Track Testing Trends – Johns Hopkins Coronavirus Resource Center

Positivity Rates: Our calculation, which is applied consistently across the site and predates most states’ test positivity tracking efforts, looks at number of cases divided by number of negative tests plus number of cases. We feel that the ideal way to calculate positivity would be number of people who test positive divided by number of people who are tested. We feel this is currently the best way to track positivity because some states include in their testing totals duplicative tests obtained in succession on the same individual, as well as unrelated antibody tests. However, many states are unable to track number of people tested, so they only track number of tests. Because states do not all publish number of positive and number of negative tests per day, we have no choice but to calculate positivity via our approach. We describe our methodology as well as our data source (COVID Tracking Project) clearly on the site.

7-Day Averages: The CRC calculates the rolling 7-day average separately for daily cases and daily tests, and then for each day calculate the percentage over the rolling averages. Some states may be calculating the positivity percentage for each day, and then doing the rolling 7-day average. The reason why we use our approach is because testing capacity issues and uneven reporting cadences create a lot of misleading peaks and valleys in the data. Since we want to give a 7-day average, it is more fair to average the raw data and then calculate the ratios. Otherwise, days when a large number of negative tests are released all at once—and positivity is going to be very low—will have the same weight as days when data was steadily released, and the overall result is going to be lower. Our approach is applied to all our testing data to correct for these uneven data release patterns.

Positivity rates can tell us whether a state’s testing capacity is sufficient. Ideally, a state should be meeting or exceeding the recommended positivity rate, which the WHO has set at 5%. A positivity rate over 5% indicates a state may only be testing the sickest patients who seek out medical care, and are not casting a wide enough net to identify milder cases and track outbreaks.

Percent positivity can also help us determine if an increase in cases is simply the result of expanded testing or if it signals increased transmission of the virus. If we see the percentage of positive tests begin to rise, it indicates insufficient testing to find infections that may be occurring. Not finding these infections may mean that the virus is transmitting without intervention, which can lead to future case growth.


If a rise in cases is the result of increased testing, the percent positive line could look flat or like it is decreasing over the time period when cases increased.

If a rise in cases is the result of increased transmission, the line could appear to be increasing over that same time period.

This content was originally published here.

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