Impact of birth rate, seasonality and transmission rate on minimum levels of coverage needed for rubella vaccination

Epidemiology and Infection

Volumn 140, Issue 12, 2012, Pages 2290-2301

  Metcalf, C J E ^a,b   Lessler, J ^c   Klepac, P ^b   Cutts, F ^d   Grenfell, B T ^b,e  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b PRINCETON UNIVERSITY   (United States)

^c JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

^d LONDON SCHOOL OF HYGIENE AND TROPICAL MEDICINE   (United Kingdom)

^e NATIONAL INSTITUTES OF HEALTH   (United States)

Author keywords

CRS; demography; extinction; rubella; seasonality; vaccine coverage

Indexed keywords

RUBELLA VACCINE;

ARTICLE; BIRTH RATE; COHORT ANALYSIS; CONGENITAL RUBELLA SYNDROME; DEMOGRAPHY; DISEASE TRANSMISSION; DRUG SAFETY; EPIDEMIC; GROUPS BY AGE; HEALTH CARE POLICY; HUMAN; NONHUMAN; NONLINEAR SYSTEM; RUBELLA VIRUS; SEASONAL VARIATION; VACCINATION; WORLD HEALTH ORGANIZATION;

AGE FACTORS; BIRTH RATE; CHILD; CHILD, PRESCHOOL; DEMOGRAPHY; FEMALE; HUMANS; IMMUNITY, HERD; INFANT; INFECTIOUS DISEASE TRANSMISSION, VERTICAL; MASS VACCINATION; MODELS, BIOLOGICAL; PREGNANCY; PREGNANCY COMPLICATIONS, INFECTIOUS; RUBELLA SYNDROME, CONGENITAL; RUBELLA VACCINE; RUBELLA VIRUS; SEASONS; WORLD HEALTH;

EID: 84869411926     PISSN: 09502688     EISSN: 14694409     Source Type: Journal    
DOI: 10.1017/S0950268812000131     Document Type: Article

References (38)

