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Ellen Kuwana, founder, WeGotThisSeattle, a volunteer effort to feed the frontline
As a night owl, I relish the “me time” hours from midnight to 2 a.m. Snuggled in bed, the rest of my family asleep, I scroll through the news and laugh at friends’ video posts.
Like many other science writers, I spent many of those quiet hours in February following the relentless spread of the new SARS-CoV-2 virus, especially as my hometown of Seattle emerged as the first US epicenter.
On Mar. 5, I started working from home. The next week, I arranged for my college-age daughter to come home from UCLA. I was relieved when Seattle Public Schools closed and my younger daughter didn’t have to walk down any crowded halls. I wanted everyone home and safe.
My husband, however, is a physician–scientist who does essential work at the University of Washington and a nearby hospital. So we could not all keep entirely safe.
Just one meal for UW Virology
As the UW Virology department scaled up its breakneck efforts to process as many COVID-19 tests as possible, I started hearing from my friends at the university that some of their grad students and postdocs were pitching in at the testing center.
I remembered how tedious it is to pipette all day—right out of college I had worked as a lab tech at the Human Genome Mapping Center at UC San Francisco. As I scrolled through Twitter one night, a tweet from UW Virology landed atop one from a pizza place offering free pizza for healthcare workers.
Something clicked. “Who’s feeding the scientists?” I said to my dog.
She looked back at me as if to say: “Good question.”
On Mar. 13, past midnight again on Twitter, I typed a hurried “Who wants to help me feed UW Virology?” with a #COVID-19 hashtag.
Pagliacci, one of the biggest pizza franchises in the region, responded within minutes. They donated enough pizzas and salads to feed 70 people who were helping out, working long hours and taking extra shifts.
As I drove to deliver the food, I marveled at the lack of traffic, but it also felt sort of weird in Seattle. I greeted the person who came out to load the food onto the cart. She was all smiles. I remember her commenting on how the food would boost morale.
I offered to get the door for her.
“Best not to touch it, or we’ll have to wipe it down,” she said somewhat apologetically.
At first, I thought I would pay for all the food as a one-time gesture of appreciation to UW Virology. But as the adrenaline of that first donation wore off, I started to think more broadly about how to support local medical researchers and hospital workers. It was a bit overwhelming to think of all the medical and research staff in Seattle who were working so hard, day and night, from processing specimens and COVID-19 tests, to caring for patients.
Getting them food was one thing that I could do, and would help to keep their energy and spirits up for a prolonged siege. An army, some famous general once said, marches on its stomach.
Pretty soon, I found myself thinking about this a lot more than just during the wee hours of the morning. With money I was prepared to spend on my own for donated meals, on Mar. 20, I called a friend, placed an order for Rubinstein Bagels and went to buy cream cheese, plates and knives.
People were not social distancing at the grocery store, which made me nervous. I needed to keep myself safe and healthy in order to be able to deliver the food to hospitals safely. Now, to figure out where the bagels could go…
I started working my contacts at UW Medicine, which had closed its hospital to visitors. Through a surgeon friend, after many emails, I reached a point person who could accept the bagels. We did the social-distance dance to unload them onto a cart.
I made a mental note: next time, let the institutional contact unload the food right from my car.
Third meal for UW Virology and WeGotThisSeattle was born
Next time came quickly. I had put up a personal fundraiser on Facebook, inviting friends in Seattle to donate money for meals to UW Virology and other sites. By this time, news was everywhere about the lack of testing nationwide, and our UW Virology lab’s heroic efforts to meet our region’s need for more tests. Within a few days, I had enough donations for a third meal delivery.
Because so many restaurants had shut down, what had started out as a token of appreciation was now more like a lifeline to those who had nowhere else to get a quick bite during their work shift. My original question, “How can I be useful?” was clearly answered. People in the labs posted pictures and thank-you notes on social media. My inbox received a few heartwarming notes. It all confirmed that this was something I should run with.
Pizza, bagels…what next? I remembered Taste of India, one of my favorite local restaurants. On the phone, the explanation of what I was doing had hardly left my lips when the owner interrupted me.
“Ellen, what do you need? We will donate it all.”
His calm, swift response made me choke up.
It was a powerful moment, and not just personally. A tweet I posted describing that act of kindness was viewed by more than 2.5 million people, with more than 31,000 likes.
I can’t explain why this tweet went viral, but I think it has to do with so many of us wanting to help, but not knowing how.
Helping local restaurants
Things took off from there. Donations poured in — donations of funds, but also of food from many restaurants. When restaurants I contacted asked me to pay full price, I happily did. Those that had to ask almost certainly need the funds. And that, too, is part of supporting our community.
From what I’ve heard, many restaurants in Seattle are down at least 80% in revenue. As I’ve picked up food, I’ve seen many places where only the chef and owner (sometimes one and same) are working. They tell me how they hope to hire back their staff, how they don’t know how to make their rent payments. I’ve learned that some of the restaurants that donated food were not in a position to do that, when they were falling behind in their rent.
It all felt quite heavy. But their hope and their eagerness to help feed healthcare professionals and others risking infection to do vital work was also uplifting.
Now when I contact restaurants, I emphasize that I want to help them as well, and it’s OK to charge something for the food. The donated funds enable us to support local business while we feed the frontline.
A recipe for success
With encouragement from friends old and new (and I am forging strong connections with restaurant owners and the point people at the hospitals and UW Virology who have promised me hugs when this crisis subsides) and support from former strangers who have contacted me to help (and I finally got smart and said Yes to offers of help), we are moving ahead with getting systems in place to scale up.
We’re now collecting tax-deductible donations at WeGotThisSeattle. Since starting this project in early March, we’ve raised about $36,000 in donations from individuals. We’ve coordinated food to 30 sites in and around Seattle from 35 local restaurants and businesses, feeding more than 6,300 people. The meals have fueled workers at nursing homes, fire and police stations, and homeless shelters. They have fed bus drivers, EMTs, hospital janitors, and switchboard operators.
I quit my job to focus full time on this volunteer effort. It seemed like time for a change anyway, and I’ll find a new job when this is over. This is the best way I can contribute, right now.
Our meal-delivery effort is one of many: since mid-March, the University of Washington has received more than $300,000 in donated meals from a wide range of groups. The Swedish Hospital system in Seattle estimates that its workers have received 190,000 meals from 280 donors.
I attribute the growth and success of WeGotThisSeattle to four crucial factors:
Thanks to everyone who has contributed to our effort thus far, and to those who are finding their own ways to help.
Ethan Weiss, MD, Associate Professor of Medicine at UCSF; Principal Investigator in the Cardiovascular Research Institute
The week things got really interesting was the week of March 16.
That’s when Sara Cody, the Santa Clara County public health officer, and her legion of public health heroes made the gutsy call – the first of its kind in the nation — to shut things down in the entire 6-county San Francisco Bay Area, home to more than 6 million people. Only two deaths from COVID-19 had been reported at the time. She stuck her neck out there, saying we had to get in front of this pandemic, or else.
That same week, I had agreed to cover the inpatient service for a colleague at UCSF who was advised to avoid the hospital by their physician.
I’m a cardiologist, not an ER doctor. I remember feeling intense uncertainty and fear – mostly fear of the unknown. Everything was eerie and everyone was anxious. We all expected the hospital to be overrun by the weekend. That was how it had happened elsewhere.
When I actually got into the hospital, my fears faded. I got busy and distracted, which created a weird sort of calm. We were just waiting for the surge. I was comforted by how prepared everyone and everything was. Sure, there was concern over lack of PPE, but mostly people were feeling good and seemed focused. There were tons of empty beds. It seemed like we were ready even despite the strange act of waiting for disaster. I don’t remember ever feeling that way before.
And then nothing happened. By the end of the first weekend, the residents were asking for teaching – from me. They were bored. I’ll admit that I started to wonder how long we’d have to wait to know if the surge might not be coming. I was counting days from the lockdown on Mar. 16. I didn’t talk about it at first but I definitely started thinking. No one wants to be overconfident, in that “famous last words” sense.
By the next weekend, I was comfortable to talk about how we were doing well at UCSF. I got this text from a friend on Mar. 26:
“how bad is SF rn? seems quieter compared to nyc”
“It is quieter,” I responded. “I believe that is meaningful. They are still expecting a big surge and are opening closed hospitals, but with each passing day, I get more optimistic. We are now 11 days into the quasi-lockdown, and there has been very little sign of badness at least at our hospital”.
We all played this game for a few more weeks while we were told the surge was coming but it was clear it was not. At the same time, it was clear that other parts of the country were being devastated.
On Mar. 20, I sent this tweet: “I don’t mean this in any other way except genuine concern but I am very worried about what is happening in NY”.
At that point, there were 2,468 cases in NYC.
As of Apr. 24, there are more than 150,000 confirmed cases and over 11,800 deaths. (Source: NYC Health).
