PROBLEM/CONDITION: An estimated 450,000 enteric illnesses, 5,000 hospitalizations, and 76 deaths associated with animal contact occur each year in the United States. Enteric illnesses are diseases that affect the stomach or intestines and cause symptoms, such as diarrhea, nausea, or vomiting, and are typically transmitted from animals to humans through the fecal-oral route. Humans might encounter animal feces or bodily fluids through contact with the animal itself, the animal's environment, or the animal's food or water. Although outbreak-associated illnesses account for a small subset of all enteric illnesses linked to animal contact, data obtained from outbreak surveillance offer insights into the underlying epidemiologic factors contributing to illnesses, including the pathogens, animals, pathogen-animal category pairs, and settings of outbreaks associated with animal contact. PERIOD COVERED: 2009-2021. DESCRIPTION OF SYSTEM: The Animal Contact Outbreak Surveillance System (ACOSS) was launched in 2009 in conjunction with the National Outbreak Reporting System (NORS), a web-based platform that includes reports of foodborne and waterborne outbreaks as well as enteric disease outbreaks transmitted by contact with environmental sources, infected persons or animals, or unknown modes. ACOSS encompasses animal contact outbreaks that are reported to CDC through NORS. Local, state, and territorial health departments voluntarily report animal contact outbreaks, which are defined as two or more enteric illnesses associated with a common animal source. Outbreaks can involve single or multiple states; CDC staff typically report multistate outbreaks on behalf of state and territorial health departments. ACOSS defines an animal source as an animal (including domestic and wild animals); an animal's feces or bodily fluids (except milk and other fluids consumed as food, which are defined as foodborne sources); an animal's fur, hair, feathers, scales, or skin; an animal's food; or an animal's environment, which includes places in which it lives and roams. RESULTS: During 2009-2021, a total of 557 animal contact outbreaks of enteric disease were reported in the United States through ACOSS, accounting for 14,377 illnesses, 2,656 hospitalizations, and 22 deaths. Exposures were reported in all 50 states, Washington, DC, and Puerto Rico. During the period there were 393 single-state outbreaks and 164 multistate outbreaks. Although multistate outbreaks comprised 29% of all outbreaks reported through ACOSS, they accounted for 80% of illnesses, 88% of hospitalizations, and 82% of deaths. Among 474 outbreaks with a confirmed single etiology, Salmonella was the most common cause of outbreaks (248 outbreaks [52%]); these outbreaks accounted for the most outbreak-associated illnesses (11,822 [85%]), hospitalizations (2,393 [91%]), and deaths (17 [77%]). Cryptosporidium (108 outbreaks [23%]) was the second leading cause of confirmed, single etiology outbreaks, followed by Escherichia coli (63 [13%]) and Campylobacter (52 [11%]). The most common exposure locations among outbreaks with a single location reported were private home (168 [40%]) and farm or dairy (89 [21%]). Among 467 outbreaks for which an animal source could be attributed to a single animal category, ruminants (171 [37%]) were the most implicated animal category (with 75% of ruminant outbreaks attributed to cattle), followed by poultry (155 [33%]) and turtles (39 [12%]). Poultry were associated with the most outbreak-associated illnesses (9,095 [66% of illnesses resulting from outbreaks attributed to a single animal category]), hospitalizations (1,804 [70%]), and deaths (15 [83%]). Most outbreaks (130 [84% of all poultry outbreaks]) attributed to poultry had private home reported as at least one of the exposure locations (i.e., backyard poultry) and were responsible for nearly all poultry-associated illnesses (8,897 [98%]). The most common confirmed pathogen-animal pair was Salmonella and poultry (132 outbreaks), followed by Cryptosporidium and ruminants (88), and Salmonella and turtles (37). Salmonella and poultry accounted for the highest number of outbreak-associated illnesses (8,965), hospitalizations (1,790), and deaths (15). INTERPRETATION: Animal contact outbreaks of enteric disease reported through ACOSS provide insights into the animals and etiologies causing outbreak-associated enteric illnesses as well as other outbreak characteristics, such as settings in which outbreaks occur. These findings can guide public health actions, developed in collaboration with specific populations (e.g., backyard poultry owners) and including interventions tailored to settings, such as private homes and farms or dairies, that are more commonly associated with animal contact outbreaks. The high proportion of outbreaks occurring in private homes identifies a potential gap in proper hygiene and enteric disease prevention knowledge among animal owners, including owners of backyard poultry, which might be considered by owners to be pets rather than livestock. Settings and populations linked to ruminants, poultry, and turtles (particularly cattle, backyard poultry, and small turtles, respectively) are important targets for public health interventions because of the high number of outbreaks and outbreak-associated illnesses associated with these animal sources. Furthermore, the disproportionate impact of multistate outbreaks reiterates the importance of a collaborative national response but also might reflect limited resources to investigate or report animal contact outbreaks at state and local levels. PUBLIC HEALTH ACTION: Public health partners should continue to report animal contact outbreaks through ACOSS to inform evidence-based interventions tailored to specific animals, pathogens, populations, and settings. Strengthening the capacity of local, state, and territorial health departments to investigate and report animal contact outbreaks is critical to improving surveillance of animal contact outbreaks. Close collaboration between state, local, and Federal public health and agricultural partners nationwide is also key in investigating and responding to multistate outbreaks. An integrated One Health approach that leverages the expertise of animal, environmental, and public health partners can facilitate successful public health interventions aimed at preventing animal contact outbreaks.

