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bioRxiv · 10.1101/411348

Influenza incidence prediction for the United States: an update for the 2018-2019 season

Du, X.·Peng, Y.·Liu, M.·Pascual, M.
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Abstract

IntroductionSeasonal influenza causes a high disease burden every year in the United States and worldwide. Anticipating epidemic size ahead of season can contribute to preparedness and more targetted control and prevention of seasonal influenza.\n\nMethodsA recently developed process-based epidemiological model that incorporates evolutionary change of the virus and generates incidence forecasts for the H3N2 subtype ahead of the season, was previously validated by several statistical criteria, including an accurate real-time prediction for the 2016-2017 influenza season. With this model, a new forecast is generated here for the upcoming 2018-2019 season. The accuracy of predictions published for the 2017-2018 season is also retrospectively evaluated.\n\nResultsFor 2017-2018, the model correctly predicted the dominance of the H3N2 subtype and its higher than average incidence. Based on surveillance and sequence data up to June 2018, the new forecast for the upcoming 2018-2019 season indicates low levels for H3N2, and suggests an H1N1 dominant season with low incidence of influenza B.\n\nDiscussionReal-time forecasts, those generated with a model that was parameterized based on data preceding the predicted season, allows valuable evaluation of the approach. Anticipating the dominant subtype and the size of the upcoming epidemic ahead of season informs disease control. Further studies are needed to promote more accurate ahead-of-season forecasts and extend the approach to multiple subtypes.

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Du, X., Peng, Y., Liu, M., Pascual, M.. 2018-09-07. Influenza incidence prediction for the United States: an update for the 2018-2019 season. https://doi.org/10.1101/411348

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