Modular programming for tuberculosis control, the "AuTuMN" platform.
Background: Tuberculosis (TB) is now the world's leading infectious killer and major programmatic advances will be needed if we are to meet the ambitious new End TB Targets. Although mathematical models are powerful tools for TB control, such models must be flexible enough to capture the complexity...
| Published in: | BMC Infectious Diseases Vol. 17; pp. 1 - 13 |
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| Main Authors: | , , , , |
| Format: | research Journal Article |
| Published: |
BioMed Central
8/7/2017
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=124534884&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 124534884 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14712334 1CHU jtl: BMC Infectious Diseases issn: 14712334 maglogo: N pubinfo: dt: 8/7/2017 vid: 17 pid: 24147 pub: BioMed Central artinfo: ui: 124534884 124534884 NLM28784094 124534884 10.1186/s12879-017-2648-6 NLM28784094 124534884 ppf: 1 ppct: 12 formats: tig: atl: Modular programming for tuberculosis control, the "AuTuMN" platform. aug: au: Trauer, James McCracken Ragonnet, Romain Tan Nhut Doan McBryde, Emma Sue Doan, Tan Nhut affil: School of Public Health and Preventive Medicine, Monash University, 99 Commercial Road, Melbourne 3004, Australia sug: subj: Software Infection Control Methods Tuberculosis Prevention and Control Tuberculosis Economics Tuberculosis Transmission Immunization Models, Theoretical Tuberculosis Epidemiology Models, Statistical Cost Benefit Analysis Human ab: Background: Tuberculosis (TB) is now the world's leading infectious killer and major programmatic advances will be needed if we are to meet the ambitious new End TB Targets. Although mathematical models are powerful tools for TB control, such models must be flexible enough to capture the complexity and heterogeneity of the global TB epidemic. This includes simulating a disease that affects age groups and other risk groups differently, has varying levels of infectiousness depending upon the organ involved and varying outcomes from treatment depending on the drug resistance pattern of the infecting strain.Results: We adopted sound basic principles of software engineering to develop a modular software platform for simulation of TB control interventions ("AuTuMN"). These included object-oriented programming, logical linkage between modules and consistency of code syntax and variable naming. The underlying transmission dynamic model incorporates optional stratification by age, risk group, strain and organ involvement, while our approach to simulating time-variant programmatic parameters better captures the historical progression of the epidemic. An economic model is overlaid upon this epidemiological model which facilitates comparison between new and existing technologies. A "Model runner" module allows for predictions of future disease burden trajectories under alternative scenario situations, as well as uncertainty, automatic calibration, cost-effectiveness and optimisation. The model has now been used to guide TB control strategies across a range of settings and countries, with our modular approach enabling repeated application of the tool without the need for extensive modification for each application.Conclusions: The modular construction of the platform minimises errors, enhances readability and collaboration between multiple programmers and enables rapid adaptation to answer questions in a broad range of contexts without the need for extensive re-programming. Such features are particularly important in simulating an epidemic as complex and diverse as TB. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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