ABSTRACT
Objective: The purpose of this research was to examine how the Coronavirus epidemic has affected the compassion of dentistry students in Bhubaneswar. Materials and Equipment: In this study, undergraduate dental students in Bhubaneswar served as the research subjects for a cross-sectional analysis. Following informed permission, dental school students from two time periods (one before and one after the occurrence of Coronavirus in India) were given the authorized and pretested Toronto Sympathy Poll (TEQ) (Bhubaneswar). A five-point scale was used to indicate members' levels of comprehension. Using a one-way analysis of variance, we compared students' TEQ scores during their four years of dentistry school (investigation of difference). The results of the meetings were analyzed using Tukey's post hoc test. The Chi-square test was used to analyze data collected before and during the recent Coronavirus epidemic (importance level, p 0.05). Only 270 of the 300 dentistry students enrolled in the focus before Coronavirus reached its conclusion;the remaining 260 enrolled thereafter. Comparing results from the same group before and after exposure to the Coronavirus revealed striking discrepancies in the compassion ratings. More than eighty-five percent of individuals answered the survey. As a result of this study's findings, it is concluded that undergraduate dental students' mean empathy ratings increased after COVID-19, indicating a discernibly greater degree of empathy at that time. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
ABSTRACT
The evacuation of the population from flood-affected regions is a non-structural measure to mitigate flood hazards. Shelters used for this purpose usually accommodate a large number of flood evacuees for a temporary period. Floods during a pandemic result in a compound hazard. Evacuations under such situations are difficult to plan as social distancing is nearly impossible in the highly crowded shelters. This results in a multi-objective problem with conflicting objectives of maximizing the number of evacuees from flood-prone regions and minimizing the number of infections at the end of the shelter's stay. To the best of our knowledge, such a problem is yet to be explored in literature. Here we develop a simulation-optimization framework, where multiple objectives are handled with a max-min approach. The simulation model consists of an extended Susceptible-Exposed-Infectious-Recovered-Susceptible model. We apply the proposed model to the flood-prone Jagatsinghpur district in the state of Odisha, India. We find that the proposed approach can provide an estimate of people required to be evacuated from individual flood-prone villages to reduce flood hazards during the pandemic. At the same time, this does not result in an uncontrolled number of new infections. The proposed approach can generalize to different regions and can provide a framework to stakeholders to manage conflicting objectives in disaster management planning and to handle compound hazards.