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Grad, Yonatan

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Now showing 1 - 10 of 33
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    Concerns about SARS-CoV-2 evolution should not hold back efforts to expand vaccination
    (2021) Cobey, Sarah; Larremore, Daniel B.; Grad, Yonatan; Lipsitch, Marc
    When vaccines are in limited supply, expanding the number of people who receive some vaccine can reduce disease and mortality compared to concentrating vaccines in a subset of the population. A corollary of such dose-sparing strategies is that vaccinated individuals may have less protective immunity. Concerns have been raised that expanding the fraction of the population with partial immunity to SARS-CoV-2 could increase selection for vaccine escape variants, ultimately undermining vaccine effectiveness. We argue that although this is possible, preliminary evidence instead suggests such strategies should slow the rate of vaccine or immune escape. As long as vaccination provides some protection against escape variants, the corresponding reduction in prevalence and incidence should reduce the rate at which new variants are generated and the speed of adaptation. Because there is little evidence for efficient immune selection of SARS-CoV-2 during typical infections, these population-level effects are likely to dominate vaccine-induced evolution.
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    Modeling the Comparative Impact of Individual Quarantine vs. Active Monitoring of Contacts for the Mitigation of COVID-19
    (2020-03-08) Peak, Corey; Kahn, Rebecca; Grad, Yonatan; Childs, Lauren; Li, Ruoran; Lipsitch, Marc; Buckee, Caroline
    Individual quarantine and active monitoring of contacts are core disease control strategies, particularly for emerging infectious diseases such as Coronavirus Disease 2019 (COVID-19). To estimate the comparative efficacy of these interventions to control COVID-19, we fit a stochastic branching model, comparing two sets of reported parameters for the dynamics of the disease. Our results suggest that individual quarantine may contain an outbreak of COVID-19 with a short serial interval (4.8 days) only in settings with high intervention performance where at least three-quarters of infected contacts are individually quarantined. However, in settings where this performance is unrealistically high and the outbreak of COVID-19 continues to grow, so too will the burden of the number of contacts traced for active monitoring or quarantine. In such circumstances where resources are prioritized for scalable interventions such as social distancing, we show active monitoring or individual quarantine of high-risk contacts can contribute synergistically to social distancing. To the extent that interventions based on contact tracing can be implemented, therefore, they can help mitigate the spread of COVID-19. Our model highlights the urgent need for more data on the serial interval and the extent of presymptomatic transmission in order to make data-driven policy decisions regarding the cost-benefit comparisons of individual quarantine vs. active monitoring of contacts.
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    Densely sampled viral trajectories suggest longer duration of acute infection with B.1.1.7 variant relative to non-B.1.1.7 SARS-CoV-2
    (2021-02-16) Kissler, Stephen; Fauver, Joseph R.; Mack, Christina; Tai, Caroline G.; Breban, Mallery I.; Watkins, Anne E.; Samant, Radhika M.; Anderson, Deverick J.; Ho, David D.; Grubaugh, Nathan D.; Grad, Yonatan
    To test whether acute infection with B.1.1.7 is associated with higher or more sustained nasopharyngeal viral concentrations, we assessed longitudinal PCR tests performed in a cohort of 65 individuals infected with SARS-CoV-2 undergoing daily surveillance testing, including seven in fected with B.1.1.7. For individuals infected with B.1.1.7, the mean duration of the proliferation phase was 5.3 days (90% credible interval [2.7, 7.8]), the mean duration of the clearance phase was 8.0 days [6.1, 9.9], and the mean overall duration of infection (proliferation plus clearance) was 13.3 days [10.1, 16.5]. These compare to a mean proliferation phase of 2.0 days [0.7, 3.3], a mean clearance phase of 6.2 days [5.1, 7.1], and a mean duration of infection of 8.2 days [6.5, 9.7] for non-B.1.1.7 virus. The peak viral concentration for B.1.1.7 was 19.0 Ct [15.8, 22.0] compared to 20.2 Ct [19.0, 21.4] for non-B.1.1.7. This converts to 8.5 log10 RNA copies/ml [7.6, 9.4] for B.1.1.7 and 8.2 log10 RNA copies/ml [7.8, 8.5] for non-B.1.1.7. These data offer evidence that SARS-CoV-2 variant B.1.1.7 may cause longer infections with similar peak viral concentration compared to non-B.1.1.7 SARS-CoV-2. This extended duration may contribute to B.1.1.7 SARS CoV-2’s increased transmissibility.