PROBLEM/CONDITION: Autism spectrum disorder (ASD). PERIOD COVERED: 2022. 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. In 2022, a total of 16 sites (located in Arizona, Arkansas, California, Georgia, Indiana, Maryland, Minnesota, Missouri, New Jersey, Pennsylvania, Puerto Rico, Tennessee, Texas [two sites: Austin and Laredo], Utah, and Wisconsin) conducted surveillance for ASD among children aged 4 and 8 years and suspected ASD among children aged 4 years. Surveillance included children who lived in the surveillance area at any time during 2022. Children were classified as having ASD if they ever received 1) an ASD diagnostic statement in a comprehensive developmental evaluation, 2) autism special education eligibility, or 3) an ASD International Classification of Diseases, Ninth Revision (ICD-9) code in the 299 range or International Classification of Diseases, Tenth Revision (ICD-10) code of F84.0, F84.3, F84.5, F84.8, or F84.9. Children aged 4 years were classified as having suspected ASD if they did not meet the case definition for ASD but had an evaluator's suspicion of ASD documented in a comprehensive developmental evaluation. RESULTS: Among children aged 8 years in 2022, ASD prevalence was 32.2 per 1,000 children (one in 31) across the 16 sites, ranging from 9.7 in Texas (Laredo) to 53.1 in California. The overall observed prevalence estimate was similar to estimates calculated using Bayesian hierarchical and random effects models. ASD was 3.4 times as prevalent among boys (49.2) than girls (14.3). Overall, ASD prevalence was lower among non-Hispanic White (White) children (27.7) than among Asian or Pacific Islander (A/PI) (38.2), American Indian or Alaska Native (AI/AN) (37.5), non-Hispanic Black or African American (Black) (36.6), Hispanic or Latino (Hispanic) (33.0), and multiracial children (31.9). No association was observed between ASD prevalence and neighborhood median household income (MHI) at 11 sites; higher ASD prevalence was associated with lower neighborhood MHI at five sites.Record abstraction was completed for 15 of the 16 sites for 8,613 children aged 8 years who met the ASD case definition. Of these 8,613 children, 68.4% had a documented diagnostic statement of ASD, 67.3% had a documented autism special education eligibility, and 68.9% had a documented ASD ICD-9 or ICD-10 code. All three elements of the ASD case definition were present for 34.6% of children aged 8 years with ASD.Among 5,292 (61.4% of 8,613) children aged 8 years with ASD with information on cognitive ability, 39.6% were classified as having an intellectual disability. Intellectual disability was present among 52.8% of Black, 50.0% of AI/AN, 43.9% of A/PI, 38.8% of Hispanic, 32.7% of White, and 31.2% of multiracial children with ASD. The median age of earliest known ASD diagnosis was 47 months and ranged from 36 months in California to 69.5 months in Texas (Laredo).Cumulative incidence of ASD diagnosis or eligibility by age 48 months was higher among children born in 2018 (aged 4 years in 2022) than children born in 2014 (aged 8 years in 2022) at 13 of the 15 sites that were able to abstract records. Overall cumulative incidence of ASD diagnosis or eligibility by age 48 months was 1.7 times as high among those born in 2018 compared with those born in 2014 and ranged from 1.4 times as high in Arizona and Georgia to 3.1 times as high in Puerto Rico. Among children aged 4 years, for every 10 children meeting the case definition of ASD, one child met the definition of suspected ASD.Children with ASD who were born in 2018 had more evaluations and identification during ages 0-4 years than children with ASD who were born in 2014 during the 0-4 years age window, with an interruption in the pattern in early 2020 coinciding with onset of the COVID-19 pandemic.Overall, 66.5% of children aged 8 years with ASD had a documented autism test. Use of autism tests varied widely across sites: 24.7% (New Jersey) to 93.5% (Puerto Rico) of children aged 8 years with ASD had a documented autism test in their records. The most common tests documented for children aged 8 years were the Autism Diagnostic Observation Schedule, Autism Spectrum Rating Scales, Childhood Autism Rating Scale, Gilliam Autism Rating Scale, and Social Responsiveness Scale. INTERPRETATION: Prevalence of ASD among children aged 8 years was higher in 2022 than previous years. ASD prevalence was higher among A/PI, Black, and Hispanic children aged 8 years than White children aged 8 years, continuing a pattern first observed in 2020. A/PI, Black, and Hispanic children aged 8 years with ASD were also more likely than White or multiracial children with ASD to have a co-occurring intellectual disability. Identification by age 48 months was higher among children born in 2018 compared with children born in 2014, suggesting increased early identification consistent with historical patterns. PUBLIC HEALTH ACTION: Increased identification of autism, particularly among very young children and previously underidentified groups, underscores the increased demand and ongoing need for enhanced planning to provide equitable diagnostic, treatment, and support services for all children with ASD. The substantial variability in ASD identification across sites suggests opportunities to identify and implement successful strategies and practices in communities to ensure all children with ASD reach their potential.

Forest changes, human population dynamics, and meteorologic conditions have been associated with zoonotic Ebolavirus spillover into humans. High-resolution spatial data for those variables can be used to produce estimates of spillover potential and assess possible annual changes. We developed a model of Ebolavirus spillover during 2001-2021, accounting for variables measured across multiple spatial and temporal scales. We estimated the annual relative odds of Ebolavirus spillover during 2021 and 2022. The highest relative spillover odds estimates occurred in patches that closely followed the spatial distribution of forest loss and fragmentation. Regions throughout equatorial Africa had increased spillover estimates related to changes in forests and human populations. Spillover events in 2022 occurred in locations in the top 0.1% of overall spillover odds estimates or where estimates increased from 2021 to 2022. This model can be used to preemptively target surveillance to identify outbreaks, mitigate disease spread, and educate the public on risk factors for infection.

INTRODUCTION: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic, complex illness. No diagnostic tests exist; illness evaluation relies on medical history, physical exam, and laboratory tests. While more is known about ME/CFS in adults, it can affect children and adolescents as a chronic condition. METHODS: We implemented an ME/CFS pediatric educational activity (diagnosis, management, and communication) with medical, physician assistant, and nursing students at one university and with medical students at a second university. Pretests, two videos and slides, and posttests were completed in approximately 40 minutes. Evaluation included quantitative and qualitative measures for knowledge, attitudes, beliefs, confidence, and clinical information about ME/CFS. RESULTS: The first group included 31 students who reported low familiarity and clinical exposure to ME/CFS. At posttest, 25 students (81%) recognized ME/CFS as a medical condition compared to seven (23%) at pretest. Using 0-5 scales, mean pretest-to-posttest ability to diagnose increased from 1.0 to 3.5, and confidence to communicate increased from 1.4 to 3.9. The second group, including 26 students pretest and 19 posttest, also reported low familiarity and clinical exposure The posttest showed increased self-rated ability to diagnose (pretest M: 0.6, posttest M: 3.3) and confidence to communicate (pretest M: 1.4, posttest M: 3.7). Qualitative feedback for this group showed understanding of pediatric ME/CFS symptoms, management, and communication. DISCUSSION: This educational activity increased knowledge of ME/CFS as self-reported ability to make a diagnosis and increased confidence to communicate about pediatric ME/CFS. Participating students showed changes in attitudes towards ME/CFS as a medical condition.

