1) After the shock of exponential growth, we seem to have been in a bit of a holding pattern for the past few weeks. Reported deaths per day have even started to decrease in most places. But the decrease is slow, and we're still losing 5000-6000 people per day, not to mention identifying ~70,000 new cases. That's about 4% of the number of people who normally die everyday worldwide. This is not as bad a catastrophe as we feared it might develop into, but it is a lot of people. Especially since this is the death rate after locking down and taking a torch to global economies, an emergency measure that is unlikely to be extended much longer.
2) The good news is that several countries have avoided the explosive increases we were seeing in March, and some have actually steadily reduced the total number of cases. Sweden got perhaps too much attention, but it is interesting that the mild action they went with was sufficient to at least stabilise the rate of increase (the active cases increase steadily there). Switzerland has done better, with a month of steadily decreasing total cases. And many developing countries have done much better than avoiding the worst-case scenarios. India slowly increases in cases (which is worrying) but it's far, far better now than scenarios that seemed possible to me; I feared bodies piling in the streets and social breakdown. Other countries such as the US have done considerably worse in containing the problem, despite having many advantages.
3) This brings us to the inevitable question: why? Why did some countries have massive outbreaks and others that seemed equally or even less prepared escape them? A month ago (seems like years) I wrote that there were several theories, ranging from the plausible to the wild: local temperature & humidity, degree of contact between generations, very small numbers of 'superspreaders', history of BCG vaccination, smoking preventing infection, and more. Amazingly, none of them has really accumulated much supporting evidence, and several have been weakened by new data. What we know well is pretty much the same as a month and a half ago: it's bad for old people. And having other health problems (respiratory, heart, obesity) probably matters; it seemed very plausible a month ago and I haven't really seen much more about this that changes my mind one way or the other.
4) One important detail is that a huge number of deaths seem to have happened in old-age/retirement/nursing homes - possibly as much as half the deaths in Europe. These types of homes are rare in developing countries, where populations are younger and the elderly typically live with their families. So the concentration of old people, perhaps along with poor health protocols for their caregivers, is likely to have been a massive contributing factor. Other major outbreaks, especially in the US, seem to have happened in prisons and meatpacking facilities.
5) In many countries, we are still not testing enough, and the testing we are doing is not designed well enough to help us understand the broader picture. So months into this pandemic, we still don't know with much precision how many cases there are out there, or how deadly the virus is. As a result of this poor testing, the stabilisation at 70,000 new cases per day may partly reflect the fact that testing has stagnated.
6) Testing was only one part of the solution that epidemiologists have been banging on about for months. The others are tracing (finding people who came into contact with infected people) and isolation (separating infected and at-risk patients from the rest of the population, sometimes including their families). As I've said, testing is in bad shape. And best I can tell, tracing and isolation are virtually non-existent in much of the developed world. Lockdowns will help temporarily but cannot be sustained indefinitely. I don't understand the lack of tracing and isolation efforts. This is yet another colossal institutional failure.
7) Forget contact tracing apps for now. Most people are aware that the basic versions that many governments want give away far too much privacy and are ripe for abuse. There are solutions to this, and Apple & Google have done really great work in pushing for privacy preservation despite pressure from governments (Europe fought against privacy!). But there are huge problems with even the versions that protect privacy. For one thing, protecting privacy means that the system is extremely vulnerable to attack by bad actors - trolls, rival companies and countries, and so on. It requires an improbably large fraction of the population to use the apps for them to work. And because of the way they are designed, there are simply too many false positives and negatives; people will soon ignore the warnings as a consequence.
8) So what would tracing and isolation look like? Massive amounts of human effort. It can be done! Forget South Korea, it does not even require much sophistication. The first state in India to get hit, Kerala, has had teams of people track down every person to come into contact with an infected individual and isolated them. They had doctors and counsellors help every affected person. They provided food and shelter for people in need during the lockdown, included hundreds of thousands (millions?) of migrant workers. Kerala has a population of 35 million people, comparable to most European countries and bigger than most states in the US. It's much poorer than either. It's had 4 deaths and presently 37 active cases. And it is not unique. A smaller state, Goa, apparently had teams visit every single household to check on them. It's a major tourist destination, and it has zero active cases! The US presently has about 7000 people to do contact tracing, for a population of 330 million. That's probably 2 orders of magnitude lower that what is needed. I don't know the situation in Europe and I would love to read about it if any of you have links you can point me to. But I suspect it's not good. I really don't understand why this is not being done, especially when there are large numbers of young people without jobs who would gladly help in this effort and are much less susceptible to infection themselves.
9) Shutdowns have been met with resistance in several countries. To be fair, some of them seem to have stabilised the situation enough that a lockdown may at present be causing more suffering than not. So we should expect some reopening soon. When this happens, we should expect a second wave in most countries (except for those like the US that are still working on their first). Without the tracing and isolation infrastructure, this might spiral out of control once again, and require subsequent lockdowns. I fail to see how any of this is supposed to save economies, especially since people voluntarily stay home even before lockdowns are declared. Stopping the damn pandemic is really the only path back to normalcy.
