Hospitalization Fatality Risk of Influenza A(H1N1)pdm09: A Systematic Review and Meta-Analysis.
ABSTRACT: During the 2009 influenza pandemic, uncertainty surrounding the severity of human infections with the influenza A(H1N1)pdm09 virus hindered the calibration of the early public health response. The case fatality risk was widely used to assess severity, but another underexplored and potentially more immediate measure is the hospitalization fatality risk (HFR), defined as the probability of death among H1N1pdm09 cases who required hospitalization for medical reasons. In this review, we searched for relevant studies published in MEDLINE (PubMed) and EMBASE between April 1, 2009, and January 9, 2014. Crude estimates of the HFR ranged from 0% to 52%, with higher estimates from tertiary-care referral hospitals in countries with a lower gross domestic product, but in wealthy countries the estimate was 1%-3% in all settings. Point estimates increased substantially with age and with lower gross domestic product. Early in the next pandemic, estimation of a standardized HFR may provide a picture of the severity of infection, particularly if it is presented in comparison with a similarly standardized HFR for seasonal influenza in the same setting.
Project description:During the early stage of an epidemic, timely and reliable estimation of the severity of infections are important for predicting the impact that the influenza viruses will have in the population. We obtained age-specific deaths and hospitalizations for patients with laboratory-confirmed H1N1pdm09 infections from June 2009 to December 2009 in Hong Kong. We retrospectively obtained the real-time estimates of the hospitalization fatality risk (HFR), using crude estimation or allowing for right-censoring for final status in some patients. Models accounting for right-censoring performed better than models without adjustments. The risk of deaths in hospitalized patients with confirmed H1N1pdm09 increased with age. Reliable estimates of the HFR could be obtained before the peak of the first wave of H1N1pdm09 in young and middle-aged adults but after the peak in the elderly. In the next influenza pandemic, timely estimation of the HFR will contribute to risk assessment and disease control.
Project description:The current Ebola virus disease (EVD) epidemic in West Africa is unprecedented in scale, and Sierra Leone is the most severely affected country. The case fatality risk (CFR) and hospitalization fatality risk (HFR) were used to characterize the severity of infections in confirmed and probable EVD cases in Sierra Leone. Proportional hazards regression models were used to investigate factors associated with the risk of death in EVD cases. In total, there were 17 318 EVD cases reported in Sierra Leone from 23 May 2014 to 31 January 2015. Of the probable and confirmed EVD cases with a reported final outcome, a total of 2536 deaths and 886 recoveries were reported. CFR and HFR estimates were 74·2% [95% credibility interval (CrI) 72·6-75·5] and 68·9% (95% CrI 66·2-71·6), respectively. Risks of death were higher in the youngest (0-4 years) and oldest (?60 years) age groups, and in the calendar month of October 2014. Sex and occupational status did not significantly affect the mortality of EVD. The CFR and HFR estimates of EVD were very high in Sierra Leone.
Project description:<h4>Background</h4>During the 2009 H1N1v influenza epidemic, the total number of symptomatic cases was estimated by combining influenza-like illness (ILI) consultations, virological surveillance and assumptions about healthcare-seeking behaviour. Changes in healthcare-seeking behaviour due to changing scientific information, media coverage and public anxiety, were not included in case estimates. The purpose of the study was to improve estimates of the number of symptomatic H1N1v cases and the case fatality rate (CFR) in England by quantifying healthcare-seeking behaviour using an internet-based survey carried out during the course of the 2009 H1N1v influenza epidemic.<h4>Methods</h4>We used an online survey that ran continuously from July 2009 to March 2010 to estimate the proportion of ILI cases that sought healthcare during the 2009 H1N1v influenza epidemic. We used dynamic age- and gender-dependent measures of healthcare-seeking behaviour to re-interpret consultation numbers and estimate the true number of cases of symptomatic ILI in 2009 and the case fatality rate (CFR).<h4>Results</h4>There were significant differences between age groups in healthcare usage. From the start to the end of the epidemic, the percentage of individuals with influenza-like symptoms who sought medical attention decreased from 43% to 32% (p < 0.0001). Adjusting official numbers accordingly, we estimate that there were 1.1 million symptomatic cases in England, over 320,000 (40%) more cases than previously estimated and that the autumn epidemic wave was 45% bigger than previously thought. Combining symptomatic case numbers with reported deaths leads to a reduced overall CFR estimate of 17 deaths per 100,000 cases, with the largest reduction in adults.<h4>Conclusions</h4>Active surveillance of healthcare-seeking behaviour, which can be achieved using novel data collection methods, is vital for providing accurate real-time estimates of epidemic size and disease severity. The differences in healthcare-seeking between different population groups and changes over time have significant implications for estimates of total case numbers and the case fatality rate.
Project description: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.
Project description:<h4>Background</h4>Accurate measures of the severity of pandemic (H1N1) 2009 influenza (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, resulting in overestimation of the severity of an average case. We sought to estimate the probabilities that symptomatic infection would lead to hospitalization, ICU admission, and death by combining data from multiple sources.<h4>Methods and findings</h4>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 (ILI) in New York--were used to estimate ratios of symptomatic cases to hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic patients who 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 an 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 7-9 x lower. sCFR and sCIR appear to be highest in persons aged 18 y and older, and lowest in children aged 5-17 y. sCHR appears to be lowest in persons aged 5-17; our data were too sparse to allow us to determine the group in which it was the highest.<h4>Conclusions</h4>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 the greatest impact in children aged 0-4 and adults 18-64. 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 total proportion of the population symptomatically infected were lower than assumed.
Project description:BACKGROUND:During the 2009 influenza pandemic, uncertainty surrounding the seriousness of human infections with the H1N1pdm09 virus hindered appropriate public health response. One measure of seriousness is the case fatality risk, defined as the probability of mortality among people classified as cases. METHODS:We conducted a systematic review to summarize published estimates of the case fatality risk of the pandemic influenza H1N1pdm09 virus. Only studies that reported population-based estimates were included. RESULTS:We included 77 estimates of the case fatality risk from 50 published studies, about one-third of which were published within the first 9 months of the pandemic. We identified very substantial heterogeneity in published estimates, ranging from less than 1 to more than 10,000 deaths per 100,000 cases or infections. The choice of case definition in the denominator accounted for substantial heterogeneity, with the higher estimates based on laboratory-confirmed cases (point estimates = 0-13,500 per 100,000 cases) compared with symptomatic cases (point estimates = 0-1,200 per 100,000 cases) or infections (point estimates = 1-10 per 100,000 infections). Risk based on symptomatic cases increased substantially with age. CONCLUSIONS:Our review highlights the difficulty in estimating the seriousness of infection with a novel influenza virus using the case fatality risk. In addition, substantial variability in age-specific estimates complicates the interpretation of the overall case fatality risk and comparisons among populations. A consensus is needed on how to define and measure the seriousness of infection before the next pandemic.
Project description:<h4>Background</h4>While children and young adults had the highest attack rates due to 2009 pandemic (H1N1) influenza A (2009 H1N1), studies of hospitalized cases noted high fatality in older adults. We analyzed California public health surveillance data to better characterize the populations at risk for dying due to 2009 H1N1.<h4>Methods and findings</h4>A case was an adult ?20 years who died with influenza-like symptoms and laboratory results indicative of 2009 H1N1. Demographic and clinical data were abstracted from medical records using a standardized case report form. From April 3, 2009-August 10, 2010, 541 fatal cases ?20 years with 2009 H1N1 were reported. Influenza fatality rates per 100,000 population were highest in persons 50-59 years (3.5; annualized rate?=?2.6) and 60-69 years (2.3; annualized rate?=?1.7) compared to younger and older age groups (0.4-1.9; annualized rates?=?0.3-1.4). Of 486 cases hospitalized prior to death, 441 (91%) required intensive care unit (ICU) admission. ICU admission rates per 100,000 population were highest in adults 50-59 years (8.6). ICU case-fatality ratios among adults ranged from 24-42%, with the highest ratios in persons 70-79 years. A total of 425 (80%) cases had co-morbid conditions associated with severe seasonal influenza. The prevalence of most co-morbid conditions increased with increasing age, but obesity, pregnancy and obstructive sleep apnea decreased with age. Rapid testing was positive in 97 (35%) of 276 tested. Of 482 cases with available data, 384 (80%) received antiviral treatment, including 49 (15%) of 328 within 48 hours of symptom onset.<h4>Conclusions</h4>Adults aged 50-59 years had the highest fatality due to 2009 H1N1; older adults may have been spared due to pre-existing immunity. However, once infected and hospitalized in intensive care, case-fatality ratios were high for all adults, especially in those over 60 years. Vaccination of adults older than 50 years should be encouraged.
Project description:Diagnostic test sensitivity affects rate estimates for laboratory-confirmed influenza-associated hospitalizations. We used data from FluSurv-NET, a national population-based surveillance system for laboratory-confirmed influenza hospitalizations, to capture diagnostic test type by patient age and influenza season. We calculated observed rates by age group and adjusted rates by test sensitivity. Test sensitivity was lowest in adults >65 years of age. For all ages, reverse transcription PCR was the most sensitive test, and use increased from <10% during 2003-2008 to ≈70% during 2009-2013. Observed hospitalization rates per 100,000 persons varied by season: 7.3-50.5 for children <18 years of age, 3.0-30.3 for adults 18-64 years, and 13.6-181.8 for adults >65 years. After 2009, hospitalization rates adjusted by test sensitivity were ≈15% higher for children <18 years, ≈20% higher for adults 18-64 years, and ≈55% for adults >65 years of age. Test sensitivity adjustments improve the accuracy of hospitalization rate estimates.
Project description:In 2003, surveillance for influenza in hospitalized persons was added to the Centers for Disease Control and Prevention Emerging Infections Program network. This surveillance enabled monitoring of the severity of influenza seasons and provided a platform for addressing priority questions associated with influenza. For enhanced surveillance capacity during the 2009 influenza pandemic, new sites were added to this platform. The combined surveillance platform is called the Influenza Hospitalization Surveillance Network (FluSurv-NET). FluSurv-NET has helped to determine the risk for influenza-associated illness in various segments of the US population, define the severity of influenza seasons and the 2009 pandemic, and guide recommendations for treatment and vaccination programs.
Project description:The novel coronavirus disease 2019 (COVID-19) was first reported in Wuhan, China, where the initial wave of intense community transmissions was cut short by interventions. Using multiple data sources, here we estimate the disease burden and clinical severity by age of COVID-19 in Wuhan from December 1, 2019 to March 31, 2020. Our estimates account for the sensitivity of the laboratory assays, prospective community screenings, and healthcare seeking behaviors. Rates of symptomatic cases, medical consultations, hospitalizations and deaths were estimated at 796 (95% CI: 703-977), 489 (472-509), 370 (358-384), and 36.2 (35.0-37.3) per 100,000 persons, respectively. The COVID-19 outbreak in Wuhan had a higher burden than the 2009 influenza pandemic or seasonal influenza in terms of hospitalization and mortality rates, and clinical severity was similar to that of the 1918 influenza pandemic. Our comparison puts the COVID-19 pandemic into context and could be helpful to guide intervention strategies and preparedness for the potential resurgence of COVID-19.