scholarly journals A Spatio-Temporal Investigation of the Growth Rate of COVID-19 Incidents in Ohio, USA, Early in the Pandemic

2021 ◽  
Vol 121 (2) ◽  
pp. 33-47
Author(s):  
Alessandro M. Selvitella ◽  
Liam Carolan ◽  
Justin Smethers ◽  
Christopher Hernandez ◽  
Kathleen L. Foster
Keyword(s):  
Growth Rate ◽  
Transmission Rate ◽  
Time Lag ◽  
Early Period ◽  
Mitigation Strategies ◽  
Initial Growth ◽  
School Closures ◽  
Policy Makers ◽  
Susceptible Population ◽  
Spatio Temporal

Understanding the initial growth rate of an epidemic is important for epidemiologists and policy makers as it can impact their mitigation strategies such as school closures, quarantines, or social distancing. Because the transmission rate depends on the contact rate of the susceptible population with infected individuals, similar growth rates might be experienced in nearby geographical areas. This research determined the growth rate of cases and deaths associated with COVID-19 in the early period of the 2020 pandemic in Ohio, United States. The evolution of cases and deaths was modeled through a Besag-York-Molliè model with linear- and power-type deterministic time dependence. The analysis showed that the growth rate of the time component of the model was subexponential in both cases and deaths once the time-lag across counties of the appearance of the first COVID-19 case was considered. Moreover, deaths in the northeast counties in Ohio were strongly related to the deaths in nearby counties.

scholarly journals Geospatially Referenced Demographic Agent-Based Modeling of SARS-CoV-2-Infection (COVID-19) Dynamics and Mitigation Effects in a Real-world Community

2020 ◽  
Author(s):  
SO Adler ◽  
O Bodeit ◽  
L Bonn ◽  
B Goldenbogen ◽  
X Escalera-Fanjul ◽  
...  
Keyword(s):  
Real World ◽  
Policy Development ◽  
Household Composition ◽  
Mitigation Strategies ◽  
List Type ◽  
Human Beings ◽  
School Closures ◽  
Agent Based ◽  
Infection Dynamics ◽  
Spatio Temporal

AbstractRe-opening societies and economies across the globe following the initial wave of the severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) pandemic requires scientifically-guided decision processes and policy development. Public health authorities now consider it highly likely that transmission of SARS-CoV-2 and COVID-19 will follow a pattern of seasonal circulation globally. To guide mitigation strategies and tactics in a location-specific manner, accurate simulation of prolonged or intermittent patterns of social/physical distancing is required in order to prevent healthcare systems and communities from collapsing. It is equally important to capture the stochastic appearance of individual transmission events. Traditional epidemiological/statistical models cannot make predictions in a geospatial temporal manner based on human individuals in a community. Thus, the challenge is to conduct spatio-temporal simulations of transmission chains with real-world geospatial and georeferenced information of the dynamics of the disease and the effect of different mitigation strategies such as isolation of infected individuals or location closures. Here, we present a stochastic, geospatially referenced and demography-specific agent-based model with agents representing human beings and include information on age, household composition, daily occupation and schedule, risk factors, and other relevant properties. Physical encounters between humans are modeled in a time-dependent georeferenced network of the population. The model (GERDA-1) can predict infection dynamics under normal conditions and test the effect of different mitigation scenarios such as school closures, reduced social contacts as well as closure or reopening of public/work spaces. Specifically, it also includes the fate and influence of health care workers and their access to protective gear. Key predictions so far entail:the effect of specific groups on the spreading, specifically that children in school contribute substantially to distribution.the result of reopening society depends crucially on how strict the measures have been during lock-down.the outcome of reopening is a stochastic process - in the majority of cases, we must expect a second wave, in some cases not. To the best of our best knowledge, the GERDA-1 model is the first model able to predict a bimodal behavior of SARS-Cov-2 infection dynamics.Given the criticality of the global situation, informing the scientific community, decision makers and the general public seems prudent. Therefore, we here provide a pre-print of the GERDA-1 model together with a first set of predictions and analyses as work in progress.

scholarly journals Non-stationary Spatio-Temporal Modeling of COVID-19 Progression in The U.S.

