Wednesday COVID-19 Briefing

Top news, reports and insights for today:

  1. Curated headline summaries for Wednesday:
  • Trump does better in COVID-19 ravaged states than expected. Exit polls show voters worried about the economic effects of lockdowns if the encumbant lost. Many voters fell victim to the false belief that policy makers must choose between public health and the economy (see Main Point 3). Meanwhile, the economic damage of the pandemic have been much less in the countries that have controlled the epidemic best (VOX)
  • A study from Mount Sinai found that SARS-CoV-2 virus was circulating in New York city in February, weeks before the first case was noticed. The study also shows that as many as 22 percent of New York City residents may have been infected, still far from the herd immunity threshold (BGR)
  • Dr. Deborah L. Birx, who has carefully straddled the line between science and politics as she helps lead the Trump administration’s coronavirus response, delivered a stark private warning on Monday, telling White House officials that the pandemic is entering a new and “deadly phase” that demands a more aggressive approach (New York Times)
  • A study of cell phone data shows that people who live in low income neighborhoods are not able to social distance to the extent those who live in affluent communities. Socioeconomic barriers to social distancing is part of why COVID-19 disproportionately impacts residents of low income communities (Nature Human Behavior)
  • Federal officials add pregnant women to high risk groups after CDC study finds that COVID-19 increases risk of preterm delivery and the need for intensive care (New York Times)
  1. U.S. cases keep climbing, crashing through 9 million. Latest million took just 2 weeks.
     It took three months for the first million U.S. official COVID-19 cases to be identified and tallied. From 8 to 9 million took just 2 weeks, the fastest million thus far, and a further indication that the coronavirus outbreak continues to accelerate (Figure A). As the U.S. edges toward 100,000 cases a day, more than half a million cases are being added each week (Figure B). A part of the current rise is due to increased testing. However, Figure C shows the trends in daily cases (red) and daily tests (blue) averaged over 7 days since September 1. The inflection point in cases happened on October 2, starting a rise from 42,000 daily cases to the current levels above 85,000. In that time, tests rose from 1.03 million a day to 1.24 million, a jump of only 16%. Since October 2, daily cases doubled while testing increased less than a quarter. Testing actually rose faster in September, while cases were fairly flat.
    Figure D is our old friend, the state daily case growth-factor situation. Where are cases rising fastest? The Midwest and Northeast, where only Oklahoma and Vermont are seeing weekly cases fall. In the Midwest, weekly cases grew by 50% or more in Iowa (+70%), Kansas (+85%), Michigan (+59%), and Minnesota (+61%). Showing no light at the end of the tunnel, weekly cases are still rising in North Dakota (+46%), South Dakota (+22%) and Wisconsin (+14%). Despite this, President Trump won or leads the election results in all these states except Wisconsin, Minnesota, and Michigan. In the Northeast, 9 states saw weekly cases grow 20 percent or more, led by Maine (+116%). Those who follow me will recall that I showed you a map over the weekend indicating that case explosions are tracking with the arrival of super cold air (e.g., Maine, Montana, Idaho, the Dakotas and Colorado).
    Bottom line: Cases are surging substantially in the U.S. which is only marginally a result of rising testing. At the current rate, adding a million cases every 2 weeks, the U.S. may reach 13 million cases before 2020 ends. There is no end in sight to the surge of cases in the Midwest and Northeast in particular. The Trump administration may win another term because of the epidemic, not despite it (see Headline 1).
Figure A
Figure B
Figure C: From COVID Tracking Project:
Figure D
  1. Government actions to control the epidemic AND maintain economic health can work: the German case
    I vish to talk about Djermany (silly accent). As I process my own reactions to the election, I am struck once again by how wrong the polls and pundits were. Most experts believed that the recent surge of cases in battleground states would hurt the President at the polls. That was largely not the case. There was no Biden landslide spearheaded by worried swing voters in the hard hit states. Trump won the Dakotas, Iowa, Montana, Idaho, Utah, Kansas, Nebraska, and Missouri, all states that have been on fire with COVID-19 in recent weeks. Exit polls indicate many voters were worried that a Biden win would mean further economic harm from tougher lockdowns. In other words, it looks like the coronavirus actually helped the President.