My colleagues and I watched the heartbreaking news from New York like everyone else.
Toward the beginning of April, I started to ask when we would consider sending people from UCSF to help in New York hospitals or to other hard-hit areas. I was told it was too soon. Then on Apr. 10, I tweeted: “Wow @UCSF is sending a team of clinicians to NY tomorrow for a month!”
I was happy. I was happy for New York. They so desperately needed the help. I had talked to friends and colleagues there. They were depleted and tired in every sense of the word. I was also happy for my colleagues – but honestly, I was also jealous.
I was busy. Not busy helping out in the ER at UCSF Medical Center, fortunately. But I was as busy as I have ever been, balancing seeing patients on Zoom with writing papers and grants while also trying to help guide this nascent startup I had helped found just a year and half ago. And then I got very caught up in the story about thrombosis and COVID-19 and have been working on helping to spin up at least two clinical trials to see if anticoagulant therapy could be helpful.
And of course at home, while my two daughters are mostly self-sufficient, there was plenty of work to be done. My wife’s business has been decimated. We are all crowded into a small house and we are doing things we don’t usually do (like clean). There were some amazing upsides and the most notable was spending so much time with the three people that mean the most to me on this planet. One of the most surprising daily joys was making and eating lunch as a family. It feels very European.
But despite all that, I still felt drawn to New York. I mentioned it at a faculty meeting a few weeks ago and was told there was no need for us. Then I heard UCSF was actually going to send a second team and they were asking for volunteers from Cardiology.
I spent at least 24 hours thinking about it. I tried hard to think about all the many reasons I wanted to go and tried as best I could to think about how much was motivated by a genuine sense of mission or perhaps a desire to be in the middle of the action or maybe even from a little envy of my colleagues or maybe even just curiosity or attention-seeking.
I wrestled with it. I finally asked my wife. I reassured her that I was not worried from a health perspective and that I’d be careful. I also acknowledged that it would be a tremendous burden on her to have to parent alone for two weeks in this absurd time, when she’s naturally stressed about her business and the kids are at home all the time. But I also said that everything else could wait. I reminded her that we had planned to take a two-week vacation to Japan in June and that I had numerous meetings and they had all been cancelled and that it was actually a very good time to go in many ways. My lab is basically closed. Most other activities are slow or non-existent. The startup is making it. And the thrombosis trials would/could go on without me.
We also talked about my motives. She grilled me about why I wanted to go, and I told her that I was not entirely sure, but I also told her that I was hearing a dog whistle and it was driving me mad. However, I also said I could not go without her support – her genuine support. After a short time, she looked me in the eye and said, “Ethan, you have to go.”
This “dog whistle” is a mysterious thing to explain. It’s some kind of call of duty, like a ghost of a first-year med school professor whispering in my ear to go. No one is explicitly calling on me, as if I have to go do this. But maybe there’s a little guilt implication in some conversations, as if to say “hmm, wonder why you aren’t getting on a plane to come to New York?”
So I told Jeff Olgin, my division chief, that I wanted to go. He connected me with Michelle Mourad who was managing the process here. By Wednesday, I was credentialed and licensed with maybe 10 minutes of work on my part. Do I have a medical license? Check. It was spectacular.
By Friday, we had a flight scheduled and had an orientation call with the hospital in New York where we are headed.
This morning, Apr. 25, three amazing women joined me in a desolate SFO airport and we boarded a plane. There was a very nice little ceremony. Mark Laret, the CEO of UCSF Health, came and gave a short talk. Sam Hawgood, our chancellor was there, as was Josh Adler and also Kim Murphy, the Director, Special Events & Community Relations at UCSF Health and the person who organized all this.
As our team of four medical personnel gathered in the jetway, we all muttered to each other about how uncomfortable we were with the pomp and circumstance. We just wanted to get there. We wanted to get to work. When we finally got on the plane, we found many other health care practitioners of many stripes from around the Bay Area – ALL of whom were volunteering to go work in NYC. Nobody gave them a ceremony.
So this brings me to the tension I have over the attention doing something like this might bring. I don’t want it to be about me. None of us does. But I also think there is value in telling the story. I think there is value in telling people about how I decided to come, how I feel and some of what I see. I don’t know too much about what I am going to do. I found out yesterday that I will be an attending physician in what used to be a cardiac ICU but that has been transformed (like all ICUs in NY) into a COVID ICU.
I’m not scared of getting sick. I am uneasy about how brutal it will be, tending to wave after seemingly endless wave of critically ill patients. But I will try to stay focused on the task.
What really bothers me is that “first day of school” fear. It’s a lot like how I felt 20 years ago when I came back from the lab to do my clinical fellowship. Will I know what to do? How do I manage a ventilator or volume status? Can I still put in a central line, and will I need to? My wife reminded me this morning on the way to the airport that it’s like riding a bike. But I also have not worked at a new hospital since 2001, so I am feeling uneasy and unsure of myself. There could be slightly different equipment, procedures, colleagues who have already been through the ringer and are moving at warp speed, while I’m trying to get up to speed.
However, all of that is balanced by a strong desire to get in there and get to work. I am excited to learn, to see, to make myself useful.
I’m slightly surprised by the emotions. I did not expect tears at the airport this morning. Ultimately, I am going to miss my family desperately. There is nothing I will ever be able to do to repay them for letting me go and answer this dog whistle.
Over the next two weeks, I will try to write occasionally about my experiences. If I do this right, it will foster a little more understanding of what it’s like on the frontlines. Those of you who know me know that I will be honest and raw and maybe even sometimes crass. But I have such tremendous respect for how people have pulled together to contribute whatever way they can in this wicked moment. This challenge is vastly bigger than any individual effort. I have been trying to remember to thank everyone who has a role to play — from the TSA agents to the custodial staff to the flight attendants (even if they are not serving coffee on this flight!).
It is precisely at times like this that I remember the lesson my Dad taught me when I started my first clinical rotation in medical school now 27 years ago: always appreciate and thank everyone – everyone and most importantly the people who never get thanked.
Now more than ever, there should be no thankless jobs. Everyone has their purpose, everyone is answering a different kind of dog whistle.
Luke Timmerman, founder & editor, Timmerman Report
The first US death from COVID-19 was reported on Feb. 29.
Today, Apr. 24, the US death toll exceeds 50,000.
That’s more than Italy and Spain combined. Even though we had early warning. It’s tragic.
There’s also a reason why the death toll hasn’t been higher. It’s because of large-scale physical distancing in this expansive country of 330 million people.
After a few weeks, people are understandably getting restless. Tens of millions are unemployed and fearful for their livelihoods. The federal government has thrown up its hands in many respects, passing the buck of leadership to state and local governments. Now we’re seeing a mishmash of local decisions.
The state of Georgia – a place with 10.6 million people, more than 20,000 confirmed infections, and the busiest airport in the country – is led by a Governor that is opening up large swaths of the economy today, relaxing the physical distancing restrictions there. He’s doing that even though his state hasn’t complied with the federal guidelines that say reopening can begin in phases after new infections go through a 14-day decline.
Local decisions like these will determine just how ferocious the second wave of infections will be across the entire country this summer and fall.
Jeff Duchin, MD. Health officer. Public Health – Seattle & King County
“It’s like peeing in one end of the pool. It doesn’t just stay there,” said Jeff Duchin, the leader of Seattle and King County’s public health agency, on a webinar I moderated yesterday for Life Science Washington, the local trade association.
Duchin called the decision of Georgia Gov. Brian Kemp “reckless.” Given the latest models he’s been reviewing, Duchin said he believes the second wave of infection this fall could be two to three times larger in magnitude than what we’re seeing now in Seattle and King County.
Meanwhile, the CDC – once the gold-standard agency in public health — is still AWOL when it comes to coordinating a national testing program. We are nowhere near the number of tests (20 million a day at peak according to one Harvard estimate) we need to be doing to gain the knowledge necessary to suppress the virus with targeted quarantines. Without knowledge from tests, it’s hard to imagine a safe and responsible reopening of the economy.
Still, without any clear idea of where the virus is, we have protestors agitating in state capitols to lift the physical distancing orders. Some people who are sick are even being urged to show up, to exercise their rights as Americans to travel freely. They revel in thumbing their noses at the experts. They’re good at provoking all of us to gape in amazement and horror, good at distracting us from what’s important.
Yesterday, the President suggested that people might want to try ingesting bleach to fend off the coronavirus. Or maybe ultraviolet light.
Talented journalists who could otherwise be investigating breakdowns in our national testing system and kicking the bureaucracy in the rear end are now writing about why it’s a bad idea to drink bleach.
How did we get ourselves into this tragedy? This farce?
How do we get out?
I don’t know all the answers. But I do know that people with education, drive, and good faith – that’s you – need to do constructive things to be part of the solution. That extends beyond this pandemic, and goes into repairing the social fabric, investing in science and education, and helping vulnerable populations. It’s a heavy topic, rethinking citizenship, rethinking what our responsibilities are to our fellow human beings. This will take time to sort out. I believe we can come out the other side better.
