Eurosurveillance - Volume 26, Issue 43, 28 October 2021

Up-to-date seroprevalence estimates are critical to describe the SARS-CoV-2 immune landscape and to guide public health decisions.

We estimate seroprevalence of anti-SARS-CoV-2 antibodies 15 months into the COVID-19 pandemic and 6 months into the vaccination campaign.

We conducted a population-based cross-sectional serosurvey between 1 June and 7 July 2021, recruiting participants from age- and sex-stratified random samples of the general population. We tested participants for anti-SARS-CoV-2 antibodies targeting the spike (S) or nucleocapsid (N) proteins using the Roche Elecsys immunoassays. We estimated the anti-SARS-CoV-2 antibodies seroprevalence following vaccination and/or infection (anti-S antibodies), or infection only (anti-N antibodies).

Among 3,355 individuals (54.1% women; 20.8% aged < 18 years and 13.4% aged ≥ 65 years), 2,161 (64.4%) had anti-S antibodies and 906 (27.0%) had anti-N antibodies. The total seroprevalence was 66.1% (95% credible interval (CrI): 64.1–68.0). We estimated that 29.9% (95% Crl: 28.0–31.9) of the population developed antibodies after infection; the rest having developed antibodies via vaccination. Seroprevalence estimates differed markedly across age groups, being lowest among children aged 0–5 years (20.8%; 95% Crl: 15.5–26.7) and highest among older adults aged ≥ 75 years (93.1%; 95% Crl: 89.6–96.0). Seroprevalence of antibodies developed via infection and/or vaccination was higher among participants with higher educational level.

Most of the population has developed anti-SARS-CoV-2 antibodies, despite most teenagers and children remaining vulnerable to infection. As the SARS-CoV-2 Delta variant spreads and vaccination rates stagnate, efforts are needed to address vaccine hesitancy, particularly among younger individuals and to minimise spread among children.

Detailed information on symptom duration and temporal course of patients with mild COVID-19 was scarce at the beginning of the COVID-19 pandemic.

We aimed to determine the longitudinal course of clinical symptoms in non-hospitalised COVID-19 patients in Berlin, Germany.

Between March and May 2020, 102 confirmed COVID-19 cases in home isolation notified in Berlin, Germany, were sampled using total population sampling. Data on 25 symptoms were collected during telephone consultations (a maximum of four consultations) with each patient. We collected information on prevalence and duration of symptoms for each day of the first 2 weeks after symptom onset and for day 30 and 60 after symptom onset.

Median age was 35 years (range 18–74), 57% (58/102) were female, and 37% (38/102) reported having comorbidities. During the first 2 weeks, most common symptoms were malaise (94%, 92/98), headache (71%, 70/98), and rhinitis (69%, 68/98). Malaise was present for a median of 11 days (IQR 7–14 days) with 35% (34/98) of cases still reporting malaise on day 14. Headache and muscle pain mostly occurred during the first week, whereas dysosmia and dysgeusia mostly occurred during the second week. Symptoms persisted in 41% (39/95) and 20% (18/88) of patients on day 30 and 60, respectively.

Our study shows that a significant proportion of non-hospitalised COVID-19 cases endured symptoms for at least 2 months. Further research is needed to assess the frequency of long-term adverse health effects in non-hospitalised COVID-19 patients.

In the SARS-CoV-2 pandemic, viral genomes are available at unprecedented speed, but spatio-temporal bias in genome sequence sampling precludes phylogeographical inference without additional contextual data.

We applied genomic epidemiology to trace SARS-CoV-2 spread on an international, national and local level, to illustrate how transmission chains can be resolved to the level of a single event and single person using integrated sequence data and spatio-temporal metadata.

We investigated 289 COVID-19 cases at a university hospital in Munich, Germany, between 29 February and 27 May 2020. Using the ARTIC protocol, we obtained near full-length viral genomes from 174 SARS-CoV-2-positive respiratory samples. Phylogenetic analyses using the Auspice software were employed in combination with anamnestic reporting of travel history, interpersonal interactions and perceived high-risk exposures among patients and healthcare workers to characterise cluster outbreaks and establish likely scenarios and timelines of transmission.

We identified multiple independent introductions in the Munich Metropolitan Region during the first weeks of the first pandemic wave, mainly by travellers returning from popular skiing areas in the Alps. In these early weeks, the rate of presumable hospital-acquired infections among patients and in particular healthcare workers was high (9.6% and 54%, respectively) and we illustrated how transmission chains can be dissected at high resolution combining virus sequences and spatio-temporal networks of human interactions.

Early spread of SARS-CoV-2 in Europe was catalysed by superspreading events and regional hotspots during the winter holiday season. Genomic epidemiology can be employed to trace viral spread and inform effective containment strategies.