Oregon Health Authority

Background/Objectives: Nosocomial outbreaks of viral respiratory infections strain healthcare systems and endanger patients and healthcare workers (HCWs). We describe two large nosocomial outbreaks with the SARS-CoV-2 Alpha variant, during its initial emergence in Germany, to assess transmission dynamics, effectiveness of control measures, and challenges in managing highly transmissible respiratory viruses. Methods: Confirmed cases were inpatients, HCWs, or their contacts testing SARS-CoV-2-positive since 1 January 2021 (Hospital A [HA])) or 21 January 2021 (Hospital B [HB])) with N501Y and delH69/V70 spike gene mutations. We conducted case interviews, reviewed medical records and shift schedules, and performed sequencing, genome reconstruction, and phylogenetic analysis. We describe cases, transmission chains, and control measures. Results: HA reported 18 patient cases, 20 HCW cases, and 33 community cases (N = 71). HB reported 48 patient cases, 43 HCW cases (13 in a COVID-19 ward), and 27 community cases (N = 118). In-hospital transmission occurred patient-to-patient, HCW-to-patient, patient-to-HCW, and HCW-to-HCW. HA halted admissions immediately after the initial cases; HB implemented measures gradually. Regular testing detected pre-symptomatic (HA = 6; HB = 18) and asymptomatic cases (HA = 3; HB = 13). Testing of agency staff was incomplete. The suspected primary case was an HCW in HA and a patient in HB who required resuscitation shortly after admission. Conclusions: Early COVID-19 outbreaks offer valuable lessons for managing emerging nosocomial outbreaks of highly transmissible respiratory viruses. Our findings provide empirical evidence for effective interventions, including rapid response, testing, HCW protection, and rigorous contact tracing in high-risk emergency situations. Managing agency staff remains a major challenge.

[This corrects the article DOI: 10.3389/fmed.2026.1763735.].

Cervical cancer screening remains vital in the early detection of precancerous lesions and promotes better treatment outcomes. Though evidence suggested multiple sexual partners and HIV infection as risk factors for cervical cancer, limited studies have investigated how multiple sexual partners and HIV infection impact cervical cancer screening in Ghana. Therefore, this study assessed the association of multiple sexual partnership and HIV testing on cervical cancer screening among Ghanaian women of reproductive age. The study utilized data from the 2022 Ghana Demographic and Health Survey. A weighted representative sample of 15,014 women from the 16 regions of Ghana was used for the analysis. Descriptive statistics, Pearson's Chi-square and multivariable logistic regressions were used to analyze the data. Adjusted odds ratios (aORs) at 95% Confidence Intervals were presented from the multivariable logistic regression. The prevalence of cervical cancer screening was 5.0%. We found lower odds of cervical cancer screening with multiple sexual partners at the bivariate level [aOR=0.69, 95% CI: 0.52-0.90], but no association was found in the multivariable model. On the other hand, women who had ever tested for HIV [aOR=4.73, 95% CI:3.39-6.59] were more likely to screen for cervical cancer than those who had never tested. This was still significant after adjusting for covariates [aOR=2.47, 95% CI:1.61-3.80]. The study highlights the influence of multiple sexual partners and HIV testing on cervical cancer screening uptake among women of reproductive age in Ghana. Though the study found no significant association between multiple sexual partners and cervical screening uptake, HIV testing was a predictor of cervical cancer screening among women in Ghana. We recommend continued creation of awareness of cervical cancer screening among women of reproductive age.

