scholarly journals SARS-CoV-2 variant dynamics across US states show consistent differences in effective reproduction numbers

2021 ◽  
Author(s):  
Marlin D. Figgins ◽  
Trevor Bedford
Keyword(s):  
Reproduction Number ◽  
Sequence Data ◽  
The United States ◽  
Transmission Rates ◽  
Reproduction Numbers ◽  
The Us ◽  
Relative Transmission ◽  
Variant Frequency ◽  
The Rich ◽  
Case Data

AbstractAccurately estimating relative transmission rates of SARS-CoV-2 Variant of Concern and Variant of Interest viruses remains a scientific and public health priority. Recent studies have used the sample proportions of different variants from sequence data to describe variant frequency dynamics and relative transmission rates, but frequencies alone cannot capture the rich epidemiological behavior of SARS-CoV-2. Here, we extend methods for inferring the effective reproduction number of an epidemic using confirmed case data to jointly estimate variant-specific effective reproduction numbers and frequencies of co-circulating variants using case data and genetic sequences across states in the US from January to October 2021. Our method can be used to infer structured relationships between effective reproduction numbers across time series allowing us to estimate fixed variant-specific growth advantages. We use this model to estimate the effective reproduction number of SARS-CoV-2 Variants of Concern and Variants of Interest in the United States and estimate consistent growth advantages of particular variants across different locations.

scholarly journals 130. increase in Multidrug Resistance (2011–2018) and the Emergence of Extensive Drug Resistance (2020) in shigella Sonnei in the United States

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S195-S195
Author(s):  
Naeemah Z Logan ◽  
Beth E Karp ◽  
Kaitlin A Tagg ◽  
Claire Burns-Lynch ◽  
Jessica Chen ◽  
...  
Keyword(s):  
United States ◽  
Multidrug Resistance ◽  
Disease Surveillance ◽  
Sequence Data ◽  
The United States ◽  
Multidrug Resistant ◽  
Shigella Sonnei ◽  
Short Read ◽  
Men 2 ◽  
The Us

Abstract Background Multidrug-resistant (MDR) Shigella sonnei infections are a serious public health threat, and outbreaks are common among men who have sex with men (MSM). In February 2020, Australia’s Department of Health notified CDC of extensively drug-resistant (XDR) S. sonnei in 2 Australian residents linked to a cruise that departed from Florida. We describe an international outbreak of XDR S. sonnei and report on trends in MDR among S. sonnei in the United States. Methods Health departments (HDs) submit every 20th Shigella isolate to CDC’s National Antimicrobial Resistance Monitoring System (NARMS) laboratory for susceptibility testing. We defined MDR as decreased susceptibility to azithromycin (MIC ≥32 µg/mL) with resistance to ampicillin, ciprofloxacin, and cotrimoxazole, and XDR as MDR with additional resistance to ceftriaxone. We used PulseNet, the national subtyping network for enteric disease surveillance, to identify US isolates related to the Australian XDR isolates by short-read whole genome sequencing. We screened these isolates for resistance determinants (ResFinder v3.0) and plasmid replicons (PlasmidFinder) and obtained patient histories from HDs. We used long-read sequencing to generate closed plasmid sequences for 2 XDR isolates. Results NARMS tested 2,781 S. sonnei surveillance isolates during 2011–2018; 80 (2.9%) were MDR, including 1 (0.04%) that was XDR. MDR isolates were from men (87%), women (9%), and children (4%). MDR increased from 0% in 2011 to 15.3% in 2018 (Figure). In 2020, we identified XDR isolates from 3 US residents on the same cruise as the Australians. The US residents were 41–42 year-old men; 2 with available information were MSM. The US and Australian isolates were highly related (0–1 alleles). Short-read sequence data from all 3 US isolates mapped to the blaCTX-M-27 harboring IncFII plasmids from the 2 Australian isolates with >99% nucleotide identity. blaCTX-M-27 genes confer ceftriaxone resistance. Increase in Percentage of Shigella sonnei Isolates with Multidrug Resistance* in the United States, 2011–2018† Conclusion MDR S. sonnei is increasing and is most often identified among men. XDR S. sonnei infections are emerging and are resistant to all recommended antibiotics, making them difficult to treat without IV antibiotics. This outbreak illustrates the alarming capacity for XDR S. sonnei to disseminate globally among at-risk populations, such as MSM. Disclosures All Authors: No reported disclosures

scholarly journals COVID-19 Time-varying Reproduction Numbers Worldwide: An Empirical Analysis of Mandatory and Voluntary Social Distancing

