Eurosurveillance - Volume 27, Issue 6, 10 February 2022

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.

SARS-CoV-2, the virus that causes COVID-19, has spread rapidly worldwide. In January 2020, a surveillance system was implemented in France for early detection of cases and their contacts to help limit secondary transmissions.

To use contact-tracing data collected during the initial phase of the COVID-19 pandemic to better characterise SARS-CoV-2 transmission.

We analysed data collected during contact tracing and retrospective epidemiological investigations in France from 24 January to 30 March 2020. We assessed the secondary clinical attack rate and characterised the risk of a contact becoming a case. We described chains of transmission and estimated key parameters of spread.

During the study period, 6,082 contacts of 735 confirmed cases were traced. The overall secondary clinical attack rate was 4.1% (95% confidence interval (CI): 3.6–4.6), increasing with age of index case and contact. Compared with co-workers/friends, family contacts were at higher risk of becoming cases (adjusted odds ratio (AOR): 2.1, 95% CI: 1.4–3.0) and nosocomial contacts were at lower risk (AOR: 0.3, 95% CI: 0.1–0.7). Of 328 infector/infectee pairs, 49% were family members. The distribution of secondary cases was highly over-dispersed: 80% of secondary cases were caused by 10% of cases. The mean serial interval was 5.1 days (interquartile range (IQR): 2–8 days) in contact tracing pairs, where late transmission events may be censored, and 6.8 (3–8) days in pairs investigated retrospectively.

This study increases knowledge of SARS-CoV-2 transmission, including the importance of superspreading events during the onset of the pandemic.

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.