Short-term Forecasting of Severe Outcomes for Seasonal and Epidemic Pathogens

Overview

Development stage

DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Not reported

Start date

2023-10 (month precision)Source: Oct-23

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Emergency Management

Operational functions

Forecasting and prediction Derived by keyword rules; see methodology

Problem the AI is intended to solve

Predict severe disease outcomes - such as emergency department visits or hospital admissions - over short time horizons (1-4 weeks) to improve situational awareness for planning and decision-making at the national, state, and local level. Traditional AI/ML models (e.g. time series models) are mainly used as baselines against which to test and improve more sophisticated modeling methods.

Expected benefits

Providing timely, accurate, and actionable forward-looking information on severe disease outcomes to government officials and the public.

System outputs

Current outputs include weekly state and national hospital admissions forecasts for COVID-19 and influenza (public-facing) and weekly state and national ED visit forecasts for COVID-19 and influenza (internal to CDC at this time).

Technology

AI classification

Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…

System name(s)

EDAV (Enterprise Data Analytics and Visualization Platform)

Custom-developed code

Yes

Public source code

github.com ↗

Sourcing

How it was built

Contract and in-houseSource: c) Developed with both contracting and in-house resources

Vendor (as reported)

Not reported

Vendors (standardized)

None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

No

Privacy Impact Assessment

Not reported

Authorization to Operate

Yes

Demographic features

k) None of the above

Training and evaluation data

Internal and publicly available hospital admissions data collected through the National Hospital Safety Network (NSHN), internal and publicly available emergency department visit data collected through the National Syndromic Surveillance Program (NSSP), internal wastewater concentration data collected through the National Wastewater Surveillance System (NWSS)

Federal Data Catalog

Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported