BACKGROUND:The distribution of early social developmental delays, which are often associated with autism spectrum disorder (ASD), is not well documented in low and middle-income countries. The UNICEF Multiple Indicator Cluster Survey (MICS) collects population-representative data on child health in many countries. OBJECTIVE:The objective of the study was to create a social developmental delay scale to estimate population-based early social delay relevant for ASD among pre-school children and identify characteristics associated with delay in a lower-middle-income country. METHODS:Data were from the Honduran 2019 MICS6. We created a 10-point social developmental delay proxy score (SDDPS) with scores ≥3 indicating possible delay. Using data from children 48-59-month-old (n = 1723), reported by primary caregivers, we estimated prevalence of social developmental delays; we used linear and Poisson regressions to characterize associations between SDDPS and socio-demographic characteristics. RESULTS:Applying the SDDPS, 4.6 % (95 % CI: 0.61 %:8.66 %) of 4-year-olds in Honduras had scores consistent with social developmental delays, indicated by 3 or more domains of concern relating to learning behavior and social interaction. Sixty-five percent had one or two domains of possible concern, with scores in domains relating to learning behavior being the most common. Differences across sex, age, urbanicity, and socioeconomic status were not significantly associated with delays in multivariate models. CONCLUSIONS:Existing surveys may be used to yield population-relevant data on social developmental delay in settings where more sensitive measures are not available at the population level. The SDDPS provided a preliminary estimate of the prevalence of social developmental delays in a lower-middle income Latin American country. The scale must be validated for use in this and other populations.

Use of telehealth assessments for toddlers at increased likelihood of autism spectrum disorder (ASD) began prior to the global COVID-19 pandemic; however, the value of telehealth assessments as an alternative to in-person assessment (IPA) became clearer during the pandemic. The Naturalistic Observation Diagnosis Assessment (NODA™), previously demonstrated as a valid and reliable tool to evaluate asynchronous behaviors for early diagnosis, was enhanced to add synchronous collection of behaviors to assist clinicians in making a differential diagnosis of ASD. This study was conducted to validate the information gathered through NODA-Enhanced (NODA-E™) as compared to a gold standard IPA. Forty-nine toddlers aged 16.0–32.1 months of age, recruited through community pediatric offices and a tertiary ASD clinic, participated in both NODA-E and IPA assessments. There was high agreement between the two assessment protocols for overall diagnosis (46 of 49 cases; 93.6

The study examined timing of autism spectrum disorder (ASD) identification in education versus health settings for 8-year-old children with ASD identified through records-based surveillance. The study also examined type of ASD symptoms noted within special education evaluations. Results indicated that children with records from only education sources had a median time to identification of ASD over a year later than children with records from health sources. Black children were more likely than White children to have records from only education sources. Restricted and repetitive behaviors were less frequently documented in educational evaluations resulting in developmental delay eligibility compared to specific ASD eligibility among children with ASD. Future research could explore strategies reduce age of identification in educational settings and increase equitable access to health evaluations.

Developmental delays, disorders, or disabilities (DDs) manifest in infancy and childhood and can limit a person's function throughout life* (1-3). To guide strategies to optimize health for U.S. children with DDs, CDC analyzed data from 44,299 participants in the 2014-2018 National Health Interview Survey (NHIS). Parents reported on 10 DDs,† functional abilities, health needs, and use of services. Among the approximately one in six (17.3%) U.S. children and adolescents aged 3-17 years (hereafter children) with one or more DDs, 5.7% had limited ability to move or play, 4.7% needed help with personal care, 4.6% needed special equipment, and 2.4% received home health care, compared with ≤1% for each of these measures among children without DDs. Children with DDs were two to seven times as likely as those without DDs to have taken prescription medication for ≥3 months (41.6% versus 8.4%), seen a mental health professional (30.6% versus 4.5%), a medical specialist (26.0% versus 12.4%), or a special therapist, such as a physical, occupational, or speech therapist, (25.0% versus 4.5%) during the past year, and 18 times as likely to have received special education or early intervention services (EIS) (41.9% versus 2.4%). These percentages varied by type of disability and by sociodemographic subgroup. DDs are common, and children with DDs often need substantial health care and services. Policies and programs that promote early identification of children with developmental delays and facilitate increased access to intervention services can improve health and reduce the need for services later in life.§ Sociodemographic inequities merit further investigation to guide public health action and ensure early and equitable access to needed care and services.

