Sentinel surveillance of SARS-CoV-2 rates and equity impacts using labor and delivery patients in Phoenix, Arizona.

Proactive management of SARS-CoV-2 requires timely and complete population data to track the evolution of the virus and identify at risk populations. However, many cases are asymptomatic and are not easily discovered through traditional testing efforts. Sentinel surveillance can be used to estimate the prevalence of infections for geographical areas but requires identification of sentinels who are representative of the larger population. Our goal is to evaluate applicability of a population of labor and delivery patients for sentinel surveillance system for monitoring the prevalence of SARS-CoV-2 infection. We tested 5307 labor and delivery patients from two hospitals in Phoenix, Arizona, finding 195 SARS-CoV-2 positive. Most positive cases were associated with people who were asymptomatic (79.44%), similar to statewide rates. Our results add to the growing body of evidence that SARS-CoV-2 disproportionately impacts people of color, with Black people having the highest positive rates (5.92%). People with private medical insurance had the lowest positive rates (2.53%), while Medicaid patients had a positive rate of 5.54% and people without insurance had the highest positive rates (6.12%). With diverse people reporting for care and being tested regardless of symptoms, labor and delivery patients may serve as ideal sentinels for asymptomatic detection of SARS-CoV-2 and monitoring impacts across a wide range of social and economic classes. A more robust system for infectious disease management requires the expanded participation of additional hospitals so that the sentinels are more representative of the population at large, reflecting geographic and neighborhood level patterns of infection and risk.

Classifying Refugee Status Using Common Features in EMR.

Automated and accurate identification of refugees in healthcare databases is a critical first step to investigate healthcare needs of this vulnerable population and improve health disparities. In this study, we developed a machine-learning method, named refugee identification system (RIS) to address this need. We curated a data set consisting of 103 refugees and 930 non-refugees in Arizona. We compiled de-identified individual-level information including age, primary language, and noise-masked home address, state-level refugee resettlement statistics, and world language statistics. We then performed feature engineering to convert language and masked address into quantitative features. Finally, we built a random forest model to classify refugee and non-refugees. RIS achieved high classification accuracy (overall accuracy=0.97, specificity=0.99, sensitivity=0.85, positive predictive value=0.88, negative predictive value=0.98, and area under receiver operating characteristic curve=0.98). RIS is customizable for refugee identification outside Arizona. Its application enables large-scale investigation of refugee healthcare needs and improvement of health disparities.

COVID-19 mortality is associated with pre-existing impaired innate immunity in health conditions.

COVID-19 can be life-threatening to individuals with chronic diseases. To prevent severe outcomes, it is critical that we comprehend pre-existing molecular abnormalities found in common health conditions that predispose patients to poor prognoses. In this study, we focused on 14 pre-existing health conditions for which increased hazard ratios of COVID-19 mortality have been documented. We hypothesized that dysregulated gene expression in these pre-existing health conditions were risk factors of COVID-19 related death, and the magnitude of dysregulation (measured by fold change) were correlated with the severity of COVID-19 outcome (measured by hazard ratio). To test this hypothesis, we analyzed transcriptomics data sets archived before the pandemic in which no sample had COVID-19. For a given pre-existing health condition, we identified differentially expressed genes by comparing individuals affected by this health condition with those unaffected. Among genes differentially expressed in multiple health conditions, the fold changes of 70 upregulated genes and 181 downregulated genes were correlated with hazard ratios of COVID-19 mortality. These pre-existing dysregulations were molecular risk factors of severe COVID-19 outcomes. These genes were enriched with endoplasmic reticulum and mitochondria function, proinflammatory reaction, interferon production, and programmed cell death that participate in viral replication and innate immune responses to viral infections. Our results suggest that impaired innate immunity in pre-existing health conditions is associated with increased hazard of COVID-19 mortality. The discovered molecular risk factors are potential prognostic biomarkers and targets for therapeutic intervention.

Severe acute respiratory syndrome coronavirus 2: a canary in the coal mine for public safety net hospitals.

