Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Refractory periods and climate forcing in cholera dynamics


Outbreaks of many infectious diseases, including cholera, malaria and dengue, vary over characteristic periods longer than 1 year1,2. Evidence that climate variability drives these interannual cycles has been highly controversial, chiefly because it is difficult to isolate the contribution of environmental forcing while taking into account nonlinear epidemiological dynamics generated by mechanisms such as host immunity2,3,4. Here we show that a critical interplay of environmental forcing, specifically climate variability, and temporary immunity explains the interannual disease cycles present in a four-decade cholera time series from Matlab, Bangladesh. We reconstruct the transmission rate, the key epidemiological parameter affected by extrinsic forcing, over time for the predominant strain (El Tor) with a nonlinear population model that permits a contributing effect of intrinsic immunity. Transmission shows clear interannual variability with a strong correspondence to climate patterns at long periods (over 7 years, for monsoon rains and Brahmaputra river discharge) and at shorter periods (under 7 years, for flood extent in Bangladesh, sea surface temperatures in the Bay of Bengal and the El Niño–Southern Oscillation). The importance of the interplay between extrinsic and intrinsic factors in determining disease dynamics is illustrated during refractory periods, when population susceptibility levels are low as the result of immunity and the size of cholera outbreaks only weakly reflects climate forcing.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Time series of cholera cases from 1966 to 2002, aggregated monthly.
Figure 2: Results of the nonlinear disease model.
Figure 3: Cholera refractory periods.
Figure 4: Environmental drivers and transmission.

Similar content being viewed by others


  1. Bouma, M. J. & Pascual, M. Seasonal and interannual cycles of endemic cholera in Bengal 1891–1940 in relation to climate and geography. Hydrobiologia 460, 147–156 (2001)

    Article  Google Scholar 

  2. Hay, S. I. et al. Etiology of interepidemic periods of mosquito-borne disease. Proc. Natl Acad. Sci. USA 97, 9335–9339 (2000)

    Article  ADS  CAS  Google Scholar 

  3. Taubes, G. Global warming: Apocalypse Not. Science 278, 1004–1006 (1997)

    Article  ADS  CAS  Google Scholar 

  4. Rogers, D. J. et al. Satellite imagery in the study and forecast of malaria. Nature 415, 710–715 (2002)

    Article  CAS  Google Scholar 

  5. Anderson, R. M. & May, R. M. Infectious Diseases of Humans: Dynamics and Control (Oxford Univ. Press, Oxford, 1991)

    Google Scholar 

  6. Schwartz, I. B. Small amplitude, long period outbreaks in seasonally driven epidemics. J. Math. Biol. 30, 473–491 (1992)

    Article  MathSciNet  CAS  Google Scholar 

  7. Zhou, G. et al. Association between climate variability and malaria epidemics in the East African highlands. Proc. Natl Acad. Sci. USA 101, 2375–2380 (2004)

    Article  ADS  CAS  Google Scholar 

  8. Pascual, M. et al. Cholera dynamics and El Niño–Southern Oscillation. Science 289, 1766–1769 (2000)

    Article  ADS  CAS  Google Scholar 

  9. Glass, R. I. et al. Endemic cholera in rural Bangladesh, 1966–1980. Am. J. Epidemiol. 116, 959–970 (1982)

    Article  CAS  Google Scholar 

  10. Koelle, K. & Pascual, M. Disentangling extrinsic from intrinsic factors in disease dynamics: a nonlinear time series approach with an application to cholera. Am. Nat. 163, 901–913 (2004)

    Article  Google Scholar 

  11. Lui, W. M., Hethcote, H. W. & Levin, S. A. Dynamical behaviour of epidemiological models with nonlinear incidence rates. J. Math. Biol. 25, 359–380 (1987)

    Article  MathSciNet  Google Scholar 

  12. de Jong, M. C. M., Diekmann, O. & Heesterbeek, H. in Epidemic Models: Their Structure and Relation to Data (ed. Mollison, D.) 84–94 (Cambridge Univ. Press, Cambridge, 1995)

    Google Scholar 

  13. Hastie, T. J. & Tibshirani, R. J. Generalized Additive Models. Monographs on Statistics and Applied Probability (Chapman & Hall, London, 1990)

    Google Scholar 

  14. Levine, M. M. & Pierce, N. F. in Cholera (eds Barua, D. & Greenough, W. B.) 285–327 (Plenum Medical, New York, 1992)

    Book  Google Scholar 

  15. Clemens, J. D. et al. Biotype as determinant of natural immunising effect of cholera. Lancet 337, 883–884 (1991)

    Article  CAS  Google Scholar 

  16. Pascual, M., Bouma, M. & Dobson, A. P. Cholera and climate: revisiting the quantitative evidence. Microbes Infect. 4, 237–245 (2002)

