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Related Experiment Video

Updated: Mar 3, 2026

Strategies for Assessing Autistic-Like Behaviors in Mice

Strategies for Assessing Autistic-Like Behaviors in Mice

Published on: September 20, 2024

GapMap: Enabling Comprehensive Autism Resource Epidemiology.

Nikhila Albert^1,2,3, Jena Daniels^1,3, Jessey Schwartz^1,3

¹Department of PediatricsDivision of Systems MedicineStanford UniversityStanford, CAUnited States.

JMIR Public Health and Surveillance

|May 6, 2017

Summary

This summary is machine-generated.

Accessing autism resources is challenging. A new mobile app, GapMap, collects data to improve autism prevalence rates and resource availability, aiding families and researchers in understanding autism epidemiology.

Keywords:

autism autism spectrum disorder crowdsourcing epidemiology prevalence resources

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Area of Science:

Autism Spectrum Disorder (ASD) research
Public Health
Geospatial Epidemiology

Background:

Individuals with autism spectrum disorder (ASD) face significant challenges in accessing necessary resources.
Lack of fine-grained epidemiological data impedes research on ASD correlations with environmental, geographical, and cultural factors.

Purpose of the Study:

To define resource load and availability for families affected by autism.
To develop a platform for accurate autism prevalence and resource epidemiology representation.

Main Methods:

Developed GapMap, a mobile application hosted on AWS, to collect location, diagnostic, and resource use data.
Utilized React/Redux front-end and AWS API Gateway/Lambda for secure data retrieval and submission.
Defined and computed measures of autism resource scarcity, including load, availability, and gaps.

Main Results:

The average distance to a diagnostic center in the US is 182 km, but for individuals with ASD, it is 32 km.
Proximity to diagnostic services correlates with a higher likelihood of diagnosis.

Conclusions:

Individuals closer to diagnostic services are more likely to receive a diagnosis.
GapMap aims to alleviate overburdened centers and support resource-poor areas by providing accurate data on autism prevalence and resource epidemiology.