The Global Influenza Hospital Surveillance Network: A Multicountry Public Health Collaboration

• Published in: Influenza and other respiratory viruses Vol. 19; no. 3; pp. e70091 - n/a
• Main Authors: Nunes, Marta C., Chauvel, Cecile, Raboni, Sonia M., López‐Labrador, F. Xavier, Andrew, Melissa K., Badar, Nazish, Baillie, Vicky, Bal, Antonin, Baral, Kedar, Baumeister, Elsa, Boutros, Celina, Burtseva, Elena, Coulibaly, Daouda, Cowling, Ben, Danilenko, Daria, Dbaibo, Ghassan, Destras, Gregory, Dia, Ndongo, Drăgănescu, Anca Cristina, Giamberardino, Heloisa I. G., Gomez‐Camargo, Doris, Josset, Laurence, Koul, Parvaiz A., Kyncl, Jan, Laguna‐Torres, Victor Alberto, Launay, Odile, Nugyen, Liem Binh Luong, McNeil, Shelly, Medić, Snežana, Mira‐Iglesias, Ainara, Mironenko, Alla, Nitsch‐Osuch, Aneta, Orrico‐Sánchez, Alejandro, Otieno, Nancy A., Regue, Hadrien, Ruiz‐Palacios, Guillermo M., Salah, Afif Ben, Salman, Muhammad, Săndulescu, Oana, Simon, Viviana, Sominina, Anna, Sordillo, Emilia, Tanriover, Mine Durusu, Unal, Serhat, Bakel, Harm, Vanhems, Philippe, Zhang, Tao, Commaille‐Chapus, Catherine, Hunsinger, Camille, Bresee, Joseph, Lina, Bruno, McCauley, John W., Ortiz, Justin R., Viboud, Cecile, Zhang, Wenqing, Torcel‐Pagnon, Laurence, Mahe, Cedric, Chaves, Sandra S.
• Format: Journal Article
• Language: English
• Published: England John Wiley & Sons, Inc 01.03.2025; Wiley Open Access
• Subjects: Clinical outcomes; Collaboration; COVID-19; COVID-19 - epidemiology; COVID-19 vaccines; Data collection; Data entry; Disease; DNA sequencing; Epidemics; Epidemiological Monitoring; Epidemiology; Gene sequencing; Genomes; Genomics; Global Health; Health promotion; Health risks; Hospital patients; Hospitalization; Hospitals; Humans; Influenza; Influenza, Human - epidemiology; Influenza, Human - virology; international; Life Sciences; Medical colleges; Medical research; Nucleotide sequencing; Pandemics; Partnerships; Patients; Public Health; Public Health Surveillance; Public private partnerships; Public-Private Sector Partnerships; Respiratory diseases; respiratory viruses; Seasons; Severe acute respiratory syndrome coronavirus 2; Surveillance; Viruses; Whole genome sequencing; World health; Northern Hemisphere; Kenya; Kyiv Ukraine; Ukraine; Russia; influenza; public–private partnerships; surveillance; international; respiratory viruses; public-private partnerships
• ISSN: 1750-2640; 1750-2659; 1750-2659
• DOI: 10.1111/irv.70091

ABSTRACT Respiratory viruses represent a significant public health threat. There is the need for robust and coordinated surveillance to guide global health responses. Established in 2012, the Global Influenza Hospital Surveillance Network (GIHSN) addresses this need by collecting clinical and virological data on persons with acute respiratory illnesses across a network of hospitals worldwide. GIHSN utilizes a standardized patient enrolment and data collection protocol across its study sites. It leverages pre‐existing national infrastructures and expert collaborations to facilitate comprehensive data collection. This includes demographic, clinical, epidemiological, and virologic data, and whole genome sequencing (WGS) for a subset of viruses. Sequencing data are shared in the Global Initiative on Sharing All Influenza Data (GISAID). GIHSN uses financing and governance approaches centered around public–private partnerships. Over time, GIHSN has included more than 100 hospitals across 27 countries and enrolled more than 168,000 hospitalized patients, identifying 27,562 cases of influenza and 44,629 of other respiratory viruses. GIHSN has expanded beyond influenza to include other respiratory viruses, particularly since the COVID‐19 pandemic. In November 2023, GIHSN strengthened its global impact through a memorandum of understanding with the World Health Organization, aimed at enhancing collaborative efforts and data sharing for improved health responses. GIHSN exemplifies the value of integrating scientific research with public health initiatives through global collaboration and public–private partnerships governance. Future efforts should enhance the scalability of such models and ensure their sustainability through continued public and private support.