Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-26T21:50:34.617Z Has data issue: false hasContentIssue false
  • English
  • Français

The population ecology of infectious diseases: pertussis in Thailand as a case study

Published online by Cambridge University Press:  13 April 2012

J. C. BLACKWOOD ,
D. A. T. CUMMINGS ,
H. BROUTIN ,
S. IAMSIRITHAWORN  and
P. ROHANI
J. C. BLACKWOOD*
Affiliation:
Department of Ecology & Evolutionary Biology University of Michigan, Ann Arbor, MI 48109, USA and Center for the Study of Complex Systems University of Michigan, Ann Arbor, MI 48109, USA
D. A. T. CUMMINGS
Affiliation:
Johns Hopkins Bloomberg School of Public Health Baltimore, MD 21205, USA Fogarty International Center, National Institutes of Health Bethesda, MD 20892, USA
H. BROUTIN
Affiliation:
MIVEGEC, UMR CNRS 5290-IRD 224-UM1-UM2 Centre de recherche IRD 911 Avenue Agropolis BP 64501 34394 Montpellier Cédex 5, France
S. IAMSIRITHAWORN
Affiliation:
Bureau of Epidemiology, Ministry of Public Health Nonthaburi, Thailand
P. ROHANI
Affiliation:
Department of Ecology & Evolutionary Biology University of Michigan, Ann Arbor, MI 48109, USA and Center for the Study of Complex Systems University of Michigan, Ann Arbor, MI 48109, USA Fogarty International Center, National Institutes of Health Bethesda, MD 20892, USA
*
*Corresponding author: Phone:(734) 615-4646. E-mail: juliecb@umich.edu
Get access Rights & Permissions [Opens in a new window]

Summary

Many of the fundamental concepts in studying infectious diseases are rooted in population ecology. We describe the importance of population ecology in exploring central issues in infectious disease research including identifying the drivers and dynamics of host-pathogen interactions and pathogen persistence, and evaluating the success of public health policies. The use of ecological concepts in infectious disease research is demonstrated with simple theoretical examples in addition to an analysis of case notification data of pertussis, a childhood respiratory disease, in Thailand as a case study. We stress that further integration of these fields will have significant impacts in infectious diseases research.