Be safe. Be strong.
To borrow a quote from my late father-in-law:
“Be Good to Each Other.”
Science
Testing
Treatments & Vaccines
Policy
Models
Worth Watching
Policy
Humanity at Its Best and Worst
TR Coverage
Personnel File
Rick Bright, the head of the US government’s Biomedical Advanced Research and Development Authority (BARDA), a key unit for vaccine development, abruptly left his post. He later filed a whistleblower complaint, saying he was being sidelined by the administration because of his unwillingness to promote unproven therapies. See his statement.
Greg Guyer was hired as chief technical officer and EVP of global manufacturing and technical operations at BioMarin Pharmaceutical. He was formerly SVP of operations at Bristol-Myers Squibb. He takes over from company veteran Robert Baffi.
Investing
Financings
Cambridge, Mass.-based Affinivax, a vaccine developer with a lead program for pneumococcal infections, raised $120 million in a Series B, led by Viking Global.
South San Francisco-based ORIC Therapeutics, a company working on cancer resistance, raised $120 million in an IPO of 7.5 million shares at $16 apiece.
Lexington, Mass.-based Accent Therapeutics, a cancer drug developer focused on RNA-modifying proteins, raised $63 million in a Series B financing. EcoR1 led.
San Diego-based Arcturus Therapeutics, an RNA-based medicine developer, raised $80 million in a stock offering of 4.7 million shares at $17 apiece.
San Francisco-based Nitrome Biosciences raised $38 million in a Series A financing co-led by Sofinnova Partners (the European-based venture group) and AbbVie Ventures. The company is working on Parkinson’s disease.
Bethesda, Maryland-based Aledade raised $64 million in a Series C financing to continue expanding its network of physician-led Accountable Care Organizations. OMERS Growth Equity led.
San Francisco-based Unlearn.AI, a company that creates ‘digital twins’ to serve in clinical trial control arms, raised $12 million in a Series A. 8VC led.
Deals
Ann Arbor, Mich.-based Esperion Therapeutics pocketed $60 million upfront from Otsuka Pharmaceuticals as part of a deal to commercialize its two new cholesterol-lowering products in Japan.
Gilead Sciences struck a three-year collaboration with oNKo-innate to work on engineered Natural Killer cell therapies for cancer.
Veracyte announced an exclusive license from Yale University to develop the first genomic test for idiopathic pulmonary fibrosis, based on a 52-gene signature.
Regulatory Action
The FDA gave the green light to Incyte to start marketing pemigatinib (Pemazyre) for patients with locally advanced or metastatic cholangiocarcinoma. The drug is made to target fibroblast growth factor receptor 2 (FGFR2) fusions, which are detected by the FoundationOne CDx test.
Sanofi got FDA clearance for a new quadrivalent meningococcal vaccine.
Data That Mattered
Exelixis and Bristol-Myers Squibb reported that they hit the primary endpoint in a clinical trial of patients getting their first round of treatment for renal cell carcinoma. Patients got the combo of nivolumab (Opdivo) and cabozantinib (Cabometyx), and were evaluated for progression-free survival, overall survival, and overall response rate. Details to come at a medical meeting.
AstraZeneca and Merck’s PARP inhibitor, olaparib (Lynparza), passed a Phase III trial for men with advanced metastatic, chemical castration-resistant prostate cancer. The study looked at men with homologous recombination repair gene mutation (HRRm). Data to come at a medical meeting.
Tweetworthy
Someone we all need a little gallows humor.
Sometime you laugh, sometimes you cry. Sometimes you just have to slap your forehead.
“Some experts say” it’s bad to drink bleach. Golly, you don’t say?
And sometimes members of the evidence-based, reality-based community decide they have to get involved in the debate, however messy and ugly it can sometimes be.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
David Shaywitz
As the nation has struggled to cope with the devastation of the COVID-19 pandemic, New York Governor Andrew Cuomo has become the voice so many have looked to for support and leadership.
What Cuomo seems both to offer and effectively communicate is not just a mastery of the facts, but also a grounded yet hopeful narrative. The story he projects serves as a resonant, unifying, activating force that helps us to see our collective trauma as a valuable opportunity to grow.
He’s challenging us “to learn the lessons and to build back better.”
The ability to reimagine your life story in a more constructive way allows some to endure unimaginable suffering and emerge intact, even stronger, in the aftermath. Such “super-survivors,” David Brooks wrote in 2015, leaning on extensive psychology research on post-traumatic growth by Richard Tedeschi among others, have traits “that enable them to come back stronger than ever. These people are often deluded in good ways about their own abilities, but completely realistic about their situations.”
Post-traumatic growth “is not blind optimism, denial, or deception of self or others,” Tedeschi told me. “It does not dismiss distress and loss.” Rather, he argues in his latest book, Transformed by Trauma, which focuses on military veterans, the experience of growth “is a process – a difficult one, and an outcome that is life-changing and worth the struggle.”
The key, Brooks continues, is the ability “to write a new story that imagines a life better than before.” He adds, “Researchers have found that people who thrive after a shock are able to tell clear, forward-looking stories about themselves, while those who don’t thrive get stuck ruminating darkly about the past.”
Holocaust super-survivors are in this group. These are people who went on to live fulfilling lives, raise families, and in some cases even win Nobel Prizes, start great companies, and write books that moved the human spirit. One thing these people had in common, Alana Newhouse explained on a recent podcast, was that they were “people who understood a story, understood that the holocaust was the prologue, and the rest of their lives was actually the book.”
I’ve seen the value of this reframing up close as well, in the context of my parents’ dyslexia research, and their “Sea of Strengths” model, which enables dyslexics to understand that while they have specific challenges matching sounds to letters, this is occurring in the context of many other strengths, including often high intelligence and exceptional creativity.
Dyslexics, as my mother and brother Jonathan describe in the new edition of Overcoming Dyslexia, are not “stupid,” despite what misinformed teachers or other adults might have said about them in their youth, when the children struggled to read. By helping dyslexics reframe their life story — and to receive the accommodations they require (realism, again) — this research has enabled so many previously despondent, struggling people to pursue ambitious careers that many had never thought possible.
California Gov. Gavin Newsom, another state leader standing out like Cuomo in crisis management, happens to be dyslexic. So is Johns Hopkins biologist Carol Greider, who received the 2009 Nobel Prize in Medicine; Nancy Brinker, founder of Susan G. Komen for the Cure; and surgeon and former CEO of the Cleveland Clinic Toby Cosgrove, who candidly discusses his struggles with dyslexia with Lisa Suennen and me on our latest episode on Tech Tonics.
The power of a reframed narrative also comes through in recent interview of legendary quarterback Tom Brady by radio personality Howard Stern (each GOATs in their own right). Brady was asked how he handled seemingly hopeless situations. His response:
“We were down 28-3 against Atlanta in Super Bowl 51. You can look at that situation and basically quit and say, you know, ‘F— it. We have no shot of winning,’ or you can say ‘This is going to be an amazing comeback. When we come back from this, this is going to be the defining moment in life,’ or a defining moment in a professional career.
“I think when you shift your mind and think that way, it becomes very empowering as opposed to very discouraging. So anytime we’re down in a game, I think, ‘Man, if we come back and win this game, we’re the hero,’ rather than ‘Oh, s—, we’re screwed. We have no shot.’”
As usual, Brady’s right. Mindset matters.
The nation now confronts the overwhelming challenge of pulling ourselves out of a devastating crisis that has left 47,430 Americans dead as of this writing on Apr. 22. Our economy is in ruins, and the nation is distraught.
To emerge as super-survivors, we need not just to persist, as Cuomo emphasizes, but to advance with energy and hope. We need to embrace a new story, one that acknowledges the brutal reality, while allowing us to envision a more promising future. We need a restorative narrative, one that recognizes our loss, supports us through our painful struggle, and enables us to move forward.
The narrative emerging from the White House — our response has been perfect and flawless, plenty of tests are available, all problems are someone else’s fault — lacks both face validity and emotional resonance.
This is not the narrative most of America is looking for. Nor is it the redemptive vision we need.
The country recognizes the global pandemic is a humbling experience for us all. No one anticipated this “perfect pathogen” with perfect clarity. We still struggle to understand even the basic scientific facts of its spread, how the virus interacts with the immune system, and ultimately how to best contain it with testing, treatments, and ultimately a vaccine. The path forward is uncertain. We get this.
We’re neither expecting nor awaiting a flawless, omniscient protagonist to lead us forward. Instead, we’re poised to be inspired by someone one who, like the rest of us, has been roughed up by this experience, yet has emerged, bruised but not defeated, wiser, and determined to coax a traumatized country through this difficult time.
