Browsing by Author "Twumasi, C."
Now showing 1 - 3 of 3
Results Per Page
Sort Options
Item Assessing the Use of Long Lasting Insecticide Treated Nets among Pregnant Women in Ga East Municipality of the Greater Accra Region(University of Ghana, 2015-07) Twumasi, C.; Adongo, P. B.; University of Ghana, College of Health Sciences, School of Public HealthBackground: Malaria is a disease which is caused by the plasmodium parasites in the blood or tissues of humans. In 2012, government of Ghana distributed bednets to pregnant women in order to reduce the transmission of malaria. Though there was a massive distribution all over the country, the consistent use of the LLIN is low. Thus this study was done to find out the use of LLIN among pregnant women in the Ga- East Municipality and find out the factors that influence the use of the bednets in the municipality. Methods: The study used a cross-sectional quantitative method. The data was collected using structured questionnaires. A simple random sampling method was used in the selection of 206 participants for the study. SPSS and Microsoft Excel were used to analyze the data. Results: The pregnant women 97.1% (200) in the Municipality had knowledge about transmission of malaria. More than half of them 53.9% (111) had very good knowledge about LLIN use and that was significant. Some of the participants 61.7% (127) had misconceptions about the use of LLIN. Despite their high level of knowledge about malaria transmission and use of LLIN, the level of usage of LLIN among the pregnant in the two sub-municipalities (Abokobi and Haatso) in the Ga East Municipality was low 43.2%. Usage of LLIN here means that, the pregnant women who slept under the LLIN the night before the day of data collection for the study. The use of LLIN was related to educational level, occupation and marital status though not statistically significantItem Markov Chain Modeling Of HIV, Tuberculosis and Hepatitis-B Transmission: A Study of a Regional Hospital in Ghana.(University of Ghana, 2018-07) Twumasi, C.This study demonstrated the application of Markov S-I-R model and other statistical methods in exploring HIV, Tuberculosis (TB) and Hepatitis B (HB)disease outcomes using Ghanaian data. Secondary datasets from cohort studies were collected from records from the Ashanti Regional Hospital. Relevant disease metrics as well as transition probabilities were generalized for each disease. Method of Competing risks was used to further estimate the crude, partial crude and net probabilities of death across age groups; whereas, the conditional relationship among the three diseases was also established using Bayesian networks. In addition, some significant demographic characteristics of individuals on the prevalence of these diseases were determined using Classification tree. The Markov Chain S-I-R model revealed that Hepatitis B (HB) was more infectious over time than Tuberculosis (TB) and HIV within the study population; although the probability of first infection of these diseases were relatively low. However, individuals infected with HIV comparatively had lower life expectancies than those infected with TB and HB. The Competing risk method revealed that individuals between the ages of 20 and 50 years had a greater chance of dying from these diseases on the average. In addition, TB was found to be very prevalent among HIV infected individuals as opposed to Hepatitis B from the fitted Bayesian network. It was deduced from the Classification tree that females within the study population were likely to contract HIV as opposed to males; whereas, males were rather prone to contracting TB. Also, sex and age of patients were found to contribute significantly to the prevalence of HIV and TB as compared to marital status and educational level. But, none of the demographic characteristics influenced Hepatitis B prevalence. Future studies should expand the application of Markov modeling to disease dynamics in Ghana by considering several major hospitals in the country.Item Modelling the Transmission Dynamics of Tuberculosis in the Ashanti Region of Ghana(Interdisciplinary Perspectives on Infectious Diseases, 2020-03-31) Mettle, F.O.; Affi, P.O.; Twumasi, C.Mathematical models can aid in elucidating the spread of infectious disease dynamics within a given population over time. In an attempt to model tuberculosis (TB) dynamics among high-burden districts in the Ashanti Region of Ghana, the SEIR epidemic model with demography was employed within both deterministic and stochastic settings for comparison purposes. /e deterministic model showed success in modelling TB infection in the region to the transmission dynamics of the stochastic SEIR model over time. It predicted tuberculosis dying out in ten of twelve high-burden districts in the Ashanti Region, but an outbreak in Obuasi municipal and Amansie West district. /e effect of introducing treatment at the incubation stage of TB transmission was also investigated, and it was discovered that treatment introduced at the exposed stage decreased the spread of TB. Branching process approximation was used to derive explicit forms of relevant epidemiological quantities of the deterministic SEIR model for stability analysis of equilibrium points. Numerical simulations were performed to validate the overall infection rate, basic reproductive number, herd immunity threshold, and Malthusian parameter based on bootstrapping, jackknife, and Latin Hypercube sampling schemes. It was recommended that the Ghana Health Service should find a good mechanism to detect TB in the early stages of infection in the region. Public health attention must also be given to districts with a potentially higher risk of experiencing endemic TB even though the estimates of the overall epidemic thresholds from our SEIR model suggested that the Ashanti Region as a whole had herd immunity against TB infection.