    That idea, that policy makers must choose between the competing goals of controlling the outbreak and supporting the economy, appears to underly this phenomenon. It is, sadly, a widespread view that such a choice is necessary, that controlling the virus means hurting the economy. Of course, that was a key part of the President’s messaging. However, the data tells us a very different story. That’s why I want to talk about Germany.
    You may have heard that the U.S. is not the only place where coronavirus is surging. Europe is dealing with another big wavelet as well. Have a look at Figure E below, taken from the European Center for Disease Control and Prevention (ECDC). It shows new case growth per 100,000 population for the two prior weeks as of October 28. This map startled me. It’s very handy to be able to see patterns at the sub-national level, similar to what I do every day with U.S. states. As a thought experiment, let us say that it is true that what national and state governments do to control COVID-19 is pointless and unimportant. If that were so, we would not expect new case rates to vary along national borders. Instead, as was more or less true very early in the pandemic, the spread of disease would not honor national boundaries. Look at Germany and its neighbors. Not only is there clearly a spatial patterning of new cases that follows national boundaries, but Germany is completely surrounded by areas at the highest level of transmission on the scale including France, the Netherlands, and Belgium to the west, Austria, the Czech Republic and Poland to the east. Similarly, Portugal outperforms Spain, Scotland looks better than the rest of the U.K., and Sweden is doing worse than its Scandinavian neighbors Finland and Norway. Greece is doing better than Bulgaria in the last 2 weeks. The best performing European nation right now is Estonia, where only 73 COVID-19 deaths have occurred and their incidence rate (402 per 100,000) is one fifth what it is in the U.S. (2,946 per 100,000). Germany has set an example for the rest of Europe and the world using a combination of stringent control measures (closing schools, banning gatherings over 50, mandatory masks) as well as highly targeted testing and contact tracing. The result is that they have outperformed their neighbors, the U.S. and much of the world consistently and dramatically. All told, the Germans have 712 cases and 13.1 deaths per 100,000 compared to the U.S. rates of 2,946 and 72.2 cases and deaths. The U.S. COVID-19 death rate is five and a half times higher than the German rate. National policies matter and make a big difference.
    Now, let’s consider the question of trade-offs between the economy and public health. That’s where all this started. For that, we need one more figure, this one from OurWorldInData. Figure F plots COVID-19 deaths per million (vertical axis) against economic decline in the second quarter as percent drop in GDP compared to the previous year. If it’s true that countries have to choose between public health and the economy, then this graph should show that the countries with the highest death rates should have less economic damage, and that countries with low death rates should have paid the price in terms of bigger GDP losses. This graph tells the opposite story. The countries that kept the disease most in check (Taiwan, South Korea, Lithuania, Nigeria, Norway and Finland have had the least negative economic declines, all well-below the United States. On the other hand, the nations with high death rates (>400 per million) including Belgium, the UK, Italy, France, Mexico, Spain (hidden behind UK), Sweden (next to USA) and the U.S., all (except the U.S. and Sweden) experienced GDP losses of 12% or more. Among big, diverse, industrialized democracies, Germany kept its deaths down among the lowest, and at the same time, has an economy that has suffered less than Canada, France, Italy, Spain, Belgium and the United Kingdom. Wunderbahr!
    Bottom Line: What countries do matters. The evidence strongly shows no trade-off. Countries that have controlled the pandemic the best have seen less economic damage, not more. Allowing the coronavirus to run rampant without control measures causes more economic damage.
Figure E. Weekly new case rate map from the European Center for Disease Control and Prevention.
Figure F:
  1. Quirky Qorner: North Dakota now has 151 cases a day per 100,000, the highest in the nation by far. Yesterday, the 8th district of the North Dakota House of Representatives elected Republican David Andahl who earned triple the votes of his democratic opponents. The problem: Representative Andahl died of COVID-19 in October
     I have been wondering what it’s like to be in North Dakota right now. By every measure, the outbreak is out of control in that state. Newsweek tells us today that the voters of North Dakota, despite how bad things are COVID-wise, gave President Trump twice as many votes as Biden. CNBC reports today that North Dakotans have also elected a man who died of COVID last month. My heart goes out to the family of Mr. Andahl, but it seems that North Dakota continues to go down the coronavirus rabbit hole.

