scholarly journals Non-Pharmaceutical Interventions and COVID-19 Burden in the United States

2021 ◽  
Author(s):  
Michael J. Ahlers ◽  
Hilary J. Aralis ◽  
Wilson L. Tang ◽  
Jeremy B. Sussman ◽  
Gregg C. Fonarow ◽  
...  
Keyword(s):  
Generalized Linear Models ◽  
Linear Models ◽  
Relative Effectiveness ◽  
State Level ◽  
The United States ◽  
Mitigation Strategies ◽  
Mortality Data ◽  
The U.S ◽  
Pharmaceutical Interventions ◽  
At Home

ABSTRACTBackgroundNon-pharmaceutical interventions (NPIs) are mitigation strategies used to reduce the spread of transmissible diseases. The relative effectiveness of specific NPIs remains uncertain.MethodsWe used state-level Coronavirus disease 2019 (COVID-19) case and mortality data between January 19, 2020 and March 7, 2021 to model NPI policy effectiveness. Empirically derived breakpoints in case and mortality velocities were used to identify periods of stable, decreasing, or increasing COVID-19 burden. The associations between NPI adoption and subsequent decreases in case or death velocities were estimated using generalized linear models accounting for weekly variability shared across states. State-level NPI policies included: stay at home order, indoor public gathering ban (mild >10 or severe ≤10), indoor restaurant dining ban, and public mask mandate.Results28,602,830 cases and 511,899 deaths were recorded. The odds of a decrease in COVID-19 case velocity were significantly elevated for stay at home (OR 2.02, 95% CI 1.63-2.52), indoor dining ban (OR 1.62, 95% CI 1.25-2.10), public mask mandate (OR 2.18, 95% CI 1.47-3.23), and severe gathering ban (OR 1.68, 95% CI 1.31-2.16). In mutually adjusted models, odds remained elevated for stay at home (AOR 1.47, 95% CI 1.04-2.07) and public mask mandate (AOR = 2.27, 95% CI 1.51-3.41). Stay at home (OR 2.00, 95% CI 1.53-2.62; AOR 1.89, 95% CI 1.25-2.87) was also associated with greater likelihood of decrease in death velocity in unadjusted and adjusted models.ConclusionsNPIs employed in the U.S. during the COVID-19 pandemic, most significantly stay at home orders, were associated with decreased COVID-19 burden.

scholarly journals How Timing of Stay-home Orders and Mobility Reductions Impacted First-Wave COVID-19 Deaths in US Counties

2020 ◽  
Author(s):  
Michelle Audirac ◽  
Mauricio Tec ◽  
Lauren Ancel Meyers ◽  
Spencer Fox ◽  
Cory Zigler
Keyword(s):  
Disease Transmission ◽  
Relative Effectiveness ◽  
Credible Interval ◽  
The United States ◽  
Transmission Risk ◽  
Mortality Data ◽  
Population Mobility ◽  
Bayesian Hierarchical ◽  
Epidemic Dynamics ◽  
At Home

AbstractSARS-CoV-2 transmission continues to evolve in the United States following the large second wave in the Summer. Understanding how location-specific variations in non-pharmaceutical epidemic control policies and behaviors contributed to disease transmission will be key for designing effective strategies to avoid future resurgences. We offer a statistical analysis of the relative effectiveness of the timing of both official stay-at-home orders and population mobility reductions, offering a distinct (but complementary) dimension of evidence gleaned from more traditional mechanistic models of epidemic dynamics. Specifically, we use a Bayesian hierarchical model fit to county-level mortality data from the first wave of the pandemic from Jan 21 2020 through May 10 2020 to establish how timing of stay-at-home orders and population mobility changes impacted county-specific epidemic growth. We find that population mobility reductions generally preceded stay-at-home orders, and among 356 counties with a pronounced early local epidemic between January 21 and May 10 (representing 195 million people and 32,000 observed deaths), a 10 day delay in population mobility reduction would have added 16,149 (95% credible interval [CI] 9,517 24,381) deaths by Apr 20, whereas shifting mobility reductions 10 days earlier would have saved 13,571 (95% CI 8,449 16,930) lives. Analogous estimates attributable to the timing of explicit stay-at-home policies were less pronounced, suggesting that mobility changes were the clearer drivers of epidemic dynamics. Our results also suggest that the timing of mobility reductions and policies most impacted epidemic dynamics in larger, urban counties compared with smaller, rural ones. Overall, our results suggest that community behavioral changes had greater impact on curve flattening during the Spring wave compared with stay at home orders. Thus, community engagement and buy-in with precautionary policies may be more important for predicting transmission risk than explicit policies.

