Tag Archives: pandemic

Covid Act Now

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This is a new site that gives a Covid risk rating based on five indicators: daily new cases, infection rate, test positivity, ICU headroom, and contacts traced. They try to give the same information by county, but they only have the data to provide a couple of the indicators at the county level. I know this data exists for my county, but it must be collected and stored (or not) differently in different counties and different states, so that there is no single organized database of it. This is the kind of thing the federal government could provide leadership on, and once again, they are just failing us in epic fashion.

I’ve added this to my running list of Covid data and simulation sites.

U.S. still isn’t screening international arrivals!

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In looking for that explanation of why some countries have largely dodged the coronavirus bullet while the U.S. is melting down, many people are focused on masks. I wonder if the almost total failure to screen airport arrivals could be the single most important factor. Thousands of plane loads of infected people from Italy landed in the U.S. northeast airports in February and March. The CDC’s screening and tracking protocols completely broke down, and it got out of control before there was any chance to contain it. Fast-forward to June, and they still aren’t effectively screening airport passengers!

Then we arrived in the US. No one at Dulles International Airport checked passengers’ temperatures. SAA had given each passenger health forms to fill in for the US authorities. No one asked for them. No sanitisers were on offer. No social distancing was practised in the immigration queues. People literally breathed down my neck. In Joburg the 2m apart rule was strictly observed.

At the immigration counter my passport was stamped and the very nice border policeman said: “Welcome to America.”

I waltzed over to baggage reclaim, got my luggage and left. I could have walked into the US coughing, sweaty and feverish and not a single authority would have known — they hadn’t bothered to do a basic check that I wasn’t indeed feverish.

JUSTICE MALALA: What three American airports taught me about Covid-19 and political leadership

Before it gets to the U.S. arrival, the article recounts the strict measures in place in South Africa (“one of the nations Trump included in the class of “shithole countries” – direct quote from the article). I’m not familiar with this person or publication, by the way, but it matches my experience traveling in Southeast Asia (Singapore and Thailand specifically) during the 2009 swine flu epidemic. Temperature screening and screening questionnaires were everywhere, beginning the moment I arrived at an airport, and continuing in shopping centers, on public transportation, etc. It was all polite and professional, but I knew that if I developed symptoms I would be taken to a government-run quarantine center for 14 days. (And as long as they had three meals a day and a decent internet connection, that didn’t sound like the end of the day!) Thailand and Singapore have both handled this pandemic very well. Thailand in particular is a middle income country with (until recently) a lot of back and forth travel to Wuhan, China.

You can argue that the “second wave” or “second peak” horror show now unfolding in the U.S. can be pinned on poor state and local leadership, but the early failures of airport screening, tracking, and testing were squarely on the federal government’s shoulders, and they not only failed spectacularly compared to most other countries, they haven’t learned anything!

coronavirus trackers and simulations revisited

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Update: December 13, 2020 (and from time to time since then, I update links if I notice they are broken)

This post is getting a surprising amount of attention. I don’t normally update posts, but I am updating this one since it is getting attention and the commentary in the original post is significantly outdated. Rest assured, if you are a historian in the far future studying what I was thinking back in June 2020, I have kept the original post at the bottom. I am keeping all the links, just grouping them somewhat and removing (from this section) the outdated commentary. (Thank you, Word Press, for making a simple copy-and-paste operation like this beyond excruciating.)

Data Trackers

  • Johns Hopkins – map, stats, access to data sets
  • New York Times – a national (U.S.) map by county and plots by state (now, with a paywall! as of 7/30/21. Which I will never pay because WEAPONS OF MASS DESTRUCTION!)
  • Financial Times – similar to others, but they look at excess deaths a little differently and have some interesting graphics
  • BBC – similar to NYT, but international
  • CDC – changed this link to their “COVID-19 by County” page on 2/26/22; the updated recommendation is to mask indoors if new cases in your county are 200,000 per 100,000 population per week, AND if the number of people entering the hospital and/or in the hospital is above certain thresholds. It’s a little hard to find the data and figure out yourself, so if you trust the CDC (and who wouldn’t?) you can just type in your county and they will tell you if it is high/medium/low.
  • https://coronavirus.thebaselab.com/ – a variety of maps and plots
  • City Observatory – intermittent data-based articles and maps
  • Our World in Data – excellent interactive country-level data, maps, and plots. A tip – you can also type in “world” or the name of a continent in the country box.
  • https://aatishb.com/covidtrends/ – a very clever animated time series of growth in cases over time, by country
  • Reuters – just more numbers and maps, similar to NYT
  • Covid Act Now – state-level data and communication in a simple, easy to understand index format
  • Harvard Global Health Institute COVID Risk Levels Dashboard – similar to Covid Act Now, but less simple and less easy to understand. Seems to have more ability to drill down into county-level data, although when you do that much of it is blank.
  • Wastewater surveillance from “Biobot Analytics” – added 4/30/22.

