Spatial Heterogeneity Can Lead to Substantial Local Variations in COVID-19 Timing and Severity
Recently published research in PNAS by Dr. Carter Butts (Department of Sociology)
IDSI Faculty Advisory Member Carter Butts and his team have published a new paper that uses a novel method for incorporating interpersonal contact network data to examine “the effects of an uneven population distribution on the spread of the COVID-19 disease.” Read the article, “Spatial heterogeneity can lead to substantial local variations in COVID-19 timing and severity.”
A Modular Microarray Imaging System for Highly Specific COVID-19 Antibody Testing
New paper published in Lab on a Chip by IDSI Faculty Advisory Board member Dr. Philip L. Felgner (School of Medicine) and colleagues
Abstract: To detect the presence of antibodies in blood against SARS-CoV-2 in a highly sensitive and specific manner. Here we describe a robust, inexpensive ($200), 3D-printable portable imaging platform (TinyArray imager) that can be deployed immediately in areas with minimal infrastructure to read coronavirus antigen microarrays (CoVAMs) that contain a panel of antigens from SARS-CoV-2, SARS-1, MERS, and other respiratory viruses. Read the article, “A modular microarray imaging system for highly specific COVID-19 antibody testing.”
COVID-19 Serology at Population Scale: SARS-CoV-2-specific Antibody Responses in Saliva
New paper by Dr. Douglas Granger (Department of Psychological Science) et al. published in Journal of Clinical Microbiology
Non-invasive SARS-CoV-2 antibody testing is urgently needed to estimate the incidence and prevalence of SARS-CoV-2 infection at the general population level. Precise knowledge of population immunity could allow government bodies to make informed decisions about how and when to relax stay-at-home directives and to reopen the economy. Read the article.
Using Multiple Data Streams to Estimate and Forecast SARS-CoV-2 Transmission Dynamics, with Application to the Virus Spread in Orange County, California (PrePrint)
Work by IDSI Co-director Vladimir N. Minin (Dept. of Statistics)
Abstract: Near real-time monitoring of outbreak transmission dynamics and evaluation of public health interventions are critical for interrupting the spread of the novel coronavirus (SARS-CoV-2) and mitigating morbidity and mortality caused by coronavirus disease (COVID-19). Formulating a regional mechanistic model of SARS-CoV-2 transmission dynamics and frequently estimating parameters of this model using streaming surveillance data offers one way to accomplish data-driven decision making. Read the article on the AR XIV website.
Estimated Seroprevalence of SARS-CoV-2 Antibodies Among Adults in Orange County, California
Preprint by Drs. Tim Bruckner, Daniel Parker, Andrew Noymer, Matt Zahn and Bernadette Boden-Albala.
Abstract: Clinic-based estimates of SARS-CoV-2 may considerably underestimate the total number of infections. Access to testing in the US has been heterogeneous and symptoms vary widely in infected persons. Public health surveillance efforts and metrics are therefore hampered by underreporting. We set out to provide a minimally biased estimate of SARS-CoV-2 seroprevalence among adults for a large and diverse county (Orange County, CA, population 3.2 million). Read the article on the Med RX IV website.