The role of mathematical modelling in guiding the science and economics of malaria elimination

Unprecedented efforts are now underway to eliminate malaria from many regions. Despite the enormous financial resources committed, if malaria elimination is perceived as failing it is likely that this funding will not be sustained. It is imperative that methods are developed to use the limited data...

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Main Authors: Richard J. Maude, Yoel Lubell, Duong Socheat, Shunmay Yeung, Sompob Saralamba, Wirichada Pongtavornpinyo, Ben S. Cooper, Arjen M. Dondorp, Nicholas J. White, Lisa J. White
Other Authors: Mahidol University
Format: Review
Published: 2018
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Online Access:https://repository.li.mahidol.ac.th/handle/123456789/29435
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spelling th-mahidol.294352018-09-24T16:46:37Z The role of mathematical modelling in guiding the science and economics of malaria elimination Richard J. Maude Yoel Lubell Duong Socheat Shunmay Yeung Sompob Saralamba Wirichada Pongtavornpinyo Ben S. Cooper Arjen M. Dondorp Nicholas J. White Lisa J. White Mahidol University Nuffield Department of Clinical Medicine Heartlands Hospital National Malaria Center London School of Hygiene & Tropical Medicine Medicine Social Sciences Unprecedented efforts are now underway to eliminate malaria from many regions. Despite the enormous financial resources committed, if malaria elimination is perceived as failing it is likely that this funding will not be sustained. It is imperative that methods are developed to use the limited data available to design site-specific, cost-effective elimination programmes. Mathematical modelling is a way of including mechanistic understanding to use available data to make predictions. Different strategies can be evaluated much more rapidly than is possible through trial and error in the field. Mathematical modelling has great potential as a tool to guide and inform current elimination efforts. Economic modelling weighs costs against characterised effects or predicted benefits in order to determine the most cost-efficient strategy but has traditionally used static models of disease not suitable for elimination. Dynamic mathematical modelling and economic modelling techniques need to be combined to contribute most effectively to ongoing policy discussions. We review the role of modelling in previous malaria control efforts as well as the unique nature of elimination and the consequent need for its explicit modelling, and emphasise the importance of good disease surveillance. The difficulties and complexities of economic evaluation of malaria control, particularly the end stages of elimination, are discussed. © 2010 Royal Society of Tropical Medicine and Hygiene. 2018-09-24T09:16:52Z 2018-09-24T09:16:52Z 2010-12-01 Review International Health. Vol.2, No.4 (2010), 239-246 10.1016/j.inhe.2010.09.005 18763413 2-s2.0-78649631980 https://repository.li.mahidol.ac.th/handle/123456789/29435 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78649631980&origin=inward
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Medicine
Social Sciences
spellingShingle Medicine
Social Sciences
Richard J. Maude
Yoel Lubell
Duong Socheat
Shunmay Yeung
Sompob Saralamba
Wirichada Pongtavornpinyo
Ben S. Cooper
Arjen M. Dondorp
Nicholas J. White
Lisa J. White
The role of mathematical modelling in guiding the science and economics of malaria elimination
description Unprecedented efforts are now underway to eliminate malaria from many regions. Despite the enormous financial resources committed, if malaria elimination is perceived as failing it is likely that this funding will not be sustained. It is imperative that methods are developed to use the limited data available to design site-specific, cost-effective elimination programmes. Mathematical modelling is a way of including mechanistic understanding to use available data to make predictions. Different strategies can be evaluated much more rapidly than is possible through trial and error in the field. Mathematical modelling has great potential as a tool to guide and inform current elimination efforts. Economic modelling weighs costs against characterised effects or predicted benefits in order to determine the most cost-efficient strategy but has traditionally used static models of disease not suitable for elimination. Dynamic mathematical modelling and economic modelling techniques need to be combined to contribute most effectively to ongoing policy discussions. We review the role of modelling in previous malaria control efforts as well as the unique nature of elimination and the consequent need for its explicit modelling, and emphasise the importance of good disease surveillance. The difficulties and complexities of economic evaluation of malaria control, particularly the end stages of elimination, are discussed. © 2010 Royal Society of Tropical Medicine and Hygiene.
author2 Mahidol University
author_facet Mahidol University
Richard J. Maude
Yoel Lubell
Duong Socheat
Shunmay Yeung
Sompob Saralamba
Wirichada Pongtavornpinyo
Ben S. Cooper
Arjen M. Dondorp
Nicholas J. White
Lisa J. White
format Review
author Richard J. Maude
Yoel Lubell
Duong Socheat
Shunmay Yeung
Sompob Saralamba
Wirichada Pongtavornpinyo
Ben S. Cooper
Arjen M. Dondorp
Nicholas J. White
Lisa J. White
author_sort Richard J. Maude
title The role of mathematical modelling in guiding the science and economics of malaria elimination
title_short The role of mathematical modelling in guiding the science and economics of malaria elimination
title_full The role of mathematical modelling in guiding the science and economics of malaria elimination
title_fullStr The role of mathematical modelling in guiding the science and economics of malaria elimination
title_full_unstemmed The role of mathematical modelling in guiding the science and economics of malaria elimination
title_sort role of mathematical modelling in guiding the science and economics of malaria elimination
publishDate 2018
url https://repository.li.mahidol.ac.th/handle/123456789/29435
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