scholarly journals Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period

Science ◽  
2020 ◽  
Vol 368 (6493) ◽  
pp. 860-868 ◽  
Author(s):  
Stephen M. Kissler ◽  
Christine Tedijanto ◽  
Edward Goldstein ◽  
Yonatan H. Grad ◽  
Marc Lipsitch
Keyword(s):  
Critical Care ◽  
Time Series Data ◽  
Herd Immunity ◽  
The United States ◽  
Series Data ◽  
Social Distancing ◽  
Serological Studies ◽  
Cross Immunity ◽  
Care Capacity ◽  
Pandemic Wave

It is urgent to understand the future of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) transmission. We used estimates of seasonality, immunity, and cross-immunity for human coronavirus OC43 (HCoV-OC43) and HCoV-HKU1 using time-series data from the United States to inform a model of SARS-CoV-2 transmission. We projected that recurrent wintertime outbreaks of SARS-CoV-2 will probably occur after the initial, most severe pandemic wave. Absent other interventions, a key metric for the success of social distancing is whether critical care capacities are exceeded. To avoid this, prolonged or intermittent social distancing may be necessary into 2022. Additional interventions, including expanded critical care capacity and an effective therapeutic, would improve the success of intermittent distancing and hasten the acquisition of herd immunity. Longitudinal serological studies are urgently needed to determine the extent and duration of immunity to SARS-CoV-2. Even in the event of apparent elimination, SARS-CoV-2 surveillance should be maintained because a resurgence in contagion could be possible as late as 2024.

scholarly journals Projecting the transmission dynamics of SARS-CoV-2 through the post-pandemic period

2020 ◽  
Author(s):  
Stephen M. Kissler ◽  
Christine Tedijanto ◽  
Edward M. Goldstein ◽  
Yonatan H. Grad ◽  
Marc Lipsitch
Keyword(s):  
Full Range ◽  
The United States ◽  
The Other ◽  
Transmission Dynamics ◽  
The Novel ◽  
Serological Studies ◽  
Cross Immunity ◽  
Using Data ◽  
Human Coronaviruses ◽  
Pandemic Wave

AbstractThere is an urgent need to project how transmission of the novel betacoronavirus SARS-CoV-2 will unfold in coming years. These dynamics will depend on seasonality, the duration of immunity, and the strength of cross-immunity to/from the other human coronaviruses. Using data from the United States, we measured how these factors affect transmission of human betacoronaviruses HCoV-OC43 and HCoV-HKU1. We then built a mathematical model to simulate transmission of SARS-CoV-2 through the year 2025. We project that recurrent wintertime outbreaks of SARS-CoV-2 will probably occur after an initial pandemic wave. We summarize the full range of plausible transmission scenarios and identify key data still needed to distinguish between them, most importantly longitudinal serological studies to determine the duration of immunity to SARS-CoV-2.

scholarly journals Social distancing strategies for curbing the COVID-19 epidemic

2020 ◽  
Author(s):  
Stephen Kissler ◽  
Christine Tedijanto ◽  
Marc Lipsitch ◽  
Yonatan H. Grad
Keyword(s):  
United States ◽  
Mathematical Model ◽  
Critical Care ◽  
Seasonal Variation ◽  
The United States ◽  
Healthcare Resources ◽  
Social Distancing ◽  
Hospital Capacity ◽  
Appropriate Care ◽  
Care Capacity

AbstractThe SARS-CoV-2 pandemic is straining healthcare resources worldwide, prompting social distancing measures to reduce transmission intensity. The amount of social distancing needed to curb the SARS-CoV-2 epidemic in the context of seasonally varying transmission remains unclear. Using a mathematical model, we assessed that one-time interventions will be insufficient to maintain COVID-19 prevalence within the critical care capacity of the United States. Seasonal variation in transmission will facilitate epidemic control during the summer months but could lead to an intense resurgence in the autumn. Intermittent distancing measures can maintain control of the epidemic, but without other interventions, these measures may be necessary into 2022. Increasing critical care capacity could reduce the duration of the SARS-CoV-2 epidemic while ensuring that critically ill patients receive appropriate care.SummaryOne-time distancing results in a fall COVID-19 peak. Intermittent efforts require greater hospital capacity and surveillance.

Faktor-Faktor Yang Mempengaruhi Nilai Tukar Dollar Amerika Serikat Terhadap Rupiah Tahun 2000–2013

2017 ◽  
Vol 1 (2) ◽  
pp. 177-191
Author(s):  
Rizki Rahma Kusumadewi ◽  
Wahyu Widayat
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Money Supply ◽  
Time Series Data ◽  
The United States ◽  
Economic Conditions ◽  
Series Data ◽  
Arch Model ◽  
United States Dollar ◽  
The Exchange Rate

