Knowledge-based normative safety measure approach: systematic assessment of capabilities to conquer COVID-19

Abstract

In this research article, we have introduced a knowledge-based approach to regional/national security measures. Proposed Knowledge-based Normative Safety Measure algorithm for safety measures helps to take practical actions to conquer COVID-19. We analyzed based on five dimensions: the correlation between detected cases and confirmed cases, social distance, the speed of detected cases, the correlation between imported cases and inbound cases, and the proportion of masks worn. It prompts actions based on the security level of the region. Through the use of our proposed algorithm, the government has accelerated the implementation of social distancing, accelerated test cases, and policies, etc., to prevent people from contracting COVID-19. This idea can be a very effective way to realize the impending danger and take action in advance. Help speed up the process of controlling the COVID-19. In pandemic times, it can be helpful to understand better. Holding the normative safety measure at a high level leads nations to perform excellently on triple T’s (testing, tracking, and treatment) policy and other safety acts. The proposed NSM approach facilitates for improve the governance of cities and communities.

A Numerical Investigation Based on Exponential Collocation Method for Nonlinear SITR Model of COVID-19

“…Each equation is describing the transmission behavior of individuals in the respective compartments. By this transmission number of individuals can vary in each of the five compartments [22][23][24][25][26][27][28][29][30]. The description of the transition rates in each cell is given in Table 2.…”

Dynamics of the COVID-19 pandemic: nonlinear approaches on the modelling, prediction and control

“…The study results suggest that the impact of lockdown on healthy individuals is negligible, while individuals with poor health incur significant effects on health. A knowledge-based approach for the implementation of safety measures to combat the spread of COVID-19 is introduced by Geetha et al [24]. The analysis is performed based on five different dimensions, including correlating the detected and confirmed COVID-19 cases, speed of detection, maintaining social distance, wearing of masks, and correlating the imported and inbound cases.…”

“…This special issue is a compilation of original research articles that address the dynamics and applications of COVID-19 through nonlinear dynamics. The articles are organized in five sections, comprising mathematical modeling and epidemics [1][2][3][4][5][6][7], the dynamics of several waves and transmission [8][9][10][11][12][13][14][15][16][17], neural network and deep learning related to COVID-19 [18][19][20][21][22][23][24], predictions and estimations related to COVID-19 [25][26][27][28][29][30], and detailed analysis on the pandemic and its applications [31][32][33][34][35].…”