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1.
EBioMedicine ; 91: 104534, 2023 May.
Article in English | MEDLINE | ID: covidwho-2251640

ABSTRACT

BACKGROUND: Throughout the COVID-19 pandemic, the SARS-CoV-2 virus has continued to evolve, with new variants outcompeting existing variants and often leading to different dynamics of disease spread. METHODS: In this paper, we performed a retrospective analysis using longitudinal sequencing data to characterize differences in the speed, calendar timing, and magnitude of 16 SARS-CoV-2 variant waves/transitions for 230 countries and sub-country regions, between October 2020 and January 2023. We then clustered geographic locations in terms of their variant behavior across several Omicron variants, allowing us to identify groups of locations exhibiting similar variant transitions. Finally, we explored relationships between heterogeneity in these variant waves and time-varying factors, including vaccination status of the population, governmental policy, and the number of variants in simultaneous competition. FINDINGS: This work demonstrates associations between the behavior of an emerging variant and the number of co-circulating variants as well as the demographic context of the population. We also observed an association between high vaccination rates and variant transition dynamics prior to the Mu and Delta variant transitions. INTERPRETATION: These results suggest the behavior of an emergent variant may be sensitive to the immunologic and demographic context of its location. Additionally, this work represents the most comprehensive characterization of variant transitions globally to date. FUNDING: Laboratory Directed Research and Development (LDRD), Los Alamos National Laboratory.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19/epidemiology , COVID-19/prevention & control , Pandemics , Retrospective Studies
2.
Virus Evol ; 8(2): veac089, 2022.
Article in English | MEDLINE | ID: covidwho-2087850

ABSTRACT

New variants of SARS-CoV-2 show remarkable heterogeneity in their relative fitness over both time and space. In this paper we extend the tools available for estimating the selection strength for new SARS-CoV-2 variants to a hierarchical, mixed-effects, renewal equation model. This formulation allows us to estimate selection effects at the global level while incorporating both measured and unmeasured heterogeneity among countries. Applying this model to the spread of Omicron in forty countries, we find evidence for very strong but very heterogeneous selection effects. To test whether this heterogeneity is explained by differences in the immune landscape, we considered several measures of vaccination rates and recent population-level infection as covariates, finding moderately strong, statistically significant effects. We also found a significant positive correlation between the selection advantage of Delta and Omicron at the country level, suggesting that other region-specific explanatory variables of fitness differences do exist. Our method is implemented in the Stan programming language, can be run on standard consumer-grade computing resources, and will be straightforward to apply to future variants.

3.
Nat Commun ; 12(1): 7239, 2021 12 14.
Article in English | MEDLINE | ID: covidwho-1574197

ABSTRACT

Controlling the SARS-CoV-2 pandemic becomes increasingly challenging as the virus adapts to human hosts through the continual emergence of more transmissible variants. Simply observing that a variant is increasing in frequency is relatively straightforward, but more sophisticated methodology is needed to determine whether a new variant is a global threat and the magnitude of its selective advantage. We present two models for quantifying the strength of selection for new and emerging variants of SARS-CoV-2 relative to the background of contemporaneous variants. These methods range from a detailed model of dynamics within one country to a broad analysis across all countries, and they include alternative explanations such as migration and drift. We find evidence for strong selection favoring the D614G spike mutation and B.1.1.7 (Alpha), weaker selection favoring B.1.351 (Beta), and no advantage of R.1 after it spreads beyond Japan. Cutting back data to earlier time horizons reveals that uncertainty is large very soon after emergence, but that estimates of selection stabilize after several weeks. Our results also show substantial heterogeneity among countries, demonstrating the need for a truly global perspective on the molecular epidemiology of SARS-CoV-2.


