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Copyright : © 2007 Olson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Monitoring the Impact of Influenza by Age: Emergency Department Fever and Respiratory Complaint Surveillance in New York City New York City Department of Health and Mental Hygiene, New York, New York, United States of America Neil M Ferguson, Academic Editor Imperial College London, United Kingdom * To whom correspondence should be addressed. E-mail: drolson/at/gmail.com (DRO); Email: burchheff/at/gmail.com (RTH) Received May 4, 2006; Accepted June 19, 2007. This article has been cited by other articles in PMC.Abstract Background The importance of understanding age when estimating the impact of influenza on hospitalizations and deaths has been well described, yet existing surveillance systems have not made adequate use of age-specific data. Monitoring influenza-related morbidity using electronic health data may provide timely and detailed insight into the age-specific course, impact and epidemiology of seasonal drift and reassortment epidemic viruses. The purpose of this study was to evaluate the use of emergency department (ED) chief complaint data for measuring influenza-attributable morbidity by age and by predominant circulating virus. Methods and Findings We analyzed electronically reported ED fever and respiratory chief complaint and viral surveillance data in New York City (NYC) during the 2001–2002 through 2005–2006 influenza seasons, and inferred dominant circulating viruses from national surveillance reports. We estimated influenza-attributable impact as observed visits in excess of a model-predicted baseline during influenza periods, and epidemic timing by threshold and cross correlation. We found excess fever and respiratory ED visits occurred predominantly among school-aged children (8.5 excess ED visits per 1,000 children aged 5–17 y) with little or no impact on adults during the early-2002 B/Victoria-lineage epidemic; increased fever and respiratory ED visits among children younger than 5 y during respiratory syncytial virus-predominant periods preceding epidemic influenza; and excess ED visits across all ages during the 2003–2004 (9.2 excess visits per 1,000 population) and 2004–2005 (5.2 excess visits per 1,000 population) A/H3N2 Fujian-lineage epidemics, with the relative impact shifted within and between seasons from younger to older ages. During each influenza epidemic period in the study, ED visits were increased among school-aged children, and each epidemic peaked among school-aged children before other impacted age groups. Conclusions Influenza-related morbidity in NYC was highly age- and strain-specific. The impact of reemerging B/Victoria-lineage influenza was focused primarily on school-aged children born since the virus was last widespread in the US, while epidemic A/Fujian-lineage influenza affected all age groups, consistent with a novel antigenic variant. The correspondence between predominant circulating viruses and excess ED visits, hospitalizations, and deaths shows that excess fever and respiratory ED visits provide a reliable surrogate measure of incident influenza-attributable morbidity. The highly age-specific impact of influenza by subtype and strain suggests that greater age detail be incorporated into ongoing surveillance. Influenza morbidity surveillance using electronic data currently available in many jurisdictions can provide timely and representative information about the age-specific epidemiology of circulating influenza viruses. Editors' Summary Background. Seasonal outbreaks (epidemics) of influenza (a viral infection of the nose, throat, and airways) send millions of people to their beds every winter. Most recover quickly, but flu epidemics often disrupt daily life and can cause many deaths. Seasonal epidemics occur because influenza viruses continually make small changes to the viral proteins (antigens) that the human immune system recognizes. Consequently, an immune response that combats influenza one year may provide partial or no protection the following year. Occasionally, an influenza virus with large antigenic changes emerges that triggers an influenza pandemic, or global epidemic. To help prepare for both seasonal epidemics and pandemics, public-health officials monitor influenza-related illness and death, investigate unusual outbreaks of respiratory diseases, and characterize circulating strains of the influenza virus. While traditional influenza-related illness surveillance systems rely on relatively slow voluntary clinician reporting of cases with influenza-like illness symptoms, some jurisdictions have also started to use “syndromic” surveillance