COVID-19 GPH|COVID-19 Genomics and Precision Public Health Weekly Update|PHGKB

COVID-19 GPH|COVID-19 Genomics and Precision Public Health Weekly Update|PHGKB

Publication Date: Aug 27, 2020

COVID-19 Genomics and Precision Public Health Weekly Update Content

Non-Genomics Precision Health Studies

• Association of Race With Mortality Among Patients Hospitalized With Coronavirus Disease 2019 (COVID-19) at 92 US Hospitals
  BR Yehya et al, JAMA Network Open, August 18, 2020
  In this cohort study of 11?210 individuals with COVID-19 presenting for care at 92 hospitals across 12 states, there was no difference in all-cause, in-hospital mortality between White and Black patients after adjusting for age, sex, insurance status, comorbidity, neighborhood deprivation, and site of care.
• The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: monitoring county level vulnerability
  SW Marvel et al, MEDRXIV, August 20, 2020
  We integrated baseline data on relevant community vulnerabilities with dynamic data on local infection rates and interventions into a Pandemic Vulnerability Index (PVI). The PVI presents a visual synthesis of county-level vulnerability indicators that can be compared in a regional, state, or nationwide context. We describe use of the PVI, supporting epidemiological modeling and machine-learning forecasts, and deployment of an interactive, web Dashboard.
• Modeling Contact Tracing Strategies for COVID-19 in the Context of Relaxed Physical Distancing Measures
  A Bilinski et al JAMA Network Open, August 21, 2020
  To support efforts to control COVID-19, contact tracing must be implemented alongside prompt and extensive community case detection, and a high proportion of contacts must be reached. Our estimates imply that contact tracing could support partial relaxation of physical distancing measures but not a full return to levels of contact before lockdown.
• A Syndromic Surveillance Tool to Detect Anomalous Clusters of COVID-19 Symptoms in the United States
  A Guemes et al. MEDRXIV, August 21, 2020
  We present a novel syndromic surveillance approach, which collects body temperature and COVID-like illness (CLI) symptoms across the US using a smartphone app and applies spatio-temporal clustering techniques and cross-correlation analysis to create maps of abnormal symptomatology incidence that are made publicly available.
• COVID-19-associated hyperinflammation and escalation of patient care: a retrospective longitudinal cohort study
  JJ Manson et al, Lancet Rheumatol, August 21, 2020
  Associations between elevated inflammatory markers, escalation of respiratory support, and survival in people with COVID-19 indicate the existence of a high-risk inflammatory phenotype. COV-HI might be useful to stratify patient groups in trial design.
• Sex differences in immune responses that underlie COVID-19 disease outcomes
  T Takahashi et al, Nature, August 26, 2020
  Male patients had higher plasma levels of innate immune cytokines such as IL-8 and IL-18 along with more robust induction of non-classical monocytes. Female patients mounted significantly more robust T cell activation than male patients during SARS-CoV-2 infection. Importantly, we found that a poor T cell response negatively correlated with patients’ age and was associated with worse disease outcome in male patients, but not in female patients.
• Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing
  WE Allen et al, Nature Human Behavior, August 26, 2020
  We developed How We Feel, a web and mobile application that collects longitudinal self-reported survey responses on health, behavior and demographics. Here, we report results from over 500,000 users in the United States. We show that self-reported surveys can be used to build predictive models to identify likely COVID-19-positive individuals.