https://hdl.handle.net/13049/9 Tue, 01 Sep 2026 07:00:09 GMT 2026-09-01T07:00:09Z https://hdl.handle.net/13049/822 Determinants of participation in charcoal production and its distributive impact on household welfare in rural Ethiopia Belay, Biruk; Guta, Dawit; Senbeta, Feyera Charcoal production is one of the main sources of households’ income in some part of rural Ethiopia. However, existing literature has rarely explored the presence of an entry barrier that might prevent the poorest from participating in this lucrative activity nor have they accounted for heterogeneity in the welfare effects of participation. To provide evidence for these issues, this study assesses the determinants of participation in charcoal production and its heterogeneous impact on household welfare using primary data from 390 households in selected rural villages of Awi zone, Ethiopia. This study uses a probit regression model to identify the determinants of participation and the quantile treatment effect (QTE) regression model to examine the welfare gap between participants and nonparticipants at different points of the welfare distribution and a decomposition technique to investigate whether the welfare gap is attributed to differences in characteristics or returns to these characteristics. Our probit model estimation result shows that poor households are less likely to participate in charcoal production, implying the existence of an entry barrier which may be attributed to the requirement of higher capital investment in the study area. Our QTE result suggests that participation affect welfare heterogeneously across the welfare distribution and the welfare gap is higher at the upper quantiles, suggesting that poor participants gain lower return from participation. Finally, our decomposition analysis reveals that the welfare gap exists due to coefficients effect. Although the results suggest the importance of policy to improve the participation of households in charcoal production for greater welfare, they also indicate the existence of uneven returns against poor participants. Journal article Thu, 24 Oct 2024 00:00:00 GMT https://hdl.handle.net/13049/822 2024-10-24T00:00:00Z https://hdl.handle.net/13049/819 Modeling the Effect of HIV/AIDS Stigma on HIV Infection Dynamics in Kenya Levy, Ben; Correia, Hannah E.; Chirove, Faraimunashe; Ronoh, Marilyn; Abebe, Ash; Kgosimore, Moatlhodi; Chimbola, Obias; Machingauta, M. Hellen; Lenhart, Suzanne; White, K. A. Jane Stigma toward people living with HIV/AIDS (PLWHA) has impeded the response to the disease across the world. Widespread stigma leads to poor adherence of preventative measures while also causing PLWHA to avoid testing and care, delaying important treatment. Stigma is clearly a hugely complex construct. However, it can be broken down into components which include internalized stigma (how people with the trait feel about themselves) and enacted stigma (how a community reacts to an individual with the trait). Levels of HIV/AIDS-related stigma are particularly high in sub-Saharan Africa, which contributed to a surge in cases in Kenya during the late twentieth century. Since the early twenty-first century, the United Nations and governments around the world have worked to eliminate stigma from society and resulting public health education campaigns have improved the perception of PLWHA over time, but HIV/AIDS remains a significant problem, particularly in Kenya. We take a data-driven approach to create a time-dependent stigma function that captures both the level of internalized and enacted stigma in the population. We embed this within a compartmental model for HIV dynamics. Since 2000, the population in Kenya has been growing almost exponentially and so we rescale our model system to create a coupled system for HIV prevalence and fraction of individuals that are infected that seek treatment. This allows us to estimate model parameters from published data. We use the model to explore a range of scenarios in which either internalized or enacted stigma levels vary from those predicted by the data. This analysis allows us to understand the potential impact of different public health interventions on key HIV metrics such as prevalence and disease-related death and to see how close Kenya will get to achieving UN goals for these HIV and stigma metrics by 2030. Research article Fri, 01 Jan 2021 00:00:00 GMT https://hdl.handle.net/13049/819 2021-01-01T00:00:00Z https://hdl.handle.net/13049/818 Mathematical models for the dynamics of alcohol related health risks with changing behavior via cultural beliefs in tanzania Mayengo, Maranya M.; Kgosimore, Moatlhodi; Chakraverty, Snehashish; Seshaiyer, Padmanabhan; Caiseda, Carmen; Shirima, Gabriel Alcoholism has continually posed health challenges in many communities for decades. In this paper, a more realistic model for health related risks associated with alcoholism is formulated. It considers a population proportion that has social cultural protection from alcohol consumption. In the context of this paper, such protection emanates from religious beliefs. The Next Generation Matrix (NGM) approach is used to compute the basic risk reproduction number. The risk free equilibrium point is proved to be globally asymptotically stable whenever the basic risk reproduction is less than unity and unstable otherwise. The sensitivity analysis of the basic risk reproduction number and numerical simulation results reveal that for effective control of the health risk problem in the community, the deliberate intervention strategies and policies should focus on discouraging alcoholic behaviors on its onset during initiation stage than focusing other population proportions already at risk. Journal article Wed, 01 Jan 2020 00:00:00 GMT https://hdl.handle.net/13049/818 2020-01-01T00:00:00Z https://hdl.handle.net/13049/816 Modeling and evaluating targeted interventions to curb avian influenza spread among humans and domestic birds Serapia, Soka; Moatlhodi, Kgosimore; Maranya, Mayengo Avian influenza, caused by influenza A viruses, has drawn substantial attention globally due to increased deaths from time to time. This study examines control interventions for avian influenza transmission in humans and domestic birds using a deterministic mathematical model. The model incorporates three time-dependent interventions: vaccinating susceptible birds, maintaining proper hygiene practice, and culling infected birds. The next-generation matrix method is used to determine the effective reproduction number. Optimal control theory is applied by incorporating: vaccination, proper human hygiene practices, and culling of infected birds. To determine the necessary conditions for the existence of optimal controls, the Pontryagin’s Maximum Principle is employed. The optimal control problem is then solved using the forward-backward sweep method based on the fourth-order Runge-Kutta algorithm, implemented in MATLAB. Results from the optimal control analysis show that the strategy combining all interventions is the most effective approach for controlling the disease. Furthermore, the Incremental Cost-Effectiveness Ratio (ICER) is used to identify the most cost-effective strategy for disease control. The findings show that Strategy VII has a negative ICER, indicating that it is less costly and averts more infections. Therefore, to eliminate the disease, we recommend the implementation of all the aforementioned control measures. Journal article Thu, 01 Jan 2026 00:00:00 GMT https://hdl.handle.net/13049/816 2026-01-01T00:00:00Z