Tracking and predicting U.S. influenza activity with a real-time surveillance network.

Sequoia I Leuba,Christoph Zimmer,Reza Yaesoubi,Marina Antillon,Ted Cohen

doi:10.1371/journal.pcbi.1008180

Abstract

Each year in the United States, influenza causes illness in 9.2 to 35.6 million individuals and is responsible for 12,000 to 56,000 deaths. The U.S. Centers for Disease Control and Prevention (CDC) tracks influenza activity through a national surveillance network. These data are only available after a delay of 1 to 2 weeks, and thus influenza epidemiologists and transmission modelers have explored the use of other data sources to produce more timely estimates and predictions of influenza activity. We evaluated whether data collected from a national commercial network of influenza diagnostic machines could produce valid estimates of the current burden and help to predict influenza trends in the United States. Quidel Corporation provided us with de-identified influenza test results transmitted in real-time from a national network of influenza test machines called the Influenza Test System (ITS). We used this ITS dataset to estimate and predict influenza-like illness (ILI) activity in the United States over the 2015-2016 and 2016-2017 influenza seasons. First, we developed linear logistic models on national and regional geographic scales that accurately estimated two CDC influenza metrics: the proportion of influenza test results that are positive and the proportion of physician visits that are ILI-related. We then used our estimated ILI-related proportion of physician visits in transmission models to produce improved predictions of influenza trends in the United States at both the regional and national scale. These findings suggest that ITS can be leveraged to improve “nowcasts” and short-term forecasts of U.S. influenza activity.

Highlights

The U.S Centers for Disease Control and Prevention (CDC) estimates that influenza is responsible annually for 9.2 to 35.6 million illnesses and 12,000 to 56,000 deaths in the United States [1]
The CDC influenza surveillance data are subject to a 1 to 2 week reporting delay, which limits how such information can be used to assess the current burden of disease and to make timely projections of the trajectory of the epidemic
We developed a volume metric to compare the number of tests recorded in the Influenza Test System (ITS) network to the number of tests reported by the CDC influenza surveillance system

Summary

Introduction

The U.S Centers for Disease Control and Prevention (CDC) estimates that influenza is responsible annually for 9.2 to 35.6 million illnesses and 12,000 to 56,000 deaths in the United States [1]. The CDC tracks influenza activity through several sources of data which contribute to a national surveillance network consisting of the World Health Organization Collaborating Laboratories System and the National Respiratory and Enteric Virus Surveillance System (WHO/ NREVSS) [2]. These systems collect weekly records of the numbers and results of diagnostic tests for influenza from approximately 100 public health laboratories and 300 additional clinical laboratories [2]. This surveillance network provides weekly estimates of the number of influenza tests ordered, the number of these tests that confirm influenza infection, the number of physician visits, and the number of these physician visits that are related to an ILI [2]

Methods

Results

Discussion

Conclusion