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    Reductions in commuting mobility predict geographic differences in SARS-CoV-2 prevalence in New York City
    (2020) Kissler, Stephen; Kishore, Nishant; Prabhu, Malavika; Goffman, Dena; Beilin, Yaakov; Landau, Ruth; Gyamfi-Bannerman, Cynthia; Bateman, Brian; Katz, Daniel; Gal, Jonathan; Bianco, Angela; Stone, Joanne; Larremore, Daniel; Buckee, Caroline; Grad, Yonatan
    Importance: New York City is the epicenter of the SARS-CoV-2 pandemic in the United States. Mortality and hospitalizations have differed substantially between different neighborhoods. Mitigation efforts in the coming months will require knowing the extent of geographic variation in SARS-CoV-2 prevalence and understanding the drivers of these differences. Objective: To estimate the prevalence of SARS-CoV-2 infection by New York City borough between March 22nd and May 3rd, 2020, and to associate variation in prevalence with antecedent reductions in mobility, defined as aggregated daily physical movements into and out of each borough. Design: Observational study of universal SARS-CoV-2 test results obtained from women hospitalized for delivery. Setting: Four New York-Presbyterian hospital campuses and two Mount Sinai hospital campuses in New York City. Participants: 1,746 women with New York City ZIP codes hospitalized for delivery. Exposures: Infection with SARS-CoV-2. Main outcomes: Population prevalence of SARS-CoV-2 by borough and correlation with the reduction in daily commuting-style movements into and out of each borough. Results: The estimated population prevalence of SARS-CoV-2 ranged from 11.3% (95% credible interval 8.9%, 13.9%) in Manhattan to 26.0% (95% credible interval 15.3%, 38.9%) in South Queens, with an estimated city-wide prevalence of 15.6% (95% credible interval 13.9%, 17.4%). The peak city-wide prevalence was during the week of March 30th, though temporal trends in prevalence varied substantially between boroughs. Population revalence was lowest in boroughs with the greatest reductions in morning commutes out of and evening commutes into the borough (Pearson R = –0.88, 95% credible interval –0.52, –0.99). Conclusions and relevance: Reductions in between-borough mobility predict geographic differences in the prevalence of SARS-CoV-2 infection in New York City. Large parts of the city may remain at risk for substantial SARS-CoV-2 outbreaks. Widespread testing should be conducted to identify geographic disparities in prevalence and assess the risk of future outbreaks.
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    Trends in Antibiotic Susceptibility in Staphylococcus aureus in Boston, Massachusetts, from 2000 to 2014
    (American Society for Microbiology, 2017) Kanjilal, Sanjat; Sater, Mohamad R. Abdul; Thayer, Maile; Lagoudas, Georgia K.; Kim, Soohong; Blainey, Paul C.; Grad, Yonatan
    ABSTRACT The rate of infection by methicillin-resistant Staphylococcus aureus (MRSA) has declined over the past decade, but it is unclear whether this represents a decline in S. aureus infections overall. To evaluate the trends in the annual rates of infection by S. aureus subtypes and mean antibiotic resistance, we conducted a 15-year retrospective observational study at two tertiary care institutions in Boston, MA, of 31,753 adult inpatients with S. aureus isolated from clinical specimens. We inferred the gain and loss of methicillin resistance through genome sequencing of 180 isolates from 2016. The annual rates of infection by S. aureus declined from 2003 to 2014 by 4.2% (2.7% to 5.6%), attributable to an annual decline in MRSA of 10.9% (9.3% to 12.6%). Penicillin-susceptible S. aureus (PSSA) increased by 6.1% (4.2% to 8.1%) annually, and rates of methicillin-susceptible penicillin-resistant S. aureus (MSSA) did not change. Resistance in S. aureus decreased from 2000 to 2014 by 0.8 antibiotics (0.7 to 0.8). Within common MRSA clonal complexes, 3/14 MSSA and 2/21 PSSA isolates arose from the loss of resistance-conferring genes. Overall, in two tertiary care institutions in Boston, MA, a decline in S. aureus infections has been accompanied by a shift toward increased antibiotic susceptibility. The rise in PSSA makes penicillin an increasingly viable treatment option.
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    WGS to predict antibiotic MICs for Neisseria gonorrhoeae
    (Oxford University Press, 2017) Eyre, David W.; De Silva, Dilrini; Cole, Kevin; Peters, Joanna; Cole, Michelle J.; Grad, Yonatan; Demczuk, Walter; Martin, Irene; Mulvey, Michael R.; Crook, Derrick W.; Walker, A. Sarah; Peto, Tim E. A.; Paul, John
    Background: Tracking the spread of antimicrobial-resistant Neisseria gonorrhoeae is a major priority for national surveillance programmes. Objectives: We investigate whether WGS and simultaneous analysis of multiple resistance determinants can be used to predict antimicrobial susceptibilities to the level of MICs in N. gonorrhoeae. Methods: WGS was used to identify previously reported potential resistance determinants in 681 N. gonorrhoeae isolates, from England, the USA and Canada, with phenotypes for cefixime, penicillin, azithromycin, ciprofloxacin and tetracycline determined as part of national surveillance programmes. Multivariate linear regression models were used to identify genetic predictors of MIC. Model performance was assessed using leave-one-out cross-validation. Results: Overall 1785/3380 (53%) MIC values were predicted to the nearest doubling dilution and 3147 (93%) within ±1 doubling dilution and 3314 (98%) within ±2 doubling dilutions. MIC prediction performance was similar across the five antimicrobials tested. Prediction models included the majority of previously reported resistance determinants. Applying EUCAST breakpoints to MIC predictions, the overall very major error (VME; phenotypically resistant, WGS-prediction susceptible) rate was 21/1577 (1.3%, 95% CI 0.8%–2.0%) and the major error (ME; phenotypically susceptible, WGS-prediction resistant) rate was 20/1186 (1.7%, 1.0%–2.6%). VME rates met regulatory thresholds for all antimicrobials except cefixime and ME rates for all antimicrobials except tetracycline. Country of testing was a strongly significant predictor of MIC for all five antimicrobials. Conclusions: We demonstrate a WGS-based MIC prediction approach that allows reliable MIC prediction for five gonorrhoea antimicrobials. Our approach should allow reasonably precise prediction of MICs for a range of bacterial species.
