RESUMEN
OBJECTIVES: The Richter Scale measures the magnitude of a seismic occurrence, but it does not feasibly quantify the magnitude of the "disaster" at the point of impact in real humanitarian needs, based on United Nations International Strategy for Disaster Reduction (UNISDR; Geneva, Switzerland) 2009 Disaster Terminology. A Disaster Severity Index (DSI) similar to the Richter Scale and the Mercalli Scale has been formulated; this will quantify needs, holistically and objectively, in the hands of any stakeholders and even across timelines. BACKGROUND: An agreed terminology in quantifying "disaster" matters; inconsistency in measuring it by stakeholders posed a challenge globally in formulating legislation and policies responding to it. METHODS: A quantitative, mathematical calculation which uses the median score percentage of 100% as a baseline, indicating the ability to cope within the local capacity, was used. Seventeen indicators were selected based on the UNISDR 2009 disaster definition of vulnerability and exposure and holistic approach as a pre-condition. The severity of the disaster is defined as the level of unmet needs. Thirty natural disasters were tested, retrospectively, and non-parametric tests were used to test the correlation of the DSI score against the indicators. RESULTS: The findings showed that 20 out of 30 natural disasters tested fulfilled the inability to cope, within local capacity in disaster terminology. Non-parametric tests showed that there was a correlation between the 30 DSI scored and the indicators. CONCLUSION: By computing a median fit percentage score of 100% as the ability to cope, and the correlation of the 17 indicators, in this DSI Scale, 20 natural disasters fitted into the disaster definition. This DSI will enable humanitarian stakeholders to measure and compare the severity of the disaster objectively, as well as enable future response to be based on needs.YewYY, Castro DelgadoR, HeslopDJ, Arcos GonzálezP. The Yew Disaster Severity Index: a new tool in disaster metrics. Prehosp Disaster Med. 2019;34(1):8-19.
RESUMEN
Advances in biological sciences have outpaced regulatory and legal frameworks for biosecurity. Simultaneously, there has been a convergence of scientific disciplines such as synthetic biology, data science, advanced computing and many other technologies, which all have applications in health. For example, advances in cybercrime methods have created ransomware attacks on hospitals, which can cripple health systems and threaten human life. New kinds of biological weapons which fall outside of traditional Cold War era thinking can be created synthetically using genetic code. These convergent trajectories are dramatically expanding the repertoire of methods which can be used for benefit or harm. We describe a new risk landscape for which there are few precedents, and where regulation and mitigation are a challenge. Rapidly evolving patterns of technology convergence and proliferation of dual-use risks expose inadequate societal preparedness. We outline examples in the areas of biological weapons, antimicrobial resistance, laboratory security and cybersecurity in health care. New challenges in health security such as precision harm in medicine can no longer be addressed within the isolated vertical silo of health, but require cross-disciplinary solutions from other fields. Nor can they cannot be managed effectively by individual countries. We outline the case for new cross-disciplinary approaches in risk analysis to an altered risk landscape.
RESUMEN
Epidemics and emerging infectious diseases are becoming an increasing threat to global populations-challenging public health practitioners, decision makers and researchers to plan, prepare, identify and respond to outbreaks in near real-timeframes. The aim of this research is to evaluate the range of public domain and freely available software epidemic modelling tools. Twenty freely utilisable software tools underwent assessment of software usability, utility and key functionalities. Stochastic and agent based tools were found to be highly flexible, adaptable, had high utility and many features, but low usability. Deterministic tools were highly usable with average to good levels of utility.