ArticleMalaria journal2016
Estimating malaria transmission intensity from Plasmodium falciparum serological data using antibody density models.
Article in Malaria journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed.
- Trial
- Reconstruction of historical malaria transmission in Senegal using multiplex serocatalytic models.PLoS computational biology · 2026Article
- Pf41 serological profiling reveals potential malaria exposure in low transmission setting in the Menoreh Hills, Central Java, Indonesia.BMC microbiology · 2026Article
- Optimizing age-structured sampling for estimating the seroconversion rate in malaria seroepidemiology: a simulation study.Scientific reports · 2026Article
- Serodynamics: A primer and synthetic review of methods for epidemiological inference using serological data.Epidemics · 2024Review
- Molecular tools are crucial for malaria elimination.Molecular biology reports · 2024Review
- Antibody selection strategies and their impact in predicting clinical malaria based on multi-sera data.BioData mining · 2024Article
- Analytical approaches for antimalarial antibody responses to confirm historical and recent malaria transmission: an example from the Philippines.The Lancet regional health. Western Pacific · 2023Article
- serosim: An R package for simulating serological data arising from vaccination, epidemiological and antibody kinetics processes.PLoS computational biology · 2023Article
- Serological Markers of Exposure to Plasmodium falciparum and Plasmodium vivax Infection in Southwestern Ethiopia.The American journal of tropical medicine and hygiene · 2023Article
- Article
- Surveillance of Plasmodium vivax transmission using serological models in the border areas of China-Myanmar.Malaria journal · 2022Article
- A threshold-free approach with age-dependency for estimating malaria seroprevalence.Malaria journal · 2022Article
- A unified and flexible modelling framework for the analysis of malaria serology data.Epidemiology and infection · 2021Article
- Herpesviruses Serology Distinguishes Different Subgroups of Patients From the United Kingdom Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Biobank.Frontiers in medicine · 2021Article
- Antibody Profiles toThe American journal of tropical medicine and hygiene · 2020Article
- Combination of Serological, Antigen Detection, and DNA Data for Plasmodium falciparum Provides Robust Geospatial Estimates for Malaria Transmission in Haiti.Scientific reports · 2020Article
- Imported Malaria in Countries where Malaria Is Not Endemic: a Comparison of Semi-immune and Nonimmune Travelers.Clinical microbiology reviews · 2020Review
- Integrated Cross-Sectional Multiplex Serosurveillance of IgG Antibody Responses to Parasitic Diseases and Vaccines in Coastal Kenya.The American journal of tropical medicine and hygiene · 2020Article
- Biannual versus annual mass azithromycin distribution and malaria seroepidemiology among preschool children in Niger: a sub-study of a cluster randomized trial.Malaria journal · 2019Article
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4 authors.
Funding
Abstract
backgroundSerological data are increasingly being used to monitor malaria transmission intensity and have been demonstrated to be particularly useful in areas of low transmission where traditional measures such as EIR and parasite prevalence are limited. The seroconversion rate (SCR) is usually estimated using catalytic models in which the measured antibody levels are used to categorize individuals as seropositive or seronegative. One limitation of this approach is the requirement to impose a fixed cut-off to distinguish seropositive and negative individuals. Furthermore, the continuous variation in antibody levels is ignored thereby potentially reducing the precision of the estimate.
methodsAn age-specific density model which mimics antibody acquisition and loss was developed to make full use of the information provided by serological measures of antibody levels. This was fitted to blood-stage antibody density data from 12 villages at varying transmission intensity in Northern Tanzania to estimate the exposure rate as an alternative measure of transmission intensity.
resultsThe results show a high correlation between the exposure rate estimates obtained and the estimated SCR obtained from a catalytic model (r = 0.95) and with two derived measures of EIR (r = 0.74 and r = 0.81). Estimates of exposure rate obtained with the density model were also more precise than those derived from catalytic models.
conclusionThis approach, if validated across different epidemiological settings, could be a useful alternative framework for quantifying transmission intensity, which makes more complete use of serological data.
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