TY - JOUR
T1 - Spatial accessibility of pre-exposure prophylaxis (PrEP)
T2 - different measure choices and the implications for detecting shortage areas and examining its association with social determinants of health
AU - Luan, Hui
AU - Li, Guangquan
AU - Duncan, Dustin T.
AU - Sullivan, Patrick S.
AU - Ransome, Yusuf
N1 - Publisher Copyright:
© 2023 Elsevier Inc.
PY - 2023/10
Y1 - 2023/10
N2 - Purpose: We examine how various pre-exposure prophylaxis (PrEP) accessibility measures impact the detection of PrEP shortage areas and the relation of shortage areas to social determinants of health (SDOH). Methods: Using ZIP Code Tabulation Areas (ZCTAs) in New York City as a case study, we compared 25 measures of spatial PrEP accessibility across four categories, including density, proximity, two-step floating catchment area (2SFCA), and Gaussian 2SFCA (G2SFCA). Bayesian spatial regression models were used to examine how PrEP accessibility is associated with SDOH. Results: Using density to measure PrEP accessibility for small areas such as ZCTAs poses challenges to statistical modeling because the measured accessibility values are highly skewed with excess zeros, leading to the necessity of using complex models such as the two-part mixture model. When G2SFCA measures are used, which account for distance decay effects and the competition from the PrEP demand side, findings on PrEP shortage area detection and the association between PrEP accessibility and SDOH were more consistent and less sensitive to spatial scales (i.e., varying from 10- to 30-minute driving). Conclusions: This research adds to the nascent research on PrEP accessibility measurement and sheds light on selecting an appropriate measure to assess spatial disparities in PrEP accessibility and its associations with SDOH.
AB - Purpose: We examine how various pre-exposure prophylaxis (PrEP) accessibility measures impact the detection of PrEP shortage areas and the relation of shortage areas to social determinants of health (SDOH). Methods: Using ZIP Code Tabulation Areas (ZCTAs) in New York City as a case study, we compared 25 measures of spatial PrEP accessibility across four categories, including density, proximity, two-step floating catchment area (2SFCA), and Gaussian 2SFCA (G2SFCA). Bayesian spatial regression models were used to examine how PrEP accessibility is associated with SDOH. Results: Using density to measure PrEP accessibility for small areas such as ZCTAs poses challenges to statistical modeling because the measured accessibility values are highly skewed with excess zeros, leading to the necessity of using complex models such as the two-part mixture model. When G2SFCA measures are used, which account for distance decay effects and the competition from the PrEP demand side, findings on PrEP shortage area detection and the association between PrEP accessibility and SDOH were more consistent and less sensitive to spatial scales (i.e., varying from 10- to 30-minute driving). Conclusions: This research adds to the nascent research on PrEP accessibility measurement and sheds light on selecting an appropriate measure to assess spatial disparities in PrEP accessibility and its associations with SDOH.
KW - Bayesian spatial analysis
KW - Gaussian 2SFCA
KW - HIV prevention
KW - Pre-exposure prophylaxis
KW - Spatial accessibility
KW - Two-part mixture model
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U2 - 10.1016/j.annepidem.2023.07.004
DO - 10.1016/j.annepidem.2023.07.004
M3 - Article
C2 - 37453464
AN - SCOPUS:85167776649
SN - 1047-2797
VL - 86
SP - 72-79.e3
JO - Annals of Epidemiology
JF - Annals of Epidemiology
ER -