Post #904: Dryer air arrives in Virginia

Source:  National weather service (, downloaded 12/2/2020.

I’ve been tracking the relative humidity in my house for roughly the past month.  November had relatively few days with truly dry outdoor air.  Air that was both cold, and had low relative humidity.

Unsurprisingly, I’ve had to run my indoor humidifier infrequently, so far this year.

Today, and looking forward to the forecast for the next two weeks, that appears to be changing.

As shown above, today is cool and dry.  That 31% outdoor relative humidity (at 47F) would result in a roughly 15% indoor relative humidity at 68F, absent any other inputs of water vapor into the indoor air.  Today my humidifier is running constantly but my indoor humidity is slowly dropping anyway.

For the next two weeks, it looks like a typical day will be 45F with 55% outdoor relative humidity.  Absent any other inputs, those conditions will translate to an indoor relative humidity of 25% at 68F.  That’s a long enough period that houses and other indoor locations should be fairly well dried out by the end of it.  Absent a humidifier, indoor air in this region will be quite dry by mid-December.

If you wonder why I’m tracking this, refer to Post #894.  I heard from a few readers who purchased humidifiers after reading that.  If you have one, but haven’t unboxed it and set it up, now would be a good time to do that, I think.

Post #903: Population weighted trends

Why do you keep hearing that the US third wave of COVID-19 is getting worse, when most of the states appear to have peaked?  Like so:

The answer is that the US totals reflect the US population.  And the (mostly) upper-Midwest and Mountain states that have peaked are all low-population states.   There was a lot of COVID-19 activity there, but there aren’t a lot of people.

By contrast, over one-third of the US population lives in just five states (CA, TX, FL, NY, TX, PA).  And in those states, you are still seeing a broadly-based and slow ramp-up of COVID-19 activity.  I would say that they show almost weirdly similar paths, given how different those five states are from one another.

In fact, we have to broaden the view to the top ten states (encompassing more than half the US population) before we pick up even one of those Midwest states where there appears to be a clear peak in COVID-19 activity.  In the graph below,  the top line is Illinois.

And so the third wave of COVID in the US has this odd multi-part nature.

First, there were crazily high growth rates for daily new COVID cases in a cluster of Midwest/Mountain states.  That’s the peak of the mountain on the first graph above. All the states where the growth rate at some point exceeded 100 new cases/100,000 population/day.

Those high rates of growth seems to have “burnt out” for the time being. Most of those states appear to have peaked just prior to Thanksgiving.  Why those peaks were so nearly synchronous is something of a mystery, and probably always will be.  But, for at least one state — North Dakota — enough people got infected during that period that they have plausibly reached COVID-19 herd immunity, or close to it (see Post #901).

But where the bulk of US residents live, we’ve seen nothing quite so dramatic.  Instead, as winter slowly settles in, the COVID-19 new infection rates have slowly risen.

What’s I find particularly odd is that “winter” means different things, weather-wise, in those different states (CA, TX, FL, NY, TX, PA).  And yet, the lines on the graph look almost identical.

NY, PA, and TX all have what I would call a “traditional east coast” winter climate.  If you were to look up today’s forecast for Dallas and for Philadelphia, you would be hard-pressed to tell which was which without the labels.

Florida spans everything from more-or-less that climate (in central Florida) to a subtropical climate in South Florida.  And yet, the entire state shows high rates of COVID-19 activity.

California, or at least Southern California, is hot and dry right now, having recorded zero precipitation for November, and frequently recording outdoor relative humidity below 20% (due in part to Santa Ana winds).

And yet, we’re seeing more-or-less the same slow rise in new cases in all five states.  I guess that’s just another seemingly random aspect of this pandemic.

Post #902: The US third wave. Oddly orderly.

Source, here and below:  NY Times Github data repository.

The graph above is the US pandemic since April 1, by state.  As you can see from the height of the peak, the rapid growth in the upper Midwest and Mountain states was unprecedented.  But at this point, it looks like almost all of those high-growth-rate states have peaked.  And, weirdly enough, almost all of them at the same time.