scholarly journals Toward Achieving a Vaccine-Derived Herd Immunity Threshold for COVID-19 in the U.S.

2021 ◽  
Vol 9 ◽  
Author(s):  
Abba B. Gumel ◽  
Enahoro A. Iboi ◽  
Calistus N. Ngonghala ◽  
Gideon A. Ngwa
Keyword(s):  
Public Health ◽  
United States ◽  
Herd Immunity ◽  
Face Mask ◽  
The United States ◽  
Mortality Data ◽  
Deterministic System ◽  
Therapeutic Benefits ◽  
The U.S ◽  
Pharmaceutical Interventions

A novel coronavirus emerged in December of 2019 (COVID-19), causing a pandemic that inflicted unprecedented public health and economic burden in all nooks and corners of the world. Although the control of COVID-19 largely focused on the use of basic public health measures (primarily based on using non-pharmaceutical interventions, such as quarantine, isolation, social-distancing, face mask usage, and community lockdowns) initially, three safe and highly-effective vaccines (by AstraZeneca Inc., Moderna Inc., and Pfizer Inc.), were approved for use in humans in December 2020. We present a new mathematical model for assessing the population-level impact of these vaccines on curtailing the burden of COVID-19. The model stratifies the total population into two subgroups, based on whether or not they habitually wear face mask in public. The resulting multigroup model, which takes the form of a deterministic system of nonlinear differential equations, is fitted and parameterized using COVID-19 cumulative mortality data for the third wave of the COVID-19 pandemic in the United States. Conditions for the asymptotic stability of the associated disease-free equilibrium, as well as an expression for the vaccine-derived herd immunity threshold, are rigorously derived. Numerical simulations of the model show that the size of the initial proportion of individuals in the mask-wearing group, together with positive change in behavior from the non-mask wearing group (as well as those in the mask-wearing group, who do not abandon their mask-wearing habit) play a crucial role in effectively curtailing the COVID-19 pandemic in the United States. This study further shows that the prospect of achieving vaccine-derived herd immunity (required for COVID-19 elimination) in the U.S., using the Pfizer or Moderna vaccine, is quite promising. In particular, our study shows that herd immunity can be achieved in the U.S. if at least 60% of the population are fully vaccinated. Furthermore, the prospect of eliminating the pandemic in the U.S. in the year 2021 is significantly enhanced if the vaccination program is complemented with non-pharmaceutical interventions at moderate increased levels of compliance (in relation to their baseline compliance). The study further suggests that, while the waning of natural and vaccine-derived immunity against COVID-19 induces only a marginal increase in the burden and projected time-to-elimination of the pandemic, adding the impacts of therapeutic benefits of the vaccines into the model resulted in a dramatic reduction in the burden and time-to-elimination of the pandemic.

scholarly journals Modeling COVID-19 scenarios for the United States

2020 ◽  
Author(s):  
Keyword(s):  
United States ◽  
State Level ◽  
The United States ◽  
Intervention Strategies ◽  
Mortality Data ◽  
Reference Scenario ◽  
Seir Model ◽  
Social Distancing ◽  
Per Capita ◽  
Pharmaceutical Interventions