systems. These use electronic health-related data rather than clinical impression to track illness in the community. For example, increased visits to emergency departments for fever or respiratory (breathing) problems can provide an early warning of an influenza outbreak. Why Was This Study Done? Rapid illness surveillance systems have been shown to detect flu outbreaks earlier than is possible through monitoring deaths from pneumonia or influenza. Increases in visits to emergency departments by children for fever or respiratory problems can provide an even earlier indicator. Researchers have not previously examined in detail how fever and respiratory problems by age group correlate with the predominant circulating respiratory viruses. Knowing details like this would help public-health officials detect and respond to influenza epidemics and pandemics. In this study, the researchers have used data collected between 2001 and 2006 in New York City emergency departments to investigate these aspects of syndromic surveillance for influenza. What Did the Researchers Do and Find? The researchers analyzed emergency department visits categorized broadly into a fever and respiratory syndrome (which provides an estimate of the total visits attributable to influenza) or more narrowly into an influenza-like illness syndrome (which specifically indicates fever with cough and/or sore throat) with laboratory-confirmed influenza surveillance data. They found that emergency department visits were highest during peak influenza periods, and that the affect on different age groups varied depending on the predominant circulating viruses. In early 2002, an epidemic reemergence of B/Victoria-lineage influenza viruses caused increased visits among school-aged children, while adult visits did not increase. By contrast, during the 2003–2004 season, when the predominant virus was an A/H3N2 Fujian-lineage influenza virus, excess visits occurred in all age groups, though the relative increase was greatest and earliest among school-aged children. During periods of documented respiratory syncytial virus (RSV) circulation, increases in fever and respiratory emergency department visits occurred in children under five years of age regardless of influenza circulation. Finally, the researchers found that excess visits to emergency departments for fever and respiratory symptoms preceded deaths from pneumonia or influenza by about two weeks. What Do These Findings Mean? These findings indicate that excess emergency department visits for fever and respiratory symptoms can provide a reliable and timely surrogate measure of illness due to influenza. They also provide new insights into how different influenza viruses affect people of different ages and how the timing and progression of each influenza season differs. These results, based on data collected over only five years in one city, might not be generalizable to other settings or years, warn the researchers. However, the present results strongly suggest that the routine monitoring of influenza might be improved by using electronic health-related data, such as emergency department visit data, and by examining it specifically by age group. Furthermore, by showing that school-aged children can be the first people to be affected by seasonal influenza, these results highlight the important role this age group plays in community-wide transmission of influenza, an observation that could influence the implementation of public-health strategies such as vaccination that aim to protect communities during influenza epidemics and pandemics. Additional Information. Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040247. • US Centers for Disease Control and Prevention provides information on influenza for patients and health professionals and on influenza surveillance in the US (in English, Spanish, and several other languages)• World Health Organization has a fact sheet on influenza and on global surveillance for influenza (in English, Spanish, French, Russian, Arabic, and Chinese)• The MedlinePlus encyclopedia contains a page on flu (in English and Spanish)• US National Institute of Allergy and Infectious Diseases has a feature called “focus on flu”• A detailed report from the US Centers for Disease Control and Prevention titled “Framework for Evaluating Public Health Surveillance Systems for Early Detection of Outbreaks” includes a simple description of syndromic surveillance• The International Society for Disease Surveillance has a collaborative syndromic surveillance public wiki• The Anthropology of the Contemporary Research Collaboratory includes working papers and discussions by cultural anthropologists