Influenza Transmission During the 1918 Pandemic
Influenza Transmission During the 1918 Pandemic
Analysis of historical data has strongly shaped our understanding of the epidemiology of pandemic influenza and informs analysis of current and future epidemics. Here, the authors analyzed previously unpublished documents from a large household survey of the "Spanish" H1N1 influenza pandemic, conducted in 1918, for the first time quantifying influenza transmissibility at the person-to-person level during that most lethal of pandemics. The authors estimated a low probability of person-to-person transmission relative to comparable estimates from seasonal influenza and other directly transmitted infections but similar to recent estimates from the 2009 H1N1 pandemic. The authors estimated a very low probability of asymptomatic infection, a previously unknown parameter for this pandemic, consistent with an unusually virulent virus. The authors estimated a high frequency of prior immunity that they attributed to a largely unreported influenza epidemic in the spring of 1918 (or perhaps to cross-reactive immunity). Extrapolating from this finding, the authors hypothesize that prior immunity partially protected some populations from the worst of the fall pandemic and helps explain differences in attack rates between populations. Together, these analyses demonstrate that the 1918 influenza virus, though highly virulent, was only moderately transmissible and thus in a modern context would be considered controllable.
The devastating impact of the 1918 "Spanish" influenza pandemic on global mortality and morbidity has been well documented. Analyses of historical data from that and later pandemics have strongly shaped our understanding of influenza epidemiology. Such analyses have been used for calibrating efforts to prepare for future influenza pandemics and provided prior information that informed the response to the 2009 pandemic.
In the current study, we gained new insight into the transmission of pandemic influenza from previously unpublished data from a survey of 7,287 Maryland households conducted in the fall of 1918. The survey was led by Wade Hampton Frost, a pioneer of both field and theoretical epidemiology, who led the US Public Health Service's investigation into the 1918 pandemic and developed one of the first mathematical models of infectious disease transmission. We extended Frost's posthumously published mathematical model of disease transmission in households and fitted a wide range of model variants to the data from 1918. This analysis yielded new insights into the epidemiology of the 1918 pandemic: We found that the epidemic was characterized by low rates of transmission within households (susceptible-infectious transmission probability (SITP) < 20%), that there was considerable interperson variability in infectiousness, and that up to 22% of the population of Baltimore may have been immune before the fall wave of influenza. In addition, we inferred that there appeared to have been very few (<6%) asymptomatic infections. Here we place our results into context by comparing them with seasonal influenza and a recent study of the 2009 pandemic. Our results demonstrate that influenza is consistently only moderately transmissible and thus potentially controllable. They also demonstrate the value of simple large-scale household surveys, such as Frost and Sydenstricker's 1918 study, for disaggregating different clinically and epidemiologically relevant components of influenza transmission during the first months of a pandemic.
The most important parameter in epidemic control is transmissibility, which is often (but, as we will see, not always) measured using the basic reproduction number R 0, the number of secondary cases that 1 typical patient infects in an entirely susceptible population. Estimates of R 0 for pandemic influenza range from 1.5 to 2.5, indicating that 33%–60% of transmission (based on the conventional formula, (R 0 − 1)/R 0) would need to be blocked to control a pandemic completely, and also that lesser interventions would have a substantive mitigating impact.
While published estimates of R0 have mostly been consistent, they share frailties. Time series of deaths (or, in some cases, morbidity reports) are analyzed to determine the rate of spread of the virus in the population. The first frailty is that estimates of R0 are highly dependent on the generation time distribution, the distribution of times between subsequent infection events. There are no good estimates for the generation time of influenza in 1918, and there are only limited data for interpandemic influenza and the 2009 H1N1 pandemic. Second, methods for estimating R0 have mostly been applied to highly aggregated data from large populations. Where outbreaks in small, isolated communities (e.g., military camps or ships) have been analyzed, estimates of R0 have been more variable and typically higher. Third, estimates of R0 for the 1918 pandemic have been reported from places where nonpharmaceutical interventions were applied with some effect. Finally, prior immunity should be accounted for. The fall epidemic of 1918 was preceded in some locations by earlier waves of transmission that may have generated immunity. Similarly, prior immunity played an important role in mitigating the 2009 H1N1 pandemic. These frailties imply that the real transmissibility of pandemic influenza viruses could be higher than expected from published estimates of R 0, and thus there is a need to obtain more robust estimates.
