UNASSIGNED: School-based asthma programs effectively address poorly controlled asthma and asthma disparities, especially when coupled with screening for and addressing social determinants of health (SDOH) needs. Existing screening tools are tailored to clinical settings; therefore, we sought to develop a community-based SDOH screening tool.
UNASSIGNED: We used a four-phase iterative design process to develop and pilot a community-based screening tool. We used a modified Delphi process to identify screening tool domains, identified validated items for inclusion, and developed an appropriate tool layout for populations with limited health/general literacy. Community advisory boards reviewed and refined a draft tool. Next, we conducted a qualitative pilot test of acceptability to parents and feasibility for staff in a community health center.
UNASSIGNED: Six domains are included in our SDOH screening tool: health care access, transportation, food insecurity, public benefits, housing, and utilities. In the pilot test, 41 screenings were completed, and 36 parents (16.7% Spanish speaking) provided feedback. Most families understood the purpose of the screening; felt that the questions were clear, appropriate, and quick to complete; and liked the pictures. The clinic\'s care coordinator expressed a preference for the pilot tool compared to their existing screening tool and recommended improvements to encourage honest reporting by patients.
UNASSIGNED: This community-based screening tool addresses key SDOH needs that impact asthma and is acceptable to families. The next steps are to implement the tool in school-based asthma programs to support improvements in asthma outcomes and disparities by identifying and addressing families\' unmet SDOH needs.

The association between SARS-CoV-2 humoral immunity and post-acute sequelae of COVID-19 (long COVID) remains uncertain. The objective of this population-based cohort study was to assess the association between SARS-CoV-2 seropositivity and symptoms consistent with long COVID. English and Spanish-speaking members ≥ 18 years old with SARS-CoV-2 serologic testing conducted prior to August 2021 were recruited from Kaiser Permanente Southern California and Kaiser Permanente Colorado. Between November 2021 and April 2022, participants completed a survey assessing symptoms, physical health, mental health, and cognitive function consistent with long COVID. Survey results were linked to SARS-CoV-2 antibody (Ab) and viral (RNA) lab results in electronic health records. Weighted descriptive analyses were generated for five mutually exclusive patient groups: (1) +Ab/+RNA; (2) +Ab/- or missing RNA; (3) -Ab/+RNA; (4a) -Ab/-RNA reporting no prior infection; and (4b) -Ab/-RNA reporting prior infection. The proportions reporting symptoms between the +Ab/+RNA and -Ab/+RNA groups were compared, adjusted for covariates. Among 3,946 participants, the mean age was 52.1 years old (SD 15.6), 68.3% were female, 28.4% were Hispanic, and the serologic testing occurred a median of 15 months prior (IQR = 12-18). Three quarters (74.5%) reported having had COVID-19. Among people with laboratory-confirmed COVID-19, there was no association between antibody positivity (+Ab/+RNA vs. -Ab/+RNA) and any symptoms, physical health, mental health, or cognitive function. As expected, physical health, cognitive function, and fatigue were worse, and palpitations and headaches limiting the ability to work were more prevalent among people with laboratory-confirmed prior infection and positive serology (+Ab/+RNA) compared to those without reported or confirmed prior infection and negative serology (-Ab/-RNA/no reported COVID-19). Among people with laboratory-confirmed COVID-19, SARS-CoV-2 serology from practice settings were not associated with long COVID symptoms and health status suggesting limited utility of serology testing for long COVID.

