Malaria attributable fractions with changing transmission intensity: Bayesian latent class vs logistic models.

Kennedy MwaiIrene NkumamaAmos ThairuJames MburuDennis OderaRinter KimathiLydia NyamakoJames TujuSamson KinyanjuiEustasius MusengeFaith Osier

Published in: Malaria journal (2022)

Malaria attributable fractions, varied with an overall decline in the malaria transmission intensity in this setting but did not significantly impact the outcomes of analyses aimed at identifying immune correlates of protection. These data confirm the statistical advantage of using probabilities over binary data.

Keyphrases

plasmodium falciparum
electronic health record
high intensity
big data
type diabetes
adipose tissue
metabolic syndrome
deep learning