Browsing by Author "Mirau, Silas"

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A two-patch model to quantify uncertainties in the transmission of brucellosis between domestic animals
(Elsevier, 2025-09) Msuya, Rehema; Mirau, Silas; Nyerere, Nkuba; Mbalawata, Isambi
Brucellosis, a neglected zoonotic disease, poses significant health risks to both humans and livestock. This study investigates a key factor influencing brucellosis transmission: the movement of animals in and out of communal grazing areas. We develop a Continuous Time Markov Chain (CTMC) stochastic model, building on its deterministic counterpart, to assess the impact of short-term animal movements on disease transmission dynamics. By incorporating stochasticity, the model captures the inherent variability in disease transmission and animal movements, providing deeper insights than traditional deterministic models. A multitype branching process is employed to evaluate the probabilities of disease extinction. We compute the basic reproduction number and the stochastic threshold . Numerical simulations indicate that brucellosis transmission accelerates when domestic animals spend more time in high-risk communal grazing areas. Additionally, the results suggest a high probability of disease extinction when animals moves out of high-risk area. Conversely, when animals from both patches increase their time in high-risk zones, the likelihood of disease extinction diminishes. This study underscores the importance of implementing strategic movement controls and targeted interventions in high-risk areas to mitigate outbreaks and enhance disease management.
Assessing the role of community involvement and capacity building in larviciding applications for malaria control in Africa: A scoping review
(Elsevier, 2025-08-14) Shirima, GloriaSalome; Masserey, Thiery; Gervas, Hamenyimana; Chitnis, Nakul; Kiware, Samson; Mirau, Silas
Larviciding offers a supplementary approach in malaria vector control, particularly when applied through community engagement and capacity building. A scoping review was performed to evaluate existing larviciding delivery mechanisms and their impacts on African malaria control. A scoping review was conducted following the PRISMA-ScR guidelines. The search strategy utilized Medical Subject Headings (MeSH) and free-text terms related to “malaria”, “larvicide”, “community engagement” and “mosquito control”. The databases PubMed, Scopus, and Embase were searched for relevant literature published until December 2024. Inclusion criteria focused on studies addressing community engagement in delivering larviciding within African settings. After applying inclusion and exclusion criteria, 32 papers were ultimately included in the analysis. The studies spanned 13 African countries, primarily in sub-Saharan regions, with findings indicating that larviciding significantly reduced mosquito density and, in some cases, malaria incidence. Community engagement strategies varied, with workshops and participatory meetings targeting various stakeholders to enhance awareness and ownership of larviciding programmes. Community engagement and capacity building were critical to success- fully implementing larviciding programmes. While challenges, such as logistical barriers, lack of awareness, and financial constraints, persist, integrating technological innovations and strengthening monitoring systems can enhance the sustainability of these efforts.
Bayesian prediction of under-five mortality rates for Tanzania
(Elsevier Inc., 2025-01-26) Mwanga, Mohamed; Mirau, Silas; Tchuenche, Jean; Mbalawata, Isambi
Under-five mortality is a burden on health and economic systems in developing countries. This study used under-five mortality rate (U5MR) data for Tanzania from 1960 to 2020 to predict trends of under-five mortality over the period of 2021 to 2051. Using a Bayesian state space model, it is found that the model is stable in forecasting. Results show that under-five mortality will continue to decline from 48.9 in 2020 to 32.9 in 2030, a decrease of 32.7%. But despite this decrease, Tanzania will likely not meet the Sustainable Development Goal (SDG) for under-five mortality by 2030. Additional efforts by the government through evidence-based interventions should be undertaken to improve child survival by expanding access to health care, especially in rural areas, taking into account local context.
