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标题：Detection of Excess Influenza Severity: Associating Respiratory Hospitalization and Mortality Data With Reports of Influenza-Like Illness by Primary Care Physicians
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作者：Cees C. van den Wijngaard ; Liselotte van Asten ; Adam Meijer 等
期刊名称：American journal of public health
印刷版ISSN：0090-0036
出版年度：2010
卷号：100
期号：11
页码：2248-2254
DOI：10.2105/AJPH.2009.168245
语种：English
出版社：American Public Health Association
摘要：Objectives. We explored whether excesses in influenza severity can be detected by combining respiratory syndromic hospital and mortality data with data on influenza-like illness (ILI) cases obtained from general practitioners. Methods. To identify excesses in the severity of influenza infections in the population of the Netherlands between 1999 and 2005, we looked for increases in influenza-associated hospitalizations and mortality that were disproportionate to the number of ILI cases reported by general practitioners. We used generalized estimating equation regression models to associate syndromic hospital and mortality data with ILI surveillance data obtained from general practitioners. Virus isolation and antigenic characterization data were used to interpret the results. Results. Disproportionate increases in hospitalizations and mortality (relative to ILI cases reported by general practitioners) were identified in 2003/04 during the A/Fujian/411/02(H3N2) drift variant epidemic. Conclusions. Combined surveillance of respiratory hospitalizations and mortality and ILI data obtained from general practitioners can capture increases in severe influenza-associated illness that are disproportionate to influenza incidence rates. Therefore, this novel approach should complement traditional seasonal and pandemic influenza surveillance in efforts to detect increases in influenza case fatality rates and percentages of patients hospitalized. Syndromic surveillance is increasingly used to monitor symptoms or clinical diagnoses such as shortness of breath or pneumonia as indicators of infectious disease. The primary objective of many syndromic surveillance systems is the detection of unexpected disease increases such as those that occur as a result of bioterrorism attacks or outbreaks of emerging diseases such as severe acute respiratory syndrome (SARS). However, the signals generated by such syndromic surveillance also reflect influenza activity.^{1 – 4} Worldwide, influenza continues to result in serious morbidity and mortality.^{5 , 6} The recurrence of influenza epidemics is predominantly caused by both the antigenic drift of influenza viruses and changes in the dominant virus types or subtypes. Antigenic drift occurs during the replication process of influenza viruses when mutations in surface proteins lead to declines in the level of immunity acquired through natural infection or vaccination.⁷ In addition, the annual variations in dominant virus types or subtypes, such as A(H1), A(H3), and B, can lead to differences in influenza-related morbidity and mortality. For example, in recent decades levels of morbidity and mortality seem to have been lower in the influenza A(H1) and B epidemic seasons than in the A(H3) seasons.^{8 , 9} In the Netherlands, as in many countries, surveillance of influenza is conducted by a network of sentinel general practitioners. Influenza-like illness (ILI) consultations are reported weekly, and antigenic properties of isolated viruses are analyzed to determine their effects on annual ILI fluctuations.^{10 , 11} Such sentinel surveillance is considered adequate for monitoring the onset and magnitude of annual influenza epidemics. However, it is not sufficient for monitoring the incidence of severe influenza infections leading to hospitalization or death. Although the relationship between the virulence and transmission capacity of influenza viruses is still incompletely understood,⁷ variations in virulence may result in disproportionate increases in severe illness relative to increases in the number of patients with ILI consulting their general practitioners. Such increases might be captured by monitoring temporal changes in the association of ILI data obtained from general practitioners (hereafter GP–ILI data) with hospitalization and mortality surveillance data. Such monitoring is not a part of current global influenza monitoring activities, although in some countries ILI data in addition to hospitalization and mortality data are included in influenza surveillance.^{12 , 13} We explored the potential of this monitoring strategy to detect excesses in influenza infection severity by investigating shifts in the annual association of respiratory hospitalizations and mortality with GP–ILI incidence data in the Netherlands between 1999 and 2005. In addition, we evaluated whether such shifts were associated with reported circulation of influenza virus drift variants, mismatches with vaccine strains, or changes in dominant circulating virus types or subtypes.