Blame Avoidance, Crisis Exploitation, and COVID-19 Governance Response in Israel

Surprisingly, although the Israeli government adopted unregulated, unorganized, inefficient, uncoordinated, and uninformed governance arrangements during the first wave of COVID-19, the public health outcome was successful, a paradox that this theoretically informed article seeks to explain. Drawing on insights from blame avoidance literature, it develops and applies an analytical framework that focuses on how allegations of policy underreaction in times of crisis pose a threat to elected executives’ reputations and how these politicians can derive opportunities for crisis exploitation from governance choices, especially at politically sensitive junctures. Based on a historical-institutional analysis combined with elite interviews, it finds that the implementation of one of the most aggressive policy alternatives on the policy menu at the beginning of the COVID-19 crisis (i.e., a shutdown of society and the economy), and the subsequent consistent adoption of the aforementioned governance arrangements constituted a politically well-calibrated and effective short-term strategy for Prime Minister Netanyahu.

Critical Review on Effect of 5G Technology on Covid-19 and Human Health Issues

This analytic research paper discusses the effects of emerging futuristic 5th Generation (5G) cellular technology over human health. The technology is growing with three major advantages of high speed, lower latency and to connect more devices at the same time. In the recent pandemic event of Covid-19, many believe that for the achievement of high speed in 5G, it will be required to have high power and this high power will decrease the immune system in short term. But actually, the reality doesn’t support the above condition. This paper defines how the speed will increase with the help of low bit error rate and also through different useful techniques thereby not just by increasing the power. In addition of high-frequency 5G radiation to an already complex mix of lower frequencies, the implementation will contribute to a negative public health outcome both from physical and mental health perspectives to a certain extent.

OP134 Predictors Of Public Health Outcomes: A Case Study From Turkey

INTRODUCTION:In Turkey, there is a scarcity of knowledge about the predictors of health outcomes at a national level, and it is well known that there is a gap between rural and urban parts of developing countries in terms of the level of health outcomes. This study aims to find out predictor factors of the public health outcomes at a province level in Turkey.METHODS:Life expectancy at birth and mortality are used as public health outcome indicators. Logistic regression and Random Forest classification generated by using 50, 100, and 150 trees were used to compare prediction performance of health outcomes. The results of different prediction methods were recorded changing the “k” parameter from 3 to 20 in k-fold cross validation. The Area Under the ROC Curve (AUC) was used as a measure of prediction accuracy. Prediction performance differences were tested using Kruskall-Wallis analysis and visualized on a heatmap. Finally, predictor variables of public health outcomes were shown on a decision tree.RESULTS:Study results revealed that Logistic regression outperformed Random Forest classification. The difference between all prediction methods to predict public health outcome indicators was statistically significant (p<.000). The heatmap shows that AUC values to predict mortality have superior performance when compared with life expectancy at birth. Decision tree graphs present that the most important predictor variables were total number of beds for mortality and percentage of higher education graduates for life expectancy at birth.CONCLUSIONS:The results of this study represent a preliminary attempt to determine public health outcome indicators. It is hoped that the results of this study serve as a basis to understand the determinants of health care outcomes at province level with focus on a developing country. This study illustrates that there is a need to spend extra effort for future studies to analyze public health outcomes to improve social welfare functions in health systems.

School-based Physical Activity: Planning with student motivation in mind

Central to providing rich and diverse PA opportunities in schools are our classroom teachers. Regardless of generalist or specialist training in health and physical education, all of our Ontario teachers play a vital role in providing opportunities for children and youth to learn through PA. This paper (a) positions student participation in school-based PA as an essential public health outcome, (b) explores barriers affecting teachers’ efforts to provide school-based PA, and (c) offers teachers one potential macro planning and instructional solution to address a single barrier-the challenge associated with planning for student motivation in school-based PA settings. Keller’s (1987) influential ARCS model of motivational design provides the foundation for the proposed solution. An adapted version, the ARCS School-Based PA model, is presented. The adapted model offers considerations and sample category success strategies that could be embedded in teachers’ current school-based PA planning and instructional practices to support the development of school-based PA programming that is firmly grounded in learner motivation and needs.