RESUMO
Los Angeles County (LAC) low-income communities of color experience uneven asthma rates, evidenced by asthma emergency department visits (AEDV). This has partly been attributed to inequitable exposure to diesel particulate matter (DPM). Promisingly, public parks and open space (PPOS) contribute to DPM mitigation. However, low-income communities of color with limited access to PPOS may be deprived of associated public health benefits. Therefore, this novel study investigates the AEDV, DPM, PPOS nexus to address this public health dilemma and inform public policy in at-risk communities. Optimized Hotspot Analysis was used to examine geographic clustering of AEDVs, DPM, and PPOS at the census tract unit of analysis in LAC. Ordinary Least Squares (OLS) regression analysis was used to examine the extent to which DPM and PPOS predict AEDVs. Finally, Geographic Weighted Regression (GWR) was employed to account for spatial dependence in the global OLS model. Optimized Hotspot Analysis confirmed significant clustering of elevated AEDVs and DPM in census tracts with reduced PPOS. After controlling for pertinent demographic characteristics (poverty, children, race/ethnicity), regression analysis confirmed that DPM was significantly positively associated with AEDVs, whereas PPOS was significantly negatively associated with AEDVs. Furthermore, GWR revealed that 71.5% of LACs census tracts would benefit from DPM reductions and 79.4% would benefit from PPOS increases toward redressing AEDVs. This is the first study to identify AEDV reductions in census tracts with higher concentrations of PPOS. Thus, reducing DPM and increasing PPOS may serve to improve asthma outcomes, particularly in low-income communities of color.
RESUMO
The catastrophic 2010 earthquake in Port-au-Prince, Haiti, led to the large-scale displacement of over 2.3 million people, resulting in rapid and unplanned urbanization in northern Haiti. This study evaluated the impact of this unplanned urbanization on mosquito ecology and vector-borne diseases by assessing land use and change patterns. Land-use classification and change detection were carried out on remotely sensed images of the area for 2010 and 2013. Change detection identified areas that went from agricultural, forest, or bare-land pre-earthquake to newly developed and urbanized areas post-earthquake. Areas to be sampled for mosquito larvae were subsequently identified. Mosquito collections comprised five genera and ten species, with the most abundant species being Culex quinquefasciatus 35% (304/876), Aedes albopictus 27% (238/876), and Aedes aegypti 20% (174/876). All three species were more prevalent in urbanized and newly urbanized areas. Anopheles albimanus, the predominate malaria vector, accounted for less than 1% (8/876) of the collection. A set of spectral indices derived from the recently launched Landsat 8 satellite was used as covariates in a species distribution model. The indices were used to produce probability surfaces maps depicting the likelihood of presence of the three most abundant species within 30 m pixels. Our findings suggest that the rapid urbanization following the 2010 earthquake has increased the amount of area with suitable habitats for urban mosquitoes, likely influencing mosquito ecology and posing a major risk of introducing and establishing emerging vector-borne diseases.