AbstractWe use COVID-19 case and mortality data from 1 February 2020 to 21 September 2020 and a deterministic SEIR (susceptible, exposed, infectious and recovered) compartmental framework to model possible trajectories of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and the effects of non-pharmaceutical interventions in the United States at the state level from 22 September 2020 through 28 February 2021. Using this SEIR model, and projections of critical driving covariates (pneumonia seasonality, mobility, testing rates and mask use per capita), we assessed scenarios of social distancing mandates and levels of mask use. Projections of current non-pharmaceutical intervention strategies by state—with social distancing mandates reinstated when a threshold of 8 deaths per million population is exceeded (reference scenario)—suggest that, cumulatively, 511,373 (469,578–578,347) lives could be lost to COVID-19 across the United States by 28 February 2021. We find that achieving universal mask use (95% mask use in public) could be sufficient to ameliorate the worst effects of epidemic resurgences in many states. Universal mask use could save an additional 129,574 (85,284–170,867) lives from September 22, 2020 through the end of February 2021, or an additional 95,814 (60,731–133,077) lives assuming a lesser adoption of mask wearing (85%), when compared to the reference scenario.

scholarly journals Timing of social distancing policies and COVID-19 mortality: county-level evidence from the U.S.

2021 ◽  
Author(s):  
Catalina Amuedo-Dorantes ◽  
Neeraj Kaushal ◽  
Ashley N. Muchow
Keyword(s):  
New York ◽  
Political Ideology ◽  
Death Rate ◽  
The United States ◽  
County Level ◽  
Level Data ◽  
Level Information ◽  
Alternative Measures ◽  
The U.S ◽  
Pharmaceutical Interventions

AbstractUsing county-level data on COVID-19 mortality and infections, along with county-level information on the adoption of non-pharmaceutical interventions (NPIs), we examine how the speed of NPI adoption affected COVID-19 mortality in the United States. Our estimates suggest that adopting safer-at-home orders or non-essential business closures 1 day before infections double can curtail the COVID-19 death rate by 1.9%. This finding proves robust to alternative measures of NPI adoption speed, model specifications that control for testing, other NPIs, and mobility and across various samples (national, the Northeast, excluding New York, and excluding the Northeast). We also find that the adoption speed of NPIs is associated with lower infections and is unrelated to non-COVID deaths, suggesting these measures slowed contagion. Finally, NPI adoption speed appears to have been less effective in Republican counties, suggesting that political ideology might have compromised their efficacy.

scholarly journals Tracking U.S. Pertussis Incidence: Correlation of Public Health Surveillance and Google Search Data Varies by State

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Christopher H. Arehart ◽  
Michael Z. David ◽  
Vanja Dukic
Keyword(s):  
Public Health ◽  
Linear Models ◽  
State Level ◽  
Individual State ◽  
Control And Prevention ◽  
Search Data ◽  
State Models ◽  
Uniform Manner ◽  
Google Search ◽  
The U.S

AbstractThe Morbidity and Mortality Weekly Reports of the U.S. Centers for Disease Control and Prevention document a raw proxy for counts of pertussis cases in the U.S., and the Project Tycho (PT) database provides an improved source of these weekly data. These data are limited because of reporting delays, variation in state-level surveillance practices, and changes over time in diagnosis methods. We aim to assess whether Google Trends (GT) search data track pertussis incidence relative to PT data and if sociodemographic characteristics explain some variation in the accuracy of state-level models. GT and PT data were used to construct auto-correlation corrected linear models for pertussis incidence in 2004–2011 for the entire U.S. and each individual state. The national model resulted in a moderate correlation (adjusted R2 = 0.2369, p < 0.05), and state models tracked PT data for some but not all states. Sociodemographic variables explained approximately 30% of the variation in performance of individual state-level models. The significant correlation between GT models and public health data suggests that GT is a potentially useful pertussis surveillance tool. However, the variable accuracy of this tool by state suggests GT surveillance cannot be applied in a uniform manner across geographic sub-regions.