Subject(s)
COVID-19/virology , Mutation , SARS-CoV-2/classification , SARS-CoV-2/genetics , Humans , Japan , Models, Theoretical , Netherlands , SARS-CoV-2/isolation & purification , Spike Glycoprotein, Coronavirus/genetics , United Kingdom
4.
Cell Host Microbe ; 29(4): 529-539.e3, 2021 04 14.
Article in English | MEDLINE | ID: covidwho-1309188

ABSTRACT

All current vaccines for COVID-19 utilize ancestral SARS-CoV-2 spike with the goal of generating protective neutralizing antibodies. The recent emergence and rapid spread of several SARS-CoV-2 variants carrying multiple spike mutations raise concerns about possible immune escape. One variant, first identified in the United Kingdom (B.1.1.7, also called 20I/501Y.V1), contains eight spike mutations with potential to impact antibody therapy, vaccine efficacy, and risk of reinfection. Here, we show that B.1.1.7 remains sensitive to neutralization, albeit at moderately reduced levels (∼sim;2-fold), by serum samples from convalescent individuals and recipients of an mRNA vaccine (mRNA-1273, Moderna) and a protein nanoparticle vaccine (NVX-CoV2373, Novavax). A subset of monoclonal antibodies to the receptor binding domain (RBD) of spike are less effective against the variant, while others are largely unaffected. These findings indicate that variant B.1.1.7 is unlikely to be a major concern for current vaccines or for an increased risk of reinfection.


Subject(s)
Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , COVID-19 Vaccines/immunology , SARS-CoV-2/immunology , 2019-nCoV Vaccine mRNA-1273 , Adolescent , Adult , Aged , Aged, 80 and over , Antibodies, Monoclonal/immunology , Female , Humans , Male , Middle Aged , Mutation , Neutralization Tests , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/immunology , Young Adult
5.
J Theor Biol ; 517: 110621, 2021 05 21.
Article in English | MEDLINE | ID: covidwho-1114510

ABSTRACT

SARS-CoV-2 rapidly spread from a regional outbreak to a global pandemic in just a few months. Global research efforts have focused on developing effective vaccines against COVID-19. However, some of the basic epidemiological parameters, such as the exponential epidemic growth rate and the basic reproductive number, R0, across geographic areas are still not well quantified. Here, we developed and fit a mathematical model to case and death count data collected from the United States and eight European countries during the early epidemic period before broad control measures were implemented. Results show that the early epidemic grew exponentially at rates between 0.18 and 0.29/day (epidemic doubling times between 2.4 and 3.9 days). We found that for such rapid epidemic growth, high levels of intervention efforts are necessary, no matter the goal is mitigation or containment. We discuss the current estimates of the mean serial interval, and argue that existing evidence suggests that the interval is between 6 and 8 days in the absence of active isolation efforts. Using parameters consistent with this range, we estimated the median R0 value to be 5.8 (confidence interval: 4.7-7.3) in the United States and between 3.6 and 6.1 in the eight European countries. We further analyze how vaccination schedules depend on R0, the duration of protective immunity to SARS-CoV-2, and show that individual-level heterogeneity in vaccine induced immunity can significantly affect vaccination schedules.


Subject(s)
COVID-19 Vaccines/therapeutic use , COVID-19 , Models, Biological , SARS-CoV-2 , Vaccination , COVID-19/epidemiology , COVID-19/prevention & control , Europe/epidemiology , Female , Humans , Male , United States/epidemiology
6.
Cell Host Microbe ; 29(1): 23-31.e4, 2021 01 13.
Article in English | MEDLINE | ID: covidwho-956078

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein acquired a D614G mutation early in the pandemic that confers greater infectivity and is now the globally dominant form. To determine whether D614G might also mediate neutralization escape that could compromise vaccine efficacy, sera from spike-immunized mice, nonhuman primates, and humans were evaluated for neutralization of pseudoviruses bearing either D614 or G614 spike. In all cases, the G614 pseudovirus was moderately more susceptible to neutralization. The G614 pseudovirus also was more susceptible to neutralization by receptor-binding domain (RBD) monoclonal antibodies and convalescent sera from people infected with either form of the virus. Negative stain electron microscopy revealed a higher percentage of the 1-RBD "up" conformation in the G614 spike, suggesting increased epitope exposure as a mechanism of enhanced vulnerability to neutralization. Based on these findings, the D614G mutation is not expected to be an obstacle for current vaccine development.