Growth through adversity isn’t a partisan message — it’s as conservative as it is progressive. As Cuomo points out, it’s deeply ingrained in the American experience. And, as he suggested, in the human experience.
“We’re going to be the better for this,” Cuomo promised this week. “It’s the hard times in life that actually make you better, make you who you are, if you’re intelligent enough to learn from them.”
He added, “We have to do this individually and collectively.”
Preach.
Ruth Etzioni, Full Member, Division of Public Health Sciences, Fred Hutch Cancer Center
What is the single thing you wish you knew about COVID-19?
Here is what I wonder about most.
How many of us have had it already without knowing it – either because we did not have symptoms, or because we thought it was something else, or because we thought it might be COVID-19 but we could not get tested?
My interest in this matter is both personal and societal.
Personal, because three days after I came back to Seattle from London Jan. 27 on a packed Delta flight, I came down with a major chest cold.
During the day, I was OK. Things went downhill as evening came on, and I suffered with coughing fits and fevers through each night. This went on for 12 miserable days.
Was it COVID-19? If, like me, you have searched for “did I have the coronavirus,” it’s clear that plenty of people are wondering the same thing.
Having recovered from that nasty cold, and having gotten a negative test earlier this month, my interest is now more societal in nature. Societal because we need to know how many people have had COVID-19 to understand the real reach of the virus, its true contagiousness. We must be able to identify who is immune in order to carefully plan our exit from lockdown.
So I have been drawn to three new studies that report the results of serology tests conducted on persons without a prior COVID-19 diagnosis – in the City of Chelsea, Massachusetts; in Gangelt, a municipality in the Heinsberg district of northwestern Germany; and in California’s Santa Clara County.
All three of these places are known virus hotspots. Chelsea has the highest rate of infections in Massachusetts, Gangelt had an outbreak following a superspreading carnival event in mid-February, and Santa Clara County (the home of Silicon Valley) became an epicenter in early March.
Their results are strikingly different. In Chelsea, 33% of individuals tested were positive, in Gangelt 15%, and in Santa Clara 1.5%.
Like all diagnostic tests, antibody tests can be wrong in two ways. First, they may produce a false negative – you have had the virus but the test doesn’t detect it. Or they may produce a false positive – you haven’t had the virus, but the test says you have. The false negative and false positive error rates define the test accuracy. There are concerns that the majority of the tests currently being marketed (more than 95 to date) do not make the grade.
Because antibody tests are not perfect, we can’t simply use the reported fraction testing positive to estimate how many people have really had the virus. If the false negative rate is high, that means we have likely undercounted; if the false positive rate is high, we have overcounted. We can use these error rates to fix the fraction found to have antibodies so that we get the right result. Let’s see how this worked in Chelsea, Gangelt and Santa Clara.
The Chelsea study used a rapid test to look for antibodies in the blood from BioMedomics. The company says its false positive and false negative error rates are around 10%. When the researchers accounted for these error rates, they found that although 33% of cases tested positive, the actual number with antibodies was lower – around 30%. That’s still a startlingly high prevalence, much higher than the 2 percent officially diagnosed via the standard RT-PCR diagnostic test. It tells us that in Chelsea, there are 15 cases that we don’t know about for each case already reported.
The Gangelt study did not specify which antibody test they used. Researchers there reported a low false positive error rate (less than 1%) but did not provide a false negative rate. More clarity on the product being used, and its error rate, is needed to evaluate the results. But as things stand, the number of people estimated to have been infected in Gangelt is between 15-17 percent. (That assumes false negative rates in the range of 5-15%.) In the Heinsberg region, in which Gangelt is located, almost 4% of the population was officially diagnosed via the RT-PCR-based diagnostic test. This implies that in Gangelt, there are roughly 4 cases we don’t know about for each diagnosed case.
And in Santa Clara? This study used a test from Minnesota’s Premier Biotech. Based on the reported performance of their test (and some independent validation at Stanford University), the authors did the math. They concluded that 2.5% had previously been infected. Based on an even tinier fraction of the population with a confirmed diagnosis, the researchers concluded that there are at least 50 cases that we don’t know about per diagnosed case in Santa Clara County.
So. 4 to 1, 15 to 1, and 50 to 1.
That’s a lot of variation in the balance between cases we know about and cases we don’t. What gives?
One answer is that the estimates may be incorrect; for example, a chorus of criticism has surfaced about the Santa Clara study. Critics argue that the method of sampling (via Facebook ads) preferentially enrolled subjects who had had symptoms, and the study likely understated the false positive rate, both of which could have inflated the estimated prevalence of antibody-positive individuals.
But a study done in Los Angeles just reported very similar results, suggesting as many as 55 undiagnosed cases per known case of COVID-19 there. This study was better designed because it used a more random sampling method, but it used the same serology test as the Santa Clara study. Therefore, it doesn’t address the false positive rate issue. This is important, because if you don’t get the error rates right, you can’t properly fix the reported fraction testing positive to figure out the real prevalence of antibody positivity.
Another answer, one that bears serious consideration, is that we’re oversimplifying. The notion that there is a single number – of silent, undiagnosed COVID-19 cases for each reported diagnosis – is just too basic. Clearly, it depends on where you live.
Going deeper, we can look to three key factors that drive the balance between cases that we know about and those that we don’t: testing, timing, and demographics.
Germany is famous for its massive testing response to COVID-19, particularly in the region of Heinsberg, the location of one of the country’s largest outbreaks. The opposite was true in Santa Clara, where testing got off to a slow start. By Apr. 1, half the number of cases per capita had been diagnosed in Santa Clara County compared with Washington State, despite both being among the locations with the earliest recorded US cases of the virus, in late January.
More testing leads to more people being diagnosed. This means more cases that we know about, and fewer that we don’t, and ultimately, less of an imbalance between undiagnosed and diagnosed cases. With much less testing, the number of known cases drops, and this could explain the Santa Clara findings.
Timing is critical too: when infections took off, when testing ramped up, when social distancing and other restrictions began, when the antibody test was actually done.
Timing impacts not only the balance between diagnosed and undiagnosed cases, but the overall size of the infected population. It’s a little hard to know how much this played a role in the dramatic difference between Chelsea (30%) and Santa Clara (2.5%) but, for the record, the Bay Area’s shelter-in-place order came on Mar. 16 when there had been just two reported deaths in Santa Clara County. Massachusetts came later, ordering the shutdown of non-essential businesses on Mar. 24 after 9 COVID-19 deaths in the state.
The size of the infected population and the balance of known infections don’t just depend on testing and timing. Demographics also matter.
According to an article in the Boston Globe, about 65% of the residents of Chelsea are Latino, and only 21% are white. Many live in crowded conditions, where it is hard to isolate. And many work in service industries and health-related fields, so they can’t shelter at home.
In contrast, only about 25% of the residents of Santa Clara County are Latino and 51% are white. Many work in the tech industry and are able to work from home. Population density in Santa Clara County is an order of magnitude lower: around 1,500 versus 18,000 per square mile in Chelsea. So, contact rates that drive infectious transmission are likely far higher in Chelsea than in Santa Clara County.
These factors are some you might want to think about when interpreting the impending blizzard of antibody studies, which I am guessing will continue to show highly variable results.
The take-home message though is this. The balance of undiagnosed to diagnosed COVID-19 cases is not just about biology. It depends on many other things. Ultimately, while 50 to 1 seems high to me, these studies make me think that the size of the undiagnosed population in the US is a lot bigger and the virus a lot more contagious than we imagined. State and national policy makers can and must use this knowledge to shape our strategy for carefully exiting from COVID-19 lockdown.
Carolyn Ng, managing director, Vertex Ventures HC
It is with a heavy heart that I pen this follow-up piece on Singapore’s COVID19 situation.
In the past few months, the city state has been hailed as an exemplar of early, preemptive and targeted response to combat the pandemic. Other countries have studied its response.
As I wrote here on Mar. 19, despite being a densely populated high-risk state, Singapore managed to keep its cases extremely low. No deaths were reported between late January and mid-March. But even then, there were warning signs. In that same piece, I expressed concern for a potential second wave of cases that could be triggered by the massive influx of Malaysian foreign workers who rushed to enter Singapore before Malaysia closed its borders on Mar. 18. Interestingly, while Singapore did experience a second wave in late March, the new cases were not attributed to foreign workers. Most of the new cases were from Singaporeans returning home from travels to global hotspots such as the UK and US (covered here).
As it turned out, that source of new cases was only the beginning. It will be a long time before Singapore can pop the champagne, (or throw back a Tiger beer in celebration, in Singapore’s case).
At time of writing today (Apr. 21), there is a total of 9,125 confirmed COVID19 cases in Singapore – and we are now seeing more than 1,000 new cases a day. So far, the death toll remains low at just 11. Source: https://www.moh.gov.sg/covid-19. While my earlier concern for the Malaysian foreign workers who rushed into Singapore overnight has fortunately not (yet) been borne out, the primary cause for this third wave of COVID19 cases did, however, turn out to be similar.
