The prevalence of at least one underlying medical condition, which increases the likelihood of developing the severe COVID-19 disease, is found in 22 of the world's population. The primary underlying medical condition that contributes to COVID-19 problems in Ghana is hypertension. This work investigate COVID-19 in a population with hypertension taking into account double dose vaccination of susceptible individuals. The study modifies a previous model proposed in the literature to include double dose vaccination and Atangana-Baleanu-Caputo fractional derivatives is used to solve the model. We give few definitions of the ABC operator and determine the existence and uniqueness of the solution. Using COVID-19 data for the period February 21, 2021 to July, 24 2021, the model is tested. The dynamics of the disease in the community were shown to be influenced by fractional-order derivatives. Contrary to the previous model proposed in the literature, the vulnerable group saw a significant reduction in the number, which may be attributed to the double dose vaccination. We recommend a cost-effective optimal control analysis in future work.

In the method comparison approach, two measurement errors are observed. The classical regression approach (linear regression) method cannot be used for the analysis because the method may yield biased and inefficient estimates. In view of that, the Deming regression is preferred over the classical regression. The focus of this work is to assess the impact of censored data on the traditional regression, which deletes the censored observations compared to an adapted version of the Deming regression that takes into account the censored data. The study was done based on simulation studies with NLMIXED being used as a tool to analyse the data. Eight different simulation studies were run in this study. Each of the simulation is made up of 100 datasets with 300 observations. Simulation studies suggest that the traditional Deming regression which deletes censored observations gives biased estimates and a low coverage, whereas the adapted Deming regression that takes censoring into account gives estimates that are close to the true value making them unbiased and gives a high coverage. When the analytical error ratio is misspecified, the estimates are as well not reliable and biased.

Fractional-order derivative modeling continues to receive great interest among researchers across the globe. In this study, Tuberculosis-COVID-19 coinfection is studied using Atangana–Baleanu fractional-order derivatives defined in Caputo sense. We confirmed the existence and singularity of the solution and investigated the model’s equilibrium points. Additionally, we examined the model’s stability in terms of the Ulam–Hyers and generalized Ulam–Hyers stability criteria. The basic reproduction number R 0 was calculated using the next-generation matrix approach. We also looked into the model’s disease-free equilibrium point’s regional stability. Numerical scheme for simulating the fractional-order system with Mittag–Leffler Kernels are presented. Numerical simulations are given to validate the model. Results of the simulation showed a decline in the number of COVID-19 infections within the population when the fractional operator was reduced.

Background: This paper presents a newly developed Matlab code for the numeri- cal simulation of compartmental/deterministic models. It addresses modeling and simulation issues concerning compartmental models. The code is easy to under- stand and edit for the simulation of compartmental models. An alternative codes for statistical software package R has been proposed for the same model. R software is freely available for use. Methods: We proposed a basic SEIR model for illustration purposes. Matlab and R software codes are developed for the SEIR model which users can follow and easily understand the computations. Results: The two codes work on all Matlab and R versions. For models with more compartments, we suggest using higher version of Matlab and R. Matlab works on windows, Mac and Linux Conclusions: New Matlab software codes purposely for numerical simulations of classical deterministic models which can run on any version of Matlab has been introduced in this paper. This code can be edited/modify to suit any deterministic models and any desired output required. An alternative open source free version has been written in R has been provided as well