1. Gregg NM. Congenital defects associated with maternal rubella. The Australian Hospital 1947; 14: 7-9.
2. Hinman AR, et al. Economic analyses of rubella and rubella vaccines : a global review. Bulletin of the World Health Organization 2002; 80(4).
3. World Health Organization. Rubella vaccines : WHO position paper. Weekly Epidemiological Record 2011; 86: 301-316.
4. Anderson RM, May RM. Vaccination and herd immunity to infectious diseases. Nature 1985; 318: 323- 329. (Pubitemid 16198489)
5. Anderson RM, May RM. Vaccination against rubella and measles: qualitative investigations of different policies. Journal of Hygiene (Cambridge) 1983; 90: 259-325. (Pubitemid 13086184)
6. Edmunds WJ, et al. The pre-vaccination epidemiology of measles, mumps and rubella in Europe: implications for modelling studies. Epidemiology and Infection 2000; 125: 635-650. (Pubitemid 32156852)
7. Gay N. Modeling measles, mumps, and rubella : Implications for the design of vaccination programs. Fifth International Conference on the Prevention of Infection 1998; 19: 570-573. (Pubitemid 128472681)
8. van der Heilden OG, et al. A model-based evaluation of the national immunization programme against rubella infection and congenital rubella syndrome in the Netherlands. Epidemiology and Infection 1998; 121: 653-671.
9. Bjørnstad ON, Finkenstadt B, Grenfell BT. Endemic and epidemic dynamics of measles: Estimating epidemiological scaling with a time series SIR model. Ecological Monographs 2002; 72: 169-184. (Pubitemid 36198821)
10. Keeling MJ, Rohani P, Grenfell BT. Seasonally forced disease dynamics explored as switching between attractors. Physica D 2001; 148: 317-335. (Pubitemid 33651593)
11. Bauch CT, Earn DJD. Transients and attractors in epidemics. Proceedings of the Royal Society of London, Series B 2003; 270: 1573-1578. (Pubitemid 36960287)
12. Knox EG. Strategy for rubella vaccination. International Journal of Epidemiology 1980; 9: 13-23. (Pubitemid 10122672)
13. World Health Organization. Rubella vaccine: WHO position paper. Weekly Epidemiological Record 2000; 75: 161-172.
14. World Health Organization. Meeting of the Strategic Advisory Group of Experts on Immunization, April 2011 - conclusions and recommendations. Weekly Epidemiological Record 2011; 86: 205-220.
15. Vynnycky E, Gay NJ, Cutts FT. The predicted impact of private sector MMR vaccination on the burden of congenital rubella syndrome. Vaccine 2003; 21: 2708- 2719. (Pubitemid 36703181)
16. World Health Organization. Global reductions in measles mortality 2000-2008 and the risk of measles resurgence. Weekly Epidemiological Record 2009; 49: 505-516.
17. Cutts FT, Vynnycky E. Modelling the incidence of congenital rubella syndrome in developing countries. International Journal of Epidemiology 1999; 28: 1176- 1184. (Pubitemid 30021322)
18. Cutts FT, et al. Sero-epidemiology of rubella in the urban population of Addis Ababa, Ethiopia. Epidemiology and Infection 2000; 124: 467-479. (Pubitemid 30623864)
19. Farrington CP, Kanaan MN, Gay NJ. Estimation of the basic reproduction number for infectious diseases from age-stratified serological survey data. Applied Statistics 2001; 50: 251-292. (Pubitemid 33297023)
20. Rios-Doria D, et al. Spatial and temporal dynamics of rubella in Peru, 1997-2006: geographic patterns, age at infection and estimation of transmissibility. In Chowell EA, ed. Mathematical and Statistical Estimation Approaches in Epidemiology. The Netherlands: Springer, 2009.
21. Metcalf CJE, et al. The epidemiology of rubella in Mexico: seasonality, stochasticity and regional variation. Epidemiology and Infection 2011; 139: 1029-1038.
22. Metcalf CJE, et al. Rubella meta-population dynamics and importance of spatial coupling to the risk of congenital rubella syndrome in Peru. Journal of the Royal Society Interface 2011; 8: 369-376.
23. Ferrari MJ, et al. The dynamics of measles in sub- Saharan Africa. Nature 2008; 451: 679-684. (Pubitemid 351220562)
24. Ferrari MJ, et al. Episodic outbreaks bias estimates of age specific force of infection : a corrected method using measles in Niamey, Niger as an example. Epidemiology and Infection 2010; 138: 108-116.
25. Klepac P, Caswell H. The stage-structured epidemic: linking disease and demography with a multi-state matrix approach. Theoretical Ecology 2010; 4: 301-319.
26. Klepac P, et al. Stage structured transmission of phocine distemper virus in the Dutch 2002 outbreak. Proceedings of the Royal Society, Series B 2009; 276: 2469-2476
27. Metcalf CJE, et al. Structured models of infectious disease : inference with discrete data. Theoretical Population Biology (in press).
28. Schenzle D. Estimation of the basic reproduction number for infectious diseases from age-stratified serological survey data. IMA Journal of Mathematics Applied in Medicine and Biology 1984; 1: 161-191.
29. Finkenstadt B, Grenfell BT. Time series modelling of childhood diseases : a dynamical systems approach. Journal of the Royal Statistical Society, Series C 2000; 49: 187-205.
30. Glass K, Xia Y, Grenfell BT. Interpreting time-series analyses for continuous-time biological models-measles as a case study. Journal of Theoretical Biology 2003; 223: 19-25. (Pubitemid 36637019)
31. Lessler J, et al. Maintaining high rates of measles immunization in Africa. Epidemiology and Infection 2010; 139; 1039-1049.
32. Boulianne N, et al. Measles, mumps, and rubella antibodies in children 5-6 years after immunization: effect of vaccine type and age at vaccination. Vaccine 1995; 13: 1611-1616.
33. Grenfell BT, Anderson RM. The estimation of agerelated rates of infection from case notifications and serological data. Journal of Hygiene (Cambridge) 1985; 95: 419-436. (Pubitemid 16227122)
34. Mclean AR, Anderson RM. Measles in developing countries part II : the predicted impact of mass vaccination. Epidemiology and Infection 1988; 100: 419-442.
35. Edmunds WJ, et al. Modelling rubella in Europe. Epidemiology and Infection 2000;125: 617-634. (Pubitemid 32156851)
36. Earn DJD, et al. A simple model for complex dynamical transitions in epidemics. Nature 2000; 287: 667-670.
37. Clarke M, et al. Epidemiological studies of rubella virus in a tropical African community. Bulletin of the World Health Organization 1980; 58: 931-935. (Pubitemid 11185561)
38. Lessler J, et al. Measuring the performance of vaccination programs using cross-sectional surveys. PLoS Medicine 2011; 8: e1001110.