Biomedical subjects

Sue Grady

Publications and source records attributed to Sue Grady.

3 recordsLinked to original sources

PubMed2005

Immigration and geographic access to prenatal clinics in Brooklyn, NY: a geographic information systems analysis.

We compared levels of geographic access to prenatal clinics in Brooklyn, NY, between immigrant and US-born mothers and among immigrant groups by country of birth. We used birth data to characterize the spatial distribution of mothers and kernel estimation to measure clinic density within a 2-mile radius of each mother. Results showed that geographic access to clinics differs substantially by country of birth. Certain groups (e.g., Pakistani, Bangladeshi) have relatively poor geographic access despite a high need for prenatal care.

Adolescent↗

PubMed2004

Prenatal care need and access: a GIS analysis.

Many municipalities provide special prenatal care services targeted to low-income women whose access to prenatal care is constrained. For such services to be successful and effective, they must be geographically targeted to the places where low-income, high-need mothers live. This paper presents a GIS analysis of prenatal care need and clinic services for low-income mothers in Brooklyn, NY. We analyze fine-grained geographic variation in need using data on the residential locations of recent mothers who lack health insurance or are covered by Medicaid. Spatial statistical methods are used to create spatially smoothed maps of the density of mothers and corresponding maps of the density of prenatal clinics. For these mothers, clinic density is positively associated with early initiation of prenatal care. Although clinic locations conform relatively well to the residential concentrations of high-need women, we identify several underserved areas with large numbers of needy women and few clinics available.

Adolescent↗

PubMed2003

Identifying West Nile virus risk areas: the Dynamic Continuous-Area Space-Time system.

The Dynamic Continuous-Area Space-Time (DYCAST) system was developed to identify and prospectively monitor high-risk areas for West Nile virus in New York, New York (New York City). The system is based on a geographic model that uses a localized Knox test to capture the nonrandom space-time interaction of dead birds, as an indicator of an intense West Nile virus amplification cycle, within a 1.5-mile (2.41-km) buffer area and 21-day moving window. The Knox analysis is implemented as an interpolation function to create a surface of probabilities over a grid of 1,400 cells overlaying New York City. The model's parameters were calibrated using year 2000 data and information on the vector-host transmission cycle. The DYCAST system was implemented in a geographic information system and used operationally in year 2001. It successfully identified areas of high risk for human West Nile virus infection in areas where five of seven human cases resided, at least 13 days prior to the onset of illness, and proved that it can be used as an effective tool for targeting remediation and control efforts.

Animals↗