Conservation of forest biomass and forest–dependent wildlife population: Uncertainty quantification of the model parameters
(Elsevier, 2023) Fanuel, Ibrahim; Mirau, Silas; Kajunguri, Damian; Moyo, Francis
The ecosystem is confronted with numerous challenges as a consequence of the escalating human population and its corresponding activities. Among these challenges lies the degradation of forest biomass, which directly contributes to a reduction in forested areas and poses a significant threat to the survival of wildlife species through the intensification of intraspecific competition. In this paper, a non–linear mathematical model to study the conservation of forest and wildlife species that are reliant on forest ecosystem within the framework of human population dynamics and its related activities is developed and analysed. The study assessed the impacts of economic measures in the form of incentives on reducing population pressure on forest resources as well as the potential benefits of technological efforts to accelerate the rate of reforestation. Qualitative and quantitative analyses reveals that economic and technological factors have the potential to contribute to resource conservation efforts. However, these efforts can only be used to a limited extent, and contrary to that, the system will be destabilised. Sensitivity analysis identified the parameters pertaining to human population, human activities, economic measures, and technological efforts as the most influential factors in the model
Conservation of forest biomass and forest–dependent wildlife population: Uncertainty quantification of the model parameters
(Elsevier, 2023-06) Fanuel, Ibrahim; Mirau, Silas; Kajunguri, Damian; Moyo, Francis
The ecosystem is confronted with numerous challenges as a consequence of the escalating human population and its corresponding activities. Among these challenges lies the degradation of forest biomass, which directly contributes to a reduction in forested areas and poses a significant threat to the survival of wildlife species through the intensification of intraspecific competition. In this paper, a non–linear mathematical model to study the conservation of forest and wildlife species that are reliant on forest ecosystem within the framework of human population dynamics and its related activities is developed and analysed. The study assessed the impacts of economic measures in the form of incentives on reducing population pressure on forest resources as well as the potential benefits of technological efforts to accelerate the rate of reforestation. Qualitative and quantitative analyses reveals that economic and technological factors have the potential to contribute to resource conservation efforts. However, these efforts can only be used to a limited extent, and contrary to that, the system will be destabilised. Sensitivity analysis identified the parameters pertaining to human population, human activities, economic measures, and technological efforts as the most influential factors in the model
Design of a Passenger Security and Safety System for the Kayoola EVs Bus
(IEEE, 2021-10-25) Koojo, Ivan; Machuve, Dina; Mirau, Silas; Miyingo, Simon
Kiira Motors Corporation seeks to avail customer satisfaction, by providing noteworthy passenger experience on its market entry product, the Kayoola EVs bus through deploying a passenger security and safety system to curtail rampant snags like passenger insecurity, loss of passenger property, shortcomings in management and accountability as well as the spread of contagious sicknesses like COVID-19 which are not alien occurrences on commuter taxis and buses in African cities. On this project, a comprehensive system was designed for remote CCTV video surveillance, video analysis for people detection, passenger count and social distance analysis, as well as digital contact tracing to solve the challenges. It denotes significant potential to improve the security of property and passengers, shrink the risk of the spread of contagious diseases, enable timely capture of contact tracing records and lessen the burden of management, monitoring and accountability for the numbers of passengers on buses for fleet owners.
A Deterministic Mathematical Model for the Control of Spread of Prosopis Juliflora Plants
(Journal of Mathematics and Informatics, 2020-09-25) Simon, Joel; Mirau, Silas; Luboobi, Livingstone
Prosopis juliflora plants are the most aggressive invasive species in the world. They spread by animal movement crossing from one place land to another. In this paper a deterministic model to examine the dynamics of Prosopis julifrola plants is formulated and presented by adopting a similar approach of a dynamical system as used in epidemiological modeling. The local and global stability analyses of the equilibrium points of the model performed by using next-generation for the basic reproduction number R0 computation and Lypunov function method. The finding from the study showed that the Prosopis free equilibrium of the model is both locally and globally asymptotically stable if and only if the number of secondary infections, is less than unit, that is R0 < 1. Furthermore, the study showed that there exist Prosopis endemic equilibrium for the spread when 0 R >1. The numerical simulation implemented in MATLAB ODE45 algorithm for solving linear ordinary differential equations. The study findings showed that as the number of ingested animals increase, the plant spread increases on land. Based on the findings, the study recommend the application of the model on endemic areas to improve through: Awareness on animal feeding the plant, provision of insight on plant invasion to policy makers and environmental stakeholders to include in environment framework, seminars and environment clubs by visiting community groups an educating them on plant invasion, through this the plant eradication could be achieved.