BACKGROUND: Polybrominated diphenyl ethers (PBDEs), synthetic chemicals previously used as flame retardants in commercial products, impact human behaviors, mood symptoms and cognitive abilities. OBJECTIVE: We estimated the association of gestational PBDE serum concentrations with early adolescent self- and caregiver-reported ratings of executive function in a prospective pregnancy and birth cohort. METHODS: We measured gestational serum concentrations of five PBDE congeners and created a summary exposure variable (∑(5)BDE: 28, -47, -99, -100 and -153). At age 12 years, we assessed executive function for 237 adolescents using self- and caregiver-reports with the Behavior Rating Inventory of Executive Functioning (BRIEF-2). We used multivariable linear regression models to estimate covariate-adjusted associations of lipid standardized, log(10)-transformed gestational PBDE concentrations with BRIEF-2 T-scores. We evaluated potential effect measure modification (EMM) of sex by examining sex-stratified regression models. RESULTS: As higher scores indicate greater deficits in executive function, gestational PBDE concentrations were positively associated with adolescent-reported BRIEF-2 T-scores for Global Executive Composite (BDE-28: β = 6.31 (95%CI: 2.59, 10.03), BDE-47: (β = 3.32 (95%CI: 0.1, 6.54), ∑(5)BDE: (β = 3.70 (95%CI: 0.37, 7.03), Behavior Regulation Index (BDE-28: β = 5.36 (95%CI: 1.56, 9.15), BDE-99: β = 3.53 (95%CI: 0.33, 6.74), ∑(5)BDE: β = 3.93 (95%CI: 0.57, 7.3), Emotion Regulation Index (BDE-28: β = 4.76 (95%CI: 0.88, 8.64) and the Cognitive Regulation Index (BDE-28: β = 6.69 (95%CI: 3.08, 10.31), BDE-47: β = 3.45 (95%CI: 0.3, 6.59), ∑(5)BDE: β = 3.57 (95%CI: 0.32, 6.82) and several other scales. We observed stronger associations with gestational PBDE concentrations for all congeners among males, especially for the caregiver-rated scales (all EMM p-values <0.1). DISCUSSION: This study provides evidence that gestational PBDE serum concentrations may adversely influence offspring executive function during adolescence.

Some studies report increased prevalence of autism spectrum disorder (ASD) and associated symptoms with prenatal cannabis exposure. We examined whether associations of maternal cannabis use from 3 months preconception through delivery ("peripregnancy") with behavior and development in the offspring varied with the presence of ASD symptoms. Children ages 30-68 months with ASD symptoms (i.e., met study criteria for ASD or had ASD symptoms on standardized assessments or community ASD diagnosis, N = 2734) and without ASD symptoms (other developmental delay/disorders or general population sample, N = 3454) were evaluated with the Child Behavior Checklist and Mullen Scales of Early Learning. We examined cannabis use during three time periods: peripregnancy, pregnancy, and only preconception. Peripregnancy cannabis exposure was reported for 6.0% of children with and 4.6% of children without ASD symptoms. Preconception-only cannabis use (versus no use) was associated with more aggressive behavior, emotional reactivity, and sleep problems in children with ASD symptoms, but not in children without ASD symptoms. Cannabis use during pregnancy was associated with increased attention and sleep problems in children with ASD symptoms; these associations did not differ significantly by ASD symptoms. Peripregnancy cannabis use was not associated with child developmental abilities regardless of ASD symptoms. In summary, associations of peripregnancy cannabis use with some behavioral outcomes differed in children with and without ASD symptoms. With rising cannabis use among pregnant women, future studies that examine a range of developmental risks associated with timing and patterns of cannabis use prior to conception as well as during pregnancy could inform clinical guidance.

BACKGROUND: Private wells use groundwater as their source and their drinking water quality is unregulated in the United States at the federal level. Due to the lack of water quality regulations, those reliant on private wells have the responsibility of ensuring that the water is safe to drink. Where extreme weather is projected to increase with climate change, contamination due to climate-related hazards adds further layers of complexity for those relying on private wells. We sought to characterize community-level climate-related hazards and vulnerability for persons dependent on private wells in the continental United States (CONUS). Additional objectives of this work were to quantify the burden to private well water communities by climate regions and demographic groups. METHODS: Grounded in the latest climate change framework and private well water literature, we created the Private Well Water Climate Impact Index (PWWCII). We searched the literature and identified nationally consistent, publicly available, sub-county data to build Overall, Drought, Flood, and Wildfire PWWCIIs at the national and state scales. We adapted the technical construction of this relative index from the California Communities Environmental Health Screening Tool (CalEnviroScreen 4.0). RESULTS: The distribution of climate-related impact census tracts varied across CONUS by nationally-normed PWWCII type. Compared to the Southeast where the majority of the 2010 estimated U.S. private well water population lived, the estimated persons dependent upon private well water living in the West had an increased odds of living in higher impact census tracts for the Overall, Drought, and Wildfire PWWCIIs across CONUS. Compared to non-Hispanic White persons, non-Hispanic American Indian and Alaska Native (AI/AN) persons had an increased odds of living in higher impact census tracts for all four PWWCII types across CONUS. CONCLUSIONS: The PWWCII fills a gap as it provides a baseline understanding of potential climate-related impacts to communities reliant on private well water.

Elevated body mass index (BMI) has been linked to severe influenza illness and impaired vaccine immunogenicity, but the relationship between BMI and clinical vaccine effectiveness (VE) is less well described. This secondary analysis of data from a test-negative study of outpatients with acute respiratory illness assessed BMI and VE against medically attended, PCR-confirmed influenza over seven seasons (2011-12 through 2017-18). Vaccination status was determined from electronic medical records (EMR) and self-report; BMI was estimated from EMR-documented height and weight categorized for adults as obesity (≥ 30 kg/m(2)), overweight (25-29 kg/m(2)), or normal and for children based on standardized z-scales. Current season VE by virus type/subtype was estimated separately for adults and children. Pooled VE for all seasons was calculated as 1-adjusted odds ratios from logistic regression with an interaction term for BMI and vaccination. Among 28,089 adults and 12,380 children, BMI category was not significantly associated with VE against outpatient influenza for any type/subtype. Adjusted VE against A/H3N2, A/H1N1pdm09, and B in adults ranged from 16-31, 46-54, and 44-57%, and in children from 29-34, 57-65, and 50-55%, respectively, across the BMI categories. Elevated BMI was not associated with reduced VE against laboratory confirmed, outpatient influenza illness.

BACKGROUND: Endocrine disrupting chemicals (EDCs) are widely used compounds with the potential to affect child neurodevelopmental outcomes including autism spectrum disorders (ASD). We aimed to examine the urinary concentrations of biomarkers of EDCs, including phthalates, phenols, and parabens, and investigate whether exposure during early infancy was associated with increased risk of later ASD or other non-typical development (Non-TD) or adverse cognitive development. METHODS: This analysis included infants from the Markers of Autism Risks in Babies-Learning Early Signs (MARBLES) study, a high-risk ASD cohort (n = 148; corresponding to 188 urine samples). Thirty-two EDC biomarkers were quantified in urine among infants 3 and/or 6 months of age. Trends in EDC biomarker concentrations were calculated using least square geometric means. At 36 months of age, children were clinically classified as having ASD (n = 36), nontypical development (Non-TD; n = 18), or typical development (TD; n = 81) through a clinical evaluation. Trinomial logistic regression analysis was used to test the associations between biomarkers with ASD, or Non-TD, as compared to children with TD. In single analyte analysis, generalized estimating equations were used to investigate the association between each EDC biomarkers and longitudinal changes in cognitive development using the Mullen Scales of Early Learning (MSEL) over the four assessment time points (6, 12, 24, and 36 months of age). Additionally, quantile g-computation was used to test for a mixture effect. RESULTS: EDC biomarker concentrations generally decreased over the study period, except for mono-2-ethyl-5-carboxypentyl terephthalate. Overall, EDC biomarkers at 3 and/or 6 months of age were not associated with an increased risk of ASD or Non-TD, and a few showed significant inverse associations. However, when assessing longitudinal changes in MSEL scores over the four assessment time points, elevated monoethyl phthalate (MEP) was significantly associated with reduced scores in the composite score (β = -0.16, 95% CI: 0.31, -0.02) and subscales of fine motor skills (β = -0.09, 95%CI: 0.17, 0.00), and visual reception (β = -0.11, 95% CI: 0.23, 0.01). Additionally, the sum of metabolites of di (2-ethylhexyl) terephthalate (ƩDEHTP) was associated with poorer visual reception (β = -0.09, 95% CI: 0.16, -0.02), and decreased composite scores (β = -0.11, 95% CI: 0.21, -0.01). Mixtures analyses using quantile g-computation analysis did not show a significant association between mixtures of EDC biomarkers and MSEL subscales or composite scores. CONCLUSION: These findings highlight the potential importance of infant exposures on cognitive development. Future research can help further investigate whether early infant exposures are associated with longer-term deficits and place special attention on EDCs with increasing temporal trends and whether they may adversely affect neurodevelopment.

