Recurrent Malaria in Kenya: Survival Distribution and Equality of Survival Distribution

Malaria is a leading cause of morbidity and mortality in Kenya, mostly affecting the rural poor, especially young children and pregnant women. Most clinical studies in malaria involve a number of equally important endpoints. This would normally portend challenges in relation to issues about the study design, analysis of the data and interpretation of the results. The majority of malaria related clinical studies do not factor in or experience difficulties in analyzing recurrent events. It is desirable to utilize multiple event times in the analysis procedures to obtain efficient inferences for therapeutic effect over time and to account for the dependence of the recurrent events in an individual. In this paper we aimed to determine the parametric distributions as an approximation of the KM nonparametric distribution of the recurrent malaria data. We considered survival distribution and the equality of survival distribution in analyzing specific covariates (gender, anemia and drug treatments) in a recurrent malaria data. We used R software to construct Kaplan – Meier survival curves and demonstrate their equality by running a Log- rank test to determine their performance and find the level of significance of the covariates survival distribution. The result showed that there was no significant difference at 95% Cl of the covariates under scrutiny. The significance level for the covariates were: gender (p-value= 0.41); anemia (p value= 0.816); the treatment drug combination 2 (p-value= 0.637) and treatment drug combination 1 (p-value= 0.808). However, majority of the patients who had recurrent malaria also had anemia. Understanding the survival distribution and the equality of the survival distribution in recurrent malaria cases is essential for designing optimal statistical procedures that do not bias study results.