% WEIGHTED ILI - National Summary
Why Use This Data Source In Your Models?
Percentage of visits for influenza like illness reported by sentinel providers Information on patient visits to health care providers for influenza-like illness is collected through the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). ILINet consists of approximately 3,200 outpatient healthcare providers in all 50 states, Puerto Rico, the District of Columbia and the U.S. Virgin Islands reporting over 36 million patient visits each year. Each week, approximately 2,000 outpatient healthcare providers around the country report data to CDC on the total number of patients seen and the number of those patients with influenza-like illness (ILI) by age group (0-4 years, 5-24 years, 25-49 years, 50-64 years, and ≥ 65 years). For this system, ILI is defined as fever (temperature of 100°F [37.8°C] or greater) and a cough and/or a sore throat in the absence of a known cause other than influenza. Sites with electronic records use an equivalent definition as determined by state public health authorities. The percentage of patient visits to healthcare providers for ILI reported each week is weighted on the basis of state population.
Seasonal Impact
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Automated Data Profiling
Suggested Treatment:
Grain Transformation:
Source:
National, Regional, and State Level Outpatient Illness and Viral Surveillance
Release:
Influenza Like Illness
Units:
Percentage
Frequency:
Week, Ending Saturday
Available Through:
05/18/2025
Suggested Treatment:
The data shows auto correlation and a non-normal distribution. The data should be differenced. While the Boxcox transformation, provides the best normality, the Order Norm variable will also perform well.
Grain Transformation:
Data is unable to be distributed by time or geography. The roll up method used is Weighted Average.
Auto Correlation Analysis:
Data shows auto correlation indicating a need for differencing
The ACF indicates 1 order differencing is appropriate.
Further differencing is reccommended
Trend Analysis:
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.04 p-value = 0.10 indicates that the data is stationary.
Distribution Analysis:
The Shapiro-Wilk test returned W = 0.80 with a p-value =0.00 indicating the data does not follow a normal distribution.
A skewness score of 2.47 indicates the data are substantially skewed.
Hartigan's dip test score of 0.01 with a p-value of 0.99 inidcates the data is unimodal
Statistics (Pearson P/ df, lower => more normal)
Auto Correlation Function
Auto Correlation Function After Differencing
Partial Auto Correlation Function
Seasonal and Trend Decompostion
Citation:
https://www.cdc.gov/flu/weekly/