Abstract and Introduction
Abstract
Analysis of historical data has strongly shaped our understanding of the epidemiology of pandemic influenza and informs analysis of current and future epidemics. Here, the authors analyzed previously unpublished documents from a large household survey of the "Spanish" H1N1 influenza pandemic, conducted in 1918, for the first time quantifying influenza transmissibility at the person-to-person level during that most lethal of pandemics. The authors estimated a low probability of person-to-person transmission relative to comparable estimates from seasonal influenza and other directly transmitted infections but similar to recent estimates from the 2009 H1N1 pandemic. The authors estimated a very low probability of asymptomatic infection, a previously unknown parameter for this pandemic, consistent with an unusually virulent virus. The authors estimated a high frequency of prior immunity that they attributed to a largely unreported influenza epidemic in the spring of 1918 (or perhaps to cross-reactive immunity). Extrapolating from this finding, the authors hypothesize that prior immunity partially protected some populations from the worst of the fall pandemic and helps explain differences in attack rates between populations. Together, these analyses demonstrate that the 1918 influenza virus, though highly virulent, was only moderately transmissible and thus in a modern context would be considered controllable.
Introduction
The devastating impact of the 1918 "Spanish" influenza pandemic on global mortality and morbidity has been well documented. Analyses of historical data from that and later pandemics have strongly shaped our understanding of influenza epidemiology. Such analyses have been used for calibrating efforts to prepare for future influenza pandemics and provided prior information that informed the response to the 2009 pandemic.
In the current study, we gained new insight into the transmission of pandemic influenza from previously unpublished data from a survey of 7,287 Maryland households conducted in the fall of 1918. The survey was led by Wade Hampton Frost, a pioneer of both field and theoretical epidemiology, who led the US Public Health Service's investigation into the 1918 pandemic and developed one of the first mathematical models of infectious disease transmission. We extended Frost's posthumously published mathematical model of disease transmission in households and fitted a wide range of model variants to the data from 1918. This analysis yielded new insights into the epidemiology of the 1918 pandemic: We found that the epidemic was characterized by low rates of transmission within households (susceptible-infectious transmission probability (SITP) < 20%), that there was considerable interperson variability in infectiousness, and that up to 22% of the population of Baltimore may have been immune before the fall wave of influenza. In addition, we inferred that there appeared to have been very few (<6%) asymptomatic infections. Here we place our results into context by comparing them with seasonal influenza and a recent study of the 2009 pandemic. Our results demonstrate that influenza is consistently only moderately transmissible and thus potentially controllable. They also demonstrate the value of simple large-scale household surveys, such as Frost and Sydenstricker's 1918 study, for disaggregating different clinically and epidemiologically relevant components of influenza transmission during the first months of a pandemic.
The most important parameter in epidemic control is transmissibility, which is often (but, as we will see, not always) measured using the basic reproduction number R 0, the number of secondary cases that 1 typical patient infects in an entirely susceptible population. Estimates of R 0 for pandemic influenza range from 1.5 to 2.5, indicating that 33%–60% of transmission (based on the conventional formula, (R 0 − 1)/R 0) would need to be blocked to control a pandemic completely, and also that lesser interventions would have a substantive mitigating impact.
While published estimates of R0 have mostly been consistent, they share frailties. Time series of deaths (or, in some cases, morbidity reports) are analyzed to determine the rate of spread of the virus in the population. The first frailty is that estimates of R0 are highly dependent on the generation time distribution, the distribution of times between subsequent infection events. There are no good estimates for the generation time of influenza in 1918, and there are only limited data for interpandemic influenza and the 2009 H1N1 pandemic. Second, methods for estimating R0 have mostly been applied to highly aggregated data from large populations. Where outbreaks in small, isolated communities (e.g., military camps or ships) have been analyzed, estimates of R0 have been more variable and typically higher. Third, estimates of R0 for the 1918 pandemic have been reported from places where nonpharmaceutical interventions were applied with some effect. Finally, prior immunity should be accounted for. The fall epidemic of 1918 was preceded in some locations by earlier waves of transmission that may have generated immunity. Similarly, prior immunity played an important role in mitigating the 2009 H1N1 pandemic. These frailties imply that the real transmissibility of pandemic influenza viruses could be higher than expected from published estimates of R 0, and thus there is a need to obtain more robust estimates.