Maybe that’s some artifact of Thanksgiving, but offhand, I don’t quite see how.  The states at the very top of the graph began to peak (in hindsight) one to two weeks before Thanksgiving.

For sure, this isn’t a consequence of recent actions by some of those state governments.  As discussed in my just-prior post, any consequences of (e.g.) mask mandates in IA or ND will begin to show up only toward the end of November.

Below is the tail-end of the same graph, starting 10/1/2020.

By eye, the lines for the various states sort themselves into three orderly groups.

  • Everything above the 100 new cases/100,000/day line shows a sharply-defined peak.
  • Everything from 60 to 100 new cases/100,000/day appears to show a broad, shallow peak, roughly coincident with the sharp peaks in the high-growth states.
  • Almost everything below 60 new cases/100,000/day does not year appear to have peaked.

Most of the lines 100 and above are for upper Midwest and Mountain states.  Most of the lines 60 and below are for East Coast and Southern states.  And the lines in the middle are a bit of a mixed bag.

I have no real idea what might be causing this.  Or whether I’m just reading too much into the graph.  I’m just noting how orderly and geographically clustered the third wave appears to be.  And that, for now at least, in the areas with the highest recent growth rates, the third wave appears to be peaking.

Here are the numbers, sorted in descending order of new cases/100,000/day, showing how far past peak each state is, and by how much.  E.g., South Dakota still has the highest rate of new cases/100,000/day, but the peak rate occurred 15 days earlier, and right now they are one-third (33%) below that peak rate.

States where the peak occurred recently, and where the difference from the peak is small, are states there the rates are probably still climbing.


Post #901: Maybe ND really has achieved herd immunity.

Source:  NY Times Github data repository, data reported through 11/27/2020.

This is one of those seemingly simple 2+2=4 analyses.   In this case, it’s literally 8*10 > 70.

The arithmetic isn’t rocket science.  Anybody can do that.  My only value-added here has been in keeping an eye on the situation, and realizing why that arithmetic might matter.

Right now, 10% of the population of North Dakota has been formally diagnosed with COVID-19.   As of data reported through 11/27/2020, they’ve had 77,242 known cases.  That’s out of a population of about 760,000 (per the US Census Bureau).  Or (77,242/760,000 = ~) 10%.

A 10/25/2020 publication by CDC staff says that, best estimate, on average, 8 people have had COVID-19 for every one that has been diagnosed. 

IF CDC staff are right, and IF that US average applies to the US Midwest, then North Dakota has probably achieved COVID-19 herd immunity.  Or is close to it.  And much of the US Midwest has or will be following suit in the near future.

Obviously, that’s two big ifs.  But anybody can follow the math.  That’s 8*10% = 80%, and that’s higher than the 70% conventionally thought to be required to achieve herd immunity to COVID-19.

Oh, and note the peaks on all the curves at the top of the graph above.

Discussion follows.  This brings together several points that I’ve brought up over the past two months or so. Continue reading Post #901: Maybe ND really has achieved herd immunity.

Post #900: Peak of the third wave: Is “dynamic herd immunity” capping the rate of spread of COVID-19?

Source:  Data from NY Times Github data repository.  Data reported through 11/23/2020.

An odd thing has been happening, even as the news is dominated by the worsening of the third wave of the pandemic nationally.  That third wave of US COVID-19 appears to be cresting in the states that led it.  And the strange part is that simultaneous crest across several states has nothing to do with any actions recently taken (or not taken) by state governments to contain the virus. 

The mere fact that some hard-hit states appear to have peaked, in terms of new COVID-19 cases per day, is not the odd part of this.  Here’s what’s odd.

First, note that several states peaked at just about the same time.  Within, say, a week of one another.  Two states peaking in the same week could be a coincidence.  But six or seven states?  Spanning more than 1000 miles?  All of them with extremely high rates of new COVID-19 cases per day?  It’s hard not to think that there’s something that ties that together.

Second, note that this peak occurred despite some states taking action and others not. Famously, for example, the governor of South Dakota refuses to institute a mask mandate or take other protective measures.

