title: Modelling challenges in context: lessons from malaria, HIV, and tuberculosis.
abstract: 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.
authors.affiliation: Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.
authors.forename: Lauren M
authors.initials: LM
authors.lastname: Childs
authors.affiliation: Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.
authors.forename: Nadia N
authors.initials: NN
authors.lastname: Abuelezam
authors.affiliation: Office of the Director General, World Health Organization, Avenue Appia, 1211 Geneva 27, Switzerland.
authors.forename: Christopher
authors.initials: C
authors.lastname: Dye
authors.affiliation: Department of Zoology, University of Oxford, Oxford OX1 3PS, United Kingdom.
authors.forename: Sunetra
authors.initials: S
authors.lastname: Gupta
authors.affiliation: Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States; Division of Global Health Equity, Brigham & Women's Hospital, Boston, MA 02115, United States.
authors.forename: Megan B
authors.initials: MB
authors.lastname: Murray
authors.affiliation: South African Centre for Epidemiological Modelling and Analysis, Stellenbosch, South Africa; Wits Reproductive Health and HIV Institute, University of the Witwatersrand, Johannesburg, South Africa.
authors.forename: Brian G
authors.initials: BG
authors.lastname: Williams
authors.affiliation: Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States. Electronic address: cbuckee@hsph.harvard.edu.
authors.forename: Caroline O
authors.initials: CO
authors.lastname: Buckee
mesh_terms: D014644:Genetic Variation; D006678:HIV / Q000235:genetics; D015658:HIV Infections / Q000453:epidemiology* / Q000517:prevention & control / Q000635:transmission; D054884:Host-Pathogen Interactions / Q000235:genetics; D006801:Humans; D008288:Malaria / Q000453:epidemiology* / Q000517:prevention & control / Q000635:transmission; D015233:Models, Statistical; D009169:Mycobacterium tuberculosis / Q000235:genetics; D014397:Tuberculosis, Pulmonary / Q000453:epidemiology* / Q000517:prevention & control / Q000635:transmission
keywords: HIV; Malaria; Modelling; Tuberculosis
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