Background Accurate measures of the severity of pandemic influenza A/H1N1 (pH1N1) are needed to assess the likely impact of an anticipated resurgence in the autumn in the Northern Hemisphere. Severity has been difficult to measure because jurisdictions with large numbers of deaths and other severe outcomes have had too many cases to assess the total number with confidence. Also, detection of severe cases may be more likely. Methods and Findings We used complementary data from two US cities: Milwaukee attempted to identify cases of medically attended infection whether or not they required hospitalization, while New York City focused on the identification of hospitalizations, intensive care admission or mechanical ventilation (hereafter, ICU), and deaths. New York data were used to estimate numerators for ICU and death, and two sources of data: medically attended cases in Milwaukee or self-reported influenza-like illness in New York, were used to estimate ratios of symptomatic cases:hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic cases that died (symptomatic case-fatality ratio, sCFR), required ICU (sCIR), and required hospitalization (sCHR), overall and by age category. Evidence, prior information and associated uncertainty were analyzed in a Bayesian evidence synthesis framework. Using medically attended cases and estimates of the proportion of symptomatic cases medically attended, we estimated sCFR of 0.048% (95% credible interval, CI 0.026%-0.096%), sCIR of 0.239% (0.134%-0.458%), and sCHR of 1.44% (0.83%-2.64%). Using self-reported ILI, we obtained estimates approximately 7-9x lower. sCFR and sCIR appear to be highest in persons 18 and older, and lowest in children 5-17. sCHR appears to be lowest in persons 5-17; our data were too sparse to allow us to determine the group in which it was the highest. Conclusions These estimates suggest that an autumn-winter pandemic wave of pH1N1 with comparable severity per case could lead to a number of deaths in the range from considerably below that associated with seasonal influenza to slightly higher, but with greatest impact in young children and non-elderly adults. These estimates of impact depend on assumptions about total incidence of infection and would be larger if incidence of symptomatic infection were higher or shifted toward adults, if viral virulence increased, or if suboptimal treatment resulted from stress on the health care system; numbers would decrease if the proportion infected or symptomatic were lower.
The present pandemic of pandemic influenza A/H1N1 (pH1N1) has resulted in over 209,000 laboratory-confirmed cases and over 3205 deaths worldwide as of September 11 (
Although it is difficult to estimate these quantities, estimates of their values and associated uncertainty are important for decision making, planning and response during the progression of this pandemic. Initially, some national and international pandemic response plans were tied partly to estimates of the CFR, but such plans had to be modified in the early weeks of this pandemic, as it became clear that the CFR could not at that time be reliably estimated
The problem of estimating severity of pH1N1 infection is also the problem of estimating how many of the infected individuals in a given population and time period subsequently develop symptoms, are medically attended, hospitalized, admitted to ICU, and die due to the virus. No large jurisdiction in the world has been able to maintain an accurate count of total pH1N1 cases once the epidemic has grown beyond hundreds of cases, because the effort required to confirm and count such cases grows in proportion to the size of the exponentially-growing epidemic
Here we use a similar framework to synthesize evidence from two cities in the United States - New York and Milwaukee - together with estimates of important detection probabilities from epidemiologic investigations carried out by the Centers for Disease Control and Prevention (CDC) and other data from CDC. We estimate the severity of pH1N1 infection from data from spring-summer, 2009 wave of infections in the United States. The New York City and Milwaukee health departments pursued differing surveillance strategies that provided high-quality data on complementary aspects of pH1N1 severity, with Milwaukee documenting medically attended cases and hospitalizations, and New York documenting hospitalizations, ICU/ventilation use, and fatalities. These are the numerators of the ratios of interest.
The denominator for these ratios is the number of symptomatic pH1N1 cases in a population, which cannot be assessed directly. We use two different approaches to estimate this quantity. In the first, we use self-reported rates of seeking medical attention for influenza-like illness from several CDC investigations to estimate the number of symptomatic cases from the number of medically attended cases, which are estimated from data from Milwaukee. In the second, we use self-reported incidence of influenza-like illness (ILI) in New York City, and making the assumption that these ILI cases represent the true denominator of symptomatic cases, we directly estimate the ratio between hospitalizations, ICU admissions/mechanical ventilation, and deaths (adjusting for ascertainment) in New York. Each of these two methods provides estimates for the general population, and also for broad age categories 0-4, 5-17, 18-64, and 65+ years. The result of each approach is a tiered severity estimate of the pandemic.
