Application of Logistic Regression Models for the Evaluation of Cholera Outbreak in Adamawa State Nigeria (Published)
Cholera outbreak occurred in four local government area of Adamawa state namely; Yola north, Yola south, Girei and Song between 11th may 2019 to 26th august 2019. WHO teams recorded 687 cholera patient whom received treatment at their various CTC with only 4 death as of the period of the outbreak. I explore cases of the disease outbreak, analyzed and estimate the parameters (demographic status and exploratory data) associated to the treatment outcome of the patients, identify the spread rate and targeted risk level using binary logistics regression. Our analysis has indicated that Yola North is the most affected area, majority of the patients are female and most of the respondent are children within the age group 1-14 years. The results depict that none of the demographic status was significantly associated with the mortality, similarly no significant association was observed for Culture status, Lab. Sample and Hospitalize status of the patients with mortality. However, the results of the association test between RDT status and mortality show that 2(0.3% of the total) who were RDT positive, were significantly associated with mortality. The binary logistic regression model estimations show that RDT, Culture, hospitalize status and LGA of the patients are the significant relationships at 10%, 10%, 5% and 10% levels respectively that determine the responses of patients to cholera treatment. Therefore, the findings depict that 99.4% of the patients “Alive” and 0.6% were “Dead”, this implies that the cholera treatment is very effective during the outbreak. Subsequently, it was deduced that the forecasting performance of the findings on both probit and logit regression model estimation from our analysis conform with the binary regression result.
SOCIO-ECONOMIC DETERMINANTS OF ERITREA’S SAVINGS AND MICRO CREDIT PROGRAM LOAN REPAYMENT PERFORMANCE: A CASE OF THE DEKEMHARE SUZ-ZONE (Published)
The Savings and Micro Credit Program of Eritrea was established to provide financial services to the poor and lower income individuals to enhance their business activities and alleviate poverty level. The study analyzed the socio-economic factors that affect the institution’s loan repayment performance and a sample of 140 beneficiaries was fixed from the Dekemhare Sub-Zone using the Stratified Sampling technique. A structured questionnaire was used to collect the primary data and descriptive statistics and the probit model were employed to analyze the data. Results of the regression analysis revealed that the level of education, loan amount and loan category have insignificant effect on the probability of the SMCP loan repayment. On the other hand age, gender, type of business and credit experience are significant determinants where age and type of business have negative relationship and gender and credit experience have positive relationship with the loan repayment probability
Factors Influencing Participation in Rice Development Projects: The Case of Smallholder Rice Farmers in Northern Ghana (Published)
Participation in rice development project is an important platform for joint learning and technology transfer. The present study quantifies the factors influencing participation in rice development projects among smallholder rice farmers in Northern Ghana. A total of 400 rice farmers selected through multi-stage sampling technique were interviewed. The result shows a significant variation in the demographic and institutional characteristics among the farmers by participation in rice development projects. Participation in rice development projects in Northern Ghana is influenced by age of the household head, marital status, access to off-farm income, market price of rice, knowledge of rice varieties and access to credit and the interactive term education and farm size. The packaging of agricultural technologies by research institutions and agricultural development organizations should focus on making them more receptive to farmers through effective training and demonstrations in order to boost participation, adoption, production and farmers income.