ArticleSpatial and spatio-temporal epidemiology2022
Statistical methods for linking geostatistical maps and transmission models: Application to lymphatic filariasis in East Africa.
Article in Spatial and spatio-temporal epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- How important is the spatial movement of people in attempts to eliminate the transmission of human helminth infections by mass drug administration?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Trial
- Towards Understanding the Microepidemiology of Lymphatic Filariasis at the Community Level in Ghana.Tropical medicine and infectious disease · 2024Article
- An Ensemble Framework for Projecting the Impact of Lymphatic Filariasis Interventions Across Sub-Saharan Africa at a Fine Spatial Scale.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024Article
- Subnational Projections of Lymphatic Filariasis Elimination Targets in Ethiopia to Support National Level Policy.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024Article
- Modernizing the design and analysis of prevalence surveys for neglected tropical diseases.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
Infectious diseases remain one of the major causes of human mortality and suffering. Mathematical models have been established as an important tool for capturing the features that drive the spread of the disease, predicting the progression of an epidemic and hence guiding the development of strategies to control it. Another important area of epidemiological interest is the development of geostatistical methods for the analysis of data from spatially referenced prevalence surveys. Maps of prevalence are useful, not only for enabling a more precise disease risk stratification, but also for guiding the planning of more reliable spatial control programmes by identifying affected areas. Despite the methodological advances that have been made in each area independently, efforts to link transmission models and geostatistical maps have been limited. Motivated by this fact, we developed a Bayesian approach that combines fine-scale geostatistical maps of disease prevalence with transmission models to provide quantitative, spatially-explicit projections of the current and future impact of control programs against a disease. These estimates can then be used at a local level to identify the effectiveness of suggested intervention schemes and allow investigation of alternative strategies. The methodology has been applied to lymphatic filariasis in East Africa to provide estimates of the impact of different intervention strategies against the disease.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.