All of these estimates were combined within a Bayesian evidence synthesis framework. This framework permits the estimation of probabilities for the quantities of interest (the sCFR, sCIR and sCHR) and associated uncertainty (expressed as credible intervals). These credible intervals appropriately reflect the combined uncertainties associated with each of the inputs to the estimate - mainly, the true numbers of cases at each level of severity, after accounting for imperfect detection - as well as the uncertainties due to sampling error (chance).
Separately, we obtained a list of 53 deaths attributed to pH1N1, of whom 44 (83%) had been hospitalized before dying. All patients with known influenza or unexplained febrile respiratory illness at the time of death had post-mortem samples and/or samples from before they died sent for PCR testing.
To account for this design, the data were weighted to the 2007 American Community Survey (ACS); respondents were weighted to householders by borough, age, gender, and race/ethnicity, and the population was weighted by age to the borough of residence.
The survey’s RDD sampling methodology gave a useful overview of ILI in the community, but it has limitations. The design does not include individual living in households only reachable by cellular telephone but not by a landline telephone number, and also omitted those living in group or institutional housing. Although households were randomly selected, for the sake of efficiency, the interviewed adult was not. Instead, an available adult in the household provided information about all household members and themselves, which may have introduced bias. The results of the survey are being compiled for publication elsewhere. Here, we use summaries of these results by age group (see
Approach 1 used three data sets to estimate successive steps of the severity pyramid. Approach 2 used self-reported influenza-like illness for the denominator, and confirmed deaths for the numerator, both from New York City. Both approaches used prior distributions, in some cases informed by additional data, to inform the probability of detecting (confirming and reporting) cases at each level of severity (not shown in the diagram; see
The key quantities of interest, sCHR, sCIR, and sCFR are products of the relevant conditional probabilities. (a) Approach 1, synthesizing data from New York City and Milwaukee. Note that
We noted that the ratios
where the first subscript indicates severity and the second indicates the population (New York, Milwaukee to May 20, Milwaukee to June 14).
In Approach 1 (New York and Milwaukee data combined), for the unobserved level of severity (symptomatic cases) we used a prior distribution of
In Approach 2 (New York case data and telephone survey data), we made the assumption that self-reported ILI cases represented symptomatic pH1N1 infection, and used the mean and 95% confidence intervals from that survey to define a prior distribution on the number of symptomatic cases overall and by age group. We then used observed hospitalizations, ICU/ventilator use, and fatalities along with prior distributions on detection probabilities as above to inform estimates of true numbers of hospitalizations, ICU/ventilator use, and fatalities, and these in turn were used to estimate sCHR, sCIR, and sCFR.
The evidence was synthesized through a full probability model in a Bayesian framework, implemented in the OpenBUGS software
Table 2 shows the numbers of medically attended cases, hospitalizations, ICU visits and deaths in the two cities, with the Milwaukee data separated into the period (to May 20) for which we believe medically attended cases were consistently detected, and the period (to June 14) for which we consider only hospitalized cases, ICU admissions and deaths.
