scholarly journals Impact of mitigating interventions and temperature on the instantaneous reproduction number in the COVID-19 epidemic among 30 US metropolitan areas

2020 ◽  
Author(s):  
Xinhua Yu
Keyword(s):  
Metropolitan Areas ◽  
Reproduction Number ◽  
Moving Average ◽  
Virus Transmission ◽  
Warm Temperature ◽  
Geographic Variations ◽  
Epidemic Process ◽  
The Us ◽  
Almost All ◽  
Aggressive Interventions

AbstractBackgroundAfter more than four months into the coronavirus disease (COVID-19) epidemic, over 347,500 people had died worldwide. The current study aims to evaluate how mitigating interventions affected the epidemic process in the 30 largest metropolitan areas in the US and whether temperature played a role in the epidemic process.MethodsPublicly available data for the time series of COVID-19 cases and deaths and weather were analyzed at the metropolitan level. The time-varying reproductive numbers (Rt) based on retrospective moving average were used to explore the trends. Student t tests were used to compare temperature and peak Rt cross-sectionally.ResultsWe found that virus transmissibility, measured by instantaneous reproduction number (Rt), had declined since the end of March for all areas and almost all of them reached a Rt of 1 or below after April 15, 2020. However, the Rts remained around 1 for most areas since then and some small and short rebounds were presented in some areas, suggesting a persistent epidemic in those areas. The timing of the main decline was concurrent with the implementation of mitigating interventions. Cities with warm temperature also tended to have a lower peak Rt than that of cities with cold temperature. However, large geographic variations existed.ConclusionsAggressive interventions might have mitigated the current epidemic of COVID-19, while temperature might have some weak effects on the virus transmission. We may need to prepare for a possible return of the coronavirus outbreak.

scholarly journals Modeling the transmission of the SARS-CoV-2 delta variant in a partially vaccinated population

2021 ◽  
Author(s):  
Ugo Avila ◽  
Eric Avila ◽  
Kuan-lin Huang
Keyword(s):  
Reproduction Number ◽  
Virus Transmission ◽  
Transmission Dynamics ◽  
Sensitivity Analyses ◽  
Behavioral Measures ◽  
Vaccination Rates ◽  
Gradual Loss ◽  
The Us ◽  
Induced Immunity ◽  
Different Levels

In a population with ongoing vaccination, the trajectory of a pandemic is determined by how the virus spreads in unvaccinated and vaccinated individuals that exhibit distinct transmission dynamics based on different levels of natural and vaccine-induced immunity. We developed a mathematical model that considers both subpopulations and immunity parameters including vaccination rates, vaccine effectiveness, and a gradual loss of protection. The model forecasted the spread of the SARS-CoV-2 delta variant in the US under varied transmission and vaccination rates. We further obtained the control reproduction number and conducted sensitivity analyses to determine how each parameter may affect virus transmission. Our results show that a combination of strengthening vaccine-induced immunity and preventative behavioral measures will likely be required to deaccelerate the rise of infectious SARS-CoV-2 variants.

BP Global Energy Outlook 2030

2013 ◽  
pp. 109-128 ◽  
Author(s):  
C. Rühl
Keyword(s):  
Emerging Economies ◽  
Energy Demand ◽  
Fossil Fuels ◽  
Net Energy ◽  
Global Energy ◽  
The Past ◽  
Market Shares ◽  
The Us ◽  
Almost All ◽  
Oil Gas

This paper presents the highlights of the third annual edition of the BP Energy Outlook, which sets out BP’s view of the most likely developments in global energy markets to 2030, based on up-to-date analysis and taking into account developments of the past year. The Outlook’s overall expectation for growth in global energy demand is to be 36% higher in 2030 than in 2011 and almost all the growth coming from emerging economies. It also reflects shifting expectations of the pattern of supply, with unconventional sources — shale gas and tight oil together with heavy oil and biofuels — playing an increasingly important role and, in particular, transforming the energy balance of the US. While the fuel mix is evolving, fossil fuels will continue to be dominant. Oil, gas and coal are expected to converge on market shares of around 26—28% each by 2030, and non-fossil fuels — nuclear, hydro and renewables — on a share of around 6—7% each. By 2030, increasing production and moderating demand will result in the US being 99% self-sufficient in net energy. Meanwhile, with continuing steep economic growth, major emerging economies such as China and India will become increasingly reliant on energy imports. These shifts will have major impacts on trade balances.

