scholarly journals COVID-19 Death Rates and County Subdivision Level Contextual Characteristics: A Connecticut Case Study

Cybergeo ◽  
2021 ◽  
Author(s):  
Yunliang Meng
Keyword(s):  
Death Rates ◽  
Contextual Characteristics ◽  
Subdivision Level

Crime rates and contextual characteristics: a case study in Connecticut, USA

2021 ◽  
Vol 15 (2) ◽  
pp. 209-228
Author(s):  
Yunliang Meng ◽  
Keyword(s):  
Crime Prevention ◽  
Ethnic Diversity ◽  
Spatial Relationship ◽  
Property Crime ◽  
Crime Rates ◽  
Explanatory Variables ◽  
Contextual Characteristics ◽  
Racial Ethnic ◽  
Subdivision Level

There is a long-standing interest in the spatial relationship between contextual characteristics and crime rates in the U.S. since such a relationship allows police and stakeholders to design crime prevention programs to better target areas at risk for crime. The objective of this research is to examine the relationships between violent/property crime rates and contextual characteristics at the county-subdivision level in the State of Connecticut. The analysis shows that predictors such as population density, type of housing, education, poverty, and racial/ethnic diversity are significantly associated with violent and property crime rates. The results are discussed in the context of different crime hypotheses, which can explain spatial variations in crime rates. Most importantly, the association between crime rates and the explanatory variables in this study significantly varied over space, highlighting that different crime prevention policies/programs should be implemented in different county subdivisions in Connecticut.

scholarly journals Evaluation of Preventive Measures and Forecasting of COVID-19 Infection: Case Study Egypt.

2022 ◽  
Author(s):  
Safaa A A Khaled ◽  
Ahmed A A Hafez
Keyword(s):  
Infectious Disease ◽  
Decision Making ◽  
Preventive Measures ◽  
Swarm Optimization ◽  
Death Rates ◽  
Health Authorities ◽  
Heuristic Technique ◽  
Egyptian Government ◽  
High Degree

Abstract Background COVID-19 is a highly infectious disease caused by SARS-CoV-2. This article assessed the effectiveness of preventive measures of COVID-19 infection, including social distancing (SD) and quarantine (Q) of patients and contacts in Egypt. Methods A simple model was developed to predict the infection rate without preventive measures. The article utilizes fertile meta- heuristic technique and particle swarm optimization (PSO), to predict the growth of the disease. Results A correlation between the predicted and actual infected cases, validated the proposed forecasting algorithm. Preventive measures together with the Egyptian Government stay home order reduced 98% of expected infections. PSO analyses showed that infection and death rates will continue to increase particularly with lifting these restrictive preventive measures. Conclusions The advised PSO model could predict COVID-19 infection and death rates with high degree of accuracy. This prediction model could help health authorities in decision making.

scholarly journals Conscription Systems, Political Survival, and Battlefield Deaths

2021 ◽  
Author(s):  
Douglas B Atkinson ◽  
Kevin Thomas Fahey ◽  
Rene Lindstadt ◽  
Zach Warner
Keyword(s):  
Vietnam War ◽  
The United States ◽  
Political Survival ◽  
Death Rates ◽  
Know How ◽  
Labor Policies ◽  
States Experience ◽  
Human Costs ◽  
Significant Attention

How do countries’ conscription systems affect their ability to fight wars? Scholars have devoted significant attention to understanding how domestic political concerns influence military strategy, but we do not yet know how these concerns are shaped by military labor policies. We argue that conscription systems determine how the human costs of war are distributed throughout society, and in turn, the government’s tolerance for battlefield casualties in pursuit of victory. Using new data on every country’s conscription policy from 1800 to the present, we demonstrate that countries with selective conscription experience more casualties than those with universal conscription or volunteer militaries. To examine the mechanism we theorize, we then conduct an in-depth case study of the United States’ experience during the Vietnam War. Using adifference-in-differences design and new data on all American deaths in Vietnam, we show that changes in county death rates after the introduction of the lottery reflect electoral considerations.

scholarly journals The stationary distribution and stochastic persistence for a class of disease models: Case study of malaria

2020 ◽  
Vol 13 (04) ◽  
pp. 2050024
Author(s):  
Divine Wanduku
Keyword(s):  
Stationary Distribution ◽  
Disease Transmission ◽  
Transmission Rate ◽  
Statistical Characteristics ◽  
Local Martingale ◽  
Natural Death ◽  
Death Rates ◽  
Plasmodium Vivax Malaria ◽  
Over Time

This paper presents a nonlinear family of stochastic SEIRS models for diseases such as malaria in a highly random environment with noises from the disease transmission and natural death rates, and also from the random delays of the incubation and immunity periods. Improved analytical methods and local martingale characterizations are applied to find conditions for the disease to persist near an endemic steady state, and also for the disease to remain permanently in the system over time. Moreover, the ergodic stationary distribution for the stochastic process describing the disease dynamics is defined, and the statistical characteristics of the distribution are given numerically. The results of this study show that the disease will persist and become permanent in the system, regardless of (1) whether the noises are from the disease transmission rate and/or from the natural death rates or (2) whether the delays in the system are constant or random for individuals in the system. Furthermore, it is shown that “weak” noise is associated with the existence of an endemic stationary distribution for the disease, while “strong” noise is associated with extinction of the population over time. Numerical simulation examples for Plasmodium vivax malaria are given.

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