Scientists have worked extensively to understand the transmission dynamics, structure, molecular interaction, and many other aspects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the virus responsible for the ongoing coronavirus 2019 (COVID-19) pandemic. It is imperative to understand the epidemiological parameters of the virus in order to contain the pandemic.

Study: Correlation between times to SARS-CoV-2 symptom onset and secondary transmission undermines epidemic control efforts. Image Credit: Menara Gravis / Shutterstock.com

Importance of epidemiological parameters

Two of the most important epidemiological parameters of infectious diseases are generation interval and incubation period, both of which are parameters used to describe the outbreak response. The generation interval, which defines the infectiousness of a pathogen in a host, is the period between infection of a host with a pathogen (infector) and transmission of the pathogen to another host (infectee).

Comparatively, the incubation period refers to the time between infection and the onset of symptoms that arise as a result of the disease. The incubation period determines the replication rate of a pathogen and indicates the duration for which an infection can remain unnoticed in an infected individual.

Therefore, the incubation period plays an important role in evaluating quarantine periods. Scientists have indicated that both these parameters provide insights into the fundamental dynamics of infection. Studies of these parameters could also help public health officials to develop effective policies to manage disease outbreaks.

Epidemiological parameters of SARS-CoV-2

Scientists previously estimated the mean incubation period of SARS-CoV-2 at the beginning of the pandemic. At this time, they faced certain difficulties in determining the exposure times that were sufficient to cause infection, as well as the direction of the transmission.

Typically, scientists use the serial interval as a proxy for estimating generation interval. This is also used to predict the basic reproduction number, which is essentially the average of the number of persons infected by a single infector, in a susceptible population.

However, the effective reproduction number involves the average number of persons infected by a single infector in the presence of immune responses owing to previous infections and other interventions such as vaccination. Researchers have stated that the use of serial intervals as a proxy for generation time can result in biased estimates of the effective reproduction number. This is because of several factors, such as the presence of asymptomatic infections.

Previous studies have revealed that SARS-CoV-2 infections are associated with substantial presymptomatic transmission, which occurs when the generation interval is shorter than the incubation period. Scientists have indicated a correlation between the generation interval and incubation period of SARS-CoV-2.

This is biologically plausible, as there is evidence that shows that the viral load of SARS-CoV-2 peaks around the time of symptom onset. Although previous research indicated the existence of such a correlation, it has not yet been estimated.

A new study

A new study published on the preprint server medRxiv* provides evidence of the aforementioned correlation and estimated the period between the generation interval and incubation period of SARS-CoV-2.

In this study, researchers obtained a dataset from public databases containing 257 SARS-CoV-2 transmission pairs in Japan and estimated the mean generation interval and mean incubation period. Additionally, the researchers also measured the dependence of these periods on demographic and epidemiological characteristics of the pairs.

The authors focused on obtaining data with high certainty on the direction of transmission. They found that among many countries, Japan applied backward contact tracing methods from the beginning of the COVID-19 pandemic. In addition to aiding in the prevention of large clusters of cases, this approach also was an apt condition to obtain transmission pair data.

The present study revealed that the correlation between the generation interval and incubation period would help quantify SARS-CoV-2 transmission which would, in turn, prevent underestimation of the presymptomatic transmission that occurs prior to the development of symptoms. This study also evaluated the effect of isolation of COVID-19 symptomatic cases on epidemic control.

Study findings

Herein, the researchers estimated the mean generation interval is between 3.7–5.1 days, whereas the mean incubation period is between 4.4–5.7 days. Therefore, the mean generation interval was found to be consistently shorter than that of the mean incubation period when jointly estimated. This observation suggested a constant presence of presymptomatic transmission.

The scientists also found a positive correlation between the generation interval and incubation period with Kendall’s tau, ranging from 0.4–0.6. This positive correlation indicated that symptomatic cases depend on the infectiousness of the virus.

Previous studies revealed that even though asymptomatic SARS-CoV-2 infections are less infectious than symptomatic cases, they play an important role in the dynamics of the epidemic.

Conclusion

The emergence of SARS-CoV-2 variants has caused a surge in COVID-19 cases across the world. However, it is unclear if the mean and variance of the generation interval and incubation period of these variants will be similar to that of the original strain.

To date, a limited number of studies have suggested that the SARS-CoV-2 Alpha variant could have a longer duration of generation intervals; however, this is not the case for the Delta variant. The current study offers novel insights into the correlation between the generation interval and incubation period, which should encourage future research in this area.

*Important notice

medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Written by

Dr. Priyom Bose

Priyom holds a Ph.D. in Plant Biology and Biotechnology from the University of Madras, India. She is an active researcher and an experienced science writer. Priyom has also co-authored several original research articles that have been published in reputed peer-reviewed journals. She is also an avid reader and an amateur photographer.