COVID-19: Time-Dependent Effective Reproduction Number and Sub-notification Effect Estimation Modeling (Preprint)

2020 ◽  
Author(s):  
Eduardo Atem De Carvalho ◽  
Rogerio Atem De Carvalho
Keyword(s):  
New York ◽  
Reproduction Number ◽  
Moving Average ◽  
Real Data ◽  
Time Dependent ◽  
Initial Value ◽  
Health Authorities ◽  
Reproduction Numbers ◽  
Effect Estimation ◽  
The Impact

BACKGROUND Since the beginning of the COVID-19 pandemic, researchers and health authorities have sought to identify the different parameters that govern their infection and death cycles, in order to be able to make better decisions. In particular, a series of reproduction number estimation models have been presented, with different practical results. OBJECTIVE This article aims to present an effective and efficient model for estimating the Reproduction Number and to discuss the impacts of sub-notification on these calculations. METHODS The concept of Moving Average Method with Initial value (MAMI) is used, as well as a model for Rt, the Reproduction Number, is derived from experimental data. The models are applied to real data and their performance is presented. RESULTS Analyses on Rt and sub-notification effects for Germany, Italy, Sweden, United Kingdom, South Korea, and the State of New York are presented to show the performance of the methods here introduced. CONCLUSIONS We show that, with relatively simple mathematical tools, it is possible to obtain reliable values for time-dependent, incubation period-independent Reproduction Numbers (Rt). We also demonstrate that the impact of sub-notification is relatively low, after the initial phase of the epidemic cycle has passed.

scholarly journals Cross-cultural adaptation of the German version of the Quality of Life in Alzheimer's Disease scale - Nursing Home version (QoL-AD NH)

2016 ◽  
Vol 28 (8) ◽  
pp. 1399-1400 ◽  
Author(s):  
Martin Nikolaus Dichter ◽  
Eva-Maria Wolschon ◽  
Gabriele Meyer ◽  
Sascha Köpke
Keyword(s):  
Quality Of Life ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Community Dwelling ◽  
Positive Effects ◽  
People With Dementia ◽  
The Us ◽  
Dementia Research ◽  
Almost All

Dementia is a chronic and currently incurable syndrome. Therefore, quality of life (QoL) is a major goal when caring for people with dementia (Gibson et al., 2010) and a major outcome in dementia research (Moniz-Cook et al., 2008). The measurement of QoL, especially proxy-rating, is challenging because of the proxy-perspective (Pickard and Knight, 2005), reliability (Dichter et al., 2016), validity (O'Rourke et al., 2015), and responsiveness (Perales et al., 2013). Probably due to these challenges, it has not been possible to show positive effects for QoL in almost all non-pharmacological interventions for people with dementia (Cooper et al., 2012). One recommended (Moniz-Cook et al., 2008) and frequently used instrument is the Quality of Life in Alzheimer's Disease scale (QoL-AD), which was originally developed in the US for community-dwelling people with dementia. The QoL-AD consists of 13 items based on a 4-point Likert scale ranging from “1”=poor to “4”=excellent (Logsdon et al., 1999). The original instrument has been adapted for people living in nursing homes (NH) by Edelmann et al. (2005).

scholarly journals Co-integration with score-driven models: an application to US real GDP growth, US inflation rate, and effective federal funds rate

