The 1918 H1N1 influenza and 2020 SARS-CoV-2 outbreaks are the two largest respiratory pandemics to have occurred in the 20th and 21st centuries. In terms of mode of disease transmission, geographical overlap, and global spread, these two pandemics are quite similar and provide epidemiologists the opportunity to explore potential correlations between the two.
CEID’s Grant Foster and Robert Richards collaborated with a team of researchers to compare the characteristics between H1N1 influenza and SARS-CoV-2 in forty-three United States cities that experienced outbreaks of both viruses. This study quantified the basic reproduction number (R0), which represents the average number of secondary cases of an infectious disease that one infected individual will produce in a population that has not previously been exposed to the disease. The basic reproduction number provides information on disease transmission throughout a population and is influenced by traits of the host population (in this case humans) and the pathogen itself.
The study results found that despite the many similarities between these viruses, they progressed very differently. For influenza, the estimated R0 values ranged from 1.25 to 1.60, with a median of 1.54 cases that one infected individual could be expected to produce. The R0 values for SARS-CoV-2 ranged from 1.49 to 2.46, with a median value of 1.82. Across these forty-three cities, the median R0 estimates for each city were not correlated between the two pandemics. For COVID-19, cities with larger populations typically had higher R0 estimates. There was no correlation between R0 values for influenza and population size of a city.
The researchers also examined the effect of outbreak timing on transmission. For COVID-19, outbreaks that started later in the year usually had lower R0 values and lower rates of spread. However, influenza epidemics that occurred later in the year were more severe than earlier outbreaks.
The lack of transmission correlation between these two similar viruses in the cities examined could be due to a variety of factors. Many changes occurred in the time period between the two epidemics, with the overall U.S. population growing and some cities’ population expanding rapidly. While there was no association found between population size and influenza, changing human behavior may play a role in infection pattern differences. Factors such as use of public transportation, travel patterns between cities, and the size and frequency of community gatherings could affect the likelihood of coming into contact with an infected individual. Furthermore, changes in city infrastructure, culture, and demographics can also potentially contribute to these differences in outbreak progression.
Variation in infection dynamics, pathology, and sickness may impact these epidemiological differences between influenza and COVID-19 as well. These conflicting patterns could also be attributed to human responses to disease outbreaks, such as wearing a mask and social distancing. R0 rates can be reduced, as more advanced disease surveillance is implemented and medical professionals learn to better diagnose and treat these illnesses. Seasonal differences in climate and human behavior (e.g. staying inside when it’s cold outside), are another reason variation can occur. Future work can build upon this research, by exploring traits of cities that influence disease spread.
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By: Brenna Daly