2020 ◽  
Author(s):  
Yue Bai ◽  
Abolfazl Safikhani ◽  
George Michailidis
Keyword(s):  
Transmission Rate ◽  
Synthetic Data ◽  
Mitigation Strategies ◽  
Modeling Framework ◽  
Temporal Modeling ◽  
Empirical Performance ◽  
Important Challenge ◽  
Auto Regressive ◽  
Break Points ◽  
Spatio Temporal

The fast transmission rate of COVID-19 worldwide has made this virus the most important challenge of year 2020. Many mitigation policies have been imposed by the governments at different regional levels (country, state, county, and city) to stop the spread of this virus. Quantifying the effect of such mitigation strategies on the transmission and recovery rates, and predicting the rate of new daily cases are two crucial tasks. In this paper, we propose a modeling framework which not only accounts for such policies but also utilizes the spatial and temporal information to characterize the pattern of COVID-19 progression. Specifically, a piecewise susceptible-infected-recovered (SIR) model is developed while the dates at which the transmission/recover rates change significantly are defined as "break points" in this model. A novel and data-driven algorithm is designed to locate the break points using ideas from fused lasso and thresholding. In order to enhance the forecasting power and to describe additional temporal dependence among the daily number of cases, this model is further coupled with spatial smoothing covariates and vector auto-regressive (VAR) model. The proposed model is applied to several U.S. states and counties, and the results confirm the effect of "stay-at-home orders" and some states' early "re-openings" by detecting break points close to such events. Further, the model performed satisfactorily short-term forecasts of the number of new daily cases at regional levels by utilizing the estimated spatio-temporal covariance structures. Finally, some theoretical results and empirical performance of the proposed methodology on synthetic data are reported which justify the good performance of the proposed method.

scholarly journals 494. COVID-19 Outbreak: A Tale of Two Psych Units

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S313-S314
Author(s):  
Marilou Corpuz ◽  
Ruchika Jain ◽  
Gregory Weston ◽  
Priya Nori ◽  
Priya Nori ◽  
...  
Keyword(s):  
Infection Control ◽  
Medical Center ◽  
Early Period ◽  
Index Patient ◽  
Structural Aspect ◽  
Practice Change ◽  
Mitigation Strategies ◽  
Inpatient Psychiatry ◽  
Control And Prevention ◽  
Infection Control And Prevention

Abstract Background COVID infections in inpatient psychiatry units present unique challenges during the pandemic, including behavioral characteristics of the patients, structural aspect of the unit, type of therapy for the patients. We present COVID outbreaks in psychiatry units in two hospitals in our medical center in Bronx, NY, and describe our mitigation strategies. Methods Hosp A: In the early period of the pandemic in NY, 2 patients in the inpatient psychiatry unit tested positive for SARS-CoV-2 PCR. The unit was temporarily closed to new admissions. Hosp B: On 4/1, one of the patients in a 22 bed Psych unit, admitted since 3/10/20, developed fever, cough and tested positive for COVID-19 PCR. Two of her close contacts tested positive for SARS-COV-2 PCR. Results Hospital A: In total, 5 of the 29 patients (17.2%) in the unit were SARS-CoV-2 positive, all of whom were asymptomatic. Hospital B: Testing of the remaining patients showed positive PCR in 10/14. PCR tests of healthcare workers (HCW) were positive in 13/46. Except for the index patient, all the patients were asymptomatic but 32/46 HCW reported symptoms. One negative patient subsequently turned positive. Infection control and prevention strategies instituted in both hospitals were the same with subtle differences due to dissimilar burden of infection and structure of the units. Table 1 shows the timing of the outbreak and the rapid institution of preventive measures in each of the hospitals. There was still difficulty with patients regarding adherence. Some of the patients refused to stay in isolation and would roam. Compliance with masking and hand hygiene was problematic. Communication was of paramount importance. Multiple meetings were held between the Psychiatry staff, Infection Control and Prevention team, executive leadership of the hospital. Environmental Services and Engineering were also involved. Communications with the NY State Department of Health occurred frequently. Conclusion Strategies for management of COVID-19 patients in inpatient psychiatric units depends on the density of infected patients in the hospital and in the community. The implementation of practice change may need to be rapidly adjusted depending on the situation and available resources. Contingency plans should be formulated early on. Disclosures Gregory Weston, MD MSCR, Allergan (Grant/Research Support)

scholarly journals Promoting Renewable Energy to Cope with Climate Change—Policy Discourse in Israel

2021 ◽  
Vol 13 (6) ◽  
pp. 3170
Author(s):  
Avri Eitan
Keyword(s):  
Climate Change ◽  
Renewable Energy ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Climate Change Mitigation ◽  
Renewable Energies ◽  
Mitigation Strategies ◽  
Policy Discourse ◽  
Policy Makers ◽  
Change Mitigation

