A unified and flexible modelling framework for the analysis of malaria serology data

Kyomuhangi, Irene and Giorgi, Emanuele (2021) A unified and flexible modelling framework for the analysis of malaria serology data. Epidemiology and Infection. ISSN 0950-2688

Full text not available from this repository.

Abstract

Serology data are an increasingly important tool in malaria surveillance, especially in low transmission settings where the estimation of parasite-based indicators is often problematic. Existing methods rely on the use of thresholds to identify seropositive individuals and estimate transmission intensity, while making assumptions about the temporal dynamics of malaria transmission that are rarely questioned. Here, we present a novel threshold-free approach for the analysis of malaria serology data which avoids dichotomization of continuous antibody measurements and allows us to model changes in the antibody distribution across age in a more flexible way. The proposed unified mechanistic model combines the properties of reversible catalytic and antibody acquisition models, and allows for temporally varying boosting and seroconversion rates. Additionally, as an alternative to the unified mechanistic model, we also propose an empirical approach to analysis where modelling of the age-dependency is informed by the data rather than biological assumptions. Using serology data from Western Kenya, we demonstrate both the usefulness and limitations of the novel modelling framework.

Item Type:
Journal Article
Journal or Publication Title:
Epidemiology and Infection
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2400/2403
Subjects:
?? malaria serologyreversible catalytic modelantibody acquisition modelmixture modelmalaria antibodyseroprevalenceimmunologystatistics and probabilitymodelling and simulationinfectious diseasesanalysisepidemiologyimmunology and allergy ??
ID Code:
153747
Deposited By:
Deposited On:
12 Apr 2021 13:25
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Jul 2024 21:35