But regardless, taking a step back and looking at market movements over multi-year periods can provide a helpful perspective. And so as we near Tuesday’s election, I enjoyed seeing and reflecting on this Axios graphic:

I expect many people would look at this and spin it to support the political narrative they want to be true. And some of those narratives are probably right. But I think the real takeaways are that (1) on average the economy grows, (2) at most points in history the stock market has been at or near its all time high, and (3) there’s a big opportunity cost associated with attempting to time the market.

The post Presidents and the Market first appeared on Something's Brewing.

I was a bit worried the new system might not work well with my shoot-edit-publish workflow, but everything went smoothly, and so far the cloud platform appears to be faster and more intuitive. The AI-based search functionality is amazing, and it also seamlessly integrates all of my iPhone photos with my DSLR shoots, which was a major pain point previously.

There are still a few features from Lightroom Classic that have not made their way over, but the gap isn’t as wide as it was a few years ago (which is why I didn’t make the transition at launch), and I don’t think I’ll ever look back.

One of the benefits I did not initially anticipate was that having my entire photo library in the cloud makes it extremely easy to maintain a perfectly synced portfolio website. I’d previously done this this manually using Zenfolio, but it was time consuming and a bit of a clunky process.

So I spent the past week building a new portfolio website from the ground up, with every photo synced directly to Adobe Cloud: www.samuelkornstein.com

It has my portfolio, along with collections from nearly every major landscape shoot I’ve completed going back to 2008.

Hope you enjoy, and would welcome any feedback!

The post My New Photography Portfolio first appeared on Something's Brewing.

In my view, it’s probably a bit of each of those, but dominated by the sad fact that a large cross-section of non-public small and medium businesses will not survive, and large public companies that can weather the storm will ultimately be able to fill the supply void, and even buy their assets/IP for pennies on the dollar.

Case in point – my dad never used Amazon until a few months ago, and previously spread his retail purchases across a diverse group of businesses. I don’t think he’ll ever look back.

I’ve seen several articles suggesting the entire rebound has been led by the handful of technology firms that have out sized weight in the S&P 500 index, and that the value of rest of the companies in the index are down YTD. And while this is kind of true if you average a lot together, it’s a bit misleading.

So I was pleased to see this thoughtful visualization that my friend Robin shared recently:

It of course depicts the strong out performance of the large tech firms – Apple up 60% and Amazon 80% YTD – but it also very intuitively shows the nuance across different sectors and their relative importance to the overall market.

The post Under the Hood of the S&P 500 Rebound first appeared on Something's Brewing.

I’ve made my favorite steak a few times over the past month, and shared the recipe with a couple friends, which made me realize I might as well just post it here for future reference and sharing.

This has basically been borrowed from several other recipes and tweaked until I no longer felt it needed tweaking.

The Marinade:

• 1 jalapeño sliced
• 4 cloves garlic minced
• 1/2 cup of spring onions sliced
• 1/2 cup of fresh cilantro finely chopped
• 1/3 cup of olive oil
• 1 orange squeezed
• 1 lime squeezed
• 1 lemon squeezed
• 2 tablespoons apple cider vinegar
• 1 teaspoon ground cumin
• 1 teaspoon salt
• 1/4 teaspoon freshly ground pepper

The Steak:

You’ll want to marinate the steak for at least three hours, and up to six. You could probably use any steak and it would taste delicious. But there are two ways I usually approach it.

The more traditional cut is a skirt steak. Easy to buy at most butchers or at Whole Foods, and it’s reasonably priced. It’s thin, so you don’t need to grill it long, just enough to sear both sides. Once it’s done, you’ll want to cut it against the grain, which is a tad counter intuitive – it’s a long cut, and you’ll want to cut it the long way to get 3-5 long strips per piece.

What I’ve also done more recently, at the encouragement of my wife, is to use tenderloin / filet mignon, which you can also easily get at any butcher or at Whole Foods, but it’s most certainly not a bargain. I cut each steak into 3-4 large chunks to marinate, then then grill for 4-5 minutes per side, depending on how thick it is and how you like your steak. I try to get the outside charred a tad, with the center still a bit pink and rare. It’s like butter.

The Chimichurri Sauce:

This is a variation of a traditional chimichurri sauce. I tend to like it lighter and less oily than it’s normally prepared, so this version has more water than oil.