Antimicrobial resistance (AMR) is a world-wide public health threat that is projected to lead to 10 million annual deaths globally by 2050. The AMR public health issue has led to the development of action plans to combat AMR, including improved antimicrobial stewardship, development of new antimicrobials, and advanced monitoring. The National Antimicrobial Resistance Monitoring System (NARMS) led by the United States (U.S) Food and Drug Administration along with the U.S. Centers for Disease Control and U.S. Department of Agriculture has monitored antimicrobial resistant bacteria in retail meats, humans, and food animals since the mid 1990's. NARMS is currently exploring an integrated One Health monitoring model recognizing that human, animal, plant, and environmental systems are linked to public health. Since 2020, the U.S. Environmental Protection Agency has led an interagency NARMS environmental working group (EWG) to implement a surface water AMR monitoring program (SWAM) at watershed and national scales. The NARMS EWG divided the development of the environmental monitoring effort into five areas: (i) defining objectives and questions, (ii) designing study/sampling design, (iii) selecting AMR indicators, (iv) establishing analytical methods, and (v) developing data management/analytics/metadata plans. For each of these areas, the consensus among the scientific community and literature was reviewed and carefully considered prior to the development of this environmental monitoring program. The data produced from the SWAM effort will help develop robust surface water monitoring programs with the goal of assessing public health risks associated with AMR pathogens in surface water (e.g., recreational water exposures), provide a comprehensive picture of how resistant strains are related spatially and temporally within a watershed, and help assess how anthropogenic drivers and intervention strategies impact the transmission of AMR within human, animal, and environmental systems.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

Lesbian, gay, and bisexual (LGB) youths continue to experience more violence victimization and suicide risk than heterosexual youths; however, few studies have examined whether the proportion of LGB youths affected by these outcomes has varied over time, and no studies have assessed such trends in a nationally representative sample. This report analyzes national trends in violence victimization and suicide risk among high school students by self-reported sexual identity (LGB or heterosexual) and evaluates differences in these trends among LGB students by sex (male or female) and race/ethnicity (non-Hispanic black, non-Hispanic white, or Hispanic). Data for this analysis were derived from the 2015, 2017, and 2019 cycles of CDC's Youth Risk Behavior Survey (YRBS), a cross-sectional, school-based survey conducted biennially since 1991. Logistic regression models assessed linear trends in prevalence of violence victimization and indicators of suicide risk among LGB and heterosexual students during 2015-2019; in subsequent models, sex-stratified (controlling for race/ethnicity and grade) and race/ethnicity-stratified (controlling for sex and grade) linear trends were examined for students self-identifying as LGB during 2015-2019. Results demonstrated that LGB students experienced more violence victimization and reported more suicide risk behaviors than heterosexual youths. Among LGB youths, differences in the proportion reporting violence victimization and suicide risk by sex and race/ethnicity were found. Across analyses, very few linear trends in these outcomes were observed among LGB students. Results highlight the continued need for comprehensive intervention strategies within schools and communities with the express goal of reducing violence victimization and preventing suicide risk behaviors among LGB students.

Intellectual disability (ID) commonly co-occurs in children with autism. Although diagnostic criteria for ID require impairments in both cognitive and adaptive functioning, most population-based estimates of the frequency of co-occurring ID in children with autism-including studies of racial and ethnic disparities in co-occurring autism and ID-base the definition of ID solely on cognitive scores. The goal of this analysis was to examine the effect of including both cognitive and adaptive behavior criteria on estimates of co-occurring ID in a well-characterized sample of 2- to 5-year-old children with autism. Participants included 3264 children with research or community diagnoses of autism enrolled in the population-based Study to Explore Early Development (SEED) phases 1-3. Based only on Mullen Scales of Early Learning (MSEL) composite cognitive scores, 62.9% (95% confidence interval [CI]: 61.1, 64.7%) of children with autism were estimated to have co-occurring ID. After incorporating Vineland Adaptive Behavior Scales, Second Edition (VABS-II) composite or domains criteria, co-occurring ID estimates were reduced to 38.0% (95% CI: 36.2, 39.8%) and 45.0% (95% CI: 43.1, 46.9%), respectively. The increased odds of meeting ID criteria observed for non-Hispanic (NH) Black and Hispanic children relative to NH White children when only MSEL criteria were used were substantially reduced, though not eliminated, after incorporating VABS-II criteria and adjusting for selected socioeconomic variables. This study provides evidence for the importance of considering adaptive behavior as well as socioeconomic disadvantage when describing racial and ethnic disparities in co-occurring ID in epidemiologic studies of autism.