Migrant workers who come to Singapore from Bangladesh, India and China, and who have been residing in crowded dormitories, are now suffering. Of the 1,426 new confirmed infected cases announced today — the highest single-day total reported so far — the vast majority are foreign workers living in dormitories. Only 16 cases of the new cases were Singaporeans or long-term residents.
After all that deliberate, thoughtful, and swift COVID19 response, how did Singapore see its curve move in the wrong direction?
Behind our beautiful Garden City (and the glorious food)
Anthony Bourdain, before his tragic suicide in 2018, filmed a CNN series called Parts Unknown. One of the episodes featured his visit to Singapore. While I was reminded fondly of home by the tantalizing street food of Singapore featured in the show (I went searching for chicken rice in San Francisco the next day), there was one particular conversation he had with the locals which struck me somewhat uncomfortably:
On that episode, a few local Singaporean ladies shared with Bourdain that in this country, most Singaporean women are in the corporate workforce. They further elaborated, rather matter-of-factly, that the career progression of Singaporean women isn’t hampered by childbearing.That’s because low-cost domestic helpers are widely available. These domestic workers live under the same roof as the local families, and are responsible for daily chores and childcare.
Bourdain, in his signature candid style, retorted, “that’s like bourgeois, man. You are living off the labor of an oppressed underclass.”
That conversation made me, a Malaysian-born Singaporean, and a proud one at that, rather unsettled. Deep down I knew that Bourdain was most probably right.
No system, or country, is perfect. Behind the ultra-modern high-rise buildings that dominate our stunning skyline are the faceless migrant construction workers from other developing countries who have toiled under the hot tropical sun to build them. Behind the ultra-clean streets of Singapore lined with gorgeous flowers and trees, that have earned us the moniker of “Garden City,” are the invisible cleaners. Many of them earn a low wage at jobs which few local Singaporeans would take.
When my significant other visited Singapore with me for the first time, he was quick to point out workers’ vehicles passing us by on the roads. They sit shoulder-to-shoulder at the back of open trucks. No seats. No seat belts.
These trucks are hard to miss. They are on the same roads as the luxury sedans driven by the locals who work in those office towers.
It was not a proud moment for me, nor should it be for any Singaporean.
While this situation is not unique to Singapore, we cannot deny the fact that we have more than 200,000 foreign workers living in cramped and relatively unsanitary conditions. On Mar 23, before the current turn of events, the Transient Workers Count Too (TWC2) organization, a local non-profit workers’ rights group, submitted an open letter to warn the government officials of a potential outbreak within the foreign worker dormitories.
As detailed in that public letter, these migrant workers are often housed in crowded dormitories of 12-20 men per room. In addition, some employers levy heavy fines, which can amount to a few times a worker’s daily salary, if they fail to show up at work; some even refuse to recognize medical leave of more than one or two days. These conditions render it almost impossible for these foreign workers to exercise social distancing or to stay at “home” even when unwell.
Knowing how this virus transmits so easily between people in close proximity, and how much pressure the workers are under to work even when feeling ill, this is an almost ideal situation for the virus to spread.
Unfortunately, the public warning from the workers’ rights group fell on deaf ears. It is always easy to realize on hindsight, but these migrant workers represent the exact demographic that was left out of Singapore’s early, effective COVID19 response. For example, the country’s nationwide mask distribution early in February to every household did not include these foreign laborers. In another instance, the government’s bid to reduce virus spread by restricting physicians to single hospitals has also severely impacted volunteer health services required by this vulnerable community.
These workers operate in a kind of blind spot to many Singaporeans. It showed in the country’s response.
As Bilahari Kausikan, the former Permanent Secretary at Singapore’s Ministry of Foreign Affairs remarked, the country “did drop the ball on foreign workers who are invisible to most Singaporeans.”
Not All Hope is Lost: Correcting the Course
While it is disheartening to see Singapore’s current setback, it is however encouraging to see the city state tackling the crisis head on with new and concrete measures. Josephine Teo, the Minister of Manpower, has outlined a three-pronged strategy:
In these special times of need, tens of thousands of Singaporeans have rallied and donated funds to help support these migrant workers. Prime Minister of Singapore, Lee Hsien Loong, publicly pledged his commitment to take care of the welfare of the affected migrant workers. The government is also working closely with employers to ensure that these workers continue to receive their salaries and to facilitate their overseas remittance to send money home.
It is also particularly heartwarming to see the volunteers at Healthserve, a Singaporean non-profit organization, step up during this time of crisis to roll out counseling via virtual means for migrant workers hit by this pandemic, with a strong focus of ensuring their mental and emotional wellness.
Apart from efforts to combat further virus spread within the foreign workers clusters, Singapore continues to combat local transmission. After resisting a nationwide lockdown for months, it eventually became apparent to Singapore that even the most aggressive and effective contact tracing and isolation measures are not sufficient to contain the virus spread. Partly, this is because of the difficulty of stemming all imported cases.The traditional method of public health can be effective, but struggles to keep up with a virus that spreads this fast. The country has since Apr. 7 been in a one-month lockdown, which the government termed, quite curiously, the “circuit breaker” (maybe someone with an electrical engineering background conjured this term?).
New Learnings
It is not only in Singapore where we witness an exceptionally severe impact of COVID19 on the lower socioeconomic classes. In the US, data showing racially disproportionate mortality rates have emerged in some of the poorest regions of the country. For an instance, 70% of fatal COVID019 cases in Louisiana are African Americans, even though they only make up one-third of the state population. Poverty, higher rates of co-morbidities, less access to healthcare and unfeasibility of practicing social distancing because of crowded housing conditions and jobs that can’t be done from home render certain populations particularly vulnerable. As countries all over the world get embroiled in the chaos of this pandemic, it is of utmost importance that we do not neglect the most vulnerable communities in our midst. Their lives are at risk more so than ever, and especially if we do not take the prudent steps in our policies.
As my esteemed friend Dr Jeremy Lim at Healthserve said in an interview, “If we don’t proactively look after the weakest link, then collectively, we will all pay the price.”
Singapore’s case study is a reminder that even when the curve appears to be flattened, as was the case initially, COVID19 can rapidly rear its head again when stringent social distancing measures are not in place. Short of an effective vaccine and/or herd immunity, subsequent waves of infection are highly possible if we were to loosen social distancing measures too liberally or prematurely.
In my new home in the United States, I’m watching nervously as Georgia — a state with 10.6 million people and more than 19,000 reported cases of COVID19 — announced plans to reopen its economy this Friday, Apr. 24. In the meantime, states like New York and California have recently extended their stay-at-home order to later dates in May than originally planned.
These highly varied individual state responses do not make it easier for what should have been a more coordinated nationwide effort to combat COVID19. We all know by now that a hotspot can quickly seed new clusters elsewhere, especially from a place like Georgia with one of the busiest airports in the US. But many US states did act quickly, and citizens quickly adapted to the stay-at-home orders, so hopefully we can respond quickly again if necessary. The coming months will be critical to watch as we thread the needle to save as many lives as possible, while also saving people’s economic livelihoods.
It is now Virus versus All Men. May those who have lost their lives in this pandemic live in our everlasting memory. In order for them to not have died in vain, let’s learn the right lessons to prevent more unnecessary death. For all of mankind, I pray.
Disclaimers:
This article expresses the personal views and perspectives of the author. The views and perspectives expressed here do not necessarily represent the views or perspectives of Vertex Ventures HC, or any officer, director, partner, member, manager or employee of Vertex Ventures HC, or any of its affiliated entities.
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Otello Stampacchia, founder, Omega Funds (illustration by Praveen Tipirneni)
When??
When can we finally go back to something resembling a “normal” life, go back to work and restart our economies, embrace again long-lost family, friends, co-workers? And, in too many cases, when can we get together to properly mourn those we have lost?
I cannot tell you “when.” Everyone wants the answer to that question. I do, too. But that is not the first question to ask.
The first question is “how”?
So, let’s discuss “how”.
First, just as much as “when” depends on “how,” “how” depends on “where”.
We are still in the “first wave” of the pandemic. There are substantial differences in rates of localized spreading as well as containment measures: differences between countries and also within different regions/states of the same country.
For example, Lombardia (Milan region in Italy), London (UK), and New York City are all at a very different stage in their pandemic than the vast majority of the rest of the countries they are in. There are all sorts of very messy complications in assuming what a “second wave” could look like and when it could hit. A LOT of these complications arise from having different regions not maintaining contemporaneous strict lockdowns (because the virus spreads there later, or because of much lower population density, or because of different local health policies). I will not go into that as my head hurts just by thinking about it (I am maintaining a strict regimen of responsible alcohol consumption during the lockdown, so that is NOT the reason for the headache, thanks very much for asking).
