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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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.
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topic |
Modelling HIV Tuberculosis Malaria |
url |
http://www.sciencedirect.com/science/article/pii/S1755436515000079 |
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