To appropriately route children with developmental disabilities to appropriate early interventions, those children must first be identified via developmental screening and/or developmental monitoring. Most early identification research emphasizes the relationship between developmental screening and Part C early intervention (EI) receipt for children birth to two. The relationship between developmental monitoring and service receipt is understudied, particularly for 3 to 5-year-old children are routed to Part B (619) early childhood special education services. Thus, this study used data from the National Surveys of Children’s Health (2007, 2012) to investigate the relationship between community-based health care providers (HCP) developmental screening and/or monitoring and the odds of early childhood special education receipt for preschool aged children (3 to 5). Across years, children whose HCP provided both developmental screening and monitoring, or developmental monitoring alone, had substantially greater odds of receiving special education compared to those who did not receive screening or monitoring. Receipt of developmental screening alone was associated with special education receipt in 2012, but not 2007. Developmental monitoring is understudied compared to developmental screening. Data presented here indicate that monitoring is associated with Part B 619 special education receipt and warrants further investigation to better understand how, with developmental screening, developmental monitoring might improve the identification of young children in need of 619 services. In particular, longitudinal analyses capturing data across systems, from screening and monitoring to assessment and service receipt, is needed to understand the effectiveness of monitoring for early identification and appropriate routing of children to relevant care systems.

Estimates from the 2019 American Community Survey (ACS) indicated that 15.2% of adults aged ≥18 years had at least one reported functional disability (1). Persons with disabilities are more likely than are those without disabilities to have chronic health conditions (2) and also face barriers to accessing health care (3). These and other health and social inequities have placed persons with disabilities at increased risk for COVID-19-related illness and death, yet they face unique barriers to receipt of vaccination (4,5). Although CDC encourages that considerations be made when expanding vaccine access to persons with disabilities,* few public health surveillance systems measure disability status. To describe COVID-19 vaccination status and intent, as well as perceived vaccine access among adults by disability status, data from the National Immunization Survey Adult COVID Module (NIS-ACM) were analyzed. Adults with a disability were less likely than were those without a disability to report having received ≥1 dose of COVID-19 vaccine (age-adjusted prevalence ratio [aPR] = 0.88; 95% confidence interval [CI] = 0.84-0.93) but more likely to report they would definitely get vaccinated (aPR = 1.86; 95% CI = 1.43-2.42). Among unvaccinated adults, those with a disability were more likely to report higher endorsement of vaccine as protection (aPR = 1.29; 95% CI = 1.16-1.44), yet more likely to report it would be or was difficult to get vaccinated than did adults without a disability (aPR = 2.69; 95% CI = 2.16-3.34). Reducing barriers to vaccine scheduling and making vaccination sites more accessible might improve vaccination rates among persons with disabilities.

National Surveys of Children’s Health (NSCH, 2016–2018) data were analyzed to determine if conjoint monitoring and screening showed stronger associations with children under 5 identified with ASD compared to monitoring alone, screening alone or no monitoring or screening; and investigate relationships between monitoring and screening across racial/ethnic subgroups. 86 of 332 children with ASD received their diagnosis in a timeframe suggesting potential monitoring and screening for identification purposes. Analyses showed that conjoint monitoring and screening and monitoring alone, but not screening alone, was associated with early identified ASD cases across race groups. Caution is warranted as interpreting NSCH monitoring and screening items solely for identification purposes is inaccurate in many cases. More research on monitoring with screening is needed.

Although autism spectrum disorder (ASD) is one of the most common neurodevelopmental disorders it is also one of the most heterogeneous conditions, making identification and diagnosis complex. The importance of a stable and consistent diagnosis cannot be overstated. An accurate diagnosis is the basis for understanding the individual and establishing an individualized treatment plan. We present those elements that should be included in any assessment for ASD and describe the ways in which ASD typically manifests itself at various developmental stages. The implications and challenges for assessment at different ages and levels of functioning are discussed.

The heterogeneity inherent in autism spectrum disorder (ASD) makes the identification and diagnosis of ASD complex. We survey a large number of diagnostic tools, including screeners and tools designed for in-depth assessment. We also discuss the challenges presented by overlapping symptomatology between ASD and other disorders and the need to determine whether a diagnosis of ASD or another diagnosis best explains the individual's symptoms. We conclude with a call to action for the next steps necessary for meeting the diagnostic challenges presented here to improve the diagnostic process and to help understand each individual's particular ASD profile.