Top pick of the day: Friday

How the virus won

Graphically intensive moving-picture presentation of the U.S. COVID-19 epidemic seen from above by Derek Watkins, Josh Holder, James Glanz, Way Can, Benedict Carey and Jeremy White, posted online at the New York Times, June 25, 2020.

If you ever think about the big-picture of how we got to this moment in the U.S., what we did wrong as a nation and how things went so badly, take 10 minutes to walk through this fascinating timeline of events for a 50,000-foot view that provides some deep and troubling lessons.

Today’s bite-sized, handpicked selection of important news, information or science for all who want to know where this epidemic is going and what we should do.

Daily COVID-19 Briefing: Thursday

Top news, reports and insights for today:

  1. Daily headline summaries for Thursday:
  • Scientists at Yale have found that viral RNA found in sewage sludge predicts COVID-19 cases and hospital burden. This paper, while not yet peer-reviewed, suggests the potential power of poop in biosurveillance (medrxiv)
  • Asked why New York City was hit so hard by the first waves of COVID-19, experts point to 4 key factors: 1) large influx of travelers from Europe, 2) early reluctance to close subways and buses, 3) hesitation to issue stay-at-home orders by the Governor, 4) sending recovering patients back to nursing homes (Bloomberg)
  • U.K. scientists honing in on the identification of blood markers for mysterious Kawasaki-like multisystem inflammatory syndrome in children (MISC-R) (NBC News)
  1. A focus on growth factors by state: Hot spots in Kansas and the south
     As the epidemic has slowed in recent weeks, it makes sense to shift the time scale of how we track it. Daily ups and downs of cases and deaths at the national level have been choppy and unclear. We know that looking at numbers for the whole country can be misleading given that the outbreak has slowed in New York, Detroit and New Orleans, only to disseminate to smaller towns and rural areas. Let’s zoom out a bit and focus instead on longer term trends at the state and regional levels. The graphs below show 7-day week-over-week growth factors, which I have said previously can be a better metric to gauge the current situation compared to looking at the daily numbers. Growth factors are ratios, so looking at them gives a different perspective. In epidemiology, we get lots of practice with ratios. If we want to know the strength of a relationship between a risk factor and a disease, we can look at the absolute amount of disease attributed to the risk factor (also called Attributable risk) or the ratio of disease in those with and without the risk factor (also called Relative risk). There are definite plus-minus trade-offs in choosing which numbers to focus on, but in this case, we can improve the signal-to-noise ratio by looking at the ratio of cases/deaths last week to the cases/deaths the week before.
     The top graph shows the growth factors for new cases. States with values greater than 1 are more active, with positive growth in new cases week over week. What this shows is that all states with stable numbers in the northeast saw negative case growth except Maine. The midwest was a mixed bag with cases rising in 6 states and falling in 6. Cases grew 20% or more in Iowa, South Dakota and Wisconsin. Michigan is slowing fastest with just over half the cases last week as the week before. While little attention has been paid to the West, new cases rose in three states (California by 16%, Idaho by 24%, and Nevada by 23%). In my view, the biggest take-home message here is that cases grew last week substantially in the south, where 10 of 12 states saw cases rise. West Virginia more than doubled new cases adding 322 compared to the 141 the week before. Cases grew sizably also in Alabama (48%), Arkansas (66%) South Carolina (26%), Tennessee (28%) and Virginia (21%).
     The bottom graph covers growth in deaths. In the northeast, deaths rose in Maine (14%) and Rhode Island (54%). All western states saw deaths decrease last week. The fastest rise in new deaths occurred in Kansas where deaths nearly doubled week-over-week. In the south, new deaths increased in half the states, led by Alabama (24%), Arkansas (30%), Georgia (21%), South Carolina (31%) and Tennessee (22%).
  1. The state of testing: which states are ready to reopen?
     Today’s Top Pick of the Day article from Vox is based on interviews and discussions with a number of infectious disease experts who were asked to list the top criteria that should be used to decide when it is safe for states to relax outbreak control measures and reopen. I thought I would take my own deeper look into two of those criteria related to testing. The two benchmarks suggested are:
     1) New daily tests of at least 150 per 100,000 population to insure adequate testing capacity for spotting new infections and tracing their contacts.
     2) A test positivity rate of less than 5% indicating that the testing is no longer selective and that a wide net is being cast.
     You can read the paper to see what they conclude about these numbers. I created two new graphs using numbers from the COVID Tracking Project (the same source they used) but looking slightly differently. The top graph below ranks 50 states and DC from highest to lowest on new daily tests per 100,000 residents, averaged over the last month. As was true before, the testing regimes in the northeast are considerably more mature than in most southern and midwestern states. Rhode Island is still in the lead, testing an average of 176 per 100,000 per day and is the only state clearly above the threshold of 150 per day. New York, Massachussetts, Louisiana and Utah are the other states that are over 100 per day. North Dakota is the only midwestern state testing more than 75 a day, which may explain why cases are growing in that state. Twenty six states are now testing less than a third of the 150 benchmark. Arizona continues to have the lowest testing rate of all states by any metric. States below average are very likely under-estimating their current case prevalences, some quite dramatically.
     The bottom graph shows the test positivity rate (or TPR) for the last month. Since lower TPR is “better” in this case, the ranking of states is reversed. A total of 21 states have a TPR in the last month that is below 5%, while 16 states still have a TPR that is high (greater than 10%). Maryland, Washington DC, Delaware and Virginia constitute a block of Atlantic seaboard states that have ramped up their testing capacity (top graph) but still are seeing a large fraction of tests come back positive.
    The bottom line: No states qualify to reopen just using these two benchmarks as proposed in the VOX analysis. Testing remains widely discrepant across states. This shows what happens when there is a complete absence of national leadership and standards for testing. We remain largely and unsettlingly in the dark about this epidemic in the vast majority of U.S. states.