National wealth, tourism and inexperience are helping drive the spread of the coronavirus

By Kent R. Kroeger (March 12, 2020)

The coronavirus (2019-nCoV) (Image provided by Dr. Fred Murphy/Centers for Disease Control)
  • Countries with a high percentage of annual deaths from communicable diseases are seeing relatively fewer COVID-19 cases (mostly African, SE Asian, and Latin American countries);
  • China has a disproportionate number of COVID-19 cases, even given its large population size;
  • Countries with higher numbers of tourists entering the country are experiencing higher numbers of COVID-19 cases.

Residual Analysis

Perhaps more interesting than those factors found to be significant correlates with COVID-19 cases were those countries where the model did not fit the data very well (see chart below).

Data sources: WHO, World Bank (Analysis by Kent R. Kroeger)


As this health crisis unfolds, I continue to test additional risk factor models using measures for volume of international trade, hospital beds/physicians per capita, quality of health care system, availability of affordable health care, demographic characteristics, income inequality, average climate, as well other variables. But so far, in every model I’ve tested, national wealth (per capita), tourism levels, and a nation’s previous experience with communicable diseases consistently maintained their statistical significance.

Personal Thoughts on COVID-19

I once thought epidemics and pandemics were generally restricted to African countries and places where people eat monkeys and bats.

Appendix: A Regression Model of Confirmed COVID-19 Cases Worldwide (as of 10 March 2020)


Dependent Variable (Source: WHO): Number of confirmed COVID-19 cases as of 10 March 2020 (log transformed)

Model Fit

Overall, the model explained 71 percent of the variance in confirmed COVID-19 cases on a national level.

Other Methodological Issues:

I should note that I used a linear regression model in this analysis. However, a Poisson model is the appropriate technique to use with count-data (such as the number of COVID-19 cases). I chose to report the linear regression model, in part, because linear regression is generally more familiar to a larger segment of readers. Nonetheless, I did run the same model using Poisson regression in SPSS and found no substantive differences in the results.

I am a survey and statistical consultant with over 30 -years experience measuring and analyzing public opinion (You can contact me at:

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