The Modeling of the Capacity of the Moroccan Healthcare System in the Context of COVID-19

The outbreak of SARS-Cov2 in China and its subsequent spread has caused a global pandemic. The authors conducted a simple susceptible-infected (SI) model of the spread of COVID-19 in Moroccan population. The model is based on combining the average contact rate (µmax) extracted from the early exponential phase of the outbreak with a logistic simulation over time. Interestingly, this modeling approach showed a perfect fit with a strong correlation between real confirmed and estimated cases when calibrated on the Chinese declining outbreak. Subsequently, the model was applied for studying the ongoing COVID-19 outbreak in Morocco to determine the needed time for reaching 10,000 confirmed cases whose 15% (1,500) are at risk of developing health complications requiring patient care in hospitals. The latter total capacity does not exceed 1,640 beds according to the authorities. Incorporating these parameters in the logistic model, they predicted that the Moroccan healthcare system will be at 27%, 50%, 76%, and 90% of saturation on April 11, 16, 23, and May 4, 2020, respectively.

Gender Differences in the Effect of Type, Level and Amount of Information on Attention Ability among Saudi High School Students

Boredom has been considered as a significant and prevalent among students in the classroom. Research indicates the necessity to tackle the negative consequences of these important and pervasive academic emotions. Despite the plethora of studies investigating the psychological effect on attention ability, far fewer have considered gender as a moderator of the effect of information characteristics on students’ attention ability. Thus, the purpose of this study is to look at gender disparities in the impact of type, level, and amount of information on students' attention capacity. Based on the Guilford structure-of-intellect (SI) model, forty tests were designed and validated to gather and analyse the data. The participants of the study were 60 high school students (level 10 and 11) from the Al-Qunfudah district. An equal number of male and female participants were selected randomly. Type of information represented in semantic and symbolic, the level of information represented in units, cases, relations, while the amount of information was represented in (5,7,9) based on Miller model. Data was collected using newly developed and verified tests. Independent t-test studies revealed no significant variations in the type, level, and amount of information on students' attention skills among male and female students. Several discussions were drawn in light of the findings. Suggestions and recommendations were presented.

A new model to identify node importance in complex networks based on DEMATEL method

It is still a hot research topic to identify node importance in complex networks. Recently many methods have been proposed to deal with this problem. However, most of the methods only focus on local or path information, they do not combine local and global information well. In this paper, a new model to identify node importance based on Decision-making Trial and Evaluation Laboratory (DEMATEL) is presented. DEMATEL method is based on graph theory which takes the global information into full consideration so that it can effectively identify the importance of one element in the whole complex system. Some experiments based on susceptible-infected (SI) model are used to compare the new model with other methods. The applications in three different networks illustrate the effectiveness of the new model.

Time-dependent SI model for epidemiology and applications to Covid-19

A generalisation of the Susceptible-Infectious model is made to include a time-dependent transmission rate, which leads to a close analytical expression in terms of a logistic function. The solution can be applied to any continuous function chosen to describe the evolution of the transmission rate with time. Taking inspiration from real data of the Covid-19, for the case of cumulative confirmed positives and deaths, we propose an exponentially decaying transmission rate with two free parameters, one for its initial amplitude and another one for its decaying rate. The resultant time-dependent SI model, which under extra conditions recovers the standard Gompertz functional form, is then compared with data from selected countries and its parameters fit using Bayesian inference. We make predictions about the asymptotic number of confirmed positives and deaths, and discuss the possible evolution of the disease in each country in terms of our parametrisation of the transmission rate.

Optimal Control of Dengue Transmission with Vaccination

Dengue disease is caused by four serotypes of the dengue virus: DEN-1, DEN-2, DEN-3, and DEN-4. The chimeric yellow fever dengue tetravalent dengue vaccine (CYD-TDV) is a vaccine currently used in Thailand. This research investigates what the optimal control is when only individuals having documented past dengue infection history are vaccinated. This is the present practice in Thailand and is the latest recommendation of the WHO. The model used is the Susceptible-Infected-Recovered (SIR) model in series configuration for the human population and the Susceptible-Infected (SI) model for the vector population. Both dynamical models for the two populations were recast as optimal control problems with two optimal control parameters. The analysis showed that the equilibrium states were locally asymptotically stable. The numerical solution of the control systems and conclusions are presented.