• 1 garlic clove
• 1 cup of parsley chopped
• 1 cup of cilantro
• 1 tablespoon lemon juice
• 2 tablespoons olive oil
• 3 tablespoons water
• 1/2 teaspoon salt
• 1/4 teaspoon pepper
• 1/4 teaspoon red pepper

Put all the ingredients in a food processor, Ninja, or blender for 10-15 seconds. That’s it.

The post Carne Asada & Chimichurri first appeared on Something's Brewing.

So I was quite surprised when both started growing new pads within a few days of being planted, and one of them flowered by the third week!

Here are a few pictures:

Still waiting to see if the fruit comes.

The post Prickly Pear first appeared on Something's Brewing.

For that one, I was in Thailand with my wife, and she thought I was completely nuts to plan our morning around watching a live rocket launch (it was actually quite convenient with the time difference, at around 9:30am). I’d watched all the previous failures (calibration exercises?), and until they succeeded, many didn’t think it was possible.

Next week will hopefully be an exciting new milestone for SpaceX and NASA. SpaceX is scheduled to launch two US astronauts to the ISS, which will be (1) the first time a private company has ever launched astronauts into orbit, and (2) the first time since the shuttle program was decommissioned in 2011 that the US has the capability to do so.

Needless to day, I’ll be watching the launch live on May 27th, currently scheduled for 4:33pm ET.

Last week, SpaceX released an ISS docking simulator to the public, which is basically what it sounds like. In a web browser, you can manually dock the Dragon space capsule with the ISS, using the same controls the astronauts would use during a manual docking sequence.

It was actually pretty simple once you get familiar with the controls, and I was surprised to pull it off on my first try:

I tried a second time with the goal of docking as quickly as possible, and came in too fast and crashed.

I found it to be an interesting learning experience, but suspect I’m in the minority here. I shared with a good friend and got this response: “I got bored and crashed into the ISS. It was anticlimatic.”

The post SpaceX ISS Docking Simulator first appeared on Something's Brewing.

I’ve spent the last 13 years in this neighborhood, living in three different houses. And it’s been awesome. Over that time, I went to grad school, started this website, got a new job, got married, and had two kids. The neighborhood’s been busy too, and has filled up with new bars, restaurants, shoppes, hotels, parks, and housing.

But a few things haven’t changed a bit. I sometimes bring my consulting clients to Whitey’s, and they actually brag about it to their colleagues and ask to go back!

So it’s bittersweet to share that tonight is my last night in Southie, and tomorrow our family is moving out of the city. The timing feels right for our next step, although we’re sure going to miss this neighborhood.

Thanks for the good times, and the great memories!

The post Goodbye Southie! first appeared on Something's Brewing.

My wife and I quickly arranged for me to be isolated in our basement, and I got in bed and took my temperature, which was 102° F. On paper, I had most of the COVID-19 symptoms, so I called my primary care doctor’s office, and was routed to MGH’s COVID-19 line. I went through their questionnaire and was told that in all likelihood I had COVID-19, but that due to limited testing capacity, I was not eligible to be tested.

I’ll come back to the lack of testing in a moment. But first, I feel very fortunate to report that whatever this was, it seems to have been mild. The rest of Sunday was not fun, and overnight was worse, but by Monday morning almost all of my symptoms were less severe and my fever was down to 100° F. By Monday afternoon my temperature was back to normal and has stayed that way.

I had a lot of questions for the nice woman on the MGH COVID-19 line about why testing wasn’t available for me. Not because I felt I needed a test – I’m low-risk and it wouldn’t have changed my plan to hydrate, rest, and stay away from my family – but because I had previously been following the outbreak statistics closely, and was under the impression that testing availability in Massachusetts had improved substantially. And testing is obviously extremely important for getting good data on what’s actually happening, putting contact tracing programs in place, and ultimately getting this whole thing under control.

I remembered in mid-March Governor Baker announced a goal of scaling daily tests from less than a thousand per day to 3,500. And then within a week, Massachusetts blew through that goal and was consistently doing 5-6k tests per day.

