A Group Emergency Decision-Making Method for Epidemic Prevention and Control Based on Probabilistic Hesitant Fuzzy Prospect Set Considering Quality of Information

Abstract

Epidemics can bring huge impacts to economic operation and human health, a practical and effective emergency decision-making (EDM) method is of great significance to reduce all kinds of losses and slow the spread of epidemics. In the process of EDM, decision information is usually uncertain and vague, and the psychological behaviors and various perspectives of decision makers (DMs) should be considered. Hence, this paper develops a group emergency decision-making (GEDM) method under risk based on the probabilistic hesitant fuzzy set (PHFS) and cumulative prospect theory (CPT), in which probabilistic hesitant fuzzy prospect set (PHFPS) that combines PHFS and CPT is developed to portray the vagueness of decision information and psychologies of DMs. Moreover, experts’ creditability in evaluation criteria is generally different because of the differences of their own knowledge structures, practical experience, individual preference and so on. A formula is proposed to measure the quality of decision information provided by experts for revising the expert weights. In addition, the evaluation criteria supporting the GEDM of epidemics are given. Finally, the proposed method is demonstrated by an empirical case study of COVID-19, and the comparison analysis based on the rank-biased overlap model and the sensitivity analysis are conducted to the illustrate the validity of the proposed method.

Decision Support Frameworks in Public Health Emergencies: A Systematic Review of Dynamic Models in Complex Contexts

“…The frameworks are presented in several formats, adopting conceptual structures [10,16,17,20]; the use of methods and modeling with a multicriteria approach [11][12][13][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58]; the application of questionnaires with experts and managers working in PHEs, [14,19,23]; and the description of steps and guidelines for guiding the context analysis [1,4,8,9,15,18,59]. Figure 3 shows the strategic plan for managing PHEs and addresses policies, planning, and coordination related to studies concerned with the resilience of structures [20,47], action plans [16,17], and government strategies [18], as well as ethical values [19] that challenge the positioning of nations in the face of a context of uncertainty, particularly for vulnerable populations.…”

“…The dimensions of information and monitoring and evaluation of the results of managers' responses deal with the evolution of risk dynamics that need to be managed in emergencies [10,23,45,52,55,59]. This is a challenge related to the production of evidence to support the best decisions at all levels [12,13,46,57] but with challenges of its own generation and quality [14,15]. Information is an input to the decision-making process, and its sharing between states and health agencies needs to be prioritized [8] so that the re-sponse is adapted to the reality of the context [9], which implies knowing the government's strategies [43,56] and the WHO's guidelines [58].…”

“…The gaps point to the development of consensus models which integrate psychological factors, information quality, and decision speed. Thus, decision-maker hesitation and perception demand weights and ranking of alternatives in structured analysis to mitigate their bounded rationality [12,13] and achieve an adequate deliberative process through a better integration of heuristics, biases, and analysis of multiple variables [3]. It is difficult to establish comprehensive, systematic, and standardized evaluation indexes in real situations [54], when organizations and governments, individuals, or groups act according to their own policies, resulting in the compromised interoperability of systems and knowledge generation on common challenges, such as cross-border disease transmission [8].…”

“…The decision-making process to response and prevention plans to the COVID-19 pandemic, according to the studies, requires the application of multicriteria methods for decision support, integrating the expression of uncertainty by decision makers, setting criteria weights for choosing an optimal solution [46], and ranking alternatives based on the quality of available information and on psychological factors of the decision maker [12,13], also the values for a range or set of variables and not exact values [57]. The challenges are the application methods restricted to experts and decision makers and their linguistic expressions, without considering information from different sources and characteristics, which may cause biased results of response ranking for emergencies [46], and the incorporation of the dynamics of the psychological process of decision makers into decision support frameworks on risk propensity or aversion in pandemic processes [57].…”

“…The bounded rationality of decision makers and the behavior of their heuristics and biases in contexts with variables of uncertainty pose a challenge to framework models [3], requiring them to acquire complicated language information and comprehend the hesitations of decision makers [12]. Consensus production among actors' nonlinear preferences, dependency on source conditions, and assessments of benefits and losses present a challenge for group decision making [13]. As an input to the decision process, at all decision levels, models must improve the quality of data regarding how managers apply strategies using low or medium certainty evidence [14][15][16].…”