Trust the experts. Believe in science. These are literal mantras that are in the air today. But I have to be frank and admit that I do not trust the experts on everything. If I have a lump in my testicle, I’ll trust the experts. But when it comes to rare events, the experts seem to suffer from some biases. When it comes to COVID-19 I’m very skeptical of experts. The reason I’m skeptical of experts is many of them didn’t anticipate the coming pandemic when they really should have.
Looking back at my record, it’s mixed. I spent much of the second half of January trying to get my wife to stop telling me COVID horror stories, as she was tracking Wuhan-related social media. Looking at the evidence we did have on hand, it looked scary. But, previous worries had been unfounded, and the idea that the pandemic would get out of control was not something I could rationally refute, but it was something I really wished would just go away.
On January 26th I mentioned coronavirus, but tried to diminish the downside risk. On the 2nd of February, I admitted I didn’t think that COVID-19 would be a big deal in a few years. But…things were changing. After talking to Greg Cochran, I changed my priors. In the first week of February we went and stocked up and I withdrew some cash (the infamous toilet paper run!). The episode of The Insight on coronavirus in February was recorded on the 16th. You can tell, I think, that I was already becoming seriously alarmed. I had expressed worries in the last week of January to co-workers but was dismissed as an alarmist. So in general I kept my opinions to myself, though on the 18th of February I took my daughter to the park and talked her friend’s dad’s ear off about coronavirus (he texted us in March to thank us for putting the pandemic on his radar). On February 20th I had my last meal indoors outside my home for 2020.
I remember February 19th, because that was when COVID-19 broke out in Iran, and I flipped my shit. I nearly didn’t go to the lunch appointment I had the next day. I couldn’t hope that there was something special about China that made it vulnerable anymore. The pandemic was going to happen, I was 100% sure then. I was very angry when Donald Trump visited India on the 24th and 25th. On the 24th my friend Default Friend asked if she should be worried, and I admitted my hysterical level of alarm (many scientists have privately messaged me and said that this was their wake-up call, as they were prompted to do research after my public alarmism).
Where were the experts? Well, I can’t survey them, but Stat News has done a great job covering COVID-19. I used the Wayback Machine to look at its front page all through February. On the following dates, COVID-19 was not their prime feature story: 3, 6, 7, 8, 10, 11, 12, 15, 19, 20, 24, 25, 26. After the 19th, when major figures in Iran seem to have caught COVID-19, I have no understanding why Stat did not pivot in totality to COVID-19.
The point is that when it comes to your own health you should keep your own counsel. Many of the public health experts were relatively sanguine deep into February. They excused Black Lives Matter protesters because of ideological affinity. They were against masks before they were for them. They talked about how border controls don’t work, but later admitted they had just asserted something they wanted to be true (?). These are people who I don’t trust because they show that their concern is not with facts, but outcomes. Social outcomes.
Like most people I initially underestimated coronavirus. Unlike most people I have a blog where I can see what I actually thought. My first mention of coronavirus is on January 26th, 2020. This is what I said:
In Coronavirus, a ‘Battle’ That Could Humble China’s Strongman. One thing I will say is that public health professionals are focused on the tail risk. The risks are real. But please note that the worst-case scenario may not be the most likely scenario.
My worries about tail risk increased gradually until the middle of February (I was still relatively sanguine in early February, though that is when we began to stock up). On February 24th I sent out a very alarmed tweet, and several people privately have told me that that’s when they also became alarmed (I tweeted in reaction to a private query from “Default Friend”).
So where are we at? I’ve been wary about giving predictions for a while because though the worst, worst, case scenarios were avoided (people have taken precautious), there are some pretty grim numbers out there. All that being said, I’m going to be cautiously optimistic. I don’t think we’ll double the death toll over the rest of the pandemic for a variety of reasons. If I had to bet. Unfortunately, I might turn out to be wrong. Who knows?
Finally, there is an intense bittersweet aspect to the stories about China in January and February. I’m glad China didn’t collapse in the plague. But as 2021 starts China is in a good position to keep pushing ahead in the great power race. I have a piece to come out in City Journal soon that ruminates on this tentatively titled “Twilight Empire.”
