ArticlePLoS neglected tropical diseases2022
Characterising spatial patterns of neglected tropical disease transmission using integrated sero-surveillance in Northern Ghana.
Article in PLoS neglected tropical diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 20 citations in OpenAlex.
- Integration of population-based surveys for neglected tropical diseases: A scoping review.PLoS neglected tropical diseases · 2026Article
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- Review
- Multiplex bead assays enable integrated serological surveillance and reveal cross-pathogen vulnerabilities in Zambezia Province, Mozambique.Nature communications · 2025Article
- Integrating vulnerability and hazard in malaria risk mapping: the elimination context of Senegal.BMC infectious diseases · 2025Article
- Integrating geospatial tools is crucial for enhancing control strategies against human lymphatic filarial infections in Ghana: A comprehensive review.Parasite epidemiology and control · 2025Review
- Integrated Serosurveillance of Infectious Diseases Using Multiplex Bead Assays: A Systematic Review.Tropical medicine and infectious disease · 2025Review
- Serodynamics: A primer and synthetic review of methods for epidemiological inference using serological data.Epidemics · 2024Review
- Spatial targeting and integration across vaccination, vitamin A and deworming programs throughout India 2019-21.International journal of epidemiology · 2024Article
- Monitoring of Leishmania transmission in the postelimination phase: The potential of serological surveys.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2024Article
- Towards Understanding the Microepidemiology of Lymphatic Filariasis at the Community Level in Ghana.Tropical medicine and infectious disease · 2024Article
- Serological evaluation of risk factors for exposure to malaria in a pre-elimination setting in Malaysian Borneo.Scientific reports · 2023Article
- Article
- Burden and Epidemiology of Human IntestinalTropical medicine and infectious disease · 2022Review
- Characterizing the spatial distribution of multiple malaria diagnostic endpoints in a low-transmission setting in Lao PDR.Frontiers in medicine · 2022Article
Corrections and comments
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Authors and funding
13 authors at 5 institutions in 4 countries.
Funding
Abstract
backgroundAs prevalence decreases in pre-elimination settings, identifying the spatial distribution of remaining infections to target control measures becomes increasingly challenging. By measuring multiple antibody responses indicative of past exposure to different pathogens, integrated serological surveys enable simultaneous characterisation of residual transmission of multiple pathogens. METHODOLOGY/PRINCIPAL
findingsHere, we combine integrated serological surveys with geostatistical modelling and remote sensing-derived environmental data to estimate the spatial distribution of exposure to multiple diseases in children in Northern Ghana. The study utilised the trachoma surveillance survey platform (cross-sectional two-stage cluster-sampled surveys) to collect information on additional identified diseases at different stages of elimination with minimal additional cost. Geostatistical modelling of serological data allowed identification of areas with high probabilities of recent exposure to diseases of interest, including areas previously unknown to control programmes. We additionally demonstrate how serological surveys can be used to identify areas with exposure to multiple diseases and to prioritise areas with high uncertainty for future surveys. Modelled estimates of cluster-level prevalence were strongly correlated with more operationally feasible metrics of antibody responses. CONCLUSIONS/SIGNIFICANCE: This study demonstrates the potential of integrated serological surveillance to characterise spatial distributions of exposure to multiple pathogens in low transmission and elimination settings when the probability of detecting infections is low.
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