Monitoring and understanding the transmission and evolution of SARS-CoV-2 remains a significant pub-lic health priority. Within-host genetic variation provides insight into viral evolution during infection and may help infer transmission events. In this study, we analyzed intrahost variation in SARS-CoV-2 genome sequences from Boston University's testing mandate. Focusing on intrahost single nucleotide variants (iSNVs), we inferred transmission events and assessed the selective forces shaping within-host viral evolution. To minimize false-positive iSNVs resulting from systematic biases, we implemented stringent data filtering and developed a heuristic to exclude contamination-derived artifacts arising from batched sequencing. We find that intrahost variation is limited and infrequently transmitted during acute infections, suggesting that shared iSNVs serve as highly specific but insensitive markers of transmission. We also observed incomplete purifying selection shaping within-host diversity, with the loci most affected changing among variants of concern. Finally, we identified a highly recurrent iSNV (G11083T) which may represent a site of positive selection. Our results highlight that within host variation provides insight towards within host pathogen evolution, in spite of a limited use towards genomic epidemiology.

BACKGROUND:People who are immunocompromised can develop persistent SARS-CoV-2 infections. Several viral mutations accumulated during the course of such persistent infections have also been observed in prominent variants of concern (VOCs). Here, we characterise persistent infection and viral evolution of SARS-CoV-2 lasting more than 750 days in a person with advanced HIV-1 infection. METHODS:Between March, 2021, and July, 2022, eight clinical specimens were collected from a person living with HIV, neither receiving antiretroviral therapy nor virally suppressed, and presumed to have been initially infected with SARS-CoV-2 in mid-May, 2020. Viral RNA was extracted from each swab and an amplicon-based sequencing approach was used for genomic analysis of SARS-CoV-2. Variable sites were characterised at the consensus and subconsensus levels, and phylogenetic tools were applied to analyse viral evolution. Publicly available SARS-CoV-2 sequences from GenBank were leveraged to contextualise our sequenced samples and identify any potential evidence of transmission. FINDINGS:Genomes formed a monophyletic cluster in the B.1 lineage. 68 consensus and 67 subconsensus single nucleotide variants were observed over the course of infection. The intrahost clock rate remained similar to that of the interhost rate in contemporaneous community sequences (6·74 × 10-4 [95% credible interval 5·05 × 10-4 to 8·54 × 10-4] substitutions per site per year vs 6·11 × 10-4 [5·54 × 10-5 to 6·66 × 10-4]). Mutations grouped into two distinct subpopulations present throughout infection. 10 non-synonymous mutations in the spike protein gene were at positions in common with those defining the omicron lineage (BA.1 or BA.2), of which nine were present before November, 2021. Nine of 18 substitutions present throughout infection were rare in online databases, suggesting a lack of long transmission chains descending from this individual. INTERPRETATION:Convergent SARS-CoV-2 evolution, both in and outside the spike protein, observed in this study suggests parallels with the evolutionary process leading to emergence of the omicron VOC. The inferred absence of onward infections might indicate a loss of transmissibility during adaptation to a single host. Our results underscore the importance of appropriate treatment to cure persistent SARS-CoV-2 infections and monitoring them to understand how mutations contribute to viral adaptation. FUNDING:National Institute of General Medical Sciences of the National Institutes of Health, Centers for Disease Control and Prevention, the National Institute of Allergy and Infectious Diseases, MassCPR, and Morris Singer Foundation.

Background: Immunocompromised patients receiving B-cell-depleting therapies are at increased risk of persistent SARS-CoV-2 infection, with many experiencing fatal outcomes. We report a successful outcome in a patient with rheumatoid arthritis (RA) on rituximab diagnosed with COVID-19 in July 2020 with persistent infection for over 245 days. Results: The patient received numerous treatment courses for persistent COVID-19 infection, including remdesivir, baricitinib, immunoglobulin and high doses of corticosteroids followed by a prolonged taper due to persistent respiratory symptoms and cryptogenic organizing pneumonia. Her clinical course was complicated by Pseudomonas aeruginosa sinusitis with secondary bacteremia, and cytomegalovirus (CMV) viremia and pneumonitis. SARS-CoV-2 positive RNA samples were extracted from two nasopharyngeal swabs and sequenced using targeted amplicon Next-Generation Sequencing which were analyzed for virus evolution over time. Viral sequencing indicated lineage B.1.585.3 SARS-CoV-2 accumulated Spike protein mutations associated with immune evasion and resistance to therapeutics. Upon slowly decreasing the patient's steroids, she had resolution of her symptoms and had a negative nasopharyngeal SARS-CoV-2 PCR and serum CMV PCR in March 2021. Conclusion: A patient with RA on B-cell depleting therapy developed persistent SARS-CoV-2 infection allowing for virus evolution and had numerous complications, including viral and bacterial co-infections with opportunistic pathogens. Despite intra-host evolution with a more immune evasive SARS-CoV-2 lineage, it was cleared after 245 days with reconstitution of the patient's immune system.

