\({\Large {\color{blue} {PREVALENCE \space OF \space AUTISM \space IN \space THE \space US}}}\)

\({\small {\color{blue}{By \space Elizabeth \space Lanspa}}}\)

\[{\large {\color{lightblue} {About \space 1 \space in \space 54 \space children \space are \space diagnosed \space with \space ASD}}}\]

\({\LARGE {\color{darkblue}{\underline{Prevalence \space Data}}}}\)

\(\bullet\) Special Education Child Count- Administrsative data collected by the US Department of Education. definition and info about it. Taken data of rates in US every year since 2000.

\(\bullet\) ADDM Network - definition and info about i. Takes data of rates every other year, ending in 2016.

###GOAL: interactive: each bullet is a folder page. click on the tab to open info about each source

\({\small Prevalence \space estimates \space can \space vary \space by \space data \space source \space because \space different \space collection \space methods \space are \space used \space across \space different \space sources. \space For \space example,\\ \space \small{ criteria \space to \space diagnose \space Autism \space varies \space from \space clinician \space to \space clinician, \space study \space to \space study. \space Because \space of \space these \space differences, \space prevalence \space rates \\ \space typically \space vary \space across \space data \space sources.}}\)

\(%Make this two sided text/graph\)

The ADDM data source, which only surveys in 11 states, reports almost twice the rates of Autism than the nations-wide SECC data source. While SECC may collect more data, the Dept. of Education is notorious for over- and under-diagnosing cases of Autism. However, the SECC data source has a much smaller CI. Therefore, we must be skeptical of both sources and look at them in unison to make a more accurate hypothesis.

\({\LARGE{\color{darkblue}{\underline{Trends \space Over \space Time}}}}\)

Below is an example of the two most reliable and valid prevalence sources from the CDC. Notice how they both show a positive correlation between prevelance and passage of time, but at significantly different rates. Among other theories, this disparity is a result of less frequency and magnitude in reporting from the ADDM data source than the SECC data source.

#Goal is to make this interactive. WHen you click on a data point, the CI intervals will appear

-As depicted above, reported prevalence of ASD has been rising higher and higher.

\[{\color {blue}{Why?}}\]

There are many theories that try and fail to completely explain the increase in diagnoses. At the forefront is the rapid number of changes to the clinical definition of Autism according to the Diagnostic and Statistics Manual IV.

********chart of previous definitions and current ASD definitions (maybe add prevalence over time graph in beginning of section?) *********** I have this done in excel, making tweaks on it to turn it into a stargazer

\({\LARGE{\color{darkblue}{\underline {2016 \space ADDM \space Network \space Data}}}}\)

ASD PREVALENCE PER 1,000 8-YEAR-OLD CHILDREN

Are There Biological, Geographic, or environmental Predictors of Autism?

#Goal is to make interactive graph: x axis year, y axis prevalence, and can toggle between male and female vvvvvvv

\({\large{\color{darkgrey}{Prevalence \space by \space Sex}}}\)

## `geom_smooth()` using formula 'y ~ x'

## `geom_smooth()` using formula 'y ~ x'