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The dynamics of measles in sub-Saharan Africa

Author

Listed:
  • Matthew J. Ferrari

    (Center for Infectious Disease Dynamics,)

  • Rebecca F. Grais

    (Epicentre)

  • Nita Bharti

    (Department of Biology and,)

  • Andrew J. K. Conlan

    (DAMTP, Centre for Mathematical Sciences, Wilberforce Road, Cambridge CB3 0WA, UK)

  • Ottar N. Bjørnstad

    (The Pennsylvania State University, University Park, Pennsylvania 16802, USA
    Fogarty International Center, National Institutes of Health, Bethesda, Maryland 20892, USA)

  • Lara J. Wolfson

    (World Health Organization, 20 Avenue Appia, CH-1211 Geneva 27, Switzerland)

  • Philippe J. Guerin

    (Epicentre)

  • Ali Djibo

    (Direction Generale de la Sante Publique, Ministere de la Sante, BP 623, Niamey, Niger)

  • Bryan T. Grenfell

    (Department of Biology and,
    Fogarty International Center, National Institutes of Health, Bethesda, Maryland 20892, USA)

Abstract

Although vaccination has almost eliminated measles in parts of the world, the disease remains a major killer in some high birth rate countries of the Sahel. On the basis of measles dynamics for industrialized countries, high birth rate regions should experience regular annual epidemics. Here, however, we show that measles epidemics in Niger are highly episodic, particularly in the capital Niamey. Models demonstrate that this variability arises from powerful seasonality in transmission—generating high amplitude epidemics—within the chaotic domain of deterministic dynamics. In practice, this leads to frequent stochastic fadeouts, interspersed with irregular, large epidemics. A metapopulation model illustrates how increased vaccine coverage, but still below the local elimination threshold, could lead to increasingly variable major outbreaks in highly seasonally forced contexts. Such erratic dynamics emphasize the importance both of control strategies that address build-up of susceptible individuals and efforts to mitigate the impact of large outbreaks when they occur.

Suggested Citation

  • Matthew J. Ferrari & Rebecca F. Grais & Nita Bharti & Andrew J. K. Conlan & Ottar N. Bjørnstad & Lara J. Wolfson & Philippe J. Guerin & Ali Djibo & Bryan T. Grenfell, 2008. "The dynamics of measles in sub-Saharan Africa," Nature, Nature, vol. 451(7179), pages 679-684, February.
  • Handle: RePEc:nat:nature:v:451:y:2008:i:7179:d:10.1038_nature06509
    DOI: 10.1038/nature06509
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    Cited by:

    1. van de Water, Antoinette & Henley, Michelle & Bates, Lucy & Slotow, Rob, 2022. "The value of elephants: A pluralist approach," Ecosystem Services, Elsevier, vol. 58(C).
    2. Wayne M. Getz & Jean-Paul Gonzalez & Richard Salter & James Bangura & Colin Carlson & Moinya Coomber & Eric Dougherty & David Kargbo & Nathan D. Wolfe & Nadia Wauquier, 2015. "Tactics and Strategies for Managing Ebola Outbreaks and the Salience of Immunization," Post-Print hal-01214432, HAL.
    3. Alexander D Becker & Bryan T Grenfell, 2017. "tsiR: An R package for time-series Susceptible-Infected-Recovered models of epidemics," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-10, September.
    4. Daniel M. Parker & James W. Wood & Shinsuke Tomita & Sharon DeWitte & Julia Jennings & Liwang Cui, 2014. "Household ecology and out-migration among ethnic Karen along the Thai-Myanmar border," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(39), pages 1129-1156.
    5. Jijun Zhao & Xinmin Li, 2016. "Determinants of the Transmission Variation of Hand, Foot and Mouth Disease in China," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-14, October.
    6. Wan Yang & Liang Wen & Shen-Long Li & Kai Chen & Wen-Yi Zhang & Jeffrey Shaman, 2017. "Geospatial characteristics of measles transmission in China during 2005−2014," PLOS Computational Biology, Public Library of Science, vol. 13(4), pages 1-21, April.
    7. Pang, Liuyong & Ruan, Shigui & Liu, Sanhong & Zhao, Zhong & Zhang, Xinan, 2015. "Transmission dynamics and optimal control of measles epidemics," Applied Mathematics and Computation, Elsevier, vol. 256(C), pages 131-147.
    8. Delin Meng & Jun Xu & Jijun Zhao, 2021. "Analysis and prediction of hand, foot and mouth disease incidence in China using Random Forest and XGBoost," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-16, December.

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