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The impact of a physical geographic barrier on the dynamics of measles

  • A. VORA (a1), D. S. BURKE (a2) (a3) and D. A. T. CUMMINGS (a2) (a3)

Spatial–temporal patterns of measles incidence reflect the spatial distribution of human hosts. The heterogeneous spatial distribution of communities has been shown to introduce spatially dependent temporal lags in the timing of measles incidence. Incidence patterns reflect internal dynamics within a community and coupling of communities through the movement of infectious individuals. The central role of human movement in coupling dynamics in separate communities suggests that physical geographic barriers to movement should reduce spatial–temporal correlation. We examine measles dynamics in Maryland and Pennsylvania during the period of 1917–1938. The central feature of interest is the Chesapeake Bay, which separates Maryland into two distinct regions. We find that correlation of measles incidences in communities separated by the bay is reduced compared to communities not separated by the bay, suggesting the bay acted as a barrier to human movement during this time sufficient to decouple measles dynamics in Maryland counties.

Corresponding author
*Author for correspondence: Dr D. A. T. Cummings, Department of Epidemiology, Bloomberg School of Public Health, 615 N. Wolfe Street, Rm. E6138, Baltimore, MD 21205, USA. (Email:
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1. London WP, Yorke JA. Recurrent outbreaks of measles, chickenpox and mumps. 1. Seasonal variation in contact rates. American Journal of Epidemiology 1973; 98: 453468.
2. Grenfell BT, Bolker BM. Cities and villages: infection hierarchies in a measles metapopulation. Ecology Letters 1998; 1: 6370.
3. Earn DJD, et al. A simple model for complex dynamical transitions in epidemics. Science 2000; 287: 667670.
4. Grenfell BT, Bjornstad ON, Finkenstadt BF. Dynamics of measles epidemics: scaling noise, determinism, and predictability with the TSIR model. Ecological Monographs 2002; 72: 185202.
5. Bartlett MS. Deterministic and stochastic models for recurrent epidemics. Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability 1956; 4: 81109.
6. Smith DL, et al. Predicting the spatial dynamics of rabies epidemics on heterogeneous landscapes. Proceedings of the National Academy of Sciences USA 2002; 99: 36683672.
7. Tidd CW, Olsen LF, Schaffer WM. The case for chaos in childhood epidemics. 2. Predicting historical epidemics from mathematical models. Proceedings of the Royal Society of London, Series B: Biological Sciences 1993; 254: 257273.
8. Cliff AD, et al. The changing geographical coherence of measles morbidity in the United States, 1962–88. Statistics in Medicine 1992; 11: 14091424.
9. Grenfell BT, Bjornstad ON, Kappey J. Travelling waves and spatial hierarchies in measles epidemics. Nature 2001; 414: 716723.
10. Cummings DAT, et al. Improved measles surveillance in Cameroon reveals two major dynamic patterns of incidence. International Journal of Infectious Diseases 2006; 10: 148155.
11. Vital Statistics Bureau, State of Pennsylvania. Vital Statistics Bulletin of the State of Pennsylvania. Pennsylvania, US, 1917.
12. State Board of Health of Maryland. Annual Report of the State Board of Health of Maryland for the year ending December 31, 1917–1938. Maryland, United States, 1917–1938.
13. Sydenstricker E, Collins SDW. Age incidence of communicable diseases in a rural population. Public Health Reports 1931, 1443.
14. Sydenstricker E. Hagerstown morbidity studies. Public Health Reports 1926, 1113.
15. Torrence C, Compo GP. A practical guide to wavelet analysis. Bulletin of the American Meteorological Society 1998; 79: 6178.
16. Bjornstad ON, Falck W. Nonparametric spatial covariance functions: estimation and testing. Environmental and Ecological Statistics 2001; 8: 5370.
17. Everitt B. Cluster Analysis. London: Heinemann Educational Books, 1974.
18. Hartigan JA, Wong MA. Algorithm AS 136: a K-means clustering algorithm. Applied Statistics 1979; 28: 100108.
19. Xia YC, Bjornstad ON, Grenfell BT. Measles metapopulation dynamics: a gravity model for epidemiological coupling and dynamics. American Naturalist 2004; 164: 267281.
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Epidemiology & Infection
  • ISSN: 0950-2688
  • EISSN: 1469-4409
  • URL: /core/journals/epidemiology-and-infection
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