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Table 1 Source of data for each step (Fig. 1) in the burden of disease calculation and years of data used

From: Assessing the magnitude and uncertainties of the burden of selected diseases attributable to extreme heat and extreme precipitation under a climate change scenario in Michigan for the period 2041–2070

Step Data Source Historical Projected
Extreme heat (EH) days Maurer 1/8-degree gridded daily maximum temperature observations [6] 1971–2000  
Extreme heat (EH) days Multi-model ensembleb of statistically-downscaled 1/8-degree dailydata sets from the North American Regional Climate Change Assessment Program [3]   2041–2070
Extreme precipitation (EP) days Multi-model ensembleb of statistically-downscaled 1/8-degree daily projections [3, 5, 14, 15] 1971–2000a 2041–2070
Population U.S. Census [16] 1971–2000  
Population Woods & Poole economic forecasting model [17]   2050
Population EPA’s Integrated Climate and Land-Use Scenarios (ICLUS) project for the A2 scenario [16, 103]   2050
All-natural-cause mortality Centers for Disease Control (CDC), National Center for Health Statistics (NCHS) [17] 2004–2006  
Renal/respiratory/heat hospitalizations, ages 65+ Medicare MedPAR billing records [20] 1990–2006  
Renal hospitalizations, ages 0–64 Michigan Inpatient Database [18] 2000–2009  
All-natural-cause and gastrointestinal emergency department (ED) visits Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality [21] 2007  
EH-mortality association case-crossover analysis, see Methods   
EH-renal/respiratory/heat hospitalization association Ogbomo et al. [18] 2000–2009  
EH-renal hospitalization association Gronlund et al. [20] 1990–2006  
EH-all-natural-cause ED visit association Kingsley et al. [25] 1999–2011  
EP-GI ED visit association Jagai et al. [27] 2003–2007  
  1. aNo additional data source needed; by definition, 2% of days in the historical period are EP days
  2. bDerived from the following six Climate Model Intercomparison Project Phase 3 global climate models (GCMs): cgcm3_t47, cgcm3_t63, cnrm, echam5, gfdl_2.1, pcm