Simulations

  • University of Washington IHME – the best place I have found for understandable future projections. At the state level.
  • FiveThirtyEight – compares different models (no longer updating as of 7/30/21)
  • https://covid19risk.biosci.gatech.edu/ – This site calculates the probability that someone in a group of a given size is infected, based on the estimated rate of active cases in a U.S. state.
  • MicroCOVID – a risk calculator based on local data and allowing you to adjust your risk tolerance and try out various scenarios (added 8/8/21), such as “one night stand with a random person” (on the latter, please remember there are other diseases besides just Covid-19, for example antibiotic-resistant syphilis…)
  • Covid-19 Forecast hub – another visualization of various models and ensembles of models

Vaccine Trackers

Local Pennsylvania/Philadelphia Interest

  • The state of Pennsylvania has a useful dashboard which they have now made public (or it was public before and I didn’t notice.) It compares cases, positive tests, and hospital data for the current and last 7-day period, at the county level.
  • Speaking of Philadelphia, a shout out to the Philadelphia Health Department which provides some open downloadable data.

Miscellaneous Stuff

Original Post (June 27, 2020)

I decided to list out and summarize the variety of trackers and simulations I’ve mentioned in previous posts. Like many people (in the U.S. Northeast at least), I was glued to coronavirus info on various screens from roughly mid-March to mid-May, then my attention started to gradually drift to other things as the situation got better. Now, it seems that it has either stabilized at a not-quite-out-of-the-woods level, or is slowly reversing itself as we see other parts of the country start to be affected more seriously (sorry if you are reading this and are being affected, we in the Northeast take no pleasure in your suffering, I promise, although we suggest you turn out any bigoted anti-science politicians in your area who are letting this happen.) Anyway, I find that I am interested in starting to look at trackers and simulations again on a daily basis. These are in the order I discovered them.

  • Johns Hopkins – a neat map early on, although now the entire world has become a blob. Still a good place to stare at data.
  • New York Times – a national (U.S.) map by county and plots by state. seems to load even though I have used all my free articles for the month.
  • BBC – they update continuously but I’m not sure if this link will be to the latest
  • CDC – this is what I would have predicted would be the go-to source of information and expertise if you asked me before all this started…but it’s mediocre at best. Yes, that just about sums it up.
  • https://coronavirus.thebaselab.com/ – a variety of maps and plots to stare at, not my first stop but a little different if I am tired of others
  • University of Washington IHME – still the most informative state-level simulations I have found, accounting for hospital capacity among other things
  • City Observatory – they did an awesome analysis by U.S. metro area, which I have not seen anyone else do (human beings interact with each other socially and economically in cities and their suburbs, which often cut across states, and states often contain metro areas that are not connected much socially or economically. Economists, social scientists and urban planners know this of course, but nobody else studying the epidemic seems to have figured this out. Seriously, other data visualization and simulation sites, you can do this, it’s just a matter of grouping data by counties.) Unfortunately, they quit updating it and have not automated it. I still check every now and then to see if they have picked it up.
  • Our World in Data – pretty much every conceivable way of looking at data by country. I like to look at confirmed deaths per million across countries. By this measure, the starkest contrast is east vs. west. The eastern countries were hit first, hard, and without warning, and their death rates are very, very low. They have a variety of government types, responses, ethnicities and cultures. I just don’t think anybody has come close to explaining it. The U.S. is in the middle of the pack of western countries, which somewhat contradicts conventional wisdom and suggests news organizations are making the obvious error of not normalizing by population.
  • https://aatishb.com/covidtrends/ – an animated time series of new confirmed cases in the past week vs. total confirmed cases, both on a log scale, by country. As I write this, shows the beginning of a concerning uptick for the United States, and Brazil out of control.
  • Reuters – I actually never wrote about this one, but it has a map and some numbers.
  • FiveThirtyEight – they have an aggregation of various simulation models out there. New York and New Jersey look like a stream sprayed horizontally out of a garden hose, while Texas and Florida (today) look more like a fire hose.
  • https://covid19risk.biosci.gatech.edu/ – This site calculates the probability that someone in a group of a given size is infected, based on the estimated rate of active cases in a U.S. state. I assume it’s estimated active cases, anyway, or it wouldn’t make sense. It would be better by metro area (seriously guys, someone just get this done), but still a nice idea. I’m in Philadelphia, but I figure the New Jersey numbers are probably the most applicable.
  • Covid Act Now – provides a composite risk index at the state level, and county when county level data is available in the right format (which is not that often)
  • Harvard Global Health Institute COVID Risk Levels Dashboard – keeps it simple with just data on new cases, but gives you a variety of nice mapping, charting, and tabular formats to slice and dice the data at country, (U.S.) state or county level.
  • The state of Pennsylvania has a useful dashboard which they have now made public (or it was public before and I didn’t notice.) It compares cases, positive tests, and hospital data for the current and last 7-day period, at the county level.
  • Speaking of Philadelphia, a shout out to the Philadelphia Health Department which provides some open downloadable data.
  • I look at the FAO food price index on occasion. It’s falling lately. Sometimes I look at oil and gold prices, and how many Special Drawing Rights can be bought with one U.S. dollar. Oh and, the Rapture Index is at an all time high!

bodies stacked like cordwood

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Here goes…I generally support police-court-prison reform and policies to reduce violence in all its forms. I support policies to help right past and present injustices, both race and class based.

