Using Markov assumption with covariates to assess the Plasmodium falciparum malaria serological markers evolution
- Resource Type
- Authors
- Abdou Kâ Diongue; Philippe Saint-Pierre; Aissatou Touré; Oumy Niass
- Source
- Afr. J. Appl. Stat. 7, no. 1 (2020), 915-932
- Subject
- Plasmodium falciparum
Ocean Engineering
maximum likelihood estimation
Biology
biology.organism_classification
medicine.disease
Virology
continuous time Markov processes
semi-Markov process
Serology
Quantitative Biology::Cell Behavior
62P10
Covariate
parasitic diseases
medicine
longitudinal serological malaria data
Markov property
60Jxx
Safety, Risk, Reliability and Quality
piecewise constant intensities
Malaria
- Language
- English
In this study, we develop Three Markov models which are continuous time-homogeneous Model, time piecewise constant intensities Markov model and semi-Markov model with Weibull distribution as the waiting time distribution to evaluate malaria serology evolution. We consider two-state model describing antibody reactivity defined by immunologists. We discuss in detail the application of these models to identify relationships between malaria control program and serological measurements of malaria transmission