COVID-19 Watch

Flu season is about to begin in the Northern Hemisphere. I got the flu vaccine this week to get ready.   It seems likely that catching both the flu and COVID-19 at the same time would increase risk of both mortality and of serious side effects. Worse, an increase in flu patients could increase the pressure on an already stressed healthcare/hospital system.  Several news outlets have been predicting a crisis as the flu and the coronavirus collide.  While I think that there are risks associated with the convergence of COVID-19 and the flu, I was skeptical that there would be a massive flu burden in the US this season all the way back in March when this fear was first mentioned. I am even more skeptical now. Why is that?  There are many reasons, but the most significant is that the level of physical distancing needed to keep COVID-19 under control should crush the flu into near nonexistence. And recent data from the Southern Hemisphere that just finished their flu ...

COVID-19 Weekly Update:  Graphs for my estimate of the % of the population that are actively infected are now finally available. They are not yet in the user interface for the web page, but you can view them from the git repository here: https://github.com/jlc42/jlc42.github.io/tree/master/figs/PercentActive I believe that this is the most useful statistic for determining the risk of a given activity. For example if you live in a location with 3% active, and you participate in an activity with 100 randomly chosen people, then on average, three people in that activity could be contagious.  Some examples: In the USA (taken as a whole) about 1.25% of the population is actively infected. So in a group of 100, you would expect just over 1 person to be contagious.  Some places in the US are significantly better than others: In Utah, the % infected is nearly 3%, so in a group of 100, we would expect around 3 people to be contagious.  In New Mexico, the % infected is 0.5%, s...

Utah is a good data point for the impact of school openings on COVID-19 case spread.  Utah opened schools in person mid August. At the time there was debate about whether opening schools would actually increase the spread of COVID-19 because children have more mild symptoms, and it was hoped that this also meant that they didn't spread the virus as well as adults.  We knew that this was likely true for children under 10, but we also knew that children over this age spread the virus as well as adults. Therefore, opening schools for older children, as well as colleges, should cause an increase in spread.  This is in fact what we can clear see in the Utah data: This is not a single one day noise spike. This trend is clearly visible in the average, over several days. Notice also that cases are rising faster than tests, so this is not the result of increased testing. Cases are now above tests in my figure. The scale is set such that when cases are above tests, that means that ...

Over the last week we have been talking about the mystery of second wave resistance across the US. After about 25% of the population is infected and recovered, there is remarkable resistance to a resurgence of the virus, even after states "reopen". This is mysterious because immunity thresholds should be around 66% if the R0 of SARS-CoV-2 is really around 3 as we believe. One likely explanation for this is that personal behavior is providing the additional protection. In the past I have used Google mobility data to characterize the level of physical distancing. But this only captures how much we are moving around, and can't capture how careful people are being. However, there is now some interesting polling data available that may capture some of these effects. Ryan Burge has provided excellent visualizations of the steps the American public is taking from the DFP COVID-19 Tracking Poll: (see: https://twitter.com/ryanburge/status/1301887909675569152/photo/1 ) Approximate...

 Today the USA passed 200,000 deaths.  World wide we are nearly at 1 million deaths.  Source: https://www.worldometers.info/coronavirus/country/us/   Early predictions back in March were that between 100,000 to 200,000 people might die from COVID-19 in the USA if we did nothing.  We didn't do nothing. But what we did was just as ineffective.  Now over 200,000 are dead, worse than the worst of the projections. There is a narrative that these projections were wrong... too "high".  It turns out that they were actually far too low.  They were wrong, in other ways. The assumed fatality rate was too high in the early models, but they under-estimated how many would be infected. They over estimated how quickly the disease would decline, and they severely over estimated the quality of our response. We failed, beyond the wildest imaginings of the worst case models from March. 

Yesterday we discussed regions that were initially hard hit , to determine how resistant some of those places have been to a second wave, places like New York, Spain, France, and Italy.  Today we want to discuss regions that were not initially hard hit, where immunity levels are very low, and the virus has a lot of room to spread if it were to get out of control there.  Excellent examples of this would include New Zealand, South Korea, and even China, where their vigorous response prevented the virus from spreading extensively beyond Wuhan. Each of these countries, in their own way, demonstrated that failure was not inevitable, and that it was possible to control (and even completely eliminate) the virus. They also demonstrate that the economic cost of COVID-19 was best minimized by first aggressively controlling the virus.  However, recent rises in cases brought this narrative into doubt. In July/August each country saw new cases rise again. And with an almost entirely ...

Predictions of Rt in the USA as a whole continue to be below 1 (currently 0.985), meaning that the rate of new cases are decelerating (you can thing of Rt as an estimate of the acceleration):  Despite this fact,  IHME is now predicting over 400,000 deaths by the end of the year, because of a proposed large second wave coming in the fall. But if new cases are currently slowing down, why would they predict that they would rise again in the fall?  Other historically more accurate models do not predict this same large second wave. IHME is predicting that daily deaths will rise between now and November, while COVID-19 Projections predicts that they will fall between now and November 1st.  The issues revolve around the surprising resistance to second waves that we have already seen in hard hit locations around the world. For example, in the US, the second peak of infections after the lockdowns were eased all happened in locations that were not initially hard hit.  T...