PROGNOSTIC MODEL OF MORTALITY FOLLOWING HUMAN INFLUENZA (A) H5N1 INFECTION

Purpose:  Human Influenza A (H5N1) infection is increasing in global prevalence, with a 58% case-fatality in 621 laboratory-confirmed human cases.  The virus has primarily spread from animals to humans; however, recent success in creating laboratory-engineered strains that can spread via aerosol has raised concerns for a severe pandemic.  We sought to analyze published human A (H5N1) case data to design a prognostic model of factors that may increase the risk of mortality following infection.

Method:  We performed a systematic review of the biomedical literature from PubMed and Scopus between December 1997 – May 2012 to identify laboratory-confirmed human Influenza A (H5N1) cases or suspected cases in a case cluster; all non-human cases were excluded.  This data was cross-referenced with confirmed cases published from 15 separate countries on the World Health Organization (WHO) Global Alert Response website. Predictor variables were country, year, per capita health expenditure (PCHE), gender, age, contact with poultry, contact with sick poultry, delay between symptom onset and hospitalization (days), and average humidity.  PCHE was obtained from the WHO Global Health Observatory Data Repository for each country, stratified by year.  Age was discretized into five clinically relevant categories to allow for nonlinearity.  Prognostic models were developed using multivariate logistic regression, and model validation was performed using bootstrapping.

Result:  To date, 484 laboratory-confirmed cases have been identified for which clinical, demographic, and outcome characteristic were included in model building and analysis.  The mortality was 60%, with significant variation in between-country mortality.  Significant risk factors include lower PCHE, age, and longer delay between symptom onset and hospitalization.  Mortality is highest in early adulthood; a similar pattern was seen in the 1918 and 2009 influenza pandemics. The final model included all predictors except the two poultry contact variables (due to missing data) and had a concordance statistic of 0.84.

Conclusion: Age, gender, PCHE, and delay between symptom onset and hospitalization are strong predictors of mortality following human infection with Influenza A (H5N1). These findings may assist policymakers in distributing prophylactic resources and devising triage guidelines for this devastating illness.