Eurosurveillance - Volume 25, Issue 17, 30 April 2020

Estimating key infectious disease parameters from the coronavirus disease (COVID-19) outbreak is essential for modelling studies and guiding intervention strategies.

We estimate the generation interval, serial interval, proportion of pre-symptomatic transmission and effective reproduction number of COVID-19. We illustrate that reproduction numbers calculated based on serial interval estimates can be biased.

We used outbreak data from clusters in Singapore and Tianjin, China to estimate the generation interval from symptom onset data while acknowledging uncertainty about the incubation period distribution and the underlying transmission network. From those estimates, we obtained the serial interval, proportions of pre-symptomatic transmission and reproduction numbers.

The mean generation interval was 5.20 days (95% credible interval (CrI): 3.78–6.78) for Singapore and 3.95 days (95% CrI: 3.01–4.91) for Tianjin. The proportion of pre-symptomatic transmission was 48% (95% CrI: 32–67) for Singapore and 62% (95% CrI: 50–76) for Tianjin. Reproduction number estimates based on the generation interval distribution were slightly higher than those based on the serial interval distribution. Sensitivity analyses showed that estimating these quantities from outbreak data requires detailed contact tracing information.

High estimates of the proportion of pre-symptomatic transmission imply that case finding and contact tracing need to be supplemented by physical distancing measures in order to control the COVID-19 outbreak. Notably, quarantine and other containment measures were already in place at the time of data collection, which may inflate the proportion of infections from pre-symptomatic individuals.

Several studies have investigated a possible association between respiratory infection and acute myocardial infarction (MI). As both influenza and pneumococcal infections are vaccine preventable, understanding the populations affected by virus-induced cardiovascular complications is important to guide public health and clinical practice.

This observational study aimed to quantify the association between laboratory-confirmed respiratory bacteria or virus infections and risk of first MI or stroke, by using self-controlled case series (SCCS) analysis of anonymised linked electronic Danish health records.

The SCCS method was used to determine the relative incidence of the first event of MI and stroke occurring within 28 days after laboratory-confirmed respiratory infections compared with the baseline time period.

In the age and season adjusted analyses for first acute MI, the incidence ratios (IR) of a MI event occurring during the risk period were significantly elevated following a Streptococcus pneumoniae infection with values of 20.1, 11.0 and 4.9 during 1–3, 4–7 and 8–14 days, respectively and following respiratory virus infection with values of 15.2, 4.5 and 4.4 during 1–3, 8–14 and 15–28 days, respectively. The significantly elevated IRs for stroke following an S. pneumoniae infection were 25.5 and 6.3 during 1–3 and 8–14 days, respectively and following respiratory virus infection 8.3, 7.8 and 6.2 during 1–3, 4–7 and 8–14 days, respectively.

This study suggested a significant cardiovascular event triggering effect following infection with S. pneumoniae and respiratory viruses (mainly influenza), indicating the importance of protection against vaccine-preventable respiratory infections.