A theory of oppositional altruism

Author’s note: I cannot claim to be the sole author of this piece.  The idea was inspired by my 8 year old daughter who recently asked me if misinformation can ever be good for society.

Social media has been used to actively spread misinformation to meet a breadth of pernicious objectives.  The spread of health misinformation may be particularly worrisome since it may change behaviours in a way that puts individuals and society at risk.

However, what is the total health impact of health misinformation?  Is it possible that some people are motivated to make better health decisions when they encounter misinformation?  If they are, then the net negative social impact of misinformation may be less than we think. 

For example, when some people read stories about anti-vaccination proponents and vaccine hesitancy they may be more inclined to ensure their vaccines are up to date than they would have been otherwise.  This could be because 1) they are concerned that vaccine hesitancy in the population puts them at greater risk of infection and 2) they are motivated to actively oppose misinformation as a way of expressing their personal views and increasing their sense of agency.  This latter motivation is similar to what has been seen in heavily contested elections; when an oppositional political movement is particularly detestable it may motivate a larger number of normally politically inactive people to get out and vote.

I propose a theory that some people make socially beneficial decisions as an oppositional response to misinformation that they would not otherwise undertake.  I refer to this as oppositional altruism.

The motivation for an oppositional altruist is to make a personally satisfying decision in response to health misinformation.  True altruists have a different motivation (they make personal sacrifices for society) but the consequences of both altruists are the same.  If oppositional or genuine altruism is a motivating force for individuals, then the resulting behaviours could offset some of the social harms of misinformation.

Consider a timely example.  Some people publicly (and often loudly) argue that we should not wear masks to reduce the spread of SARS-CoV-2.  If masks do offer protection from the spread of infection then not wearing them has a negative social impact—increasing spread of infection and sickness in others—and the message not to wear a mask is misinformation.  In response to this misinformation oppositional altruists may be more inclined to wear masks than they would otherwise, offsetting (at least to some degree) the decisions of anti-maskers.  Moreover, if there are considerably more oppositional altruists than there are anti-maskers, then the net impact of the misinformation may be more mask wearing overall and less infection!

There is no direct evidence for oppositional altruism that I know of.  However, the theory of risk homeostasis offers some evidence from a risk management perspective.  The theory says that people try to maintain a tolerable risk level in their life; we take some risks but we then compensate for them by avoiding others. We seek to balance these risks in order to meet a perceived level of target risk that we find satisfying.  Some risks that we face occur in the social environment, and when we see these risks increase, we may take personal actions to reduce these and/or other risks to achieve our target risk level.  When these personal decisions could also reduce the risks that others experience, it is oppositional altruism.

Oppositional altruism is not guaranteed to offset the harms of health misinformation.  However, if people do sometimes behave as oppositional altruists, it could give us reason to be optimistic and hopeful in spite of the abundance and rapid spread of health misinformation.  Perhaps the more health misinformation the greater the oppositional altruism—acting as a sort of social risk taking governor that prevents health misinformation from causing runaway social harms.

Covid-19 Infodemiology

Here is a new publication that I worked on with a current and two former graduate students. In this study we try to understand the value of reported Covid-19 data (mostly based on positive SARS-CoV-2 test results). Our conclusion is that the data are not terribly useful over short time horizons. This doesn’t call into question the overall value of data sharing, but does call into question the value of daily news reports about the rise and fall of positive Covid-19 tests.

Covid-19 in the US and Canada – deaths and unemployment

A few month ago I drew a comparison between US and Canada on two dimensions: Covid-19 deaths and employment losses since January. The data I used told a simple story: Canada has seen less death and roughly similar employment losses. This suggests that Canada is doing something (relatively) right: compared to the US, deaths are lower at no obvious economic cost.

Well, I have updated these data and in the process accessed some more reliable labour force information from the US and Canada. The sources for employment data:

Canada: Labour Force Survey, Statistics Canada

US: US Bureau of Labor Statistics

For Covid-19 data, I went to national government sources. All of these numbers contain some error — there is a lag in reporting deaths, and there are all sorts of ways that labour force data can be wrong. However if the data are anywhere close to correct, they tell an interesting story:

Note first that the employment recovery in Canada is well ahead of that in the US, and it has been trending that way since June. Second, note that the risk of Covid-19 death in the US is about 2.5 times higher than it is in Canada, but that this difference is particularly striking since July, at which point mortality risk began to diverge considerably. As of September 2020, the probability of dying from Covid-19 in the US is 16 times higher than in Canada.

In terms of attributable risk, in Canada, more than 14,000 lives were saved by not having the same risk profile as the US; conversely, over 120,000 American lives would have been saved if the US had Canada’s risk profile.

Take a look at the calculations yourself. Feel free to tell me if there are any necessary corrections!

Update to Covid-19 death comparison between Canada and the US

With a month of new Covid-19 data and employment data, the evidence I made reference to in my previous post can be updated. I’ll make a quick note here about it.

In August, the US saw more than 30,000 Covid-19 deaths. Canada saw 206. This amounts to a near 17 times difference in the rate of death–meaning that the average American was 17 times more likely to die from Covid-19 than the average Canadian in the month of August. I am not aware of any other cause of death, disease or injury that shows an equivalently striking difference between these two countries 1. For reference, the homicide rate in the US is only 2.8 times that of Canada.

The trend in employment growth remains about the same as in previous months. Canada saw a larger percent improvement in employment growth in August at 1.28% when compared to 1.08% in the US, but Canada is still slightly behind the overall return to normal (Canada is 5.57% below January employment and the US is 5.24% below January).

So far the message is clear: the behaviour of Canadians has saved lives that would not have been saved if Canadians adopted the US response to Covid-19. Let’s keep at it. Whatever we are doing seems to be working fairly well in comparison to the most available alternative approach.

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  1. I did a quick and dirty estimate of curling related injuries based on some research and Internet-based data. Google says there are around 436,000 regular curlers Canada. In the US, Google says there are 25,000 registered curlers. The injury rate (per curling exposure) has been estimated at around 2 per 1000. Putting these numbers together suggests that the average Canadian has a 17 times greater risk of curling injury than the average American.