Coronavirus disease (COVID-19)

To control epidemic waves, it is important to know the susceptibility to SARS-CoV-2 and its evolution over time in relation to the control measures taken.

To assess the evolving SARS-CoV-2 seroprevalence and seroincidence related to the first national lockdown in Belgium, we performed a nationwide seroprevalence study, stratified by age, sex and region using 3,000–4,000 residual samples during seven periods between 30 March and 17 October 2020.

We analysed residual sera from ambulatory patients for IgG antibodies against the SARS-CoV-2 S1 protein with a semiquantitative commercial ELISA. Weighted seroprevalence (overall and by age category and sex) and seroincidence during seven consecutive periods were estimated for the Belgian population while accommodating test-specific sensitivity and specificity.

The weighted overall seroprevalence initially increased from 1.8% (95% credible interval (CrI): 1.0–2.6) to 5.3% (95% CrI: 4.2–6.4), implying a seroincidence of 3.4% (95% CrI: 2.4–4.6) between the first and second collection period over a period of 3 weeks during lockdown (start lockdown mid-March 2020). Thereafter, seroprevalence stabilised, however, significant decreases were observed when comparing the third with the fifth, sixth and seventh period, resulting in negative seroincidence estimates after lockdown was lifted. We estimated for the last collection period mid-October 2020 a weighted overall seroprevalence of 4.2% (95% CrI: 3.1–5.2).

During lockdown, an initially small but increasing fraction of the Belgian population showed serologically detectable signs of exposure to SARS-CoV-2, which did not further increase when confinement measures eased and full lockdown was lifted.

COVID-19 mortality, excess mortality, deaths per million population (DPM), infection fatality ratio (IFR) and case fatality ratio (CFR) are reported and compared for many countries globally. These measures may appear objective, however, they should be interpreted with caution.

We examined reported COVID-19-related mortality in Belgium from 9 March 2020 to 28 June 2020, placing it against the background of excess mortality and compared the DPM and IFR between countries and within subgroups.

The relation between COVID-19-related mortality and excess mortality was evaluated by comparing COVID-19 mortality and the difference between observed and weekly average predictions of all-cause mortality. DPM were evaluated using demographic data of the Belgian population. The number of infections was estimated by a stochastic compartmental model. The IFR was estimated using a delay distribution between infection and death.

In the study period, 9,621 COVID-19-related deaths were reported, which is close to the excess mortality estimated using weekly averages (8,985 deaths). This translates to 837 DPM and an IFR of 1.5% in the general population. Both DPM and IFR increase with age and are substantially larger in the nursing home population.

During the first pandemic wave, Belgium had no discrepancy between COVID-19-related mortality and excess mortality. In light of this close agreement, it is useful to consider the DPM and IFR, which are both age, sex, and nursing home population-dependent. Comparison of COVID-19 mortality between countries should rather be based on excess mortality than on COVID-19-related mortality.

Universal SARS-CoV-2 testing at hospital admission has been proposed to prevent nosocomial transmission.

To investigate SARS-CoV-2 positivity in patients tested with low clinical COVID-19 suspicion at hospital admission.

We characterised a retrospective cohort of patients admitted to Karolinska University Hospital tested for SARS-CoV-2 by PCR from March to September 2020, supplemented with an in-depth chart review (16 March–12 April). We compared positivity rates in patients with and without clinical COVID-19 suspicion with Spearman’s rank correlation coefficient. We used multivariable logistic regression to identify factors associated with test positivity.

From March to September 2020, 66.9% (24,245/36,249) admitted patient episodes were tested; of those, 61.2% (14,830/24,245) showed no clinical COVID-19 suspicion, and the positivity rate was 3.2% (469/14,830). There was a strong correlation of SARS-CoV-2 positivity in patients with low vs high COVID-19 suspicion (rho = 0.92; p < 0.001).

From 16 March to 12 April, the positivity rate was 3.9% (58/1,482) in individuals with low COVID-19 suspicion, and 3.1% (35/1,114) in asymptomatic patients. Rates were higher in women (5.0%; 45/893) vs men (2.0%; 12/589; p = 0.003), but not significantly different if pregnant women were excluded (3.7% (21/566) vs 2.2% (12/589); p = 0.09). Factors associated with SARS-CoV-2 positivity were testing of pregnant women before delivery (odds ratio (OR): 2.6; 95% confidence interval (CI): 1.3–5.4) and isolated symptoms in adults (OR: 3.3; 95% CI: 1.8–6.3).

This study shows a relatively high SARS-CoV-2 positivity rate in patients with low COVID-19 suspicion upon hospital admission. Universal SARS-CoV-2 testing of pregnant women before delivery should be considered.

The COVID-19 pandemic has led to an unprecedented daily use of RT-PCR tests. These tests are interpreted qualitatively for diagnosis, and the relevance of the test result intensity, i.e. the number of quantification cycles (Cq), is debated because of strong potential biases.

We explored the possibility to use Cq values from SARS-CoV-2 screening tests to better understand the spread of an epidemic and to better understand the biology of the infection.