Third, note that these peaks occurred well before we could plausibly expect to see any results of any state actions, in any case.  For example, ND and IA mask mandates were passed 11/14/2020 (Post #890) and 11/17/2020 (Post #893), respectively.  Any reduction in infections that result from those changes could not possibly appear in the data prior to the end of November.

That’s due the “pipeline” of cases that are already infected, at any point in time, but haven’t yet appeared in the numbers.  It takes, on average, in most areas, about 12 days for any change in infection rates to appear in the data.  (That’s about five days from infection to onset of symptoms, and then another 7 on average for seeking medical attention, getting tested, and having the test results appear in the data).

Meanwhile, three other states in that vicinity have high case rates and continue with a relatively steep upward trajectory.  But all are well below the peak demonstrated by ND.

Finally, I need to supplement the above with one chart of states that got covered up in the tangle of lines above, and then the remainder of that block of states.

Note that, in particular, MN appears to have peaked in the last week.

And when I put that all on one map, it looks like this.  The block of green-ish states are those that a) had high rates of new cases and b) all appear to have peaked in the past, oh, week or so.  The red-ish states are those, in the same area, with high rates of new COVID-19 cases, but where trends continue upward, with no evident peak or leveling-off of new cases per day.

All pandemics are local.  And by that I mean that you’re going to be reading news articles about individual cities, within those states, that are running out of hospital beds.  And will continue to do so for some weeks.  But in terms of total cases within the states, for some reason, almost all of the states with extreme new-case loads decided to do a 180 in the past couple of weeks.  All in the same geographic area.  All at the same time.

Speculation on what might cause this.

First, let me be clear, I have no firm idea on what is causing this.  I just noticed the oddity, that’s all.

1:  Maybe it’s the weather, and so this break is temporary.  I note that this area had a heat wave just about weeks before these states started peaking.  That should have temporarily raised indoor relatively humidity, and if humidity is key to transmission (Post #894), should have slowed transmission.  And so, maybe this isn’t a peak, but it’s just a temporary break in the trend, due to that past weather event.

The problem there is that the heat wave affected all of those states.  Here’s Bismark, ND and Cheyenne, WY.  Pretty much the same weather pattern across both areas.  If it were solely an artifact of weather, we’d see a break in the trend for Wyoming.  Which we do not.

2: Maybe people wise up before their state government does.  The high incidence of COVID-19 in these states was public knowledge.  Maybe there’s some common threshold of hard-headedness that people can get past, with enough news coverage of how dire the situation is becoming.  And so, these peaks are an artifact of enough people waking up to the situation and changing their behavior, in each state, to break the back of the upward trend.

But the sharp reversals of trend, and the tight synchronization, don’t really seem to fit with that.  At least, not to my eye.  This has the look of something far more mechanical or automatic, and less the look of (e.g.) the will of the people shifting in favor of mask use.

3:  Maybe this is how herd immunity works in this situation:  It generates a natural cap on the rate of spread, for a given set of underlying conditions.  We keep hearing that we need 70% of the population to be immune before we achieve “herd immunity”.  That’s the point where the pandemic dies out for lack of enough “infectable” people to maintain the chains of disease transmission.  But maybe herd-immunity-type effects also limit continued rapid spread.

Herd immunity is not going to be a smooth process.  It’s not as if you’re going to run right up to the herd immunity level, and then have the pandemic stop all at once.  Instead, as a smaller and smaller portion of the population is at risk of infection, presumably the rate of transmission would slow.

At this point, best guess, somewhere around a quarter to a third of the entire population of North Dakota has already been infected with COVID-19.  (See Post #889 for details.)  That’s the roughly 8 percent that had been formally diagnosed, as of mid-November.  Times some unknown multiplier to account for cases that were never diagnosed (asymptomatic individuals and individuals with symptoms mild enough that they did not seek treatment or diagnosis.)

I’m not familiar enough with the techniques used to model epidemics to say for sure, but I’d bet that having a third of your population immune to the disease is enough to put a crimp in the rates of spread.  It might not stop it, but it might plausibly prevent the highest possible rates of spread from occurring.  Except for the fact that COVID-19 spreads largely via clusters, you’d be tempted to say, well, at this point, a third of the chains of infection that used to continue are now being truncated by running into an immune individual.