We examined fentanyl use and outcomes among people who inject drugs (PWID) in the urban Pacific Northwest (PNW). We conducted secondary analysis of data from the 2022 National HIV Behavioral Surveillance PWID cycle from Seattle, WA and Portland, OR. We calculated proportions of any fentanyl, injection fentanyl, non-injection fentanyl, and street pill use. Next, we compared characteristics, behaviors, and outcomes by any fentanyl use. Finally, we estimated adjusted relative risk (aRR) of overdose outcomes associated with fentanyl use and injecting less associated with type of street pill use. Among 830 PWID, 76% reported any fentanyl use, 47% specifically reported injection fentanyl use, 68% specifically reported non-injection fentanyl use, and 66% reported street pill use. Of those who used pills, 94% smoked them. Fentanyl use was crudely associated with age; race; housing; detainment; usual drug injected; injection frequency; syringe service programs, substance treatment, non-fatal overdose, and naloxone (p < 0.05). With adjustment, any fentanyl use (aRR = 3.20, 95% CI 1.58-6.47), injection fentanyl use (aRR = 3.51, 95% CI 1.63-7.58), and non-injection fentanyl use (aRR = 2.29, 95% CI 1.23-4.28) were associated with higher risk of overdose. Participants who smoked street pills were more likely to report injecting less because of pill use (aRR = 1.82, 95% CI 1.24-2.66). Fentanyl use was highly prevalent among PWID in the urban PNW. Non-injection fentanyl use was most common and street pills were frequently administered by smoking which was associated with injecting less. All fentanyl use was associated with increased risk for overdose. There is ongoing need for access to naloxone for PWID who use fentanyl.

Agrochemical use is an integral component of modern agricultural production in the United States, yet long-term occupational exposure among farmers has been associated with a range of chronic health outcomes. Accurately characterizing these exposures remains challenging due to spatial heterogeneity in land use, application practices, and environmental dispersion. Over the past three decades, geographic information systems (GIS) have emerged as important tools for addressing these challenges by enabling spatially explicit modeling of agrochemical exposure and its potential health impacts. This review synthesizes and critically evaluates peer-reviewed epidemiological studies published between 1995 and 2024 that apply GIS-based methods to examine associations between agrochemical exposure and chronic disease risk among U.S. farmers. The review focuses on studies employing spatial modeling techniques such as buffer and proximity analyses, land-use regression models, interpolation methods, and hybrid frameworks integrating pesticide application records, land-use data, environmental monitoring datasets, and remote sensing products. These approaches have been applied most frequently to cancer and neurodegenerative disease outcomes, with comparatively fewer studies addressing respiratory and other chronic conditions. By systematically comparing GIS-based exposure modeling strategies, this review uniquely highlights methodological strengths, recurring limitations, and sources of uncertainty across the literature, including exposure misclassification, ecological inference, temporal misalignment, and spatial scale variability. Overall, GIS-based approaches have strengthened population-level exposure assessment by improving spatial resolution and identifying geographic disparities in disease risk. The review underscores the need for greater methodological standardization, improved temporal modeling, and integration of individual-level data to advance spatial epidemiology and support occupational health surveillance, risk assessment, and policy development.

Newborn screening for familial hypercholesterolemia (FH) would dramatically increase the diagnosis of a common, potentially fatal but highly treatable genetic condition in newborns and relatives. To report the results of genetic testing of residual newborn screening dried blood spots (DBS) with biomarkers suggesting high risk for FH as an initial step toward development of multitier newborn screening for FH. A cross-sectional study design from July 2021 to July 2022 was used to test residual DBS from newborns with sample collection between 24 and 72 hours of life for total cholesterol, low-density lipoprotein cholesterol, and apolipoprotein B. Principal component analysis identified biomarker combinations that accounted for the greatest variance. Mahalanobis distance was calculated to generalize the idea of a standardized z score of a single variable to several correlated variables; approximately 8% of samples with the greatest positive Mahalanobis distance were selected for genetic FH testing. The study included a population-based screening for newborns in Wisconsin. Study data were analyzed from July 2022 to June 2024. Newborn residual DBS were tested for total cholesterol, low-density lipoprotein cholesterol, and apolipoprotein B, with a subset tested for pathogenic variants in 8 genes associated with FH. Prevalence of pathogenic variants for FH in a population-based sample of newborn screening DBS. Of 59 927 total newborns, DBS samples were obtained from 10 004 newborns (mean [SD] age, 27.8 [5.6] hours; 5142 male [51.4%]). From 10 004 specimens tested, principal component analysis demonstrated the combination of low-density lipoprotein cholesterol and apolipoprotein B accounted for the greatest variance, and 768 specimens were selected for genetic testing. A pathogenic variant for FH was found in 16 samples yielding a population-based prevalence of 1 in 625 (1.6 per 1000; 95% CI, 0.91-2.60 per 1000) newborns. Pathogenic variants were distributed throughout the entire range of Mahalanobis scores selected for genetic testing. This cross-sectional study found that screening newborns for FH using first-tier biochemical testing with reflex second-tier genetic testing was feasible and, in this population, identified 1 in 625 newborns with FH. Further refinement and validation are needed before implementation in newborn screening. Routine newborn screening for FH would substantially increase diagnosis of this common, potentially fatal, yet readily treatable condition while providing opportunities for cascade screening.