Environmentally-mediated protozoan diseases like cryptosporidiosis and giardiasis are likely to be highly impacted by extreme weather, as climate-related conditions like temperature and precipitation have been linked to their survival, distribution, and overall transmission success. Our aim was to investigate the relationship between extreme temperature and precipitation and cryptosporidiosis and giardiasis infection using monthly weather data and case reports from Colorado counties over a twenty-one year period. Data on reportable diseases and weather among Colorado counties were collected using the Colorado Electronic Disease Reporting System (CEDRS) and the Daily Surface Weather and Climatological Summaries (Daymet) Version 3 dataset, respectively. We used a conditional Poisson distributed-lag nonlinear modeling approach to estimate the lagged association (between 0 and 12-months) between relative temperature and precipitation extremes and the risk of cryptosporidiosis and giardiasis infection in Colorado counties between 1997 and 2017, relative to the risk found at average values of temperature and precipitation for a given county and month. We found distinctly different patterns in the associations between temperature extremes and cryptosporidiosis, versus temperature extremes and giardiasis. When maximum or minimum temperatures were high (90th percentile) or very high (95th percentile), we found a significant increase in cryptosporidiosis risk, but a significant decrease in giardiasis risk, relative to risk at the county and calendar-month mean. Conversely, we found very similar relationships between precipitation extremes and both cryptosporidiosis and giardiasis, which highlighted the prominent role of long-term (>8 months) lags. Our study presents novel insights on the influence that extreme temperature and precipitation can have on parasitic disease transmission in real-world settings. Additionally, we present preliminary evidence that the standard lag periods that are typically used in epidemiological studies to assess the impacts of extreme weather on cryptosporidiosis and giardiasis may not be capturing the entire relevant period.

OBJECTIVE: Explore factors influencing patient comfort with and perceived helpfulness of screening for health-related social needs.
METHODS: In a parallel secondary mixed-methods analysis of data from three primary care clinics, we used logistic regression to examine effects of practice- and patient-level factors on comfort with and perceived helpfulness of social needs screening. We applied narrative analysis to 20 patient interviews to further understand how patients\' lived experiences influenced their perceptions of screening.
RESULTS: Among 511 patients, receiving an explanation about screening was associated with increased odds of comfort (OR 2.1, 95% CI [1.1-4.30]) and perceived helpfulness (OR 4.7 [2.8-7.8]). Those experiencing more needs were less likely to report comfort (3 + needs vs. 0: OR 0.2 [0.1-0.5]). Narratives elucidated how a history of stigmatizing experiences increased discomfort disclosing needs and captured how relationship quality with healthcare teams influenced perceptions of screening for patients with extensive needs.
CONCLUSIONS: Practice-level (screening explanation and therapeutic rapport) and patient-level factors (history and extent of needs) are key influences on comfort with and perceived helpfulness of screening.
CONCLUSIONS: Good communication about screening benefits all patients. Patients with extensive social needs may require additional sensitivity to their past experiences.

OBJECTIVE: To assess whether increasing levels of hospital stress-measured by intensive care unit (ICU) bed occupancy (primary), ventilators in use and emergency department (ED) overflow-were associated with decreasing COVID-19 ICU patient survival in Colorado ICUs during the pre-Delta, Delta and Omicron variant eras.
METHODS: A retrospective cohort study using discrete-time survival models, fit with generalised estimating equations.
METHODS: 34 hospital systems in Colorado, USA, with the highest patient volume ICUs during the COVID-19 pandemic.
METHODS: 9196 non-paediatric SARS-CoV-2 patients in Colorado hospitals admitted once to an ICU between 1 August 2020 and 1 March 2022 and followed for 28 days.
METHODS: Death or discharge to hospice.
RESULTS: For Delta-era COVID-19 ICU patients in Colorado, the odds of death were estimated to be 26% greater for patients exposed every day of their ICU admission to a facility experiencing its all-era 75th percentile ICU fullness or above, versus patients exposed for none of their days (OR: 1.26; 95% CI: 1.04 to 1.54; p=0.0102), adjusting for age, sex, length of ICU stay, vaccination status and hospital quality rating. For both Delta-era and Omicron-era patients, we also detected significantly increased mortality hazard associated with high ventilator utilisation rates and (in a subset of facilities) states of ED overflow. For pre-Delta-era patients, we estimated relatively null or even protective effects for the same fullness exposures, something which provides a meaningful contrast to previous studies that found increased hazards but were limited to pre-Delta study windows.
CONCLUSIONS: Overall, and especially during the Delta era (when most Colorado facilities were at their fullest), increasing exposure to a fuller hospital was associated with an increasing mortality hazard for COVID-19 ICU patients.

