A multiple criteria approach for building a pandemic impact assessment composite indicator: The case of COVID-19 in Portugal.

The COVID-19 pandemic has caused major damage and disruption to social, economic, and health systems (among others). In addition, it has posed unprecedented challenges to public health and policy/decision-makers who have been responsible for designing and implementing measures to mitigate its strong negative impact. The Portuguese health authorities have used decision analysis techniques to assess the impact of the pandemic and implemented measures for counties, regions, or across the entire country. These decision tools have been subject to some criticism and many stakeholders requested novel approaches. In particular, those which considered the dynamic changes in the pandemic's behaviour due to new virus variants and vaccines. A multidisciplinary team formed by researchers from the COVID-19 Committee of Instituto Superior Técnico at the University of Lisbon (CCIST analyst team) and physicians from the Crisis Office of the Portuguese Medical Association (GCOM expert team) collaborated to create a new tool to help politicians and decision-makers to fight the pandemic. This paper presents the main steps that led to the building of a pandemic impact assessment composite indicator applied to the specific case of COVID-19 in Portugal. A multiple criteria approach based on an additive multi-attribute value theory aggregation model was used to build the pandemic assessment composite indicator. The parameters of the additive model were devised based on an interactive socio-technical and co-constructive process between the CCIST and GCOM team members. The deck of cards method was the adopted technical tool to assist in the assessment the value functions as well as in the assessment of the criteria weights. The final tool was presented at a press conference and had a powerful impact on the Portuguese media and on the main health decision-making stakeholders in the country. In this paper, a completed mathematical and graphical description of this tool is presented.

XOR-analytic network process and assessing the impact of COVID-19 by sector.

The consequences of any extreme event can deteriorate any system at all levels: socially, economically, and operationally. The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), provides a good example of the tremendous impact that can be produced by such extreme events. To effectively measure and mitigate the impact of the COVID-19 pandemic and relaunch the Moroccan economy, policymakers need to determine which sectors have been most impacted. Due to the high level of uncertainty and complexity surrounding this health crisis, this study first develops a new technique for dealing with decision problems under uncertainty using exclusive-or (XOR) logic, called the XOR-analytic network process (XOR-ANP). Then, the proposed technique is adopted to assess the impact of COVID-19 on seven relevant sectors (tourism, transport, industrial, financial, agriculture, education, and healthcare) by considering social, operational, and economic dimensions. The key findings show that COVID-19 has a significant impact on Moroccan's tourism, healthcare, and transport sectors, with respect to social-economic and operational dimensions by 30.99%, 21.81%, and 17.88%, respectively. These results indicate that most of the United Nations Sustainable Development Goals for 2030, such as "Healthy Lives", "Decent Work" and "Economic Growth" have been severely impacted, thus, assistance and recovery are urgently needed.

Methodology applied to managerial decision-making in the context of COVID-19

Purpose - This paper aims to propose a methodology for managerial decision-making based on scenario planning and a multi-criteria approach. Design/methodology/approach - The methodology consists of two stages, one referring to scenario planning and the other to multi-criteria decision-making. The methodology was applied to a company in the Brazilian agribusiness sector, aiming to help managers face the current situation of the COVID-19 pandemic. Findings - The proposal addresses a set of simple methods for developing a scenario analysis based on different approaches. Although the methodology may allow the future addition of new, perhaps more robust strategies, the purpose of the analysis is not only to tell the decision maker which strategy should be adopted, but also to provide greater knowledge about the problem and possible scenarios. Originality/value - The contribution of this research is to propose a structured and easily applicable methodology that can help managers in the future planning of their companies, especially when faced with complex decisions and high level of uncertainty.

Effects of country success on COVID-19 cumulative cases and excess deaths in 169 countries.