I’ve been seeing this Twitter thread being passed around my Facebook circles yesterday:
It relates to the curiosity of all of these #pangolinpapers being released on Feb 18-20, driving a mania that SARS2 came from pangolins; all 4 papers used the same 2019 dataset; there is a web of co-authorship (scroll to end of the thread cited here):https://t.co/wydmatOBmY
You’ve been tracking the pandemic deeply for quite some time. How plausible do you regard the theory from Alina Chan that COVID19 originated as a accidental/criminally incompetent lab leak from the Wuhan Institute of Virology?
“Tracking the pandemic” is a big job, and really you can only focus on a small subset of what’s going on. In mid-November 2020 we know a lot, but there’s a lot we don’t know. In fact, to be frank, we know a lot less than I would have thought in the spring of 2020. I haven’t been focusing much personally on the various ideas related to the origin of the current coronavirus that’s responsible for the COVID-19 pandemic. So I will pass on a few things:
– As early as late February a friend who has done work in evolutionary genetics and pathogens mentioned that both they and their mentor suspected the Chinese were covering something up, perhaps lab escape, on a Zoom call with a few others and myself. This person was told to not even bring up such views by others at the time.
– Another friend, whose own area of expertise is molecular genetics, arrived at the same conclusion independently (lab escape) and devoted some time in the late spring to the topic and queried me about my own opinions (unfortunately I had far less clear or informed views than they did, though I did tell them that others had come to the same conclusion).
– A contact of mine who is well-connected in D.C. political circles told me at about the same time that there was worry that the Chinese were covering things up, but that the PRC has a track record of “going after” people with credibility that came after them, so many people were wary of sticking their necks out (obviously no one cares about Alex Jones’ opinion, so he can say whatever he wants).
– Finally, I think I can say that there are many people who find Alina Chan’s critiques and concerns quite credible within science (e.g., people who have spoken positively about her courage and views privately to me who work in academia or industry). I am included in that number. This does not mean she is correct. But, it does mean that the time has come to evaluate various possibilities in a calm and objective manner. It looks plausible that we will have a vaccine in 2021, and COVID-19 will be in the rear-view mirror. We need to take stock and examine what happened in January once we have the spare bandwidth.
I am by no means a Sinophobe. On the contrary. But the behavior of the PRC as a whole needs to be examined with clarity, rather than hopefulness. China deserves accolades for its ability to contain and crush COVID-19, but that doesn’t mean that their record is unblemished. At a minimum, the PRC was using WHO as its mouthpiece in January. But, it is not out of the realm of possibility that elements within the PRC are engaging in disinformation to cover-up their own culpability.
Note: Here’s a Boston Magazine profile of Chan and her ideas. If you don’t follow her on Twitter, I would suggest you do so.
About three weeks ago the Chinese reported a few instances of community spread in Qingdao. Five days ago a story broke that there were now 13 individuals. The government said they would perform 9 million tests.
Today the results came back on 7 million tests. None of them were positive. It turns out that the 13 positive individuals were traced back to a hospital that quarantined people who had tested positive abroad. Ultimately there was “less to see” here than we originally thought since it is reasonable that now and then COVID-19 might leak out of the quarantine hospitals.
In February I was doing some “back-of-the-envelope” calculations and they suggested that a bad-case (but not worst-case) scenario was 250,000 deaths in the USA. We are probably already there in terms of excess deaths. I wasn’t pessimistic enough. It is not implausible that we’ll reach 500,000 deaths, though the combination of social distancing, monoclonal antibodies, and infections of those at lower risk first before herd immunity, and probably next year vaccination, will mean we’ll be in the 300,000-400,000 range of excess mortalities.
The situation in China is different. And surprisingly so. It seems that the 1.4 billion Chinese have successfully implemented the “contain and crush” strategy. They crushed the virus in Wuhan. But then they also crushed the virus when it resurged in Manchuria and a district of Beijing. All the powers of an authoritarian state were brought to bear, but it seems likely that the public has a high degree of compliance in China.
Of course, this elicits the standard skepticism of China’s numbers, which I initially shared. The reason I believe that the Chinese have contained COVID-19 is that the people in China themselves seem to think it is contained. You can watch how “normal” people behave in public. You can contact ex-pats who live in China. Life is back to where it was.
Finally, is there a moral to this story? You can draw your own conclusions in terms of comparisons. I’m happy that the Chinese seem to have COVID-19 under control, but I’m worried about America’s comparative state and social capacity…
I haven’t been talking about coronavirus much. What’s there to talk about? In April I tried to be optimistic, and well that didn’t work out. We’re not at worst-case disaster scenarios, but likely “excess deaths” of 200,000 don’t look good. The idea expressed by some (and which I really hoped for) that weather or decreased virulence would “take care” of coronavirus seems to have not panned out.
