Coordinating the real‐time use of global influenza activity data for better public health planning. Issue 2 (3rd December 2019)

• Record Type: Journal Article
• Authors: Biggerstaff, Matthew; Dahlgren, Fredrick Scott; Fitzner, Julia; George, Dylan; Hammond, Aspen; Hall, Ian; Haw, David; Imai, Natsuko; Johansson, Michael A.; Kramer, Sarah; McCaw, James M.; Moss, Robert; Pebody, Richard; Read, Jonathan M.; Reed, Carrie; Reich, Nicholas G.; Riley, Steven; Vandemaele, Katelijn; Viboud, Cecile; Wu, Joseph T.
• Is Part Of: Influenza and other respiratory viruses. Volume 14:Issue 2(2020)
• Page Start: 105
• Page End: 110
• Publication Date: 2019-12-03
• Subjects: forecasting -- incidence -- influenza; Influenza -- Periodicals; Respiratory infections -- Periodicals; Virus diseases -- Periodicals; Influenza, Human -- Periodicals; Respiratory Tract Diseases -- Periodicals; Virus Diseases -- Periodicals; Grippe -- Périodiques; Appareil respiratoire -- Infections -- Périodiques; Maladies à virus -- Périodiques; 616.203
• DOI: 10.1111/irv.12705
• Languages: English
• ISSNs: 1750-2640

Abstract

Abstract: Health planners from global to local levels must anticipate year‐to‐year and week‐to‐week variation in seasonal influenza activity when planning for and responding to epidemics to mitigate their impact. To help with this, countries routinely collect incidence of mild and severe respiratory illness and virologic data on circulating subtypes and use these data for situational awareness, burden of disease estimates and severity assessments. Advanced analytics and modelling are increasingly used to aid planning and response activities by describing key features of influenza activity for a given location and generating forecasts that can be translated to useful actions such as enhanced risk communications, and informing clinical supply chains. Here, we describe the formation of the Influenza Incidence Analytics Group (IIAG), a coordinated global effort to apply advanced analytics and modelling to public influenza data, both epidemiological and virologic, in real‐time and thus provide additional insights to countries who provide routine surveillance data to WHO. Our objectives are to systematically increase the value of data to health planners by applying advanced analytics and forecasting and for results to be immediately reproducible and deployable using an open repository of data and code. We expect the resources we develop and the associated community to provide an attractive option for the open analysis of key epidemiological data during seasonal epidemics and the early stages of an influenza pandemic.