studying modern vital systems security and syndromic surveillanceIntroduction Throughout the twentieth century, epidemic and pandemic influenza was responsible for causing widespread illness, economic disruption, and considerable loss of life worldwide [1–3]. While the seasonal recurrence of influenza is anticipated each year, it remains difficult to predict the predominant seasonal strains and impossible to know when and where the next human pandemic will emerge. Timely regional monitoring of influenza-related morbidity is a priority for seasonal surveillance and pandemic preparedness [4]. Influenza surveillance currently conducted in the United States encompasses systems for monitoring influenza-related illness and death, investigating unusual respiratory disease outbreaks, and identifying and characterizing viral influenza strains [5]. The rapid epidemiological assessment of influenza-related morbidity and mortality remains a challenge for public health due to the nonspecific symptoms, rarity of laboratory confirmation, and difficulty in obtaining continuous, representative, and age-specific data [1,2]. Across the US, influenza-like illness (ILI) and pneumonia and influenza (P&I) mortality surveillance coordinated by the Centers for Disease Control and Prevention (CDC) has relied on weekly reporting of ILI visits by physicians in a voluntary sentinel network, and of P&I deaths by participating municipal vital records offices [5]. The primary shortcomings of these systems include the burden on health department and physician practices resulting in low and variable participation, with reporting delays and an absence of timely year-round data limiting their usefulness. In recent years, New York City (NYC) and other jurisdictions have tracked influenza using syndromic surveillance systems such as those based on electronically reported emergency department (ED) patient chief complaints [6]. Several studies based on these systems have reported seasonal increases in respiratory or influenza-like syndrome visits coincident with documented influenza epidemics [6–12]. Coded respiratory and influenza-like ED visits have been reported to provide a timely, sensitive, and year-round measure that enables detection of epidemic influenza 1–2 wk earlier than does P&I mortality data [7]; and age-specific respiratory visits have been reported to show that data from children aged 3–4 y provide the earliest indicator, leading P&I mortality by 7 wk [8]. The absence of viral surveillance data from these studies, however, leave important questions unanswered: To what degree do early seasonal morbidity increases correlate with actual influenza or other respiratory virus circulation? And to what degree does circulating viral type, subtype, and strain impact the timing and magnitude of age-specific morbidity and mortality? Epidemiologic community and family studies [13–18] and retrospective analyses of mortality and hospitalization data [19–27] have provided considerable insight into the age-specific patterns of seasonal and epidemic influenza. Prospective morbidity surveillance systems, however, have not taken full advantage of age-specific data. Important epidemiologic insights gained by scrutinizing how influenza impacts specific age groups include evidence that influenza often spreads earliest among school-age children [1,16–18]; that school breaks may slow or delay seasonal impact [1,16]; that age-specific impact can be related to prior antigenic exposure in the population [1–3,28]; and that each influenza pandemic last century was marked by a signature shift in relative impact from older to younger age groups [24,25]. The purpose of this study was to evaluate the use of ED visit data for monitoring the age-specific timing and impact of epidemic influenza by predominant circulating viral type, subtype, and antigenic strain. Using a broad definition of ED visits classified as fever or respiratory syndrome chief complaints, we applied a statistical method, routinely used for monitoring clinical ILI [29,30] and P&I mortality data [5,19,20], to ED surveillance data to monitor visits during periods of influenza circulation and provide a surrogate measure of incident influenza-attributable ED visits in NYC. By quantifying and visualizing the temporal and age-specific course of influenza morbidity in the context of available laboratory surveillance data, we sought to improve ongoing influenza surveillance efforts in NYC. Methods Emergency Department Surveillance Data Electronic reporting of ED chief complaint data from NYC hospitals occurred daily during the study period from mid-November 2001 through June 2006. Data received each morning were typically >90% complete for the preceding day, and data received Monday mornings >95% complete for the preceding week. During the 2001–2002 season participating hospital EDs captured an estimated 65% of all ED visits citywide. Coverage gradually increased through the study period, reaching 79% of all ED visits citywide during 2002–2003, 88% during 2003–2004 and 90% during 2004–2005 and 2005–2006. Individual ED visit data were aggregated by age group, chief complaint syndrome group, and week ending Saturday. Of the 13.3 million ED visits reported by participating NYC facilities during the study period, 2.3 million were categorized into a broad “fever and respiratory” syndrome composed of the hierarchical and mutually exclusive syndromes “respiratory,” “fever/flu,” “common cold,” and “sepsis,” as previously described [6]. These syndromes have been used as part of daily surveillance activities in NYC since 2001, and were defined as follows: The “sepsis” syndrome captured ED visits whose chief complaint contained key words representing sepsis, bacteremia, cardiac arrest, unresponsive, unconscious, or dead on arrival—the sepsis syndrome was included to capture visits with chief complaints describing potential, severe influenza outcomes that would otherwise have been missed. The “common cold” syndrome captured visits with key words representing stuffy nose or nasal or cold symptoms that were not in visits captured within sepsis. The “respiratory” syndrome captured visits with key words and International Classification of Diseases 9th edition (ICD-9) codes representing pneumonia, shortness of breath, bronchitis, upper respiratory tract infection, difficulty breathing, pleurisy, croup, cough, dyspnea, and chest cold, which were not captured within the sepsis or common cold syndromes. And the “fever/flu” syndrome captured visits with key words and ICD-9 codes representing fever, chills, malaise, body aches, viral syndrome, and influenza, which were not captured within the sepsis, common cold, or respiratory categories, and did not include key words representing acute gastroenteritis, enteritis, or diarrhea. While chief complaints of “fever with diarrhea” could potentially be due to influenza, these were excluded in our analysis to avoid confounding with coincident epidemic viral gastroenteritis. The broad “fever and respiratory” syndrome category described above was used to provide the most sensitive measure of ED visits potentially attributable to influenza. We also created a specific “ILI” syndrome following the commonly used clinical surveillance definition of fever with cough and/or sore throat: Of the 2.3 million visits categorized into the broad fever and respiratory syndrome, 260,000 visits were categorized as ILI, defined as a chief complaint composed of an influenza keyword or of a fever-related key word with a mention of “cough” and/or “sore throat.” The broad fever and respiratory and the narrow ILI syndrome data are shown in Figure 1
Laboratory Surveillance Data Weekly counts of influenza A and Bvirus isolates were reported duringthe study by three World HealthOrganization (WHO) collaboratinglaboratories located in NYC(Figure1
Hospitalization and Death Data Confirmed hospitalizations by admission date in NYC from 1997–1998 to 2004–2005 were analyzed by multiple cause ICD-9 code reports for influenza (487), P&I (480–487), and respiratory syncytial virus (RSV) (079.6, 466.11) [22,23]. Confirmed deaths from 1997–1998 to 2003–2004 were analyzed as all-cause and by reported primary cause of death code for P&I (ICD-9 480–487; ICD-10 J10.0–J11.8, J12.0–J18.9) [20,21]. The hospitalization and death data for 1997–1998 through 2000–2001 are shown for comparison (Figure 3
Estimating Excess Morbidity and Mortality Weekly counts of ED visits coded by chief complaint into the broad fever and respiratory syndrome and the narrow ILI syndrome categories followed annual sinusoidal patterns of winter seasonal increase, punctuated by seven distinct periods of 6–12 wk duration coincident with positive influenza A or B isolate reporting by WHO collaborating laboratories in the city (Figure 1