COVID-19 has caused over 260 million confirmed cases and over 5 million deaths globally. The results of statistical and multiple criteria analyses on the success of 169 countries and on COVID-19 cumulative cases and excess deaths show that the prosperity of a country relates directly to the consequences due to the pandemic. The topic of this article is the Country Success and COVID-19 (CSC) Map of the World. As a country's success grows, this map shows how cumulative cases of COVID-19 increase; at the same time, excess deaths decrease. The indicators in the system of criteria regarding country success and sustainability are interrelated. Conditional country successes remain quite similar, despite changes to the numbers of countries and their indicators. Likewise, the seven clusters of countries under consideration group together independently of which system of indicators had been applied for their analysis. The 2020 Inglehart-Welzel Cultural Map of the World, which is grounded on surveys, and the CSC Map, which is grounded on statistical indicators, have axes that correlate with one another significantly. The CSC Map Model explains over 63% of the dispersions pertinent to COVID-19 cumulative cases, over 52% of COVID-19 excess deaths, and over 95% of country success variables. The layout of the clusters on the CSC Map changes little over time. Upon performance of the correlation analysis, it was established that strong and statistically significant relationships exist between 169 countries success and sustainability linked with their current air quality score (r = 0.602, p < 0.01) and the environmental performance index (EPI) score (r = 0.931, p < 0.01). The results obtained show that when a country's EPI score and current air quality improve by 1%, excess deaths decrease, respectively, by 2.33 and 1.55%. Global integrated analysis on country successes, COVID-19 cumulative cases, and excess deaths comprise this study.

A sociotechnical approach to vaccine manufacturer selection as part of a global immunization strategy against epidemics and pandemics.

These are unprecedented times while the world weathers the highly infectious respiratory pandemic caused by coronavirus disease-19 (COVID-19). Humanity has experienced other cataclysmic events, but something as novel as this pandemic cannot be easily described. A safe COVID-19 vaccine is often hailed as the only effective public health method to prevent the further spread of this virus. New vaccines' cost has increased even as policymakers struggle with limited resources and budget constraints. Thus, more decision-support tools are needed to facilitate the selection of vaccine manufacturers as part of a global immunization strategy against COVID-19 or other epidemics and pandemics. This study sought to address this issue by combining three well-established operational research methods (i.e., cognitive mapping, decision-making trial and evaluation laboratory, and the Choquet integral). Based on the insights provided by a panel of experts on vaccination and infectious diseases, a vaccine manufacturer selection mechanism was developed that incorporates the World Health Organization's guidelines. This approach facilitated the identification of multiple selection criteria regarding vaccine manufacturers, their allocation into six major clusters (i.e., soundness of scientific approach and technology used; speed of delivery; cost; liability and risk sharing; ability to supply sufficient quantities through production capacity development; and global solidarity), and subsequent analysis of the respective cause-and-effect relationships. The results of a real-life application of the proposed selection system were further consolidated by a member of Saint Francisco Xavier Hospital Infectious Diseases Unit in Lisbon, Portugal. The mechanism's advantages and limitations are also discussed.

Selection of healthcare waste disposal firms using a multi-method approach.

The aim of this study is to propose a hybrid multi criteria decision making model with a linear programming (LP) model to tackle the issue of safe disposal of hazardous and infectious healthcare waste. For this, ten criteria in this study have been identified from literature and field surveys which are modelled using Decision making trial and evaluation (DEMATEL) and Analytic network process (ANP) methods to select the best disposal firm i.e. single sourcing for a hospital. We found that Experience of the firm, Technology for disposal, and Waste collection infrastructure acts as the most vital criteria in selecting a healthcare waste disposal firm for single sourcing. Furthermore, to optimize the total value of disposal and mitigating the risk involved in disposing waste through single sourcing; the LP model considering constraints such as waste lose constraint and waste processing constraint etc. Is solved for multiple sourcing using Lingo 18.0. The solution to LP results into allocation of 500, 500, and 1000 (kg/day) disposables to healthcare waste disposal firms D1, D2 and D3, respectively. The multi-method approach proposed in this study helps the hospital management in selecting economically, socially, and environmentally sustainable healthcare waste disposal firm.