2021 ◽  
pp. 1-21
Author(s):  
Szabolcs Blazsek ◽  
Alvaro Escribano ◽  
Adrian Licht
Keyword(s):  
Inflation Rate ◽  
Predictive Accuracy ◽  
Moving Average ◽  
Impulse Response Functions ◽  
Federal Funds ◽  
Federal Funds Rate ◽  
Vector Autoregressive ◽  
Autoregressive Moving Average Model ◽  
Long Run ◽  
The Us

Abstract Nonlinear co-integration is studied for score-driven models, using a new multivariate dynamic conditional score/generalized autoregressive score model. The model is named t-QVARMA (quasi-vector autoregressive moving average model), which is a location model for the multivariate t-distribution. In t-QVARMA, I(0) and co-integrated I(1) components of the dependent variables are included. For t-QVARMA, the conditions of the maximum likelihood estimator and impulse response functions (IRFs) are presented. A limiting special case of t-QVARMA, named Gaussian-QVARMA, is a Gaussian-VARMA specification with I(0) and I(1) components. As an empirical application, the US real gross domestic product growth, US inflation rate, and effective federal funds rate are studied for the period of 1954 Q3 to 2020 Q2. Statistical performance and predictive accuracy of t-QVARMA are superior to those of Gaussian-VAR. Estimates of the short-run IRF, long-run IRF, and total IRF impacts for the US data are reported.

scholarly journals Reptile smuggling is predicted by trends in the legal exotic pet trade

2021 ◽  
Author(s):  
Oliver Stringham ◽  
Pablo García‐Díaz ◽  
Adam Toomes ◽  
Lewis Mitchell ◽  
Joshua V. Ross ◽  
...  
Keyword(s):  
Time Lag ◽  
The United States ◽  
Wildlife Trade ◽  
Live Animal ◽  
Pet Trade ◽  
Reptile Species ◽  
The Us ◽  
Disease Risks ◽  
Almost All ◽  
Species Being

Western countries are less frequently implicated in illegal wildlife trade (IWT), contrasted with other transnational consumers, yet substantial evidence suggests that they contribute prominently. Live animal smuggling presents a suite of biosecurity concerns, including invasive species and disease risks. Here, we compared the live alien reptile species smuggled to Australia (75 species) to the legal trade of live reptile species in the United States (US) and constructed a Bayesian regularized model to predict the species most likely to be of greatest future smuggling risk to Australia. Australia has particularly strict import laws barring the entry and keeping of alien reptiles and maintains detailed biosecurity seizure records. Almost all smuggled reptile species were found in the legal US exotic pet market (98.6%), and we observed an average time lag of 4.2 years between a species first appearing in the US market and its subsequent detection in Australia. A species popularity in US pet stores, popularity on international online markets, and the number of years in US import-export records were all positively associated with the probability of species being smuggled to Australia. Our predictive model provides a much-needed early-warning guide for future biosecurity enforcement of the IWT and provides a framework for anticipating future trends in wildlife smuggling.

scholarly journals Injuries related to respiratory masks in the US are very rare

2021 ◽  
Author(s):  
Philip N. Cohen
Keyword(s):  
Census Data ◽  
Incidence Rates ◽  
Common Type ◽  
Respiratory Protection ◽  
Risk Of Falling ◽  
Injury Surveillance System ◽  
Household Products ◽  
The Us ◽  
Protection Devices ◽  
Almost All

Background. Protective facemasks are important for preventing the spread of COVID-19, and almost all Americans have worn them at least some of the time during the pandemic. There are reasonable concerns about some ill effects of mask-wearing, especially for people who wear masks for extended periods, and for the risk of falling as a result of visual obstruction. But there are also unsupported fears and objections stemming from misinformation and fueled by political disputes. Methods. The study analyzed the Consumer Product Safety Commission’s National Electronic Injury Surveillance System (NEISS) for 2020, using the product code for Respiratory Protection Devices, and calculated population incidence rates using Census data. Results. The NEISS included 128 cases, representing an estimated 5122 reported injuries in the population (95% CI 3322, 6922). The overall rate of injury reports was 1.54 per 100,000 U.S. residents (95% CI 1.00, 2.08). People over age 75 had higher rates than the population overall, with 5.27 injuries per 100,000 (95% CI 2.17, 8.37). The most common type of incidents involved facial injuries, rashes, falls, and those that might be considered anxiety-related. Conclusion. Wearing protective face masks is extremely safe, especially in comparison with other common household products, and in light of their protective benefits with regard to prevent the spread of COVID-19. This information may be useful for public health messaging, and for practitioners trying to increase compliance with mask-wearing guidance.

