Predictors of Severity of Influenza-Related Hospitalizations: Results From the Global Influenza Hospital Surveillance Network (GIHSN)

Lily E. Cohen; Chelsea L. Hansen; Melissa K. Andrew; Shelly A. McNeil; Philippe Vanhems; Jan Kyncl; Javier Díez Domingo; Tao Zhang; Ghassan Dbaibo; Victor Alberto Laguna-Torres; Anca Draganescu; Elsa Baumeister; Doris Gomez; Sonia M. Raboni; Heloisa I.G. Giamberardino; Marta C. Nunes; Elena Burtseva; Anna Sominina; Snežana Medić; Daouda Coulibaly; Afif Ben Salah; Nancy A. Otieno; Parvaiz A. Koul; Serhat Unal; Mine Durusu Tanriover; Marie Mazur; Joseph Bresee; Cecile Viboud; Sandra S. Chaves

doi:10.1093/infdis/jiad303

Predictors of Severity of Influenza-Related Hospitalizations: Results From the Global Influenza Hospital Surveillance Network (GIHSN)

Lily E. Cohen^*, Chelsea L. Hansen, Melissa K. Andrew, Shelly A. McNeil, Philippe Vanhems, Jan Kyncl, Javier Díez Domingo, Tao Zhang, Ghassan Dbaibo, Victor Alberto Laguna-Torres, Anca Draganescu, Elsa Baumeister, Doris Gomez, Sonia M. Raboni, Heloisa I.G. Giamberardino, Marta C. Nunes, Elena Burtseva, Anna Sominina, Snežana Medić, Daouda CoulibalyAfif Ben Salah, Nancy A. Otieno, Parvaiz A. Koul, Serhat Unal, Mine Durusu Tanriover, Marie Mazur, Joseph Bresee, Cecile Viboud, Sandra S. Chaves^*

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › Research › peer-review

Abstract

Background.

The Global Influenza Hospital Surveillance Network (GIHSN) has since 2012 provided patient-level data on severe influenza-like-illnesses from >100 participating clinical sites worldwide based on a core protocol and consistent case definitions.

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 level.

Results.

The data set included 73 121 patients hospitalized with respiratory illness in 22 countries, including 15 660 with laboratory-confirmed 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 (LMICs), compared with high-income countries (P = .01). The risk of mechanical ventilation and in-hospital death also increased by 4-fold in LMICs, though these differences were not statistically significant. We also find that influenza mortality increased significantly with older age and number of comorbid conditions. Across all severity outcomes studied and after controlling for patient characteristics, infection with influenza A/H1N1pdm09 was more severe than with A/H3N2.

Conclusions.

Our study provides new information on influenza severity in underresourced populations, particularly those in LMICs.

Original language	English
Journal	Journal of Infectious Diseases
Volume	229
Issue number	4
Pages (from-to)	999-1009
Number of pages	11
ISSN	0022-1899
DOIs	https://doi.org/10.1093/infdis/jiad303
Publication status	Published - 15 Apr 2024

Bibliographical note

Funding Information:
Financial support. This work was supported by the Foundation for Influenza Epidemiology (France; support to the Global Influenza Hospital Surveillance Network [GIHSN]) and by Ready2Respond (funding for data analysis under Wellcome Trust grant 224690/Z/21/Z).

Keywords

disease severity
global health
influenza epidemiology
lower middle-income countries
surveillance

Link to document

10.1093/infdis/jiad303

Cite this

Cohen, L. E., Hansen, C. L., Andrew, M. K., McNeil, S. A., Vanhems, P., Kyncl, J., Domingo, J. D., Zhang, T., Dbaibo, G., Laguna-Torres, V. A., Draganescu, A., Baumeister, E., Gomez, D., Raboni, S. M., Giamberardino, H. I. G., Nunes, M. C., Burtseva, E., Sominina, A., Medić, S., ... Chaves, S. S. (2024). Predictors of Severity of Influenza-Related Hospitalizations: Results From the Global Influenza Hospital Surveillance Network (GIHSN). Journal of Infectious Diseases, 229(4), 999-1009. https://doi.org/10.1093/infdis/jiad303

@article{4800b44eba4e4f3aa7b4b1479f167fa2,

title = "Predictors of Severity of Influenza-Related Hospitalizations: Results From the Global Influenza Hospital Surveillance Network (GIHSN)",

abstract = "Background. The Global Influenza Hospital Surveillance Network (GIHSN) has since 2012 provided patient-level data on severe influenza-like-illnesses from >100 participating clinical sites worldwide based on a core protocol and consistent case definitions. 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 level. Results. The data set included 73 121 patients hospitalized with respiratory illness in 22 countries, including 15 660 with laboratory-confirmed 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 (LMICs), compared with high-income countries (P = .01). The risk of mechanical ventilation and in-hospital death also increased by 4-fold in LMICs, though these differences were not statistically significant. We also find that influenza mortality increased significantly with older age and number of comorbid conditions. Across all severity outcomes studied and after controlling for patient characteristics, infection with influenza A/H1N1pdm09 was more severe than with A/H3N2. Conclusions. Our study provides new information on influenza severity in underresourced populations, particularly those in LMICs.",

keywords = "disease severity, global health, influenza epidemiology, lower middle-income countries, surveillance, disease severity, global health, influenza epidemiology, lower middle-income countries, surveillance",

