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AI agent for public health officers

Vaccination Clinic Planning Agent

Clinic schedules that reach low-coverage areas with enough staff and vaccine

Vaccination Clinic Planning Agent: what goes in, what the agent does and what you get

What it does

Vaccination drives need the right sites, dates, staff and vaccine supply, and gaps in any one of them waste a clinic day. This agent pulls coverage data by neighborhood each month and ranks areas by coverage gap and population. It proposes clinic sites, dates and expected turnout, then checks vaccine inventory, cold chain capacity and staff schedules. If doses, storage or staff fall short, it reduces clinic size, moves dates or flags an order need. Lots expiring within 60 days are scheduled first. The health officer approves sites and public announcements. After each clinic, the agent compares actual turnout with the estimate and uses it for the next plan. Edge case: if a lot nears expiry, it schedules that lot first and suggests extra outreach in the busiest area.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Monthly planning begins 2 USES A TOOL Pull coverage data by neighborhood 3 DOES Rank areas by gap and population 4 DOES Propose sites, dates and expected turnout 5 USES A TOOL Check vaccine inventory, cold chain and staffschedules 6 CHECKS THE RESULT Are doses, storage and staff enough for everyclinic? If not: reduce clinic size, move dates, or flag an orderneed. Back to step 4. 7 YOU APPROVE Officer approves sites and announcements 8 USES A TOOL After each clinic, compare actual turnout withestimate 9 RESULT Clinic plan and turnout log
Read the steps as a list
  1. Monthly planning begins
  2. Pull coverage data by neighborhood
  3. Rank areas by gap and population
  4. Propose sites, dates and expected turnout
  5. Check vaccine inventory, cold chain and staff schedules
  6. Are doses, storage and staff enough for every clinic?If not: reduce clinic size, move dates, or flag an order need. Back to step 4.
  7. Officer approves sites and announcementsThe agent waits here for your OK.
  8. After each clinic, compare actual turnout with estimate
  9. Clinic plan and turnout log

How it decides

Areas are ranked by coverage gap and population. Turnout estimates use past clinics in similar areas.

  • Largest coverage gaps go first
  • Lots expiring within 60 days are used first
  • Turnout estimates update from actuals

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Coverage threshold for targeting
  • Expiry window (default 60 days)
  • Staff per 100 expected doses
  • Planning frequency

What keeps you in control

It always asks you first

  • Officer approves sites, dates and public announcements
  • Vaccine orders are placed by staff

Hard limits

  • Never publishes announcements
  • Never orders vaccine

It stops when

  • Done: month's clinics planned
  • Stop: no vaccine supply available

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensTwo zip codes had flu shot coverage below 30%. The plan set 4 clinics needing 1,200 doses, but inventory held 900 with the cold chain full. The supply check failed, so the agent cut one clinic, moved it to the week after the Oct 20 delivery, and used 300 doses from a lot expiring in 40 days first. The officer approved the sites, and turnout ran 8% above estimate.

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