CoSiT: An Agent-based Tool for Training and Awareness to Fight the Covid-19 Spread

Since the beginning of 2020 and following the recommendation of the Emergency Committee, the WHO (World Health Organization) Director General declared that the Covid-19 outbreak constitutes a Public Health Emergency of International Concern. Given the urgency of this outbreak, the international community is mobilizing to find ways to significantly accelerate the development of interventions. These interventions include raising awareness of ethical solutions such as wearing a face mask and respecting social distancing. Unfortunately, these solutions have been criticized and the number of infections and deaths by Covid-19 has only increased because of the lack of respect for these gestures on the one hand, and because of the lack of awareness and training tools on the spread of this disease through simulation packages on the other. To give importance to the respect of these measures, the WHO is going to try to propose to his member states, training and sensitization campaigns on coronavirus through simulation packages, so that the right decisions are taken in time to save lives. Thus, a rigorous analysis of this problem has enabled us to identify three directions for reflection. First, how to propose an IT tool based on these constraints in order to generalize training and awareness for all? Secondly, how to model and simulate these prescribed measures in our current reality? Thirdly, how to make it playful, interactive, and participative so that it is flexible according to the user’s needs? To address these questions, this paper proposes an interactive Agent-Based Model (ABM) describing a pedagogical (training and educational) tool that can help understanding the spread of Covid-19 and then show the impact of the barrier measures recommended by the WHO. The tool implemented is quite simple to use and can help make appropriate and timely decisions to limit the spread of Covid-19 in the population. © 2022,International Journal of Advanced Computer Science and Applications. All Rights Reserved.

Design and Implementation of a Blended Learning System for Higher Education in the Democratic Republic of Congo as a Response to Covid-19 Pandemic

Until now, the higher education system in the Democratic Republic of Congo has relied on the traditional face-to-face teaching method, which consists in the real physical presence of students and teachers during classes and lectures. Thus, the United Nations Educational, Scientific and Cultural Organization (UNESCO) is currently advocating e-learning as the only alternative for education in the COVID-19 era. It goes without saying that this requires specific frameworks and appropriate resources, including access to a good quality internet connection. Several countries around the world have implemented this recommendation since the first quarter of 2020 to protect their populations from the significant risks of Covid-19 contamination. In educational environment however, given the disadvantageous realities of the Democratic Republic of Congo, including the cost and quality of internet, the low rate of electrification, and the lack of experience of the educational stakeholders involved, the shift to e-learning remains a challenge. Thus, we propose in this paper a blended learning model that can smoothly introduce e-learning through a platform specially designed to integrate the traditional way of delivering courses in Congolese higher education with e-learning based on ICT. © 2022. International Journal of Emerging Technologies in Learning. All Rights Reserved.

Analysis, modeling and optimal control of COVID-19 outbreak with three forms of infection in Democratic Republic of the Congo.

This paper deals with modeling and simulation of the novel coronavirus in which the infectious individuals are divided into three subgroups representing three forms of infection. The rigorous analysis of the mathematical model is provided. We provide also a rigorous derivation of the basic reproduction number R 0 . For R 0 < 1 , we prove that the Disease Free Equilibium (DFE) is Globally Asymptotically Stable (GAS), thus COVID-19 extincts; whereas for R 0 > 1 , we found the co-existing phenomena under some assumptions and parametric values. Elasticity indices for R 0 with respect to different parameters are calculated with baseline parameter values estimated. We also prove that a transcritical bifurcation occurs at R 0 = 1 . Taking into account the control strategies like screening, treatment and isolation (social distancing measures), we present the optimal control problem of minimizing the cost due to the application of these measures. By reducing the values of some parameters, such as death rates (representing a management effort for all categories of people) and recovered rates (representing the action of reduction in transmission, improved screening, treatment for individuals diagnosed positive to COVID-19 and the implementation of barrier measures limiting contamination for undiagnosed individuals), it appears that after 140 - 170 days, the peak of the pandemic is reached and shows that by continuing with this strategy, COVID-19 could be eliminated in the population.