The point here is that that maybe the basic arithmetic of this pandemic makes the rate of spread somewhat self-limiting. Once it reaches some high rate of new cases per day, for long enough, the rate has to go down due to the rapid build-up of surviving immune individuals.

Notably, the case mortality rate for COVID-19 is now quite low (e.g., about 1% in the Commonwealth of Virginia).  That makes the situation for COVID-19 materially different from that of the 1918 Spanish Flu. With this low mortality, if  COVID-19 tears through a population rapidly, then it rapidly builds up a large population of immune individuals. And that large population, while not enough to stop the pandemic from continuing to spread, may be enough to cap the rate of spread.  The very fastest rates are no longer feasible, because enough chains of transmission are being truncated.

If so, that’s very good news for my “reefer test” ( Post #888).  That means that the rates won’t continue to climb until you finally run out of potential victims.  Instead, for a given set of circumstances, you’ll see the rates all peak around the same point.  And the commonality of that peak occurs because you’ve built up enough survivors to “clog up the works” just enough to cap the rate of spread.

As a footnote, I’ll bring back an earlier version of the diagram above.  Oddly, note that the two peak summertime states both peaked at just about the same daily rate of new cases.  Despite being in completely different climates and locations.  That was for the air-conditioning-led summer outbreak.  And now, with what I’d call the heating-led winter outbreak, we’re kind of seeing the same thing.  Just at a different level of new cases per day.

(But that may just be reading too much into the data.  There was a spectrum of peaks in the summer outbreak.  Obviously, the ones at the top are all going to be near the top.)

4:  Does “herd immunity” really require 70% of the entire population to be immune.  Maybe you run out of risk-takers well before 70% are infected.

How about people like me, who are basically minimizing exposure already, scrupulous about mask use, and wearing an aerosol-filtering fitted mask when shopping (Post #780, Post #807).  Does herd immunity require 70% of people in my situation to be infected before the pandemic stops on its own?  Or, by dint of isolating myself, am I more-or-less irrelevant to the herd immunity calculation?

Let me put it this way:  A vaccine provides (we hope) 90% protection against being infected.  We count (90% of) the vaccinated population as part of that 70% in the herd immunity calculation.

But suppose that a good mask and careful behavior results in 80% protection against being infected.  What’s the difference, exactly, between that, and being vaccinated?  (In terms of the herd immunity concept.)  The vaccinated individual is assumed to be (more-or-less) permanently removed from the pool of persons who can be infected.  The mask-and-behavior person remains at risk of infection, regardless.  So there’s clearly a long-run difference — the virus can slowly “pick off” persons from the mask-and-behavior pool, but not from the vaccine pool.  But in terms of breaking the chains of transmission, in the short run, I’d say that those two routes to stopping spread of the virus are roughly equivalent.  One terminates 90% of the chains, the other terminates 80% of the chains.  So to speak.

And so maybe, at some point, the population of risk takers that is responsible for high rates of spread gets thinned down somewhat.  Not by mortality, but by becoming infected and so becoming immune.  And so, even if just a third of ND residents are immune, maybe that’s a lot closer to 70% of the risk takers.

If so, the rapid spread attributable to failure to take precautions might be self-limiting well before 70% of the entire population is immune.  Maybe, to prevent the most rapid spread, all you need is 70% of the risk-taking population.  And that might be a much smaller fraction than 70% of the entire population.

Best guess:  “dynamic herd immunity”.

These synchronized and rapid reversals of the upward state trends, for the states with high growth rates, suggest a mechanistic explanation, rather than a behavioral one.

For sure, it’s not a result of government action.  That’s been piecemeal, and in key states (ND, IA) occurred far too recently to account for the turnaround.

The weather is something that would affect a broad area.  But the same heat wave that plausibly might have resulted in the peak in (say) SD also affected states where a peak has not yet occurred, such as WY.

Having the populations of these states all “wise up” at the same time seems improbable, given how close the timing is.

