Introduction to Epidemiological Terms

Epidemic Parameters

$R_{0} = \beta * \kappa * D$

in which **β** is the risk of transmission per contact, **κ **is the contact rate, and **D*** *is the duration of infectiousness. (CDC)

$R_e = R_o * X$

where X is the proportion of the population susceptible. Therefore, vaccination would decrease X and correspondingly the Re value. Additionally, as more people are infected with a virus, more individuals become immune to reinfection from the virus, and X decreases. When Re < 1, the total number of infected persons declines, and the outbreak dies out. Re = 1 would keep numbers stable, and Re > 1 would lead to continued growth in the numbers of infected persons. Re gives an idea of transmission over time and is useful for monitoring during an outbreak, as compared to R0, which is most useful in forecasting potential severity and spread at the start of an outbreak. (CDC, Giesecke 2002)

Note that incomplete data can skew the CFR. For example, if severe cases are more likely to be diagnosed than milder cases, then the denominator would be artificially lowered relative to the numerator and CFR would be inflated. Conversely, if many people were dying of the cause without being diagnosed (e.g. at home without interfacing with the medical system), the CFR could be artificially lowered. (CDC)

Case Descriptors

Adapted from Giesecke, J. Modern Infectious Disease Epidemiology. 2002.

Non-Pharmaceutical Interventions

Containment and Suppression

Mitigation

Last modified 1yr ago