Frequentist and Bayesian Approaches in Modeling and Prediction of Extreme Rainfall Series: A Case Study from Southern Highlands Region of Tanzania
(Hindawi, 2024-01-30) Kyojo, Erick; Mirau, Silas; Osima, Sarah; Masanja, Verdiana
This study focuses on modeling and predicting extreme rainfall based on data from the Southern Highlands region, the critical for rain-fed agriculture in Tanzania. Analyzing 31 years of annual maximum rainfall data spanning from 1990 to 2020, the Gen- eralized Extreme Value (GEV) model proved to be the best for modeling extreme rainfall in all stations. Tree estimation methods–L-moments, maximum likelihood estimation (MLE), and Bayesian Markov chain Monte Carlo (MCMC)–were employed to estimate GEV parameters and future return levels. Te Bayesian MCMC approach demonstrated superior per- formance by incorporating noninformative priors to ensure that the prior information had minimal infuence on the analysis, allowing the observed data to play a dominant role in shaping the posterior distribution. Furthermore, return levels for various future periods were estimated, providing guidance for food protection measures and infrastructure design. Trend analysis using p value, Kendall’s tau, and Sen’s slope indicated no statistically signifcant trends in rainfall patterns, although a weak positive trend in extreme rainfall events was observed, suggesting a gradual and modest increase over time. Overall, the study contributes valuable insights into extreme rainfall patterns and underscores the importance of L-moments in identifying the best ft dis- tribution and Bayesian MCMC methodology for accurate parameter estimation and prediction, enabling effective measures and infrastructure planning in the region.
Fuzzy modelling on the depletion of forest biomass and forest-dependent wildlife population
(Elsevier, 2023-09) Fanuel, Ibrahim; Mirau, Silas; Mayengo, Maranya; Moyo, Francis
This paper presents a system of non-linear differential equations describing the depletion of forest biomass and forest-dependent wildlife population caused by human population and its associated activities. The model incorporates the imprecise nature of the parameters, which are treated as triangular fuzzy numbers to reflect the inherent uncertainty. We utilised cut to transform these imprecise parameters into intervals. Subsequently, employing the principles of interval mathematics, we effectively converted the related differential equation into a pair of distinct differential equations. By leveraging the signed distance of the fuzzy numbers, we further simplified the equations, resulting in a single differential equation, which led to the formulation of a defuzzified model. The existence of equilibrium points with their stability behaviour is presented. Furthermore, the existence of trans-critical bifurcation is analysed. Through numerical simulations, we observe significant differences between the solutions of system in crisp and fuzzy environments. These findings highlight the importance of using fuzzy models to accurately represent the dynamics of complex natural systems. Consequently, we conclude that fuzzy models provide a trustworthy representation of the dynamics of complex natural systems.
Fuzzy modelling on the depletion of forest biomass and forest-dependent wildlife population
(Elsevier, 2023-09-01) Fanuel, Ibrahim; Mirau, Silas; Mayengo, Maranya; Moyo, Francis
This paper presents a system of non-linear differential equations describing the depletion of forest biomass and forest-dependent wildlife population caused by human population and its associated activities. The model incorporates the imprecise nature of the parameters, which are treated as triangular fuzzy numbers to reflect the inherent uncertainty. We utilised cut to transform these imprecise parameters into intervals. Subsequently, employing the principles of interval mathematics, we effectively converted the related differential equation into a pair of distinct differential equations. By leveraging the signed distance of the fuzzy numbers, we further simplified the equations, resulting in a single differential equation, which led to the formulation of a defuzzified model. The existence of equilibrium points with their stability behaviour is presented. Furthermore, the existence of trans-critical bifurcation is analysed. Through numerical simulations, we observe significant differences between the solutions of system in crisp and fuzzy environments. These findings highlight the importance of using fuzzy models to accurately represent the dynamics of complex natural systems. Consequently, we conclude that fuzzy models provide a trustworthy representation of the dynamics of complex natural systems.