Exchange rate is one tool to measure a country’s economic conditions. The growth of a stable currency value indicates that the country has a relatively good economic conditions or stable. This study has the purpose to analyze the factors that affect the exchange rate of the Indonesian Rupiah against the United States Dollar in the period of 2000-2013. The data used in this study is a secondary data which are time series data, made up of exports, imports, inflation, the BI rate, Gross Domestic Product (GDP), and the money supply (M1) in the quarter base, from first quarter on 2000 to fourth quarter on 2013. Regression model time series data used the ARCH-GARCH with ARCH model selection indicates that the variables that significantly influence the exchange rate are exports, inflation, the central bank rate and the money supply (M1). Whereas import and GDP did not give any influence.

scholarly journals Associations between Google Search Trends for Symptoms and COVID-19 Confirmed and Death Cases in the United States

2021 ◽  
Vol 18 (9) ◽  
pp. 4560
Author(s):  
Mostafa Abbas ◽  
Thomas B. Morland ◽  
Eric S. Hall ◽  
Yasser EL-Manzalawy
Keyword(s):  
Functional Data ◽  
Time Series Data ◽  
Principal Component ◽  
State Level ◽  
The United States ◽  
Functional Principal Component Analysis ◽  
Series Data ◽  
Dynamic Correlation ◽  
The Us ◽  
Google Search

We utilize functional data analysis techniques to investigate patterns of COVID-19 positivity and mortality in the US and their associations with Google search trends for COVID-19-related symptoms. Specifically, we represent state-level time series data for COVID-19 and Google search trends for symptoms as smoothed functional curves. Given these functional data, we explore the modes of variation in the data using functional principal component analysis (FPCA). We also apply functional clustering analysis to identify patterns of COVID-19 confirmed case and death trajectories across the US. Moreover, we quantify the associations between Google COVID-19 search trends for symptoms and COVID-19 confirmed case and death trajectories using dynamic correlation. Finally, we examine the dynamics of correlations for the top nine Google search trends of symptoms commonly associated with COVID-19 confirmed case and death trajectories. Our results reveal and characterize distinct patterns for COVID-19 spread and mortality across the US. The dynamics of these correlations suggest the feasibility of using Google queries to forecast COVID-19 cases and mortality for up to three weeks in advance. Our results and analysis framework set the stage for the development of predictive models for forecasting COVID-19 confirmed cases and deaths using historical data and Google search trends for nine symptoms associated with both outcomes.

scholarly journals The 2010 Structural-Demographic Forecast for the 2010–2020 Decade: A Retrospective Assessment

2020 ◽  
Author(s):  
Peter Turchin ◽  
Andrey Korotayev
Keyword(s):  
Western Europe ◽  
Time Series Data ◽  
Political Instability ◽  
The United States ◽  
Stress Index ◽  
Series Data ◽  
Strongly Correlated ◽  
Retrospective Assessment ◽  
The United Kingdom ◽  
The Usa

This article revisits the prediction, made in 2010, that the 2010–2020 decade would likely be a period of growing instability in the United States and Western Europe (Turchin 2010). This prediction was based on a computational model that quantified in the USA such structural-demographic forces for instability as popular immiseration, intraelite competition, and state weakness prior to 2010. Using these trends as inputs, the model calculated and projected forward in time the Political Stress Index, which in the past was strongly correlated with socio-political instability. Ortmans et al. (2017) conducted a similar structural-demographic study for the United Kingdom and obtained similar results. Here we use the Cross-National Time-Series Data Archive for the US, UK, and Western European countries to assess these structural-demographic predictions. We find that such measures of socio-political instability as anti-government demonstrations and riots increased dramatically during the 2010–2020 decade in all of these countries.

Gendered Funding: United Way Board Composition and the Funding of Women- and Girl-Serving Organizations

2021 ◽  
pp. 089976402110574
Author(s):  
Lauren Dula
Keyword(s):  
Time Series Data ◽  
Critical Mass ◽  
Interrupted Time Series ◽  
The United States ◽  
Women In Leadership ◽  
Representative Bureaucracy ◽  
Series Data ◽  
Leadership Positions ◽  
United Way ◽  
Bureaucracy Theory

Representative bureaucracy theory posits that the passive representation of women in leadership positions will lead to active representation of the concerns of women in general. This article attempts to identify whether this theory plays out on boards of nonprofit funding organizations, specifically United Ways across the United States. Using random effects modeling of interrupted time series data covering 15 years, the findings suggest a small yet significant nonlinear effect of women in leadership positions on boards upon the size of funding for women- and girl-serving organizations. This partially supports representative bureaucracy theory, but raises questions as to why there is a negative representational effect past a certain “critical mass” of women.

Abstract 19225: Impact of Change in Resuscitation Guidelines on National Out-of-hospital Cardiac Arrest Outcomes: Fulfilled Expectations?