My bet is that the rapid growth is self-limiting.  The virus leaves so many immune survivors behind, in such as short period of time, that it chokes off that very rapid growth.  So it’s not herd immunity (that disappearance of the virus) but instead a natural limit on the rapid spread.  Rapid spread can only go on for just so long before it (in effect) chokes on its own impact on the population.

Let me call this “dynamic herd immunity”.  That’s the idea that a high rate of spread can go on for just so long before it has to slow down.  And that it will slow down well before 70% of the population has been infected.

How long that high growth may continue, and how rapid that growth can be, will of course depend on underlying conditions.  In these mask-averse states with dry and cold winters, that can proceed much faster than it might in states with good mask use and milder climate.

Seeing all these states, all peaking around the same time, around the same growth rate, suggests that there’s something about the mechanics of epidemics at work here.  My best guess is “dynamic herd immunity”.  A high rate of new case growth chokes itself off, at some point.  The virus will still be spreading, but at a slower rate.  And if so, that’s very good news from the standpoint of running out of hospital beds.  Maybe the lower apparent severity of the average case (Post #897), and “dynamic herd immunity”, mean that we won’t have to fail the reefer test after all.  We’ll manage to get through this, despite ourselves.

Post #899: Vaccine allocation rule is straight per-capita

Per this reporting from NPR, the initial doses of COVID-19 available in the US will be distributed across the States on a straight per-capita basis.  So I have to take back everything I said in Post #896.  Even if allocating on a per-capita basis isn’t the smartest way to do it, it certainly is transparent.

The reason this is straightforward may simply be a matter of arithmetic:  The number of doses they are talking about (6.4 million) is about enough to immunize half of US hospital workers (6.6 million, per the US Bureau of Labor Statistics), given that that these first two vaccines require two shots.

So, under these rules, Virginia should be allocated about 165,000 doses, which is enough to immunize just over 80,000 people.  At present, hospital employment in Virginia is listed as 165,000 (from the US BLS). That would not count (e.g.) physicians who have admitting privileges at those hospitals.

Bottom line is that allocation of the first round of vaccines is fairly uncontroversial, because it’s probably all going to be allocated to (and still not fully cover) hospital workers and similar high-risk front-line workers (e.g., paramedics, physicians).  It is unlikely to result in significant immunizations beyond that core group of health workers.

In short there’s really nothing to fight over, yet, regarding the allocation of vaccines to states.

Post #898: Quarantining your college student rationally. Or, should I lock my daughter in her room while I go grocery shopping?

This post is motivated by the need to bring my daughter back from college next week.  What I was wondering is, should we all be wearing masks in the car?  But more generally, what’s the standard protocol, quarantine-wise, for returning college students?

Seems like a fairly straightforward question.  Given that there are going to be millions of college students returning from campus to home in the next few weeks, it seems like there ought to be be some standard answer to that question.

Sure seems like it.  Ought to be.  But there ain’t.  Let me summarize what I found.

When I do the math, under the circumstances I face, the likelihood that my daughter is going to give me a COVID-19 infection is 1-in-30,000.  Over the same period, the likelihood that I would just pick one up, as an average member of the community, is 1-in-93. 

So, to answer the question in the title, it makes no sense to lock up my college-age daughter, while I continue to go grocery shopping. 

Unless that’s to protect her, from the risk of COVID-19 infection that I might be bringing home.

Want do the quick-and-dirty calculation for your own returning college student?  Based on the assumptions below (the student tests negative for COVID-19 and doesn’t pick up an infection while traveling home), the 1-in-X odds of  your student transmitting infection to you, X = 11*campus enrollment / new campus COVID cases in the last two weeks.  If they don’t have a negative COVID-19 test, then replace the factor of 11 with a factor of 3.

Continue reading Post #898: Quarantining your college student rationally. Or, should I lock my daughter in her room while I go grocery shopping?

Post #897: Preparing for a hard winter, #9: Recent COVID-19 trends in Virginia, cold spots as hot spots, and extrapolating to mid-winter

It has been more than a month since I tabulated the trends in new COVID-19 cases in Virginia.  It’s no secret that the trend has been up.  Here’s Virginia, in the national context, as of yesterday’s data reporting.

