Flexible parametric modeling of malaria survival:Application to Burkina Faso
DOI:
https://doi.org/10.5281/zenodo.22668966Keywords:
Malaria; survival analysis; parametric models; Weibull model; prognostic factors; Burkina FasoAbstract
Objectives: Severe malaria remains a major cause of childhood mortality in sub-Saharan Africa.
Identifying prognostic factors associated with death among hospitalized children is therefore an
important public health priority. This study aimed to identify the parametric model that best describes
hospital survival among children with severe malaria and to determine the clinical factors associated
with death.
Methods: We analyzed a cohort of 444 children aged 1–59 months who were hospitalized for confirmed
malaria at Dori Regional Hospital, Burkina Faso. Five parametric survival models were fitted and
compared: Exponential, Weibull, three-parameter Weibull, Beta-Weibull, and modified Beta-Weibull
models. Model performance was assessed using the Akaike information criterion (AIC) and Bayesian
information criterion (BIC). A simulation study was conducted to assess estimator stability. Clinical
factors associated with death were investigated using the selected model under an accelerated failure
time (AFT) formulation.
Results: The three-parameter Weibull model provided the best fit (AIC = 595.11; BIC = 607.40). Its
shape parameter was k = 0.912, indicating a decreasing hazard. The estimated threshold parameter was
approximately one day. The Beta-Weibull and modified Beta-Weibull models showed identifiability
problems. In the multivariable analysis, respiratory distress (TR = 0.209; p < 0.001) and shock (TR =
0.147; p < 0.001) were the factors most strongly associated with shorter survival times. These findings
correspond to reductions of 79% and 85% in survival time, respectively.
Conclusions: Flexible parametric modeling, particularly the three-parameter Weibull model, provided a suitable framework for characterizing hospital mortality among children with severe malaria.Respiratory distress and shock were major warning signs and may warrant early intensive management.
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