Dashboard Measures and Interpretations
The Ohio State University maintains a public COVID-19 dashboard to keep students, parents, faculty, staff and the public informed about COVID-19 at the university and in Ohio.
The dashboard is here to:
- Promote transparency of testing and test results
- Provide details on our comprehensive approach to monitoring and addressing the pandemic on and around campus
- Communicate with our surrounding communities our commitment to a safe and healthy environment
- Support public health efforts to curtail the pandemic
- Encourage every Buckeye’s support in wearing masks, physical distancing and taking other measures to slow the spread of infection
The following are explanations of what you will find on the dashboard, which will continue to evolve over time. Individual measures on the dashboard should be interpreted cautiously. These and other factors must be considered as a whole when determining the current status of our COVID-19 control efforts on and around campus.
What's on this page:
- Daily cases in Ohio
- R(t) numbers for Ohio and Franklin County
- Hospital capacity in Ohio
- Student tests by test date
- Cumulative tests - students and faculty
- Isolation and quarantine
- Personal protective equipment
- Enhanced cleaning
The daily cases measure is taken directly from the Ohio Department of Health (ODH) dashboard. The measure reflects the number of cases reported to ODH each day.
The daily cases measure gives some insight into the status of the pandemic in the state, but the measure depends on several factors that influence its interpretation. First, people with COVID-19 must be tested to be identified and since not all infected Ohioans are tested — especially those without symptoms — it will always be an underestimate. Second, the reporting of cases is delayed. The sawtooth pattern in the cases reflects decreased testing and delays in reporting over weekends. Finally, the last two weeks are typically labeled as preliminary as cases are backfilled when reports are delayed. This backfilling process is why the gray box is labeled “preliminary data."
The reproduction number (R) is an epidemiological measure of the potential for ongoing transmission. R is the average number of people to whom a single person passes the infection. For example, if R=2, then each person with an infection would infect two other people, on average. When R=2, the epidemic would expand quickly. When R=1, the epidemic would be at a plateau. And when R<1, the epidemic would be slowing. R measures depend on how infectious the virus is, how long infections last, how much contact people have and how susceptible the population is to infection. The version we present is referred to as R(t), the reproduction number over time. R0, or “R-naught” is used in other settings and is the reproduction number in an entirely susceptible population.
R(t) is calculated for both the state of Ohio and Franklin County. The calculation uses a publicly available algorithm and COVID-19 data derived from ODH reports.
R(t) is derived from the reported cases. As a result, it has similar limitations. If testing is reduced due to a lack of supply or increased testing efforts, the proportion of the true underlying cases that are identified may change. That means that R(t) may change not as a result of changes in transmission but rather as a result of changes in identification of cases. R(t) goes up and down regularly because of reporting variations throughout the week.
One important thing to note: With COVID-19, transmissibility seems to vary considerably between people. Some people, sometimes called “super spreaders” appear to be very infectious and cause many infections while others infect no one.
COVID-19 can cause serious illness requiring hospitalization and intensive care. The hospital capacity measures provide an indication of the readiness of Ohio hospitals to respond to a surge in COVID-19 cases.
The medical-surgical adult bed capacity can be changed to some extent. For example, if a surge in cases occurred, elective medical procedures could be postponed, increasing capacity. The cancellation of surgeries can also influence the number of available intensive care unit beds.
This figure reflects the total number of tests (gray bars), the number of positive tests (scarlet bars) and percentage of positive test results (line graph). Toggle buttons allow you to review by residence, total, on-campus or off-campus, and by date range, single-day, cumulative, or seven-day moving average. The dates reflect the day the sample for the test was taken, not the date of the result. The figure will lag the current date by one to two days and data for a given date may change as additional results come in.
- Total tests: All tests performed, including the routine student surveillance tests (taken weekly), focused testing of students at greater risk and tests for diagnostic purposes primarily taken when someone has symptoms. The data reflects tests performed, not people tested, so many people will be included in the total tests more than once over time.
- Positive tests: All positive tests from all testing programs.
- Percentage positive: Positive tests divided by the total number of tests, multiplied by 100.
- On-campus: Students living in on-campus residence halls and a limited number of off-campus housing units owned by the university.
- Off-campus: Students living off campus in non-university housing.
- 7-day average: For each of the three measures, an average of the seven previous days. This measure smooths unexpected fluctuations in the data.
- Cumulative: All tests and results to date.
- Single day: Tests and results for the specific date given.
- The data include tests performed for any reason, which may include routine student testing, surveillance, focused testing, or diagnosis. Shifts in the total number of tests, the number of positives or the percentage positive may occur because of changes in who is being tested and why. For example, if a cluster of cases is suspected and testing is performed, the percentage positive may increase more than expected. Alternatively, if additional groups of students with no symptoms and no known increased risk are tested in the routine testing program, the percentage positive may decline.
- Because the number of tests is large, a few days of higher than expected positive tests will not be immediately visible in the cumulative results.
- The single-day data will vary based on the testing program and the university’s response. For example, a group of students at higher risk may be referred for testing on a given day. But this data also provides a useful glimpse at trends over time. Deviations from these trends must be interpreted carefully, though, because of the different types of testing programs that are combined in these data.
- The seven-day average removes some of the variability of the single-day estimates and provides a better estimate of the total number of tests and positive tests. It also provides a more stable estimate of the percentage positive. Overall, this measure is probably the most informative.
These two donut-shaped charts provide a summary of all tests, positive tests and percentage positive tests performed for students beginning on Aug. 14 and for employees beginning on Aug. 1.
The student chart data will be the same as the cumulative trend data. The data for all testing programs are included. The employee data is different because it does not include widespread, mandatory testing of people without symptoms. In addition, when an employee has a positive test, it is less safe to assume that the infection was acquired on or near campus.
Isolation and quarantine are critical strategies for reducing COVID-19 transmission on Ohio State’s campus. Isolation keeps an infected person away from other people. Quarantine keeps a person who has been exposed to an infected person (known as a “close contact”) from other people because of the increased risk that the close contact is also infected. Students who live on campus are moved to Ohio State-supported isolation and quarantine rooms. Off-campus residents must isolate or quarantine in their residence. Some students in both circumstances choose to go home. Monitoring isolation and quarantine capacity allows university leaders to identify the need for additional beds or make adjustments to plans for on-campus residency.
Isolation and quarantine bed capacity may change over time. People will move into and out of isolation and quarantine over time.
Please reference this website for the most up-to-date guidelines. The university’s COVID-19 Transition Task Force’s Safe Campus and Scientific Advisory Subgroup will continue monitoring changing conditions and consult with local and state health authorities. Recommendations and requirements will be refined as needed.