BACKGROUND: Eating behaviors are controlled by the neuroendocrine system. Whether endocrine disrupting chemicals have the potential to affect eating behaviors has not been widely studied in humans. We investigated whether maternal and paternal preconception and maternal pregnancy urinary phthalate biomarker and bisphenol-A (BPA) concentrations were associated with children's eating behaviors. METHODS: We used data from mother-father-child triads in the Preconception Environmental exposure And Childhood health Effects (PEACE) Study, an ongoing prospective cohort study of children aged 6-13 years whose parent(s) previously enrolled in a fertility clinic-based prospective preconception study. We quantified urinary concentrations of 11 phthalate metabolites and BPA in parents' urine samples collected preconceptionally and during pregnancy. Parents rated children's eating behavior using the Child Eating Behavior Questionnaire (CEBQ). Using multivariable linear regression, accounting for correlation among twins, we estimated covariate-adjusted associations of urinary phthalate biomarkers and BPA concentrations with CEBQ subscale scores. RESULTS: This analysis included 195 children (30 sets of twins), 160 mothers and 97 fathers; children were predominantly non-Hispanic white (84%) and 53% were male. Paternal and maternal preconception monobenzyl phthalate (MBzP) concentrations and maternal preconception mono-n-butyl phthalate (MnBP) were positively associated with emotional overeating, food responsiveness, and desire to drink scores in children (β(')s= 0.11 [95% CI: 0.01, 0.20]-0.21 [95% CI: 0.10, 0.31] per log(e) unit increase in phthalate biomarker concentration). Paternal preconception BPA concentrations were inversely associated with scores on food approaching scales. Maternal pregnancy MnBP, mono-isobutyl phthalate (MiBP) and MBzP concentrations were associated with increased emotional undereating scores. Maternal pregnancy monocarboxy-isononyl phthalate concentrations were related to decreased food avoiding subscale scores. CONCLUSIONS: In this cohort, higher maternal and paternal preconception urinary concentrations of some phthalate biomarkers were associated with increased food approaching behavior scores and decreased food avoiding behavior scores, which could lead to increased adiposity in children.

The raccoon (Procyon lotor) variant of the rabies virus (RRV) is enzootic in the eastern United States and oral rabies vaccination (ORV) is the primary strategy to prevent and control landscape spread. Breaches of ORV management zones occasionally occur, and emergency "contingency" actions may be implemented to enhance local control. Contingency actions are an integral part of landscape-scale wildlife rabies management but can be very costly and routinely involve enhanced rabies surveillance (ERS) around the index case. We investigated two contingency actions in Ohio (2017-2019 and 2018-2021) and one in Virginia (2017-2019) using a dynamic, multi-method occupancy approach to examine relationships between specific management actions and RRV occurrence, including whether ERS was sufficient around the index case. The RRV occupancy was assessed seasonally at 100-km(2) grids and we examined relationships across three spatial scales (regional management zone, RRV free regions, and local contingency areas). The location of a grid relative to the ORV management zone was the strongest predictor of RRV occupancy at the regional scale. In RRV free regions, the neighbor effect and temporal variability were most important in influencing RRV occupancy. Parenteral (hand) vaccination of raccoons was important across all three contingency action areas, but more influential in the Ohio contingency action areas where more raccoons were hand vaccinated. In the Virginia contingency action area, ORV strategies were as important in reducing RRV occupancy as a hand vaccination strategy. The management action to trap, euthanize, and test (TET) raccoons was an important method to increase ERS, yet the impacts of TET on RRV occupancy are not clear. The probability of detecting additional cases of RRV was exceptionally high (>0.95) during the season the index case occurred. The probability of detecting RRV through ERS declined in the seasons following initial TET efforts but remained higher after the contingency action compared to the ERS detection probabilities prior to index case incidence. Local RRV cases were contained within one year and eliminated within 2-3 years of each contingency action.

The majority of vector-borne disease cases reported annually in the United States are caused by pathogens spread by the blacklegged tick, Ixodes scapularis. The number and geographic distribution of cases have increased as the geographic range and abundance of the tick have expanded in recent decades. A large proportion of Lyme disease and other I. scapularis-borne diseases are associated with nymphal tick bites; likelihood of such bites generally increases with increasing nymphal densities. National tick surveillance was initiated in 2018 to track changes in the distribution and abundance of medically important ticks at the county spatial scale throughout the United States. Tick surveillance records, including historical data collected prior to the initiation of the national program, are collated in the ArboNET Tick Module database. Through exploration of ArboNET Tick Module data, we found that efforts to quantify the density of host-seeking I. scapularis nymphs (DON) were unevenly distributed among geographic regions with the greatest proportion of counties sampled in the Northeast and Upper Midwest. Submissions covering tick collections from 2004 through 2022 revealed extensive variation in DON estimates at collection site, county, state, and regional spatial scales. Throughout the entire study period, county DON estimates ranged from 0.0 to 488.5 nymphs/1,000 m(2). Although substantial variation was recorded within regions, DON estimates were greatest in the Northeast, Upper Midwest, and northern states within the Southeast regions (Virginia and North Carolina); densities were intermediate in the Ohio Valley and very low in the South and Northern Rockies and Plains regions. The proportion of counties classified as moderate or high DON was greater in the Northeast, Ohio Valley, and Southeast regions during the 2004 through 2017 time period (prior to initiation of the national tick surveillance program) compared to 2018 through 2022; DON estimates remained similarly low between these time periods in the South and the Northern Rockies and Plains regions. Despite the limitations described herein, the ArboNET Tick Module provides useful data for tracking changes in acarological risk across multiple geographic scales and long periods of time.

While walking along the bustling streets of Beijing, Chengde, Shenyang, Wuhan, or other Chinese cities during the Qing dynasty (1644–1911), people would regularly brush past bats, cranes, pheasants, peacocks, egrets, or ducks; slow their step so a lion, leopard, tiger, rhinoceros, or bear could hurry past; or yield to allow passage to a dragon, unicorn, or qilin (a chimera with horns, a dragon’s head, fish scales, an oxen’s tail, horse’s hooves, and multicolored skin). Of course, it was not those actual animals jostling their way through the crowded causeways but rather myriad Chinese statesmen, civic officials, military officers, and members of the imperial court, as well as their wives, all of whom indicated their rank and status by wearing embroidered badges featuring images of those creatures on their outer coats. | | From the late 14th century until the early 20th century ce, these ornate rank badges (called buzi or Mandarin squares) featured fierce animals to denote military officials, various bird species to identify civic officials, and exotic and imaginary creatures to signify members of the imperial court. Art historian Mary Dusenbury writes, “Qing badges generally include an abbreviated cosmic diagram with an earth-mountain in the lower center, and a multitude of auspicious symbols filling up the surrounding space. In the center, the animal or bird looks up at a prominent red sun, symbol of the emperor.”

OBJECTIVE: There is a need for a systematic method to implement the World Health Organization's Clinical Progression Scale (WHO-CPS), an ordinal clinical severity score for coronavirus disease 2019 patients, to electronic health record (EHR) data. We discuss our process of developing guiding principles mapping EHR data to WHO-CPS scores across multiple institutions. MATERIALS AND METHODS: Using WHO-CPS as a guideline, we developed the technical blueprint to map EHR data to ordinal clinical severity scores. We applied our approach to data from 2 medical centers. RESULTS: Our method was able to classify clinical severity for 100% of patient days for 2756 patient encounters across 2 institutions. DISCUSSION: Implementing new clinical scales can be challenging; strong understanding of health system data architecture was integral to meet the clinical intentions of the WHO-CPS. CONCLUSION: We describe a detailed blueprint for how to apply the WHO-CPS scale to patient data from the EHR.

