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Statistical methods for linking geostatistical maps and transmission models : application to lymphatic filariasis in East Africa

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Touloupou, Panayiota, Retkute, Renata, Hollingsworth, T. Déirdre and Spencer, Simon E. F. (2020) Statistical methods for linking geostatistical maps and transmission models : application to lymphatic filariasis in East Africa. Spatial and Spatio-temporal Epidemiology . 100391. doi:10.1016/j.sste.2020.100391 (In Press)

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Official URL: https://doi.org/10.1016/j.sste.2020.100391

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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.

Item Type: Journal Article
Subjects: R Medicine > RA Public aspects of medicine
Divisions: Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH): Communicable diseases -- Mathematical models, Bayesian statistical decision theory, Lymphatics -- Diseases -- Transmission -- Mathematical models, Geology -- Statistical methods
Journal or Publication Title: Spatial and Spatio-temporal Epidemiology
Publisher: Elsevier Science BV
ISSN: 1877-5845
Official Date: 21 November 2020
Dates:
DateEvent
21 November 2020Available
6 November 2020Accepted
Article Number: 100391
DOI: 10.1016/j.sste.2020.100391
Status: Peer Reviewed
Publication Status: In Press
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
OPP1152057Bill and Melinda Gates Foundationhttp://dx.doi.org/10.13039/100000865
OPP1053230Bill and Melinda Gates Foundationhttp://dx.doi.org/10.13039/100000865
OPP1156227Bill and Melinda Gates Foundationhttp://dx.doi.org/10.13039/100000865
OPP1186851Bill and Melinda Gates Foundationhttp://dx.doi.org/10.13039/100000865
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