Estimated duration of SARS-CoV-2 infection

The main causative agent of ongoing coronavirus disease 2019 (COVID-19) is severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Scientists say it is essential to understand the main epidemiological parameters of the virus in order to develop strategies to mitigate the spread of the virus.

study: COVID-19 Infectious unmitigated profile.. Image credit: Kateryna Kon

Background

An important epidemiological parameter that determines the rate of infection of a virus is the interval between outbreaks, that is, the period between infections of the infected person (first case) and the infected person (second case). Determining the exact time of infection is not an easy task, so it is difficult to estimate the generation interval.

In this regard, to determine the interval between emergences of emerging infectious diseases, researchers typically have an incubation period (the time between viral infection and the onset of symptoms) and a continuous interval (the time between the onset of symptoms in an infected person). ) Depends on and infected person).

Previous studies have shown that these epidemiological factors depend on the host and conditions of infection. This is why epidemiological parameters are described as distributions rather than fixed values.

In general, in an ongoing pandemic, whether infection rate or virus spread is controlled is determined by examining the distribution of generational intervals. At the population level, the generation interval is characterized by virus reproduction number (R).

Short generation intervals caused before onset COVID-19 infection We challenge the effectiveness of various mitigation strategies, such as quarantine. Contact tracing, And testing.

As mentioned above, the distribution of generational and serial intervals can change depending on the behavior of the population. For example, following various non-pharmaceutical strategies such as social distance expansion and quarantine will prevent further transmission of the virus.

New research

New research published in medRxiv* The preprint server focuses on estimating the temporal dynamics of infectious cases in the absence of intervention (unmitigated generation intervals). This estimate is very important as it reflects the effectiveness of the mitigation policy in the absence of other interventions. However, such an estimation is a difficult task, as symptomatic individuals may self-isolate and prevent infection.

The authors addressed this issue by applying rigorous data curation procedures. That is, we considered outbound events that occurred before major mitigation measures were implemented and before COVID-19 awareness became widespread. So far, researchers have not considered factors such as contact tracing and case isolation to estimate generational spacing distributions.

In this study, scientists measured the distribution of generational intervals and incubation periods, taking into account all serial intervals in the transmission pair dataset. Although many studies are available to assess generation intervals, some major methodological issues can lead to significantly biased results in such studies.

In this study, researchers were able to combine all available infection data associated with the first COVID-19 outbreak when mitigation policies were minimal and collect infection pair data from 12 datasets. I did. They then conducted statistical studies to infer the main causes of bias in estimating the generation interval distribution.

Investigation result

Researchers have found that the effects of mitigation steps and awareness-driven behavior have a significant impact on late-stage COVID-19 infection. Without these sources, the distribution of generation intervals would be underestimated.

Scientists have shown that mitigation strategies reduce the amount of asymptomatic infections and increase the rate of asymptomatic infections. These results were validated using the initiation of transmission from symptoms (TOST).

Current studies report a median generation interval of 7.9 days and an average of 9.7 days, which means that the duration of infection is much longer than previously expected. ..

Limitations

One of the main limitations of this study is that the dataset used for the analysis was taken from a previously published study.

In addition, the data of infected pairs are not useful for determining the direction of infection, especially if the infected person develops symptoms after the infected person due to presymptomatic infection and it is difficult to identify who was infected with whom. Tends to be appropriate.

The author addressed these biases through a bootstrap approach. This approach omits some data points in each bootstrap sample.

In addition, sensitivity analysis was performed to address some important biases. For example, consider the long serial intervals in the dataset to evaluate the time period associated with unreduced transmissions.

Although these analyzes may reduce the distribution of generation intervals estimated by bias, the main conclusions about long unmitigated generation intervals remain solid.

Conclusion

Scientists have stated that the estimates presented in the current study may help develop quarantine policies. This study shows that individuals released from quarantine on day 14 can still be infected with SARS-CoV-2.

In the future, the methodology developed in this study may help estimate the generation interval of newly emerging SARS-CoV-2 mutants that exhibit altered infectious dynamics.

*Important Notices

medRxiv publishes unpeer-reviewed preliminary scientific reports and should not be considered definitive, guide clinical / health-related behaviors, or be treated as established information.