BACKGROUND: Nonpharmaceutical interventions (NPIs) may be considered as part of national pandemic preparedness as a first line defense against influenza pandemics. Preemptive school closures (PSCs) are an NPI reserved for severe pandemics and are highly effective in slowing influenza spread but have unintended consequences. METHODS: We used results of simulated PSC impacts for a 1957-like pandemic (i.e., an influenza pandemic with a high case fatality rate) to estimate population health impacts and quantify PSC costs at the national level using three geographical scales, four closure durations, and three dismissal decision criteria (i.e., the number of cases detected to trigger closures). At the Chicago regional level, we also used results from simulated 1957-like, 1968-like, and 2009-like pandemics. Our net estimated economic impacts resulted from educational productivity costs plus loss of income associated with providing childcare during closures after netting out productivity gains from averted influenza illness based on the number of cases and deaths for each mitigation strategy. RESULTS: For the 1957-like, national-level model, estimated net PSC costs and averted cases ranged from $7.5 billion (2016 USD) averting 14.5 million cases for two-week, community-level closures to $97 billion averting 47 million cases for 12-week, county-level closures. We found that 2-week school-by-school PSCs had the lowest cost per discounted life-year gained compared to county-wide or school district-wide closures for both the national and Chicago regional-level analyses of all pandemics. The feasibility of spatiotemporally precise triggering is questionable for most locales. Theoretically, this would be an attractive early option to allow more time to assess transmissibility and severity of a novel influenza virus. However, we also found that county-wide PSCs of longer durations (8 to 12 weeks) could avert the most cases (31-47 million) and deaths (105,000-156,000); however, the net cost would be considerably greater ($88-$103 billion net of averted illness costs) for the national-level, 1957-like analysis. CONCLUSIONS: We found that the net costs per death averted ($180,000-$4.2 million) for the national-level, 1957-like scenarios were generally less than the range of values recommended for regulatory impact analyses ($4.6 to 15.0 million). This suggests that the economic benefits of national-level PSC strategies could exceed the costs of these interventions during future pandemics with highly transmissible strains with high case fatality rates. In contrast, the PSC outcomes for regional models of the 1968-like and 2009-like pandemics were less likely to be cost effective; more targeted and shorter duration closures would be recommended for these pandemics.

BACKGROUND: Vitamin B(12) deficiency is a major public health problem worldwide, with the highest burden in elderly people, pregnant women, and young children. Due to its role in DNA synthesis and methylation, folate metabolism, and erythropoiesis, vitamin B(12) supplementation during pregnancy may confer longer-term benefits to maternal and child health outcomes. OBJECTIVES: To evaluate the benefits and harms of oral vitamin B(12) supplementation during pregnancy on maternal and child health outcomes. SEARCH METHODS: We searched the Cochrane Pregnancy and Childbirth's Trials Register, ClinicalTrials.gov, the World Health Organization International Clinical Trials Registry Platform (ICTRP) on 2 June 2023, and reference lists of retrieved studies. SELECTION CRITERIA: Randomised controlled trials (RCTs), quasi-RCTs, or cluster-RCTs evaluating the effects of oral vitamin B(12) supplementation compared to placebo or no vitamin B(12) supplementation during pregnancy. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Four review authors independently assessed trial eligibility. Two review authors independently extracted data from included studies and conducted checks for accuracy. Three review authors independently assessed the risk of bias of the included studies using the Cochrane RoB 1 tool. We used GRADE to evaluate the certainty of evidence for primary outcomes. MAIN RESULTS: The review included five trials with 984 pregnant women. All trials were conducted in low- and middle-income countries, including India, Bangladesh, South Africa, and Croatia. At enrolment, 26% to 51% of pregnant women had vitamin B(12) deficiency (less than 150 pmol/L), and the prevalence of anaemia (haemoglobin less than 11.0 g/dL) ranged from 30% to 46%. The dosage of vitamin B(12) supplementation varied from 5 μg/day to 250 μg/day, with administration beginning at 8 to 28 weeks' gestation through to delivery or three months' postpartum, and the duration of supplementation ranged from 8 to 16 weeks to 32 to 38 weeks. Three trials, involving 609 pregnant women, contributed data for meta-analyses of the effects of vitamin B(12) supplementation compared to placebo or no vitamin B(12) supplementation. Maternal anaemia: there may be little to no difference for maternal anaemia by intervention group, but the evidence is very uncertain (70.9% versus 65.0%; risk ratio (RR) 1.08, 95% confidence interval (CI) 0.93 to 1.26; 2 trials, 284 women; very low-certainty evidence). Maternal vitamin B(12) status: vitamin B(12) supplementation during pregnancy may reduce the risk of maternal vitamin B(12) deficiency compared to placebo or no vitamin B(12) supplementation, but the evidence is very uncertain (25.9% versus 67.9%; RR 0.38, 95% CI 0.28 to 0.51; 2 trials, 272 women; very low-certainty evidence). Women who received vitamin B(12) supplements during pregnancy may have higher total vitamin B(12) concentrations compared to placebo or no vitamin B(12) supplementation (mean difference (MD) 60.89 pmol/L, 95% CI 40.86 to 80.92; 3 trials, 412 women). However, there was substantial heterogeneity (I(2) = 85%). Adverse pregnancy outcomes: the evidence is uncertain about the effect on adverse pregnancy outcomes, including preterm birth (RR 0.97, 95% CI 0.55 to 1.74; 2 trials, 340 women; low-certainty evidence), and low birthweight (RR 1.50, 95% CI 0.93 to 2.43; 2 trials, 344 women; low-certainty evidence). Two trials reported data on spontaneous abortion (or miscarriage); however, the trials did not report quantitative data for meta-analysis and there was no clear definition of spontaneous abortion in the study reports. No trials evaluated the effects of vitamin B(12) supplementation during pregnancy on neural tube defects. Infant vitamin B(12) status: children born to women who received vitamin B(12) supplementation had higher total vitamin B(12) concentrations compared to placebo or no vitamin B(12) supplementation (MD 71.89 pmol/L, 95% CI 20.23 to 123.54; 2 trials, 144 children). Child cognitive outcomes: three ancillary analyses of one trial reported child cognitive outcomes; however, data were not reported in a format that could be included in quantitative meta-analyses. In one study, maternal vitamin B(12) supplementation did not improve neurodevelopment status (e.g. cognitive, language (receptive and expressive), motor (fine and gross), social-emotional, or adaptive (conceptual, social, practical) domains) in children compared to placebo (9 months, Bayley Scales of Infant and Toddler Development Third Edition (BSID-III); 1 trial; low-certainty evidence) or neurophysiological outcomes (72 months, event-related potential measures; 1 trial; low-certainty evidence), though children born to women who received vitamin B(12) supplementation had improved expressive language domain compared to placebo (30 months, BSID-III; 1 trial; low-certainty evidence). AUTHORS' CONCLUSIONS: Oral vitamin B(12) supplementation during pregnancy may reduce the risk of maternal vitamin B(12) deficiency and may improve maternal vitamin B(12) concentrations during pregnancy or postpartum compared to placebo or no vitamin B(12) supplementation, but the evidence is very uncertain. The effects of vitamin B(12) supplementation on other primary outcomes assessed in this review were not reported, or were not reported in a format for inclusion in quantitative analyses. Vitamin B(12) supplementation during pregnancy may improve maternal and infant vitamin B(12) status, but the potential impact on longer-term clinical and functional maternal and child health outcomes has not yet been established.

