Mortality attributable to environmental risks can rise despite population decline

Description

This dataset contains the complete reproducibility materials for the manuscript “Mortality attributable to environmental risks can rise despite population decline.” It links GBD 2023 age-specific attributable mortality-rate profiles for ambient particulate matter pollution, ambient ozone pollution and non-optimal temperature with UN World Population Prospects 2024 age-specific populations for Türkiye and six European comparators. The fixed-profile 2023–2040 counterfactual compares headcount-only and full age-structured mortality signals and decomposes demographic change into population-size and age-structure contributions using a symmetric two-factor Shapley method. The dataset contains the harmonised analytical input, executable Python code, primary and supplementary outputs, planning-signal tables, fine-age and profile-variant sensitivity analyses, zero-truncation checks, independent algebraic verification, dependency pins, source-provenance notes and SHA-256 integrity hashes. This is a conditional demographic diagnostic, not a forecast of future exposure or mortality. Risk-specific attributable deaths should not be summed.

Steps to reproduce

Download all files and preserve the folder structure. Use Python 3.12.14, pandas 2.2.3 and numpy 2.3.5, or install the pinned dependencies with: python -m pip install -r requirements.txt. From the package root run: python reproduce_JPH_analysis.py --input harmonized_analytical_input.csv --out outputs_reproduced. A successful run prints REPRODUCIBILITY CHECK: PASS and recreates the primary, planning-signal, fine-age, 189 profile-variant, zero-truncation and independent algebraic outputs. Compare outputs_reproduced with outputs; they should be identical. See README_JPH_Reproducibility.md and SOURCE_PROVENANCE.md.

Institutions

• Kocaeli Üniversitesi

  Kocaeli, İzmit

Categories

Licence