Background Throughout the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, healthcare workers (HCWs) have faced risk of infection from within the workplace via patients and staff as well as from the outside community, complicating our ability to resolve transmission chains in order to inform hospital infection control policy. Here we show how the incorporation of sequences from public genomic databases aided genomic surveillance early in the pandemic when circulating viral diversity was limited. Methods We sequenced a subset of discarded, diagnostic SARS-CoV-2 isolates between March and May 2020 from Boston Medical Center HCWs and combined this data set with publicly available sequences from the surrounding community deposited in GISAID with the goal of inferring specific transmission routes. Results Contextualizing our data with publicly available sequences reveals that 73% (95% confidence interval, 63%-84%) of coronavirus disease 2019 cases in HCWs are likely novel introductions rather than nosocomial spread. Conclusions We argue that introductions of SARS-CoV-2 into the hospital environment are frequent and that expanding public genomic surveillance can better aid infection control when determining routes of transmission.

Background: Assessment of disease severity associated with a novel pathogen or variant provides critical information needed by public health agencies and governments to develop appropriate responses. The SARS-CoV-2 Omicron Variant of Concern (VOC) spread rapidly through populations worldwide before robust epidemiological and laboratory data were available to investigate its relative severity. Here we develop a set of methods that make use of non-linked, aggregate data to answer questions of severity and variant dynamics.Methods: Using data from the National Institute for Communicable Disease in South Africa, we determined lag intervals most consistent with time from case ascertainment to hospital admission and within-hospital death. We then utilize these intervals to estimate and compare case hospitalization and case fatality ratios across the four epidemic waves that South Africa has faced, each dominated by a different VOC.Findings: We find that lag intervals and disease severity are age-dependent and have varied throughout the pandemic as different VOCs have driven infections. At an aggregate level, fluctuations in cases are generally followed by a similar trend in hospitalizations within 7 days and deaths within 15 days. We note a marked reduction in disease severity throughout the Omicron period relative to prior waves, most significant in older age groups.Interpretation: These methods provide useful estimates of the impact of novel SARS-CoV-2 VOCs, especially for application in settings where resources and access to individual-level data are limited.Funding: National Institute for Communicable Diseases of South Africa, South African National GovernmentDeclaration of Interest: WH reports his position as a member of Biobot Analytics’ scientific advisory board and has received stock options in Biobot Analytics, as well as payment for expert witness testimony on the expected course of the COVID-19 pandemic. DS reports previous employment at Pfizer Inc. prior to the initiation of this analysis and stock in Pfizer Inc. DS also reports compensation for occasional one-hour blinded consultancies for several consulting companies over the past 36 months. MS reports receipt of institutional research funds from the Johnson and Johnson Foundation and from Pfizer Inc.; neither funder had a role in the design or content of the current manuscript. CC reports grant funding from the Wellcome Trust, South Africa MRC, US CDC, and Sanofi Pasteur to institute COVID-19 research in the past 36 months, as well as a role on the scientific advisory committee for “BCHW: Burden of COVID-19 among health care workers, assessing infection, risk factors, vaccine effectiveness, working experiences and one-health implications: a mixed methodology, multisite international study”. RW reports shareholding stock in the following health/pharmaceutical companies in South Africa, none related to this work: Adcock Ingram Holdings Ltd, Dischem Pharmacies Ltd, Discovery Ltd, Netcare Ltd, Aspen Pharmacare Holdings Ltd. All interests listed are outside the current work. All other authors declare no competing interests. Ethical Approval: Ethics approval was not required for this study; data obtained through the data-sharing agreement between study authors and utilized in the analysis was aggregated and properly de-identified.

