Chapter 1 A Novel Method for Generating Spatially Resolved Synthetic Populations for Health Impact Assessments in Vulnerable Populations

Flannery Black-Ingersoll1, Chad W. Milando1, Zach Popp1, Mariangelí Echevarría-Ramos2, M. Patricia Fabian1,3, Amruta Nori-Sarma4,5, and Jonathan I. Levy1

1 Department of Environmental Health, Boston University School of Public Health, 715 Albany St, Boston, MA 02118, US

2 Mystic River Watershed Association, 23 Maple Street, Arlington, MA 02746, US

3 Institute for Global Sustainability, Boston University, 111 Cummington Mall Suite 149, Boston, MA 02215, US

4 Department of Environmental Health, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115, US

5 Center for Climate, Health, and the Global Environment (C-CHANGE), Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115, US

Corresponding author: Flannery Black-Ingersoll (fblackin@bu.edu)

Senior corresponding author: Jonathan I. Levy (jonlevy@bu.edu)

The code and methods described in this article are outlined in further detail in this R bookdown document. The code is provided in the github repository here: https://github.com/Flannery-BIng/synth_pop.