I’m very concerned about thousands of people out on the streets just when we thought we were getting Covid-19 under control. This is a disease that has killed black people and poor people disproportionately. About 100,000 people dead in the last couple months vs. about 1,000 per year killed by police (which is certainly too much). Now is just not the time, in my view. If we wanted to devise an experiment to find out whether people gathering in the streets by the thousands, packed in like sardines but largely wearing masks, would reverse our progress on Covid-19 or not, this would be the experiment. It would not be an ethical experiment!

A history lesson: In 1918, Philadelphians took to the streets by the thousands in the midst of the flu epidemic that year, with devastating consequences. From Smithsonian:

When the Fourth Liberty Loan Drive parade stepped off on September 28, some 200,000 people jammed Broad Street, cheering wildly as the line of marchers stretched for two miles. Floats showcased the latest addition to America’s arsenal – floating biplanes built in Philadelphia’s Navy Yard. Brassy tunes filled the air along a route where spectators were crushed together like sardines in a can. Each time the music stopped, bond salesmen singled out war widows in the crowd, a move designed to evoke sympathy and ensure that Philadelphia met its Liberty Loan quota…

Within 72 hours of the parade, every bed in Philadelphia’s 31 hospitals was filled. In the week ending October 5, some 2,600 people in Philadelphia had died from the flu or its complications. A week later, that number rose to more than 4,500. With many of the city’s health professionals pressed into military service, Philadelphia was unprepared for this deluge of death.

Attempting to slow the carnage, city leaders essentially closed down Philadelphia. On October 3, officials shuttered most public spaces – including schools, churches, theaters and pool halls. But the calamity was relentless. Understaffed hospitals were crippled. Morgues and undertakers could not keep pace with demand. Grieving families had to bury their own dead. Casket prices skyrocketed. The phrase “bodies stacked like cordwood” became a common refrain.

Smithsonian

Let’s hope this is a history lesson and not history repeating itself!

In another case of “let’s hope this is a history lesson”, Trump is calling for a military crack down almost exactly 50 years (May 1970) after the Ohio National Guard mowed down protestors with machine guns at Kent State.

how are people really getting coronavirus?

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This blog post from a professor of epidemiology has some interesting logic. I don’t know this person, but they are a professor at a reputable university and I give their opinion some weight based on that. You can review their credentials and decide for yourself.

I took microbiology as a graduate student in environmental engineering, and I’ve done just a bit of microbial risk assessment since then. Which in no way qualifies me as an expert on covid-19. But this post did help me to think about some things harkening back to my classes, which are almost entirely absent from other media sources I am reading. In my classes and my professional work, there is a logic of dose response – you have to ingest a certain amount of material, and it has to contain a certain amount of a pathogen, for you to get sick. This usually has to do with small amounts of fecal matter present in the environment or water in my case, and the consequence typically is a bout of gastrointestinal distress curable with rest and fluids, although pretty much any disease is more dangerous to the very old, the very young, and the very sick.

That was a long preamble. You should read the blog post. But here is the brief summary:

  • If someone coughs or sneezes directly in your face, you are likely to get infected.
  • If you spend significant time indoors in a place where an infected person has recently coughed or sneezed, you are likely to get infected.
  • Other than that, you are not likely to get infected from someone breathing or even talking to you as you briefly pass on the street. You would need to talk to that person for at least 5-10 minutes to be likely to take in enough virus to get infected. That is just not very likely if you pass someone while walking, jogging, or biking. The advice of my local and state health departments is consistent with these facts. The behavior of people I observe in my neighborhood is not consistent with these facts. My behavior is consistent with these facts, even if other people in my neighborhood choose to have opinions that are not consistent with the known facts, and to try to impose those opinions on me.
  • Now, if you are indoors for awhile in a place where a lot of people are talking and breathing, and someone is infected, your odds of getting infected are high. This is why offices and schools are closed.
  • The bigger the crowd in the indoor space you are in, the more likely someone is infected. This is why conferences, religious services, sporting events, and Disney World are shut down.
  • So, people are getting infected when they have to be indoors around a lot of other people for a period of time, like in warehouses and meatpacking plants and unfortunately nursing homes. They are getting infected when they choose to attend large group events they don’t need to attend, like parades or worship services. And finally, they are getting infected when a family member goes out, gets infected, and brings it home.

plague lit

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Wired has an article on science fiction novels involving plagues, and over at the New Yorker is a long article from the more literary genre (Steven King appears to have breached this category!).

