Emergency preparedness during the COVID-19 pandemic: Modelling the roles of social media with fuzzy DEMATEL and analytic network process

Geoepidemiological perspective on COVID-19 pandemic review, an insight into the global impact

The COVID-19 pandemic showed major impacts, on societies worldwide, challenging healthcare systems, economies, and daily life of people. Geoepidemiology, an emerging field that combines geography and epidemiology, has played a vital role in understanding and combatting the spread of the virus. This interdisciplinary approach has provided insights into the spatial patterns, risk factors, and transmission dynamics of the COVID-19 pandemic at different scales, from local communities to global populations. Spatial patterns have revealed variations in incidence rates, with urban-rural divides and regional hotspots playing significant roles. Cross-border transmission has highlighted the importance of travel restrictions and coordinated public health responses. Risk factors such as age, underlying health conditions, socioeconomic factors, occupation, demographics, and behavior have influenced vulnerability and outcomes. Geoepidemiology has also provided insights into the transmissibility and spread of COVID-19, emphasizing the importance of asymptomatic and pre-symptomatic transmission, super-spreading events, and the impact of variants. Geoepidemiology should be vital in understanding and responding to evolving new viral challenges of this and future pandemics.

Using MCDA to assist an Intermunicipal community develop a resilience strategy in face of the pandemic caused by the SARS-CoV-2

The topic of regional economic resilience has been the subject of intense debate in the academic and political fields over the past decade and gained a new sense of urgency because of the pandemic caused by the SARS-CoV-2 virus as territories faced relevant impacts on their economies and social structures. The economic downturn, the increase in unemployment, and the deterioration of social conditions lead policy makers to search for solutions to make their territories more resilient to this type of event. The current article discusses how multicriteria decision analysis (MCDA) was used to help a Portuguese Intermunicipal Community, formed by 16 councils, develop a strategy to make its territory more cohesive, competitive, sustainable, and resilient. In addition to discussing an innovative application of a MCDA technique, this article illustrates how, through a MCDA approach, it was possible to reach a consensus among several policymakers, despite each of them having their own political agendas.

Exploring the Critical Driving Forces and Strategy Adoption Paths of Professional Competency Development for Various Emergency Physicians Based on the Hybrid MCDM Approach

The implementation of competency-based medical education (CBME) focuses on learners' competency outcomes and performance during their training. Competencies should meet the local demands of the healthcare system and achieve the desired patient-centered outcomes. Continuous professional education for all physicians also emphasizes competency-based training to provide high-quality patient care. In the CBME assessment, trainees are evaluated on applying their knowledge and skills to unpredictable clinical situations. A priority of the training program is essential in building competency development. However, no research has focused on exploring strategies for physician competency development. In this study, we investigate the professional competency state, determine the driving force, and provide emergency physicians' competency development strategies. We use the Decision Making Trial and Evaluation Laboratory (DEMATEL) method to identify the professional competency state and investigate the relationship among the aspects and criteria. Furthermore, the study uses the PCA (principal component analysis) method to reduce the number of components and then identify the weights of the aspects and components using the ANP (analytic network process) approach. Therefore, we can establish the prioritization of competency development of emergency physicians (EPs) with the VIKOR (Vlse kriterijumska Optimizacija I Kompromisno Resenje) approach. Our research demonstrates the priority of competency development of EPs is PL (professional literacy), CS (care services), PK (personal knowledge), and PS (professional skills). The dominant aspect is PL, and the aspect being dominated is PS. The PL affects CS, PK, and PS. Then, the CS affects PK and PS. Ultimately, the PK affects the PS. In conclusion, the strategies to improve the professional competency development of EPs should begin with the improvement from the aspect of PL. After PL, the following aspects that should be improved are CS, PK, and PS. Therefore, this study can help establish competency development strategies for different stakeholders and redefine emergency physicians' competency to reach the desired CBME outcomes by improving advantages and disadvantages.