Medically |
Hospitalized | ICU-admitted | Dead | ||
to May 20 / to June 14 | to June 14 | to June 14 | |||
0-4 | 126 (16%) | 7 (28%) | 27 (18%) | 5 (20%) | 0 |
5-17 | 470 (60%) | 6 (24%) | 29 (20%) | 7 (26%) | 2 (50%) |
18-64 | 189 (24%) | 12 (48%) | 87 (59%) | 14 (52%) | 2 (50%) |
65+ | 3 (0.4%) | 0 | 4 (3%) | 1 (4%) | 0 |
Total | 788 | 25 | 147 | 25 | 4 |
Dead (total) / Dead but not hospitalized | |||||
0-4 | 225 (23%) | 44 (17%) | 2 (4%) / 2 | ||
5-17 | 197 (20%) | 51 (20%) | 2 (4%) / 1 | ||
18-64 | 518 (52%) | 147 (57%) | 46 (87%) / 6 | ||
65+ | 56 (6%) | 15 (6%) | 3 (6%) / 0 | ||
Total | 996 | 257 | 53 / 9 |
The naïve estimate would suggest a median (95% credible interval (CI)) ratio of deaths to hospitalizations (
Incorporating prior evidence of the detection probabilities at each level of severity, and thus accommodating structural and statistical uncertainties in these probabilities, we estimated that ratio of deaths to hospitalizations (
Table 3 shows the estimates for the quantities of primary interest, overall and by age group, in the analysis that incorporated prior evidence of detection probabilities. Here, the posterior median estimate for the symptomatic case-fatality ratio is 0.048% (95% credible interval 0.026%-0.096%) and for the symptomatic case-ICU admissions ratio is 0.239% (95% CI 0.134%-0.458%). The symptomatic case-hospitalization ratio is estimated as 1.44% (95% CI 0.83%-2.64%).
age | 0-4 | 0.026% | (0.006%-0.092%) | 0.321% | (0.133%-0.776%) | 2.45% | (1.10%-5.56%) |
5-17 | 0.010% | (0.003%-0.031%) | 0.106% | (0.043%-0.244%) | 0.61% | (0.27%-1.34%) | |
18-64 | 0.159% | (0.066%-0.333%) | 0.542% | (0.230%-1.090%) | 3.00% | (1.35%-5.92%) | |
65+ | 0.090% | (0.008%-1.471%) | 0.327% | (0.035%-4.711%) | 1.84% | (0.21%-25.38%) | |
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We have estimated, using data from two cities on tiered levels of severity and self-reported rates of seeking medical attention, that approximately 1.44% of symptomatic 2009 pH1N1 patients during the spring in the United States were hospitalized; 0.239% required intensive care or mechanical ventilation; and 0.048% died. Within the assumptions made in our model, these estimates are uncertain up to a factor of about 2 in either direction, as reflected in the 95% credible intervals associated with the estimates. These estimates take into account differences in detection and reporting of cases at different levels of severity, which we believe, based on some evidence, to be more complete at higher levels of severity. Without such corrections for detection and reporting, estimates are approximately two-fold higher for each level of severity. Using a second approach, which uses self-reported rates of influenza-like illness in New York City to estimate symptomatic infections, we have estimated rates approximately an order of magnitude lower, with a symptomatic case-hospitalization ratio (sCHR) of 0.16%, a symptomatic case-intensive care ratio of 0.028%, and a symptomatic case-fatality ratio of 0.007%. In both approaches, the sCFR was highest in adults and lowest in school-age children (5-17); data on children 0-4 and adults 65 and older were relatively sparse, making statements about their ordering more difficult. Nonetheless, given the large number of cases in nonelderly adults, this represents a substantial shift in the burden of hospitalization and mortality from those over 65, for whom seasonal influenza is most severe
These estimates are valuable for attempting to project, in approximate terms, the possible severity of a fall-winter wave of pH1N1, under the assumption that the virus does not change its characteristics. From the 1957 and 1968 pandemics, it appears that perhaps 40-60% of the population was serologically infected, and that of those, 40-60% were symptomatic
To date, symptomatic attack rates seem to be far lower than 25% in both the completed Southern Hemisphere winter epidemic and the autumn epidemic in progress in the United States; severe outcomes seem to be considerably less numerous than those described for Approach 1 with a 25% attack rate. In New Zealand, just under 2% of the population consulted a general practitioner for influenza-like illness during the winter wave of the pandemic there (
Our estimates reflect a level of antiviral treatment and health care capacity that will not be available in all populations. Oseltamivir use was common in Milwaukee (Milwaukee Department of Health, unpublished data), and although the health system was stressed in both cities studied, there was no shortage of intensive care or other life-saving medical resources. In a situation of greater stress on the health system, as has been observed in certain locations in the Southern Hemisphere
Estimates of severity for an infection such as influenza are fraught with uncertainties
Despite our efforts to account for sources of uncertainty, several others remain and have not been accounted for in our analysis. First, we have assumed that for each level of severity (from medically attended up to fatal), case reporting was equal across age groups; for example, we assumed that medically attended cases were as likely to be reported for young children as for adults. It is possible that this is not the case, for example that mild cases were more likely to come to medical attention if they occurred in children than if they occurred in adults. If this were true, our conclusion that severity was higher in adults than children could be partly a result of differential reporting.