Human-Wildlife Conflict Early Warning System Using the Internet of Things and Short Message Service
(Engineering, Technology and Applied Science Research, 2022-04) Ronoh, E.; Mirau, Silas; Dida, Mussa
Human-wildlife conflict (HWC) is an important challenge to communities living in areas bordering wildlife game parks and reserves. It is more evident in the United Republic of Tanzania, whose economy depends on wildlife tourism. This paper proposes a low-cost and low-power early warning system using the Internet of Things (IoT) and Short Message Service (SMS) to support HWC respond teams in mitigating these challenges. The system comprises three primary units: sensing, processing, and alerting. The sensing unit consists of a Passive Infrared (PIR) sensor, a Global Positioning System (GPS), and a Raspberry Pi camera. The PIR sensor detects the proximity of the animal using the heat signature, GPS senses and records the current location, while the Raspberry Pi camera has the primary purpose of taking a picture after the PIR sensor detects the proximity of the animal. The processing unit with a Raspberry microcomputer performs data processing and image inferencing using the You Only Look Once (YOLO) algorithm. Last is the alerting unit, which includes a Global System for Mobile (GSM) communications module for sending SMS messages to the human-wildlife conflict response team and the nearer community response team leader whenever wild animals are spotted near the park’s border. The system detects, identifies, and reports the detected wild animals. The GPRS provides internet connectivity to support data collection, storage, and monitoring in the cloud.
Mathematical Approach to Investigate Stress due to Control Measures to Curb COVID-19
(Hindawi, 2022-01-13) Paul, James; Mirau, Silas; Mbalawata, Isambi
COVID-19 is a world pandemic that has affected and continues to affect the social lives of people. Due to its social and economic impact, different countries imposed preventive measures that are aimed at reducing the transmission of the disease. Such control measures include physical distancing, quarantine, hand-washing, travel and boarder restrictions, lockdown, and the use of hand sanitizers. Quarantine, out of the aforementioned control measures, is considered to be more stressful for people to manage. When people are stressed, their body immunity becomes weak, which leads to multiplying of coronavirus within the body. Therefore, a mathematical model consisting of six compartments, Susceptible-Exposed-Quarantine-Infectious-Hospitalized-Recovered (SEQIHR) was developed, aimed at showing the impact of stress on the transmission of COVID-19 disease. From the model formulated, the positivity, bounded region, existence, uniqueness of the solution, the model existence of free and endemic equilibrium points, and local and global stability were theoretically proved. The basic reproduction number () was derived by using the next-generation matrix method, which shows that, when , the disease-free equilibrium is globally asymptotically stable whereas when the endemic equilibrium is globally asymptotically stable. Moreover, the Partial Rank Correlation Coefficient (PRCC) method was used to study the correlation between model parameters and . Numerically, the SEQIHR model was solved by using the Rung-Kutta fourth-order method, while the least square method was used for parameter identifiability. Furthermore, graphical presentation revealed that when the mental health of an individual is good, the body immunity becomes strong and hence minimizes the infection. Conclusively, the control parameters have a significant impact in reducing the transmission of COVID-19.