Our estimates of expected ED visits by age and syndrome group during week t (Mt) were derived from least squares regression of the observed data by group using a constant α0, secular trend α1, annual sinusoidal terms γ1 and δ1, semiannual terms γ2 and δ2, and an error term et, applied to noncensored weeks. Estimates of excess weekly ED visits were calculated as observed minus expected. Our significance level, or “epidemic threshold,” was arbitrarily set at two standard deviations above the expected, as derived from the model variance of nonepidemic weeks. We applied the seasonal model and threshold to all weekly ED visit, hospitalization, and death time series. Estimates of excess seasonal epidemic ED visits were calculated as observed minus expected visits during influenza epidemic periods and consecutive weeks adjacent to those periods when the observed was above expected (shaded areas, Figure 1 To better understand age-specific visit patterns that occurred during periods of sporadic or no influenza circulation, we evaluated the timing and impact of two additional causes of seasonal respiratory illness: RSV and tree pollen. We identified predominant RSV periods as the upper quartile weeks of RSV hospitalizations from 2001 to mid-December 2005 (data shown in Figure S2) and predominant seasonal tree pollen periods as the 4 wk of greatest tree pollen counts recorded in 2005 and 2006 from a single environmental monitoring site in NYC. Estimating Epidemic Timing We defined initial detection of annual influenza epidemics as the first week ED visits, hospitalizations or deaths exceeded the two-standard-deviation threshold above model baseline. We compared the date of initial detection based on ED visits, hospitalizations, and deaths by age group (Table S1). We additionally evaluated age-specific epidemic timing by cross correlation [7], restricting our analysis to the 33-wk window centered on the viral influenza isolate peaks each season. We calculated Pearson cross-correlation coefficients with lags. And we considered the lag or lead time with the greatest single week coefficient, or with similar consecutive week coefficients, as providing the best estimated measure of inherent epidemic timing relative to influenza isolates. We evaluated age-specific epidemic timing for ED visits, hospitalizations, and deaths for 2003–2004, the only influenza season in our study with available data and with significant excess ED visits, hospitalizations, and deaths across age groups (Figure 4
Visualization of Morbidity by Age To visualize the temporal course of age-specific illness trends in NYC, fever and respiratory ED visits were detrended, normalized, and plotted by week and age group. To detrend the data, we fit a least-squares linear regression to the nonepidemic fever and respiratory ED visit data by age group, as above, but with the annual and semiannual seasonal sinusoidal terms removed. We divided the observed data time series by the nonepidemic linear fit to obtain normalized ED visits by week and category. We made a surface plot of normalized weekly time series as a gradient interpolated between adjacent week and age-group data points (Figure 5
Results Seasonal Impact From the 2001–2002 to 2005–2006 influenza seasons in NYC, we estimate on average that 40,000 excess ED visits (5.0 visits per 1,000 population) occurred per season during the documented influenza circulation periods. We estimate that 2,800 excess P&I hospitalizations (0.35 per 1,000) on average occurred per season from 2001–2002 to 2004–2005, and 500 excess all-cause (0.065 per 1,000) and 100 excess P&I (0.012 per 1,000) deaths occurred per season from 2001–2002 to 2003–2004. The seasonal impact of excess ED visits, hospitalizations, and deaths, however, varied greatly by age group and circulating virus. We summarize our results by season and predominant viral period. 2001–2002 season: An estimated 24,000 excess fever and respiratory ED visits (3.0 visits per 1,000 population), 2,200 excess P&I hospitalizations (0.28 per 1,000), 540 excess all-cause deaths (0.067 per 1,000), and 90 excess P&I deaths (0.011 per 1,000) occurred during the influenza A/H3N2 predominant period in NYC from December 2001 to February 2002 (weeks 50–07) (Figures 1 2002–2003 season: An estimated 10,000 excess ED visits (1.2 per 1,000 population) occurred during the predominant influenza A/H1 period (Figure 1 2003–2004 season: An estimated 71,000 excess fever and respiratory ED visits (8.9 per 1,000 population) occurred during the influenza A/H3N2 predominant period from November 2003 to January 2004 (weeks 46–01) (Figure 1 2004–2005 season: An estimated 42,000 excess fever and respiratory ED visits (5.2 per 1,000 population) and 3,600 excess P&I hospitalizations (0.44 per 1,000) occurred during the influenza A/H3N2 predominant period from November 2004 through January 2005 (weeks 46–04) (Figures 1 2005–2006 season: An estimated 12,000 excess ED visits (1.5 per 1,000 population) occurred during the influenza A/H3N2 predominant period, with excess ED visits detected in the age groups 2–4 y, 5–12 y, 13–17 y, 18–39 y, and 40–64 y (Figure 2 Epidemic Timing Influenza epidemic period increases were seen earlier in ED visits than in hospitalizations or