关键词: 多粒度粗糙集, 双论域量化模型, 应急决策, 公共卫生事件, 医务人员

Abstract: Outbreaks of major public infectious diseases are characterized by strong infectiousness, high pathogenicity and difficult curability, which pose serious threats to social and economic operations, production and living order, and people’s physical and mental health. Efficient protective measures, active patient identification and scientific precise treatment are the key to preventing the expansion of the epidemic. Medical staff, as a group deeply involved in the whole process of anti-epidemic, have the heavy workload of prevention, control and treatment, and are always facing the risk of being infected by the virus and the threat of shortage of medical resources. The negative emotions of the patients and atmosphere of tension and panic around them make the medical staff close to the physical and psychological limits. In this state, the deployment of epidemic prevention and control, and the economic and social development will be affected to varying degrees.
The accuracy of information acquisition will be affected by subjective mental tension and emotional instability of medical staff and objective time constraints after the outbreak of the epidemic, resulting in insufficient and inaccurate information on the impact of the epidemic on the physical and mental health of medical staff, so decision-makers need to make decisions from the perspective of absolute measurement and relative measurement to solve the physical and mental health problems of medical staff scientifically, efficiently and accurately. Therefore, this article takes the physical and mental health status of medical staff in the outbreak of major public infectious diseases as the research object and proposes a decision model for assessing the physical and mental health status of medical staff. We extract the key indicators affecting the physical and mental health of medical personnel from the combination of absolute and relative measures, construct a new model to deal with the uncertain decision problem called double quantitative multi-granulation fuzzy rough set model over two universes by using different kinds of medical stuff groups and the impact of the epidemic on their physical and mental health indexes, and discuss its definition and basic properties as well as its relationship with existing models. In this way, a quantitative portrayal of the characteristic indicators affecting the physical and mental health of medical staff is achieved, so as to solve the problems such as the characterization of imprecise characteristic information, the representation and fusion of multi-perspective characteristic indicator information, the applicability of theoretical models and the interpretability of results. At the same time, the model is simulated and applied to the impact of public infectious diseases on medical staff’s real data collected from the survey, and the results of the impact of major infectious diseases on medical staff in three perspectives of emotions, behaviors and attitudes in cities of different administrative levels are obtained.
The results show that the medical staff in prefecture-level cities are most affected by the epidemic from the perspectives of emotion, behavior and attitude. The reason is that although the provincial capital cities have more cases, larger population base and higher risk of infection, they have strong technical force, advanced hardware equipment, standardized epidemic prevention system and stable living order, so the medical staff working in this environment are less affected by the epidemic. In towns and counties, there are few cases, low population density, and low frequency of communication with the outside world in terms of human resources, materials and information, so medical staff have a higher sense of psychological security. On the contrary, compared with provincial capital cities, prefecture-level cities have backward medical equipment and are lack of medical resources, and there are possible omissions in the epidemic prevention system; prefecture-level cities have more cases of illness and frequent communication with the outside world than towns and county areas, so the medical staff in this area are more affected by the epidemic and have a low sense of security. To sum up, we suggest that the relevant medical institutions in prefecture-level urban areas should pay more attention to the physical and mental health of medical staff, and provide them with reasonable psychological assistance and treatment if necessary.

Key words: multi-granulation rough set, double quantitative model over two universes, emergency decision-making, public health events, medical staff