Predictors of severity of influenza-related hospitalizations: Results from the Global Influenza Hospital Surveillance Network (GIHSN)

Background

The Global Influenza Hospital Surveillance Network (GIHSN) has since 2012 provided patient-level data on severe influenza-like illnesses from over 100 participating clinical sites worldwide based on a core protocol and consistent case definitions. To our knowledge, this is the first study to analyze multiple years of global, patient-level data generated by prospective, hospital-based surveillance across a large number of countries to investigate geographic differences in influenza severity.

Methods

We used multivariable logistic regression to assess the risk of intensive care unit admission, mechanical ventilation, and in-hospital death among hospitalized patients with influenza and explored the role of patient-level covariates and country income. Results: The dataset included 73,121 patients hospitalized with respiratory illness in 22 countries, with 15,660 laboratory-confirmed for influenza. After adjusting for patient-level covariates we found a 7-fold increase in the risk of influenza-related intensive care unit admission in lower-middle-income countries, compared to high-income countries (p = 0.01). The risk of mechanical ventilation and in-hospital death also increases four-fold in lower-middle-income countries, though these values were not statistically significant. We also find that influenza severity increased with older age and the number of comorbidities. Across all severity outcomes studied and after controlling for patient characteristics, infection with influenza A/H1N1pdm09 was more severe than with A/H3N2.

Conclusion

Our study provides new information on influenza severity in under-resourced populations, particularly those in lower-middle-income countries. Understanding the mechanisms responsible for these disparities will be important to improve the management of influenza, optimize vaccine allocation, and mitigate the global disease burden.

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