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Shaker M Eid ◽  
Aiham Albaeni ◽  
Rebeca Rios ◽  
May Baydoun ◽  
Bolanle Akinyele ◽  
...  
Keyword(s):  
Time Series ◽  
Cardiac Arrest ◽  
Time Series Data ◽  
Statistical Significance ◽  
Interrupted Time Series ◽  
The United States ◽  
Series Data ◽  
National Database ◽  
Resuscitation Guidelines ◽  
Hospital Cardiac Arrest

Background: The intent of the 5-yearly Resuscitation Guidelines is to improve outcomes. Previous studies have yielded conflicting reports of a beneficial impact of the 2005 guidelines on out-of-hospital cardiac arrest (OHCA) survival. Using a national database, we examined survival before and after the introduction of both the 2005 and 2010 guidelines. Methods: We used the 2000 through 2012 National Inpatient Sample database to select patients ≥18 years admitted to hospitals in the United States with non-traumatic OHCA (ICD-9 CM codes 427.5 & 427.41). A quasi-experimental (interrupted time series) design was used to compare monthly survival trends. Outcomes for OHCA were compared pre- and post- 2005 and 2010 resuscitation guidelines release as follows: 01/2000-09/2005 vs. 10/2005-9/2010 and 10/2005-9/2010 vs. 10/2010-12/2012. Segmented regression analyses of interrupted time series data were performed to examine changes in survival to hospital discharge. Results: For the pre- and post- guidelines periods, 81600, 69139 and 36556 patients respectively survived to hospital admission following OHCA. Subsequent to the release of the 2005 guidelines, there was a statistically significant worsening in survival trends (β= -0.089, 95% CI -0.163 – -0.016, p =0.018) until the release of the 2010 guidelines when a sharp increase in survival was noted which persisted for the period of study (β= 0.054, 95% CI -0.143 – 0.251, p =0.588) but did not achieve statistical significance (Figure). Conclusion: National clinical guidelines developed to impact outcomes must include mechanisms to assess whether benefit actually occurs. The worsening in OHCA survival following the 2005 guidelines is thought provoking but the improvement following the release of the 2010 guidelines is reassuring and worthy of perpetuation.

scholarly journals De-Escalation by Reversing the Escalation with a Stronger Synergistic Package of Contact Tracing, Quarantine, Isolation and Personal Protection: Feasibility of Preventing a COVID-19 Rebound in Ontario, Canada, as a Case Study

Biology ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 100 ◽  
Author(s):  
Biao Tang ◽  
Francesca Scarabel ◽  
Nicola Luigi Bragazzi ◽  
Zachary McCarthy ◽  
Michael Glazer ◽  
...  
Keyword(s):  
Time Series Data ◽  
Necessary Conditions ◽  
Reproduction Number ◽  
Contact Tracing ◽  
Series Data ◽  
Personal Protection ◽  
Dynamics Model ◽  
Social Distancing ◽  
Canadian Provinces

Since the beginning of the COVID-19 pandemic, most Canadian provinces have gone through four distinct phases of social distancing and enhanced testing. A transmission dynamics model fitted to the cumulative case time series data permits us to estimate the effectiveness of interventions implemented in terms of the contact rate, probability of transmission per contact, proportion of isolated contacts, and detection rate. This allows us to calculate the control reproduction number during different phases (which gradually decreased to less than one). From this, we derive the necessary conditions in terms of enhanced social distancing, personal protection, contact tracing, quarantine/isolation strength at each escalation phase for the disease control to avoid a rebound. From this, we quantify the conditions needed to prevent epidemic rebound during de-escalation by simply reversing the escalation process.

scholarly journals Exchange Rate Dynamics and the Bilateral Trade Balance: The Case of U.S. Agriculture

2009 ◽  
Vol 38 (2) ◽  
pp. 213-228 ◽  
Author(s):  
Jungho Baek ◽  
Won W. Koo ◽  
Kranti Mulik
Keyword(s):  
United States ◽  
Exchange Rate ◽  
Bilateral Trade ◽  
Time Series Data ◽  
The United States ◽  
Agricultural Trade ◽  
Agricultural Products ◽  
Series Data ◽  
J Curve ◽  
Trading Partners

This study examines the dynamic effects of changes in exchange rates on bilateral trade of agricultural products between the United States and its 15 major trading partners. Special attention is paid to investigate whether or not the J-curve hypothesis holds for U.S. agricultural trade. For this purpose, an autoregressive distributed lag (ARDL) approach to cointegration is applied to quarterly time-series data from 1989 and 2007. Results show that the exchange rate plays a crucial role in determining the short- and long-run behavior of U.S. agricultural trade. However, we find little evidence of the J-curve phenomenon for U.S. agricultural products with the United States’ major trading partners.

scholarly journals Revisiting the Relationship between Economic Growth and Government Size

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Atrayee Ghosh Roy
Keyword(s):  
Economic Growth ◽  
Time Series Data ◽  
Government Expenditure ◽  
Private Investment ◽  
The United States ◽  
Simultaneous Equation ◽  
Series Data ◽  
Government Size ◽  
Government Investment ◽  
Government Consumption

The purpose of this paper is to explore the association between government size and economic growth in the United States using time-series data over the period 1950–2007. In particular, this paper examines the effects of two key components of government expenditure, namely, government consumption and government investment, on US economic growth. A simultaneous-equation model is used to deal with the problem of bi-directional relationship between government size and economic growth. The results suggest that an increase in government consumption slows economic growth, while a rise in government investment enhances economic growth. Furthermore, the results also show that government investment crowds out private investment. Therefore, the overall effect of total government expenditure on economic growth is ambiguous.

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