Evidence shows that global climate change is increasing over time, and requires the adoption of a variety of coping methods. As an alternative for conventional electricity systems, renewable energies are considered to be an important policy tool for reducing greenhouse gas emissions, and therefore, they play an important role in climate change mitigation strategies. Renewable energies, however, may also play a crucial role in climate change adaptation strategies because they can reduce the vulnerability of energy systems to extreme events. The paper examines whether policy-makers in Israel tend to focus on mitigation strategies or on adaptation strategies in renewable energy policy discourse. The results indicate that despite Israel’s minor impact on global greenhouse gas emissions, policy-makers focus more on promoting renewable energies as a climate change mitigation strategy rather than an adaptation strategy. These findings shed light on the important role of international influence—which tends to emphasize mitigation over adaptation—in motivating the domestic policy discourse on renewable energy as a coping method with climate change.

scholarly journals Comparison of spatio-temporal transmission characteristics of COVID-19 and its mitigation strategies in China and the US

2020 ◽  
Vol 30 (12) ◽  
pp. 1963-1984
Author(s):  
Zhiming Feng ◽  
Chiwei Xiao ◽  
Peng Li ◽  
Zhen You ◽  
Xu Yin ◽  
...  
Keyword(s):  
Mitigation Strategies ◽  
Transmission Characteristics ◽  
The Us ◽  
Spatio Temporal

scholarly journals COVID-TRACK: world and USA SARS-COV-2 testing and COVID-19 tracking

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Ye Emma Zohner ◽  
Jeffrey S. Morris
Keyword(s):  
Web Application ◽  
The United States ◽  
Mitigation Strategies ◽  
Time Lags ◽  
Policy Makers ◽  
Major Health ◽  
Dynamic Representation ◽  
Graphical Displays ◽  
The Usa ◽  
User Friendly

Abstract Background The COVID-19 pandemic has caused major health and socio-economic disruptions worldwide. Accurate investigation of emerging data is crucial to inform policy makers as they construct viral mitigation strategies. Complications such as variable testing rates and time lags in counting cases, hospitalizations and deaths make it challenging to accurately track and identify true infectious surges from available data, and requires a multi-modal approach that simultaneously considers testing, incidence, hospitalizations, and deaths. Although many websites and applications report a subset of these data, none of them provide graphical displays capable of comparing different states or countries on all these measures as well as various useful quantities derived from them. Here we introduce a freely available dynamic representation tool, COVID-TRACK, that allows the user to simultaneously assess time trends in these measures and compare various states or countries, equipping them with a tool to investigate the potential effects of the different mitigation strategies and timelines used by various jurisdictions. Findings COVID-TRACK is a Python based web-application that provides a platform for tracking testing, incidence, hospitalizations, and deaths related to COVID-19 along with various derived quantities. Our application makes the comparison across states in the USA and countries in the world easy to explore, with useful transformation options including per capita, log scale, and/or moving averages. We illustrate its use by assessing various viral trends in the USA and Europe. Conclusion The COVID-TRACK web-application is a user-friendly analytical tool to compare data and trends related to the COVID-19 pandemic across areas in the United States and worldwide. Our tracking tool provides a unique platform where trends can be monitored across geographical areas in the coming months to watch how the pandemic waxes and wanes over time at different locations around the USA and the globe.

scholarly journals Corruption in Construction Projects: Bibliometric Analysis of Global Research

2021 ◽  
Vol 13 (8) ◽  
pp. 4400
Author(s):  
Zhao Zhai ◽  
Ming Shan ◽  
Amos Darko ◽  
Albert P. C. Chan
Keyword(s):  
Construction Projects ◽  
Research Policy ◽  
Mitigation Strategies ◽  
Future Research ◽  
Policy And Practice ◽  
Policy Makers ◽  
Research Areas ◽  
Body Of Knowledge ◽  
Emerging Trends ◽  
Global Research

Corruption has been identified as a major problem in construction projects. It can jeopardize the success of these projects. Consequently, corruption has garnered significant attention in the construction industry over the past two decades, and several studies on corruption in construction projects (CICP) have been conducted. Previous efforts to analyze and review this body of knowledge have been manual, qualitative and subjective, thus prone to bias and limited in the number of reviewed studies. There remains a lack of inclusive, quantitative, objective and computational analysis of global CICP research to inform future research, policy and practice. This study aims to address this lack by providing the first inclusive bibliometric study exploring the state-of-the-art of global CICP research. To this end, a quantitative and objective technique aided by CiteSpace was used to systematically and computationally analyze a large corpus of 542 studies retrieved from the Web of Science and published from 2000 to 2020. The findings revealed major and influential CICP research journals, persons, institutions, countries, references and areas of focus, as well as revealing how these interact with each other in research networks. This study contributes to the in-depth understanding of global research on CICP. By highlighting the principal research areas, gaps, emerging trends and directions, as well as patterns in CICP research, the findings could help researchers, practitioners and policy makers position their future CICP research and/or mitigation strategies.

