Modeling infectious disease dynamics in the complex landscape of global health

Hans Heesterbeek; Roy M Anderson; Viggo Andreasen; Shweta Bansal; Daniela De Angelis; Chris Dye; Ken T D Eames; W John Edmunds; Simon D W Frost; Sebastian Funk; T Deirdre Hollingsworth; 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 M Anderson, Viggo Andreasen, Shweta Bansal, Daniela De Angelis, Chris Dye, Ken T D Eames, W John Edmunds, Simon D W Frost, Sebastian Funk, T Deirdre Hollingsworth, 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

Strategic Infection Biology Program (SIB) FVM

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health.

Original language	English
Article number	aaa4339
Journal	Science
Volume	347
Issue number	6227
DOIs	https://doi.org/10.1126/science.aaa4339
Publication status	Published - 2015

Keywords

Animals
Basic Reproduction Number
Coinfection
Communicable Disease Control
Communicable Diseases
Communicable Diseases, Emerging
Disease Outbreaks
Global Health
Health Policy
Hemorrhagic Fever, Ebola
Humans
Models, Biological
Public Health
Zoonoses

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Heesterbeek, H., Anderson, R. M., Andreasen, V., Bansal, S., De Angelis, D., Dye, C., Eames, K. T. D., Edmunds, W. J., Frost, S. D. W., Funk, S., Hollingsworth, 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 = "Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health.",

keywords = "Animals, Basic Reproduction Number, Coinfection, Communicable Disease Control, Communicable Diseases, Communicable Diseases, Emerging, Disease Outbreaks, Global Health, Health Policy, Hemorrhagic Fever, Ebola, Humans, Models, Biological, Public Health, Zoonoses",

author = "Hans Heesterbeek and Anderson, {Roy M} and Viggo Andreasen and Shweta Bansal and {De Angelis}, Daniela and Chris Dye and Eames, {Ken T D} and Edmunds, {W John} and Frost, {Simon D W} and Sebastian Funk and Hollingsworth, {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}",

note = "Copyright {\textcopyright} 2015, American Association for the Advancement of Science.",

year = "2015",

doi = "10.1126/science.aaa4339",

language = "English",

volume = "347",

journal = "Science",

issn = "0036-8075",

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Heesterbeek, H, Anderson, RM, Andreasen, V, Bansal, S, De Angelis, D, Dye, C, Eames, KTD, Edmunds, WJ, Frost, SDW, Funk, S, Hollingsworth, 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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AU - Heesterbeek, Hans

AU - Anderson, Roy M

AU - Andreasen, Viggo

AU - Bansal, Shweta

AU - De Angelis, Daniela

AU - Dye, Chris

AU - Eames, Ken T D

AU - Edmunds, W John

AU - Frost, Simon D W

AU - Funk, Sebastian

AU - Hollingsworth, 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

Y1 - 2015

N2 - Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health.

AB - Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health.

KW - Animals

KW - Basic Reproduction Number

KW - Coinfection

KW - Communicable Disease Control

KW - Communicable Diseases

KW - Communicable Diseases, Emerging

KW - Disease Outbreaks

KW - Global Health

KW - Health Policy

KW - Hemorrhagic Fever, Ebola

KW - Humans

KW - Models, Biological

KW - Public Health

KW - Zoonoses

U2 - 10.1126/science.aaa4339

DO - 10.1126/science.aaa4339

M3 - Article

C2 - 25766240

SN - 0036-8075

VL - 347

JO - Science

JF - Science

IS - 6227

M1 - aaa4339

ER -

Modeling infectious disease dynamics in the complex landscape of global health

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Keywords

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