The two very positive things for me are:
– children seem relatively unscathed. The original age-trends hold
– the outdoor spread is very low. The “superspreader” events tend to happen indoors
A possible point of optimism, which I’m uncertain of, is that “herd immunity” may in some cases be lower than 70%. In many areas, it looks like “herd immunity” is really what’s going to happen, though treatments and vaccines may be important for some regions (e.g., Taiwan).
Anyway, I was curious about public and media concern about coronavirus, so I looked at Google Trends. You can see the public, against the baseline peak, tends to delay a bit. The American media also seems to have gotten bored with coronavirus into the middle of February, just like all of society (this is when some of the really stupid pieces making fun of coronavirus alarmists showed up in the bluecheck clickbait world).
There has been a fair amount of anecdotal and a bit of statistical evidence that obesity is somehow associated with individuals who have worse progression of COVID-19. The data out of China I saw wasn’t significant statistically speaking. The problem? There didn’t seem to be enough obese people in their samples. Then anecdotes and some data came out of Europe implicating obesity as a risk factor. And, doctors started reporting a disproportionate number of obese patients in the ICU.
We conducted a cross-sectional analysis of all patients with laboratory-confirmed Covid-19 treated at a single academic health system in New York City between March 1, 2020 and April 2, 2020, with follow up through April 7, 2020. Primary outcomes were hospitalization and critical illness (intensive care, mechanical ventilation, hospice and/or death). We conducted multivariable logistic regression to identify risk factors for adverse outcomes, and maximum information gain decision tree classifications to identify key splitters….Strongest hospitalization risks were age ≥75 years (OR 66.8, 95% CI, 44.7-102.6), age 65-74 (OR 10.9, 95% CI, 8.35-14.34), BMI>40 (OR 6.2, 95% CI, 4.2-9.3), and heart failure (OR 4.3 95% CI, 1.9-11.2)…In the decision tree for admission, the most important features were age >65 and obesity; for critical illness, the most important was SpO2<88, followed by procalcitonin >0.5, troponin <0.1 (protective), age >64 and CRP>200. Conclusions: Age and comorbidities are powerful predictors of hospitalization; however, admission oxygen impairment and markers of inflammation are most strongly associated with critical illness.
I’ve reformated table 3 of the regression below. It’s important to note here that the whole population is infected. The table is assessing the risk out of the infected sample that someone is going to go critical (which means a host of things, but entails hospitalization). Remember that a lot of the comorbidities associated with obesity are in the table. That means the risk of obesity is viewed as an independent variable. One can make some mechanistic arguments about the inflammatory effects of lipids, etc. That’s neither here nor there.
When assessing the risk of various nations is that 3% of Japanese are obese, while 40% of Americans are obese. Read More
A lot of my Covid-19 commentary is on Twitter, but since I delete my tweets every 2 weeks it’s ephemeral. So I’ll post about once a week about a “status update” of sorts of my perceptions, predictions, and general sense.
First, I’m more optimistic than I was a few weeks ago. The main reason is that most of the nation is shut down, and social distancing is happening, broadly, albeit to various degrees. My mid-February back-of-the-envelope estimate of ~500,000 excess deaths is unlikely. I think the range of 100,000 to 200,000, given by the American government, is reasonable. But I’m hoping we can do a little better than that. Let’s say ~85,000.
The reason I’ll go on the low side is that I think there is still much to learn. And, a lot of the unknowns are “positive” for us in the medium term. If regional heterogeneity persists, that means we can learn from the successes (e.g., test-and-trace as in South Korea). Perhaps there is a “miracle drug” in the offing. We don’t know. I think the “worst-case” scenario of untrammeled infection is pretty well understood, so I don’t actually see as many downside unknowns.
A lot of people are asking me about the IHME model, and the fact that hospital bed shortfalls don’t seem to be as bad as the model predicted. I think this isn’t an issue with the model, it’s an issue with how accurate people think models are going to be. Model-building is important for fine-grained decision making but at the high level, the metrics are going to be more coarse. Currently, the COVID-19 epidemic is highly regional in the USA. A friend whose best friend is a medical resident at a New York City hospital confirms it is as bad as the media represents.
