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|Title:||Identifying Autism Resource Gaps: Enabling Global Autism Epidemiology and Connecting Families to Fundamental Services|
|Abstract:||For individuals with autism spectrum disorder, finding resources can be a lengthy and difficult process. The difficulty in obtaining global, fine-grained autism epidemiological data hinders researchers from quickly, cheaply, and efficiently studying large-scale correlations between ASD, environmental factors, and geographical/cultural factors. To help solve these two problems in autism resource findability and autism epidemiology, a web tool, GAPMap, was created to inexpensively and feasibly amass geographical information from individuals with autism and compile a global database of autism resources. This application will therefore be an invaluable tool to members of the autism community, enable a better understanding of autism epidemiology, and allow the detection of significant resource gaps. Raw prevalence rates and resources were scraped to provide starter data for GAPMap and preliminary analyses. A strong negative correlation between tree cover and prevalence rates, as well as the extremely short average distance from an individual with autism to the nearest diagnostic center (32 km and 31 km in the US and the UK, respectively), suggesting that autism diagnosis is highly contingent on resource accessibility.|
|Type of Material:||Princeton University Senior Theses|
|Appears in Collections:||Computer Science, 1988-2017|
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