Abstract Background The COVID-19 pandemic has been marked by long-term persistence of SARS-CoV-2 in immunocompromised patients receiving B-cell-depleting therapies, with many individuals experiencing fatal COVID-19. Methods We report an individual treated with rituximab who survived persistent COVID-19 over 9 months. SARS-CoV-2 positive RNA samples were sequenced using targeted amplicon NGS sequencing with backup sequencing on a nanopore platform. The resulting sequences were analyzed for genomic variance over time at the consensus and sub-consensus level. Results An individual with rheumatoid arthritis (RA) treated with azathioprine and rituximab (last dose in May 2020) was diagnosed with COVID-19 in July 2020 and admitted with pneumonia. After initial incomplete recovery, the patient had persistent infection through March 2021 and received both remdesivir and convalescent plasma (January 2021). The patient received three doses of mRNA vaccine (Pfizer BioNTech) in December 2020, April 2021, and November 2021, but was seronegative for nucleocapsid IgG in both January 2021 and March 2021; positive spike IgG developed by September 2021 (512 AU/ml) and December 2021 (621 AU/ml) (Figure 1). The patient recovered with new oxygen dependence (2-3L) and manages RA off B-cell depletion; they required an extended corticosteroid taper to manage organizing pneumonia and treatment for several opportunistic infections. Viral sequencing over the course of illness indicated a persistent infection with a lineage B.1.585.3 virus that accumulated 14 mutations throughout the infection. Two mutations (S494P, S D737Y) are associated with therapy resistance and are similar to those found in other immunocompromised individuals with persistent COVID-19. Additional mutations were of unknown consequence. Figure 1:Timeline of Immunocompromised Patient’s Clinical Course of COVID-19 Conclusion SARS-CoV-2 was able to establish persistent infection and accumulated mutations associated with therapeutic resistance; repeated vaccination was associated with successful resolution following repeated vaccination after stopping rituximab. Cessation of B-cell-depleting therapy was likely the critical factor in the patient’s recovery, but repeated vaccination was associated with a delayed seroconversion in this patient with reversibly immunosuppression. Disclosures William P. Hanage, PhD, Biobot Analytics Inc: Advisor/Consultant|Merck Vaccines: Advisor/Consultant.

Background Assessment of disease severity associated with a novel pathogen or variant provides crucial information needed by public health agencies and governments to develop appropriate responses. The SARS-CoV-2 omicron variant of concern (VOC) spread rapidly through populations worldwide before robust epidemiological and laboratory data were available to investigate its relative severity. Here we develop a set of methods that make use of non-linked, aggregate data to promptly estimate the severity of a novel variant, compare its characteristics with those of previous VOCs, and inform data-driven public health responses.Methods Using daily population-level surveillance data from the National Institute for Communicable Diseases in South Africa (March 2, 2020, to Jan 28, 2022), we determined lag intervals most consistent with time from case ascertainment to hospital admission and within-hospital death through optimisation of the distance correlation coefficient in a time series analysis. We then used these intervals to estimate and compare age-stratified case -hospitalisation and case-fatality ratios across the four epidemic waves that South Africa has faced, each dominated by a different variant.Findings A total of 3 569 621 cases, 494 186 hospitalisations, and 99 954 deaths attributable to COVID-19 were included in the analyses. We found that lag intervals and disease severity were dependent on age and variant. At an aggregate level, fluctuations in cases were generally followed by a similar trend in hospitalisations within 7 days and deaths within 15 days. We noted a marked reduction in disease severity throughout the omicron period relative to previous waves (age-standardised case-fatality ratios were consistently reduced by >50%), most substantial for age strata with individuals 50 years or older.Interpretation This population-level time series analysis method, which calculates an optimal lag interval that is then used to inform the numerator of severity metrics including the case-hospitalisation and case-fatality ratio, provides useful and timely estimates of the relative effects of novel SARS-CoV-2 VOCs, especially for application in settings where resources are limited.

