COVID-19 and Kinsa FAQs

Not everyone experiences fever as a COVID symptom. Why is a thermometer useful for capturing transmission of illness? Won’t it miss a lot of cases?
We don’t need every COVID-19 patient to have a fever to see how illness is spreading across a population in real-time. Similar to testing, even if not everyone gets a test, the number of people who do test lets us estimate how much illness is in the population. For example, if 50% of COVID-19 patients experience a fever, a doubling of people with fever in a particular location means that the same proportion was likely infected in that time period but did not get a fever.
How are COVID-19-related fevers differentiated from fevers caused by the flu or other illnesses?
We can probabilistically identify COVID-like illness from the broader category of Influenza-like illness in two ways. First, if the number of fevers is statistically higher than expected for influenza-like illness, we call this "atypical illness" and it is likely COVID-like illness. Second, we can identify transmission rates that don't statistically conform to normal cold and flu patterns, called atypical transmission, also likely indicating CLI. To support these findings, we can review positivity rates for Flu A, Flu B, RSV, and COVID-19 tests to see if the trends match our findings and confirm that the spike in fever is likely the result of CLI.
What are the privacy implications of sharing this data?
We can both protect personal privacy and also gather and share the information necessary to detect and effectively respond to outbreaks like COVID-19. Kinsa shares population health insights -- i.e., the percentage of people in a county who are ill. There is no way to identify an individual from this illness signal. Just as we incentivize the creation of drugs, diagnostics and vaccines, we too should incentivize the creation, adoption, and effective use of novel datasets by local, state and federal public health agencies. This can be done while protecting personal privacy. 

How does Kinsa complement testing, contact tracing, or vaccine distribution strategies?
With an early warning system, officials can make earlier, more precise decisions about where to focus scarce testing resources, activate clinical trial sites, and more effectively target initially-limited quantities of an approved vaccine to areas with impending case surges. Furthermore, because the network serves as a two-way communication channel, the Kinsa platform can leverage its high engagement and retention levels to channel sick people toward contact tracing applications, increasing the traction and efficacy of those efforts.
Why does Kinsa focus so much on schools with its FLUency program?
Through schools, we can reach larger household sizes and traditionally underserved communities, which also helps us cover a larger share of the population. Additionally, schools play a central role within communities, and promoting outbreak detection in schools effectively helps detect outbreaks in the broader community. For the past five years, Kinsa’s school health program has sustained high levels of engagement amongst participants, with 65% of participants viewing and contributing to health trends weekly. We’ve seen that the program reduces illness in schools by guiding families to earlier care and treatment, directing symptomatic students and staff to stay home, and increasing preventive behaviors of those at-risk. Past results of this program include a 27% decrease in illness-based school absenteeism during the peak of flu season.