Understanding Commonly Used Epidemiology Statistics

Last updated by our Medical Anthropology & Epidemiology Team on 09.04.2020

Infection Progression

There are three basic stages in the progression of an infectious disease. First is the Latent Period, the time from a person’s exposure to a pathogen up until they are capable of transmitting the disease to others. Next is the Incubation Period, the time between when a person is exposed to the pathogen and when they show their first symptom of illness. Finally, the Infectious Period is when an infected person can transmit the disease to others around them.

If your incubation period lasts longer than the latent period, you may infect others around you before you know you are sick and have symptoms.


Common Epidemiology Statistics

R0 (pronounced “R Naught”) represents the average number of people that can be infected by one sick person. This number can be wildly different for different diseases.


Incidence and prevalence are similar but are not interchangeable.

Incidence refers to the number of new cases of a disease in a population during a specific time period (for example, a rolling 2-week daily average new cases)

  Number of NEW CASES of a disease in a time period 
the total population at risk of getting the disease

Prevalence counts both new and existing cases of a disease in a population (for example, total number of cases this past week).

  Number of NEW and EXISTING cases of a disease in a time period  
the total population at risk of getting the disease


Despite also sounding similar, mortality rates and case fatality rates (CFR) are not synonymous. A mortality rate is the number of deaths that occur in a total population during a specific time period. A cause-specific mortality rate is the number of deaths due to a specific condition in the population.

In contrast, a case fatality rate (CFR) is the percent of deaths caused by a disease among those that actually have that disease.

Mortality rates help us understand how many people in a population are dying, but case fatality rates help us understand how deadly any particular disease is. Though mortality rates cannot demonstrate the deadliness of a disease, they can be used to show how severe and/or widespread an outbreak is.


When you read statistics about COVID-19, double-check the type of statistic being given to you. If someone is trying to use “per capita” mortality rates to tell you how deadly the virus is, be careful – this is a misleading way to frame the data. Likewise, if someone uses case fatality rates to describe how widespread the infection is, know that this is a misleading use of these statistics.

Test statistics

Two types of test are currently in use to determine who has been infected by COVID-19. Polymerase Chain Reaction (PCR), tests that use spit or nasal swabs, and Antigen/Rapid tests are used to determine if a person is currently infected with COVID-19; these are considered diagnostic tests. Serology/antibody tests, which use blood samples, determine if a person has ever been infected with COVID-19.

The percent positive statistic tells us what percentage of those who get tested are positive. Meanwhile, testing rates help us describe how much of the population we are able to provide testing for. Just remember: statistics about testing are momentary snapshots of a population’s health at different times, and are dependent on the amount of tests performed and how widespread the infection is in the community.



Science is an iterative process. As new information becomes available, our statistics and calculated rates will be updated to reflect current data. This is not an indication of “bad science” or scientists/researchers attempting to mislead you – it simply means previous estimates were limited by the data available to the scientific community at that time.

If you’d like to learn more about Commonly Used Epidemiology Statistics, you can read our summary (presentations will open in a new window or tab) below.

Commonly Used Epidemiology Statistics