Uniform guidance has not been established regarding the inclusion of International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code R45.88 (non-suicidal self-harm), with or without the presence of an injury code, as a self-harm case. This study explores the differences between discharge patients identified with self-harm and co-occurring injury, and those identified with self-harm and no co-occurring injury. Analyses were conducted using Wisconsin and Oregon discharge records from 2022 to 2023. Two mutually exclusive groups were created based on ICD-10-CM codes: Group A) patients with a self-harm injury code, or R45.88 with another injury diagnosis or e-code and, Group B) patients with R45.88 and no other injury code. Hospital and emergency department (ED) patients were analysed separately by jurisdiction. Univariate analyses were conducted, and logistic regression models were run separately for each patient type. The models analysed differences between patients in Groups A and B. For both jurisdictions and patient type, Group B was significantly younger: mean of 14 and 5 years younger among Wisconsin and Oregon hospital patients and 5 and 3 years younger among Wisconsin and Oregon ED patients, respectively. Age remained significant in the models for both types of patients in both jurisdictions. Comorbidities, such as suicidal ideation and mental health disorders, and some demographics, were significantly different between groups, and this varied by jurisdiction. Surveillance of self-harm that incorporates all instances of R45.88 is more inclusive of all self-harm behaviours, whether resulting in injury or not. This will support a more accurate representation of self-harm burden, and the populations impacted.

BackgroundThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccine showed high clinical efficacy against the ancestral variant, but immunological waning, emergence of new variants, and the durability of infection-induced immunity complicate the estimation of population-level effectiveness. We used mathematical modeling to calculate the proportion of hospitalizations averted by vaccination in Washington and Oregon.MethodsWe used an age- and region-structured compartmental model of vaccine-induced and infection-induced immunity from January 2020 until December 2022. We parameterized the strength and durability of immunity via a meta-regression of vaccine efficacy. We calibrated a time-varying contact matrix to weekly hospitalizations reported by the Washington Department of Health and Oregon Health Authority. We validated our model with Centers for Disease Control and Prevention serosurveillance data. To estimate vaccine effectiveness, we created counterfactual scenarios with no vaccination either in the entire population or in select age groups.ResultsWe found that total hospitalizations were reduced 74% (95% credible interval [CrI], 69%–78%) and 15% (95% CrI, 9%–19%) by primary vaccination and boosters, respectively. Vaccination effectiveness was highest during the Alpha wave, averting 90% (95% CrI, 88%–93%) of hospitalizations and in people aged 65+, averting 78% (95% CrI, 73%–81%). Relative to only vaccinating individuals aged 50+, vaccination of individuals aged 18–49 averted 52% (95% CrI, 44%–58%) of hospitalizations overall and 42% (95% CrI, 35%–48%) of hospitalizations among individuals 65+.ConclusionsThe SARS-CoV-2 vaccination program in Washington and Oregon averted the majority of hospitalizations. Vaccinating individuals aged 18–49 significantly reduced hospitalization among individuals aged 65+.