Second, the overall estimates of severity (not stratified by age group) reflect the age composition of cases in the sample we studied, especially the age composition of the lowest level of severity examined, medically attended illness. Among medically attended cases in Milwaukee, 60% were in the 5-17 age group, the one in which severe outcomes were the least likely. A preponderance of cases within this age group may be typical of the early part of influenza epidemics, and while it has been argued that there is a shift from younger to older age groups in seasonal influenza
We note that the association between age and severity may also affect observed trends in the characteristics of cases. The World Health Organization has noted worldwide a shift from younger to older mean age among confirmed cases (
Third, the symptomatic case-fatality, case-ICU admission and case-hospitalization ratios are dependent upon our estimates of the true number of symptomatic cases,
Finally, the small sample sizes in some age groups, the over-65 year olds in particular, lead to large uncertainty about the age-specific estimates. This level of uncertainty is reflected in the wide 95% credible intervals for the estimates.
Our two approaches yield estimates that differ by almost an order of magnitude in the severity of the infection, on each of the three measures considered. How should planners evaluate these contrasting estimates? The lower estimates, using the denominator of self-reported influenza-like illness in New York City, may reasonably be considered lower bounds on the true ratios. Influenza-like illness is thought to be relatively rare in May-June, hence true influenza-like illness was probably largely attributable to pH1N1 during this period in New York. However, self-reported ILI is notoriously prone to various biases, most of which suggest that true rates are probably lower than self-reported rates. A previous telephone survey conducted in New York City found that 18.5% of New Yorkers reported influenza-like illness in the 30 days prior to being surveyed in late March, 2003
Age-specific severity patterns as estimated here are largely consistent with those one would obtain by simply comparing the incidence of confirmed cases, hospitalizations, and deaths in the United States as a whole for a similar period
The estimates provided here may be compared to those for seasonal influenza. Compared to seasonal influenza, these estimates (assuming a 25% symptomatic attack rate) suggest a number of deaths in the United States that could range from about half the number estimated for an average year to nearly twice the number estimated for an average year
Our estimate of the symptomatic case-fatality ratio is lower than those provided by Garske et al.
While we have been careful to highlight uncertainties in the estimates of severity, our results are sufficiently well-resolved to have important implications for ongoing pH1N1 pandemic planning. The estimated severity indicates that a reasonable expectation for the autumn pandemic wave in the United States is a death toll less than or equal to that which is typical for seasonal influenza, though possibly with considerably more deaths in younger persons. If attack rates in the autumn match those of prior pandemics and hospitalization rates are comparable to our estimates using Approach 1, the surge of ill individuals and subsequent burden on hospitals and intensive care units could be large. However, using Approach 2, estimates of hospitalizations and intensive care admissions are considerably lower. Either set of estimates places the epidemic within the lowest category of severity considered in pandemic planning conducted prior to the appearance of pH1N1 in the United States, which considered case-fatality ratios up to 0.1% (
Continued close monitoring of severity of pandemic H1N1 disease is needed to assess how patterns of hospitalization, intensive care utilization, and fatality are varying in space and time, and across age groups. Increases in severity might reflect changes in the host population – for example, infection of persons with conditions that predispose them to severe outcomes, or increased severity might reflect changes in the age distribution of cases, for example a shift toward adults, in whom infection is more severe. Changes in severity might also reflect changes in the virus or variation in the access and quality of care available to infected persons.
ML has received consulting fees from the Avian/Pandemic Flu Registry (Outcome Sciences), sponsored in part by Roche. All other authors declare no conflict of interest.
We thank Michael G. Baker for helpful discussions and Carolyn Bridges for useful comments on earlier drafts.