A geographic analysis of population density thresholds in the influenza pandemic of 1918–19

Abstract

BackgroundGeographic variables play an important role in the study of epidemics. The role of one such variable, population density, in the spread of influenza is controversial. Prior studies have tested for such a role using arbitrary thresholds for population density above or below which places are hypothesized to have higher or lower mortality. The results of such studies are mixed. The objective of this study is to estimate, rather than assume, a threshold level of population density that separates low-density regions from high-density regions on the basis of population loss during an influenza pandemic. We study the case of the influenza pandemic of 1918–19 in India, where over 15 million people died in the short span of less than one year.MethodsUsing data from six censuses for 199 districts of India (n=1194), the country with the largest number of deaths from the influenza of 1918–19, we use a sample-splitting method embedded within a population growth model that explicitly quantifies population loss from the pandemic to estimate a threshold level of population density that separates low-density districts from high-density districts.ResultsThe results demonstrate a threshold level of population density of 175 people per square mile. A concurrent finding is that districts on the low side of the threshold experienced rates of population loss (3.72%) that were lower than districts on the high side of the threshold (4.69%).ConclusionsThis paper introduces a useful analytic tool to the health geographic literature. It illustrates an application of the tool to demonstrate that it can be useful for pandemic awareness and preparedness efforts. Specifically, it estimates a level of population density above which policies to socially distance, redistribute or quarantine populations are likely to be more effective than they are for areas with population densities that lie below the threshold.

The influenza pandemic of 1918–1919 in Sri Lanka: its demographic cost, timing, and propagation

“…The sparsely populated central zone separated the northern and southern zones from each other, appears to have been isolated from the global system, and experienced a dynamic all of its own. This finding further suggests that geographic contiguity alone was not a sufficient condition for the transmission of the mortality wave and that other factors such as person‐to‐person contact across regions, or the lack of it, may have played an important role in the spread of the disease . Given the scarcity of studies that examine the spread of the 1918 influenza pandemic at a relatively high level of geographic and temporal resolution, it is hoped that the methods used in this paper will encourage scholars to develop a more complete picture of the pandemic in different locations, thereby illuminating the factors that facilitated or hampered its spread.…”

“…This finding further suggests that geographic contiguity alone was not a sufficient condition for the transmission of the mortality wave and that other factors such as person-toperson contact across regions, or the lack of it, may have played an important role in the spread of the disease. 35 Given the scarcity of studies that examine the spread of the 1918 influenza pandemic at a relatively high level of geographic and temporal resolution, it is hoped that the methods used in this paper will encourage scholars to develop a more complete picture of the pandemic in different locations, thereby illuminating the factors that facilitated or hampered its spread. These insights can then be leveraged to inform strategies to contain similar events in the future using our existing knowledge about the importance of social distancing and other relevant spatial features of populations.…”

Influence of Media on Seasonal Influenza Epidemic Curves

“…It was reported that meteorological and demographic factors such as humidity, 3 temperature, 4 population-density 5 and urbanization 6 influence on the onset and spread of seasonal influenza. With regard to epidemic curves of seasonal influenza, vaccination, 7 low activity of society 8 and education of people through media 9 are estimated to depress the peak and widen the base of the curve.…”

The evolution of pandemic influenza: evidence from India, 1918–19

“…As the centenary of the 1918–1919 pandemic approaches, scholars are returning to its study to design appropriate pandemic control strategies [ 54 – 56 ]. By establishing a baseline picture of how the worst epidemiologic disaster of the modern era unfolded at its global focal point, it is hoped that this study will prompt future research that delves into the complex factors that created and shaped it spatially and temporally [ 8 , 57 , 58 ].…”