2021 ◽  
Author(s):  
Alexander Chudik ◽  
M. Hashem Pesaran ◽  
Alessandro Rebucci
Keyword(s):  
Reproduction Number ◽  
Transmission Rate ◽  
Economic Incentives ◽  
Moment Condition ◽  
Time Varying ◽  
Linear Interaction ◽  
Susceptible Population ◽  
Social Distancing ◽  
Transmission Rates ◽  
Reproduction Numbers

AbstractThis paper estimates time-varying COVID-19 reproduction numbers worldwide solely based on the number of reported infected cases, allowing for under-reporting. Estimation is based on a moment condition that can be derived from an agent-based stochastic network model of COVID-19 transmission. The outcomes in terms of the reproduction number and the trajectory of per-capita cases through the end of 2020 are very diverse. The reproduction number depends on the transmission rate and the proportion of susceptible population, or the herd immunity effect. Changes in the transmission rate depend on changes in the behavior of the virus, re-flecting mutations and vaccinations, and changes in people’s behavior, reflecting voluntary or government mandated isolation. Over our sample period, neither mutation nor vaccination are major factors, so one can attribute variation in the transmission rate to variations in behavior. Evidence based on panel data models explaining transmission rates for nine European countries indicates that the diversity of outcomes resulted from the non-linear interaction of mandatory containment measures, voluntary precautionary isolation, and the economic incentives that gov-ernments provided to support isolation. These effects are precisely estimated and robust to various assumptions. As a result, countries with seemingly different social distancing policies achieved quite similar outcomes in terms of the reproduction number. These results imply that ignoring the voluntary component of social distancing could introduce an upward bias in the estimates of the effects of lock-downs and support policies on the transmission rates.JEL ClassificationD0, F6, C4, I120, E7

scholarly journals Estimation of COVID-19 transmission rates in California and the U.S. with reporting delays

2020 ◽  
Author(s):  
Lee Worden ◽  
Rae Wannier ◽  
Micaela Neus ◽  
Jennifer C. Kwan ◽  
Alex Y. Ge ◽  
...  
Keyword(s):  
United States ◽  
Symptom Onset ◽  
The United States ◽  
Time Varying ◽  
Transmission Rates ◽  
Reproduction Numbers ◽  
Serial Interval ◽  
Reporting Delays ◽  
Interval Distribution ◽  
The U.S

We estimated time-varying reproduction numbers of COVID-19 transmission in counties and regions of California and in states of the United States, using the Wallinga-Teunis method of estimations applied to publicly available data. The serial interval distribution assumed incorporates wide uncertainty in delays from symptom onset to case reporting. This assumption contributes smoothing and a small but meaningful increase in numerical estimates of reproduction numbers due to the likely existence of secondary cases not yet reported. Transmission in many areas of the U.S. may not yet be controlled, including areas in which case counts appear to be stable or slowly declining.

Wealth Defense and the Complicity of Liberal Democracy

Wealth ◽  
2017 ◽  
Author(s):  
Jeffrey A. Winters
Keyword(s):  
Government Policy ◽  
Wealth Inequality ◽  
The United States ◽  
Protective Services ◽  
Historical View ◽  
Wealth Concentration ◽  
The Social ◽  
The Us ◽  
The Rich ◽  
Modern Era

Sustaining extreme material inequality is neither easy nor automatic. It requires constant and active strategies of wealth defense by the rich, including using their money to hire protective services (which in the twentieth century took the form of a specialized wealth defense industry). An important transformation over the centuries was the movement of violence out of the hands of the rich in exchange for their support for impersonal institutions of coercion whose first priority has been the defense of property rights that make great fortunes viable politically. This chapter focuses on the changing politics and power that undergird wealth stratification. The analysis takes a deep historical view of the social tensions inherent in wealth concentration, starting with the origins of wealth inequality, and continuing with a discussion of the strategies and politics of wealth defense as personal fortunes grew in scale and as threats and predations multiplied. The second half of the chapter focuses on the modern era through an examination of the United States from the 1780s to the present. The US case demonstrates that for democracy and extreme wealth stratification to be compatible, democracy must first be structurally impaired and ideologically reframed to hinder egalitarian impulses from becoming government policy.

