Policy Impact Analysis - 117/S/3534

Bill Overview

Title: Tracking Pathogens Act

Description: This bill requires the Centers for Disease Control and Prevention (CDC) to take specified actions related to the genomic sequencing of pathogens. Specifically, the CDC must issue guidance on sharing specimens and other activities to support collaboration in the genomic sequencing of pathogens. The CDC must also strengthen and expand activities related to the use of genomic sequencing of pathogens in public health surveillance, including by providing technical assistance to health departments. The CDC may award grants, contracts, or cooperative agreements to academic and other laboratories related to these activities. In addition, the CDC must establish through public health agencies (or partnerships of such agencies) centers of excellence to promote innovation in pathogen genomics and molecular epidemiology.

Sponsors: Sen. Baldwin, Tammy [D-WI]

Target Audience

Population: People globally at risk of infectious diseases

Estimated Size: 332000000

Reasoning

Simulated Interviews

Epidemiologist (Atlanta, GA)

Age: 45 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 20.0 years

Commonness: 5/20

Statement of Opinion:

  • Improved genomic sequencing will make our work more efficient and effective.
  • Collaboration through centers of excellence will foster innovation and data sharing.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 7 6
Year 3 8 6
Year 5 8 5
Year 10 9 5
Year 20 9 5

University Researcher (New York, NY)

Age: 32 | Gender: male

Wellbeing Before Policy: 5

Duration of Impact: 15.0 years

Commonness: 7/20

Statement of Opinion:

  • The policy would provide more funding opportunities for groundbreaking research.
  • Access to shared genomic data will accelerate the pace of discovery.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 5
Year 2 7 5
Year 3 7 5
Year 5 8 5
Year 10 9 5
Year 20 9 5

Public Health Official (Houston, TX)

Age: 37 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 10.0 years

Commonness: 6/20

Statement of Opinion:

  • Access to detailed genomic data will improve outbreak response strategies.
  • Training from CDC's technical assistance proves invaluable.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 6
Year 2 7 6
Year 3 7 6
Year 5 7 5
Year 10 8 5
Year 20 8 5

Software Developer (San Francisco, CA)

Age: 52 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 5.0 years

Commonness: 10/20

Statement of Opinion:

  • I may enhance my existing systems with pathogen tracking features influenced by this policy.
  • Hope it leads to faster data sharing between institutions.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 7 7
Year 3 7 7
Year 5 7 7
Year 10 8 7
Year 20 8 7

Microbiologist (Los Angeles, CA)

Age: 28 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 15.0 years

Commonness: 8/20

Statement of Opinion:

  • Stronger networks among labs will boost our research capabilities.
  • Looking forward to potential grants for advanced equipment.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 5
Year 2 6 5
Year 3 7 5
Year 5 8 5
Year 10 9 5
Year 20 9 5

Public School Teacher (Chicago, IL)

Age: 40 | Gender: other

Wellbeing Before Policy: 6

Duration of Impact: 8.0 years

Commonness: 15/20

Statement of Opinion:

  • Increased genomic awareness could enhance my lessons.
  • I hope it brings more public health education to schools.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 6
Year 2 6 6
Year 3 6 6
Year 5 7 6
Year 10 8 6
Year 20 8 6

Retired (Miami, FL)

Age: 55 | Gender: male

Wellbeing Before Policy: 8

Duration of Impact: 0.0 years

Commonness: 20/20

Statement of Opinion:

  • The policy sounds like it will improve disease management nationally.
  • I worry about the long-term cost implications.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 8 8
Year 2 8 8
Year 3 8 8
Year 5 8 8
Year 10 8 8
Year 20 8 8

Healthcare Policy Analyst (Seattle, WA)

Age: 29 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 10.0 years

Commonness: 10/20

Statement of Opinion:

  • I believe this aligns with ongoing prevention efforts.
  • Metrics on its impact would be crucial for continued support.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 8 7
Year 3 8 7
Year 5 9 7
Year 10 9 7
Year 20 9 7

Hospital Administrator (Philadelphia, PA)

Age: 63 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 8.0 years

Commonness: 12/20

Statement of Opinion:

  • I expect improvements in hospital protocol adaptability.
  • This policy might streamline data management procedures for us.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 7 6
Year 3 7 6
Year 5 8 6
Year 10 8 6
Year 20 8 6

Freelance Journalist (Austin, TX)

Age: 34 | Gender: male

Wellbeing Before Policy: 5

Duration of Impact: 5.0 years

Commonness: 18/20

Statement of Opinion:

  • Will provide material for more informative articles.
  • Important to cover the societal implications.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 5 5
Year 2 6 5
Year 3 6 5
Year 5 6 5
Year 10 7 5
Year 20 7 5

Cost Estimates

Year 1: $250000000 (Low: $200000000, High: $300000000)

Year 2: $260000000 (Low: $210000000, High: $310000000)

Year 3: $270000000 (Low: $220000000, High: $320000000)

Year 5: $300000000 (Low: $250000000, High: $350000000)

Year 10: $350000000 (Low: $300000000, High: $400000000)

Year 100: $400000000 (Low: $350000000, High: $450000000)

Key Considerations