The present study examined early socioeconomic status (SES) and neighborhood disadvantage (ND) as independent predictors of antisocial behavior (ASB) and addressed the etiology of the associations (i.e., genes versus the environment) using a longitudinal adoption design. Prospective data from the Colorado Adoption Project (435 adoptees, 598 nonadopted children, 526 biological grandparents of adoptees, 481 adoptive parents, and 617 nonadoptive parents including biological parents of unrelated siblings of adoptees) were examined. SES and ND were assessed during infancy and ASB was evaluated from ages four through 16 using parent and teacher report. Associations between predictors and ASB were compared across adoptive and nonadoptive families and sex. Early SES was a nominally significant, independent predictor of antisocial ASB, such that lower SES predicted higher levels of ASB in nonadoptive families only. ND was not associated with ASB. Associations were consistent across aggression and delinquency, and neither SES nor ND was associated with change in ASB over time. Nominally significant associations did not remain significant after controlling for multiple testing. As such, despite nonsignificant differences in associations across sex or adoptive status, we were unable to make definitive conclusions regarding the genetic versus environmental etiology of or sex differences in the influence of SES and ND on ASB. Despite inconclusive findings, in nonadoptees, results were consistent-in effect size and direction-with previous studies in the literature indicating that lower SES is associated with increased risk for ASB.

We evaluated the sensitivity of estimated PM2.5 and NO2 health impacts to varying key input parameters and assumptions including: 1) the spatial scale at which impacts are estimated, 2) using either a single concentration-response function (CRF) or using racial/ethnic group specific CRFs from the same epidemiologic study, 3) assigning exposure to residents based on home, instead of home and work locations for the state of Colorado. We found that the spatial scale of the analysis influences the magnitude of NO2, but not PM2.5, attributable deaths. Using county-level predictions instead of 1 km2 predictions of NO2 resulted in a lower estimate of mortality attributable to NO2 by ∼ 50 % for all of Colorado for each year between 2000 and 2020. Using an all-population CRF instead of racial/ethnic group specific CRFs results in a 130 % higher estimate of annual mortality attributable for the white population and a 40 % and 80 % lower estimate of mortality attributable to PM2.5 for Black and Hispanic residents, respectively. Using racial/ethnic group specific CRFs did not result in a different estimation of NO2 attributable mortality for white residents, but led to ∼ 50 % lower estimates of mortality for Black residents, and 290 % lower estimate for Hispanic residents. Using NO2 based on home instead of home and workplace locations results in a smaller estimate of annual mortality attributable to NO2 for all of Colorado by 2 % each year and 0.3 % for PM2.5. Our results should be interpreted as an exercise to make methodological recommendations for future health impact assessments of pollution.

BACKGROUND: Routine vaccination coverage for adolescents living in the rural US is lower than adolescents living in urban areas. We sought to measure the effect of Boot Camp Translation (BCT), a community-based participatory intervention, on rural adolescent vaccination coverage.
METHODS: A cluster randomized controlled trial was performed September 2018-November 2021 involving 16 rural Colorado counties. Intervention county community members engaged in BCT to develop interventions to improve adolescent vaccination locally. Adolescent vaccination coverage was measured using the Colorado Immunization Information System.
RESULTS: For 11-12-year-olds, HPV initiation, HPV up-to-date, MenACWY, and Tdap vaccination coverage was lower post- versus pre-intervention in the control and intervention groups. For 11-12-year-olds in the intervention group, there was no significant difference post- versus pre-intervention in the odds of HPV vaccine initiation (adjusted ratio of odds ratios [aROR] = 0.93, 95 %: 0.85-1.02, p = 0.10) or up-to-date HPV vaccination (aROR: 1.10, 95 % CI: 0.98-1.23, p = 0.11) compared with the control group. Among 11-12-year-olds, the decrease in the proportion vaccinated with MenACWY and Tdap in the intervention group was significantly greater than the control group. Among 13-17-year-olds, there were significant increases in HPV initiation, HPV up-to-date, MenACWY, and Tdap vaccination coverage from pre- to post-intervention for both groups, with no significant differences between groups.
CONCLUSIONS: 11-12-year-old vaccination coverage decreased slightly from pre- to post-intervention while 13-17-year-old vaccination coverage increased. We saw no effect from the BCT intervention. Our findings about the effectiveness of BCT for improving vaccine uptake may not be generalizable because the study coincided with the COVID-19 pandemic.
BACKGROUND: This study was registered with ClinicalTrials.gov, NCT03955757.