Value, politics and democracy in the United States

2011 ◽  
Vol 59 (2) ◽  
pp. 186-199 ◽  
Author(s):  
David Graeber
Keyword(s):  
Working Class ◽  
Common Good ◽  
Intrinsic Value ◽  
The United States ◽  
Economic Interests ◽  
White American ◽  
The Arts ◽  
The Us ◽  
The Rich ◽  
American Working Class

This article examines the role of values in the political discourse of the last decade in the US. It embarks from what many observers had described as a puzzle: the fact that significant parts of the American working class voted against their economic interests but in line with what they perceived to be their values. As a result, a president had been re-elected who cut taxes for the rich while waging an expensive war in Iraq and increasing public debt to historically unprecedented levels. It is argued that large sectors of the white American working class were disappointed with liberal politicians because they associated them with a cultural elite that occupied positions in society that allowed them to pursue careers of intrinsic value in the arts, science, or politics but which were largely closed to the working class. It is thus suggested that the ‘culture wars’ in the US are better interpreted as a struggle over access to the means to behave altruistically. The article rejects the widespread assumption that individuals are narrowly conceived economic self-interest maximizers. Rather, it suggests that human fulfilment can be related to the satisfaction derived from working for the common good.

scholarly journals Forecasting the Spread of COVID-19 under Different Reopening Strategies

2020 ◽  
Author(s):  
Meng Liu ◽  
Raphael Thomadsen ◽  
Song Yao
Keyword(s):  
United States ◽  
Growth Rate ◽  
Population Density ◽  
The United States ◽  
Sir Model ◽  
Social Distancing ◽  
Mobility Data ◽  
The Social ◽  
The Us ◽  
Case Data

ABSTRACTWe combine COVID-19 case data with demographic and mobility data to estimate a modified susceptible-infected-recovered (SIR) model for the spread of this disease in the United States. We find that the incidence of infectious COVID-19 individuals has a concave effect on contagion, as would be expected if people have inter-related social networks. We also demonstrate that social distancing and population density have large effects on the rate of contagion. The social distancing in late March and April substantially reduced the number of COVID-19 cases. However, the concave contagion pattern means that when social distancing measures are lifted, the growth rate is considerable but will not be exponential as predicted by standard SIR models. Furthermore, counties with the lowest population density could likely avoid high levels of contagion even with no social distancing. We forecast rates of new cases for COVID-19 under different social distancing norms and find that if social distancing is eliminated there will be a massive increase in the cases of COVID-19, about double what would occur if the US only restored to 50% of the way to normalcy.

scholarly journals What can we learn from COVID-19 data by using epidemic models with unidentified infectious cases?

2021 ◽  
Author(s):  
quentin Griette ◽  
Jacques Demongeot ◽  
pierre magal
Keyword(s):  
Social Interactions ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Social Effects ◽  
Time Dependent ◽  
Reproduction Numbers ◽  
The Social ◽  
The World ◽  
Early Beginning ◽  
Case Data

Background: The COVID-19 epidemic, which started in late December 2019 and rapidly spread throughout the world, was accompanied by an unprecedented release of reported case data. Our objective is to propose a fresh look at this data by coupling a phenomenological description to the epidemiological dynamics. Methods: We use a phenomenological model to describe and regularize the data. This model can be matched by a single mathematical model reproducing the epidemiological dynamics with a time-dependent transmission rate. We provide a method to compute this transmission rate and reconstruct the changes in the social interactions between people as well as changes in host-pathogen interactions. This method is applied to the cumulative case data of 8 different geographic areas. Findings: We reconstruct the transmission rate from the data, therefore we are in position to understand the contribution of the dynamical effects of social interactions (contacts between individuals) and the contribution of the dynamics of the epidemic. We deduce from the comparison of several instantaneous reproduction numbers that the social effects are the most important in the dynamic of COVID-19. We obtain an instantaneous reproduction number that stays below $3.5$ from early beginning of the epidemic. Conclusion: The instantaneous reproduction number staying below $3.5$ implies that it is sufficient to vaccinate $71\%$ of the population in each state or country considered in our study. Therefore assuming the vaccines will remain efficient against the new variants, and to be more confident it is sufficient to vaccinate $75-80\%$ to get rid of COVID-19 in each state or country. Funding: This research was funded by the Agence Nationale de la Recherche in France (Project name: MPCUII (PM) and (QG))

scholarly journals Optimizing COVID-19 vaccine distribution across the United States using deterministic and stochastic recurrent neural networks

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253925
Author(s):  
Mohammad Reza Davahli ◽  
Waldemar Karwowski ◽  
Krzysztof Fiok
Keyword(s):  
Short Term Memory ◽  
The United States ◽  
Self Organizing Map ◽  
Us States ◽  
Mixture Density ◽  
Reproduction Numbers ◽  
The Us ◽  
Production And Distribution ◽  
Long Short Term Memory ◽  
Vaccine Distribution

