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.

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.