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Universities are particularly vulnerable to infectious disease outbreaks and are also ideal environments to study transmission dynamics and evaluate mitigation and surveillance measures when outbreaks occur. Here, we introduce a SARS-CoV-2 surveillance and response framework based on high-resolution, multimodal data collected during the 2020-2021 academic year at Colorado Mesa University. We analyzed epidemiological and sociobehavioral data (demographics, contact tracing, and wifi-based co-location data) alongside pathogen surveillance data (wastewater, random, and reflexive diagnostic testing; and viral genomic sequencing of wastewater and clinical specimens) to characterize outbreak dynamics and inform policy decisions. We quantified group attributes that increased disease risk, and highlighted parallels between traditional and wifi-based contact tracing. We additionally used clinical and environmental viral sequencing to identify cryptic transmission, cluster overdispersion, and novel lineages or mutations. Ultimately, we used distinct data types to identify information that may help shape institutional policy and to develop a model of pathogen surveillance suitable for the future of outbreak preparedness.
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Prolonged infections in immunocompromised individuals may be a source for novel SARS-CoV-2 variants, particularly when both the immune system and antiviral therapy fail to clear the infection, thereby promoting adaptation. Here we describe an approximately 16-month case of SARS-CoV-2 infection in an immunocompromised individual. Following monotherapy with the monoclonal antibody Bamlanivimab, the individuals virus was resistant to this antibody via a globally unique Spike amino acid variant (E484T) that evolved from E484A earlier in infection. With the emergence and spread of the Omicron Variant of Concern, which also contains Spike E484A, E484T may arise again as an antibody-resistant derivative of E484A.
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The consequences of past COVID-19 infection for personal health and long-term population immunity are only starting to be revealed. Unfortunately, detecting past infection is currently a challenge, limiting clinical and research endeavors. Widely available anti-SARS-CoV-2 antibody tests cannot differentiate between past infection and vaccination given vaccine-induced anti-spike antibodies and the rapid loss of infection-induced anti-nucleocapsid antibodies. Anti-membrane antibodies develop after COVID-19, but their long-term persistence is unknown. Here, we demonstrate that anti-membrane IgG is a sensitive and specific marker of past COVID-19 infection and persists at least one year. We also confirm that anti-receptor binding domain (RBD) Ig is a long-lasting, sensitive, and specific marker of past infection and vaccination, while anti-nucleocapsid IgG lacks specificity and quickly declines after COVID-19. Thus, a combination of anti-membrane and anti-RBD antibodies can accurately differentiate between distant COVID-19 infection, vaccination, and naive states to advance public health, individual healthcare, and research goals.
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Multiple summer events, including large indoor gatherings, in Provincetown, Massachusetts (MA), in July 2021 contributed to an outbreak of over one thousand COVID-19 cases among residents and visitors. Most cases were fully vaccinated, many of whom were also symptomatic, prompting a comprehensive public health response, motivating changes to national masking recommendations, and raising questions about infection and transmission among vaccinated individuals. To characterize the outbreak and the viral population underlying it, we combined genomic and epidemiological data from 467 individuals, including 40% of known outbreak-associated cases. The Delta variant accounted for 99% of sequenced outbreak-associated cases. Phylogenetic analysis suggests over 40 sources of Delta in the dataset, with one responsible for a single cluster containing 83% of outbreak-associated genomes. This cluster was likely not the result of extensive spread at a single site, but rather transmission from a common source across multiple settings over a short time. Genomic and epidemiological data combined provide strong support for 25 transmission events from, including many between, fully vaccinated individuals; genomic data alone provides evidence for an additional 64. Together, genomic epidemiology provides a high-resolution picture of the Provincetown outbreak, revealing multiple cases of transmission of Delta from fully vaccinated individuals. However, despite its magnitude, the outbreak was restricted in its onward impact in MA and the US, likely due to high vaccination rates and a robust public health response.
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BackgroundHealthcare workers (HCWs) are at the frontlines of the COVID-19 pandemic and are at risk of exposure to SARS-CoV-2 infection from their interactions with patients and in the community (1, 2). Limited availability of recommended personal protective equipment (PPE), in particular N95 respirators, has fueled concerns about whether HCWs are adequately protected from exposure while caring for patients. Understanding the source of SARS-CoV-2 infection in a HCW - the community or the healthcare system - is critical for understanding the effectiveness of hospital infection control and PPE practices. In Dane County, Wisconsin, community prevalence of SARS-CoV-2 is relatively low (cumulative prevalence of ~0.06% - positive cases / total population in Dane county as of April 17). Although SARS-CoV-2 infections in HCWs are often presumed to be acquired during the course of patient care, there are few reports unambiguously identifying the source of acquisition. ObjectiveTo determine the source of transmission of SARS-CoV-2 in a healthcare worker.
