The downstream effects of COVID-19 on adolescent girls in the Peruvian Amazon: qualitative findings on how the pandemic affected education and reproductive health.

Due to COVID-19, schools were closed to mitigate disease spread. Past studies have shown that disruptions in education have unintended consequences for adolescents, including increasing their risk of school dropout, exploitation, gender-based violence, pregnancy and early unions. In Peru, the government closed schools from March 2020 to March 2022, declaring a national emergency that affected an estimated 8 million children.

Early Identification of Autism Spectrum Disorder Among Children Aged 4 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2020.

Problem/condition: Autism spectrum disorder (ASD).

Period Covered: 2020.

Description Of System: The Autism and Developmental Disabilities Monitoring Network is an active surveillance program that estimates prevalence and characteristics of ASD and monitors timing of ASD identification among children aged 4 and 8 years.

Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2020.

Problem/condition: Autism spectrum disorder (ASD).

Period Covered: 2020.

Description Of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years.

Statewide county-level autism spectrum disorder prevalence estimates-seven U.S. states, 2018.

Purpose: Autism spectrum disorder (ASD) prevalence information is necessary for identifying community needs such as addressing disparities in identification and services.

Methods: Seven Autism and Developmental Disabilities Monitoring (ADDM) Network sites participated in a pilot project to link statewide health and education data to generate statewide and county-level prevalence estimates for a broader age range for their states for the first time.

Results: Statewide prevalence of ASD for ages 3-21 years in 2018 ranged from 1.

Interventions to increase early infant diagnosis of HIV infection: A systematic review and meta-analysis.

Objectives: Early infant diagnosis (EID) of HIV infection increases antiretroviral therapy initiation, which reduces pediatric HIV-related morbidity and mortality. This review aims to critically appraise the effects of interventions to increase uptake of early infant diagnosis.

Design: This is a systematic review and meta-analysis of interventions to increase the EID of HIV infection.

Early Identification of Autism Spectrum Disorder Among Children Aged 4 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2018.

Problem/condition: Autism spectrum disorder (ASD).

Period Covered: 2018.

Description Of System: The Autism and Developmental Disabilities Monitoring Network is an active surveillance program that estimates ASD prevalence and monitors timing of ASD identification among children aged 4 and 8 years.

Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2018.

Problem/condition: Autism spectrum disorder (ASD).

Period Covered: 2018.

Description Of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts active surveillance of ASD.

Progress and Disparities in Early Identification of Autism Spectrum Disorder: Autism and Developmental Disabilities Monitoring Network, 2002-2016.

Objective: Early identification can improve outcomes for children with autism spectrum disorder (ASD). We sought to assess changes in early ASD identification over time and by co-occurring intellectual disability (ID) and race/ethnicity.

Method: Using data for 2002-2016 from a biennial population-based ASD surveillance program among 8-year-old children in the United States, we defined identification as a child's earliest recorded ASD diagnosis or special education eligibility.

Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2016.

Problem/condition: Autism spectrum disorder (ASD).

Period Covered: 2016.

Description Of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years whose parents or guardians live in 11 ADDM Network sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin).

Early Identification of Autism Spectrum Disorder Among Children Aged 4 Years - Early Autism and Developmental Disabilities Monitoring Network, Six Sites, United States, 2016.

Problem/condition: Autism spectrum disorder (ASD).

Period Covered: 2016.

Description Of System: The Early Autism and Developmental Disabilities Monitoring (Early ADDM) Network, a subset of the overall ADDM Network, is an active surveillance program that estimates ASD prevalence and monitors early identification of ASD among children aged 4 years.

Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 4 Years - Early Autism and Developmental Disabilities Monitoring Network, Seven Sites, United States, 2010, 2012, and 2014.

Problem/condition: Autism spectrum disorder (ASD) is estimated to affect up to 3% of children in the United States. Public health surveillance for ASD among children aged 4 years provides information about trends in prevalence, characteristics of children with ASD, and progress made toward decreasing the age of identification of ASD so that evidence-based interventions can begin as early as possible.

Period Covered: 2010, 2012, and 2014.

Optimizing Corpus Creation for Training Word Embedding in Low Resource Domains: A Case Study in Autism Spectrum Disorder (ASD).

Automating the extraction of behavioral criteria indicative of Autism Spectrum Disorder (ASD) in electronic health records (EHRs) can contribute significantly to the effort to monitor the condition. Word embedding algorithms such as Word2Vec can encode semantic meanings of words in vectors and assist in automated vocabulary discovery from EHRs. However, text available for training word embeddings for ASD is miniscule compared to the billions of tokens typically used.

Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2012.

Problem/condition: Autism spectrum disorder (ASD).

Period Covered: 2012.

Description Of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that provides estimates of the prevalence and characteristics of ASD among children aged 8 years whose parents or guardians reside in 11 ADDM Network sites in the United States (Arkansas, Arizona, Colorado, Georgia, Maryland, Missouri, New Jersey, North Carolina, South Carolina, Utah, and Wisconsin).

Automated Extraction of Diagnostic Criteria From Electronic Health Records for Autism Spectrum Disorders: Development, Evaluation, and Application.

