Modeling COVID-19 outbreaks is an important public health strategy in managing this disease. Join me as I go over a crucial paper published in Science that explains how immunity and seasonality affects modeling and the decisions we will have to make.
Update: Hi everyone, thanks for watching! I left a couple of key things out of my analysis of the paper in an attempt to be clear and brief (and may have failed on both accounts ). All models are based on assumptions, many of which won’t hold true in the future which is why they are constantly updated (and the authors addressed this extensively). My take on their work was that they were not trying to predict next year but to elucidate two of the key questions: seasonality and length of immunity. The point I really wish I had covered is that the models assume we do nothing on the second wave which, of course, we will. For example, in the seasonality model with a 8 week quarantine, they show an impressive flattening of the curve in the first wave and then predict a large second wave if we do nothing. But one take away could be: well timed quarantines in the future could also flatten the curve in future waves as well and could be a mitigation strategy. As a side note, I am psyched to hear people are enjoying these. As an extroverted educator who is now isolated at home, I am finding this keeps my mind active and I would like to believe it is adding to the conversation in some small way. Cheers, Mark