Background: COVID-19 vaccine trials and post-implementation data suggest vaccination decreases SARS-CoV-2 infections. Objective: Estimate COVID-19 vaccinations impact on SARS-CoV-2 case rates and viral diversity among healthcare workers (HCW) during a high community prevalence period. Design, Setting, Participants: A prospective cohort study from Boston Medical Center (BMC)s HCW vaccination program, where staff received two doses of BNT162b2 or mRNA-1273. Measurements: PCR-confirmed SARS-CoV-2 cases among HCWs from December 09, 2020 to February 23, 2021. Weekly SARS-CoV-2 rates per 100,000 person-day overall and by time from first injection (1-14 and >14 days) were compared with surrounding community rates. Viral genome sequences from SARS CoV-2 positive samples. Results: SARS-CoV-2 cases occurred in 1.4% (96/7109) of HCWs given at least a first dose and 0.3% (17/5913) of HCWs given both vaccine doses. Adjusted SARS-CoV-2 infection rate ratios were 0.73 (95% CI 0.53-1.00) 1-14 days and 0.18 (0.10-0.32) >14 days from first dose. HCW SARS-CoV-2 cases >14 days from initial dose compared to within 14 days were more often older (46 versus 38 years, p=0.007), Latinx (10% versus 8%, p=0.03), and asymptomatic (48% versus 11%, p=0.0002). SARS-CoV-2 rates among HCWs fell below those of the surrounding community, with a 18% versus 11% weekly decrease respectively (p=0.14). Comparison of 48 SARS-CoV-2 genomes sequenced from post-first dose cases did not indicate selection pressure towards known spike-antibody escape mutations. Limitations: Unable to adjust for infection risk outside of the workplace. Lack follow up on symptoms post SARS-CoV-2 diagnosis. Small number of vaccinated HCW cases. Conclusion: Our results indicate a positive impact of COVID-19 vaccines on SARS-CoV-2 case rates. Post-vaccination isolates did not show unusual genetic diversity or selection for mutations of concern.

An outbreak of over 1,000 COVID-19 cases in Provincetown, Massachusetts (MA), in July 2021—the first large outbreak mostly in vaccinated individuals in the US—prompted a comprehensive public health response, motivating changes to national masking recommendations and raising questions about infection and transmission among vaccinated individuals. To address these questions, we combined viral genomic and epidemiological data from 467 individuals, including 40% of outbreak-associated cases. The Delta variant accounted for 99% of cases in this dataset; it was introduced from at least 40 sources, but 83% of cases derived from a single source, likely through transmission across multiple settings over a short time rather than a single event. Genomic and epidemiological data supported multiple transmissions of Delta from and between fully vaccinated individuals. However, despite its magnitude, the outbreak had limited onward impact in MA and the US overall, likely due to high vaccination rates and a robust public health response.

Abstract Background Coronavirus disease 2019 (COVID-19) vaccine trials and post-implementation data suggest that vaccination decreases infections. We examine vaccination’s impact on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) case rates and viral diversity among health care workers (HCWs) during a high community prevalence period. Methods In this prospective cohort study, HCW received 2 doses of BNT162b2 or mRNA-1273. We included confirmed cases among HCWs from 9 December 2020 to 23 February 2021. Weekly SARS-CoV-2 rates per 100,000 person-days and by time from first injection (1–14 and ≥15 days) were compared with surrounding community rates. Viral genomes were sequenced. Results SARS-CoV-2 cases occurred in 1.4% (96/7109) of HCWs given at least a first dose and 0.3% (17/5913) of HCWs given both vaccine doses. Adjusted rate ratios (95% confidence intervals) were 0.73 (.53–1.00) 1–14 days and 0.18 (.10–.32) ≥15 days from first dose. HCW ≥15 days from initial dose compared to 1-14 days were more often older (46 vs 38 years, P = .007), Latinx (10% vs 8%, P = .03), and asymptomatic (48% vs 11%, P = .0002). SARS-CoV-2 rates among HCWs fell below the surrounding community, an 18% vs 11% weekly decrease, respectively (P = .14). Comparison of 50 genomes from post–first dose cases did not indicate selection pressure toward known spike antibody escape mutations. Conclusions Our results indicate an early positive impact of vaccines on SARS-CoV-2 case rates. Post-vaccination isolates did not show unusual genetic diversity or selection for mutations of concern.

If enough individuals in a population are immune to a pathogen, it cannot cause an outbreak. Deliberately seeking such herd immunity through infection during a potentially lethal pandemic is contrary to all principles of public health, given the potential for uncontrolled outbreaks and risks to vulnerable populations.

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.