Calculate administrative vaccination coverage against target populations

baltor_vaccination_coverage_dropout

Calculate administrative vaccination coverage for declared antigen doses against explicit target-population denominators, dose-to-dose dropout rates and zero-dose estimates, flagging coverage above 100 percent and negative dropout instead of hiding them.

Files, names only

LICENSE 1.0 KB
SKILL.md 4.8 KB
contracts/input.schema.json 5.1 KB
contracts/output.schema.json 21.3 KB
examples/example.expected.json 6.7 KB
examples/example.input.json 1.6 KB
references/provenance.json 5.2 KB
scripts/tool.py 12.5 KB
verification/test_tool.py 15.5 KB

Full files in your harness.

What it takes and gives

Command: python3 -B scripts/tool.py < examples/example.input.json
Input fields: period, areas, dropout_pairs, zero_dose_reference
Test: python3 -B -m unittest discover -s verification -p 'test_*.py' -v
Files: SKILL.md, contracts/input.schema.json, contracts/output.schema.json, scripts/tool.py
Placed for: OpenCode

Limits and scope

Limits: This is a supporting calculation for SDG target 3.b on caller-supplied administrative data, not a WHO and UNICEF national coverage estimate. It does not adjust denominators, reconcile with surveys, measure timeliness or age at vaccination, or deduplicate children counted in two areas.

Details

Kind: Skill
Licence: MIT
Declared effects: reads files, runs commands
Placed for: OpenCode
Source: docs/architecture/NORTH-STAR.md
Size: 9 files, 73.8 KB
Identity: baltor_vaccination_coverage_dropout
Version: 9827094ee59406a7af3f6be0f11e9f4cefd760854d40aaf0742b73c4e4434d53

The version is the SHA-256 of the item your harness downloads; every file in it names its own checksum.

Where it is shown

Calculators for public statisticsDeterministic skills

Related components

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