That being said, the western United States seems to be doing OK. The catastrophe in Washington state never really materialized. People are dying and have died, but the early actions of the government and populace of Washington seem to have forestalled a major outbreak. Similarly, the early actions of the Bay area leadership seem to have made a difference.
With that optimism put out there, we need to note the difference between mortality and morbidity. COVID-19 patients who have to go to the hospital use many resources and even mild cases have a longer course than the flu. More importantly, like SARS it is likely that for the severe cases, who outnumber the deaths by several folds, there will be lifetime problems.
Some parts of the USA will come out of lockdown on May 1st. Others will not. We will have a better sense of the variables that impact R and virulence as the summer progresses.
Of them, 53·1% were normal weight, 4·2% were underweight, 32·0% were overweight, and 10·7% were obese. Patients with obesity, versus without, were tended to have cough (P=0·03) and fever (P=0·06). After adjusting for potential confounders, compared to normal weight, overweight showed 86% higher, and obesity group showed 2·42-fold higher odds of developing severe pneumonia. Despite a non-significant sex interaction was found (P=0·09), the association appeared to be more pronounced in men than in women. The odds ratios (95% confidence intervals) for severe pneumonia in overweight and obesity was 1·96 (0·78-4·98) and 5·70 (1·83-17·76) in men, and 1·51 (0·57-4·01) and 0·71 (0·07-7·3) in women, respectively.
The average American adult has a BMI of ~26.5. We define “obese” as BMI > 30.
A friend of mine recently quipped that everyone seems to act like probability can be assigned two values 0 or 1. The same sort of logic seems to apply when it comes to talking about the environmental parameters which might affect the progress of COVID-19, such as temperature, humidity, and density. Many people seem to strenuously want to deny there is any plausible evidence that COVID-19 might exhibit seasonality. There is a fair amount of correlational work which suggests that there is an environmental factor shaping the spread and depth of COVID-19. And, we know three out of the four previous coronaviruses exhibit seasonality.
Well, I noticed this note on medRxiv today, Stability of SARS-CoV-2 in different environmental conditions. It’s a very short write-up of their experimental results. I don’t really know much about virology so I can’t evaluate it well, but you can see the figure above. As you increase the temperature the virus titer seems to drop much faster. At a very high temperature of 70 Celsius, they basically can’t detect anything after 1 minute.
Nearly every country is now combating the 2019 novel coronavirus (COVID-19). It has been hypothesized that if COVID-19 exhibits seasonality, changing temperatures in the coming months will shift transmission patterns around the world. Such projections, however, require an estimate of the relationship between COVID-19 and temperature at a global scale, and one that isolates the role of temperature from confounding factors, such as public health capacity. This paper provides the first plausibly causal estimates of the relationship between COVID-19 transmission and local temperature using a global sample comprising of 166,686 confirmed new COVID-19 cases from 134 countries from January 22, 2020 to March 15, 2020. We find robust statistical evidence that a 1◦C increase in local temperature reduces transmission by 13% [-21%, -4%, 95%CI]. In contrast, we do not find that specific humidity or precipitation influence transmission. Our statistical approach separates effects of climate variation on COVID-19 transmission from other potentially correlated factors, such as differences in public health responses across countries and heterogeneous population densities. Using constructions of expected seasonal temperatures, we project that changing temperatures between March 2020 and July 2020 will cause COVID-19 transmission to fall by 43% on average for Northern Hemisphere countries and to rise by 71% on average for Southern Hemisphere countries. However, these patterns reverse as the boreal winter approaches, with seasonal temperatures in January 2021 increasing average COVID-19 transmission by 59% relative to March 2020 in northern countries and lowering transmission by 2% in southern countries. These findings suggest that Southern Hemisphere countries should expect greater transmission in the coming months. Moreover, Northern Hemisphere countries face a crucial window of opportunity: if contagion-containing policy interventions can dramatically reduce COVID-19 cases with the aid of the approaching warmer months, it may be possible to avoid a second wave of COVID-19 next winter.
To be clear. Does this mean weather/climate determine whether COVID-19 will spread or not? No. Rather, I think that weather/climate has some effect on the margin on the R0. I am not sure of the exact reason, but if the virus degrades much faster in hot climates, that could be one explanation of why spreading is more limited. It also does not seem to be the case that tropical countries are going to avoid mass healthcare crises. Rather, as these countries formulate policies to decrease R0, it may not be as long of a haul.