BACKGROUND: The coronavirus disease 2019 pandemic has exposed disproportionate health inequities among underserved populations, including refugees. Public safety net healthcare systems play a critical role in facilitating access to care for refugees and informing coordinated public health prevention and mitigation efforts during a pandemic. OBJECTIVE: This study aimed to evaluate the prevalence ratios of severe acute respiratory syndrome coronavirus 2 infection between refugee women and nonrefugee parturient patients admitted to the hospital for delivery. Here, we suspected that the burden of infection was disproportionately distributed across refugee communities that may act as sentinels for community outbreaks. STUDY DESIGN: A cross-sectional study was conducted examining parturient women admitted to the maternity unit between May 6, 2020, and July 22, 2020, when universal testing for severe acute respiratory syndrome coronavirus 2 was first employed. Risk factors for severe acute respiratory syndrome 2 positivity were ascertained, disaggregated by refugee status, and other clinical and sociodemographic variables examined. Prevalence ratios were calculated and comparisons made to county-level community prevalence over the same period. RESULTS: The positive test percentage at the county-level during this study period was 21.6%. Of 350 women admitted to the hospital for delivery, 33 (9.4%) tested positive for severe acute respiratory syndrome 2. When refugee status was determined, 45 women (12.8%) were identified as refugees. Of the 45 refugee women, 8 (17.8%) tested positive for severe acute respiratory syndrome 2 compared with 25 nonrefugee patients (8.19%) who tested positive for severe acute respiratory syndrome 2 (prevalence ratio, 2.16; 95% confidence interval, 1.04-4.51). In addition, 7 of the refugee women who tested positive for severe acute respiratory syndrome coronavirus 2 were from Central Africa. CONCLUSION: The severe acute respiratory syndrome coronavirus 2 outbreak has disproportionately affected refugee populations. This study highlighted the utility of universal screening in mounting a rapid response to an evolving pandemic and how we can better serve refugee communities. Focused response may help achieve more equitable care related to severe acute respiratory syndrome 2 among vulnerable communities. The identification of such populations may help mitigate the spread of the disease and facilitate a timely, culturally, and linguistically enhanced public health response.

Factors Associated with New Uptake of Long-Acting Reversible Contraceptives Since the Affordable Care Act Among Privately Insured Women in Pennsylvania.

BACKGROUND: The Affordable Care Act eliminated out-of-pocket costs for contraceptives, including highly effective long-acting reversible contraception (LARC), for most insured women. Patient characteristics associated with new LARC uptake after the Affordable Care Act have not been well-studied. We hypothesized that awareness of no-cost intrauterine device (IUD) coverage would be associated with new LARC use. METHODS: Data included were from 883 women not using a LARC at baseline who participated in the MyNewOptions study, a 2-year study of privately insured women in Pennsylvania. Multivariable analysis assessed whether the following baseline characteristics predicted new LARC use over 2 years: awareness of no-cost IUD coverage, future pregnancy intention, baseline contraceptive use, contraceptive attitudes, and sociodemographic characteristics. RESULTS: At baseline, 54.4% of participants were using prescription methods; 21.1% nonprescription methods; 12.1% natural family planning, withdrawal, or spermicide alone; and 12.5% no method. A minority (7.2%) was aware of no-cost coverage for IUDs. Over 2 years, 7.2% of participants became new LARC users, but awareness of no-cost coverage for IUDs was not associated with new LARC use (adjusted odds ratio, 0.84; 95% confidence interval, 0.27-2.55). New LARC use was associated with already using prescription methods, not intending pregnancy within the next 5 years, prior unintended pregnancy, and desire to change method if cost were not a factor. CONCLUSIONS: Among privately insured women, wanting to switch methods if cost were not a factor was associated with new LARC uptake, although awareness of no-cost IUD coverage was not. Providing women with information about their contraceptive coverage benefits may help women to seek and obtain the methods better aligned with their personal needs.

Questioning the Clinical Utility of Exome Sequencing in Developing Countries.

The availability of whole-exome sequencing has revolutionized the study of genetic disease in recent years, particularly in dermatology, where clinical phenotypes are readily recognized. As this technology becomes increasingly affordable and accessible, questions are emerging regarding the clinical and ethical responsibilities of physicians who determine variants underlying disease, especially with regard to children, for whom treatment may be warranted and clinical course improved based on a known genotype. These responsibilities are accentuated in the developing countries, which harbor most consanguineous populations and thus bear the brunt of monogenic genodermatoses. Although many genetic disorders are identified in these populations, limited educational and clinical infrastructure rarely offers opportunities to improve the course of disease. Here we report a genetic study that illustrates these challenges.

Transcription restores DNA repair to heterochromatin, determining regional mutation rates in cancer genomes.

Somatic mutations in cancer are more frequent in heterochromatic and late-replicating regions of the genome. We report that regional disparities in mutation density are virtually abolished within transcriptionally silent genomic regions of cutaneous squamous cell carcinomas (cSCCs) arising in an XPC(-/-) background. XPC(-/-) cells lack global genome nucleotide excision repair (GG-NER), thus establishing differential access of DNA repair machinery within chromatin-rich regions of the genome as the primary cause for the regional disparity. Strikingly, we find that increasing levels of transcription reduce mutation prevalence on both strands of gene bodies embedded within H3K9me3-dense regions, and only to those levels observed in H3K9me3-sparse regions, also in an XPC-dependent manner. Therefore, transcription appears to reduce mutation prevalence specifically by relieving the constraints imposed by chromatin structure on DNA repair. We model this relationship among transcription, chromatin state, and DNA repair, revealing a new, personalized determinant of cancer risk.