Fuzzy Modelling of Clinical and Epidemiological Factors for COVID-19

During this pandemic outbreak of COVID-19, the whole world is getting severely affected in respect of population health and economy. This novel virus has brought the whole world including the most developed countries to a standstill in a very short span like never before. The prime reason for this unexpected outburst of COVID-19 is lack of effective medicine and lack of proper understanding of the influencing factors. Here, the authors aim to find the effect of epidemiological factors that influence its spread using a fuzzy approach. For the same, a total of nine factors have been considered which are classified into risk and preventive factors. This fuzzy model supports to understand and evaluate the impact of these factors on the spread of COVID-19. Also, the model establishes a basis for understanding the effect of risk factors on preventive factors and vice versa. It is worth mentioning that this is the first attempt to analyze the effect of clinical and epidemiological factors with respect to COVID-19 using a fuzzy approach.

Usable-Security Assessment of Healthcare Software System Through Fuzzy ANP-TOPSIS Method

To address this research possibility, the present empirical study undertakes the assessment of usable-security of healthcare software system. The attributes considered for the assessment are: four factors at first level; thirteen sub-factors at the second level with six Hospital Management Software Systems (HMSS) as alternatives. Fuzzy Analytic Network Process (F-ANP) has been applied for evaluating the weights of the attributes and their relationship with one other. Finally, fuzzy Technique for Order of Preference by Similarity to Ideal Solutions (F-TOPSIS) technique has been applied and alternatives ranking has been estimated. Results of the study conclude that HMSS-1 provides better usable–security. Furthermore, as analysed, F-TOPSIS produced more convincing results in assessing the usable-security of the HMSS. This research analysis also corroborates that when compared with the Classical ANP TOPSIS, the Fuzzy-ANP TOPSIS is the ideal methodology for producing accurate results.