Mapping the 1889-1890 Russian Flu
In November 1889, a rash of cases of influenza-like-illness appeared in St. Petersburg, Russia. Soon, the “Russia Influenza” spread across Europe and the world. This outbreak is being researched by teams of Virginia Tech students as a case-study of the relationship between the spread of the disease and the spread of reporting about the disease. In this first of three posts, Circulating Now welcomes guest bloggers Nicholas Mehfoud, Veronica Kimmerly, and Marin Shipe, who look at geographical representations of the spread of the disease.
During 1889 a global epidemic emerged from eastern Russia to encircle the globe. The National Library of Medicine has valuable resources illustrating the spread of this epidemic during its peak years. These documents also illustrate how health experts in the late nineteenth century and today document the spread of influenza across space and time. Flu Near You, Google Flu Trends, and CDC reports on ILI (influenza like illness) are some examples of current efforts to document the spread of disease using a variety of data sources. In the early 1890s, a team of international scholars produced a colorful and dense map showing the spread of the Russian flu in two-week time periods.In the map’s published version, different symbols and colors illustrate the first instances of the disease as it spread around the globe. The first outbreaks occurred in a region stretching from northern India through Central Asia and Siberia, with reports ranging from May to October 1889. Beginning in November, however, the map becomes more detailed, with two-week increments showing the movement of the disease westward, from Russia through Europe to the United States and then the rest of the Americas, Australia, and coastal regions of Africa. By the fall of 1890, according to this map, the Russian Flu had reached Asia, thus completing the global circumnavigation in about a year’s time.
We animated the same information contained in this static map into a version that more clearly depicts the movement of disease through time and space. Placing the dates on the same page as the map makes it easier to see the disease’s spread in a sequential progression and observe the path of the disease at points in time. Both the original print map and the animated map illustrate how the Russian Flu circumnavigated the globe, moving from east to west, in approximately one year’s time.
These same principles of mapping disease across space and time offer historians additional ways to depict the impact of the Russian Flu in specific contexts. In the case of Paris, for example, a city that suffered the ravages of influenza for several weeks in December and early January, it is possible to use printed newspaper reports to map both the spread of disease and the introduction of public health measures. In this map, we outlined areas in pink to show concentrations of disease while the areas outlined in blue indicate where emergency hospitals and clinics were established to treat the very high number of patients.
Both the world map and the Paris map illustrate the spread of the Russian Flu, but neither is particularly useful for showing the impact of the disease, because they do not show the rates of morbidity and mortality. The latter information is available, however, from both contemporary published sources (specifically newspapers) and reports published soon after the disease subsided (similar to the Baginsky report cited above). Using these sources we were able to visualize the impact of the Russian Flu with data showing the peak of the disease (highest number of deaths) and the duration of the disease (time from first to last cases).
Deriving meaningful data about mortality rates from daily reporting in newspapers is challenging because the categories for reporting disease varied across cities, sources, and time periods. Comparing mortality tables in the Swiss newspaper Intelligenzblatt in early 1890 and a report published by British scientist F. A. Dixey in Epidemic Influenza: A Study in Comparative Statistics more than a year after the epidemic subsided reveals broadly similar patterns despite the differences in timing.
By contrast, the daily reporting of deaths in local newspapers provided much higher death rates during the influenza epidemic than these more comprehensive reports. On January 2, 1890, for example, a French newspaper La lanterne reported 450 burials on a single day, December 31, 1890. Less than a week later, the same newspaper reported 327 more burials, presumably of victims of influenza. On January 12, this newspaper reported the number of deaths had declined, to 353 on January 8 and 275 on January 9. Even with these declining numbers, the total numbers reported in the daily papers were higher than the international reporting shown in the table above.
Many factors could account for these differences. Newspapers probably received reports about deaths from multiple sources. Deaths reportedly from influenza may have been due to other causes that were differentiated in the more through statistical reporting. Finally, reports in newspapers may have included broader regions, whereas the later reports may have been more strictly bounded. As illustrated by the recent discussion of the predictive analytics of Google Flu Trends, these factors continue to challenge epidemiologists as they seek to answer questions about the scope and severity of disease outbreaks. The most important lesson to be derived from this historical analysis is the importance of drawing upon multiple sources of data in order to measure seemingly simple facts such as illness and death rates.
Using materials from the National Library of Medicine as well as newspaper sources located, and in many cases translated, by the research teams at Virginia Tech, these postings address core issues for epidemiologists related to the speed, scope, and severity of a disease outbreak. By studying these patterns in the past, historians of medicine can contribute to contemporary and future responses to the threat of widespread infectious diseases. Learn more about the Tracking the Russian Flu project at: http://blogs.lt.vt.edu/russianflu/
Veronica Kimmerly is a Chemical Engineering and Mathematics major at Virginia Tech.
Nicholas Mehfoud graduated as a Biological Sciences major from Virginia Tech.
Marin Shipe is a French and Marketing major at Virginia Tech.