And yet I was told over the phone that MGH was generally only doing tests for:

• Individuals being admitted to the hospital
• Individuals with symptoms AND risk factors such as old age or other conditions known to increase the severity of COVID-19
• Medical professionals and first responders

I subsequently checked if I could make an online appointment for on of the drive-up testing sites, and received the same response.

In a limited testing capacity situation, this seems to be exactly the right thing to do. But it does mean that (1) actual cases are still being grossly under-reported, and (2) testing capacity is probably an order of magnitude lower than it needs to be.

I knew both of these were likely true before this experience, but it helped highlight the extent of the issue.

In mid-March everyone knew the data was significantly distorted by testing practices and the lack of capacity. But at this point I’d hoped that most people who were told by a medical professional that their symptoms matched COVID-19 would be able to get a test, and ideally we’d already be doing random testing to identify asymptomatic individuals as Iceland is doing.

Nate Silver had a nice piece on this – Coronavirus Case Counts are Meaningless. He uses four different testing scenarios in a made up country called Covidia to explain how testing capacity can both distort the understanding of what’s actually happening, as well as the right policy response. He highlights how small differences in policy responses and their timing can have significant differences in infection rates and deaths.

So what does it mean if we’re still only testing high-risk individuals? Here are a few thoughts, none are particularly original, but all are relevant to thinking about what has to happen next:

• Were significantly under-counting cases. If basically nobody under the age of 55 is tested unless they are high-risk or show up at a hospital, and young people are (1) much more likely to disregard social distancing recommendations, and (2) much less likely to need to go to the hospital when infected, I’d guess the real case count is 5-10x what we’re seeing. Possibly more if asymptomatic cases are as common as some reports are suggesting.

• We’re overstating severe case rates and death rates. If we don’t have a true handle on how many infections there are, the data will not be useful in getting an accurate estimate of the true rate of bad outcomes. Maybe that’s less important now when it’s more critical to estimate the absolute number of severe case hospital admissions, but it will be very important down the road when assessing risk and evaluating longer term policies.

• We don’t know where new infections are growing the fastest. This has important implications on social distancing policy, and where it needs to be stricter. Getting good at this seems critical to preventing a second wave once we get through this first one.

• We’re not yet equipped to properly conduct contact tracing. I understand Massachusetts has launched an initiative to begin tracing, which is great, but they’ll likely only be tracing the contacts of a small subset of infected individuals. But that’s not a reason to delay this, as first phases will likely have some impact and will provide valuable leanings that can inform improvements and help scale the program.

So what should happen next?

There’s been a lot of talk about the lack of competence in various levels of government. I agree with most of it. And yet it’s also clear that some state and local governments are doing an outstanding job, despite minimal support from the Federal government. I’d put Massachusetts in that group, all things considered.

At this moment in time, I’m not sure how useful it is to dwell on exactly how incompetent the incompetent people and agencies are. We can do that later. I’m fairly certain they won’t become competent over the next 8-12 weeks, which will be the most critical time to lay the groundwork for what society and the economy look like over the next year.

My take is that we still aren’t throwing enough money at the problem. At least in the right places.

Since Sunday, I’ve been encouraged to rest and work a bit less. Guidance that I’ve mostly followed. So yesterday I decided to review in more detail what’s in the $2.2 trillion stimulus bill. Here’s the simplest visualization I found:

Almost all of the money goes towards treating the symptoms of social distancing (e.g., keeping businesses afloat, unemployment benefits), which is important, but almost none towards eliminating the virus itself. We need to be doing both, otherwise social distancing will extend much longer, the economic costs will be much greater, and more people will likely die.

Why aren’t there hundreds of billions earmarked for scaling up testing so that every American can be tested multiple times, accelerating vaccine development (Bill Gates is obviously a hero in all this, but why shouldn’t the government be paying to build factories to manufacture all the vaccine candidates?), and deploying massive contact tracing programs leveraging a mix of technology (i.e., smartphones) and providing jobs to many of the newly unemployed people?

