Calculate the prevalence of undernourishment

baltor_undernourishment_prevalence

Calculate the prevalence of undernourishment as the share of a lognormal habitual dietary energy intake distribution below a minimum dietary energy requirement, from caller-supplied mean intake, coefficient of variation and sex-age requirement groups.

Files, names only

LICENSE 1.0 KB
SKILL.md 4.8 KB
contracts/input.schema.json 6.0 KB
contracts/output.schema.json 6.4 KB
examples/example.expected.json 1.2 KB
examples/example.input.json 589 bytes
references/provenance.json 4.9 KB
scripts/tool.py 9.6 KB
verification/test_tool.py 10.0 KB

Full files in your harness.

What it takes and gives

Command: python3 -B scripts/tool.py < examples/example.input.json
Input fields: mean_intake_per_person_day, coefficient_of_variation, requirement, population, cv_sensitivity
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 2.1 (indicator 2.1.1) on caller-supplied parameters, not an official estimate. It assumes a lognormal distribution only; official FAO estimates may use a skew-normal distribution and estimate the CV from household survey data.

Details

Kind: Skill
Licence: MIT
Declared effects: reads files, runs commands
Placed for: OpenCode
Source: docs/architecture/NORTH-STAR.md
Size: 9 files, 44.6 KB
Identity: baltor_undernourishment_prevalence
Version: 2f5d689bc0f9f2fce752eeca83cc13f4c5d62f654a6a24c79e7fe8cfdd45996b

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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