scholarly journals Assessment of thoron contribution to indoor radon exposure in Canada

2022 ◽  
Author(s):  
Jing Chen
Keyword(s):  
Detection Limit ◽  
Indoor Environment ◽  
Metropolitan Areas ◽  
Indoor Radon ◽  
Geometric Mean ◽  
Pooled Analysis ◽  
Geometric Standard Deviation ◽  
Radon Exposure ◽  
Canadian Population ◽  
Almost All

AbstractFrom 2007 to 2013, simultaneous radon (222Rn) and thoron (220Rn) measurements were conducted in a total of 3534 residential homes in 34 metropolitan areas covering 71% of the Canadian population. While radon levels were above the detector’s detection limit in almost all homes, thoron concentrations were measurable in only 1738 homes. When analysis was limited to homes where thoron concentrations exceeded the detection limit, a pooled analysis confirmed that thoron is log-normally distributed in the indoor environment, and the distribution was characterized by a population-weighted geometric mean of 13 Bq/m3 and a geometric standard deviation of 1.89. Thoron contribution to indoor radon dose varied widely, ranging from 1.3 to 32% geographically. This study indicated that on average, thoron contributes 4% of the radiation dose due to total indoor radon exposure (222Rn and 220Rn) in Canada.

Data Analysis and Forecasting of COVID-19 Pandemic in Kuwait Based on Daily Observation and Basic Reproduction Number Dynamics

2021 ◽  
Author(s):  
Kayode Oshinubi ◽  
◽  
Fahimah Al-Awadhi ◽  
Mustapha Rachdi ◽  
Jacques Demongeot ◽  
...  
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Moving Average ◽  
Arima Model ◽  
Exponential Model ◽  
Spreading Rate ◽  
Support Vector ◽  
Global Threat ◽  
Log Linear ◽  
Second Wave

Coronavirus (COVID-19) has continued to be a global threat to public health. When the coronavirus pandemic began early in 2020, experts wondered if there would be waves of cases, a pattern seen in other virus pandemics. The overall pattern so far has been one of increasing cases of COVID-19 followed by a decline, and we observed a second wave of increased cases and yet we are still exploring this pandemic. Hence, updating the prediction model for the new cases of COVID-19 for different waves is essential to monitor the spreading of the virus and control the disease. Time series models have extensively been considered as the convenient methods to predict the prevalence or spreading rate of the disease. This study, therefore, aimed to apply the Autoregressive Integrated Moving Average (ARIMA) modelling approach for predicting new cases of coronavirus (COVID-19). We propose a deterministic method to predict the basic reproduction number Ro of first and second wave transition of COVID-19 cases in Kuwait and also to forecast the daily new cases and deaths of the pandemic in the country. Forecasting has been done using ARIMA model, Exponential smoothing model, Holt’s method, Prophet forecasting model and machine learning models like log-linear, polynomial and support vector regressions. The results presented aligned with other methods used to predict Ro in first and second waves and the forecasting clearly shows the trend of the pandemic in Kuwait. The deterministic prediction of Ro is a good forecasting tool available during the exponential phase of the contagion, which shows an increasing trend during the beginning of the first and second waves of the pandemic in Kuwait. The results show that support vector regression has achieved the best performance for prediction while a simple exponential model without trend gives good optimal results for forecasting of Kuwait COVID-19 data.

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