Keywords

Population ecologyspatio-temporal dynamicspersistencepertussis
Type
Research Article
Information
Parasitology , Volume 139 , Issue 14: Dynamics of parasite distributions: modern analytical approaches , December 2012 , pp. 1888 - 1898
Copyright
Copyright © Cambridge University Press 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Altizer, S., Dobson, A., Hosseini, P., Hudson, P., Pascual, M. and Rohani, P. (2006). Seasonality and the dynamics of infectious diseases. Ecology Letters 9, 467–484.CrossRefGoogle ScholarPubMed
Anderson, R. M. and May, R. M. (1979). Population biology of infectious diseases: Part I. Nature 280, 361–367.CrossRefGoogle ScholarPubMed
Anderson, R. M. and May, R. M. (1991). Infectious Diseases of Humans. Oxford University Press, New York.CrossRefGoogle Scholar
Bailey, N. T. J. (1975). The Mathematical Theory of Infectious Diseases and its Applications. Griffin, London.Google Scholar
Bartlett, M. S. (1957). Measles periodicity and community size. Journal of the Royal Statistical Society Series A (General) 120(1), 48–70.CrossRefGoogle Scholar
Bass, J. W. and Stephenson, S. R. (1987). The return of pertussis. Pediatric Infectious Disease Journal 6, 141–144.CrossRefGoogle ScholarPubMed
Bauch, C. T. and Earn, D. J. D. (2003). Transients and attractors in epidemics. Proceedings of the Royal Society London B: Biological Sciences 270, 1573–1578.CrossRefGoogle ScholarPubMed
Bharti, N., Tatem, A. J., Ferrari, M. J., Grais, R. F., Djibo, A. and Grenfell, B. T. (2011). Explaining seasonal fluctuations of Measles in Niger using nighttime lights imagery. Science 334, 1424–1427.CrossRefGoogle ScholarPubMed
Bhunbhu, T. (1989). Expanded programme on immunization in Thailand. Reviews of Infectious Diseases 11, Supplement 3: S514–S517.CrossRefGoogle ScholarPubMed
Bjørnstad, O. N. and Falck, W. (2001). Nonparametric spatial covariance functions: Estimation and testing. Environmental and Ecological Statistics 8, 53–70.CrossRefGoogle Scholar
Bolker, B. M. and Grenfell, B. T. (1996). Impact of vaccination on the spatial correlation and persistence of measles dynamics. Proceedings of the National Academy of Sciences, USA 93, 12648–12653.CrossRefGoogle ScholarPubMed
Breban, R., Drake, J. M., Stallknecht, D. E. and Rohani, P. (2009). The role of environmental transmission in recurrent avian influenza epidemics. PLoS Computational Biology 5, e1000346.CrossRefGoogle ScholarPubMed
Broutin, H., Guegan, J. F., Elguero, E., Simondon, F. and Cazelles, B. (2005). Large-scale comparative analysis of pertussis population dynamics: periodicity, synchrony, and impact of vaccination. American Journal of Epidemiology 161, 1159–1167.CrossRefGoogle ScholarPubMed
Broutin, H., Simondon, F. and Guegan, J.-F. (2004). Whooping cough metapopulation dynamics in tropical conditions: disease persistence and impact of vaccination. Proceedings of the Royal Society Series B Biological Sciences 271, SupplementS302–S305.CrossRefGoogle ScholarPubMed
Broutin, H., Viboud, C., Grenfell, B. T., Miller, M. A. and Rohani, P. (2010). Impact of vaccination and birth rate on the epidemiology of pertussis: a comparative study in 64 countries. Proceedings of the Royal Society B Biological Sciences 277, 3239–3245.CrossRefGoogle ScholarPubMed
Brown, J. H. and Kodric-Brown, A. (1977). Turnover rates in insular biogeography: effect of immigration on extinction. Ecology 58, 445–449.CrossRefGoogle Scholar
Celentano, L. P., Massari, M., Paramatti, D., Salmaso, S. and Tozzi, A. E. (2005). Resurgence of pertussis in Europe. The Pediatric Infectious Disease Journal 24, 761–765.CrossRefGoogle ScholarPubMed
Chatfield, C. (1996). The Analysis of Time Series – An Introduction. 5th ed. Chapman and Hall, London.CrossRefGoogle Scholar
Choisy, M., Guégan, J.-F., and Rohani, P. (2006). Dynamics of infectious diseases and pulse vaccination: Teasing apart the embedded resonance effects. Physica D: Nonlinear Phenomena 223, 26–35.CrossRefGoogle Scholar
Conlan, A. J. K., Rohani, R., Lloyd, A. L., Keeling, M. and Grenfell, B. T. (2010). Resolving the impact of waiting time distributions on the persistence of measles. Journal of the Royal Society Interface 7, 623–640.CrossRefGoogle ScholarPubMed