A Mathematical Model for Transmission of Taeniasis and Neurocysticercosis
(Hindawi, 2024-03-11) Rwabona, Gideon; Masanja, Verdiana; Mfinanga, Sayoki; Degoot, Abdoelnaser; Mirau, Silas
In this study, we present a mathematical model for the codynamics of taeniasis and neurocysticercosis and rigorously analyze it. To understand the underlying dynamics of the proposed model, basic system properties such as the positivity and boundedness of solutions are investigated through the completing differential process. The basic reproduction number was calculated using the next-generation matrix method, and the analysis showed that when R0 < 1, the disease in the community eventually dies out, and when R0 > 1, the diseases persist. Local stability of the equilibria was analyzed using the Jacobian matrix, and Lyapunov function techniques were used to determine the global analysis, which showed that the endemic equilibrium point was globally stable when R0 > 1. On the other hand, the disease-free equilibrium was determined to be globally stable when R0 < 1. To identify the most influential parameters of the proposed model, partial correlation coefficient techniques were used. The numerical results depict that the model aligns well with the transmission dynamics, which goes through two populations: humans and pigs, whereby the model system stabilizes after some time, showing the validity of the proposed model. Furthermore, the simulations of the proposed model revealed that the shedding habit of infected humans with taeniasis and the bad cooking habit or eating of raw or undercooked pork products have a higher impact on the spread of neurocysticercosis and taeniasis in the community. Hence, this study proposes that in order to control taeniasis and neurocysticercosis, effective disease control measures should primarily prioritize hygienic behaviour and proper cooking of pork meat to the required temperature.
Mathematical model to assess the impacts of aflatoxin contamination in crops, livestock and humans
(Elsevier, 2024-03-01) Mgandu, Filimon; Nyerere, Nkuba; Mbega, Ernest; Chirove, Faraimunashe; Mirau, Silas
Aflatoxin contamination poses a significant challenge in food safety and security as it affects both the health of consumers and supply chains. Due to the health impacts associated with aflatoxin contamination, countries have set standards and restrictions for importing food crops and animal feed, resulting in greater economic losses to farmers, transporters, and crop processors. This study aimed to develop a mathematical model that tracks the contamination status of crops, livestock and humans in supporting efforts to control aflatoxin. The analysis of the mathematical model shows that both aflatoxin contamination-free equilibrium (ACFE) and aflatoxin contamination-persistence equilibrium (ACPE) exist. To study the dynamics of contamination, we derived the basic aflatoxin contamination number, 𝑅0 which is analogous to the basic reproduction number in epidemiological models. When 𝑅0 < 1, the ACFE is globally asymptotically stable, whereas when 𝑅0 > 1 the ACPE is globally asymptotically stable. Partial Rank Correlation Coefficients (PRCCs) for global sensitivity analysis were calculated using Latin Hypercube Sampling (LHS) to see how sensitive and significant the parameter is on each variable. Results from numerical simulations showed that decreasing crop contamination and shading rates and increasing the death rate of aflatoxin fungi in soil by 50% can reduce the basic contamination number by above 92%. Thus, it is important to introduce control measures that target crop contamination, shading and death rates of aflatoxin fungi in soil to reduce contamination in the population. Compared to other studies in aflatoxin contamination, the current study provides a thoroughly global sensitivity analysis of parameters involved in contamination and indicated the most important ones for control strategies
Mathematical model to study the impact of anthropogenic activities on forest biomass and forest-dependent wildlife population
(Springer Berlin Heidelberg, 2023-07-21) Fanuel, Ibrahim; Mirau, Silas; Kajunguri, Damian; Moyo, Francis
This paper proposes and analyses a nonlinear mathematical model to study the impact of anthropogenic activities on forest biomass and forest-dependent wildlife populations using a system of differential equations. It is assumed that the growth of forest biomass, forest-dependent wildlife populations, and the human population follow logistic equations. The effect of forest biomass depletion on the survival of forest-dependent wildlife populations is investigated by introducing a function that denotes the dependence on forest biomass. The system’s behaviour near all ecologically acceptable equilibria is studied, and to confirm the analytical conclusions, a numerical simulation is performed. The model analysis shows that as forest biomass declines due to an increase in human population and its associated activities, the population of wildlife species also declines, and if no measures are taken, both forest biomass and the wildlife population may become extinct.
