At a glance
Estimating the prevalence of ASD
There are several ways to estimate the number of children with ASD. This estimate is referred to as prevalence, a scientific term that describes the number of people with a disease or condition among a defined group (or 'population'). Prevalence is typically shown as a percent (e.g., 0.1%) or a proportion (e.g., 1 in 1,000).
Fact
About 1 in 31 children were identified with autism spectrum disorder among a 2022 sample of 8-year-olds from 16 US communities in CDC's ADDM Network.1
Explore the information below to see autism spectrum disorder (ASD) prevalence estimates and demographic characteristics at the national, state, and community levels.
ASD prevalence estimates from the following four data sources are presented on this webpage:
Administrative data collected by the US Department of Education. The Individuals with Disabilities Education Act (IDEA) classifies children with disabilities who receive special education and related services into 13 primary disability categories, including ASD. Students 3–21 years old are eligible for services under IDEA. Under Section 618 of IDEA, states are required to report the number of students who receive special education and related services under the primary disability category for ASD. National and state-level data are available for years 2000–2022. CDC used special education child count data to report the number of children 6–17 years old with ASD who are receiving special education and related services in each state.
The (NSCH) is an annual, cross-sectional, address-based survey that collects information on the health and well-being of children ages 0-17 years, and related health care, family, and community-level factors that can influence health. The NSCH is funded and directed by the Health Resources and Services Administration's Maternal and Child Health Bureau and fielded by the US Census Bureau, using both web-based and paper and pencil methodologies, beginning in 2016. Previous survey years (2003, 2007, and 2011-12) were collected via telephone. NSCH data reflect information collected from parents or caregivers and are weighted to produce both national- and state-level estimates.
Administrative claims data are from the Centers for Medicare and Medicaid Services (CMS). States report data to CMS, which released Medicaid Analytic eXtract (MAX) datasets from 2000-2014, and Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF), beginning in 2013, for analysis; some states had data in both MAX and TAF datasets during the transitional period in 2013-2015. CDC analyzed CMS data for each state with available data for years 2000–2022, and identified children 3–17 years old who had received Medicaid benefits, were continuously enrolled in Medicaid for at least 89 days, and had at least two outpatient billing codes for ASD or one inpatient billing code in the specified year. Data from 2014 and 2015 were excluded due to data quality issues for diagnosis codes.
The Autism and Developmental Disabilities Monitoring (ADDM) Network is a program funded by CDC to estimate the number of children with ASD and other developmental disabilities living in different areas of the United States. ADDM Network sites collect data from health and/or education records of 8-year-old children using the same methods across sites. They use these data to estimate the number of 8-year-old children identified with ASD. Community-level data are available for various communities across the United States for even-numbered years from 2000 through 2022.
Understanding Trends and Changes in ASD Prevalence
Ongoing monitoring and reporting help us identify trends and changes in the number of people with ASD over time. To see these trends and changes, we can look at ASD prevalence
- Across multiple years,
- Across multiple data sources,
- In different geographic locations, and
- Among different demographic groups.
These findings can be used in local communities and nationwide to inform initiatives, policies, and research that help children and families living with ASD.
1. Reported prevalence has changed over time
The reported prevalence of ASD has been higher in recent years, and this trend is consistent across data sources. It is unclear how much this is due to changes to the clinical definition of ASD (which may include more people than previous definitions) and better efforts to diagnose ASD (which would identify people with ASD who were not previously identified). Choose a data source below to see how prevalence estimates have changed over time.
2. Reported prevalence varies by geographic location
ASD prevalence varies widely across geographic areas. Currently, no research has shown that living in certain communities increases the chance that a child will have ASD. Geographic variation could, however, be related to differences in how children with ASD are identified and/or served in their local communities and how this information is collected and reported. Choose the data source below to see prevalence estimates by geographic area.
3. Reported prevalence varies by sex
Since the first ADDM reporting period (2000), ASD prevalence has been higher among boys than girls across all ADDM sites. There are no clear explanations for this difference. One consideration is that boys may be at greater risk for developing ASD. Another consideration is that ASD can have different signs and symptoms in boys versus girls. This can contribute to differences in how ASD is identified, diagnosed, and reported. Choose the data source below to see how prevalence estimates vary by sex.
4. Reported prevalence varies by race and ethnicity
There have been racial and ethnic differences observed over the years in ADDM data. Prior to 2014, the percentage of 8-year-old White children with ASD was higher than other groups. In 2014, the percentage of Black children with ASD began to be similar to White children. Asian or Pacific Islander children began to have a similar percentage of children with ASD 2016, as did Hispanic children in 2018. For the first time in 2020, the percentage of 8-year-old Asian or Pacific Islander, Hispanic, and Black children identified with ASD was higher than among 8-year-old White children. This pattern continued in 2022. These shifts may reflect improved screening, awareness, and access to services among historically underserved groups.
5. Early identification has been increasing over time
The ADDM Network also tracks progress in early identification of ASD among children aged 4 years. When compared to children aged 8 years in the same community, it enables communities to assess whether the amount of children identified as having ASD by age 4 is increasing over time. This is measured by the cumulative incidence of ASD identification; cumulative incidence was calculated by dividing the total number of children identified with ASD at each month of age by the entire population denominator for each age group.