I believe that many are worried that if there is some relationship between temperature and COVID-19, people will think they are safe in a particular climate. The way to deal with this is not to ratchet up skepticism to an inordinately high extent. Rather, it is to be more clear and careful in how one presents the data.
Similarly, I think density has some impact. But, South Korea, Japan, and Taiwan show that density does not seal one’s fate.
I’ve been waiting for the pandemic to reach India. And not just me. Every day for the last week I see headlines which shout: “India the next hotspot!” In fact, Bloomberg put up a video interview, Is India the Next Coronavirus Hotspot?, predicting 300 to 500 million infections, just before I wrote this post.
But, it hasn’t happened yet. Yet. I’m not holding my breath. But until India explodes, we can still make jokes about caste, untouchability, and social distancing.
I just got off a podcast with Phillip “the Frog” Lemoine, where we discussed our coronablogging, and one thing we’re both struck by is the heterogeneity of the pandemic. The death rate is very high in Italy, rather low in Germany. And this difference persists. Spain is on an Italian trajectory, France is somewhat different. South Korea, Japan, Taiwan, and Singapore have contained the pandemic, all in somewhat different ways.
Coronavirus has been tardy to come to the tropics, and we’ve discussed why. Or possibilities for why.
But Phillip, and others, have marveled at the success of the Asian societies. Some peculiar internet Hindus claim that it illustrates the genius of the Sanatana Dharma. More generally, Hong Kong, Singapore, Japan, South Korea, Thailand, Cambodia, and India, are all are kingdoms of unreprentent heathenry. They do not bow before the God of Abraham, the God of Isaac, the God of Jacob. In contrast, Shia Iran was struck early, and the pandemic burns quite close to the seat of the Roman Catholic Church. The kami take their revenge against those who have given themselves to the new gods.
I jest. But I think differences will persist, and in a year we’ll know why. It looks now that New York City will be the “American Wuhan.” This is appropriate in light of the fact that New York City and Wuhan have the same population, and only New York City of the great American metropolises resembles those of the Old World in its density.
In two weeks China will lift its lockdown on Wuhan. Today we are arguing about nationwide lockdown in the United States. But it seems eminently plausible that conditions for the coronavirus pandemic will be attenuated in some regions in comparison to New York City. Our problems could be more regional than we’d expect, and our solutions might have to be too.
It’s the beginning of the official spring of 2020, and the United States of America is now in the midst of a massive upsurge in positive test results for COVID-19, the illness caused by SARS-Cov-2. Right now, New York City is the major focus. Seattle, which was an early outbreak hotzone has taken a backseat. The frequency and ubiquity of the positive test results suggest to many that this virus has been in these United States for a while.
One issue that keeps coming up: what are the environmental covariates of COVID-19? These are early days yet, but peculiar patterns such as Italy’s high death rate, and Germany’s low death rate, are not understood yet. One issue brought up rather early by President Donald J. Trump, is that weather warming might mitigate the impact of the virus. And there is a seasonality with many respiratory diseases.
Four human coronaviruses that cause colds and other respiratory diseases are more revealing. Three have “marked winter seasonality,” with few or no detections in the summer, molecular biologist Kate Templeton, also at the University of Edinburgh, concluded in a 2010 analysis of 11,661 respiratory samples collected between 2006 and 2009. These three viruses essentially behave like the flu.
The flu is not a coronavirus, but it’s the most famous seasonal illness.
One of the stranger things about the spread of COVID-19 is the relatively slow spread of the disease in many tropical locations. This is glaring in Southeast Asia, which has extensive contact with China (and some early introductions of COVID-19). In contrast, COVID-19 exploded outside of China first in Iran, and then in Italy.
Some early papers suggested there was no correlation with temperature or perhaps a very modest one. Others made a stronger case. The problem is with data. During the early days of the pandemic, there weren’t many data points, and those came from China. Now we have more data, and more analyses are coming out.
