Improved time-varying reproduction numbers using the generation interval for COVID-19

Area of Science:

• Epidemiology
• Infectious Disease Dynamics
• Public Health

Background:

• Accurate estimation of epidemiological parameters like incubation period, serial interval (SI), and generation interval (GI) is crucial for understanding COVID-19 transmissibility and intervention effectiveness.
• These parameters are fundamental for calculating the basic reproduction number and assessing disease spread.
• Surveillance data from South Korea (February 2020 - April 2021) provided a basis for estimating these critical metrics.

Purpose of the Study:

• To estimate key epidemiological parameters for COVID-19 using infector-infectee surveillance data.
• To quantify the proportion of presymptomatic transmission.
• To compare the impact of generation interval (GI) versus serial interval (SI) on estimating the time-varying reproduction number.

Main Methods:

• Analysis of COVID-19 infector-infectee surveillance data collected in South Korea.
• Estimation of mean incubation period, generation interval (GI), and serial interval (SI).
• Calculation and comparison of time-varying reproduction numbers using both GI and SI.

Main Results:

• The mean incubation period was estimated at 4.9 days (95% CI: 4.2, 5.7).
• The mean generation interval (GI) was estimated at 4.3 days (95% CI: 4.2, 4.4), and the mean serial interval (SI) was 4.3 days (SD: 4.2).
• ~57% of transmissions occurred presymptomatically, highlighting significant pre-symptomatic infectiousness.

Conclusions:

• Presymptomatic transmission significantly contributes to COVID-19 spread, necessitating its consideration in epidemiological models.
• Estimating the time-varying reproduction number using the generation interval (GI) may provide a more accurate reflection of transmission potential during rapid case increases.
• Accurate estimation of epidemiological parameters is vital for effective public health strategies and interventions against COVID-19.