Research Progress and Improvement Ideas of Anti-Epidemic Resilience in China's Urban Communities

In the post-epidemic era, China's urban communities are at the forefront of implementing the whole chain of accurate epidemic prevention and control. However, the uncertainty of COVID-19, the loopholes in community management and people's overly optimistic judgment of the epidemic have led to the frequent rebound of the epidemic and serious consequences. Existing studies have not yet formed a panoramic framework of community anti-epidemic work under the concept of resilience. Therefore, this article first summarizes the current research progress of resilient communities from three perspectives, including ideas and perspectives, theories and frameworks and methods and means, and summarizes the gap of the current research. Then, an innovative idea on the epidemic resilience of urban communities in China is put forward: (1) the evolution mechanism of community anti-epidemic resilience is described through the change law of dynamic networks; (2) the anti-epidemic resilience of urban communities is evaluated or predicted through the measurement criteria; (3) a simulation platform based on Multi-Agent and dynamic Bayesian networks simulates the interactive relationship between "epidemic disturbance-cost constraint--epidemic resilience"; (4) the anti-epidemic strategies are output intelligently to provide community managers with decision-making opinions on community epidemic prevention and control.

Optimal configuration of polygeneration plants under process failure, supply chain uncertainties, and emissions policies

The COVID-19 pandemic exacerbated the erratic demand, supply, and prices of energy. It is unlikely that these effects would subside post-pandemic, especially with the pre-existing climate change crisis that also needs to be addressed. Emissions policies aimed at mitigating climate change place economic pressures on already disrupted energy systems, which could worsen energy insecurity. Configuring disrupted energy systems to build robustness to supply chain-related uncertainties and economic pressures of emissions policies are desired to simultaneously address these problems. To this end, this study introduces a robust mixed-integer linear program that simultaneously incorporates the abovementioned needs for configuring energy production systems. The proposed model is tested through a demonstrative case study that deals with a biomass-based polygeneration plant design problem. The scenario analysis and sensitivity test on the model concerning the case under consideration yields the following results: (1) setting ambitious target profits reduces the probability of the resulting plant configuration to achieving the set targets in the presence of supply chain-related uncertainties, while conservative targets promote the opposite; (2) the inoperability of the plant's process units reduces the robustness of optimal process configurations, and drastic configurations may be required to achieve targets despite the inoperability of process units; (3) a hybrid cap-and-trade and emissions tax policy yields approximately similar implications to the robustness of the resulting optimal plant configurations compared to a pure cap-and-trade policy, but the rate of decrease in robustness with respect to the initial emissions cap is lesser in the hybrid policy than in the pure cap-and-trade policy.

An intuitionistic fuzzy decision support system for COVID-19 lockdown relaxation protocols in India

In January 2020, the World Health Organization (WHO) identified a world-threatening virus, SARS-CoV-2. To diminish the virus spread rate, India implemented a six-month-long lockdown. During this period, the Indian government lifted certain restrictions. Therefore, this study investigates the efficacy of India's lockdown relaxation protocols using fuzzy decision-making. The decision-making trial and evaluation laboratory (DEMATEL) is one of the fuzzy MCDM methods. When it is associated with intuitionistic fuzzy circumstances, it is known as the intuitionistic fuzzy DEMATEL (IF-DEMATEL) method. Moreover, converting intuitionistic fuzzy into a crisp score (CIFCS) algorithm is an aggregation technique utilized for the intuitionistic fuzzy set. By using IF-DEMATEL and CIFCS, the most efficient lockdown relaxation protocols for COVID-19 are determined. It also provides the cause and effect relationship of the lockdown relaxation protocols. Additionally, the comparative study is carried out through various DEMATEL methods to see the effectiveness of the result. The findings would be helpful to the government's decision-making process in the fight against the pandemic.

How Do People Decide on Getting Vaccinated? Evaluating the COVID-19 Vaccination Program through the Lens of Social Capital Theory

The COVID-19 pandemic has disrupted economies at a scale unprecedented in recent history, and vaccination is deemed the only option to ultimately halt its spread. However, vaccine hesitancy remains a global issue that must be addressed. If left unaddressed, it will impede the recovery of both the economy and public health following the pandemic. To better understand the issue, on the premise that individuals have layers of social ties to achieve common goals, social capital theory is proposed to examine the social connections associated with vaccine acceptance. A case study of the Republic of the Philippines’ vaccination program, in the form of an online survey involving 430 participants, was conducted using logistic binomial regression to analyze the data. Findings reveal that people’s vaccination decisions are influenced by their perceptions of their social ties regarding the vaccines, such as the perceptions one’s social ties’ trust in the vaccines, safety of use, benefits vaccines can offer, the role of media in information dissemination, and the influence of social networks. Insights regarding these findings are also discussed.