2007/04/06 by Martin Bootsma, Neil M. Ferguson · 7 citations
Mathematics · Medicine · Environmental Science · Nursing · #COVID-19 epidemiological studies #Influenza Virus Research Studies #Climate Change and Health Impacts #Pandemic #Influenza pandemic #Public health #Coronavirus disease 2019 (COVID-19) #Pandemic influenza #Environmental health #2019-20 coronavirus outbreak #Political science #Virology #Geography #Medicine #Nursing #Infectious disease (medical specialty) #Outbreak #Disease
paper · doi:10.1073/pnas.0611071104
openalex publication_date 2007/04/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
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.