Human Trafficking, Immigration Regulation, and Subfederal Criminalization

2017 ◽  
Vol 20 (1) ◽  
pp. 96-129 ◽  
Author(s):  
Jennifer M. Chacón
Keyword(s):  
State Level ◽  
The United States ◽  
Trafficking In Persons ◽  
International Regulation ◽  
The Past ◽  
Women And Children ◽  
Comparative Treatment ◽  
Systemic Problems ◽  
Trafficking Victims ◽  
The U.S

In the fifteen years since the enactment of the Trafficking Victims Protection Act—the U.S. legislation implementing the Protocol to Prevent, Suppress and Punish Trafficking in Persons, Especially Women and Children—every state in the United States has enacted its own, state-level antitrafficking law. This paper presents a multistate survey of state-level antitrafficking laws and the criminal prosecutions that have been conducted pursuant to those over the past decade. The comparative treatment of noncitizens and citizens in antitrafficking prosecutions is of particular concern. This research reveals that while subfederal implementation of antitrafficking laws has the potential to complement stated federal and international antitrafficking objectives, it also has the power to subvert and undermine those goals. State-level enforcement both mirrors and amplifies some of the systemic problems that arise when the criminal law is used as a tool to combat trafficking, including the manipulation of antitrafficking tools and rhetoric to perpetuate racial subordination and migrant criminalization. Ultimately, this research offers broader theoretical insights into the promises and pitfalls of overlapping criminal jurisdiction both within federalist systems and within frameworks of international regulation.

scholarly journals SAT-447 Thyroid Function, Cardiovascular Disease, and Mortality: A Mediation Analysis

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Kosuke Inoue ◽  
Beate Ritz ◽  
Gregory A Brent ◽  
Ramin Ebrahimi ◽  
Connie Rhee ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Mediation Analysis ◽  
Subclinical Hypothyroidism ◽  
The United States ◽  
Thyroid Stimulating Hormone ◽  
Mediation Effect ◽  
Mortality Data ◽  
All Cause Mortality ◽  
The U.S ◽  
Stimulating Hormone

Abstract Background: Subclinical hypothyroidism is a common clinical entity among the United States (U.S) adults and has been associated with increased risk of cardiovascular disease (CVD) and mortality in some studies. However, the mediation effect of CVD from elevated serum thyroid stimulating hormone (TSH) to mortality has not yet been well established or sufficiently quantified. In this study, we aimed to elucidate the extent to which subclinical hypothyroidism or high-normal thyroid stimulating hormone [TSH] concentrations (i.e. upper normative-range TSH concentrations) contribute to mortality through its effect on CVD among U.S. adults. Methods: This study relies on the U.S. representative samples of 9,020 adults enrolled in the National Health and Nutrition Examination Surveys (NHANES) 2001-2002, 2007-2012 and their mortality data through 2015. We employed Cox proportional hazards regression models to investigate associations between the TSH concentration categories (subclinical hypothyroidism or tertiles of serum TSH concentrations within the reference range) and all-cause mortality. Utilizing mediation analysis within the counterfactual framework, we estimated the mediation effect of CVD on the association between TSH and all-cause mortality. Results: The median duration of follow-up for mortality ascertainment was 7.3 (interquartile range, 5.4–8.3) years, during which 435 deaths from all causes were identified. Subjects with TSH in the subclinical hypothyroidism and the high-normal TSH tertile concentrations were associated with increased all-cause mortality (subclinical hypothyroidism: hazard ratio [HR], 1.90; 95% confidence interval [CI], 1.14–3.19; high-normal TSH: HR, 1.36; 95% CI, 1.07–1.73) compared with the middle-normal TSH tertile concentration. CVD mediated 14.3% and 5.9% of the effects of subclinical hypothyroidism and high-normal TSH on all-cause mortality, respectively, with the CVD mediation effect being most pronounced in women and subjects ≥60 years old. No mediation through CVD was found for low-normal TSH levels and all-cause mortality. Conclusion: CVD mediated the effects of subclinical hypothyroid and high-normal TSH concentrations on all-cause mortality in the U.S. general population. These findings may have potential implications for treatment, and early and more aggressive CVD screening for such at risk populations. Further studies are needed to examine the clinical impact of targeted therapy towards mid-normal TSH concentration.

