Returns transmission parameter values for gamma, mu, kappa and R0 given a specific variant
Source:R/covid_transmission_parameters.R
covid_transmission_parameters.RdParameters are returned in vector form for age-structured models, and scalar form for non-age-structured models.
Source
The following are a list of sources used for parameter estimates:
Xin, Hualei, et al. "Estimating the latent period of coronavirus disease 2019 (COVID-19)." Clinical Infectious Diseases: an Official Publication of the Infectious Diseases Society of America (2021).
Li, Baisheng, et al. "Viral infection and transmission in a large well-traced outbreak caused by the Delta SARS-CoV-2 variant." MedRxiv (2021).
Jansen, Lauren. "Investigation of a SARS-CoV-2 B. 1.1. 529 (Omicron) Variant Cluster—Nebraska, November–December 2021." MMWR. Morbidity and Mortality Weekly Report 70 (2021).
Grant, Rebecca, et al. "Impact of SARS-CoV-2 Delta variant on incubation, transmission settings and vaccine effectiveness: Results from a nationwide case-control study in France." The Lancet Regional Health-Europe (2021): 100278.
Verity, Robert, et al. "Estimates of the severity of coronavirus disease 2019: a model-based analysis." The Lancet infectious diseases 20.6 (2020): 669-677.
He, Xi, et al. "Temporal dynamics in viral shedding and transmissibility of COVID-19." Nature medicine 26.5 (2020): 672-675.
Ferguson, Neil, et al. "Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand." (2020).
Liu, Ying, and Joacim Rocklöv. "The reproductive number of the Delta variant of SARS-CoV-2 is far higher compared to the ancestral SARS-CoV-2 virus." Journal of travel medicine (2021).
Zhang, Meng, et al. "Transmission dynamics of an outbreak of the COVID-19 Delta variant B. 1.617. 2—Guangdong Province, China, May–June 2021." China CDC Weekly 3.27 (2021): 584.
Burki, Talha Khan. "Omicron variant and booster COVID-19 vaccines." The Lancet Respiratory Medicine (2021).
Arguments
- variant
a string specifying the variant of SARS-CoV-2: base, delta or omicron.
- agestructured
a boolean indicating whether or not the model is age-structured
Value
lists of numbers or (for gamma and mu for age-structured models) dataframes representing transmission parameter values
Details
1/kappa is the typical latent period, i.e. the period in which an individual is infected but not infectious. The latent period for the base variant is estimated to be 5.5 days (Xin et al. 2021). The latent period for the Delta variant is estimated to be around 3.7 days (Li et al. 2021). The incubation period for the Omicron variant is estimated to be 3 days (Jansen 2021), but no estimate for the latent period is currently available. Because the incubation period of the delta variant is estimated to be approximately 0.6 days longer than its latent period (Grant et al. 2021), we assume the latent period for omicron to be 2.4 days. We thus obtain values of kappa for each of the variants: for base kappa = 1/5.5, for Delta kappa = 1/3.7, and for omicron kappa = 1/2.4.
We assume that on average 0.66% of individuals infected with the virus die (Verity et al. 2020): this is termed an infection fatality ratio (IFR). For age-structured models, we use age-specific IFR estimates (Verity et al. 2020). Changing either gamma or mu affects both the rate at which individuals recover or die and the proportions which recover or die. As such, the implications of the individual parameter values are hard to intuit without recourse to the other. Here, we choose a different parameterisation that makes it simpler to set these parameters to appropriate values:
gamma = zeta (1-IFR) mu = zeta IFR
The proportion of infected individuals who go on to die due to infection is given by the ratio of the rate of death to the overall rate out from the infectious compartment, which is the definition of the IFR:
zeta = zeta IFR / (zeta IFR + zeta (1-IFR)) = IFR
The average duration spent in the infectious compartment is given by:
1 / (zeta IFR + zeta (1-IFR)) = 1 / zeta
Viral load data from hospitalised patients with known infector-infectee pairs can be used to determine the probability that infection occurs at a given time after the infector is first infected (He et al. 2020): in so doing, determining a distribution representing the duration of infectiousness. It has been estimated that viral loads decline quickly within 7 days of being symptomatic (He et al. 2020). So, here, for models without asymptomatic transmission we assume an average infectious period of 7 days, resulting in zeta=1/7.
The R0 of the base variant is assumed to be 2.4 in Report 9 (Ferguson et al. 2020). Estimates of R0 for the delta variant range between 3.2 and 7, so we estimate it as 5 (Liu et al. 2021; Meng et al. 2021; Burki 2021). Estimating R0 for Omicron is difficult with the many confounding variables like vaccine escape, but a preliminary guess is 10 (Burki 2021).