Coronavirus Dynamics:The Undulating Playing Field

The goal of the paper is to conduct an exploratory review and analyses of the dynamics of the pandemic focusing on two themes:pandemic morbidity and vulnerable populations.Method:Review of literature,anecdotal evidence,and reports on the morbidity of COVID-19;including scope of its devastating effects in selected countries.Findings:The devastating effects of the coronavirus are felt across different vulnerable populations.These include the elderly,front line workers,marginalized communities,visible minorities,and more.Inadequate and sometimes conflicting remarks by“experts”have only contributed in exacerbating the confusion in the general population.However,compassion and empathy from different communities have had positive effects on mitigating some of the health outcomes like mental health and other health-related effects of the pandemic.Institutional support needs to be strengthened,especially with regard to individual risks and supply chain coordination:personal protection equipment(PPE),masks,swabs,reagents,etc.The challenge in Africa is especially daunting,because of limited and inadequate financial resources and infrastructure,as confirmed by the health budget allocations as a percentage of their respective GDP(gross domestic product).Discussion:The effects of the COVID-19 are producing unprecedented and catastrophic outcomes in many countries.These have been exacerbated by the level of unpreparedness and inadequate degrees of prevention and intervention strategies.With a few exceptions,the common and current intervention approach is driven by many unknowns including compilation of relevant reliable and compelling data sets.Vulnerable communities continue to suffer most:a situation that is highlighted in this essay as one attempt to remind institutions of their duty to provide appropriate support,including compassion and empathy to these populations.The repercussions of no or inadequate action are numerous,significant,and mind-boggling with unpredictable future outcomes and possible dire consequences.The continuous carnage caused by COVID-19 is a wake-up call reminding all stakeholders(public and private institutions)that once again the inequality infiltrating vulnerable populations needs to be effectively addressed with emphasis on affordability,improved quality of life,and an inclusive long-term strategic plan.Ubiquitous and inadequate supply chain coordination mechanisms have been a major deterrent towards mitigating the effects of this coronavirus pandemic.

Towards intelligent geospatial data discovery:a machine learning framework for search ranking

Current search engines in most geospatial data portals tend to induce users to focus on one single-data characteristic dimension(e.g.popularity and release date).This approach largely fails to take account of users’multidimensional preferences for geospatial data,and hence may likely result in a less than optimal user experience in discovering the most applicable dataset.This study reports a machine learning framework to address the ranking challenge,the fundamental obstacle in geospatial data discovery,by(1)identifying a number of ranking features of geospatial data to represent users’multidimensional preferences by considering semantics,user behavior,spatial similarity,and static dataset metadata attributes;(2)applying a machine learning method to automatically learn a ranking function;and(3)proposing a system architecture to combine existing search-oriented open source software,semantic knowledge base,ranking feature extraction,and machine learning algorithm.Results show that the machine learning approach outperforms other methods,in terms of both precision at K and normalized discounted cumulative gain.As an early attempt of utilizing machine learning to improve the search ranking in the geospatial domain,we expect this work to set an example for further research and open the door towards intelligent geospatial data discovery.