I will add, however, one comment from Rhode Island Governor Gina Raimondo (another fellow Italian, and a former medtech VC) on Mon. Apr 13. Her remarks came during the launch of a regional coordination initiative between governors of NY, NJ, CT, RI, DE, PA, MA: “The reality is this virus doesn’t care about state borders, and our response shouldn’t either.”
I will focus below mostly on the US, since this is where I now live. I will also try to translate some lessons hopefully learned by other countries who entered the peak of their regional clusters before the US. For some background, please refer to the previous articles in the Timmerman Report.
Before I start, a (not so quick, it turns out) reminder. Lesson No. 1 with exponential infection spreading: you might think you are running ahead of the viral spread, but it is probably the virus that is way ahead of you.
There is now substantial evidence, as if things were not bad enough, that this virus has an R-naught (R0) probably well in excess of 2, which makes it very infectious indeed. If you want a primer on this, and do not want to read my older Timmerman Report posts, you should watch a movie.
“Contagion”, the eerily prescient film from 2011 on a fictitious pandemic originating from Hong Kong, in my opinion, should be shown in every house all around the world for the next 6 months. It should become practically required school viewing, and get a “posthumous” Oscar. Watch, in particular, the TV interview Jude Law’s character gives roughly mid-film. Though a great actor (one of my wife’s very favorites), he is not a good guy in the movie (and I am still confused by how he manages an Australian accent at times). BUT he is spot-on about exponential spreading. The scientific consultant to the movie, Larry Brilliant, helped eradicate smallpox. Apart from having the most apt last name in the universe (can you tell I am jealous? No? Did you forget my first name? Go check your Shakespeare), Larry is a GREAT epidemiologist: read more about him here.
Apart from a few, required dramatic Hollywood flourishes (a vaccine created, manufactured and distributed in only 133 days against a totally new virus is practically science fiction; viruses do not “mutate” dramatically that quickly, etc.), the movie covers incredibly well virus provenance (also from bats originally), infectivity from touch (do not touch your face, wash hands), and contact tracing, as well as many other important aspects (who gets vaccine first etc.). I watch it almost once a week now. It does also have a happy ending, I think. This tragedy we are living through will, too.
Now, back to “when”.
I am assuming by now that you are all more or less familiar with the three gating “phases” to re-open US states’ economies in the coming months: after all, the audience of this report is quite knowledgeable about Phase I, II and III trials. And this is very much a trial we are all going through.
For those who are not as avid a consumer of news (or not US-based), the US administration has given state governors guidance and criteria on how to reopen state economies. Note that states (from the very little I know of the US Constitution) very much have discretion on how to execute these guidelines. The full outline from the administration is here.
There are a number of gating criteria which need to be satisfied before entering Phase I:
Subsequently to satisfying these criteria, each of the phases should last, at a minimum, 14 days. Phase I includes many of the current lockdown measures (avoid non-essential travel; do not gather in groups). BUT it says venues such as restaurants, churches and sport arenas “can operate under strict physical distancing protocols”. In Phase II, non-essential travel can resume, schools can reopen and bars can operate “with diminished standing-room occupancy”. Phase III is almost back to our old definition of “normal”, in which states that are seeing a continued downward trend of symptoms and confirmed cases could allow “public interactions” with physical distancing and unrestricted staffing at worksites. Visits to care homes and hospitals can resume and bars can increase their standing room capacity. The at-risk demographic should still avoid public, crowded areas.
So, back to “how”. What do we need to achieve to get even to Phase I?
Until we see ALL these fundamental steps in place, NATION WIDE, it is very hard to start thinking about “when.” If only New York were to follow these steps, then it’s only too easy for people to spread the virus elsewhere as people travel around the country by planes, trains, buses and cars. What we are doing right now with social distancing measures, and at incredible, horrific economic costs, is lowering R-naught (R0), the rate of infection of the virus, below 1. This is essential if we are going to catch up.
There is evidence it’s working. Every day there is a lower number of new people who become infected. This is a prerequisite step to be able to reduce the number of infected people to manageable numbers. The painful work of social distancing to bring down the rate of transmission has to be done first. Without that step, testing and contact tracing are impossible: there are just too many people infected to trace all their connections.
Think of New York City, with roughly ~50% tests coming back positive: how do you trace contacts in a densely populated urban area, which necessarily requires the use of public transportation to function, when there are so many cases? Also do not forget, New York was very much part of the first wave: the same will apply to any other large metro area as soon as we relax restrictions, without having a commensurable capacity of performing tests/contact tracing (and provided we have rapid assay formats).
So, it is sensible, in the government’s guidelines above, to stress a “reduction” in the number of positive tests over 14 days (roughly the period required for a person to not infect others any more). This should allow the current pool of people infected to shrink, perhaps even very substantially, to numbers low enough to be traced if tested positive. I also encourage you (if you have not gotten to watch the movie yet) to do a mental exercise of how many people we interacted with in close proximity, and how many surfaces we used to touch during the “old normal” days we used to live in. It is literally hundreds, at least in my case (Italians are eminently social and we are also quite tactile in our social interactions). Again, watch “Contagion” (Disclosure: I do not receive royalties on the movie streams…).
So, now to the (blind) guessing part: “when” do we think we might have figured out the “how” well enough to hazard some projections for when Phase I will start?
Spoilers: I do not think it is going to be before June, at the earliest. This is not a pessimistic projection, I believe. PLEASE take that with a “couple of mines” worth of salt. I would really like to see some random RNA and serological testing in a couple of places (outside of NY or NJ or Michigan) to understand more how diffused the virus is in the country. As of this writing on Apr. 17, we are still flying blind. I cannot wait to see the results of the serological random survey of 100,000 people that Germany is performing.
Some other random data points to support the very rickety framework I used to come to that “June” guess:
On Apr. 14, Anthony Fauci (in the impossibility that anybody who reads this does not know who he is, “Tony” is director of the National Institute of Allergy and Infectious Diseases (NIAID) and member of the White House Coronavirus Task Force), told the Associated Press that the May 1 reopening projection was “a bit overly optimistic” for many areas of the country. That’s because a strong testing and tracing system would be needed before social distancing measures were lifted. I guess we all agree with the good doctor here, especially since Fauci is an Italian name (which, hilariously enough, means “Jaws” in Italian: the comic implications / associations with the movie of the same title and the various decisions made by elected officials in said movie are too funny to mention). “Overly optimistic” feels a bit “overly kind” to that prediction statement, but, you know, some people have to be mindful of their audience.
Yesterday, Apr. 16, New York Gov. Andrew Cuomo said that his state would remain under stay-at-home orders until May 15. New York is likely beginning to descend the slope of the infectious spread. Note that a number of other countries (from Italy to the UK) have repeatedly pushed off the timing of a potential “re-opening” due to the scale of the infection spread being detected as more testing has gone online. I am guessing the same thing will happen here, especially since New York is detecting a positive testing rate of ~50% of tests – an incredibly high rate. The statistic can be biased since they are only testing people at high probability of being infected, but still.
Germany will reopen schools on May 3, with Austria even earlier than Germany. Both countries did a great job of containing the infection early on, have first-class and abundant hospital critical care units (Germany has the highest ICU bed concentration probably in the world) and both scaled up testing very early. So, even states and cities which were very much hit in the first wave might need to wait longer to get there. Not every city / state hit in the first wave is in the same spot: The San Francisco Bay Area and all of California are way ahead of the curve. So is Washington state: both acted early and ramped up social distancing / testing early, and have also much lower population density than New York City.
The issue is then, again, the “where” to decide the “how” that gets us to “when”: you can see here when different states issued stay-at-home orders. The differences are very wide, and frankly, puzzling. How do we solve for interstate travel/traffic to avoid a large second wave, at the same time as summer kicks in and people want to escape their home confinements and rejoin families/ friends as soon as restrictions are lifted?
This is a huge problem, and has massive implications for how we behave. I do not think we can simply rely on individual self-policing of behavior. I know this does not jibe with the ruggedly individualistic, “frontier” culture of the country. But, guess what: the virus does not care. We should.
Follow Otello Stampacchia on Twitter: @OtelloVC
This article expresses the personal views and perspectives of the author. The views and perspectives expressed here do not necessarily represent the views or perspectives of Omega Fund Management, LLC or any officer, director, partner, member, manager or employee of Omega Fund Management, LLC or any of its affiliated entities.
