This paper is concerned with the formulation and analysis of an epidemic model of COVID-19 governed by an eight-dimensional system of ordinary differential equations, by taking into account the first dose and the second dose of vaccinated individuals in the population. The developed model is analyzed and the threshold quantity known as the control reproduction number [Formula: see text] is obtained. We investigate the equilibrium stability of the system, and the COVID-free equilibrium is said to be locally asymptotically stable when the control reproduction number is less than unity, and unstable otherwise. Using the least-squares method, the model is calibrated based on the cumulative number of COVID-19 reported cases and available information about the mass vaccine administration in Malaysia between the 24th of February 2021 and February 2022. Following the model fitting and estimation of the parameter values, a global sensitivity analysis was performed by using the Partial Rank Correlation Coefficient (PRCC) to determine the most influential parameters on the threshold quantities. The result shows that the effective transmission rate [Formula: see text], the rate of first vaccine dose [Formula: see text], the second dose vaccination rate [Formula: see text] and the recovery rate due to the second dose of vaccination [Formula: see text] are the most influential of all the model parameters. We further investigate the impact of these parameters by performing a numerical simulation on the developed COVID-19 model. The result of the study shows that adhering to the preventive measures has a huge impact on reducing the spread of the disease in the population. Particularly, an increase in both the first and second dose vaccination rates reduces the number of infected individuals, thus reducing the disease burden in the population.
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http://dx.doi.org/10.1007/s10441-023-09460-y | DOI Listing |
Sci Rep
January 2025
University of São Paulo, ICMC, São Carlos, 13566-590, Brazil.
Identifying driver genes is crucial for understanding oncogenesis and developing targeted cancer therapies. Driver discovery methods using protein or pathway networks rely on traditional network science measures, focusing on nodes, edges, or community metrics. These methods can overlook the high-dimensional interactions that cancer genes have within cancer networks.
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January 2025
Department of Applied Physics and Chemical Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo, 184-8588, Japan.
We report the synthesis, crystal structure, and magnetic properties of a new Kitaev honeycomb cobaltate, KCoAsO, which crystallizes in two distinct forms: P2/c and R[Formula: see text] space groups. Magnetic measurements reveal ordering temperatures of ~ 14 K for the P2/c structure and ~ 10.5 K for the R[Formula: see text] structure.
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January 2025
School of Computer Science and AI, SR University, Warangal, Telangana, India.
One of the most fatal diseases that affect people is skin cancer. Because nevus and melanoma lesions are so similar and there is a high likelihood of false negative diagnoses challenges in hospitals. The aim of this paper is to propose and develop a technique to classify type of skin cancer with high accuracy using minimal resources and lightweight federated transfer learning models.
View Article and Find Full Text PDFProc Biol Sci
January 2025
School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA.
In animals, metabolic rates during ontogeny often scale differently from the way they do in cross-species or population comparisons, with near-isometric scaling patterns more often observed during juvenile growth. In multiple social insect taxa, colony metabolic rate scales hypometrically across species or populations at the same developmental stage, but metabolic patterns during ontogeny have not been examined for any social insect species. We performed the first ontogenetic study of social metabolic scaling in harvester ant colonies () over 3.
View Article and Find Full Text PDFJ R Soc Interface
January 2025
Structure and Motion Laboratory, The Royal Veterinary College, North Mymms, Hatfield AL9 7TA, UK.
Swimming and flying animals produce thrust with oscillating fins, flukes or wings. The relationship between frequency , amplitude and forward velocity can be described with a Strouhal number , where = 2/, where animals are observed to cruise with [Formula: see text]-0.4.
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