Mathematical model to study the impact of anthropogenic activities on forest biomass and forest-dependent wildlife population
(Springer Berlin Heidelberg, 2023-07-21) Fanuel, Ibrahim; Mirau, Silas; Kajunguri, Damian; Moyo, Francis
This paper proposes and analyses a nonlinear mathematical model to study the impact of anthropogenic activities on forest biomass and forest-dependent wildlife populations using a system of differential equations. It is assumed that the growth of forest biomass, forest-dependent wildlife populations, and the human population follow logistic equations. The effect of forest biomass depletion on the survival of forest-dependent wildlife populations is investigated by introducing a function that denotes the dependence on forest biomass. The system’s behaviour near all ecologically acceptable equilibria is studied, and to confirm the analytical conclusions, a numerical simulation is performed. The model analysis shows that as forest biomass declines due to an increase in human population and its associated activities, the population of wildlife species also declines, and if no measures are taken, both forest biomass and the wildlife population may become extinct.
Mathematical modeling of COVID-19 transmission dynamics between healthcare workers and community
(Elsevier, 2021-10) Masandawa, Lemjini; Mirau, Silas; Mbalawata, Isambi
Corona-virus disease 2019 (COVID-19) is an infectious disease that has affected different groups of humankind such as farmers, soldiers, drivers, educators, students, healthcare workers and many others. The transmission rate of the disease varies from one group to another depending on the contact rate. Healthcare workers are at a high risk of contracting the disease due to the high contact rate with patients. So far, there exists no mathematical model which combines both public control measures (as a parameter) and healthcare workers (as an independent compartment). Combining these two in a given mathematical model is very important because healthcare workers are protected through effective use of personal protective equipment, and control measures help to minimize the spread of COVID-19 in the community. This paper presents a mathematical model named SWE 𝐼𝑠 𝐼𝑎HR; susceptible individuals (S), healthcare workers (W), exposed (E), symptomatic infectious (𝐼𝑠 ), asymptomatic infectious (𝐼𝑎 ), hospitalized (H), recovered (R). The value of basic reproduction number 𝑅0 for all parameters in this study is 2.8540. In the absence of personal protective equipment 𝜉 and control measure in the public 𝜃, the value of 𝑅0 ≈ 4.6047 which implies the presence of the disease. When 𝜃 and 𝜉 were introduced in the model, basic reproduction number is reduced to 0.4606, indicating the absence of disease in the community. Numerical solutions are simulated by using Runge–Kutta fourth-order method. Sensitivity analysis is performed to presents the most significant parameter. Furthermore, identifiability of model parameters is done using the least square method. The results indicated that protection of healthcare workers can be achieved through effective use of personal protective equipment by healthcare workers and minimization of transmission of COVID-19 in the general public by the implementation of control measures. Generally, this paper emphasizes the importance of using protective measures.