Abstract 180: The Growth Rate of Early DWI Lesions is Highly Variable and Associated with Penumbral Salvage and Clinical Outcomes Following Endovascular Reperfusion

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Hayley M Wheeler ◽  
Michael Mlynash ◽  
Manabu Inoue ◽  
Aaryani Tipirneni ◽  
John Liggins ◽  
...  
Keyword(s):  
Growth Rate ◽  
Acute Stroke ◽  
Clinical Outcomes ◽  
Endovascular Therapy ◽  
Symptom Onset ◽  
Growth Rates ◽  
Initial Growth ◽  
Stroke Patients ◽  
Final Volume ◽  
Favorable Clinical Response

Background: The degree of variability in the rate of early DWI expansion has not been well characterized. We hypothesized that Target Mismatch patients with slowly expanding DWI lesions have more penumbral salvage and better clinical outcomes following endovascular reperfusion than Target Mismatch patients with rapidly expanding DWI lesions. Methods: This substudy of DEFUSE 2 included all patients with a clearly established time of symptom onset. The initial DWI growth rate was determined from the baseline scan by assuming a volume 0 ml just prior to symptom onset. Target Mismatch patients who achieved reperfusion (>50% reduction in PWI after endovascular therapy), were categorized into tertiles according to their initial DWI growth rates. For each tertile, penumbral salvage (comparison of final volume to the volume of PWI (Tmax > 6 sec)/ DWI mismatch prior to endovascular therapy), favorable clinical response, and good functional outcome (see figure for definitions) were calculated. We also compared the growth rate in patients with the Target mismatch vs. Malignant Profile. Results: 64 patients were eligible for this study. Target mismatch patients (n=44) had initial growth rates (range 0 to 43 ml/hr, median of 3 ml/hr) that were significantly less than the growth rates in Malignant profile (n=7) patients (12 to 92 ml/hr, median 39 ml/hr; p < 0.001). In Target mismatch patients who achieved reperfusion (n=30), slower early DWI growth rates were associated with better clinical outcomes (p<0.05) and a trend toward more penumbral salvage (n=27, p=0.137). Conclusions: The growth rate of early DWI lesions in acute stroke patients is highly variable; Malignant profile patients have higher growth rates than other MRI profiles. Among Target Mismatch patients, a slower rate of DWI growth is associated with a greater degree of penumbral salvage and improved clinical outcomes following endovascular reperfusion.

scholarly journals Molecular Dynamics Study on the Mechanism of Nanoscale Jet Instability Reaching Supercritical Conditions

2018 ◽  
Vol 8 (10) ◽  
pp. 1714 ◽  
Author(s):  
Qingfei Fu ◽  
Yunxiao Zhang ◽  
Chaojie Mo ◽  
Lijun Yang
Keyword(s):  
Molecular Dynamics ◽  
Growth Rate ◽  
Theoretical Result ◽  
Molecular Model ◽  
Simulation Method ◽  
Dynamics Simulation ◽  
Jet Instability ◽  
Subcritical Region ◽  
Thermodynamic Conditions ◽  
Spatio Temporal

This paper investigates the characteristics of a nitrogen jet (the thermodynamic conditions ranging from subcritical to supercritical) ejected into a supercritical nitrogen environment using the molecular dynamics (MD) simulation method. The thermodynamic properties of nitrogen obtained by molecular dynamics show good agreement with the Soave-Redlich-Kwong (SRK) equation of state (EOS). The agreement provides validation for this nitrogen molecular model. The molecular dynamics simulation of homogeneous nitrogen spray is carried out in different thermodynamic conditions from subcritical to supercritical, and a spatio-temporal evolution of the nitrogen spray is obtained. The interface of the nitrogen spray is determined at the point where the concentration of ejected fluid component reaches 50%, since the supercritical jet has no obvious vapor-liquid interface. A stability analysis of the transcritical jets shows that the disturbance growth rate of the shear layer coincides very well with the classical theoretical result at subcritical region. In the supercritical region, however, the growth rate obtained by molecular dynamics deviates from the theoretical result.

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