Spatial and Temporal Dynamics of Rubella in Peru, 1997–2006: Geographic Patterns, Age at Infection and Estimation of Transmissibility

  • Daniel Rios-Doria
  • Gerardo Chowell
  • Cesar Munayco-Escate
  • Alvaro Witthembury
  • Carlos Castillo-Chavez

Abstract

Detailed studies on the spatial and temporal patterns of rubella transmission are scarce particularly in developing countries but could prove useful in improving epidemiological surveillance and intervention strategies such as vaccination. We use highly refined spatial, temporal and age-specific incidence data of Peru, a geographically diverse country, to quantify spatial-temporal patterns of incidence and transmissibility for rubella during the period 1997–2006. We estimate the basic reproduction number (R0) based on the mean age at infection and the per capita birth rate of the population as well as the reproduction number (accounting for the fraction of the population effectively protected to infection) using the initial intrinsic growth rate of individual outbreaks and estimates of epidemiological parameters for rubella. A wavelet time series analysis is conducted to explore the periodicity of the rubella weekly time series, and the results of our analyses are compared to those carried out for time series of other childhood infectious diseases. We also identify the presence of a critical community size and quantify spatial heterogeneity across geographic regions through the use of Lorenz curves and their corresponding Gini indices. The underlying distributions of rubella outbreak attack rates and epidemic durations across Peru are characterized.

Keywords

Rubella Peru Epidemic Periodicity Reproduction number Age at infection 

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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Daniel Rios-Doria
    • 1
    • 2
  • Gerardo Chowell
    • 3
    • 4
    • 5
  • Cesar Munayco-Escate
    • 6
  • Alvaro Witthembury
    • 7
  • Carlos Castillo-Chavez
    • 8
    • 9
    • 10
    • 11
  1. 1.School of Human Evolution and Social ChangeArizona State UniversityTempeUSA
  2. 2.Mathematical, Computational, Modeling Sciences CenterArizona State UniversityTempeUSA
  3. 3.School of Human Evolution and Social ChangeArizona State UniversityTempeUSA
  4. 4.Mathematical, Computational, Modeling Sciences CenterArizona State UniversityTempeUSA
  5. 5.Division of Epidemiology and Population Studies, Fogarty International Center, National Institutes of HealthBethesdaUSA
  6. 6.Dirección General de Epidemiología, Ministerio de Salud, Perú, Jr. Camilo-Carrillo 402Peru
  7. 7.Dirección General de Epidemiología, Ministerio de Salud, Perú, Jr. Camilo-Carrillo 402Perú
  8. 8.Mathematical, Computational, and Modeling Sciences Center, P.O. Box 871904Arizona State UniversityTempeUSA
  9. 9.School of Human Evolution and Social ChangeArizona State UniversityTempeUSA
  10. 10.Department of Mathematics and StatisticsArizona State UniversityTempeUSA
  11. 11.Santa Fe InstituteSanta FeUSA

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