Epidemic Model Predictions | hsye

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Closing the Loop by Operationalizing Systems Engineering and Design (CLOSED)

Motivation:

Specific Aims :

Aim 1:Use systems engineering and patient engagement to design, develop, and refine a highly reliable “closed loop” system for diagnostic tests and referrals that ensures diagnostic orders and follow-up occur reliably within clinically- and patient-important time-frames.

Aim 2: Use systems engineering and patient engagement to design, develop, and refine a highly reliable “closed loop” system for symptoms that ensures clinicians receive and act on feedback about evolving symptoms and physical findings of concern to patients or clinicians.

Aim 3: Design for generalizability across health systems more broadly so that the processes created in Aims 1 and 2 are effective in (1) a practice in an underserved community, (2) a large tele-medicine system, and (3) a representative range of simulated other health system settings and populations.

Partners:

Sunday, June 2, 2019

Sunday, June 2, 2019

Approach:

Sunday, June 2, 2019

Results to Date:

THEORY INTO PRACTICE

COVID-19 Modeling & Analytics Tools

Surge Capacity

Tools

Epidemic Model Predictions

Statistical

Monitoring

General Tool

Overview

Epidemic Models by Geographic Location

Overview/Interpretation

Dots: New and cumulative COVID infections and mortality

Lines: 14-day ahead predictions (color coded)

Signals: Data consistently above (below) lines indicate increases (decreases)

Methodology

Fits optimized epidemic growth curves on rolling daily basis

Computes 14-day ahead expected value (and intervals, not shown)

Flags data outside statistical intervals

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Click here for additional countries and regions
Click here for countries and regions with recent significant changes in infection or death counts

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