deaths. During the influenza A/H3N2 epidemics in 2001–2002 and 2003–2004, excess all-ages fever and respiratory ED visits exceeded our two-standard-deviation Serfling model threshold 1 wk prior to P&I hospitalizations and, respectively, 1 and 3 wk prior to P&I deaths. During the mild influenza A/H1 epidemic in 2002–2003, all-ages fever and respiratory ED visits exceeded threshold 2 wk prior to deaths, and in the A/H3N2 epidemic in 2004–2005, all-ages ED visits exceeded threshold 3 wk prior to P&I hospitalizations (Figures 1 Fever and respiratory ED visits among children often exceeded threshold before adults, but there were differences between seasons. During 2001–2002, ED visits exceeded model thresholds in the < 2 y and 2–4 y age groups 1 wk before the 13–17 y and 18–39 y age groups, and 2 wk before the 5–12 y and 40–64 y age groups. During the more severe 2003–2004 A/H3N2 epidemic, age-specific ED visits exceeded threshold in the 13–17 y age group 1 wk before the < 2 y, 2–4 y, 5–12 y, and 18–39 y groups, 3 wk before the 40–64 y group, and 4 wk before the ≥ 65 y group (Figure 2 In our estimation of inherent epidemic timing, we limited our analysis to the 2003–2004 season, since it was the most severe and the only one with available ED, hospitalization, and death data and significant excess estimates across age groups (Figures 1 Visualizing Age-Specific Morbidity Patterns Observed fever and respiratory ED visits peaked annually during influenza epidemic periods as defined by laboratory evidence (Figure 1 The more specific subset of ILI ED visits, with mention of influenza or co-occurrence of fever with cough and/or sore throat, constituted only 11% of the broader fever and respiratory category (Figure 1 Discussion In our analysis of New York City ED data, we found that predominant increases in fever and respiratory visits corresponded in timing and magnitude with laboratory-confirmed influenza, and we suggest that our estimates of excess ED visits provide a reliable surrogate measure of the incident impact attributable to influenza. By applying standard statistical methods to electronic ED chief complaint data, and interpreting results in the context of available information about circulating viruses, we were able to evaluate and track age-specific influenza morbidity in greater detail than was previously possible in NYC. We found the burden of excess ED visits was greatest during peak influenza periods, disproportionately impacted children, often impacted children earliest, generally coincided in timing with P&I hospitalization admission data, and preceded P&I death data by roughly 1–2 wk. The age-specific pattern of excess ED visits varied depending on the predominant circulating viral type, subtype, and strain. We expand on these findings below. Reemergence of B/Victoria-Lineage Influenza, 2001–2002 Beginning the week ending February 16, 2002 (week 06–2002), a marked and sustained increase in ED fever and respiratory visits began in NYC that predominated among school-aged children (5–17 y). In the US, influenza B/Victoria-lineage viruses had last been widespread 13 y prior, during 1988–1989 in a mixed influenza B and A/H1N1 season, and had last been the predominant epidemic virus 16 y earlier, during the 1985–1986 season [23,31,32]. This pattern would suggest that in 2002, children age 13–16 y had minimal prior exposure, and children age 12 y and under had very little or no opportunity for prior exposure to this influenza B antigenic lineage, consistent with observed excess fever and respiratory (Figure 2 Epidemic A/H3N2 Fujian-Lineage Influenza Antigenic variant influenza A/H3N2 Fujian-lineage viruses emerged in autumn 2003 and were widespread across the US by the beginning of winter. The 2003–2004 seasonal influenza vaccine was reported to be poorly matched with the circulating A/Fujian viruses [5]. Our analysis of fever and respiratory ED visits indicated that the epidemic impact on morbidity was significant across all age groups, though greater among children (Figure 2 In autumn 2004, influenza viruses reported to be antigenically A/Fujian-like [5] reemerged and were epidemic in NYC. The pattern and age distribution of morbidity in 2004–2005 presented a distinct shift in impact compared to 2003–2004, in both ED fever and respiratory and ILI visits (Figures 2 Seasonal RSV While RSV surveillance data were not available during the study period, coded hospitalizations allowed us to retrospectively identify predominant RSV periods in NYC (Figure S2). The impact of RSV hospitalizations during the 2001–2002, 2002–2003, and 2005–2006 seasons occurred prior to the beginning of the influenza epidemic periods (Figure 5 Spring Tree