Browsing by Author "Ndlovu, Meshach"

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    Exploring the impact of how criminals interact with cyber-networks—a mathematical modeling approach
    (Taylor & Francis, 2024-01-11) Chikore, Tichaona; Nyirenda-Kayuni, Mwawi; Chukwudum, Queensley C.; Chazuka, Zviiteyi; Mwaonanji, John; Ndlovu, Meshach; Zhangazha, Moster; Mhlabane, Fezile; Osman, Shaibu; Nyabadza, Farai; White, K. A. Jane; Shang, Yilun
    There is a growing interest in using mathematical models to understand crime dynamics, crime pre-vention, and detection. The past decade has experienced a relative reduction in conventional crimes, but this has been replaced by significant increases in cybercrime. In this paper, we use deterministic modelling to describe the spread of cybercrime across a cyber-network by describing the hetero-geneity of interactions between individuals using a nonlinear interaction between individuals in the network, and we allow criminals to operate either internally or externally to the cyber-network. We are able to determine the impact of the location of the criminal relative to the cyber-network which is being attacked. The model structure incorporates key elements of a social network structure thereby allowing for limited rates of victimisation. Both model structure and our observations are novel and provide a new contribution to the theoretical discussion of cybercrime dynamics, offering potential avenues to consider control strategies. Using steady-state analysis and extensive numerical simu-lations, we find that the location of criminals relative to the network does not impact the system qualitatively, although there are quantitative differences. Cyber-networks that are more clustered are likely to experience greater levels of cybercrime, but there is also a saturation effect that limits the level of victimisation as the number of criminals attempting to undertake crimes on given network increases. We discuss model limitations and describe how the model might be used with datasets to translate the theoretical findings into a useful tool in the fight to detect and eradicate cybercrime activity.
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    Modeling COVID-19 infection in high-risk settings and low-risk settings
    (Elsevier, Science Direct, 2022-11-02) Ndlovu, Meshach; Mpofu, Mqhelewenkosi A.; Moyo, Rodwell G.
    In this research paper we present a mathematical model for COVID-19 in high-risk settings and low-risk settings which might be infection dynamics between hotspots and less risky communities. The main idea was to couple the SIR model with alternating risk levels from the two different settings high and low-risk settings. Therefore, building from this model we partition the infected class into two categories, the symptomatic and the asymptomatic. Using this approach we simulated COVID-19 dynamics in low and high-risk settings with auto-switching risk settings. Again, the model was analyzed using both analytic methods and numerical methods. The results of this study suggest that switching risk levels in different settings plays a pivotal role in COVID-19 progression dynamics. Hence, population reaction time to adhere to preventative measures and interventions ought to be implemented with flash speed targeting first the high-risk setting while containing the dynamics in low-risk settings.
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    Modelling COVID-19 infection with seasonality in Zimbabwe
    (Elsevier, Science Direct, 2022-05-25) Ndlovu, Meshach; Moyo, Rodwell; Mpofu, Mqhelewenkosi
    This paper presents evidence and the existence of seasonality in current existing COVID-19 datasets for three different countries namely Zimbabwe, South Africa, and Botswana. Therefore, we modified the SVIR model through factoring in the seasonality effect by incorporating moving averages and signal processing techniques to the disease transmission rate. The simulation results strongly established the existence of seasonality in COVID-19 dynamics with a correlation of 0.746 between models with seasonality effect at 0.001 significance level. Finally, the model was used to predict the magnitude and occurrence of the fourth wave.
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    Nutrition and work efficiency as a strategic variable necessary in a mining environment for high productivity: A case of Filabusi mining community
    (Qeios, 2023-06-09) Ndlovu, Meshach; Zulu, Eldon
    Work has a central role in the lives of big share of mine employees and meals they eat during the workday comprise an important factor in their nutrition, health, and wellbeing. The objective of this study was to examine the contribution of agricultural dimension, vegetable markets enhancing nutrition and work efficiency as a strategic necessity in a mining environment for high productivity during the COVID 19 pandemic. The study employed a Quasi –experiment quantitative research paradigm and a questionnaire was distributed to the mentioned population. Also of note, are the socio-demographic, socio- economic and work-related factors to the eating patterns of 150 mine employees from 6 different mines around Filabusi community during the working day and how their eating patterns influence dietary intake and productivity? The study revealed that, all the variables in the pre-test analysis indicated no significant difference in each of the listed variables between the two groups then the evidence in the post-test analysis point out that the two variables with a significant difference between the two group is strongly as a result of the treatment (eating habits, nutrition and diet) during this COVID-19 pandemic that has led to better emotional strength and improved productivity at work place.