Crowcroft, N. S. and Pebody, R. G. (2006). Recent developments in pertussis. Lancet 367, 1926–1936.CrossRefGoogle ScholarPubMed
Crowcroft, N. S., Stein, C., Duclos, P. and Birmingham, M. (2003). How to best estimate the global burden of pertussis? The Lancet Infectious Diseases 3, 413–418.CrossRefGoogle ScholarPubMed
Cummings, D. A. T., Iamsirithaworn, S., Lessler, J. T., McDermott, A., Prasanthong, R., Nisalak, A., Jarman, R. G., Burke, D. S. and Gibbons, R. V. (2009). The impact of the demographic transition on dengue in Thailand: Insights from a statistical analysis and mathematical modeling. PLoS Medicine 6(9), e1000139.CrossRefGoogle Scholar
Cummings, D. A. T., Irizarry, R. A., Huang, N. E., Endy, T. P., Nisalak, A., Ungchusak, K. and Burke, D. S. (2004). Travelling waves in the occurrence of dengue haemorrhagic fever in Thailand. Nature 427, 344–347.CrossRefGoogle ScholarPubMed
Dietz, K. (1976). The incidence of infectious diseases under the influence of seasonal fluctuations. In Lecture Notes in Biomathematics, vol. 11 (ed. Berger, J. et al. ), pp. 1–15. Springer, Berlin.Google Scholar
Dowell, S. F. (2001). Seasonal variation in host susceptibility and cycles of certain infectious diseases. Emerging Infectious Diseases 7, 369–374.CrossRefGoogle ScholarPubMed
Earn, D. J. D., Rohani, P., Bolker, B. M. and Grenfell, B. T. (2000). A simple model for complex dynamical transitions in epidemics. Science 287, 667–670.CrossRefGoogle ScholarPubMed
Earn, D. J. D., Rohani, P. and Grenfell, B. T. (1998). Synchronicity in ecology and epidemiology. Proceedings of the Royal Society of London B: Biological Sciences 265, 7–10.CrossRefGoogle Scholar
Ferrari, M. J., Grais, R. F., Bharti, N., Conlan, A. J. K., Bjørnstad, O. N., Wolfson, L. J., Guerin, P. J., Djibo, A. and Grenfell, B. T. (2008). The dynamics of measles in sub-Saharan Africa. Nature 451, 679–684.CrossRefGoogle ScholarPubMed
Fine, P. E. M. and Clarkson, J. A. (1982). Measles in England and Wales–i: An analysis of factors underlying seasonal patterns. International Journal of Epidemiology 11(1), 5–14.CrossRefGoogle ScholarPubMed
Finkenstädt, B. F., Bjørnstad, O. N. and Grenfell, B. T. (2002). A stochastic model for extinction and recurrence of epidemics: estimation and inference for measles outbreaks. Biostatistics 3, 493–510.CrossRefGoogle ScholarPubMed
Finkenstädt, B. F. and Grenfell, B. T. (2000). Time series modelling of childhood diseases: a dynamical systems approach. Applied Statistics 49, 187–205.Google Scholar
Grassly, N. C. and Fraser, C. (2006). Seasonal infectious disease epidemiology. Proceedings of the Royal Society B: Biological Sciences 273, 2541–2550.CrossRefGoogle ScholarPubMed
Grenfell, B. T., Bjørnstad, O. N. and Kappey, J. (2001). Travelling waves and spatial hierarchies in measles epidemics. Nature 414, 716–723.CrossRefGoogle ScholarPubMed
Grenfell, B. T. and Harwood, J. (1997). (Meta)population dynamics of infectious diseases. Trends in Ecology and Evolution 12, 395–399.CrossRefGoogle ScholarPubMed
Hamer, W. H. (1906). Epidemic disease in England. Lancet i, 733–739.Google Scholar
Hethcote, H. W. (1998). Oscillations in an endemic model for pertussis. Canadian Applied Mathematics Quarterly 6, 61–88.Google Scholar
Heymann, D. L. and Aylward, R. B. (2004). Eradicating polio. New England Journal of Medicine 351(13), 1275–1277.CrossRefGoogle ScholarPubMed
Hoshen, M. B. and Morse, A. P. (2004). A weather-driven model of malaria transmission. Malaria Journal 3, 32–46.CrossRefGoogle ScholarPubMed
Johansson, M. A., Cummings, D. A. T. and Glass, G. E. (2009). Multiyear climate variability and dengue? El Nino southern oscillation, weather, and dengue incidence in Puerto Rico, Mexico, and Thailand: A longitudinal data analysis. PLoS Medicine 6, e1000168.CrossRefGoogle ScholarPubMed
Keeling, M. J. and Rohani, P. (2008). Modeling Infectious Diseases in Humans and Animals, Princeton University Press, Princeton.CrossRefGoogle Scholar
