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, 104 (18), 7588-93

The Effect of Public Health Measures on the 1918 Influenza Pandemic in U.S. Cities


The Effect of Public Health Measures on the 1918 Influenza Pandemic in U.S. Cities

Martin C J Bootsma et al. Proc Natl Acad Sci U S A.


During the 1918 influenza pandemic, the U.S., unlike Europe, put considerable effort into public health interventions. There was also more geographic variation in the autumn wave of the pandemic in the U.S. compared with Europe, with some cities seeing only a single large peak in mortality and others seeing double-peaked epidemics. Here we examine whether differences in the public health measures adopted by different cities can explain the variation in epidemic patterns and overall mortality observed. We show that city-specific per-capita excess mortality in 1918 was significantly correlated with 1917 per-capita mortality, indicating some intrinsic variation in overall mortality, perhaps related to sociodemographic factors. In the subset of 23 cities for which we had partial data on the timing of interventions, an even stronger correlation was found between excess mortality and how early in the epidemic interventions were introduced. We then fitted an epidemic model to weekly mortality in 16 cities with nearly complete intervention-timing data and estimated the impact of interventions. The model reproduced the observed epidemic patterns well. In line with theoretical arguments, we found the time-limited interventions used reduced total mortality only moderately (perhaps 10-30%), and that the impact was often very limited because of interventions being introduced too late and lifted too early. San Francisco, St. Louis, Milwaukee, and Kansas City had the most effective interventions, reducing transmission rates by up to 30-50%. Our analysis also suggests that individuals reactively reduced their contact rates in response to high levels of mortality during the pandemic.

Conflict of interest statement

The authors declare no conflict of interest.


Fig. 1.
Fig. 1.
Predictors of excess influenza-related mortality in 1918–1919. Correlation of peak mortality (per 100,000) with all-cause mortality in 1917 (a), total mortality with the week (counting from the week of September 7–13, weekly mortality first exceeds 20/100,000) (b), total mortality with mortality up to 12 days after start date of interventions (c), and peak mortality with mortality up to 12 days after start date of interventions (d). a and b show data for the 45 U.S. cities for which mortality data were relatively complete. c and d show data for the 23 cities for which the start date of public health interventions was known. Peak and total 1918 mortality refers to excess pneumonia- and influenza-related mortality in the period September 7, 1918, to May 10, 1919. Regression shows all slopes to be significantly different from zero (P < 0.01).
Fig. 2.
Fig. 2.
Effects of transient imperfect health interventions on epidemic dynamics. (a) Total proportion of the population infected in an epidemic in the absence of controls or reactive contact reduction compared with the minimal proportion needing to be infected to achieve herd immunity and therefore stop transmission, shown as a function of R0. Results derived from a simple deterministic susceptible–infected–recovered (SIR) epidemic model (6). (b) Weekly infection incidence over 6 months from a SIR model with 3.5-day infectious period, R0 = 2, 100,000 population, two seed infections at time 0, and controls imposed from day 25. Green curve, no controls; red curve, overeffective controls that reduce R by 40% and stop on day 75 (leading to a second wave); blue curve, controls that reduce R by 32.5% and stop on day 110 (giving the minimal possible epidemic size).
Fig. 3.
Fig. 3.
Weekly excess mortality (per 100,000) resulting from the 1918 pandemic in 16 U.S. cities (blue points), compared with the fit of model variant 4, Table 1 (red curves). This variant fits R0 and T, the duration of the population “memory” of past mortality, as parameters common to all cities and other parameters as city-specific. Estimated weekly mortality, had controls not been implemented, is also plotted (dark-green curves). The effectiveness and period of implementation of control measures are also shown as light-green horizontal lines; horizontal position and length, indicate start date and duration of interventions, and vertical position indicates estimated effectiveness. The top of the vertical axis is 100% effectiveness, and the bottom of this axis is 0%.

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