Record new cases, but not record hospitalizations or deaths.

Continue reading Post #897: Preparing for a hard winter, #9: Recent COVID-19 trends in Virginia, cold spots as hot spots, and extrapolating to mid-winter

Post #896: Has anybody seen our vaccine distribution plan?


I’ve seen it.  I think.  Such as it is.  Maybe.

Before I even try to be amusing about this, take a look at it yourself.  You can read it by following the links on this US DHHS web page.  This is the plan, as released in late September (.pdf).  And this is the “playbook” for executing that plan, released late October (.pdf).

The whole gist of the plan, such as it is, is that vaccines will be distributed through the States.  Presumably, via state public health departments.  You can see an outstanding summary of the status of those State plans via the Kaiser Family Foundation website.   It’s agreed-upon that certain vulnerable or critical populations will get vaccinated first, such as health care workers.  Beyond that, it’s up to the States to determine the distribution routes.

But now, turn to the key table in the Federal plan showing how the vaccine doses will be divided up among the States.  Our allocation plan, as part of the overall distribution plan.  And you will soon find that there is no such table.  Continue reading Post #896: Has anybody seen our vaccine distribution plan?

Post #895: A few words on room humidifiers

Source:  That well-known font of medical knowledge, the American Society of Heating, Refrigerating and Air-Conditioning Engineers.  This is from the 2016 ASHRAE Handbook—HVAC Systems and Equipment (SI), Chapter 22:  Humidifiers.

I started to look up the standards, if any, for room humidifiers, and stumbled across the graph above in, of all places the AHSRAE HVAC engineering standards manual.  I thought that was such an odd coincidence, given my last post, that it deserved special mention here.  HVAC engineers start their discussion of calculations for humidifiers by summarizing the significant health implications of maintaining proper indoor humidity.  The impact of humidity on flu mortality was demonstrated experimentally, thirty years ago, on mice.  And, sure enough, 40% to 60% is the zone that prevented the most flu deaths.

And now, a few words on room humidifiers:

I hate them.  All types of them.  Each in their own separate way.

If you already own and use a humidifier or two, the opinions in this posting are probably irrelevant.  Either you’re satisfied with what you have, or you aren’t.  But if you’ve never bought a humidifier before, you might find a useful tip or two here. Let me get you oriented.

1:  There are no standards, so buy big.

2:  The humidifier is an appliance that increases household work.

3:  Noisy, dusty, stinky, and/or expensive:  Pick one or more.

Think of all the worst properties of every appliance you’ve ever had, and they come together in the average room humidifier.  There are no standards.  They are built as cheaply as they can possibly be built.  You fill them by hand, in any of several awkward ways, frequently.  In some cases, you need to clean them frequently, again by hand.  Some require using distilled water, others require you to dump poison in the water.  Replacement items are expensive.  And so on.

Over the years, I’ve tried more-or-less every type of humidifier there is.  I have grudgingly settled on a fixed-pad evaporative humidifier with use of bacteriostat (bacteria-suppressing solution).  In particular, my go-to humidifier is this one.   For reasons that I’ll eventually get to in this posting.


1:  There are no standards, so buy big.

Pretty much every humidifier on the market will tell you how many square feet it is capable of humidifying.  And if you think about that for even thirty seconds, you’ll realize that, whatever that number is, it’s not well-defined.

  • What outdoor temperature and humidity do they assume?
  • What ceiling height do they assume?
  • How leaky or tight is the construction being humidified?
  • What level of indoor relative humidity do they guarantee?
  • Is that the max output — do you have to run it on high all the time to get that?

And so on.  Let’s face it.  Something that will effectively humidify 1000 square feet of housing in Virginia is going to be inadequate for 1000 square feet in Bismark or Cheyenne.  So that one-size-fits-all rating has to be taken with a grain of salt.

If you look at an actual engineering discussion of humidifiers (as in the ASHRAE manual), you soon realize that the whole subject is pretty tricky.   It’s all about the amount of water that you need to put in the air, per hour, to maintain humidity.  And that’s affected by lots of factors and lots of limits.