…While influenza virus has been shown to be affected by weather, it is unknown if COVID19 is similarly affected. In this work, we analyze the effect of local weather on the transmission of the 2019-nCoV virus. Our results indicate that 90% of the 2019-nCoV transmissions have so far occurred within a certain range of temperature (3 to 17C) and absolute humidity (4 to 9g/m3) and the total number of cases in countries with mean Jan-Feb-March temperature >18C and and absolute humidity >9 g/m3 is less than 6%. Current data indicates that transmission of 2019-nCoV virus might have been less efficient in warmer humid climate. We could not differentiate which of the two environmental factors is more important, however, given the tight range of absolute humidity (4 – 9g/m3) across which the majority of the cases are observed, and previous associations between viral transmission and humidity, we believe that absolute humidity might play a bigger role in determining the spread of 2019-nCoV. Theoretical calculations suggest that absolute humidity is always lower than 9 g/m3 for temperature less than 15C and for temperatures between 15 and 25 C, the relative humidity has to be >60% for absolute humidity to be >9g/m3. Therefore if humidity plays a bigger role than temperature, then the chances of 2019-nCoV transmission slowing down due to environmental factors would be fairly limited for regions above 35 degree N due to environmental factors. On the other hand, Asian countries experiencing monsoon from mid-June can see a slowdown in transmission. On the contrary if temperature is more important, then most of the northern hemisphere should see a slow down in the spread of the 2019-nCoV with the approaching summer temperatures. Our hypothesis is based on currently available data and its validity will automatically be tested in the next few weeks with reporting of new cases across the world. The relation between temperature and humidity and 2019-nCoV cases should be closely monitored and if a strong environmental dependence in the spread of 2019-nCOV exists then it should be used to optimize the 2019-nCoV mitigation strategies. Our results in no way suggest that 2019-nCoV would not spread in warm humid regions and effective public health interventions should be implemented across the world to slow down the transmission of 2019-nCoV.
The idea that absolute humidity (basically the amount of water vapor that is present in the air) matters comes in part from a 2009 paper, Absolute humidity modulates influenza survival, transmission, and seasonality. If flu is spread through droplets that are aerosolized, then more absolute humidity means water accrues to the droplets, and they don’t stay in the air as long. Though there is still some controversy about the details of how COVID-19 spreads, often it’s through droplets from coughing or sneezing (though the possible spread from asymptomatic people is troubling, as they would not be coughing or sneezing).
A critique of their data easily presents itself. Russia, at this moment, seems highly likely to be masking their cases. The pandemic is in early stages, and literally every day the media declares that India has the potential to be the next major epicenter. Pretty soon, within four weeks, we’ll probably see if every region of the world is going through the exponential increase that we’re seeing in the United States of America, making the climate modifier model moot. But we’re not there yet.
Figure 4 from the preprint presents their primary result (recapitulating earlier work), that most of the infections seem to occur at a particular temperature/humidity range:
You see here that the infections are occurring in the range of absolute humidity between 4 and 8 g/m3. There are all sorts of reasons these are artifacts, but this clearly comports with intuition when you look at the map of where infections are. As is clear in the preprint, the authors are not claiming that climate is the only variable that constraints or shapes the spread of the disease. To name some off the top of my head, density, cultural practices (e.g., physical greetings that require contact), age structure, and frequency of comorbidities and other infections probably matter.
Using a temperature and humidity table I computed when cities get “warm enough” to reduce the risk of COVID-19 transmission (I ignored the cold as a mitigator because I don’t think we really have enough reliable data):
Metro Area
The month when it gets humid enough
New York
June
Los Angeles
June
Chicago
May
Dallas
April
Houston
April
Washington DC
May
Miami
(all year within the zone)
Philadelphia
June
Atlanta
May
Boston
June
San Francisco
(all year outside of zone)
Seattle
July
Milan
June
London
June
Tehran
June
Mumbai
(all year within the zone)
Cairo
June
Karachi
(all year within the zone)
Lahore
July
The key point to note is that absolute humidity is dependent upon relative humidity and temperature. Very dry cities, such as Cairo and Tehran don’t do so well, because even though they get warm rapidly in spring, they remain dry. There should be a huge difference in Pakistan, between balmy Karachi, and Lahore inland, which is drier and more continental.
Unfortunately, San Francisco is too cool all year, though the whole region has many microclimates, so I wouldn’t overgeneralize. Seattle summers tend to be dry and only moderately warm.
Another major wild-card here is that air-conditioning is now very popular and widespread. This reduces absolute humidity in the environments that many people live in. Rural residents of tropical countries, who have less access to air-conditioning (and live at lower densities), may actually be relatively lightly impacted by COVID-19 compared to their jet-setting urban compatriots, who work in air-conditioned offices.