This company Kinsa sells internet connected thermometers. Their "US Health Weather Map" (that I called a Fever Heatmap) shows areas with more fevers than normal. Under the map note the chart of fevers vs Date.
Normally (sans epidemic) these fevers are from flue and colds. On the chart, the blue line extending thru May is the number of fevers expected. The Orange line is the Observed number, and Red shows fevers exceeding the expected range.
This data is recorded by Kinsa's servers as their customers measure their temperature. As such it is 5-10 days (my estimate) ahead of the case numbers reported by doctors and hospitals. This is because people wait until they feel really sick before calling a doctor.
Therefore, these numbers are timely, but harder to interpret. Remember these are all fevers, not just SARS-COV2. Also this is most certainly NOT a random sampling of the population. The sample must be small, and skewed by income and age.
That said, what the chart shows is that in the USA, fevers exceeded the expected range about Mar 9, then fell back into the expected range about Mar 20, and are now below expected.
The conclusion drawn is that these Atypical Fevers represent people sick with Covid-19. And that Social distancing quickly reduced the spread of ALL viruses. Fevers dropped below expectation because isolation reduces the spread of influenza, rhinovirus, and coronavirus.
I have been plotting current cases and deaths for this epidemic all month, hoping to see a break in the exponential growth. That has not yet happened. But this cart is the first good news I've seen.
(Note: You must track Current Cases, not Cumulative Cases to see the real exponential growth. Recovered & dead patients do not spread the disease. So the graph of Cumulative Cases will fall below exponential growth early due to attrition, not effective isolation.)
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This company Kinsa sells internet connected thermometers. Their "US Health Weather Map" (that I called a Fever Heatmap) shows areas with more fevers than normal. Under the map note the chart of fevers vs Date.
Normally (sans epidemic) these fevers are from flue and colds. On the chart, the blue line extending thru May is the number of fevers expected. The Orange line is the Observed number, and Red shows fevers exceeding the expected range.
This data is recorded by Kinsa's servers as their customers measure their temperature. As such it is 5-10 days (my estimate) ahead of the case numbers reported by doctors and hospitals. This is because people wait until they feel really sick before calling a doctor.
Therefore, these numbers are timely, but harder to interpret. Remember these are all fevers, not just SARS-COV2. Also this is most certainly NOT a random sampling of the population. The sample must be small, and skewed by income and age.
That said, what the chart shows is that in the USA, fevers exceeded the expected range about Mar 9, then fell back into the expected range about Mar 20, and are now below expected.
The conclusion drawn is that these Atypical Fevers represent people sick with Covid-19. And that Social distancing quickly reduced the spread of ALL viruses. Fevers dropped below expectation because isolation reduces the spread of influenza, rhinovirus, and coronavirus.
I have been plotting current cases and deaths for this epidemic all month, hoping to see a break in the exponential growth. That has not yet happened. But this cart is the first good news I've seen.
(Note: You must track Current Cases, not Cumulative Cases to see the real exponential growth. Recovered & dead patients do not spread the disease. So the graph of Cumulative Cases will fall below exponential growth early due to attrition, not effective isolation.)