Optimizing COVID-19 vaccine distribution can help plan around the limited production and distribution of vaccination, particularly in early stages. One of the main criteria for equitable vaccine distribution is predicting the geographic distribution of active virus at the time of vaccination. This research developed sequence-learning models to predict the behavior of the COVID-19 pandemic across the US, based on previously reported information. For this objective, we used two time-series datasets of confirmed COVID-19 cases and COVID-19 effective reproduction numbers from January 22, 2020 to November 26, 2020 for all states in the US. The datasets have 310 time-steps (days) and 50 features (US states). To avoid training the models for all states, we categorized US states on the basis of their similarity to previously reported COVID-19 behavior. For this purpose, we used an unsupervised self-organizing map to categorize all states of the US into four groups on the basis of the similarity of their effective reproduction numbers. After selecting a leading state (the state with earliest outbreaks) in each group, we developed deterministic and stochastic Long Short Term Memory (LSTM) and Mixture Density Network (MDN) models. We trained the models with data from each leading state to make predictions, then compared the models with a baseline linear regression model. We also remove seasonality and trends from a dataset of non-stationary COVID-19 cases to determine the effects on prediction. We showed that the deterministic LSTM model trained on the COVID-19 effective reproduction numbers outperforms other prediction methods.

scholarly journals Forecasting the spread of COVID-19 under different reopening strategies

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Meng Liu ◽  
Raphael Thomadsen ◽  
Song Yao
Keyword(s):  
United States ◽  
Social Networks ◽  
Exponential Growth ◽  
The United States ◽  
Sir Model ◽  
Disease Spread ◽  
Social Distancing ◽  
Mobility Data ◽  
The Us ◽  
Case Data

AbstractWe combine COVID-19 case data with mobility data to estimate a modified susceptible-infected-recovered (SIR) model in the United States. In contrast to a standard SIR model, we find that the incidence of COVID-19 spread is concave in the number of infectious individuals, as would be expected if people have inter-related social networks. This concave shape has a significant impact on forecasted COVID-19 cases. In particular, our model forecasts that the number of COVID-19 cases would only have an exponential growth for a brief period at the beginning of the contagion event or right after a reopening, but would quickly settle into a prolonged period of time with stable, slightly declining levels of disease spread. This pattern is consistent with observed levels of COVID-19 cases in the US, but inconsistent with standard SIR modeling. We forecast rates of new cases for COVID-19 under different social distancing norms and find that if social distancing is eliminated there will be a massive increase in the cases of COVID-19.

scholarly journals Identification of Microbes Associated with the Urethra during Health and Inflammation

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Jonathan Alessi ◽  
Rowan Farrell ◽  
Evelyn Toh ◽  
Xiaoli Zhang ◽  
David E. Nelson ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Sequence Data ◽  
The United States ◽  
Metagenomic Sequence ◽  
Sexually Transmitted ◽  
The Us ◽  
Novel Taxa ◽  
Complete Survey ◽  
Crucial Information ◽  
Metagenomic Sequence Data

The number of cases of urethritis, or inflammation of the male urethra, in the US has been estimated to be 2.8 million each year in the United States.1 It is the most common reason young men seek primary care and this syndrome is associated with acute proctitis, epididymitis, and orchitis.2 Approximately half of the cases are idiopathic, meaning that a causative agent cannot be identified. The goal of my project is to identify and characterize novel microorganisms that may be associated with male idiopathic urethritis. We used a variety of approaches to cultivate microorganisms from archived urethral swabs collected from men with idiopathic urethritis and healthy controls. We defined the phylogeny of the isolates using 16S rRNA sequencing to identify organisms that are not presently represented in microbial databases. Currently, we are scaling up a number of novel taxa we identified for genome sequencing. By adding these new genome sequencing to the existing databases we will be able to assign a higher proportion of reads from corresponding metagenomic sequence data and achieve a more complete survey of the male urethral microbiota in health and urethritis. This will provide crucial information which may permit us to identify urethritis associated organisms, develop new molecular diagnostics for these organisms, and discern if how these organisms are sexually transmitted References 1. Brill JR. Diagnosis and treatment of urethritis in men. Am Fam Physician 2010; 81:873–8. 2. Bachmann LH, Manhart LE, Martin DH, Sena AC, Dimitrakoff J, Jensen JS, et al. Advances in the Understanding and Treatment of Male Urethritis. Clin Infect Dis. 2015;61 Suppl 8:S763–S9.

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