The objectives of our study were to (a) report how many children met an autism spectrum disorder (ASD) surveillance definition but had no clinical diagnosis of ASD in health or education records and (b) evaluate differences in demographic, individual, and service factors between children with and without a documented ASD diagnosis. ASD surveillance was conducted in selected areas of Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin. Children were defined as having ASD if sufficient social and behavioral deficits and/or an ASD diagnosis were noted in health and/or education records. Among 4,498 children, 1,135 (25%) had ASD indicators without having an ASD diagnosis. Of those 1,135 children without a documented ASD diagnosis, 628 (55%) were not known to receive ASD services in public school. Factors associated with not having a clinical diagnosis of ASD were non-White race, no intellectual disability, older age at first developmental concern, older age at first developmental evaluation, special education eligibility other than ASD, and need for fewer supports. These results highlight the importance of reducing disparities in the diagnosis of children with ASD characteristics so that appropriate interventions can be promoted across communities. Autism Res 2020, 13: 464-473. © 2019 International Society for AutismResearch,Wiley Periodicals, Inc. LAY SUMMARY: Children who did not have a clinical diagnosis of autism spectrum disorder (ASD) documented in health or education records were more likely to be non-White and have fewer developmental problems than children with a clinical diagnosis of ASD. They were brought to the attention of healthcare providers at older ages and needed fewer supports than children with a clinical diagnosis of ASD. All children with ASD symptoms who meet diagnostic criteria should be given a clinical diagnosis so they can receive treatment specific to their needs.

An infant or toddler can begin the process of receiving Part C early intervention services by having a diagnosed condition with a high probability of developmental delay (Individuals with Disabilities Education Improvement Act, 2004). How states define those diagnosed conditions that begin the initiation process varies widely. Lists of diagnosed conditions were collected from state Part C websites and Part C coordinators for a descriptive analysis. Across 49 states, the District of Columbia, and 4 territories, a final list of 620 unique conditions was compiled. No single condition was listed by all jurisdictions. Hearing impairment was the condition listed by the most states (n = 38), followed by fetal alcohol syndrome (n = 34). Of the 620 conditions, 168 (27%) were listed by only 1 state, 554 (89%) were listed by fewer than 10 states, and 66 (11%) were listed by 10 or more states. Of these 66 conditions, 47 (71%) were listed by fewer than 20 states. Most of these 66 conditions (n = 48; 72.7%) had a prevalence of "very rare or rare," 8 (12%) were "common," 6 (9%) were "very common," and 4 (6.1%) were "unknown." The wide heterogeneity in the number and type of diagnostic conditions listed across states should be further investigated as it may represent imbalances in children with diagnosed conditions gaining access to Part C evaluations and individualized family service plans and potentially the services themselves across states. In addition, providing ready access to lists of diagnosed conditions is a simple step that could help states and Part C programs facilitate access to services.

In this response, we build on insights from Dr. David Foreman's commentary on our recent article “Socio-emotional Surveillance in Preschoolers: Monitoring and Screening Best Identify Children Who Need Mental Health Treatment.” In particular, we build on Foreman's insights that underidentification is likely related to clinician error, measurement error, and population properties by also including the role of community systems within which children are identified. We also provide frameworks for considering screening tools and developmental monitoring processes to help direct future research on this important topic.

In this response, we build on insights from Dr. David Foreman's commentary on our recent article Socio-emotional Surveillance in Preschoolers: Monitoring and Screening Best Identify Children Who Need Mental Health Treatment. In particular, we build on Foreman's insights that underidentification is likely related to clinician error, measurement error, and population properties by also including the role of community systems within which children are identified. We also provide frameworks for considering screening tools and developmental monitoring processes to help direct future research on this important topic.

