Active Cases: A Misleading Metric
23 July 2020 (updated 24 September 2020)
Amidst the onslaught of data and charts surrounding the COVID-19 pandemic, how are we to answer the critical question: What is the current severity of the outbreak and the associated risk to the community?
It may be appealing to look at the current active cases metric. The number of active cases, also known as prevalence, filters out people who have recovered or died of the disease. It is tempting, then, to surmise that active cases must reflect the actual number of contagious people, and therefore the associated risk to the community. The reality is a fair bit more complicated.
Consider these caveats, or sources of noise in the active cases metric:
People who are identified as a COVID-19 case are instructed to isolate. Some people will have the means to do this quite effectively—others less so.
People who are hospitalized with COVID-19 are isolated within a healthcare facility, so the risk of them spreading the virus in the community during that time is very low.
Contagiousness of an infected person varies over the course of the disease and can be significant early on—often before a person may develop symptoms or be identified as a case. (source: CDC)
COVID-19 disease outcomes are non-binary, and contagiousness of people with lingering symptoms is yet unknown.
The definition of inactive/recovered cases varies among state jurisdictions and, for Tennessee, has changed multiple times.
The Hamilton County Health Department’s reporting of inactive/recovered cases is sporadic.
The time duration between when a person is identified as a COVID-19 case and when that person is reported as recovered or as a death varies based on a myriad of factors including: a) the time lag between test sample collection date and case identification date, b) disease severity, and c) the time lag between when a person recovers or dies and when the recovery or death is reported.
To accurately measure prevalence, we would need to test the entire population, or a sufficiently large randomized sample, every day using a highly accurate test. On a community scale, this is not a current possibility.
How, then, shall we answer the question of outbreak severity and the associated risk?
In the absence of a coordinated national approach to risk communication, a group of top scientists, led by the Harvard Global Health Institute, has put forward a unified framework of metrics and risk levels for local jurisdictions. These more accurately reflect the outbreak severity and risk to the community.
Daily New Cases
Every day, we see the total number of cases increase. We average these increases over the past 7 days. Then, we express that number as a proportion of the population (per 100,000 people). This number is also referred to as incidence.
The daily new cases metric and the trend (increasing or decreasing), taken in context with test positivity rate, daily new hospitalizations, and daily new deaths, provides a much more accurate view of disease spread. In addition to establishing easy-to-understand risk levels, the key metrics framework also offers strategies for suppression of COVID-19 including level-dependent benchmarks for testing, contact tracing, supportive isolation, and other non-pharmaceutical interventions.
More details on the Key Metrics for COVID Suppression unified framework can be found at globalepidemics.org. For additional explanation about incidence, prevalence, and infection rate, see https://blog.covidactnow.org/what-is-covid-incidence/.