    Article  Google Scholar 

  17. Rodó, X. et al. ENSO and cholera: A nonstationary link related to climate change? Proc. Natl Acad. Sci. USA 99, 12901–12906 (2002)

    Article  ADS  Google Scholar 

  18. Parthasarathy, B., Munot, A. A. & Kothwale, D. R. Monthly and Seasonal Rainfall Series for all-India Homogeneous Regions and Meteorological Subdivisions: 1871–1994 (Research Report RR-065, Indian Institute of Tropical Meteorology, Pune, 1995)

    Google Scholar 

  19. Siddique, A. K. et al. Survival of classic cholera in Bangladesh. Lancet 337, 1125–1127 (1991)

    Article  CAS  Google Scholar 

  20. Kawamura, R. A possible mechanism of the Asian summer monsoon–ENSO coupling. J. Met. Soc. Jpn 76–1027 (1998)

  21. Shukla, J. & Fennessy, M. J. Simulation and Predictability of Monsoons 567–575 (Proc. Int. Conf. on Monsoon Variability and Prediction, Technical Report WCRP-84, World Climate Research Programme, Geneva, 1994)

    Google Scholar 

  22. Lau, N.-C. & Nath, M. J. Impact of ENSO on the variability of the Asian–Australian monsoons as simulated in GCM experiments. J. Clim. 13, 4287–4309 (2000)

    Article  ADS  Google Scholar 

  23. Lau, N.-C. & Nath, M. J. Coupled GCM simulation of atmosphere–ocean variability associated with zonally asymmetric SST changes in the tropical Indian Ocean. J. Clim. 17, 245–265 (2004)

    Article  ADS  Google Scholar 

  24. Webster, P. J. et al. in Meteorology at the Millennium. Int. Geophys. Series Vol. 83, 198–219 (Academic, New York, 2002)

    Book  Google Scholar 

  25. Dixon, P. A., Milicich, M. J. & Sugihara, G. Episodic fluctuations in larval supply. Science 283, 1528–1530 (1999)

    Article  ADS  CAS  Google Scholar 

  26. Elsner, J. B. & Tsonis, A. A. Singular Spectrum Analysis: A New Tool in Time Series Analysis (Plenum, New York, 1996)

    Book  Google Scholar 

  27. Kaplan, D. & Glass, L. Understanding Nonlinear Dynamics. Text in Applied Mathematics (eds Marsden, J. E. et al.) 342–346 (Springer, New York, 1995)

    Book  Google Scholar 

  28. Waldor, M. K., Colwell, R. & Mekalanos, J. J. The Vibrio cholerae 0139 serogroup antigen includes an O-antigen capsule and lipopolysaccharide virulence determinants. Proc. Natl Acad. Sci. USA 91, 11388–11392 (1994)

    Article  ADS  CAS  Google Scholar 

  29. Glass, R. I. & Black, R. E. in Cholera (eds Barua, D. & Greenough, W. B.) 129–154 (Plenum Medical, New York, 1992)

    Book  Google Scholar 

  30. Woodward, W. E. & Mosley, W. H. The spectrum of cholera in rural Bangladesh. II. Comparison of El Tor Ogawa and Classical Inaba infection. Am. J. Epidemiol. 96, 342–351 (1972)

    Article  CAS  Google Scholar 

Download references


We thank B. Sack for discussions on cholera immunity, K. Streatfield for support with the cholera data, A. Dobson for comments on the manuscript, P. Webster and the Climate Forecast Applications Project at Georgia Tech for the river discharge data, and the Bangladesh Water Development Board, Dhaka, Bangladesh, for flood area data. M.P. acknowledges the joint support of the NSF-NIH (Ecology of Infectious Diseases) and NOAA (Oceans and Health), as well as funding from NOAA's Joint Program on Climate Variability and Human Health, with EPRI–NSF–NASA, under which the work was initiated. Further support was provided by the James S. McDonnell Foundation Centennial fellowship to M.P. and by ICREA and an AGAUR-DURSI grant to X.R.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Mercedes Pascual.

Ethics declarations

Competing interests

Reprints and permissions information is available at The authors declare no competing financial interests.

Supplementary information

Supplementary Notes

This contains text on the statistical procedure for fitting the extended nonlinear disease model. It also contains three Supplementary Figures. Supplementary Figure S1 presents the results of the Scale-Dependent Correlation (SDC) analysis, revealing that only one particular biotype at a time is responsible for the response of cases to climate for a given El Niño event. Supplementary Figure S2 shows that the 1982-83 ENSO years exhibited intense drought conditions with a comparison between rainfall deviations for the 1982/1983 El Niño event and deviations for the other El Niño events over the time period 1976-2003. Supplementary Figure S3 provides evidence for the uniqueness of this drought's spatial extent. (PDF 587 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Koelle, K., Rodó, X., Pascual, M. et al. Refractory periods and climate forcing in cholera dynamics. Nature 436, 696–700 (2005).

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI:

This article is cited by


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing