title: Validation of statistical models for estimating hospitalization associated with influenza and other respiratory viruses.
abstract: BACKGROUND
  Reliable estimates of disease burden associated with respiratory viruses are keys to deployment of preventive strategies such as vaccination and resource allocation. Such estimates are particularly needed in tropical and subtropical regions where some methods commonly used in temperate regions are not applicable. While a number of alternative approaches to assess the influenza associated disease burden have been recently reported, none of these models have been validated with virologically confirmed data. Even fewer methods have been developed for other common respiratory viruses such as respiratory syncytial virus (RSV), parainfluenza and adenovirus.
  
  
  RESULTS
  We had recently conducted a prospective population-based study of virologically confirmed hospitalization for acute respiratory illnesses in persons <18 years residing in Hong Kong Island. Here we used this dataset to validate two commonly used models for estimation of influenza disease burden, namely the rate difference model and Poisson regression model, and also explored the applicability of these models to estimate the disease burden of other respiratory viruses. The Poisson regression models with different link functions all yielded estimates well correlated with the virologically confirmed influenza associated hospitalization, especially in children older than two years. The disease burden estimates for RSV, parainfluenza and adenovirus were less reliable with wide confidence intervals. The rate difference model was not applicable to RSV, parainfluenza and adenovirus and grossly underestimated the true burden of influenza associated hospitalization.
  
  
  CONCLUSIONS
  The Poisson regression model generally produced satisfactory estimates in calculating the disease burden of respiratory viruses in a subtropical region such as Hong Kong.
authors.affiliation: Department of Community Medicine, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Yang
authors.forename: Susan S
authors.initials: SS
authors.lastname: Chiu
authors.forename: King-Pan
authors.initials: KP
authors.lastname: Chan
authors.forename: Kwok-Hung
authors.initials: KH
authors.lastname: Chan
authors.forename: Wilfred Hing-Sang
authors.initials: WH
authors.lastname: Wong
authors.forename: J S Malik
authors.initials: JS
authors.lastname: Peiris
authors.forename: Chit-Ming
authors.initials: CM
authors.lastname: Wong
mesh_terms: D000256:Adenoviridae / Q000502:physiology; D006723:Hong Kong / Q000453:epidemiology; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D009975:Orthomyxoviridae / Q000502:physiology*; D016012:Poisson Distribution; D012044:Regression Analysis; D015203:Reproducibility of Results; D012136:Respiratory Syncytial Viruses / Q000502:physiology; D012141:Respiratory Tract Infections / Q000453:epidemiology* / Q000821:virology*; D018108:Respirovirus / Q000502:physiology