The Library
Statistical methods for linking geostatistical maps and transmission models : application to lymphatic filariasis in East Africa
Tools
Tools
Tools
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)
|
PDF
WRAP-Statistical-methods-linking-geostatistical-maps-lymphatic-filariasis-Spencer-2020.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (2832Kb) | Preview |
|
![[img]](http://wrap.warwick.ac.uk/style/images/fileicons/application_pdf.png) |
PDF
WRAP-Statistical-methods-linking-geostatistical-maps-lymphatic-filariasis-Spencer-2020.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only - Requires a PDF viewer. Download (10Mb) |
Official URL: https://doi.org/10.1016/j.sste.2020.100391
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: |
|
|||||||||||||||
| 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: |
|
|||||||||||||||
| Related URLs: |
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