It seems that large amounts of money focused on eliminating the virus could be spent in some reasonably obvious ways:

Infection Testing. The technology to test if someone has COVID-19 exists. This seems to be a logistics/operations problem – how you scale and deploy that technology at an unprecedented pace? Smart people are working hard at this and doing incredible things – the US went from 25k tests per day three weeks ago to 135k today – but this clearly needs to be scaled more quickly. What would it cost to get to 20 million tests per day, and what creative solutions – potentially leveraging the Defense Production Act – could help get there yesterday? There’s been a lot of talk about using this law for the production of ventilators, but why not tests? We need to first be able to test anyone with any symptoms whatsoever, but then quickly pivot to randomly testing a portion of the population. It seems that an ideal solution – one that would facilitate some loosening of social distancing – would be to test everyone in the country that hasn’t already had COVID-19 every couple weeks until a vaccine is available.

Serological/Antibody Testing. Similar to infection testing, this technology exists and these tests are beginning to roll out in the US and many countries around the world. These tests will tell us who has already had the infection so that they can (1) confidently stop social distancing, and (2) potentially donate blood with antibodies to help those who have the infection. These tests also need to be scaled rapidly to a very large number.

Vaccines. Lots of people keep asking why vaccines take so long, and credible experts keep repeating that it’s likely going to be 12-18 months before a mainstream vaccine is available. I’ll be honest, I trust them, but I still don’t understand why. The progression seems to be: research, trials, mass manufacturing. Many vaccine candidates are already in the trial phase. What could be done to run elements of this in parallel, and what shortcuts could be taken that would be an acceptable risk given the severity of the virus? Also, it’s clear from Bill Gates’ announcement that you can expedite the whole process by starting to build manufacturing capacity for candidates before they are proven, with the implication being that the investment will be wasted if the candidate trial fails (or if it proves to be less compelling than another option). When the global economy is losing trillions of dollars, it’s smart to risk a few billion on this. But could even more funding build this capacity faster, or at a larger scale? Why not match the few billion Bill Gates is putting into this with another $10 billion? I read an article earlier about how in 1957 a US microbiologist was alarmed about a novel strain of the flu, and helped to develop a vaccine and manufacture 40 million doses in 4-5 months. That was over 60 years ago. I appreciate the technological challenges may be different, but surely there must be a way to match or beat that speed today when the government is in the middle of spending 10%+ of annual GDP on stimulus?

Contact Tracing. I’ve caught wind of some large technology firms being hired to design and implement these programs at the state level. To get this right, you probably do need lots of different experiments to nail down the approach, logistics, technology, and privacy. But the whole thing could move a lot faster if the Federal government awarded 10 or so pilot contracts at the state level, and promised the company with the most effective solution a contract to roll something out nationally.

Better Data: The states are all beginning to report data in a similar way, and there are many great academic, non-profit, and other web resources pulling together dashboards/tracking to help understand what is going on. But why not fund a much more comprehensive effort? This is basically the CDC’s job, but if the agency isn’t up to the task, outsource it. In addition to test results, hospitalizations, and deaths, there are many other things that should be tracked. Take me for example. I’m now in an MGH database, likely flagged as a clinical diagnosis of COVID-19. That’s not as accurate as a test, but it’s better than nothing. For every positive test there are probably many more people who called their doctor, reported COVID-19 symptoms, and were told to stay home unless they have trouble breathing. Why can’t a standard best practice for collecting and storing this information be defined, and then have the information be aggregated and reported for the entire US?

Congress is beginning to plan the next round of stimulus. I don’t mean to diminish the need for more support for individuals, families, and businesses. These should all be prioritized again. But I’d like to see some of the above items also prioritized in the same bill, such that meaningful progress can be made in the next 8-12 weeks and we can get this done with one more bill.

The post A few thoughts after being remotely diagnosed with COVID-19 first appeared on Something's Brewing.

The site is called 91-DIVOC and is updated several times per day with 4 charts:

• Cases by Country
• Cases by US State
• Cases by Country, Normalized by Population
• Cases by State, Normalized by Population

In each of the 4 charts, you can toggle to view any of 5 metrics: active cases, confirmed cases, new cases / day, deaths, and recoveries. You can also jump between linear and log scales.

There are the typical caveats that the charts are only as good as the data quality, and data quality varies significantly based on country/state reporting practices and differences in testing.

