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. 2008 Jun 6;5(23):631-9.
doi: 10.1098/rsif.2007.1197.

Quantifying Social Distancing Arising From Pandemic Influenza

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Free PMC article

Quantifying Social Distancing Arising From Pandemic Influenza

Peter Caley et al. J R Soc Interface. .
Free PMC article

Abstract

Local epidemic curves during the 1918-1919 influenza pandemic were often characterized by multiple epidemic waves. Identifying the underlying cause(s) of such waves may help manage future pandemics. We investigate the hypothesis that these waves were caused by people avoiding potentially infectious contacts-a behaviour termed 'social distancing'. We estimate the effective disease reproduction number and from it infer the maximum degree of social distancing that occurred during the course of the multiple-wave epidemic in Sydney, Australia. We estimate that, on average across the city, people reduced their infectious contact rate by as much as 38%, and that this was sufficient to explain the multiple waves of this epidemic. The basic reproduction number, R0, was estimated to be in the range of 1.6-2.0 with a preferred estimate of 1.8, in line with other recent estimates for the 1918-1919 influenza pandemic. The data are also consistent with a high proportion (more than 90%) of the population being initially susceptible to clinical infection, and the proportion of infections that were asymptomatic (if this occurs) being no higher than approximately 9%. The observed clinical attack rate of 36.6% was substantially lower than the 59% expected based on the estimated value of R0, implying that approximately 22% of the population were spared from clinical infection. This reduction in the clinical attack rate translates to an estimated 260 per 100000 lives having been saved, and suggests that social distancing interventions could play a major role in mitigating the public health impact of future influenza pandemics.

Figures

Figure 1
Figure 1
Maximum attainable percentage reduction in the attack rate for epidemics in relation to the extent that the infectious contact rate is reduced across the community. If the intervention is not introduced immediately and sustained indefinitely, a lower reduction will be achieved.
Figure 2
Figure 2
(a) Epidemic curve for Sydney 1919 showing daily hospitalizations h(t) (black bars) and deaths d(t) (grey bars). Data on hospitalizations were not readily available after day 224. Periods A–F are labelled and characterized as follows: A, first cases, infection control measures; B, threat considered passed, lifting of control measures; C, reimposition of control measures, first wave; D, epidemic considered passed, lifting of control measures; E, second wave; F, epidemic passed. (b) Daily effective reproduction numbers estimated from hospitalizations (black circles and black line) and deaths (grey circles and grey line) with a smoothed cubic spline curve. Day t=25 is 25 January 1919.
Figure 3
Figure 3
Distribution of time from symptom onset to death for the cases of pandemic influenza in Sydney 1919 (after Armstrong 1920). Fitted curve is a gamma (k=2.74, θ=3.23) distribution.
Figure 4
Figure 4
Reproduction number adjusted for the depletion of susceptibles, assuming a serological attack rate of 36.6 and 91.2% susceptibility at the start of the epidemic and the degree of social distancing. Fitted curve is a smoothed cubic spline curve. Day t=25 is 25 January 1919.
Figure 5
Figure 5
The relationship between the reproduction number adjusted for susceptible depletion (RA(t)) and the daily number of deaths (D(t)) during the (a) first and (b) second waves. The trajectory of the reproduction number based on deaths adjusted for the depletion of susceptibles in relation to the daily number of deaths advanced 9 days (D(t+9)) during the (c) first and (d) second waves.

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