Wired mentions:

  • three Neal Stephenson novels: Seveneaves, Anathem, and The Fall, or, Dodge in Hell
  • The Expanse (which I have heard great things about but probably won’t read because the show has spoiled it for me)
  • Mars Trilogy by Kim Stanley Robinson (who I recently learned is a dude. I read the first book, and liked it, but didn’t love it enough to read the other two. It is one of those books I find myself thinking about though.)
  • Ender’s Game (big fan)
  • The Moon is a Harsh Mistress (I’ve been burned out just a bit on Heinlein, but maybe I’ll give this one a chance at some point.)
  • William Gibson. No specific books, just William Gibson. (I like that I have read William Gibson, but I don’t )

The New Yorker mentions:

  • A Journal of the Plague Year by Daniel Defoe, 1722. (Yes, it’s about that plague. Also know as the plague.)
  • The Last Man by Mary Shelley, 1826.
  • Oedipus Rex (mentions the plague apparently)
  • Angels in America (yes, AIDS counts as a plague, complete with a long incubation time, asymptomatic transmission, initial government denial and botched response, and eventual development of more effective treatments, although there is still no vaccine or absolute cure.)
  • The Masque of the Red Death by Edgar Allen Poe, 1842.
  • The Scarlet Plague by Jack London, 1912. (sort of a sequel to the Poe story, apparently)
  • The Plague by Albert Camus, 1947. (I didn’t realize Camus was that recent, but that is just me being ignorant.)
  • Blindness by Jose Saramago, 1995. (“brilliant” according to the New Yorker, but just sounds too depressing for right now.)
  • And of course, The Stand.

The science fiction book I keep thinking about though, which is not on either list, is Robots of Dawn by Isaac Asimov. In Robots of Dawn, life on Earth is nasty, brutish and short. But there is a race (of humans) who have moved to space, and they live hundreds of years in part by avoiding virtually all physical contact with each other. They can do this because the human population is very low on a large planet, robots do all the work, and they have excellent video conferencing facilities. Humans basically never come into close physical proximity, with the one exception that husbands and wives get together only for the purpose of making babies, which is surprising because you would think a futuristic civilization where robots do all the work would have discovered in vitro fertilization. At the very least, you could send a robot over to your wife’s place with a turkey baster full of…well, you get the idea.

I’m thinking about a 2020 summer reading theme. I don’t think I want a plague theme! I could do worse than dig into some Neal Stephenson novels I’ve missed. I could always go back and read some Edgar Allen Poe. I’ve never read The Stand, so maybe.

ferrets and coronavirus

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Ferrets are highly susceptible to coronavirus. Apparently, ferrets are susceptible to similar respiratory diseases as humans in general and are used in research for that reason. Cats are also susceptible, but dogs and farm animals generally aren’t.

If this were a movie, humans would eradicate the virus but it would persist in a small community of feral cats somewhere, mutate into something even more horrible, and jump back to humans.

more from Bill Gates on coronavirus

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You can still decide for yourself if Bill Gates is someone we should listen to on coronavirus. But he sounds cautiously optimistic, at least when it comes to developed Asia and the U.S.

[Someone asking Bill a question on Reddit: ]I read the Imperial College COVID-19 Response Team report as well as this explanation in a historical context. Essentially, it says that by doing nothing, 4 million Americans die. Through the mitigation strategy—i.e. social distancing and “flattening the curve”— it says that 1.1-2 million Americans will die. However, it also says that the suppression strategy, or “shutting everything down for 18 months”—will lead to only a few thousand people dying...

[Bill’s answer: ]Fortunately it appears the parameters used in that model were too negative. The experience in China is the most critical data we have. They did their “shut down” and were able to reduce the number of cases. They are testing widely so they see rebounds immediately and so far there have not been a lot. They avoided widespread infection. The Imperial model does not match this experience…

China is seeing very few cases now because their testing and “shut down” was very effective. If a country does a good job with testing and “shut down” then within 6-10 weeks they should see very few cases and be able to open back up…

Gates Notes

more coronavirus tracking

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This massive data analysis entry from Our World in Data is a pretty good example of how to take a data set and beat the crap out of it from every angle.

I like what they did. Since it’s by country, it allows interesting comparisons across countries but is not meant to provide local or regional-specific information. Countries are pretty big. My favorite trackers that are most relevant to my situation are still the City Observatory analyses of U.S. metro areas and the University of Washington simulations of available hospital capacity. The latter are by state.