“Testing capacity”, as well as “contact tracing” are very vague terms. As I am not sure everybody is familiar with what they actually mean, here are some thoughts: to test and contact trace effectively, at the scale we are talking about here (literally hundreds of millions of test), you need to think and coordinate a huge number of factors (each of which is very likely a rate-limiting factor). Some of these factors are: type of testing (batch testing in a central laboratory, which can process at high throughput a large number tests but has slow turnaround, vs localized testing in city hospitals?); number of locations where tests are available (dense cities vs rural areas: you do not want people piling up in a queue to get tested); number of total test kits; reagents needed to produce the tests (which are in very scarce supply right now); personnel trained to extract the material needed to perform the test; personnel trained to perform the test (they are not necessarily the same); protective equipment needed for all this personnel. Same thing for contact tracing: it is a process that needs to be taught, requires a certain amount of psychological expertise and understanding of what is going through the head of the person in front of us, who might well be under a certain amount of distress. So it’s hard to train thousands of people to perform this without some technical tools to aid in contact tracing. So this is not simple. And every US state should not have to go through a steep learning curve to develop all this infrastructure, in all its complexity and inevitable mistakes, on their own. This is where it pays to adopt best practices in a coordinated fashion across the country.
Ruth Etzioni, Full Member, Division of Public Health Sciences, Fred Hutch Cancer Center
Last week I felt like I was coming down with something. My throat hurt and I had a bit of a dry cough.
A dreadful feeling set in. Obviously, I had COVID-19.
My mother and her partner, both in their 70s, are currently living with me in Seattle. My friend’s son had recently returned from New York. A few days earlier, I had chatted briefly with him (outside, keeping my distance) not realizing he would be diagnosed shortly thereafter. These factors made me eligible for testing through my employer, Fred Hutch.
Thankfully, I was negative.
I never thought that my test might have been a false negative, that I might actually be harboring the virus and still capable of spreading the virus to those around me. No, in this case I had confidence in the accuracy of the result. I heaved a sigh of relief and returned to my socially distanced life. When my symptoms cleared up quickly, it seemed to confirm that the test had been accurate.
But many people who get tested for COVID-19, and are told they do not have it, are not so lucky. It has been estimated that as many as 30 percent of patients with negative test results are “false negatives.” That means they actually are infected, and able to infect others.
Many of us trust the tests we take, and believe the yes-or-no results they return. But we need to be more curious.
In the fraught deliberations about the optimal path to re-opening the US, one theme has emerged louder and clearer than any other: testing, testing, testing. In practically every forum and on practically every stage a consensus has emerged that if widespread rapid testing is not made readily available, and easily accessible, the US cannot reopen for the business of everyday life. But it’s not that simple.
There are two main types of tests. Diagnostic tests are designed to tell you whether you have the virus: are you sick now? Antibody tests, also called serologic tests, are designed to tell you whether you had the virus in the past: were you sick and are you now immune?
It is not altogether clear which test is the magic bullet that will return our lives to normal. Right now in Wuhan, both are being used; diagnostic tests to find existing asymptomatic cases and serologic tests to learn how much of the population still remains susceptible.
There are at least 95 antibody tests and the number keeps going up. Yet, we have little information about how well they work. This is most certainly not front and center in press releases and advertisements.
We need to be much more curious about this.
No test is completely accurate. There are false negative results, meaning that the test is negative, but you are sick. There are also false positive results, meaning that the test is positive, but you are just fine. And some tests have much better performance than others; their error rates are lower.
Development of new tests involves rigorous assessment of these two types of testing errors, by examining the test results for people known to have the disease and known to be disease-free. The process of actually creating the test involves a lot of tweaking and refining to produce error rates that are acceptable. It’s a little like having a custom jacket tailored to your size and build. The jacket fits you well, but how will it fit the average person?
To assess this, the test performance needs to be confirmed, or validated, in a whole new sample, with no tweaking allowed. This is like seeing how well your tailored jacket, sitting in a boutique, fits folks coming in off the street. Many of the new antibody test have not been validated. This means that the error rates cited (if you can find them) are likely to be too low, making the test performance seem overly optimistic.
Different types of testing errors have different consequences. Sometimes people worry more about a false negative than a false positive. Women going for their annual mammogram are far more concerned about a false negative – not finding a silent tumor – than a false positive – having an unnecessary biopsy for something that looked suspicious but was actually nothing.
What are the consequences of testing errors in the case of COVID-19 tests?
For diagnostic tests, a false negative test has two potentially fatal consequences. First, it means that an infected person can continue in principle to keep spreading the virus; second it may delay the opportunity to offer potentially life-saving treatment. A false-positive test, on the other hand, is less consequential; it will increase the likelihood of self-quarantine for a time. Thus, for diagnostic testing, it is clear that we need tests that are highly sensitive, meaning that they almost never miss a case of the virus.
Interestingly, the opposite is true for antibody tests. Let’s first note that these tests are really only useful for asymptomatic individuals who do not know whether they had COVID-19 in the past. A false negative antibody test means that a person who has had the virus and recovered gets told they never had it. This is unfortunate for the individual who is immune and does not know it, and will certainly put a damper on their lifestyle. If the opportunity exists to do serial testing, then requiring more than one negative test result could bring down the fraction of people so affected.
In the case of antibody tests, the real problem is the false positives. The false positives will be told that they have antibodies but in fact they don’t. They will likely resume life with a vengeance (I know I would), distancing themselves from the memories of social distancing, potentially exposing themselves to becoming infected and then spreading the virus to others. So, in the case of antibody tests, we really need to focus on making sure that the false positive error rate is exceedingly low.
How low is low enough? It turns out that we can actually answer this question, but it requires knowing what fraction of the population is still susceptible. Even in Wuhan, only 2-3 per 100 people tested had antibodies, so the vast majority were still susceptible. In the state of Washington, the early center of the US outbreak, the fraction of people with antibodies is closer to 1 per 1,000. This means that even if the false positive rate is very low at 1%, 9.9 people per 1,000 tested will be wrongly informed that they have antibodies; scaling up, this would amount to 9,900 per million people tested going about their lives under the mistaken impression that they were immune. It is easy to see how this could provide sparks for new clusters of infection in the absence of a vaccine or other means of eradicating the virus. So, when the prevalence of true cases is low, the antibody test has to have a vanishingly small false positive rate.
When we think about getting a test, particularly for a disease that scares us, like COVID-19 or mammography, we naturally think about sensitivity – if I have it, will the test detect it? We want to know that there will be no false negatives. But false positives can have enormous costs, not only for individuals but for society. A study of women getting mammograms estimated that, over ten years, at least half of women screened annually received at least one false-positive recall. Many went on to have unnecessary biopsies, with all the pain, cost, and anxiety these create.
There are many other questions about the new antibody tests, including the extent to which they actually measure immunity. This only reinforces the message: Be curious; Trust less.
I should have heeded my own advice when I went for my own COVID-19 diagnostic test. It’s human nature to breathe a sigh of relief, like I did with that negative result. But it’s not too late to be skeptical. I’ll do better when I get tested for antibodies one day. First, I’ll ask which test is being used, and whether it is from a reputable source. Then I’ll read the fine print about the testing error rates.
Today’s guest on The Long Run is George Scangos.
George is the CEO of San Francisco-based VIR Biotechnology.
VIR has been all over the news the past couple months. It’s at the forefront of companies racing to discover and develop broadly neutralizing antibodies against the SARS-CoV-2 virus that’s sparked a global pandemic.
George Scangos, CEO, VIR Biotechnology
VIR was founded in early 2017 by some deep pocketed venture investors who saw big strides being made in immunology for cancer, but a gap in how that immunology was being applied against infectious diseases.
VIR was able to pull together a lot of money, a variety of technology platforms, and a lot of smart people over the past three years. If you have time for a deeper backstory, listen to a previous episode of The Long Run from a year ago.
The company has been making progress, but the value of its work became more abundantly clear as the world came to grips with the seriousness of COVID19 in January 2020. It has an antibody discovery platform that could be quite useful in the near term. VIR has working intensely with partners that can help with various aspects of the effort – GSK, Alnylam Pharmaceuticals, WuXi and Samsung Biologics among them.
In this conversation, George spoke about the scientific rationale for what VIR is doing, and the changing approach to collaboration and regulation necessary to operate at pandemic speed.
Now, please join me and George Scangos on The Long Run.
The Long Run is sponsored by RareCyte
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Alex Harding, MD, associate, Atlas Venture
Halfway through an explanation to a patient I am treating for a suspected case of COVID-19, I realize I don’t know the Spanish term for “sanitizing wipes.”
I’m in my new clinical home base, where Massachusetts General Hospital has cordoned off special care for COVID-19 patients.
There are modular plastic walls and bright fluorescent lights. A few weeks ago, this space was converted from a parking garage for ambulances into a fully functional medical clinic for patients with respiratory illnesses.
The floor still has painted lines to indicate where the ambulances are supposed to park. Drops of motor oil from a leaky ambulance engine have stained the concrete. I’m sitting on a stool in front of a computer on wheels. The only other items in the room are three boxes of rubber gloves, a wall-mounted hand sanitizer dispenser, a floppy disposable stethoscope, and an exam table where my patient is perched, hands on her knees, waiting for me to finish my sentence.
I fill in the blank with “paper towels with Lysol.”
She nods, and we move on.
