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A threshold-free approach with age-dependency for estimating malaria seroprevalence

Abstract:
Abstract Background In malaria serology analysis, the standard approach to obtain seroprevalence, i.e the proportion of seropositive individuals in a population, is based on a threshold which is used to classify individuals as seropositive or seronegative. The choice of this threshold is often arbitrary and is based on methods that ignore the age-dependency of the antibody distribution. Methods Using cross-sectional antibody data from the Western Kenyan Highlands, this paper introduces a novel approach that has three main advantages over the current threshold-based approach: it avoids the use of thresholds; it accounts for the age dependency of malaria antibodies; and it allows us to propagate the uncertainty from the classification of individuals into seropositive and seronegative when estimating seroprevalence. The reversible catalytic model is used as an example for illustrating how to propagate this uncertainty into the parameter estimates of the model. Results This paper finds that accounting for age-dependency leads to a better fit to the data than the standard approach which uses a single threshold across all ages. Additionally, the paper also finds that the proposed threshold-free approach is more robust against the selection of different age-groups when estimating seroprevalence. Conclusion The novel threshold-free approach presented in this paper provides a statistically principled and more objective approach to estimating malaria seroprevalence. The introduced statistical framework also provides a means to compare results across studies which may use different age ranges for the estimation of seroprevalence.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1186/s12936-021-04022-4

Authors

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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0002-2797-015X
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Role:
Author
ORCID:
0000-0003-0640-181X


Publisher:
BioMed Central
Journal:
Malaria Journal More from this journal
Volume:
21
Issue:
1
Pages:
1-1
Publication date:
2022-01-03
DOI:
EISSN:
1475-2875
ISSN:
1475-2875


Language:
English
Keywords:
Pubs id:
2427846
Local pid:
pubs:2427846
Source identifiers:
W4205495235
Deposit date:
2026-06-02
ARK identifier:
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