Just to give one example, in colder climates, the type of window glazing sets an upper limit on how well you can humidify an indoor space.  Set the humidity too high, and the water simply condenses on the insides of the windows.  If it’s freezing out (32F), and you have single-glazed windows, you’ll get condensation on the windows if you try to maintain anything above 30% relative humidity.

Arguably, the single largest contributor to your humidification load is the number of air changes per hour for your home.  The air in your home is being continuously replaced with outside air.  The current US standard is that all the air in your home should be replaced at least once every three hours.  Most modern building codes aim for roughly one change every two hours.  A typical value for an older home would be one air change per hour.

If you have an older home, the upshot is that you need to re-humidify the entire air volume of your home, once per hour.  In a more modern home, that might be once per two hours, or even three hours.

Let me now do a little calculation to show you just how much water that might entail, in the dead of winter, in this area.  In January, in Washington DC, the average outdoor air temperature is 36F and the average relative humidity is about 61% (per this source).  Let’s say you have an older home, 3000 square feet, with 8′ ceilings.  And, finally, you want to maintain 40% relative humidity inside your home, at 68F.

Under those assumptions, you need to put 0.75 gallons of water, per hour, into the air.  Or 18 gallons per day.  Just to overcome that one air change per hour.  This doesn’t count moisture that literally escapes through the walls of your house.  But it also doesn’t count the modest amount of moisture added to the house by cooking, showers, and so on.

If you have a tightly-constructed modern home, you’d need far less.  Or a smaller home.  But if you have a bigger, older house, of the type described here, you need somewhere around that 18 gallons of water per day to maintain 40% relative humidity in the dead of winter.

You’d need four or five of  my go-to humidifier, running at top speed (four gallons/day), all day long, to maintain 40% relative humidity.  (Whereas, if I went by the rating on the box, I’d only need three. And I want to avoid running at top speed, due to the noise.)

The upshot of that is:  Think big, and buy a hygrometer (humidity meter) or two.  If you’re planing to humidify your entire house, buy somewhat more humidification capacity than you think you’ll need.  You can always turn the humidifiers down to a lower speed, if you don’t need that capacity.  But you will be surprised how frequently you will exceed your humidification capacity in the dead of winter.

It is possible to over-humidify a home.  Particularly if you have a modern, well-sealed home.  But if you live in an older home, over-humidification is tough to achieve unless you really go overboard.

2:  The humidifier is an appliance that increases household work.

I don’t need to belabor this, I think.  In the example above, that theoretical 3000 square foot older house needed 18 gallons of water per day.  That you, the homeowner would have to carry to the humidifier.  That’s 150 pounds of water, per day, carried by hand.  Inside your house.  Every winter day.

That gets really old, really fast.  Needless to say, Rule #1 is to locate any large humidifier near a source of water.

The only other thing to mention is routine cleaning.  If you have an evaporative humidifier, at a minimum, even if you put chemicals (“bacteriostat”) into the water, you have to inspect it weekly.  And take it apart and clean it every couple of weeks or so.  Maybe soak the evaporative pads to remove the mineral buildup.  And so on.

Just understand that it’s not like your other appliances.  Your other appliances, they reduce the amount of work you do.  Humidifiers increase it.

3:  Noisy, dusty, stinky, and/or expensive:  Pick one.

There’s no such thing as an inexpensive low-maintenance humidifier.  At least, not that I’ve come across, for humidifying a large area.

Cool mist humidifiers break water up into tiny droplets using ultrasound or some mechanical (“disk”) means.  They are quiet and reasonably energy efficient.  In my experience, they rarely have problems with mold or bacteria.

But 1:  But you’ll probably want to use distilled water.  And that’s expensive.  And environmentally unfriendly, for the energy required to produce and ship distilled water.  If you break down and use tap water, they produce mineral dust.  This is not just unsightly, it’s arguably bad for your lungs.  Some units have “de-mineralization” systems, allowing you to avoid distilled water, but I question the effectiveness of those.

But 2:  They are typically small, single-room units capable of producing no more than a gallon per day.  So if you’re of a mind to humidify your whole house, count the number of these you’ll need before you buy.  And every one of them will need to have the water reservoir filled periodically.