Pollenosis In NYC we have consistently observed increases in ED respiratory and asthma visits outside of influenza season during the spring and early fall. The impact seen each spring is often severe enough to affect any syndrome that includes respiratory chief complaints, but is not associated with an increase in febrile illness. Pollen data obtained for the spring of 2005 and 2006 show that increases apparent in the broad fever and respiratory syndrome group among patients aged 5–64 y were coincident with the predominant annual tree pollen release (Figures 2 Influenza Timing In our analysis, we found that increases in influenza-attributable ED visits preceded hospitalizations, which in turn preceded deaths (corresponding to the logical progression of illness). During the 2003–2004 A/Fujian epidemic season we found fever and respiratory ED visits and P&I hospitalizations and deaths strongly correlated with viral isolate data, with an optimum lag between ED visits and deaths on the order of 2–3 wk (Figure 4 A study of Boston area ED surveillance data reported that ED respiratory visits increased first among preschool age children (aged 3–4 y), some 5–7 wk before ED visits among older persons [8]. This finding may have been be due to the impact of RSV, and to the use of aggregate interseasonal waves masking within-season variation by age. Analysis of the period from 2001 to 2006 using these methods on NYC ED visit data would show the age-specific impact of RSV shifting the overall timing of < 5 y ED visits earlier, while the spring influenza B/Victoria epidemic would shift 5–17 y ED visits later. Aggregate interseasonal time series analysis can be valid for seasonal influenza mortality, where a single wave of mortality predominates each season. Assessment of aggregated seasonal time series of ILI, fever, or respiratory morbidity data, where multiple etiologically distinct within-season waves are common, however, must be done with caution and at the appropriate scale [43]. Influenza Impact While the burden of influenza-attributable hospitalizations and deaths occurred predominantly among older adults, the burden of influenza-attributable excess fever and respiratory visits to NYC EDs during our study was predominantly among children (Figure 2 Our study had several limitations. First, estimating influenza-attributable morbidity and mortality is imperfect due to the nonspecific nature of influenza symptoms and the lack of laboratory confirmation for the vast majority of influenza cases [1]. We considered excess visits as primarily attributable to influenza when they occurred during periods of virally confirmed influenza circulation, but some of the fever and respiratory syndrome visits outside of these periods were likely due to influenza infection, and to some extent excess visits during influenza periods could clearly be due to coincidentally circulating viruses. Furthermore, the free-text chief complaints used to categorize ED visits into syndrome groups are imprecise indicators of illness, and many influenza-attributable visits may have been missed. We also did not explicitly consider the influence of ED utilization on age-specific visit rates. For example, parents may be more likely to bring a young child to the ED for an evaluation of influenza-like illness than to visit the ED themselves. A greater proportion of younger patients with acute influenza infection may have had fever with respiratory symptoms and been captured in our syndrome definition, while older patients with influenza-attributable illness and complications may have presented later and with a broader range of complaints, many of which might not have been captured by our syndrome coding. Finally, we had only 5 y of data covering a unique, large, and dense urban population, and our findings may not be generalizable to other years or to other regions. Within the context of these limitations, our results highlight the fact that each influenza season and epidemic period is unique in its age-specific timing, progression, and impact. The reliance of researchers on hospitalization and death data, and the difficulty of obtaining population-based and age-detailed estimates of morbidity have contributed to the misconception that influenza affects only the very young and the very old. While the burden of severe morbidity and mortality occurs at the extremes of age, our findings support the observation that school-aged children experience early and high attack rates and exhibit significant morbidity, supporting evidence that they play an important role in communitywide transmission [16–18]. Vaccination of school-aged children has been suggested to provide both direct