NYC Public Health Data

Yesterday I posted about Lack of Imagination over at Epsilon Theory. In that piece Rusty references some fantastic public health data published by NYC Health. They have a number of datasets available, the most interesting/useful one currently being influenza-like admissions to NYC emergency rooms.

What's clear in the data is that there's an abnormal spike in March that doesn't exist in any prior year, even in 2018, which appears to have been a particularly bad flu season.

Influenza-like admissions to NYC emergency rooms, 12/31/2017-3/16/2020

We see the same trend if we change the Syndrome filter to Respiratory, which presumably would be the admission reason listed for people with later-stage COVID19 respiratory issues.

Respiratory admissions to NYC emergency rooms, 12/31/2017-3/16/2020

This level of transparency into the health care system is incredibly useful at a time like this. The official coronavirus confirmed case numbers are extremely low, due primarily to the fact that almost no testing has taken place up to this point (though that will likely change this week). These datasets provide a useful proxy for what's actually happening in hospitals, despite what the lagging testing data says.

The NYC syndromic dataset query tool can be accessed here. To get the graph/filter view, click on one of the cells when the page loads.

I'm inspired that the NYC government collects and publishes this data. Other cities should follow their lead and provide this level of transparency. It gives local news organization and individuals a near real-time view of hospital capacity, which is especially important in the midst of a public health crisis, where hospital capacity is one of the key metrics we have to manage to effectively contain and treat the virus.

#covid19, coronavirus, public health, open government

A Collection of COVID-19 Resources

For my own education and preparedness, I've begun compiling a list of resources related to COVID19; news articles, personal accounts, data, and anything else that increases understanding of the virus, potential dangers, containment strategies, effects, etc. I've tried to filter the highest quality and most accurate information (the signal) from the speculative and incorrect (the noise). I've built this list primarily for myself, but hopefully it'll prove useful to others.

Context (why I've compiled this post)

The wealth of information about COVID19 has become overwhelming. As the virus moves through the world, any one person's ability to distinguish the signal from the noise becomes impossible. This is especially true here in the United States, as the virus has taken full hold of daily life, much as it has in other countries.

I've come across an unbelievable number of different resources regarding Coronavirus aka Covid-19 over the last few days, most of which have not come from traditional news organizations or media sources, which focus primarily on official numbers (Ben Thompson has written about this phenomenon in great detail in his post Zero Trust Information).

I'll continue to update this post as I encounter new information.

Finally, I want to be clear: I'm not a medical or public health professional. I'm just a person trying to separate the signal from the noise.

Personal Accounts

Twitter has once again shown what a powerful platform it can be for sharing and spreading knowledge, and transmitting it to the world in a way that otherwise wouldn't be possible.

I've encountered a staggering number of powerful, informative, and often heart-breaking personal accounts on Twitter. For me personally, they have been some of the most effective in improving my understanding and empathy for what is actually happening; what it's like to be a citizen or Doctor working at an overwhelmed clinic in Northern Italy. The actual human cost and experience has been largely downplayed in the mainstream media, reduced to numbers, and often focuses on policy-makers and governments rather than on the ground experiences (this has begun to change somewhat, but the stories shared on Twitter were weeks ahead of the rest of the media).

The Italy Situation

Italy is worth isolating and focusing on for a number of reasons. First, Italy has emerged as the second-most deadly outbreak of COVID19, second only to China, making it a very useful contrast (and warning) to the tactics that seem to have worked in China and South Korea (many of which do not seem to have been adopted in Italy). Second, Italy could very well be a harbinger of things to come in other western countries. Indeed, on March 14, both Spain and France locked down their countries in nearly identical fashion.

The Italian health care system is effectively operating in combat triage mode. They're rationing critical health care supplies and making impossible decisions:

Doctors and nurses in Italy face an impossible dilemma: who to treat and who to let die. - Yascha Mounk

From an Italian doctor - "It's war"

Why It's So Deadly In Italy

This post tries to understand why the death rate is so high in Italy. It seems to come down to the fact that a much higher percentage of elderly Italians been infected compared with South Korea:

Grouping the age in ten-year-intervals and comparing the percentage shares of cases that fall into each age group reveals a striking dissimilarity between South Korea (red bars) and Italy (green bars): Recently, 3% of all confirmed cases in South Korea were at least 80 years old. At about the same time, 19.1% of all confirmed cases in Italy were at least 80 years old.

The extraordinary decisions facing Italian doctors

Yascha Mounk wrote this thread, which is also summarized in this Atlantic piece.

New York

Looking at leading indicators using publicly available NYC health data Ben Hunt suggests that NYC hospitals may already be getting overwhelmed by an abnormal spike in flu-like symptom admissions. Normally admissions to emergency rooms due to flu-like symptoms spike in the early winter months (Nov-Dec), but NYC ER admissions are seeing this currently in late February/early March.

The Python and the Pig


If you're trying to understand how quickly COVID19 can spread within your community, look here:

COVID19 Case Data Sources

  • Johns Hopkins Coronavirus COVID-19 Global Cases
    This data is much more accurate than the "official" CDC data below, which is only based on the extremely limited number of CDC-administered/approved tests performed.
  • Johns Hopkins Github Virus Data
    The data powering the above dashboard.
  • CDC Coronavirus Data
    I take this data with a giant, enormous grain of salt, because it only accounts for the number of tests the CDC has performed or overseen. My conservative guess (pure speculation) is that the number of tests performed probably doesn't even account for 1% of the actual real cases on the ground.

Products, Resources, Getting Involved

A lot of efforts are underway to help organize information:


Coronavirus: Why You Must Act Now
I've probably seen this post shared more than almost any other. It makes a strong case for policy-makers taking aggressive action to slow the growth rate, aka flatten the curve.

Required Reading - How we got here

These two seminal pieces by Ben Hunt (aka @EpsilonTheory) provide some background on how we arrived at this moment. First, by examining the political corruption amongst WHO senior leadership (The Industrially Necessary Doctor Tedros), and second, by looking at how horribly the US government has botched the testing situation – Don't Test Don't Tell (10 Days Later).


Korea bending the curve

Sacramento turns off quarantine as of 3/10/20

Health Effects

On the long term health effects of covid19:

#covid19, coronavirus