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

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 te

SUBMITTER: Kyomuhangi I 

PROVIDER: S-EPMC8161365 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature