HHS · no agency ID · record R0688

Nowcasting Burden and Infection Trends for Seasonal and Epidemic Pathogens

Department of Health and Human Services · HHS/CDC

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: 2023-11 (month precision)Source: Nov-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

Improve real-time estimates of disease burden and infection trends for better 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 information on current and near-future disease risk and effort required for control to government officials and the public.

System outputs

Current outputs include weekly state-level estimates of the time-varying reproductive number (Rt) – a measure of epidemic trajectory and indicator of the level of effort needed to bring an epidemic under control – for COVID-19 and influenza (public-facing) and RSV (internal to CDC at this time), and weekly nowcasts of hospital admissions within the Respiratory Virus Hospitalization Surveillance Network (RESP-NET; 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: a) Race/Ethnicity; b) Sex; c) Age
Training and evaluation data: Internal and publicly available hospital admissions data collected through the Respiratory Virus Hospitalization Surveillance Network (RESP-NET), internal and publicly available emergency department visit data collected through the National Syndromic Surveillance Program (NSSP)
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.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported