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Unraveling R0: Considerations for public health applications

Author

Listed:
  • Ridenhour, B.
  • Kowalik, J.M.
  • Shay, D.K.

Abstract

We assessed public health use of R0, the basic reproduction number, which estimates the speed at which a disease is capable of spreading in a population. These estimates are of great public health interest, as evidenced during the 2009 influenza A (H1N1) virus pandemic. We reviewed methods commonly used to estimate R0, examined their practical utility, and assessed how estimates of this epidemiological parameter can inform mitigation strategy decisions. In isolation, R0 is a suboptimal gauge of infectious disease dynamics across populations; other disease parameters may provide more useful information. Nonetheless, estimation of R0 for a particular population is useful for understanding transmission in the study population. Considered in the context of other epidemiologically important parameters, the value of R 0 may lie in better understanding an outbreak and in preparing a public health response.

Suggested Citation

  • Ridenhour, B. & Kowalik, J.M. & Shay, D.K., 2014. "Unraveling R0: Considerations for public health applications," American Journal of Public Health, American Public Health Association, vol. 104(2), pages 32-41.
  • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2013.301704_9
    DOI: 10.2105/AJPH.2013.301704
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    Cited by:

    1. Christopher Avery & William Bossert & Adam Clark & Glenn Ellison & Sara Fisher Ellison, 2020. "Policy Implications of Models of the Spread of Coronavirus: Perspectives and Opportunities for Economists," NBER Working Papers 27007, National Bureau of Economic Research, Inc.
    2. Jude Dzevela Kong & Edward W Tekwa & Sarah A Gignoux-Wolfsohn, 2021. "Social, economic, and environmental factors influencing the basic reproduction number of COVID-19 across countries," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-17, June.
    3. Gilgur, Alexander & Ramirez-Marquez, Jose Emmanuel, 2022. "Modeling mobility, risk, and pandemic severity during the first year of COVID," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    4. Na, Jiaming & Tibebu, Haileleol & De Silva, Varuna & Kondoz, Ahmet & Caine, Michael, 2020. "Probabilistic approximation of effective reproduction number of COVID-19 using daily death statistics," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    5. Christopher Avery & William Bossert & Adam Thomas Clark & Glenn Ellison & Sara Ellison, 2020. "Policy Implications of Models of the Spread of Coronavirus: Perspectives and Opportunities for Economists," CESifo Working Paper Series 8293, CESifo.
    6. Qasim Bukhari & Joseph M. Massaro & Ralph B. D’Agostino & Sheraz Khan, 2020. "Effects of Weather on Coronavirus Pandemic," IJERPH, MDPI, vol. 17(15), pages 1-12, July.
    7. Mark C. Quigley & Januka Attanayake & Andrew King & Fabian Prideaux, 2020. "A multi-hazards earth science perspective on the COVID-19 pandemic: the potential for concurrent and cascading crises," Environment Systems and Decisions, Springer, vol. 40(2), pages 199-215, June.

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