Design of a University Pandemic Response Decision Support System

The global effort to combat the COVID-19 pandemic has changed how people conduct their daily lives. Institutions of higher education have been greatly impacted by these changes and must find ways to adapt to this new environment. Universities are a unique case because they must control disease spread, while maintaining the same or similar quality of education. The University Pandemic Response Decision Support System (UPRDSS) is a system designed to help universities pick the most suitable method for instruction delivery when faced with any pandemic. Using George Mason University as a case study, the goal was to design a system that allows university administrations to make an educated operations decision. The UPRDSS achieves this by simulating the spread of disease, analyzing learning outcome data, and using a multi-attribute utility function to determine the most appropriate method of instruction that enables positive learning and health outcomes.

Advocating for scientifically sound spill response decision making in a social media driven world

In today's world of rapid information sharing, multiple communication platforms, data sources, and an unending stream of opinions and commentary are the norm. In this increasingly interconnected world there is a tendency to blur the critical distinction between opinion and fact and to consider that all opinions are created equally and are of equal weight. Add to this an increased noise level around most subjects and a general lack of scientific discourse around technical topics and the end result has been an increased lack of acceptance or understanding of expert, fact-based opinions. This presents a challenge during the outreach efforts of the spill response community in that a number of potential stakeholders, often with less experience, may have developed their own “expert attitude” with respect to spill response tools and their use. In spill response, this growing trend of questioning established knowledge or expert opinion presents a unique challenge as timely decision making is critical towards mounting a successful response. Spill incidents are complex and usually consist of evolving scenarios, where scientifically-sound decisions are to be made against the wider context of operational considerations and ecological, socio-economic and cultural sensitivities. Often these nuances are missed or unknown to the general public and established practices and proven operational principles may be disregarded in the presence of other, potentially less rigorous or fact-based information that is easily found via social media channels and/or through the opinions and beliefs of less informed laypersons. It is difficult to ensure that a scientifically-sound message is getting through these multiple inputs of unfiltered data and this has the potential to negatively influence response decision making or, in the worst cases, hinder the successful use of all tools in the response toolbox. In the following paper, the authors examine spill response advocacy efforts aimed at promoting scientifically-sound response decision-making by various oil spill industry stakeholders since the Deepwater Horizon incident. While reviewing the lessons learned from these efforts, the authors will closely examine the heightened public awareness and engagement through social media channels and how it influences stakeholder risk perception of oil spills and various response options. The paper will assess the emerging challenges towards stakeholder engagement in relation to the oil spill response community and make recommendations for the future on scientific discourse, outreach and communication and potential effects on response decision making in a social media obsessed world.

Outbreak response intervention models of vaccine-preventable diseases in humans and foot-and-mouth disease in livestock: a protocol for a systematic review

IntroductionOutbreaks of vaccine-preventable diseases continue to threaten public health, despite the proven effectiveness of vaccines. Interventions such as vaccination, social distancing and palliative care are usually implemented, either individually or in combination, to control these outbreaks. Mathematical models are often used to assess the impact of these interventions and for supporting outbreak response decision making. The objectives of this systematic review, which covers all human vaccine-preventable diseases, are to determine the relative impact of vaccination compared with other outbreak interventions, and to ascertain the temporal trends in the use of modelling in outbreak response decision making. We will also identify gaps and opportunities for future research through a comparison with the foot-and-mouth disease outbreak response modelling literature, which has good examples of the use of modelling to inform outbreak response intervention decision making.Methods and analysisWe searched on PubMed, Scopus, Web of Science, Google Scholar and some preprint servers from the start of indexing to 15 January 2020. Inclusion: modelling studies, published in English, that use a mechanistic approach to evaluate the impact of an outbreak intervention. Exclusion: reviews, and studies that do not describe or use mechanistic models or do not describe an outbreak. We will extract data from the included studies such as their objectives, model types and composition, and conclusions on the impact of the intervention. We will ascertain the impact of models on outbreak response decision making through visualisation of time trends in the use of the models. We will also present our results in narrative style.Ethics and disseminationThis systematic review will not require any ethics approval since it only involves scientific articles. The review will be disseminated in a peer-reviewed journal and at various conferences fitting its scope.PROSPERO registration numberCRD42020160803.

Parallel Simulation Decision-Making Method for a Response to Unconventional Public Health Emergencies Based on the Scenario–Response Paradigm and Discrete Event System Theory

ABSTRACTGiven the non-repeatability, complexity, and unpredictability of unconventional public health emergencies, building accurate models and making effective response decisions based only on traditional prediction–response decision-making methods are difficult. To solve this problem, under the scenario–response paradigm and theories on parallel emergency management and discrete event system (DES), the parallel simulation decision-making framework (PSDF), which includes the methods of abstract modeling, simulation operation, decision-making optimization, and parallel control, is proposed for unconventional public health emergency response processes. Furthermore, with the example of the severe acute respiratory syndrome (SARS) response process, the evolutionary scenarios that include infected patients and diagnostic processes are transformed into simulation processes. Then, the validity and operability of the DES–PSDF method proposed in this paper are verified by the results of a simulation experiment. The results demonstrated that, in the case of insufficient prior knowledge, effective parallel simulation models can be constructed and improved dynamically by multi-stage parallel controlling. Public health system bottlenecks and relevant effective response solutions can also be obtained by iterative simulation and optimizing decisions. To meet the urgent requirements of emergency response, the DES–PSDF method introduces a new response decision-making concept for unconventional public health emergencies.