BACKGROUND: Studies examining the association between in utero Zika virus (ZIKV) exposure and child neurodevelopmental outcomes have produced varied results. METHODS: We aimed to assess neurodevelopmental outcomes among normocephalic children born from pregnant people enrolled in the Zika in Pregnancy in Honduras (ZIPH) cohort study, July-December 2016. Enrollment occurred during the first prenatal visit. Exposure was defined as prenatal ZIKV IgM and/or ZIKV RNA result at enrollment. Normocephalic children, >6 months old, were selected for longitudinal follow-up using the Bayley Scales of Infant and Toddler Development (BSID-III) and the Ages & Stages Questionnaires: Social-Emotional (ASQ:SE-2). RESULTS: One hundred fifty-two children were assessed; after exclusion, 60 were exposed and 72 were unexposed to ZIKV during pregnancy. Twenty children in the exposed group and 21 children in the unexposed group had a composite score <85 in any of the BSID-III domains. Although exposed children had lower cognitive and language scores, differences were not statistically significant. For ASQ:SE-2 assessment, there were not statistically significant differences between groups. CONCLUSIONS: This study found no statistically significant differences in the neurodevelopment of normocephalic children between in utero ZIKV exposed and unexposed. Nevertheless, long-term monitoring of children with in utero ZIKV exposure is warranted. IMPACT: This study found no statistically significant differences in the neurodevelopment in normocephalic children with in utero Zika virus exposure compared to unexposed children, although the exposed group showed lower cognitive and language scores that persisted after adjustment by maternal age and education and after excluding children born preterm and low birth weight from the analysis. Children with prenatal Zika virus exposure, including those normocephalic and have no evidence of abnormalities at birth, should be monitored for neurodevelopmental delays. Follow-up is important to be able to detect developmental abnormalities that might not be detected earlier in life.

Ixodes scapularis (the blacklegged tick) is widely distributed in forested areas across the eastern United States. The public health impact of I. scapularis is greatest in the north, where nymphal stage ticks commonly bite humans and serve as primary vectors for multiple human pathogens. There were dramatic increases in the tick's distribution and abundance over the last half-century in the northern part of the eastern US, and climate warming is commonly mentioned as a primary driver for these changes. In this review, we summarize the evidence for the observed spread and proliferation of I. scapularis being driven by climate warming. Although laboratory and small-scale field studies have provided insights into how temperature and humidity impact survival and reproduction of I. scapularis, using these associations to predict broad-scale distribution and abundance patterns is more challenging. Numerous efforts have been undertaken to model the distribution and abundance of I. scapularis at state, regional, and global scales based on climate and landscape variables, but outcomes have been ambiguous. Across the models, the functional relationships between seasonal or annual measures of heat, cold, precipitation, or humidity and tick presence or abundance were inconsistent. The contribution of climate relative to landscape variables was poorly defined. Over the last half-century, climate warming occurred in parallel with spread and population increase of the white-tailed deer, the most important reproductive host for I. scapularis adults, in the northern part of the eastern US. There is strong evidence for white-tailed deer playing a key role to facilitate spread and proliferation of I. scapularis in the US over the last century. However, due to a lack of spatially and temporally congruent data, climate, landscape, and host variables are rarely included in the same models, thus limiting the ability to evaluate their relative contributions or interactions in defining the geographic range and abundance patterns of ticks. We conclude that the role of climate change as a key driver for geographic expansion and population increase of I. scapularis in the northern part of the eastern US over the last half-century remains uncertain.

BACKGROUND: Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used. METHODS: We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.). RESULTS: We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures. CONCLUSIONS: Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping.

This study investigated the prevalence, and the developmental, behavior and emotional outcomes of 675 preschoolers with ASD with or without a history of regression, who participated in the Study to Explore Early Development (SEED). The SEED project is a cross-sectional case-control study that collected data between 2007 and 2011. Children’s history of regression, adaptive skills, and behavior problems were assessed using the Autism Diagnostic Interview-Revised (ADI-R), the Vineland Adaptive Behavior Scales-Second Edition (Vineland-2), and the Child Behavior Checklist (CBCL), respectively; and children’s developmental levels were assessed using the Mullen Scales of Learning (MSEL). Findings from this study indicated that 26% of children experienced social and language regression, and of those with regression, 76% had regained lost skills upon completion of the study. Compared to children without a history of regression, children with social regression demonstrated increased internalizing problems and decreased fine motor skills, and children with language regression demonstrated poorer language skills. Also, children with language and social regression displayed poorer adaptive communication skills than children without regression. Children who experienced regression in one area of development demonstrated better outcomes than those who experience regression in multiple areas. To conclude, children with regression are at risk for poorer outcomes during their preschool years. © 2023, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.

Objectives The COVID-19 pandemic has had a substantial impact on health systems. The WHO Antimicrobial Resistance (AMR) Collaborating Centres Network conducted a survey to assess the effects of COVID-19 on AMR surveillance, prevention and control.Methods From October-December 2020, WHO Global Antimicrobial Resistance and Use Surveillance System (GLASS) national focal points completed a questionnaire including Likert-scales and open-ended questions. Data were descriptively analysed, income/regional differences were assessed, and free-text questions were thematically analysed.Results Seventy-three countries across income levels participated. During the COVID-19 pandemic, 67% reported limited ability to work with AMR partnerships; decreases in funding were frequently reported by low- and middle-income countries (LMICs; p&lt;0.01). Reduced availability of nursing, medical and public health staff for AMR was reported by 71%, 69% and 64%, respectively, whereas 67% reported stable cleaning staff availability. The majority (58%) reported reduced reagents/consumables, particularly LMICs (p&lt;0.01). Decreased numbers of cultures, elective procedures, chronically ill admissions and outpatients and increased intensive care unit admissions reported could bias AMR data. Reported overall infection prevention and control (IPC) improvement could decrease AMR rates, whereas increases in selected inappropriate IPC practices and antibiotic prescribing could increase rates. Most did not yet have complete data on changing AMR rates due to COVID-19.Conclusions This was the first survey to explore the global impact of COVID-19 on AMR among GLASS countries. Responses revealed universal patterns but also captured country variability. Although focus is understandably on COVID-19, gains in detecting and controlling AMR, a global health priority, cannot afford to be lost.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThis work was supported by a working group belonging to the WHO AMR Surveillance and Quality Assessment Collaborating Centres Network. It was led by the coordinator of the Network at the Robert Koch Institute in Berlin, Germany, who received funding from the Global Protection Programme (GHPP) at the German Federal Ministry of Health.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:The anonymous survey was conducted as part of routine public health work by the WHO Antimicrobial Resistance (AMR) Surveillance and Quality Assessment Collaborating Centres Network. No human subjects, samples or data were involved for this research purpose. As per the policy in Germany, the survey protocol was reviewed and waived by the data protection institutional review board of the Network coordinator at Robert Koch Institute, Berlin, Germany.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesThe aggregated data is avaiable on a case-by-case basis upon consultation with the WHO AMR Surveillance and Quality Assessment Collaborating Centres Network coordinator (Robert Koch Institute, Berlin, Germany)

Motivation Methods for analyzing microbiome data generally fall into one of two groups: tests of the global hypothesis of any microbiome effect, which do not provide any information on the contribution of individual operational taxonomic units (OTUs); and tests for individual OTUs, which do not typically provide a global test of microbiome effect. Without a unified approach, the findings of a global test may be hard to resolve with the findings at the individual OTU level. Further, many tests of individual OTU effects do not preserve the false discovery rate (FDR).Results We introduce the linear decomposition model (LDM), that provides a single analysis path that includes global tests of any effect of the microbiome, tests of the effects of individual OTUs while accounting for multiple testing by controlling the FDR, and a connection to distance-based ordination. The LDM accommodates both continuous and discrete variables (e.g., clinical outcomes, environmental factors) as well as interaction terms to be tested either singly or in combination, allows for adjustment of confounding covariates, and uses permutation-based p-values that can control for correlation. The LDM can also be applied to transformed data, and an “omnibus” test can easily combine results from analyses conducted on different transformation scales. We also provide a new implementation of PERMANOVA based on our approach. For global testing, our simulations indicate the LDM provided correct type I error and can have comparable power to existing distance-based methods. For testing individual OTUs, our simulations indicate the LDM controlled the FDR well. In contrast, DESeq2 often had inflated FDR; MetagenomeSeq generally had the lowest sensitivity. The flexibility of the LDM for a variety of microbiome studies is illustrated by the analysis of data from two microbiome studies. We also show that our implementation of PERMANOVA can outperform existing implementations.

Time series data provide a crucial window into infectious disease dynamics, yet their utility is often limited by the spatially aggregated form in which they are presented. When working with time series data, violating the implicit assumption of homogeneous dynamics below the scale of spatial aggregation could bias inferences about underlying processes. We tested this assumption in the context of the 2015-2016 Zika epidemic in Colombia, where time series of weekly case reports were available at national, departmental, and municipal scales. First, we performed a descriptive analysis, which showed that the timing of departmental-level epidemic peaks varied by three months and that departmental-level estimates of the time-varying reproduction number, R(t), showed patterns that were distinct from a national-level estimate. Second, we applied a classification algorithm to six features of proportional cumulative incidence curves, which showed that variability in epidemic duration, the length of the epidemic tail, and consistency with a cumulative normal density curve made the greatest contributions to distinguishing groups. Third, we applied this classification algorithm to data simulated with a stochastic transmission model, which showed that group assignments were consistent with simulated differences in the basic reproduction number, R0. This result, along with associations between spatial drivers of transmission and group assignments based on observed data, suggests that the classification algorithm is capable of detecting differences in temporal patterns that are associated with differences in underlying drivers of incidence patterns. Overall, this diversity of temporal patterns at local scales underscores the value of spatially disaggregated time series data.

Despite widespread vaccination, eleven thousand mumps cases were reported in the United States (US) in 2016–17, including hundreds in Massachusetts, primarily in college settings. We generated 203 whole genome mumps virus (MuV) sequences from Massachusetts and 15 other states to understand the dynamics of mumps spread locally and nationally, as well as to search for variants potentially related to vaccination. We observed multiple MuV lineages circulating within Massachusetts during 2016–17, evidence for multiple introductions of the virus to the state, and extensive geographic movement of MuV within the US on short time scales. We found no evidence that variants arising during this outbreak contributed to vaccine escape. Combining epidemiological and genomic data, we observed multiple co-circulating clades within individual universities as well as spillover into the local community. Detailed data from one well-sampled university allowed us to estimate an effective reproductive number within that university significantly greater than one. We also used publicly available small hydrophobic (SH) gene sequences to estimate migration between world regions and to place this outbreak in a global context, but demonstrate that these short sequences, historically used for MuV genotyping, are inadequate for tracing detailed transmission. Our findings suggest continuous, often undetected, circulation of mumps both locally and nationally, and highlight the value of combining genomic and epidemiological data to track viral disease transmission at high resolution.

Background Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedesborne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used. Methods We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc). Results We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 183 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, ii) regional models used to predict the spread of major epidemics between countries and iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 33/148) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc) and only 48% of studies assessed predictive performance via out-of-sample validation procedures. Conclusions Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We outline specific recommendations for future studies regarding aims and data choice, covariate selection, model formulation and evaluation. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

Prescribed burning is a major source of a fine particular matter, especially in the southeastern United States, and quantifying emissions from burning operations accurately is an integral part of ascertaining air quality impacts. For instance, a critical factor in calculating fire emissions is identifying fire activity information (e.g., location, date/time, fire type, and area burned) and prior estimations of prescribed fire activity used for calculating emissions have either used burn permit records or satellite-based remote sensing products. While burn permit records kept by state agencies are a reliable source, they are not always available or readily accessible. Satellite-based remote sensing products are currently used to fill the data gaps, especially in regional studies; however, they cannot differentiate prescribed burns from the other types of fires. In this study, we developed novel algorithms to distinguish prescribed burns from wildfires and agricultural burns in a satellite-derived product, Fire INventory from NCAR (FINN). We matched and compared the burned areas from permit records and FINN at various spatial scales: individual fire level, 4 km grid level, and state level. The methods developed in this study are readily usable for differentiating burn type, matching and comparing the burned area between two datasets at various resolutions, and estimating prescribed burn emissions. The results showed that burned areas from permits and FINN have a weak correlation at the individual fire level, while the correlation is much higher for the 4 km grid and state levels. Since matching at the 4 km grid level showed a relatively higher correlation and chemical transport models typically use grid-based emissions, we used the linear regression relationship between FINN and permit burned areas at the grid level to adjust FINN burned areas. This adjustment resulted in a reduction in FINN-burned areas by 34%. The adjusted burned area was then used as input to the BlueSky Smoke Modeling Framework to provide long-term, three-dimensional prescribed burning emissions for the southeastern United States. In this study, we also compared emissions from different methods (FINN or BlueSky) and different data sources (adjusted FINN or permits) to evaluate uncertainties of our emission estimation. The comparison results showed the impacts of the burned area, method, and data source on prescribed burning emission estimations. © 2023 by the authors.