Modelling challenges in context: Lessons from malaria, HIV, and tuberculosis

Malaria, HIV, and tuberculosis (TB) collectively account for several million deaths each year, with all three ranking among the top ten killers in low-income countries. Despite being caused by very different organisms, malaria, HIV, and TB present a suite of challenges for mathematical modellers th...

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Main Authors: Lauren M. Childs, Nadia N. Abuelezam, Christopher Dye, Sunetra Gupta, Megan B. Murray, Brian G. Williams, Caroline O. Buckee
Format: Article
Language:English
Published: Elsevier 2015-03-01
Series:Epidemics
Subjects:
HIV
Online Access:http://www.sciencedirect.com/science/article/pii/S1755436515000079
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spelling doaj-64e594286d9f44f5813bbc4d4a0b35422020-11-25T02:41:25ZengElsevierEpidemics1755-43651878-00672015-03-0110C10210710.1016/j.epidem.2015.02.002Modelling challenges in context: Lessons from malaria, HIV, and tuberculosisLauren M. Childs0Nadia N. Abuelezam1Christopher Dye2Sunetra Gupta3Megan B. Murray4Brian G. Williams5Caroline O. Buckee6Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United StatesDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United StatesOffice of the Director General, World Health Organization, Avenue Appia, 1211 Geneva 27, SwitzerlandDepartment of Zoology, University of Oxford, Oxford OX1 3PS, United KingdomDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United StatesSouth African Centre for Epidemiological Modelling and Analysis, Stellenbosch, South AfricaCenter for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States Malaria, HIV, and tuberculosis (TB) collectively account for several million deaths each year, with all three ranking among the top ten killers in low-income countries. Despite being caused by very different organisms, malaria, HIV, and TB present a suite of challenges for mathematical modellers that are particularly pronounced in these infections, but represent general problems in infectious disease modelling, and highlight many of the challenges described throughout this issue. Here, we describe some of the unifying challenges that arise in modelling malaria, HIV, and TB, including variation in dynamics within the host, diversity in the pathogen, and heterogeneity in human contact networks and behaviour. Through the lens of these three pathogens, we provide specific examples of the other challenges in this issue and discuss their implications for informing public health efforts. http://www.sciencedirect.com/science/article/pii/S1755436515000079ModellingHIVTuberculosisMalaria
collection DOAJ
language English
format Article
sources DOAJ
author Lauren M. Childs
Nadia N. Abuelezam
Christopher Dye
Sunetra Gupta
Megan B. Murray
Brian G. Williams
Caroline O. Buckee
spellingShingle Lauren M. Childs
Nadia N. Abuelezam
Christopher Dye
Sunetra Gupta
Megan B. Murray
Brian G. Williams
Caroline O. Buckee
Modelling challenges in context: Lessons from malaria, HIV, and tuberculosis
Epidemics
Modelling
HIV
Tuberculosis
Malaria
author_facet Lauren M. Childs
Nadia N. Abuelezam
Christopher Dye
Sunetra Gupta
Megan B. Murray
Brian G. Williams
Caroline O. Buckee
author_sort Lauren M. Childs
title Modelling challenges in context: Lessons from malaria, HIV, and tuberculosis
title_short Modelling challenges in context: Lessons from malaria, HIV, and tuberculosis
title_full Modelling challenges in context: Lessons from malaria, HIV, and tuberculosis
title_fullStr Modelling challenges in context: Lessons from malaria, HIV, and tuberculosis
title_full_unstemmed Modelling challenges in context: Lessons from malaria, HIV, and tuberculosis
title_sort modelling challenges in context: lessons from malaria, hiv, and tuberculosis
publisher Elsevier
series Epidemics
issn 1755-4365
1878-0067
publishDate 2015-03-01
description Malaria, HIV, and tuberculosis (TB) collectively account for several million deaths each year, with all three ranking among the top ten killers in low-income countries. Despite being caused by very different organisms, malaria, HIV, and TB present a suite of challenges for mathematical modellers that are particularly pronounced in these infections, but represent general problems in infectious disease modelling, and highlight many of the challenges described throughout this issue. Here, we describe some of the unifying challenges that arise in modelling malaria, HIV, and TB, including variation in dynamics within the host, diversity in the pathogen, and heterogeneity in human contact networks and behaviour. Through the lens of these three pathogens, we provide specific examples of the other challenges in this issue and discuss their implications for informing public health efforts.
topic Modelling
HIV
Tuberculosis
Malaria
url http://www.sciencedirect.com/science/article/pii/S1755436515000079
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