Overpopulation and Contagion

The Theory

High population densities cause epidemics. The more people one comes in contact with each day, the more chances there are to pass on a contagious disease. The more people you meet, the more different germs and viruses you can pick up. Furthermore, overcrowding causes problems with sanitation and pollution, and these things also contribute to spreading diseases.

In his book, The Population Explosion, Paul Ehrlich devotes an entire chapter to "Population and Public Health". He states, "It has long been realized that high densities in human population made them -- all else being equal -- subject to high rates of disease."¹ And "Many bacterial and viral diseases that pass directly from person to person depend on cities -- densely packed communities of thousands of people -- for their persistence. Otherwise they run out of susceptible individuals to infect, and they die out."²

That's the theory, anyway. But is it really happening that way in practice? Is there any evidence to support these claims? Let's see if we can confirm this with statistics.

Supporting Evidence

Unfortunately, "health" and "epidemics" are difficult to measure. It is not very meaningful to simply count the number of "sick people": a million people suffering from colds is surely not equivalent to a million people suffering from AIDS. Indeed, it is often difficult to say exactly which disease a particular person died of, or if it was simply old age. And once we start applying complex criteria, our results become more and more debatable.

So for this analysis I tried to use the simplist plausible measure: death rates. Of course not all deaths are from disease, but a society with rampant epidemics will surely have a higher death rate than a generally healthy society. (A country in the midst of an all-out war might have a high death rate despite being healthy, but fortunately most of the world's population is not in such a situation today, and a few unusual cases should not upset the general pattern of any statistics.)

If high population density causes disease to spread faster, than we would expect that countries with high population densities would have higher death rates than countries with low population densities. Of course no one is claiming that population density is the only factor; we would not expect the pattern to be simple and universal. But we would expect to be able to see a general trend.

So, using data from the CIA World Fact Book,³ I constructed the graph below. I took the 205 geographical "entities" listed in that reference book.⁴ I arranged these in order by population density, and then broke them into groups of 25. (As 205 is not an even multiple of 25, the last group was smaller than the rest.) For each group I found the average death rate. I then drew a graph of the results.

By an overpopulation-causes-contagion theory, we would expect the general trend of this graph to be upward as we move to the right. If there is no connection between population density and contagion, then the graph should be close to a straight line. In either case there might be some fluctuations, of course. But by putting countries into groups of 25 like this other factors which might affect death rates should tend to cancel out, at least somewhat.

What do we actually see? The resulting graph is shown in Figure 1.

Figure 1: Population Density vs Death Rate

The horizontal axis shows the highest population density of any country in each group. The vertical axis shows the average death rate.

Shockingly, we see that neither the overpopulation-causes-contagion nor the density-unrelated-to-contagion theory bears out. Instead, increasing population density is consistently associated with lower death rates. The last group, consisting solely of countries with population densities of over 1100 people per square kilometer, has the lowest death rate of all.

If you're looking for a healthy place to live then, it would seem that you are much better off to go to crowded Monaco -- 15,501 people per square kilometer, death rate 7 per thousand -- then to wide-open Chad -- 3 people per square kilometer, death rate 22 per thousand.

Objections

There are three objections that I expect to this analysis.

One: The analysis is unfair because countries with high death rates will inevitably have lower population densities. If a lot of people are dying, the country cannot remain very crowded for long.

Reply: First, it is not at all inevitable that high death rates lead to lower population density. People could have a very short life expectancy but still have many children, giving both high death rates and high populations. Indeed, this is the horror scenario that anti-populationists typically paint: A world with teeming masses of people, having more children than they can possibly support, so that there are many many people all living short, unpleasant lives. What the above chart shows is that, while this scenario is mathematically conceivable, it is not the reality.

Two: The analysis is invalid because there are places which are clearly overcrowded and which have real health problems, like Mexico City or New Delhi.

Reply: No one denies that there could be isolated examples that would fit the theory. The whole point of this analysis was to be more thorough, to look at all the countries in the world. You can "prove" almost any connection you like if you accept one or two examples as proof. (Like: Joe flunked out of high school. Joe is from Ruritania. Therefore, Ruritanians are stupid. Would you find that "logic" convincing?)