The Formative Years of the Iran–United States Claims Tribunal

1997 ◽  
Vol 66 (1) ◽  
pp. 23-32
Author(s):  
Keyword(s):  
United States ◽  
The United States ◽  
Arbitral Tribunal ◽  
International Arbitration ◽  
Wide Range ◽  
The Hague ◽  
The U.S ◽  
Formative Years ◽  
At Home

AbstractAfter the seizure of the U.S. Embassy in Tehran on 4 November 1979 and the taking of 52 American citizens as hostages, and after President Carter in retaliation froze Iranian assets in the United States banks, at home and overseas, valued at some 12 billion dollars, the grave crisis was not finally settled until 19 January 1981, after 444 days. The hostages were released and arrangements were made for the free transfer of the frozen Iranian assets. The settlement also provided for the establishment of an Arbitral Tribunal at the Hague for the solution of a wide range of specified claims. An ``insider'' tries in this article to describe the complex and burdensome building up and organisation of the largest and most important international arbitration to date.

Who Writes Criminal Laws? Actors, Values, and Institutions in Criminal Law-Making / Wer schreibt das Strafrecht? Akteure, Werte und Institutionen der Strafrechts-gesetzbegung

2014 ◽  
Vol 34 (1-2) ◽  
Author(s):  
Andrew Hammel
Keyword(s):  
Criminal Law ◽  
Structural Difference ◽  
State Level ◽  
The United States ◽  
Expert Control ◽  
Nation States ◽  
Historical Factors ◽  
Penal Law ◽  
The U.S ◽  
Law Making

AbstractThe responses of the U.S. and Europe to increased crime from the 1960s to the 1990s differed starkly: the U.S. enacted a punitive agenda, while penal polity and incarceration rates in Western (and Eastern) Europe remained gener­ally stable. To explain this divergence, many commentators invoke cultural or historical factors such as America’s ‘frontier mentality” or Calvinist religious heritage. This article proposes another focus: differing cultures of criminal law-making. During the Enlightenment, a pattern of expert control over penal law emerged in most European nation-states. The pattern still holds - even today, major changes to penal polity are still entrusted to groups of elite professors, jurists and senior civil servants, who create coherent codes covering the entire national territory. In the United States, no tradition of expert control took hold. Criminal law is made at the state level, there is little emphasis on logical code-drafting and shifting local majorities can pass new criminal laws almost at will This structural difference in who writes criminal laws has far-reaching effects not only on the how crime is defined, but on other factors such as public expectations of the criminal justice system and the values penal legislation is thought to express.

scholarly journals Population Optimally Immunized after Accounting for Type-Specific COVID-19 Vaccine Waning Intervals: State-Level Prevalence and Trends

2021 ◽  
Author(s):  
Elizabeth B Pathak ◽  
Jason L Salemi
Keyword(s):  
New York ◽  
Booster Dose ◽  
Classification Scheme ◽  
Total Population ◽  
State Level ◽  
The United States ◽  
Mitigation Strategies ◽  
Accurate Assessment ◽  
National Immunization ◽  
Waning Immunity

BACKGROUND: COVID-19 vaccines exhibit real-world waning effectiveness against SARS-CoV-2 infection within the first 3-6 months after a completed series. Consequently, the main metric tracked by the CDC (percent "fully vaccinated," with no adjustment for booster status) has become insufficiently informative. METHODS: We analyzed CDC daily vaccination data to quantify COVID-19 immunization status for 4 mutually-exclusive groups: (1) not immunized; (2) partially immunized (people who received the 1st dose of a 2-dose series); (3) immunized with waning immunity (previously immunized people whose booster dose is overdue); and (4) optimally immunized (people who: (a) received the Janssen vaccine <2 months ago or completed an mRNA vaccine series <6 months ago, or (b) received the Janssen vaccine >2 months ago or completed an mRNA vaccine series >6 months ago and received a booster dose.) RESULTS: The proportion of the total US population who were optimally immunized against COVID-19 fell from a high of 45.3% on July 17 to 29.4% on November 30. During November, the majority of states experienced a worsening trend in the percent of the total population who were overdue for a booster dose, including the 4 largest states, with percentage point increases of 3.5 in New York, 3.4 in California, 2.3 in Texas and 1.7 in Florida. CONCLUSIONS: Our proposed classification scheme accounts for type-specific vaccine waning intervals, provides an accurate assessment of progress toward national immunization goals, and reveals the urgent need for additional public health mitigation strategies to successfully combat the COVID-19 pandemic in the United States.

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