Context: Despite the fact that obesity is both treatable and preventable, treating the comorbidities, rather than obesity per se remains the mainstay of therapy. Objective: To evaluate the efficacy and implementation of a pragmatic approach to weight management in primary care that prioritizes treatment of weight rather than weight-related diseases (PATHWEIGH). Study Design and Analysis: PATHWEIGH is a hybrid type 1 cluster randomized stepped wedge clinical trial. Clinics were enrolled and randomized to three sequences using covariate constrained randomization. Descriptive statistics were used to summarize clinic and patient characteristics with t-tests, Wilcoxon rank sums or Fisher\'s exact tests used to compare groups. Setting: Fifty-seven primary care clinics in rural, suburban and urban Colorado in a single healthcare system were utilized. Population Studied: Patients age >18 years and body mass index (BMI) >25 kg/m2 who had a weight-prioritized visit (WPV) in the prior year were enrolled. A WPV was defined as a chief complaint or reason for visit that included \"weight\", ICD-10 codes for weight or use of an intake questionnaire for weight. Intervention: None. This abstract describes the baseline (pre-intervention) characteristics of the clinics and patients treated with standard-of-care (SOC) for weight management. Outcome Measures: Baseline characteristics of the clinics and patients undergoing a WPV from March 17, 2020 - March 16, 2021. Results: 20,410 patients met these eligibility requirements representing 12% of patients >18 years and body mass index (BMI) >25 kg/m2 seen at the clinic during this baseline period. The three randomization sequences of 20, 18, and 19 sites were similar with an overall median age of 53 years (IQR: 39-65), 58% women, 76% non-Hispanic whites, 64% commercial insurance, and median BMI of 36 kg/m2 (IQR: 32-41). No sequence differences were seen for vital signs, relevant laboratory values, or numbers of comorbidities or medications that cause weight loss or weight gain. Referral for anything weight-related was low (<6%) and only 334 prescriptions of an anti-obesity medication were noted. Conclusions: Of patients >18 years and body mass index (BMI) >25 kg/m2 seen in the 57 primary care clinics, 12% had a weight-prioritized visit during the baseline period. Despite most being commercially insured, referral to any weight-related service or prescription of anti-obesity medication was uncommon.

Acid mine drainage (AMD) is recognized as a major environmental challenge in the Western United States, particularly in Colorado, leading to extreme subsurface contamination issue. Given Colorado\'s arid climate and dependence on groundwater, an accurate assessment of AMD-induced contamination is deemed crucial. While in past, machine learning (ML)-based inversion algorithms were used to reconstruct ground electrical properties (GEP) such as relative dielectric permittivity (RDP) from ground penetrating radar (GPR) data for contamination assessment, their inherent non-linear nature can introduce significant uncertainty and non-uniqueness into the reconstructed models. This is a challenge that traditional ML methods are not explicitly designed to address. In this study, a probabilistic hybrid technique has been introduced that combines the DeepLabv3+ architecture-based deep convolutional neural network (DCNN) with an ensemble prediction-based Monte Carlo (MC) dropout method. Different MC dropout rates (1%, 5%, and 10%) were initially evaluated using 1D and 2D synthetic GPR data for accurate and reliable RDP model prediction. The optimal rate was chosen based on minimal prediction uncertainty and the closest alignment of the mean or median model with the true RDP model. Notably, with the optimal MC dropout rate, prediction accuracy of over 95% for the 1D and 2D cases was achieved. Motivated by these results, the hybrid technique was applied to field GPR data collected over an AMD-impacted wetland near Silverton, Colorado. The field results underscored the hybrid technique\'s ability to predict an accurate subsurface RDP distribution for estimating the spatial extent of AMD-induced contamination. Notably, this technique not only provides a precise assessment of subsurface contamination but also ensures consistent interpretations of subsurface condition by different environmentalists examining the same GPR data. In conclusion, the hybrid technique presents a promising avenue for future environmental studies in regions affected by AMD or other contaminants that alter the natural distribution of GEP.