Background: Autism spectrumdisorder (ASD) commonly presents with co-occurring medical conditions (CoCs). Little is known about patterns in CoCs in a time of rising ASD prevalence. Aims: To describe trends in number and type of documented CoCs in 8-year-old children with ASD. Methods: We used Autism and Developmental Disabilities Monitoring Network (ADDM) data, a multi-source active surveillance system monitoring ASD prevalence among 8-year-old children across the US. Data from surveillance years 2002, 2006, 2008, and 2010 were used to describe trends in count, categories, and individual CoCs. Results: Mean number of CoCs increased from 0.94 CoCs in 2002 to 1.06 CoCs in 2010 (p < 0.001). The percentage of children with ASD with any CoC increased from 44.5% to 56.4% (p < 0.001). CoCs with the greatest increases were in general developmental disability (10.4% to 14.5%), language disorder (18.9% to 23.6%), and motor developmental disability (10.5% to 15.6%). Sex modified the relationship between developmental (P = 0.02) and psychiatric (P < 0.001) CoCs and surveillance year. Race/ethnicity modified the relationship between neurological conditions (P = 0.04) and surveillance year. Conclusions: The increase in the percentage of children with ASD and CoCs may suggest the ASD phenotype has changed over time or clinicians are more likely to diagnose CoCs.

Authors conducted a systematic literature review on early identification steps leading at-risk young children to connect with Part C services. Authors classified data collection settings as primary (settings for general population) or specialized (settings for children at risk of developmental delay) and according to the phases of early identification in the study: (a) original population of children aged 0 to 6 years who had received Part C services, (b) screening and/or referral and/or developmental assessment from 0 through age 2 years, and (c) were deemed eligible and/or received Part C services. Authors identified 43 articles including at least two phases of the early identification process. The literature about connecting children to Part C early intervention (EI) is sparse and fragmented; few studies document the full process from community monitoring to service receipt. Results indicate opportunities for development of systems to better track and improve the identification of young children in need of EI.

Objective: Although data on publicly available special education are informative and offer a glimpse of trends in autism spectrum disorder (ASD) and use of educational services, using these data for population-based public health monitoring has drawbacks. Our objective was to evaluate trends in special education eligibility among 8-year-old children with ASD identified in the Autism and Developmental Disabilities Monitoring Network. Methods: We used data from 5 Autism and Developmental Disabilities Monitoring Network sites (Arizona, Colorado, Georgia, Maryland, and North Carolina) during 4 surveillance years (2002, 2006, 2008, and 2010) and compared trends in 12 categories of special education eligibility by sex and race/ethnicity. We used multivariable linear risk regressions to evaluate how the proportion of children with a given eligibility changed over time. Results: Of 6010 children with ASD, more than 36% did not receive an autism eligibility in special education in each surveillance year. From surveillance year 2002 to surveillance year 2010, autism eligibility increased by 3.6 percentage points ( P = .09), and intellectual disability eligibility decreased by 4.6 percentage points ( P < .001). A greater proportion of boys than girls had an autism eligibility in 2002 (56.3% vs 48.8%). Compared with other racial/ethnic groups, Hispanic children had the largest increase in proportion with autism eligibility from 2002 to 2010 (15.4%, P = .005) and the largest decrease in proportion with intellectual disability (–14.3%, P = .004). Conclusion: Although most children with ASD had autism eligibility, many received special education services under other categories, and racial/ethnic disparities persisted. To monitor trends in ASD prevalence, public health officials need access to comprehensive data collected systematically, not just special education eligibility.

Background: Widely recommended developmental surveillance methods include developmental monitoring (DM) and development screening (DS). Much research has been done on DS, but very little research has compared the effectiveness of DM and DS together. Objectives: To investigate the relationship between DM and DS in Part C early intervention (EI) service receipt. Methods: Authors used data from the 2007/2008 and 2011/2012 National Survey of Children's Health (NSCH). Authors report the prevalence of children aged 10 months to 3 years who received (a) DM only, (b) DS only, (c) both DM and DS, and (c) no DM or DS across survey years. Authors compare the odds of EI receipt across these groups. Results: During both periods, estimated EI receipt prevalence was higher for children receiving both DM and DS (8.38% in 2007/2008; 6.47% in 2011/2012) compared to children receiving no DM or DS (1.31% in 2007/2008; 1.92% in 2011/2012), DM alone (2.74% in 2007/2008; 2.70% in 2011/2012), or DS alone (3.59% in 2007/2008; 3.09% in 2011/2012) (for both time frames, p < .05). From 2007/2008 to 2011/2012, the proportion of children receiving DS only and both DM and DS increased, while children receiving DM only and no DM or DS decreased. Conclusions: Children receiving DM and DS together were more likely to receive EI compared to children receiving DM alone, DS alone, or neither DM nor DS. These findings support the AAP recommendations indicating that DM and DS are complementary strategies for improving early identification and linkage to EI for young children. Published by Elsevier Inc.