But 3:  In my experience, the interlock mechanism that keeps the water in the reservoir is tricky, fragile, and effectively impossible to replace.  It’s typically a spring-loaded contraption with plastic parts, and so is destined for the landfill one way or the other.

Warm mist (a.k.a.) steam humidifiers simply boil water.  They are quiet and you can typically use tap water.

But 1:  They are not energy-efficient.  You are literally using an electric resistance heating element to boil water, which is the least efficient and most carbon-intensive heat source you could choose.

Just as an example, boiling 18 gallons of water requires about 45 KWH of electricity/day, which would work out to about $200/month at $0.15/KWH.

(I could use an extras-for-experts here, because all the other humidifiers also use heat, but indirectly.  “Cool mist” isn’t a feature of the ultrasonic humidifiers, it’s an unfortunate and unavoidable side effect.  Without getting into the physics of sensible versus latent heat, cool mist (and evaporative) humidifiers more-or-less suck heat out of the air.  They require your heating system to work harder to maintain a given temperature.  Whereas warm mist humidifiers put that heat directly into the water at the outset.  So it’s not that warm mist humidifiers are inefficient because they require heat input.  They’re inefficient because they use a particularly inefficient heat source (resistance electric heat) for that heat input.)

But 2:  As with cool mist humidifiers, you’d be hard-pressed to find one capable of humidifying more than one small room.  So, as with cool mist, you’re going to need a lot of these if you’re going to humidify a house.

But 3:  As with cool-mist humidifiers, the interlock mechanism that keeps the water in the reservoir is tricky, fragile, and effectively impossible to replace.  The only exception is “baby humidifiers” where the electric unit just inserts into the top of the reservoir.

Evaporative humidifiers simply blow air over wet pad.  The air picks up moisture from the pad.  Some of them (“console” humidifiers) might have that pad in the form of a moving belt that dips down into a water reservoir.  Others have the pads fixed in place.  Some have to be filled (e.g.) by carrying pitchers of water to them.  Others have detachable reservoirs that can be filled at the sink, similar to cool mist and warm mist humidifiers.  You can use tap water with these humidifiers.  These are made in large sizes capable of humidifying several rooms.

But 1:  The use of a fan makes these noisy, particularly on their highest settings.  I’ve never had one that I would call “quiet”.

But 2:  These are prone to mold and bacteria problems.  You (IMHO) MUST use chemicals (“bacteriostat”) in the water reservoir to suppress mold.  You MUST inspect the pads weekly for any sign of growth.  You typically have to replace the pads at least once per heating season, at a cost of a few tens of dollars.  Barring that, you may need to take them out and soak them once per season to remove mineral build-up.  And it’s not a bad idea to empty these out and scrub the interior at least once per heating season, just to be on the safe side.

Summary:  What I use, and why.

Source:  Amazon.

I use the simplest, high-volume evaporative humidifier that I have found.  Because:

a)  I’m too cheap to buy massive quantities of distilled water.  That, and the size of the space to be humidified rules out cool mist humidifiers.

b) The inefficiency of resistance electric heat, and the small size of warm mist humidifiers, rule them out.

So I’m left with evaporative humidifiers.  The lesser of three evils.

The model I prefer has a few nice features.

First, few moving parts.  In particular, it has removable reservoirs for re-filling, but they have no mechanical seal mechanism.  Instead, they just sit on the humidifier the way a water jug sits on a water cooler.  And you “flip” them into place the same way you would put a jug onto a water cooler. It’s one of those bulletproof systems that is clever for its lack of cleverness.

Second, if forces you to look at the evaporative pads every time you refill the reservoirs.  So you can’t accidentally overlook mold growth, or skip required cleanings.  The pads are right where you can see them, all the time.

Third, all the electronics simply lift off, which makes it easy to scrub down the plastic base and sides.

When it comes to humidifiers, they are all made just as cheaply as they can be made.  In that situation, the less there is to them, the more robust they’ll be.  This is the least humidifier I could buy that gets the job done for me.