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    Systematic analysis of protein identity between Zika virus and other arthropod-borne viruses
    (WHO Press, 2017) Chang, Hsiao-Han; Huber, Roland G; Bond, Peter J; Grad, Yonatan; Camerini, David; Maurer-Stroh, Sebastian; Lipsitch, Marc
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    In Vitro Selection of Neisseria gonorrhoeae Mutants with Elevated MIC Values and Increased Resistance to Cephalosporins
    (American Society for Microbiology, 2014) Johnson, S. R.; Grad, Yonatan; Ganakammal, S. R.; Burroughs, M.; Frace, M.; Lipsitch, Marc; Weil, R.; Trees, D.
    Strains of Neisseria gonorrhoeae with mosaic penA genes bearing novel point mutations in penA have been isolated from ceftriaxone treatment failures. Such isolates exhibit significantly higher MIC values to third-generation cephalosporins. Here we report the in vitro isolation of two mutants with elevated MICs to cephalosporins. The first possesses a point mutation in the transpeptidase region of the mosaic penA gene, and the second contains an insertion mutation in pilQ.
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    Epidemiologic data and pathogen genome sequences: a powerful synergy for public health
    (BioMed Central, 2014) Grad, Yonatan; Lipsitch, Marc
    Epidemiologists aim to inform the design of public health interventions with evidence on the evolution, emergence and spread of infectious diseases. Sequencing of pathogen genomes, together with date, location, clinical manifestation and other relevant data about sample origins, can contribute to describing nearly every aspect of transmission dynamics, including local transmission and global spread. The analyses of these data have implications for all levels of clinical and public health practice, from institutional infection control to policies for surveillance, prevention and treatment. This review highlights the range of epidemiological questions that can be addressed from the combination of genome sequence and traditional ‘line lists’ (tables of epidemiological data where each line includes demographic and clinical features of infected individuals). We identify opportunities for these data to inform interventions that reduce disease incidence and prevalence. By considering current limitations of, and challenges to, interpreting these data, we aim to outline a research agenda to accelerate the genomics-driven transformation in public health microbiology.
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    Within-Host Whole-Genome Deep Sequencing and Diversity Analysis of Human Respiratory Syncytial Virus Infection Reveals Dynamics of Genomic Diversity in the Absence and Presence of Immune Pressure
    (American Society for Microbiology, 2014) Grad, Yonatan; Newman, Richard; Zody, M; Yang, Xiao; Murphy, Rebecca; Qu, J.; Malboeuf, C. M.; Levin, J. Z.; Lipsitch, Marc; DeVincenzo, J.
    Human respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract disease in infants and young children and an important respiratory pathogen in the elderly and immunocompromised. While population-wide molecular epidemiology studies have shown multiple cocirculating RSV genotypes and revealed antigenic and genetic change over successive seasons, little is known about the extent of viral diversity over the course of an individual infection, the origins of novel variants, or the effect of immune pressure on viral diversity and potential immune-escape mutations. To investigate viral population diversity in the presence and absence of selective immune pressures, we studied whole-genome deep sequencing of RSV in upper airway samples from an infant with severe combined immune deficiency syndrome and persistent RSV infection. The infection continued over several months before and after bone marrow transplant (BMT) from his RSV-immune father. RSV diversity was characterized in 26 samples obtained over 78 days. Diversity increased after engraftment, as defined by T-cell presence, and populations reflected variation mostly within the G protein, the major surface antigen. Minority populations with known palivizumab resistance mutations emerged after its administration. The viral population appeared to diversify in response to selective pressures, showing a statistically significant growth in diversity in the presence of pressure from immunity. Defining escape mutations and their dynamics will be useful in the design and application of novel therapeutics and vaccines. These data can contribute to future studies of the relationship between within-host and population-wide RSV phylodynamics.