But putting that aside, this to me is the simplest and easiest way to determine what’s actually going on throughout the US. Here’s Massachusetts highlighted, looking at active cases by state on a log scale:

Another resource – The COVID Tracking Project – appears to be making good progress at providing clean data across all states, and rating states on their data quality to encourage best practices and consistency. Here’s an example, Massachusetts gets a ‘B’:

It’s encouraging to see that testing capacity is showing signs on improving. A week ago the US was doing 30-40k/day, while the past few days it’s been around 100k/day. I suspect we’ll need to exceed 1m+/day and include many people who are asymptomatic to really get a handle on community spread. While a bit late, at least things appear to be moving in that direction.

The post State by State Coronavirus Tracking first appeared on Something's Brewing.

The first is this article on Medium by Tomas Pueyo. Everyone should read this, and he’s helpfully had it translated into 26 languages. It’s the single best synthesis I’ve seen of everything going on.

He starts with this summary:

When you’re done reading the article, this is what you’ll take away:
The coronavirus is coming to you.
It’s coming at an exponential speed: gradually, and then suddenly.
It’s a matter of days. Maybe a week or two.
When it does, your healthcare system will be overwhelmed.
Your fellow citizens will be treated in the hallways.
Exhausted healthcare workers will break down. Some will die.
They will have to decide which patient gets the oxygen and which one dies.
The only way to prevent this is social distancing today. Not tomorrow. Today.
That means keeping as many people home as possible, starting now.

The most eye opening chart is his timeline of events in Hubei:

Due to the lag between when people are infected, and when they are diagnosed, it’s very likely that the true number of cases in many parts of the US is as much as 10X what’s been reported:

The grey bars show the true daily coronavirus cases. The Chinese CDC found these by asking patients during the diagnostic when their symptoms started.

Crucially, these true cases weren’t known at the time. We can only figure them out looking backwards: The authorities don’t know that somebody just started having symptoms. They know when somebody goes to the doctor and gets diagnosed.

What this means is that the orange bars show you what authorities knew, and the grey ones what was really happening.

On January 21st, the number of new diagnosed cases (orange) is exploding: there are around 100 new cases. In reality, there were 1,500 new cases that day, growing exponentially. But the authorities didn’t know that. What they knew was that suddenly there were 100 new cases of this new illness.

Two days later, authorities shut down Wuhan. At that point, the number of diagnosed daily new cases was ~400. Note that number: they made a decision to close the city with just 400 new cases in a day. In reality, there were 2,500 new cases that day, but they didn’t know that.

Later he makes some comparisons:

Washington State is the US’s Wuhan.The number of cases there is growing exponentially. It’s currently at 140.

But something interesting happened early on. The death rate was through the roof. At some point, the state had 3 cases and one death.

We know from other places that the death rate of the coronavirus is anything between 0.5% and 5% (more on that later). How could the death rate be 33%?

It turned out that the virus had been spreading undetected for weeks. It’s not like there were only 3 cases. It’s that authorities only knew about 3, and one of them was dead because the more serious the condition, the more likely somebody is to be tested.

This is a bit like the orange and grey bars in China: Here they only knew about the orange bars (official cases) and they looked good: just 3. But in reality, there were hundreds, maybe thousands of true cases.

He then goes on to talk about how to contain it, and what will happen if we don’t. Read it.

“Social Distancing” has become the core containment strategy. Last week very few people had heard this phrase, now it’s everywhere. And the Washington Post has a simple and outstanding simulation illustrating how this works: Why outbreaks like coronavirus spread exponentially and show to “flatten the curve”.

It’s short, and uses several simplified hypothetical simulations to demonstrate how effective social distancing can be. Here’s an example:

Anyone who watches these simulations will likely understand why social distancing is so critical right now.

In terms of data, I’ve found the Johns Hopkins dashboard is the best source to track what’s going on in any area. They aggregate data from all over the world, updated hourly. I find it frustrating to read news articles to get the facts about what’s happening in MA, as they always have an angle, and are inevitably outdated soon after they are published. This dashboard is a simple way to check on an area.

Here’s what’s going on in MA as of right now:

Using some back of the envelope math, if the true infected count could be 10X what we know today (i.e., 1,380), and the death rate stays at 1-3%, we should expect 14-42 deaths in MA over the next few weeks, assuming containment starts now, and much worse if it doesn’t. I hope I’m wrong about that, but that’s what I take from what I’ve read.

The post Good Data on the Coronavirus first appeared on Something's Brewing.