Explore the data
Now it’s your turn to explore the data! Select a location from the drop-down menu below to explore ASD prevalence estimates (with the option to select a second location or data source). There is an option to view the data with or without a confidence interval, or a range of possible values. Even though all available data will be displayed, keep in mind that data are not available for all states across data sources.
Where do ASD data come from
Different ways to estimate the prevalence of ASD
There are many ways to gather data used to estimate the prevalence of ASD. These data collection methods include
- Screening and evaluating all children in a population;
- Examining data from national surveys, registries, and administrative sources; and
- Reviewing health and education records of children in a chosen population.
Each method has its advantages and disadvantages.
How are ASD data gathered
Different data sources gather ASD data in different ways. Much of the variation in reported ASD prevalence is related to these different data collection methods. The population studied and differing ASD criteria across data sources also contribute to this variation.
Criteria
The ADDM Network estimates the number of 8-year-old children with ASD using a record review method. Currently, this review includes both children who have an ASD diagnosis, ASD classification in special education, or have a medical billing code for ASD in their records.
Sample Size
The ADDM Network tracked more than 270,000 8-year-old children in 2022.
Method
The ADDM Network uses a systematic record review method. Data reported by the ADDM Network are based on the analysis of data collected from the health, service, and special education records (if available) of 8-year-old children who lived in one of the surveillance areas throughout the United States during the surveillance year (the most recent surveillance year is 2022).
Why this matters
The ADDM Network tracks the number and characteristics of children with ASD in multiple communities in the United States. ASD prevalence could be underestimated if children have not been diagnosed or assessed for any developmental delay or if children with ASD were not enrolled in special education.
Criteria
Medicaid data used by CDC estimates the number of children (3–17 years old) who have two or more outpatient or one or more inpatient Medicaid claims using an ASD diagnosis code.
Sample Size
Medicaid data were derived from approximately 15 million participants in 2000 to approximately 55 million participants in 2022, reflecting a growing population of Medicaid recipients.
Method
Medicaid data are gathered from all states. States send Medicaid healthcare administrative claims data to CMS annually. CMS converts the state-submitted data into analytical data sets, called Medicaid Analytic eXtract (MAX; 2000-2014) or Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF; 2013-2022). The study sample was restricted to children who were continuously enrolled in Medicaid for at least 89 days during the calendar year, excluding children who were only briefly enrolled in Medicaid. Children with ASD are determined by counting the number of children who are receiving Medicaid benefits who have at least two outpatient billing codes for ASD or one inpatient billing code (ICD-9 code of 299.XX or ICD-10 code of F84.X) for ASD in the specified year.
Why this matters
Medicaid data consolidate a large amount of administrative claims data available from CMS, but could underestimate prevalence among those receiving Medicaid because
- Not all children with ASD have been diagnosed, or
- They may not have received services during a specific year, or
- There could be coding errors.
Not all children (with or without ASD) are enrolled in Medicaid; therefore, this data source only represents those children insured under Medicaid.
Criteria
The NSCH data estimates the number of children (3–17 years old) identified with ASD through parental report of ASD diagnosed by a healthcare provider. Although NSCH data includes ages 0–17, CDC only uses data for children older than 3 years of age since ASD generally is not diagnosed until after 3 years of age, despite early identification efforts.
Sample Size
The most recent NSCH data reflect 104,995 surveys collected during a 2-year period from 2021 through 2022. In previous surveys (from 2003–2012), approximately 91,000–102,000 surveys were conducted in each year.
Method
NSCH data are gathered through two methods: a nationally representative telephone survey (2003, 2007, 2011–2012) and mail invitation to an online survey (beginning in 2016). The NSCH survey asks whether a child was ever diagnosed with ASD and if the child has a current ASD diagnosis. Reported prevalence estimates count only "current" responses.
Why this matters
As a national survey, the NSCH is representative of national characteristics. However, the survey could over- or underestimate prevalence because
- Some parents may not correctly report if their child has an ASD diagnosis, or
- The characteristics of survey participants did not represent those not participating in the survey.
Criteria
The Special Education child count data used by CDC estimates the number of children (6–17 years old) with ASD receiving special education and related services in each state. Each state has different criteria for identifying students 3–21 years old with ASD. CDC focuses on Special Education child count data for children 6–17 years old, as they are most likely to be in grade school.
Sample Size
Special Education child count data were collected from more than 5 million children each year from 2000 to 2022. These data represent the 60 states and entities that receive IDEA Part B formula grants.
Method
Special Education child count data are gathered from all states. Children with ASD are determined by counting the number of children served by special education programs under the ASD primary disability category on a state-determined child count date between October 1 and December 1, as reported by the states to the US Department of Education annually.
Why this matters
Special Education child count data consolidate a large amount of information from the US Department of Education. However, these data can underestimate prevalence because not all children with ASD have been diagnosed or are receiving special education and related services for ASD based on an Individualized Education Program (IEP) or service plan. Also, children may be assigned an autism classification based on service needs, even if they do not consider the child to have autism.
- Shaw KA, Williams S, Patrick ME, et al. Prevalence and Early Identification of Autism Spectrum Disorder Among Children Aged 4 and 8 Years — Autism and Developmental Disabilities Monitoring Network, 16 Sites, United States, 2022. MMWR Surveill Summ 2025;74(No. SS-2):1–22.