Background: Electronic health records (EHRs) bring many opportunities for information utilization. One such use is the surveillance conducted by the Centers for Disease Control and Prevention to track cases of autism spectrum disorder (ASD). This process currently comprises manual collection and review of EHRs of 4- and 8-year old children in 11 US states for the presence of ASD criteria.

Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2014.

Problem/condition: Autism spectrum disorder (ASD).

Period Covered: 2014.

Description Of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that provides estimates of the prevalence of autism spectrum disorder (ASD) among children aged 8 years whose parents or guardians reside within 11 ADDM sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin).

Characterizing Health Disparities in the Age of Autism Diagnosis in a Study of 8-Year-Old Children.

The diagnosis of autism spectrum disorder (ASD) is often delayed from the time of noted concerns to the actual diagnosis. The current study used child- and family-level factors to identify homogeneous classes in a surveillance-based sample (n = 2303) of 8-year-old children with ASD. Using latent class analysis, a 5-class model emerged and the class memberships were examined in relation to the child's median age at ASD diagnosis.

Recognition of clinical characteristics for population-based surveillance of fetal alcohol syndrome.

Background: The diagnosis of fetal alcohol syndrome (FAS) rests on identification of characteristic facial, growth, and central nervous system (CNS) features. Public health surveillance of FAS depends on documentation of these characteristics. We evaluated if reporting of FAS characteristics is associated with the type of provider examining the child.

Prevalence of Caesarean sections in Enugu, southeast Nigeria: Analysis of data from the Healthy Beginning Initiative.

Background: In order to meet the Sustainable Development Goal to decrease maternal mortality, increased access to obstetric interventions such as Caesarean sections (CS) is of critical importance. As a result of women's limited access to routine and emergency obstetric services in Nigeria, the country is a major contributor to the global burden of maternal mortality. In this analysis, we aim to establish rates of CS and determine socioeconomic or medical risk factors associated with having a CS in Enugu, southeast Nigeria.

Autism spectrum disorder reporting in lower socioeconomic neighborhoods.

Utilizing surveillance data from five sites participating in the Autism and Developmental Disabilities Monitoring Network, we investigated contributions of surveillance subject and census tract population sociodemographic characteristics on variation in autism spectrum disorder ascertainment and prevalence estimates from 2000 to 2008 using ordinal hierarchical models for 2489 tracts. Multivariable analyses showed a significant increase in ascertainment of autism spectrum disorder cases through both school and health sources, the optimal ascertainment scenario, for cases with college-educated mothers (adjusted odds ratio = 1.06, 95% confidence interval = 1.

DSM Criteria that Best Differentiate Intellectual Disability from Autism Spectrum Disorder.

Clinical characteristics of autism spectrum disorder (ASD) and intellectual disability (ID) overlap, creating potential for diagnostic confusion. Diagnostic and statistical manual of mental disorders (DSM) criteria that best differentiate children with ID and some ASD features from those with comorbid ID and ASD were identified. Records-based surveillance of ASD among 8-year-old children across 14 US populations ascertained 2816 children with ID, with or without ASD.

Autism spectrum disorder prevalence and associations with air concentrations of lead, mercury, and arsenic.

Lead, mercury, and arsenic are neurotoxicants with known effects on neurodevelopment. Autism spectrum disorder (ASD) is a neurodevelopmental disorder apparent by early childhood. Using data on 4486 children with ASD residing in 2489 census tracts in five sites of the Centers for Disease Control and Prevention's Autism and Developmental Disabilities Monitoring (ADDM) Network, we used multi-level negative binomial models to investigate if ambient lead, mercury, and arsenic concentrations, as measured by the US Environmental Protection Agency National-Scale Air Toxics Assessment (EPA-NATA), were associated with ASD prevalence.

Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years--Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2012.

Problem/condition: Autism spectrum disorder (ASD).

Period Covered: 2012.

Description Of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that provides estimates of the prevalence and characteristics of ASD among children aged 8 years whose parents or guardians reside in 11 ADDM Network sites in the United States (Arkansas, Arizona, Colorado, Georgia, Maryland, Missouri, New Jersey, North Carolina, South Carolina, Utah, and Wisconsin).

Prevalence and Characteristics of Autism Spectrum Disorder Among 4-Year-Old Children in the Autism and Developmental Disabilities Monitoring Network.

Objective: Early identification of children with autism spectrum disorder (ASD) facilitates timely access to intervention services. Yet, few population-based data exist on ASD identification among preschool-aged children. The authors aimed to describe ASD prevalence and characteristics among 4-year-old children in 5 of 11 sites participating in the 2010 Autism and Developmental Disabilities Monitoring Network.

Population-based prevalence of malaria among pregnant women in Enugu State, Nigeria: the Healthy Beginning Initiative.

Background: Malaria adversely affects pregnant women and their fetuses or neonates. Estimates of the malaria burden in pregnant women based on health facilities often do not present a true picture of the problem due to the low proportion of women delivering at these facilities in malaria-endemic regions.

Methods: Data for this study were obtained from the Healthy Beginning Initiative using community-based sampling.