We used linear regression models to analyse a large database of 793,479 Cq values from tests performed on more than 2 million samples between 21 January and 30 November 2020, i.e. the first two pandemic waves. We performed time series analysis using autoregressive integrated moving average (ARIMA) models to estimate whether Cq data information improves short-term predictions of epidemiological dynamics.

Although we found that the Cq values varied depending on the testing laboratory or the assay used, we detected strong significant trends associated with patient age, number of days after symptoms onset or the state of the epidemic (the temporal reproduction number) at the time of the test. Furthermore, knowing the quartiles of the Cq distribution greatly reduced the error in predicting the temporal reproduction number of the COVID-19 epidemic.

Our results suggest that Cq values of screening tests performed in the general population generate testable hypotheses and help improve short-term predictions for epidemic surveillance.

The COVID-19 pandemic is one of the most serious global public health threats of recent times. Understanding SARS-CoV-2 transmission is key for outbreak response and to take action against the spread of disease. Transmission within the household is a concern, especially because infection control is difficult to apply within this setting.

The objective of this observational study was to investigate SARS-CoV-2 transmission in Danish households during the early stages of the COVID-19 pandemic.

We used comprehensive administrative register data from Denmark, comprising the full population and all COVID-19 tests from 27 February 2020 to 1 August 2020, to estimate household transmission risk and attack rate.

We found that the day after receiving a positive test result within the household, 35% (788/2,226) of potential secondary cases were tested and 13% (98/779) of these were positive. In 6,782 households, we found that 82% (1,827/2,226) of potential secondary cases were tested within 14 days and 17% (371/2,226) tested positive as secondary cases, implying an attack rate of 17%. We found an approximate linear increasing relationship between age and attack rate. We investigated the transmission risk from primary cases by age, and found an increasing risk with age of primary cases for adults (aged ≥ 15 years), while the risk seems to decrease with age for children (aged < 15 years).

Although there is an increasing attack rate and transmission risk of SARS-CoV-2 with age, children are also able to transmit SARS-CoV-2 within the household.

Several SARS-CoV-2 variants of concern (VOC) have emerged through 2020 and 2021. There is need for tools to estimate the relative transmissibility of emerging variants of SARS-CoV-2 with respect to circulating strains.

We aimed to assess the prevalence of co-circulating VOC in Italy and estimate their relative transmissibility.

We conducted two genomic surveillance surveys on 18 February and 18 March 2021 across the whole Italian territory covering 3,243 clinical samples and developed a mathematical model that describes the dynamics of co-circulating strains.

The Alpha variant was already dominant on 18 February in a majority of regions/autonomous provinces (national prevalence: 54%) and almost completely replaced historical lineages by 18 March (dominant across Italy, national prevalence: 86%). We found a substantial proportion of the Gamma variant on 18 February, almost exclusively in central Italy (prevalence: 19%), which remained similar on 18 March. Nationally, the mean relative transmissibility of Alpha ranged at 1.55–1.57 times the level of historical lineages (95% CrI: 1.45–1.66). The relative transmissibility of Gamma varied according to the assumed degree of cross-protection from infection with other lineages and ranged from 1.12 (95% CrI: 1.03–1.23) with complete immune evasion to 1.39 (95% CrI: 1.26–1.56) for complete cross-protection.

We assessed the relative advantage of competing viral strains, using a mathematical model assuming different degrees of cross-protection. We found substantial co-circulation of Alpha and Gamma in Italy. Gamma was not able to outcompete Alpha, probably because of its lower transmissibility.

Since the onset of the COVID-19 pandemic, the disease has frequently been compared with seasonal influenza, but this comparison is based on little empirical data.

This study compares in-hospital outcomes for patients with community-acquired COVID-19 and patients with community-acquired influenza in Switzerland.

This retrospective multi-centre cohort study includes patients > 18 years admitted for COVID-19 or influenza A/B infection determined by RT-PCR. Primary and secondary outcomes were in-hospital mortality and intensive care unit (ICU) admission for patients with COVID-19 or influenza. We used Cox regression (cause-specific and Fine-Gray subdistribution hazard models) to account for time-dependency and competing events with inverse probability weighting to adjust for confounders.

In 2020, 2,843 patients with COVID-19 from 14 centres were included. Between 2018 and 2020, 1,381 patients with influenza from seven centres were included; 1,722 (61%) of the patients with COVID-19 and 666 (48%) of the patients with influenza were male (p < 0.001). The patients with COVID-19 were younger (median 67 years; interquartile range (IQR): 54–78) than the patients with influenza (median 74 years; IQR: 61–84) (p < 0.001). A larger percentage of patients with COVID-19 (12.8%) than patients with influenza (4.4%) died in hospital (p < 0.001). The final adjusted subdistribution hazard ratio for mortality was 3.01 (95% CI: 2.22–4.09; p < 0.001) for COVID-19 compared with influenza and 2.44 (95% CI: 2.00–3.00, p < 0.001) for ICU admission.

Community-acquired COVID-19 was associated with worse outcomes compared with community-acquired influenza, as the hazards of ICU admission and in-hospital death were about two-fold to three-fold higher.