Youyang Gu, an independent data scientist, has created a statistical projection model for Covid-19 (https://covid19-projections.com/) that uses machine learning techniques to fit a classical SEIR infectious disease model to the data for daily confirmed cases and deaths, taking into account the effects of social distancing and other factors. From the results I’ve looked at, it appears to be one of the better performing models around. The plots below show results for Switzerland, USA and United Kingdom based on data up to 31 May.
The second plot for each country shows R-t, the effective reproduction number at time t. When R is greater than 1, the epidemic is growing exponentially, and when R is less than 1 it is declining. The basic reproduction number in the absence of interventions to reduce transmission, R0, is typically around 2 for most countries, depending on factors such as population density and crowding. R0 was close to 4 for New York for example.
Looking across the country projections, it is interesting that R-t is currently slightly below 1 for countries such as Switzerland and UK, and marginally above 1 for the USA. It is more substantially below 1 for a few countries such as Norway and Australia, and above 1 for some countries, eg. Brazil, Russia and Nigeria.
A lot of people have now published strong criticisms of the IHME modelling, many identifying the major problem of fitting a mathematically symmetric curve to the epidemic which I noticed early on. Youyang Gu also compares IHME projections with his and shows severe under- and over-estimation issues with the IHME projections, which change wildly with model updates and iterations. See the plot below for a comparison.
“Models are going to make wrong predictions, but it’s important that we correct them as soon as new data shows otherwise. The problem with IHME is that they refused to recognize and update their wrong assumptions for many weeks. Throughout April, millions of Americans were falsely led to believe that the epidemic would be over by June because of IHME’s projections.
“On April 30, the director of the IHME, Dr. Chris Murray, appeared on CNN and continued to advocate their model’s 72,000 deaths projection by August. On that day, the US reported 63,000 deaths, with 13,000 deaths coming from the previous week alone. Four days later, IHME nearly doubled their projections to 135,000 deaths by August. One week after Dr. Murray’s CNN appearance, the US surpassed his 72,000 deaths by August estimate. It seems like an ill-advised decision to go on national television and proclaim 72,000 deaths by August only to double the projections a mere four days later.
“Unfortunately, by the time IHME revised their projections in May, millions of Americans have heard their 60,000-70,000 estimate. It may take a while to undo that misconception and undo the policies that were put in place as a result of this misleading estimate.”