DATA README

ICF - April 2025
This README provides an overview of the included files and their content descriptions.

Analysis and Modeling Input Files

  1. gis.zip (1.2M):
    • Contains geospatial files necessary for mapping and geographic analysis.
  2. processed-climate.zip (813M):
    • Includes processed climate datasets, formatted as inputs for analysis and modeling.
  3. processed-other.zip (221M):
    • Contains processed population, incidence, health impact function, and valuation data formatted as inputs for analysis and modeling.
  4. raw-incidence.zip (862M):
    • Raw incidence data from which modeling and analysis inputs are derived.
  5. raw-population.zip (16M):
    • Raw population data from which modeling and analysis inputs are derived.
  6. raw-valuation.zip (122M):
    • Raw valuation datasets from which modeling and analysis inputs are derived.

Results Files

Summary Results

  • results-summaries.zip (952M):
    • Comprehensive summary results across all analyses as well as manuscript tables, figures, and maps.
  • results-point_2025-0411-county_climate_annual_metrics.zip (39M):
    • County-level climate metrics used in the analysis, aggregated up to the year.

County-level Central (Point) Results

  • results-point_2025-0411-county_D1D6.zip (1G):
    • Combined results for county-level point data for warming degree scenarios D1 through D6.
  • results-point_2024-1010-county_[YEAR].zip:
    • County-level point data results for the year [YEAR].
    • Results are available for years (sizes in parentheses): Y2015 (588M), Y2025 (586M),Y2035 (588M), Y2045 (587M), Y2055 (586M), Y2065 (588M), Y2075 (586M), Y2085 (588M), Y2095 (594M).

State-level Central (Point) Results

  • results-point_2025-0411-state_D1D6.zip (23M):
    • State-level point data results for warming degree scenarios D1, D2, D3, D4, D5, D6.
  • results-point_2024-1010-state_Y2015Y2095.zip (64M):
    • State-level point data results for years 2015, 2025, 2035, 2045, 2055, 2065, 2075, 2085,2095.

State-level Monte Carlo Sampling Results

  • results-sampling_2025-0411-state_[DEG]_[POP].zip
  • State-level results from Mont Carlo sampling for warming degree scenarios ([DEG]: D1, D2, D3, D4, D5, D6) and health impact functions applicable to various CONUS ([POP]: allCONUS, urbanCONUS). Files with all CONUS results (POP: allCONUS) contain acute exposure results for general population, high-income subpopulation, and low-income subpopulation. Files with urban CONUS results (POP: urbanCONUS) contain acute exposure results and chronic exposure results for urban subpopulation.
    • D1: allCONUS (2.6G), urbanCONUS (1.7G)
    • D2: allCONUS (2.6G), urbanCONUS (1.7G)
    • D3: allCONUS (2.6G), urbanCONUS (1.7G)
    • D4: allCONUS (2.6G), urbanCONUS (1.7G)
    • D5: allCONUS (1G), urbanCONUS (684M)
    • D6: allCONUS (1G), urbanCONUS (684M)

