Modeling infectious disease dynamics in the complex landscape of global health

Hans Heesterbeek; Roy Anderson; Viggo Andreasen; Shweta Bansal; Daniella De Angelis; Chris Dye; Ken Eames; W. John Edmunds; Simon D W Frost; Sebastian Funk; T Deirdre Hollongsworth; Thomas House; Valerie Isham; Petra Klepac; Justin Lessler; James O Lloyd-Smith; C. Jessica E. Metcalf; Denis Mollison; Lorenzo Pellis; Juliet R C Pulliam; Mick G Roberts; Cecile Viboud; Isaac Newton Institute IDD Collaboration

doi:10.1126/science.aaa4339

Modeling infectious disease dynamics in the complex landscape of global health

Hans Heesterbeek, Roy Anderson, Viggo Andreasen, Shweta Bansal, Daniella De Angelis, Chris Dye, Ken Eames, W. John Edmunds, Simon D W Frost, Sebastian Funk, T Deirdre Hollongsworth, Thomas House, Valerie Isham, Petra Klepac, Justin Lessler, James O Lloyd-Smith, C. Jessica E. Metcalf, Denis Mollison, Lorenzo Pellis, Juliet R C PulliamMick G Roberts, Cecile Viboud, Isaac Newton Institute IDD Collaboration

Mathematics and Physics (IMFUFA)

Research output: Contribution to journal › Review › peer-review

Abstract

The spread of infectious diseases can be unpredictable. With the emergence of antibiotic resistance and worrying new viruses, and with ambitious plans for global eradication of polio and the elimination of malaria, the stakes have never been higher. Anticipation and measurement of the multiple factors involved in infectious disease can be greatly assisted by mathematical methods. In particular, modeling techniques can help to compensate for imperfect knowledge, gathered from large populations and under difficult prevailing circumstances. Heesterbeek et al. review the development of mathematical models used in epidemiology and how these can be harnessed to develop successful control strategies and inform public health policy

Original language	English
Article number	aaa4339
Journal	Science
Volume	347
Issue number	6227
Number of pages	10
ISSN	0036-8075
DOIs	https://doi.org/10.1126/science.aaa4339
Publication status	Published - 13 Mar 2015

Link to document

10.1126/science.aaa4339

http://science.sciencemag.org/content/347/6227/aaa4339.full

Cite this

Heesterbeek, H., Anderson, R., Andreasen, V., Bansal, S., De Angelis, D., Dye, C., Eames, K., Edmunds, W. J., Frost, S. D. W., Funk, S., Hollongsworth, T. D., House, T., Isham, V., Klepac, P., Lessler, J., Lloyd-Smith, J. O., Metcalf, C. J. E., Mollison, D., Pellis, L., ... Isaac Newton Institute IDD Collaboration (2015). Modeling infectious disease dynamics in the complex landscape of global health. Science, 347(6227), Article aaa4339 . https://doi.org/10.1126/science.aaa4339

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title = "Modeling infectious disease dynamics in the complex landscape of global health",

abstract = "The spread of infectious diseases can be unpredictable. With the emergence of antibiotic resistance and worrying new viruses, and with ambitious plans for global eradication of polio and the elimination of malaria, the stakes have never been higher. Anticipation and measurement of the multiple factors involved in infectious disease can be greatly assisted by mathematical methods. In particular, modeling techniques can help to compensate for imperfect knowledge, gathered from large populations and under difficult prevailing circumstances. Heesterbeek et al. review the development of mathematical models used in epidemiology and how these can be harnessed to develop successful control strategies and inform public health policy",

author = "Hans Heesterbeek and Roy Anderson and Viggo Andreasen and Shweta Bansal and {De Angelis}, Daniella and Chris Dye and Ken Eames and Edmunds, {W. John} and Frost, {Simon D W} and Sebastian Funk and Hollongsworth, {T Deirdre} and Thomas House and Valerie Isham and Petra Klepac and Justin Lessler and Lloyd-Smith, {James O} and Metcalf, {C. Jessica E.} and Denis Mollison and Lorenzo Pellis and Pulliam, {Juliet R C} and Roberts, {Mick G} and Cecile Viboud and {Isaac Newton Institute IDD Collaboration}",

year = "2015",

month = mar,

day = "13",

doi = "10.1126/science.aaa4339",

language = "English",

volume = "347",

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Heesterbeek, H, Anderson, R, Andreasen, V, Bansal, S, De Angelis, D, Dye, C, Eames, K, Edmunds, WJ, Frost, SDW, Funk, S, Hollongsworth, TD, House, T, Isham, V, Klepac, P, Lessler, J, Lloyd-Smith, JO, Metcalf, CJE, Mollison, D, Pellis, L, Pulliam, JRC, Roberts, MG, Viboud, C & Isaac Newton Institute IDD Collaboration 2015, 'Modeling infectious disease dynamics in the complex landscape of global health', Science, vol. 347, no. 6227, aaa4339 . https://doi.org/10.1126/science.aaa4339

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T1 - Modeling infectious disease dynamics in the complex landscape of global health

AU - Heesterbeek, Hans

AU - Anderson, Roy

AU - Andreasen, Viggo

AU - Bansal, Shweta

AU - De Angelis, Daniella

AU - Dye, Chris

AU - Eames, Ken

AU - Edmunds, W. John

AU - Frost, Simon D W

AU - Funk, Sebastian

AU - Hollongsworth, T Deirdre

AU - House, Thomas

AU - Isham, Valerie

AU - Klepac, Petra

AU - Lessler, Justin

AU - Lloyd-Smith, James O

AU - Metcalf, C. Jessica E.

AU - Mollison, Denis

AU - Pellis, Lorenzo

AU - Pulliam, Juliet R C

AU - Roberts, Mick G

AU - Viboud, Cecile

AU - Isaac Newton Institute IDD Collaboration

PY - 2015/3/13

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N2 - The spread of infectious diseases can be unpredictable. With the emergence of antibiotic resistance and worrying new viruses, and with ambitious plans for global eradication of polio and the elimination of malaria, the stakes have never been higher. Anticipation and measurement of the multiple factors involved in infectious disease can be greatly assisted by mathematical methods. In particular, modeling techniques can help to compensate for imperfect knowledge, gathered from large populations and under difficult prevailing circumstances. Heesterbeek et al. review the development of mathematical models used in epidemiology and how these can be harnessed to develop successful control strategies and inform public health policy

AB - The spread of infectious diseases can be unpredictable. With the emergence of antibiotic resistance and worrying new viruses, and with ambitious plans for global eradication of polio and the elimination of malaria, the stakes have never been higher. Anticipation and measurement of the multiple factors involved in infectious disease can be greatly assisted by mathematical methods. In particular, modeling techniques can help to compensate for imperfect knowledge, gathered from large populations and under difficult prevailing circumstances. Heesterbeek et al. review the development of mathematical models used in epidemiology and how these can be harnessed to develop successful control strategies and inform public health policy

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DO - 10.1126/science.aaa4339

M3 - Review

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