protection for those vaccinated and indirect protection for unvaccinated age groups within the population during interpandemic [45] as well as pandemic periods [13]. The early and specific increases in fever and respiratory ED visits that we observed among children during the first season of A/H3N2 Fujian circulation are consistent with other studies showing that epidemic influenza strains may circulate and amplify first among children before spreading to older age groups [16–18]. These findings may have implications for targeted nonpharmaceutical intervention, antiviral, and vaccination strategies, and lend support for broadening the age categories recommended for routine and pandemic vaccination. Twentieth-century influenza can inform twenty-first-century surveillance. The experience with pandemic influenza in the last century in New York City illustrates that early waves, multiple waves, and within- and between-season age shifts in morbidity and mortality can occur [46–48]. While the timing and age-specific impact in the next pandemic cannot currently be predicted, experience during the last five seasons in New York City suggests that age-stratified ED surveillance can provide a timely surrogate measure of morbidity that can be used to monitor and describe the age-specific epidemiology of influenza. Recent analyses of the 1918 pandemic in US cities have shown that even transitory and imperfect public health intervention strategies, when initiated early enough, were partially beneficial [49,50]. While our study does not identify surveillance triggers for public health intervention or address control measure efficacy, our data do show that near-time monitoring is feasible. Our results highlight the fact that influenza epidemics can differ in timing, progression, and impact by age. The integration of detailed and rapid morbidity surveillance data, such as we have presented, with viral, antigenic, and whole-genome analysis [51–54], may improve our understanding of the complex dynamics of influenza [55], and provide better opportunity for informed and successful public health responses in the future. Figure S1: Weekly Age-Specific ILI Visits to the ED in New York City during the 2001–2002 to 2005–2006 Seasons Observed ILI syndrome ED visits by age group are shown as black lines, and seasonally expected Serfling baseline visits as red lines. Dashed lines represent epidemic thresholds as model estimates plus two-standard deviations. Shaded areas represent estimated influenza attributable excess ED visits: blue areas correspond to periods of increasing and dominant influenza A circulation and red areas to influenza B. Vertical lines indicate the first week of continuous influenza isolate reporting each season. (249 KB PDF) Click here for additional data file.(250K, pdf) Figure S2: Weekly Influenza Viral Isolate Surveillance and RSV Hospitalizations in New York City during the 2001–2002 to 2005–2006 Seasons Vertical lines indicate the first week of continuous influenza virus isolate reporting, viral isolate surveillance is indicated as in Figure 1 (172 KB PDF) Click here for additional data file.(173K, pdf) Table S1: Summary of Consecutive Weeks of Influenza Circulation Reporting, Epidemic Influenza Isolate Reporting, Epidemic Fever and Respiratory ED Visits, and Epidemic P&I Hospitalizations and Deaths in New York City during the 2001–2002 to 2005–2006 Seasons Influenza isolate circulation dates are the CDC weeks from the first influenza isolate reported in continuous weeks (vertical lines in Figures 1 (36 KB DOC) Click here for additional data file.(37K, doc) Acknowledgments We thank D. Das, T. Singh, and W. Li for assistance with NYC ED surveillance, hospitalization, and mortality data; and S. Harper, M. Layton, D. Morens, and C. Viboud for helpful comments on earlier drafts. We are indebted to A. Galvani, S. Morse, L. Simonsen, and A-J Valleron for critical comments and generously shared insights. Abbreviations
Footnotes Author contributions. DRO, RTH, and FM conceived of the study. DRO, RTH, DW, and FM designed the study. DRO, KK, and FM analyzed the data. All authors contributed to writing the paper. DRO, RTH, MP, and KK collected data or performed experiments for this study. DRO, RTH, MP, and KK participated in the rotation of analysts who clean, analyze, and report data daily. RTH oversaw the syndromic surveillance unit that collected the data. Funding: This work was supported by US Centers for Disease Control and Prevention Cooperative Agreement for Public Health Emergency Preparedness No. U90/CCU221298. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. References
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