Subject(s)
COVID-19/therapy , Mutation , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/immunology , Adolescent , Adult , Animals , Antibodies, Monoclonal/immunology , Binding Sites , COVID-19/immunology , COVID-19 Vaccines/immunology , Female , HEK293 Cells , Humans , Immunization, Passive/methods , Macaca mulatta , Male , Mice, Inbred BALB C , Middle Aged , Neutralization Tests , SARS-CoV-2/pathogenicity , Spike Glycoprotein, Coronavirus/chemistry , Young Adult , COVID-19 Serotherapy
7.
PLoS One ; 15(8): e0236776, 2020.
Article in English | MEDLINE | ID: covidwho-696584

ABSTRACT

We analyzed COVID-19 data through May 6th, 2020 using a partially observed Markov process. Our method uses a hybrid deterministic and stochastic formalism that allows for time variable transmission rates and detection probabilities. The model was fit using iterated particle filtering to case count and death count time series from 55 countries. We found evidence for a shrinking epidemic in 30 of the 55 examined countries. Of those 30 countries, 27 have significant evidence for subcritical transmission rates, although the decline in new cases is relatively slow compared to the initial growth rates. Generally, the transmission rates in Europe were lower than in the Americas and Asia. This suggests that global scale social distancing efforts to slow the spread of COVID-19 are effective although they need to be strengthened in many regions and maintained in others to avoid further resurgence of COVID-19. The slow decline also suggests alternative strategies to control the virus are needed before social distancing efforts are partially relaxed.


Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Americas/epidemiology , Asia/epidemiology , Betacoronavirus/isolation & purification , COVID-19 , Coronavirus Infections/diagnosis , Coronavirus Infections/transmission , Coronavirus Infections/virology , Databases, Factual , Europe/epidemiology , Humans , Markov Chains , Pandemics , Pneumonia, Viral/diagnosis , Pneumonia, Viral/transmission , Pneumonia, Viral/virology , SARS-CoV-2
8.
Emerg Infect Dis ; 26(7): 1470-1477, 2020 07.
Article in English | MEDLINE | ID: covidwho-668858

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 is the causative agent of the ongoing coronavirus disease pandemic. Initial estimates of the early dynamics of the outbreak in Wuhan, China, suggested a doubling time of the number of infected persons of 6-7 days and a basic reproductive number (R0) of 2.2-2.7. We collected extensive individual case reports across China and estimated key epidemiologic parameters, including the incubation period (4.2 days). We then designed 2 mathematical modeling approaches to infer the outbreak dynamics in Wuhan by using high-resolution domestic travel and infection data. Results show that the doubling time early in the epidemic in Wuhan was 2.3-3.3 days. Assuming a serial interval of 6-9 days, we calculated a median R0 value of 5.7 (95% CI 3.8-8.9). We further show that active surveillance, contact tracing, quarantine, and early strong social distancing efforts are needed to stop transmission of the virus.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Basic Reproduction Number , COVID-19 , China/epidemiology , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Disease Outbreaks , Humans , Models, Theoretical , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , SARS-CoV-2 , Travel
9.
Cell ; 182(4): 812-827.e19, 2020 08 20.
Article in English | MEDLINE | ID: covidwho-628613

ABSTRACT

A SARS-CoV-2 variant carrying the Spike protein amino acid change D614G has become the most prevalent form in the global pandemic. Dynamic tracking of variant frequencies revealed a recurrent pattern of G614 increase at multiple geographic levels: national, regional, and municipal. The shift occurred even in local epidemics where the original D614 form was well established prior to introduction of the G614 variant. The consistency of this pattern was highly statistically significant, suggesting that the G614 variant may have a fitness advantage. We found that the G614 variant grows to a higher titer as pseudotyped virions. In infected individuals, G614 is associated with lower RT-PCR cycle thresholds, suggestive of higher upper respiratory tract viral loads, but not with increased disease severity. These findings illuminate changes important for a mechanistic understanding of the virus and support continuing surveillance of Spike mutations to aid with development of immunological interventions.


Subject(s)
Betacoronavirus/genetics , Betacoronavirus/pathogenicity , Coronavirus Infections/virology , Pneumonia, Viral/virology , Spike Glycoprotein, Coronavirus/genetics , COVID-19 , Coronavirus Infections/epidemiology , Coronavirus Infections/physiopathology , Epidemiological Monitoring , Genetic Fitness , Genetic Variation , Geographic Information Systems , Hospitalization , Humans , Pandemics , Phylogeny , Pneumonia, Viral/epidemiology , Pneumonia, Viral/physiopathology , Respiratory System/virology , SARS-CoV-2 , Severity of Illness Index , Viral Load
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