Statistical Analysis of Risk factors of Malaria re-infection among Outpatients in DR, Congo: A Comparison Approach of AFT and Cox PH Models
Abstract
Background: Malaria is an infectious disease caused by a Plasmodium parasite and is one of the highest causes of mortality globally. This study aims to determine models to detect the effect of risk factors on malaria re-infection of patients survival.
Methods: The study includes 109 malaria outpatients in Lubumbashi Congo Hospital, who had re-infection status after six months follow-up. The survival status of the re-infected patients was based on the effect of various factors. The best model was selected through Akaike Information Criterion (AIC) and Cox-Snell Residuals using SAS and R packages.
Results: The results from the analysis showed that Gamma model (AIC=147.092) was better in the analysis compared to accelerated failure-time models.
Conclusion: Although, many researchers prefer proportional hazard model in analysing a survival data but accelerated failure-time model is a good alternative method as they do not require proportionality of hazards as key assumption.
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