Three: The analysis is unfair because other factors might outweigh overcrowding. A crowded country with good health care facilities could have a lower death rate than a sparsely-populated country with poor health facilities. Even though the crowding is causing medical problems, the country is able to deal with these.

Reply: This rebuttal would be plausible if we simply picked two countries at random, compared them, and found the relationship was not what was predicted. But the above graph was constructed by taking every place listed in a standard reference work covering the entire world. It is hard to believe that densely populated countries all over the world just happen to have conditions that lead to better health than sparsely populated countries. Unless, that is, there is something about densely populated countries that causes them to have conditions leading to better health.

Conclusion

And that is precisely the point. It may well be the crowding causes health problems. But if so, in practice this factor is routinely overridden by other conditions which are also associated with more dense population. Namely, "overpopulated" countries tend to be wealthier and more technologically advanced than sparsely populated countries. The connection to population density is too strong to be dismissed as coincidence. See our article, Overpopulation and Standard of Living. Far from invalidating an overpopulation-causes-health theory, this provides a theory to explain it. It may well be that overcrowding causes health problems. But "overcrowding" also causes conditions that lead to better health, and these conditions consistently outweigh the problems. In practice, then, it turns out that we are better off if we are more crowded.

Afterword

The overpopulation-causes-contagion theory is, in one way, typical of the claims of anti-populationists. They construct a theory based on plausible, sometimes very persuasive, logic. They collect a few examples or anecdotes that agree with the theory, lending it additional credence. Then they stop there. They do not make any serious investigation if reality in general conforms to this theory, or if the examples they found are just special cases or coincidence. (Or if they do make such an investigation, they don't tend to publicize the results.)

People often say, when discussing any number of subjects, "That sounds good in theory, but it doesn't work in practice." The fact that something sounds plausible doesn't make it true. There have been many ideas throughout history that have been accepted as "obvious" or "common sense" ... that have later been proven to be completely wrong. A plausible theory is a good starting point for investigation and experiment. But a plausible theory is not a fact, and speculation is not proof.

A Sidenote on The Population Explosion

Lest I be accused of misquoting the above-mentioned book, let me hasten to add that the author is cautious on this point. He repeatedly mixes bold assertions with qualifying statements. Indeed, the chapter on population and health begins with the caution, "The role of population size in public health is often very subtle ..."⁵

Most curious of all: He devotes an entire chapter to explaining why increasing population causes public health problems, including several references specifically to the United States, lest anyone should think that that country is immune to these problems or has not yet reached a critical stage. But in the very next chapter, while he is working to rebut the argument that slowing population growth would cause problems for social security and medicare, he argues that the elderly need not be a burden on the economy, because "the health of the American population as a whole is improving".⁶

So: In chapter 7 we are told that Americans face a grave health crisis. In chapter 8 we are told that Americans are getting healthier. Apparently contradictory arguments are acceptable as long as they serve to advance the cause.

Footnotes

1. Ehrlich, Paul. The Population Explosion, 1990, p 153.

2. Ehrlich, p 141.

3.CIA World Fact Book, 1990. (I used the admittedly-old 1990 edition for the simple reason that I have an electronic copy, that allowed me to tabulate the data and construct the graphs on the computer. If anyone wishes to present evidence that the overall pattern has changed significantly in the last seven years, I'm happy to hear it.)

4.The CIA World Factbook gives data on 249 geographical "entities", i.e. countries, dependent areas, territories, and various special cases. (See the book for a more complete explanation.) My only selection criteria was to eliminate those for which no statistics on area, population, or death rate were given, plus I eliminated the "world" summary entry. This left 205 "entities". Most of the eliminated places were uninhabited islands. If a place has no inhabitants, it's difficult to talk meaningfully about their health. A few were countries for which the editors were apparently unable to get data they considered reliable, but there were too few of these to make much difference to this analysis.

5. Ehrlich, p 136.

6. Ehrlich, p 160.

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Posted 10 Sep 2000.