She almost certainly has COVID-19. She has a high fever and a cough, muscle aches throughout her body, and a sensation of tightness in her chest, like she can’t take a full breath. She also has an important risk factor: She lives in Chelsea, MA.
Chelsea, a community just outside Boston with 40,000 residents, most of whom identify as Hispanic or Latino and many of whom are below the poverty level, has been hit harder by COVID-19 than any other town in Massachusetts. Although it is separated from Boston by just a short bridge across the Mystic River, it nonetheless has an infection rate nearly triple that of Boston.
There has been some speculation that this discrepancy in infection rates is because of biological differences that may place Hispanic people at higher risk of infection.
I favor a simpler explanation—that low socioeconomic status is a risk factor for COVID-19.
My patient had a retail job and was still required to go into work while the pandemic ripped through Massachusetts. Being at work in a retail setting, coming into close contact with many customers per day, put her at higher risk for exposure than people in white collar jobs that can be done from home.
She also lived in a three-bedroom apartment with her husband and kids, parents, and her brother-in-law’s family. Her nephew had been sick with fever for several days. Any of those relatives, and all the people they came into contact with, could potentially have spread the virus to her.
Based on her symptoms and risk factors, I advised her to isolate herself in a room to avoid getting her family members sick. She asked me how she could do that when her nephew was already self-isolating in another room, leaving just one room for 8 other people. The math didn’t work out.
People from lower socioeconomic groups are less able to perform many of the protective measures that reduce the risk of COVID-19. They often don’t have jobs that can be done from home and can’t afford to give up hours. Call in sick day after day, and you might lose your job. They sometimes live in close quarters with large extended family units, making it hard to perform home isolation. And they lack certain amenities that facilitate social distancing. People without laundry machines at home have to use laundromats, for example, which means potentially coming into contact with other people, or touching surfaces that have been touched by many other people.
Lower income patients also have a more difficult time accessing healthcare. They may lack insurance and fear getting a large medical bill. They may not have a primary care doctor. And in the case of immigrants, like many of the people in Chelsea, they may fear deportation if they seek medical help and are discovered to be undocumented. As a result, we have been seeing many patients wait until their illness is severe before seeking care. Sadly, some have died because they sought help too late.
In theory, coronavirus is indifferent to someone’s ethnicity and bank statement. But in practice, social factors play a powerful role in determining a person’s health outcomes. Chelsea, as a low-income community, has felt the consequences of that imbalance during this pandemic.
While all our attention is turned to COVID-19, this is a lesson that applies to drug development in general. Basic science might happen in test tubes, but human disease happens in the real world and is just as complex as human society itself.
Unfortunately, biopharma’s clinical trials have not geared toward the people in greatest need. In a review of 230 oncology trials from 2008 to 2018, for example, only 6.1% of patients were Hispanic and only 3.1% were black—far below national averages for both groups. The result is that our future drugs are being studied in distorted populations that do not represent all the patients who could be treated with those drugs in the future. We are not accurately capturing the biological differences between ethnic groups, but, just as importantly, the social differences between us that affect how we experience disease.
Mass General Hospital and the local government are working together to counteract the disadvantages facing Chelsea during this pandemic. The hospital has given away thousands of ‘quarantine kits’ containing masks, soap, and educational information to residents. A hotel is now accepting COVID-19 patients who cannot effectively quarantine themselves at home. Mass General is undertaking mass testing campaigns to identify cases in the community early. And the hospital has opened the doors of its clinic in Chelsea to everyone who comes in, regardless of whether they have a Mass General doctor.
We’re starting to realize that we need to do more to support vulnerable communities like Chelsea during the COVID-19 pandemic. We should take this lesson and apply it to all aspects of medicine and drug development. People respond to diseases and therapies differently based on socioeconomic factors. We need to make sure not to leave any groups behind.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Ruth Etzioni, Full Member, Division of Public Health Sciences, Fred Hutch Cancer Center
A few years ago, I was preparing for a live radio interview about prostate cancer screening, my main area of research for the past 20 years.
As a statistician focused on getting the numbers right, I disagreed strongly with the new national recommendation from an influential task force that guides practice and reimbursement. Members of that task force argued against routine population-wide screening for this most common cancer in men, saying essentially that there wasn’t any discernable benefit.
In the last few seconds before we went on air, the host whispered to me, “just don’t talk about numbers please!”
The problem was not with the numbers, I told him. It was with a faulty comparison.
To support their recommendation, the panel had relied heavily on data from a national, randomized clinical trial that showed similar numbers of prostate cancer deaths among men screened and not screened.
This was the obvious comparison to make, the one mandated by established research principles, and the one for which the data was readily available.
But it was the wrong comparison.
It turned out that the national trial had started late, after prostate cancer screening was already commonplace. It was not a comparison of screening versus no screening; rather, the trial compared a group that had been screened against a group that had been screened almost as much.
As we face critical decisions about whether and how to resume our daily lives in the midst of the COVID-19 pandemic, we are being tempted into making the wrong comparisons again. This may be dangerous for individuals, but it could be catastrophic for national and state policies.
Comparison 1: Number of lives lost (so far) because of COVID-19 versus the seasonal flu. Even as the numbers change, the current projections of COVID-19 deaths (estimated at approximately 60,000 as of yesterday) are being compared with the reported deaths from flu in the current 2019-2020 season.
The CDC’s latest estimates are that 24,000 to 62,000 US deaths can be attributable to the flu in the season stretching from Oct. 1, 2019 to Apr. 4, 2020.
If all you did was look at the current COVID-19 projection, and compared it with the upper-end worst estimate of this year’s flu season, you could say they are in the same ballpark.
But this is a faulty comparison. The deaths from these two illnesses are occurring under completely different circumstances.
The COVID-19 deaths are in the presence of a nearly national shutdown, with school and university closures and widespread practicing of social distancing. The flu deaths from last season occurred largely in the absence of all of these interventions. What would the number of flu deaths be if every winter we locked down early in the season, in October or November, like we are doing now for COVID-19? That is the question to ask.
The takeaway here is that if we want to compare COVID-19 deaths with flu deaths, we need to do so under the same prevailing policies. We could compare reported COVID-19 deaths with the flu deaths expected under current work/school closures and social distancing policies. Alternatively, we could compare COVID-19 deaths expected in the absence of any of these interventions with the flu deaths actually reported. Either way, we would not have hard data from past experience to work with. We would have to resort to modeling. So let’s talk about models.
Comparison 2: Numbers of COVID-19 deaths reported or projected today versus those projected by earlier models.
Much has been made recently of updated projections of COVID-19 deaths that are considerably lower that what was predicted based on earlier model reports. A highly influential model from Imperial College London, early in the outbreak response, predicted upwards of 2.2 million deaths in the United States if policymakers did nothing to mitigate the spread of the virus. Subsequently, a US-developed model from the Institute for Health Metrics and Evaluation (IHME) had projected between 100,000 and 240,000 deaths, taking into account the ongoing mitigation policies. This model is the one most frequently cited by the Trump administration, but its predictions have changed considerably as the pandemic has evolved, and now stand at approximately 60,000 COVID-19 deaths in the US by the end of August.
Some people are using the changing numbers to argue that our efforts to mitigate the pandemic have been wildly successful. Some are arguing that the numbers are proof that we overreacted and intervened too dramatically. This comparison of current model projections with earlier ones is even fueling calls to rapidly unwind social distancing policies and reopen the economy.
This is the wrong comparison to be driving any decisions about relaxing the current restrictions.
We can’t compare current observations or predictions from the model with earlier predictions as if they were set in stone. This gives far too much credibility to earlier versions of a model that could not have been expected to provide accurate predictions in the first weeks of COVID-19 spread in the US.
Originally, the IHME model was constructed to replicate the increasing and subsequently declining pattern of deaths officially reported by China. To port this model to the US setting, the modelers had to compress or stretch the China curve to match the accumulating US data. In the early days of the pandemic in the US in early March, the IHME modelers had about 70 days of data from China to work with. But there was very little data to tailor the model to the US experience. The current version of the model is privy to a more complete, but still evolving, picture of COVID-19 in the US; it also incorporates data from Europe. No wonder the results keep changing.
The takeaway here is that comparing different versions of a model to learn about facts on the ground is a mistake. If we want to discern the likely impact of mitigating policies, we need to be using the same version of the model to do the comparison. This could help us to understand how well current polices might be working and what to expect if in their absence. We should not lose sight of how limited models are and how uncertain their predictions can be, but we should at least use and interpret them in a defensible way.
And what of prostate cancer screening?
Ultimately, the question of prostate screening benefit was put to rest by a trial conducted in Europe before screening became widespread there, along with a set of related modeling studies based on all of the accumulated data. My team published that work in 2017, confirming that screening saves lives.
The general lesson here is not about models, or cancer, or even COVID-19. It is about thinking clearly when using statistics to make life-or-death decisions. The numbers do matter, but first you have to get the comparison straight.
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