Antecedents of patients Covid-19 management outcomes

Abstract

Background: Effective Covid-19 management calls for clear understanding of determinants of possible outcomes. The likelihood of mortality or extent of recovery are the only two eventual outcomes. Examining influences of exposure, effect multiplier, moderating, and confounding factors in Covid-19 management is key to safeguarding human life and protecting livelihoods. Method: An assessment of covid-19 resurgence preparedness was conducted in Lake Region Economic Bloc Counties of Kenya. Data on cumulative cases, mortality, vaccination, oxygen flow per minute, and ages of infected was collected. Mortality is taken as the response variable where cumulative cases is exposure variable, vaccination as moderating variable, oxygen flow rate as effect multiplier, and age taken as a confounding factor. Age frequency is used as a categorical variable and divided in three groups: 0-19, 20-49, and 50 < years. A multiple logistic regression model is formulated, fitted, and estimated. Finally, an outcome predictive model is fitted. Findings: Adjusting for all variables, the likelihood of mortality after being infected is 5.3%, (1.053:95% CI, 1.03 - 3.34). A patient is 27%, (95% CI, 7% -33%) more likely to succumb to Covid-19 because of insufficient oxygen compared to a patient without critical oxygen need. Unvaccinated patient is 1.27 times (95% CI, 1.14 -6.26) more likely to die of Covid-19 compared to the vaccinated. A patient aged (20-49) years is 21%, (95% CI, 2% -30.4%) more likely to succumb to Covid-19 compared to one aged (0-19) years. Lastly, a patient aged 50 years and older is 47%, (95% CI, 3% - 56%) more likely to succumb to Covid-19 compared to one in (0-19) years age bracket.