author = "Cohen, {Lily E.} and Hansen, {Chelsea L.} and Andrew, {Melissa K.} and McNeil, {Shelly A.} and Philippe Vanhems and Jan Kyncl and Domingo, {Javier D{\'i}ez} and Tao Zhang and Ghassan Dbaibo and Laguna-Torres, {Victor Alberto} and Anca Draganescu and Elsa Baumeister and Doris Gomez and Raboni, {Sonia M.} and Giamberardino, {Heloisa I.G.} and Nunes, {Marta C.} and Elena Burtseva and Anna Sominina and Sne{\v z}ana Medi{\'c} and Daouda Coulibaly and Salah, {Afif Ben} and Otieno, {Nancy A.} and Koul, {Parvaiz A.} and Serhat Unal and Tanriover, {Mine Durusu} and Marie Mazur and Joseph Bresee and Cecile Viboud and Chaves, {Sandra S.}",

note = "Funding Information: Financial support. This work was supported by the Foundation for Influenza Epidemiology (France; support to the Global Influenza Hospital Surveillance Network [GIHSN]) and by Ready2Respond (funding for data analysis under Wellcome Trust grant 224690/Z/21/Z).",

year = "2024",

month = apr,

day = "15",

doi = "10.1093/infdis/jiad303",

language = "English",

volume = "229",

pages = "999--1009",

journal = "Journal of Infectious Diseases",

issn = "0022-1899",

publisher = "Oxford University Press",

number = "4",

}

Cohen, LE, Hansen, CL, Andrew, MK, McNeil, SA, Vanhems, P, Kyncl, J, Domingo, JD, Zhang, T, Dbaibo, G, Laguna-Torres, VA, Draganescu, A, Baumeister, E, Gomez, D, Raboni, SM, Giamberardino, HIG, Nunes, MC, Burtseva, E, Sominina, A, Medić, S, Coulibaly, D, Salah, AB, Otieno, NA, Koul, PA, Unal, S, Tanriover, MD, Mazur, M, Bresee, J, Viboud, C & Chaves, SS 2024, 'Predictors of Severity of Influenza-Related Hospitalizations: Results From the Global Influenza Hospital Surveillance Network (GIHSN)', Journal of Infectious Diseases, vol. 229, no. 4, pp. 999-1009. https://doi.org/10.1093/infdis/jiad303

TY - JOUR

T1 - Predictors of Severity of Influenza-Related Hospitalizations

T2 - Results From the Global Influenza Hospital Surveillance Network (GIHSN)

AU - Cohen, Lily E.

AU - Hansen, Chelsea L.

AU - Andrew, Melissa K.

AU - McNeil, Shelly A.

AU - Vanhems, Philippe

AU - Kyncl, Jan

AU - Domingo, Javier Díez

AU - Zhang, Tao

AU - Dbaibo, Ghassan

AU - Laguna-Torres, Victor Alberto

AU - Draganescu, Anca

AU - Baumeister, Elsa

AU - Gomez, Doris

AU - Raboni, Sonia M.

AU - Giamberardino, Heloisa I.G.

AU - Nunes, Marta C.

AU - Burtseva, Elena

AU - Sominina, Anna

AU - Medić, Snežana

AU - Coulibaly, Daouda

AU - Salah, Afif Ben

AU - Otieno, Nancy A.

AU - Koul, Parvaiz A.

AU - Unal, Serhat

AU - Tanriover, Mine Durusu

AU - Mazur, Marie

AU - Bresee, Joseph

AU - Viboud, Cecile

AU - Chaves, Sandra S.

N1 - Funding Information: Financial support. This work was supported by the Foundation for Influenza Epidemiology (France; support to the Global Influenza Hospital Surveillance Network [GIHSN]) and by Ready2Respond (funding for data analysis under Wellcome Trust grant 224690/Z/21/Z).

PY - 2024/4/15

Y1 - 2024/4/15

N2 - Background. The Global Influenza Hospital Surveillance Network (GIHSN) has since 2012 provided patient-level data on severe influenza-like-illnesses from >100 participating clinical sites worldwide based on a core protocol and consistent case definitions. 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 level. Results. The data set included 73 121 patients hospitalized with respiratory illness in 22 countries, including 15 660 with laboratory-confirmed 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 (LMICs), compared with high-income countries (P = .01). The risk of mechanical ventilation and in-hospital death also increased by 4-fold in LMICs, though these differences were not statistically significant. We also find that influenza mortality increased significantly with older age and number of comorbid conditions. Across all severity outcomes studied and after controlling for patient characteristics, infection with influenza A/H1N1pdm09 was more severe than with A/H3N2. Conclusions. Our study provides new information on influenza severity in underresourced populations, particularly those in LMICs.

AB - Background. The Global Influenza Hospital Surveillance Network (GIHSN) has since 2012 provided patient-level data on severe influenza-like-illnesses from >100 participating clinical sites worldwide based on a core protocol and consistent case definitions. 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 level. Results. The data set included 73 121 patients hospitalized with respiratory illness in 22 countries, including 15 660 with laboratory-confirmed 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 (LMICs), compared with high-income countries (P = .01). The risk of mechanical ventilation and in-hospital death also increased by 4-fold in LMICs, though these differences were not statistically significant. We also find that influenza mortality increased significantly with older age and number of comorbid conditions. Across all severity outcomes studied and after controlling for patient characteristics, infection with influenza A/H1N1pdm09 was more severe than with A/H3N2. Conclusions. Our study provides new information on influenza severity in underresourced populations, particularly those in LMICs.

KW - disease severity

KW - global health

KW - influenza epidemiology

KW - lower middle-income countries

KW - surveillance

KW - disease severity

KW - global health

KW - influenza epidemiology

KW - lower middle-income countries

KW - surveillance

U2 - 10.1093/infdis/jiad303

DO - 10.1093/infdis/jiad303

M3 - Journal article

C2 - 37527470

AN - SCOPUS:85185448470

SN - 0022-1899

VL - 229

SP - 999

EP - 1009

JO - Journal of Infectious Diseases

JF - Journal of Infectious Diseases

IS - 4

ER -