Purpose: The study aimed to investigate the factors influencing blood pressure levels in hypertensive adult patients in Kenya's Kakamega County. The specific objectives were as follows: to assess patient factors that influence blood pressure levels among hypertensive adult patients in Kakamega County, examine health-care provider factors that influence blood pressure levels in hypertensive adult patients; determine institutional factors that influence blood pressure levels in hypertensive adult patients in Kakamega County based on the clinical recommendations for cardiovascular disease management from 2018. Methodology: The researcher used a cross-sectional analytical study design. Patients and health care providers were requested to sign a written consent before data was collected using a questionnaire and an observation checklist. Quantitative data were evaluated using descriptive and inferential statistics, statistical package for social sciences version 22, with a statistically significant p-value of 0.05. The strength of the relationship between the variables and the patient's blood pressure level was tested using multiple regression. Findings: The findings showed that the number of years a patient was told he or she had hypertension patient sensitization about the disease (p = 0.04), the patient's BMI (p = 0.01), BP stability at the time of admission (0.0001), having a treatment supporter to advise the patient when to take medications (0.04). The health care provider's age group and knowledge about the disease (p = 0.02) was all separately correlated with blood pressure control. According to the current analysis, in Kakamega County, being a male without adequate patient sensitization about the hypertension disease made patients to be more likely to have uncontrolled blood pressure levels. Unique contribution to theory, practice and policy: The study recommends a model that combines patient and health-care system variables emphasizing on patient sensitization about the hypertension disease, modifiable and modifiable risk factors should be created in attempt to have blood pressure controlled.

Purpose: The main objective of the study was to determine health care provider factor influencing trauma care preparedness among health care providers working in accident and emergency department of the selected hospitals. Materials and Methods: This was a cross-sectional Analytic study. Census sampling was used to select General Practitioner hospitals. Systematic sampling technique was used to choose study participants from 11 selected hospitals. The study participants were 183 health care providers (Doctors, Clinical Officers and Nurses) working in the selected hospitals’ accident and emergency departments.  Data was collected using structured questionnaires and observation checklists. Data was analyzed using statistical package for Social Science software version 22.0. Inferential statistics were used to test the strength of association.  Findings; Health care providers’ factors that influenced trauma care preparedness were; specific training on trauma care (p=0.002), attending Continuing medical education (p=0.0008) and duration when last update was received (p= 0.04).  Unique contributions to Theory, Practice and Policy: Trauma related training, trauma related continuing medical education and duration when last trauma update was received influence trauma. Health care providers working in accident and emergency department should undergo trauma related training and get frequent updates on trauma care.

In this paper, a mathematical model for COVID-19 disease incorporating clinical management based on a system of Ordinary Differential Equations is developed. The existence of the steady states of the model are determined and the effective reproduction number derived using the next generation matrix approach. Stability analysis of the model is carried out to determine the conditions that favour the spread of COVID-19 disease in a given population. The Disease Free Equilibrium is show to be locally asymptotically stable when \(R\)e < 1 and the Endemic Equilibrium is locally asymptotically stable when \(R\)e > 1. The Disease Free Equilibrium is shown not to be globally asymptotically stable using a technique by Castillo Chavez and the Endemic Equilibrium is shown to be globally asymptotically stable by means of Lyapunov's direct method and LaSalle's invariance principle. This implies that COVID-19 disease transmission can be kept low or manageable with the incorporation of clinical management. Sensitivity analysis of the model is carried out by use of the normalised forward sensitivity index (elasticity) which shows that the higher the rates of clinical management the lower the rate of infection. Numerical simulations carried out using MATLAB software showed that with high success of clinical management, there is low contact rate and low prevalence rate of the disease in the population.

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