Definitions of variables across detailed results files

Variable Description
ITER Iteration number, representing Monte Carlo simulation run. ITER=0 identifies central (point) results.
ST State abbreviation for 49 CONUS states and Washington DC.
FIPS U.S. County FIPS code
DEG Warming degree scenario 1°C–6°C.
ARR_YR Calendar year of the warming degree arrival.
YEAR_CLIM Calendar year of the climate projection.
YEAR_POP Calendar year of the population projection: 2022 (present-day) or 2095 (end-of-century).
YEAR_INC Calendar year of the income level projection: 2022 (present-day) or 2095 (end-of-century).
SOC_YR Sociodemographic scenario. Includes: PRESENT, FUTURE.
MODEL General Circulation Model (GCM) used for climate projections. Includes: ACCESS-CM2, EC-Earth3-Veg, GFDL-ESM4, MPI-ESM1-2-HR, NorESM2-MM.
HIF Health Impact Function (HIF) used to generate results. Includes several types of exposure-response (ER) functions. Acute temperature and precipitation exposure: binned_dem (sex-specific ER), binned_dem_urb (sex-specific ER, applied to urban subpopulation), binned_gen (general population ER), binned_hi (high-income ER), binned_li (low-income ER), binnedx_gen (general population ER with extra temperature bin). Acute precipitation exposure: binned_dem_precip, binned_gen_precip, binned_hi_precip, binned_li_precip, binnedx_gen_precip. Acute temperature exposure: binned_dem_temp, binned_gen_temp, binned_hi_temp, binned_li_temp, binnedx_gen_temp. Chronic temperature exposure: longdiff_urb_anntemp (urban population ER using annual max temperature change), longdiff_urb_seastemp (urban population ER using seasonal max temperature change). Manuscript tables and figures are generated using: binned_dem, binned_hi, binned_li, binned_dem_urb, longdiff_urb_seastemp.
SEX Subpopulation sex category: female, male.
AGE Subpopulation age group (years): 18to24, 25to34, 35to44, 45to54, 55to64, 65+.
SUBPOP Subpopulation socio-geographic category: gen (general population), hi (high-income subpopulation), li (low-income subpopulation), urb (urban subpopulation).
ANX_MHD Ratio of anxiety symptom-days to mental health difficulty (MHD) symptom-days.
DEP_MHD Ratio of depression symptom-days to MHD symptom-days.
VANX_0DR Value per avoided anxiety symptom-day (2023$, using 0% discount rate to estimate baseline quality-of-life adjusted life expectancy).
VANX_2DR Value per avoided anxiety symptom-day (2023$, using 2% discount rate to estimate baseline quality-of-life adjusted life expectancy).
VDEP_0DR Value per avoided depression symptom-day (2023$, using 0% discount rate to estimate baseline quality-of-life adjusted life expectancy).
VDEP_2DR Value per avoided depression symptom-day (2023$, using 2% discount rate to estimate baseline quality-of-life adjusted life expectancy).
D_le_0 Change in the annual number of days with temperature ≤0°C.
D_0_5 Change in the annual number of days with temperature in (0°C, 5°C].
D_5_10 Change in the annual number of days with temperature in (5°C, 10°C].
D_15_20 Change in the annual number of days with temperature in (15°C, 20°C].
D_20_25 Change in the annual number of days with temperature in (20°C, 25°C].
D_25_30 Change in the annual number of days with temperature in (25°C, 30°C].
D_30_ge Change in the annual number of days with temperature >30°C.
D_30_35 Change in the annual number of days with temperature in (30°C, 35°C].
D_35_ge Change in the annual number of days with temperature >35°C.
AMT Change in maximum annual temperature (°C).
AMT_spring Change in maximum spring temperature (°C).
AMT_summer Change in maximum summer temperature (°C).
AMT_fall Change in maximum fall temperature (°C).
AMT_winter Change in maximum winter temperature (°C).
P_0_5 Change in the annual number of months with (0, 5] precipitation days.
P_5_10 Change in the annual number of months with (5, 10] precipitation days.
P_10_15 Change in the annual number of months with (10, 15] precipitation days.
P_15_20 Change in the annual number of months with (15, 20] precipitation days.
P_20_25 Change in the annual number of months with (20, 25] precipitation days.
P_25_ge Change in the annual number of months with >25 precipitation days.
POP_SIZE Population size for a given demographic and socio-geographic subpopulation.
IR Baseline number of MHD symptom-days per person-year.
Y Average annual probability of at least one MHD symptom-day per person-month.
ALPHA Average overdispersion parameter for MHD symptom-day distribution.
BASE_MHD Baseline annual number of MHD symptom-days for a given demographic and socio-geographic subpopulation.
BASE_ANX Baseline annual number of anxiety symptom-days for a given demographic and socio-geographic subpopulation.
BASE_DEP Baseline annual number of depression symptom-days for a given demographic and socio-geographic subpopulation.
DELTA_P Change in average annual probability of at least one MHD symptom-day per person-month.
CASES_MHD Estimated number of excess MHD symptom-days.
CASES_ANX Estimated number of excess anxiety symptom-days.
CASES_DEP Estimated number of excess depression symptom-days.
PDV_ANX_0DR Value of avoiding excess anxiety symptom-days (2023$, undiscounted).
PDV_DEP_0DR Value of avoiding excess depression symptom-days (2023$, undiscounted).
PDV_ANX_2DR Value of avoiding excess anxiety symptom-days (2023$, discounted at constant 2% rate to 2023).
PDV_DEP_2DR Value of avoiding excess anxiety symptom-days (2023$, discounted at constant 2% rate to 2023).
Notes
  • File sizes are approximate and listed to provide a sense of resource requirements.
  • Ensure sufficient disk space and appropriate software for extracting and handling these files.

For questions or further assistance, please contact the corresponding author.