Positivity Rates: The positivity rate is the number of positive tests divided by the total number of tests given. In the COVID-19 pandemic, medical professionals are watching the positivity rate as an indicator of the severity of the spread of the disease in their communities. Like most of the measures in the pandemic, we want to see this metric declining and eventually reach 0. Using data from covidtracking.com, the chart below shows the USA positivity rate from June 1 through July 29.
Data downloaded from covidtracking.com API https://covidtracking.com/api/v1/us/daily.csv on July 30, 2020.
US Positivity Rate June 1 - July 29
The WHO guidelines identify 5% positivity as a target rate for controlling COVID-19, and lower is always better.. The USA briefly hovered around 4.5%, and even dipped below 4% earlier in June, then climbed to the 8.5% range and remained there at a plateau until just the last 5 days. 5 days is far too short a period to draw any conclusions about a trend, particularly since that period includes a weekend period during which the U.S. experienced disruptions from a major hurricane. But it is at least possible that the second thoughts many leaders are now having about re-opening phases may be having an effect on the spread of COVID-19.
This measure is far more important at regional levels, since outbreaks of COVID-19 do not happen uniformly nationwide. They are in states, counties, and towns and cities. A local medical establishment's positivity rate is critical for decision-makers thinking about how to keep from exhausting their medical resources.
A positivity rate of 25.9%, in the city of Houston, for example, should be considered catastrophically high. It has declined only slightly in the most recent days.
As always, multiple confounding factors are problematic for this measure:
Different regions use different methods of administering tests and reporting cases
External circumstances can interfere with the timing of reporting, such as Hurricane Hannah's direct hit on a major hotspot in south Texas
Huge swings are observed the daily numbers - an average over multiple days is a more useful indicator for this measure
The national aggregate number obscures huge variations among different regions
A lack of available testing capacity may skew the results to look artificially high, as tests are conserved for patients in more immediate need. Of course, a lack of available testing capacity is an extremely serious problem in its own right, so the policy implications are the same: take immediate steps to control the spread
A backlog of test results will obscure both increasing and decreasing trends
All opinions expressed in this blog are solely those of the authors, and do not reflect those of University of Texas Rio Grande Valley, or any organizations of which either is a member.