Infection fatality risk of the pandemic A(H1N1)2009 virus in Hong Kong

Abstract

One measure of the severity of a pandemic influenza outbreak at the individual level is the risk of death among people infected by the new virus. However, there are complications in estimating both the numerator and denominator. Regarding the numerator, statistical estimates of the excess deaths associated with influenza virus infections tend to exceed the number of deaths associated with laboratory-confirmed infection. Regarding the denominator, few infections are laboratory confirmed, while differences in case definitions and approaches to case ascertainment can lead to wide variation in case fatality risk estimates. Serological surveillance can be used to estimate the cumulative incidence of infection as a denominator that is more comparable across studies. We estimated that the first wave of the influenza A(H1N1)pdm09 virus in 2009 was associated with approximately 232 (95% confidence interval: 136, 328) excess deaths of all ages in Hong Kong, mainly among the elderly. The point estimates of the risk of death on a per-infection basis increased substantially with age, from below 1 per 100,000 infections in children to 1,099 per 100,000 infections in those 60-69 years of age. Substantial variation in the age-specific infection fatality risk complicates comparison of the severity of different influenza strains.

Figure 1.

All-cause deaths, pandemic A(H1N1)2009 virus (pH1N1) hospitalizations and deaths, and estimated pH1N1 incidence rates in Hong Kong, 2009. A) Weekly number of all-cause deaths; B) weekly number of hospitalizations of patients with confirmed pH1N1; C) weekly number of deaths of patients with confirmed pH1N1; D) age-specific estimated incidence rates of pH1N1 infection, estimated by deconvoluting hospital admission rates and scaling to serological surveillance data. Incidence rates by age group: 5–14 years (dot-dash-dot); 15–19 years (long dash); 20–29 years (double dash); 30–39 years (thin solid); 40–49 years (short dash); and 50–59 years (dotted), respectively, and the age-standardized incidence rates (thick solid), expressed as rates per 100,000 population per week. Incidence rates were standardized to the local Hong Kong population. Three-letter names and abbreviations on the inner label of the x-axis represent months of the year.

Figure 2.

Correlation between influenza-like illness (ILI) surveillance data, laboratory (LAB) detection data, and age-standardized incidence rate estimates (per 100,000 population per week) based on hospital admissions and serological surveillance data in Hong Kong, 2009. A) Correlation between ILI data based on general practitioners and incidence rates; B) correlation between LAB data and incidence rates; C) correlation between ILI × LAB and incidence rates. In each panel, the solid line indicates the least-squares regression line, and the dashed line indicates the constrained ordinary least-squares regression line through the origin. The dashed line in each panel has the intercept coefficient fixed at zero. The estimated intercept coefficients for the solid line in each panel were estimated as follows: A) 41 (95% confidence interval (CI): 29, 53); B) 70 (95% CI: 37, 100); C) −1.3 (95% CI: −7.4, 4.7).