The analysis and data behind these insights are based on what is known about how illnesses, like the flu and common cold, are spread. By providing more thermometers to these communities, we strive to give the individuals in power the information they need to save lives. Kinsa for Families. The chart shows that Kinsa’s thermometer distribution tends to mirror population density, with more active users in higher populated urban areas than in less populated rural areas. New York is the focus of most of the country’s attention because of the soaring number of positive tests there, but if Kinsa is right then we have a big — big — problem brewing in Florida. In counties where there are enough active thermometers, these forecasts can be made down to the county level. Due to the how contagious illness transmits from person to person, the more densely populated an area is, the more likely it is for illness to spread. Nor does the map (yet) have a feature that lets you see growth in atypical illness in real time. In collaboration with Benjamin Dalziel, Associate Professor at Oregon State University, our data team has shown that they can forecast and, When comparing the cumulative cases of positive COVID-19 with Kinsa’s cumulative atypical illness data, a correlation is seen. If you’re interested in tracking your own illness and contributing to Kinsa’s public health data, you can pre-order one of Kinsa’s thermometers here. This relationship is statistically significant, with a correlation of 0.58. Company scientists are uniquely positioned to identify unusual clusters of fever because they have years of data for expected flu cases in each ZIP code. This is represented by the trend line that has an R2 value of .9. Kinsa Health has sold or given away more than a million smart thermometers to households in which two million people reside, and thus can record fevers almost as soon as consumers experience them. In a conference call with a reporter, Dr. Dalziel and Kinsa’s senior data scientist, Sam Chamberlain, showed twin maps overlaying one another: the first showing where this year’s flu season currently is, and another showing ZIP codes where high fevers are two or three times as common as they ought to be, according to the flu model. Alyssa Milano extends an olive branch to Trump supporters – It doesn’t go well. Kinsa’s smart thermometers are sold at major retailers in the country and online, and are also given away for free through the Kinsa FLUency school health program (see the buy one give one offer to support this program). A major challenge in responding to the current COVID-19 epidemic is the lack of early warning systems and limited number of testing kits. This is shown in figure 1. by Donald G. McNeil Jr. NYTimes.com March 18, 2020 “. Two million families use the Kinsa thermometer and app to detect illness and get guidance on the care and treatment to get better faster. Since the beginning of the pandemic we've been checking in with Kinsa Thermometer, a company that compiles data from millions of smart thermometer users … Smart thermometer maker Kinsa has been working on building accurate, predictive models of how seasonal illnesses like the flu travel in and among communities — and its fever map is … The chart shows that as the illness level increases, the reported COVID-19 cases from the CDC also increases at the same rate. KINSA: predictive models for atypical illness levels. Kinsa’s latest map of fever spikes shows areas that are known to have many cases of Covid-19, the illness caused by the coronavirus. This chart shows the correlation between Kinsa’s cumulative atypical illness level and the CDC’s cumulative positive cases of COVID-19. The closer this number is to 1, the higher the correlation. A sudden spike that far exceeds estimates for flu for a given date may well indicate the coronavirus has arrived. TechCrunch fait partie de Verizon Media. The company has smart thermometers in every county in the U.S., but it … . Bookmark it. All of the data on the map comes from Kinsa smart thermometers, which log temperatures of users and then relay that data to Kinsa HQ to be aggregated and logged. The C.D.C.’s system lags because it relies on weekly reports from hundreds of doctors’ offices and hospital emergency rooms about what symptoms they are seeing in patients. Asked for comment about Kinsa’s proposal, a C.D.C. However, our research shows there is a statistically significant correlation between the two and that Kinsa’s atypical illness levels are a strong indicator of a COVID-19 outbreak. Kinsa’s smart thermometers are sold at major retailers in the country and online, and are also given away for free through the Kinsa. When comparing the cumulative cases of positive COVID-19 with Kinsa’s cumulative atypical illness data, a correlation is seen. This is a promising indicator that atypical fever data from Kinsa’s connected thermometers point to areas of confirmed COVID-19 cases. “This is very, very exciting,” said Dr. William Schaffner, a professor of preventive medicine at Vanderbilt University. The analysis and data behind these insights are based on what is known about how illnesses, like the flu and common cold, are spread. Within days, testing showed that South Florida had indeed become an epicenter. “It is a good thing to give thanks unto the Lord.”, “Reviewing its guidance and recommendations”, Krakens released: Powell publishes lawsuits in GA, MI alleging massive fraud, Why big-city dominance is a problem for Democrats. Normally, Mr. Singh said, the company submits its data to peer-reviewed medical journals. The AstraZeneca COVID vaccine data isn’t up to snuff, New Mexico governor shuts down grocery stores with new public health order, Latest from the CDC: Shortening quarantine times is likely the next big announcement. (Scroll down beneath the map and you’ll see a graph showing just how far the current rate deviates from the normal rate.) . There are many studies that show how these types of illnesses spread within communities, and how demographics like age, sex, and zip code, play a role in community spread. One in every 5 Kinsa thermometers in the US has been distributed to a family in a Title 1 school participating in FLUency. You can also search by zip code or county to see what your own backyard looks like, or view the whole United States if you like. Beginning on Feb. 24, however, another spike of fevers began to grow out of the downward slope of the normal flu recordings. This makes it hard to know when and where outbreaks are happening, which in turn creates challenges for those in power to know where to distribute the necessary medical support and supplies. All of the data on the map comes from Kinsa smart thermometers, which log temperatures of users and then relay that data to Kinsa HQ to be aggregated and logged. Through retail sales and school donations, Kinsa has amassed a user base broadly consistent with the overall US population distribution by age. Check this out: King County was the site of one of the biggest outbreaks in America earlier this month. In the absence of widespread testing, we cannot definitively prove that an increase in Kinsa’s atypical illness levels means there is an outbreak of COVID-19. Nos partenaires et nous-mêmes stockerons et/ou utiliserons des informations concernant votre appareil, par l’intermédiaire de cookies et de technologies similaires, afin d’afficher des annonces et des contenus personnalisés, de mesurer les audiences et les contenus, d’obtenir des informations sur les audiences et à des fins de développement de produit. close window. This is shown in. One problem with the map is that there’s insufficient data for many counties. The app then gives them general advice on when to seek medical attention. Knowing that families with school aged children are the largest part of Kinsa’s user base, it makes sense that the most engaged users are mothers with school-aged children. The company can “see” clusters of fever among its customers instantly, in other words. Kinsa's smart thermometers work with an app. Epidemiological evidence suggests that women of childbearing age are at higher risk for complications related to the flu, though there is mixed evidence that show that women suffer from higher infection rates than men3. For a few months now, Kinsa has worked with Benjamin Dalziel, a disease modeler at Oregon State University who uses electronic medical records, C.D.C.’s influenza surveillance network and other data to map the way the flu season historically rises and falls across the country. “But we think this could be super helpful even without peer review, and we think there’s a moral imperative to do this right now so everyone can see it and judge it,” Mr. Singh added. The little graph beneath the map does show change over time, though. I assume the company’s customers also skew younger since older people who are less tech-savvy might shy away from smart thermometers. Kinsa CEO Inder Singh says the company is able to predict COVID-19 outbreaks 10 days in advance. On March 14, Kinsa’s data indicated an unusual rise in fevers in South Florida, even though it was not known to be a Covid-19 epicenter.