kidney and lung disease (aRR: 4.3, 2.8, 2.4, 2.0, respectively) had stronger associations with ICU admission, while for death they were kidney, cardiovascular and chronic neurological disease (aRR: 2.9, 2.6, 2.0).

Older age was the strongest risk factor for all severe outcomes. These findings from the early stages of the COVID-19 pandemic support risk-stratified public health measures that should prioritise protecting older people. Epidemiological scenarios and clinical guidelines should consider this, even though under-ascertainment should also be considered.