10) This pandemic has brought out some of the worst tendencies of the press, so I'd very strongly urge you not to pay attention to the story of the day. With rare exception, journalists don't have the training to understand and criticise science, so we have a lot of glowing reports about the latest drug study (Remdesivir! Hydroxychloroquine!) or estimate of disease incidence. Most of these studies are not good enough to pay attention to. Almost no study you will hear about is done well enough and at a scale that will substantially shift the present consensus. At best they will prove to be the basis for further, better studies. If you're going to try and track this sudden profusion of studies, you will exhaust yourself, give yourself false hope, and likely end up misinformed. The normal progress of science involves most studies having substantial weaknesses, and there is plenty of disagreement and argument around them. You don't hear about it because it doesn't make its way into the press ordinarily. Right now, much of the press is reporting the studies based on the authors' interpretations without offering you the criticism from other specialists. Or when they quote someone, they don't understand the topic well enough to show you who is more believable - the author or the critic. If you want to follow one science writer, read Ed Yong in The Atlantic.
11) Aside from the press, many health agencies and governments have also done a pretty awful job of communication. They have stressed certainties ("Masks don't work!") when evidence was weak or absent. When subsequent evidence has proven them wrong, they have earned mistrust and enabled the conspiracy theorists. If you want good information, go straight to the sources: epidemiologists are laying it all out for anyone to see on twitter.
12) Speaking of uncertainty: the question of whether people can be reinfected by the virus keeps popping up. We don't know for sure but there's good reason to expect immunity. It's worth keeping in mind two things when you see reports that someone has caught the disease a second time: (i) There are a lot of false negative and false positive tests. When someone is thought to have been reinfected, it's almost certainly because the test that declared them recovered was a false negative. (ii) Immunity is not perfect. If your probability of catching the disease goes from say 30% to 0.03% (warning: made-up numbers), I would call it strong immunity but you will still have a lot of people catching the disease a second time.
13) You've seen or are going to see big fights over how many people died because of the virus, because of the implied culpability associated with higher numbers. Already, there's plenty of people who are suspicious that deaths are attributed to COVID without testing the corpse. But why would we waste our limited tests on a dead person? And people die for a combination of reasons and it's frequently impossible to say that the precise reason was previous lung problems or heart disease and not COVID; in reality, the combination of factors led to the death. Also, plenty of people are dying without having been checked, so frequently we have no idea. How do we solve this problem? The most reasonable solution is to compare how many people are dying right now with the 'normal' number of people that die at this time of year. We usually define 'normal' by taking the average of many years because some years are better and some are worse. This is not perfect: there are fewer traffic accidents now, less pollution, less flu transmission because of lockdowns, and other factors. But it's the best simple answer. There are clever ways to adjust for the other factors, but they are complicated and the conspiracy theorists will accuse the scientists doing those adjustments of cooking the books. Just be aware that there's a simple and pretty reliable answer that you can calculate yourself.
14) We're now seeing a profusion of epidemiological models coming out. Keep in mind that for the most part they are not designed to tell you exactly what is going to happen. Instead, they tell you what is likely to happen if societies take different actions, so that we can decide about how best to respond. Any change we make (lockdown, reopening, voluntary distancing) changes the situation and makes the model predictions inaccurate. Criticising modellers for being alarmist when we have taken the actions they recommended to prevent their predictions coming true is both ridiculous and exactly what I said would happen in the first of these posts. Please fight these lousy critiques.
15) I've talked about different types of models and expressed my preference for mechanistic epidemiological models (specifically SEIR models) over phenomenological/statistical models (like the IHME model). I used to think that the basic versions I was taught had unjustifiable assumptions that make them ill-suited to making COVID predictions. But I'm now leaning towards the view that many of the complexities they ignore (variation in population density, number of people contacted, susceptibility, mobility, etc.) are not such a big problem, relatively speaking. The bigger issue is that all the models use parameters that are hard to measure directly, so instead we have to infer them from the very bad data we have on reported cases and deaths. None of the models is going to provide a precise picture of the future because of all these uncertainties; even the very best is likely to be wrong about the time of peak, total number of deaths, and more. But some are still better than others and if you're interested in predictions, I'd tentatively recommend https://covid19-projections.com/, https://github.com/ryansmcgee/seirsplus, https://mr-sir.herokuapp.com/main, https://epiforecasts.io/covid/posts/global/, https://covid19-scenarios.org/ as good resources. Keep in mind that ultimately, they all rely on data for their inputs. To the extent that the data has problems (and it does), this makes the model predictions have problems too.
16) We seem kind of stuck till we get a vaccine. The most informed voices are talking about a 2-year timeline for this; the fastest previous vaccine developed took 5 years. I have no expertise in this but if I had to bet, I think it will be done faster. That's because this situation is unprecedented and there are incredibly strong incentives at play. By dusting off every possible angle of attack and technology, skipping a lot of regulatory and testing hurdles, essentially throwing a million darts at the board, I imagine we will achieve this faster. You should not trust me on this, I cannot really justify this opinion.
17) That said, developing a vaccine is very different from deploying it at the scale of billions of people. So far, much of public health infrastructure has failed quite miserably. Much will depend on whether this shock enables the bureaucratic problems to be fixed in the next few months. But institutional knowledge and expertise is not easy to accumulate rapidly.
18) We don't know yet, but it seems likely that people who have recovered will suffer long-term health consequences. The toll from this pandemic is even higher than the body count.