Marc L. Serre

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A major challenge in mapping health data is protecting patient privacy while maintaining the spatial resolution necessary for spatial surveillance and outbreak identification. A new adaptive geomasking technique, referred to as the donut method, extends current methods of random displacement by ensuring a user-defined minimum level of geoprivacy. In donut(More)
Geomasking is used to provide privacy protection for individual address information while maintaining spatial resolution for mapping purposes. Donut geomasking and other random perturbation geomasking algorithms rely on the assumption of a homogeneously distributed population to calculate displacement distances, leading to possible under-protection of(More)
OBJECTIVE We analysed and mapped the distribution of four reportable sexually transmitted diseases, chlamydial infection/non-gonococcal urethritis (chlamydial infection), gonorrhoea, primary and secondary syphilis (syphilis), and HIV infection, for Wake County, North Carolina, to optimise an intervention. METHODS We used STD surveillance data reported to(More)
BACKGROUND Recent studies suggest that exposure to traffic-related air pollutants, including particulate matter (PM), is associated with autism spectrum disorder (autism). METHODS Children with autism were identified by records-based surveillance (n = 645 born in North Carolina in 1994, 1996, 1998, or 2000, and n = 334 born in the San Francisco Bay Area(More)
The health risks of As exposure due to the installation of millions of shallow tubewells in the Bengal Basin are known, but fecal contamination of shallow aquifers has not systematically been examined. This could be a source of concern in densely populated areas with poor sanitation because the hydraulic travel time from surface water bodies to shallow(More)
This study quantifies the national burden of disease attributed to particulate matter (PM) and ozone (O(3)) in ambient air in the United Arab Emirates (UAE), a rapidly growing nation in which economic development and climatic conditions pose important challenges for air quality management. Estimates of population exposure to these air pollutants are based(More)
Airborne fine particulate matter exhibits spatiotemporal variability at multiple scales, which presents challenges to estimating exposures for health effects assessment. Here we created a model to predict ambient particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) across the contiguous United States to be applied to health effects modeling.(More)
BACKGROUND A better understanding of the adverse health effects of chronic exposure to fine particulate matter (PM2.5) requires accurate estimates of PM2.5 variation at fine spatial scales. Remote sensing has emerged as an important means of estimating PM2.5 exposures, but relatively few studies have compared remote-sensing estimates to those derived from(More)
The goal of this study was to test hollow-fiber ultrafiltration as a method for concentrating in situ bacteria and viruses in groundwater samples. Water samples from nine wells tapping a shallow sandy aquifer in a densely populated village in Bangladesh were reduced in volume approximately 400-fold using ultrafiltration. Culture-based assays for total(More)
Knowledge of particulate matter concentrations <2.5 μm in diameter (PM2.5) across the United States is limited due to sparse monitoring across space and time. Epidemiological studies need accurate exposure estimates in order to properly investigate potential morbidity and mortality. Previous works have used geostatistics and land use regression (LUR)(More)