London, W. P. and York, J. A. (1973). Recurrent outbreaks of measles, chickenpox and mumps I: seasonal variation in contact rates. American Journal of Epidemiology 98, 453–468.CrossRefGoogle ScholarPubMed
Mantilla-Beniers, N. B., Bjørnstad, O. N., Grenfell, B. T. and Rohani, P. (2010). Decreasing stochasticicty through enhanced seasonality in measles epidemics. Journal of the Royal Society Interface 7, 727–739.CrossRefGoogle ScholarPubMed
Metcalf, C. J. E., Bjørnstad, O. N., Grenfell, B. T. and Andreasen, V. (2009). Seasonality and comparative dynamics of six childhood infections in pre-vaccination Copenhagen. Proceedings of the Royal Society B: Biological Sciences 276, 4111–4118.CrossRefGoogle ScholarPubMed
Metcalf, C. J. E., Munayco, C. V., Chowell, G., Grenfell, B. T. and Bjørnstad, O. N. (2010). Rubella metapopulation dynamics and the importance of spatial coupling to the risk of congenital rubella syndrome in Peru. Journal of the Royal Society Interface 8, 369–376. doi: 10.1098/rsif.2010.0320CrossRefGoogle Scholar
National Statistical Office of Thailand (1980). 1980 census. Technical report, Bangkok: National Statistical Office of Thailand.Google Scholar
National Statistical Office of Thailand (1991). 1990 census. Technical report, Bangkok: National Statistical Office of Thailand.Google Scholar
National Statistical Office of Thailand (2001). 2000 census. Technical report, Bangkok: National Statistical Office of Thailand.Google Scholar
Nee, S. (1994). How populations persist. Nature 367, 123–124.CrossRefGoogle Scholar
Nokes, D. J. and Swinton, J. (1997). Vaccination in pulses: a strategy for global eradication of measles and polio? Trends in Microbiology 5, 14–19.CrossRefGoogle ScholarPubMed
Rohani, P., Earn, D. J. D. and Grenfell, B. T. (1999). Opposite patterns of synchrony in sympatric disease metapopulations. Science 286, 968–971.CrossRefGoogle ScholarPubMed
Rohani, P., Earn, D. J. D. and Grenfell, B. T. (2000). Impact of immunisation on pertussis transmission in England and Wales. Lancet 355, 285–286.CrossRefGoogle ScholarPubMed
Rohani, P. and King, A. A. (2010). Never mind the length, feel the quality: Long-term epidemiological data in theory, application and policy. Trends in Ecology and Evolution 25, 611–618.CrossRefGoogle ScholarPubMed
Shaman, J., Pitzer, V. E., Viboud, C., Grenfell, B. T. and Lipsitch, M. (2010). Absolute humidity and the seasonal onset of influenza in the continental United States. PLoS Biology 8(2), e1000316.CrossRefGoogle ScholarPubMed
Soper, H. E. (1929). The interpretation of periodicity in disease prevalence. Journal of the Royal Statistical Society 92(1), 34–73.CrossRefGoogle Scholar
Thai, K. T. D., Cazelles, B., Nguyen, N. V., Vo, L. T., Boni, M. F., Farrar, J., Simmons, C. P., Rogier van Doorn, H. and de Vries, P. J. (2010). Dengue dynamics in Binh Thuan province, southern Vietnam: Periodicity, synchronicity and climate variability. PLoS Neglected Tropical Diseases 4(7), e747.CrossRefGoogle ScholarPubMed
Torrence, C. and Compo, G. P. (1998 a). Wavelet Software, available at http://paos.colorado.edu/research/wavelets/software.html.Google Scholar
Torrence, C. and Compo, G. P. (1998 b). A practical guide to wavelet analysis. Bulletin of the American Meteorological Society 79, 61–78.2.0.CO;2>CrossRefGoogle Scholar
Viboud, C., Bjørnstad, O. N., Smith, D. L., Simonsen, L., Miller, M. A. and Grenfell, B. T. (2006). Synchrony, waves, and spatial hierarchies in the spread of influenza. Science, 312, 447–451.CrossRefGoogle ScholarPubMed
Watts, D., Burke, D., Harrison, B., Whitmore, R. and Nisalak, A. (1987). Effect of temperature on the vector efficiency of Aedes aegypt} for dengue 2 virus. American Journal of Tropical Medicine and Hygiene 36, 143–152.CrossRefGoogle Scholar
Wearing, H. J. and Rohani, P. (2009). Estimating the duration of pertussis immunity using epidemiological signatures. PLoS Pathogens 5(10), e1000647.CrossRefGoogle ScholarPubMed
Supplementary material: PDF

Blackwood supplementary material

Blackwood supplementary material

Download Blackwood supplementary material(PDF)
PDF 44.1 KB