First, here’s the link to the current US Centers for Disease Control (CDC) situation reports. As the National Hurricane Center is the official word on hurricanes, the CDC is the official source for information on diseases. The DHS/FEMA “ready.gov” site has some good advice on disaster planning, including pandemics.
Please be careful of other sources – even the major media (and especially bloggers – yes, even well connected and informed sites like this one) – and be careful of how CDC data is interpreted. Determining risk in a dynamic situation like this is tricky. For example … from the New York Times today:
Experts have said that, based on the number of dead, the total number of cases in Iran is probably much higher, as the illness linked to the virus appears to kill about one of every 50 people infected.
I’d be really interested in hearing exactly what was said to the reporter(s). There is no doubt that with 14 deaths, based on what we know, there would be a lot of infections. But the statement that “the virus appears to kill about one of every 50 people infected” is extremely misleading. A more accurate statement is that it appears to kill about one in 50 people who were able or sick enough to seek medical care and were diagnosed as having COVID-19. The present state of understanding of COVID-19 (as of Monday, 24 Feb 2020) is that it seems like a lot of people get infected and don’t need to seek out medical care. There is also uncertainty in the mortality in that especially in China it is likely deaths are under-reported. But using the data from outside China, 1 in 50 of people who were sick enough to be checked seems reasonable. So what does than mean? Let’s say that conservatively only 1 in 2 people seek care – the other half think they just had normal flu or a cold. That would make the rate 1 in 100 (1 percent). But the likely number is more like only 1 in 10 people get sick enough to seek medical care. That makes the rate 0.2 percent. So you can see how sensitive the numbers are to figuring out how many people were actually exposed, and then got sick.
Exposed, infected, mildly symptomatic, sick, hospitalized, and/or died. All these categories are important, and have to be carefully assessed. If you are exposed, how likely are you to you to become infected? If infected, how bad will it be, how much medical care will you need (if any), and so forth? At this stage we don’t have great data (thanks, China) to get firm handle on some of these numbers – which means reporters have to take extra care to avoid either underestimating or, as seems to be the case here, overestimating, the real risk.
Addendum: The Diamond Princess was a pretty good test case to see what is going on independent of Chinese stats. Out of 3700 passengers and crew, 634 people have to date tested positive, 328 are to date asymptomatic (not sick), 306 are sick to one degree or the other. 3 have died. So assuming those numbers hold, that’s about about a 10% morbidity rate (got sick) and 0.1% mortality rate (died), in a pretty bad environment for infection and spreading (most of the 3700 probably were exposed to one degree or another), but with good health care. Usual disclaimers, small sample size, blah, blah – especially for mortality. But morbidity is the interesting stat from my perspective, and one that says this isn’t so bad – from a medical standpoint. Perspective: the 2017-2018 influenza season, which was the worst in the last decade or so, in the US the morbidity rate was 13.8% of the total population, 6% had some interaction with a health care provider. 0.25% required hospitalization, and 0.018% mortality rate.
Additional note: To a large extent we are playing a guessing game with the numbers, especially the mortality rate. People are extrapolating mortality rates by multiplying some rate based on reported cases (which drastically underestimates exposure) times the US population and getting numbers like 27 million sick and 270 thousand deaths. But as noted, the Diamond Princess numbers are probably an extreme case with respect to infection rates; even a bit more isolation (as in a typical US city with lots of single family homes, and more space per person, etc.) are likely to have smaller rates.