Mathematical modeling of vaccination as a control measure of stress to fight COVID-19 infections
(Elsevier, 2023-01) Paul, James; Mbalawata, Isambi; Mirau, Silas; Masandawa, Lemjini
The world experienced the life-threatening COVID-19 disease worldwide since its inversion. The whole world experienced difficult moments during the COVID-19 period, whereby most individual lives were affected by the disease socially and economically. The disease caused millions of illnesses and hundreds of thousands of deaths worldwide. To fight and control the COVID-19 disease intensity, mathematical modeling was an essential tool used to determine the potentiality and seriousness of the disease. Due to the effects of the COVID-19 disease, scientists observed that vaccination was the main option to fight against the disease for the betterment of human lives and the world economy. Unvaccinated individuals are more stressed with the disease, hence their body’s immune system are affected by the disease. In this study, the 𝑆𝑉 𝐸𝐼𝐻𝑅 deterministic model of COVID- 19 with six compartments was proposed and analyzed. Analytically, the next-generation matrix method was used to determine the basic reproduction number (𝑅0). Detailed stability analysis of the no-disease equilibrium (𝐸0) of the proposed model to observe the dynamics of the system was carried out and the results showed that 𝐸0 is stable if 𝑅0 < 1 and unstable when 𝑅0 > 1. The Bayesian Markov Chain Monte Carlo (MCMC) method for the parameter identifiability was discussed. Moreover, the sensitivity analysis of 𝑅0 showed that vaccination was an essential method to control the disease. With the presence of a vaccine in our 𝑆𝑉 𝐸𝐼𝐻𝑅 model, the results showed that 𝑅0 = 0.208, which means COVID-19 is fading out of the community and hence minimizes the transmission. Moreover, in the absence of a vaccine in our model, 𝑅0 = 1.7214, which means the disease is in the community and spread very fast. The numerical simulations demonstrated the importance of the proposed model because the numerical results agree with the sensitivity results of the system. The numerical simulations also focused on preventing the disease to spread in the community
Mathematical Modelling and Analysis of Corruption Dynamics with Control Measures in Tanzania
(Journal of Mathematics and Informatics, 2020-09-11) Danford, Oscar; Kimathi, Mark; Mirau, Silas
Corruption is a worldwide problem that affects many countries where by individuals loses their rights, lower community confidence in public authorities, absence of peace and security, misallocation of resources and termination of employment. Despite various measures which have been taken by various countries to control corruption, the problem still exists. In this paper, we formulate and analyze a mathematical model for the dynamics of corruption in the presence of control measures. Analysis of the model shows that both Corruption Free Equilibrium (CFE) and Corruption Endemic Equilibrium (CEE) exist. The next generation matrix method was used to compute the effective reproduction number ( ) which is used to study the corruption dynamics. The results indicate that CFE is both locally and globally asymptotically stable when < 1 whereas CEE is globally asymptotically stable when > 1. The normalized forward sensitivity method was used to describe the most sensitive parameters for the spread of corruption. The most positive sensitive parameters are κ and ν while the most negative sensitive parameters are α and β . Therefore, the parameters of mass education α and religious teaching β are the best parameters for control of corruption. The model was simulated using Runge-Kutta fourth order method in MATLAB and the results indicate that the combination of mass education and religious teaching is effective to corruption control within short time compared to when each control strategy is used separately. Therefore, this study recommends that more efforts in providing both mass education and religious teaching should be applied at the same time to control corruption.
Mathematical models for aflatoxin contamination in crops, livestock and humans: A review
(SCIK Publishing Corporation, 2022-11-07) Mgandu, Filimon; Ngailo, Triphonia; Mugume, Isaac; Mbalawata, Isambi; Mirau, Silas
Aflatoxin is among the highest-threatening food contaminants as it affects both the health of consumers and the entire value chain. Researchers are of the view that aflatoxin contamination will increase due to the impacts of climate change. This study aimed to review studies on modelling the impacts of climate change on aflatoxin contamination to gain a deeper understanding of the progress achieved, methodologies used and potential gaps or opportunities for further studies. A critical analysis of the available literature revealed that aflatoxin contamination is a spatial-temporal phenomenon as it depends on both location and time. In many regions, data unavailability has been an obstacle in developing predictive models. We note that it is necessary for each region to have their own models according to the crop, soil characteristics and projected climate of the given area for better and more accurate results. Future studies should focus on the first; surveillance of susceptible crops and gathering of aflatoxin contamination data. Second, developing models to assess the aflatoxin contamination risk due to projected climate change, soil properties, and crop characteristics so that proper strategies can be adopted. Third, laboratory experimental results must be validated in fields to increase their usability.