Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-31T15:24:29.105Z Has data issue: false hasContentIssue false
  • English
  • Français

A model-based design of a vaccination strategy against rubella in a non-immunized community of São Paulo State, Brazil

Published online by Cambridge University Press:  15 May 2009

E. Massad ,
M. Nascimento Burattini ,
R. S. De Azevedo Neto ,
Hyun Mo Yang ,
F. A. B. Coutinho  and
D. M. T. Zanetta
E. Massad
Affiliation:
Discipline of Medical Informatics, School of Medicine, The University of São Paulo, and LIM-01 HCFMUSP. Av. Dr Arnaldo, 455. CEP 01246-903. São Paulo, Brazil
M. Nascimento Burattini
Affiliation:
Discipline of Medical Informatics, School of Medicine, The University of São Paulo, and LIM-01 HCFMUSP. Av. Dr Arnaldo, 455. CEP 01246-903. São Paulo, Brazil Discipline of Infectious Diseases, Escola Paulista de Medicina, São Paulo, Brazil
R. S. De Azevedo Neto
Affiliation:
Discipline of Medical Informatics, School of Medicine, The University of São Paulo, and LIM-01 HCFMUSP. Av. Dr Arnaldo, 455. CEP 01246-903. São Paulo, Brazil
Hyun Mo Yang
Affiliation:
Discipline of Medical Informatics, School of Medicine, The University of São Paulo, and LIM-01 HCFMUSP. Av. Dr Arnaldo, 455. CEP 01246-903. São Paulo, Brazil
F. A. B. Coutinho
Affiliation:
Physics Institute, The University of São Paulo, Brazil
D. M. T. Zanetta
Affiliation:
Discipline of Medical Informatics, School of Medicine, The University of São Paulo, and LIM-01 HCFMUSP. Av. Dr Arnaldo, 455. CEP 01246-903. São Paulo, Brazil
Rights & Permissions [Opens in a new window]

Summary

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

A mixed vaccination strategy against rubella is proposed. We describe how the vaccination strategy was designed with the help of mathematical techniques. The strategy was designed for application in a non-immunized community of the State of São Paulo, Brazil, and was implemented by local health authorities in 1992. This strategy comprises a pulse vaccination campaign, covering the age interval between 1 and 10 years, followed by the introduction of the vaccine in the immunization calendar at 15 months of age. The expected impact of the proposed strategy is discussed.

Type
Research Article
Information
Epidemiology & Infection , Volume 112 , Issue 3 , June 1994 , pp. 579 - 594
Copyright
Copyright © Cambridge University Press 1994

References

REFERENCES

1.Coutinho, FAB. Massad, E. Burattini, MN, Yang, HM. Azevedo, Neto RS. Effects of vaccination programmes on transmission rates of infections and related threshold conditions for control. IMA J Math Appl Med Biol 1993; 10: 187–206.CrossRefGoogle ScholarPubMed
2.Bailey, NTJ. The mathematical theory of infectious diseases. 2nd ed.London: Griffin. 1975.Google Scholar
3.Anderson, RM. Directly transmitted viral and bacterial infections of man. In: Anderson, RM. ed. Population dynamics of infectious diseases, London: Chapman and Hall. 1982: 1–37.Google Scholar
4.Anderson, RM. May, RM. Directly transmitted infectious diseases: control by vaccination. Science 1982; 215 1053–60.CrossRefGoogle ScholarPubMed
5.Anderson, RM, May, RM. Vaccinations against rubella and measles: quantitative investigations of different policies. J Hyg 1983; 90: 259–325.CrossRefGoogle ScholarPubMed
6.Anderson, RM, May, RM. Age-related changes in the rate of disease transmission: implications for the design of vaccination programmes. J Hyg 1985: 94: 365–436.CrossRefGoogle ScholarPubMed
7.Anderson, RM, May, RM. Infectious diseases of humans: dynamics and control. Oxford: Oxford University Press, 1991.CrossRefGoogle Scholar
8.Hethcote, HW. A vaccination model for an endemic disease with maternal antibodies in infants. In: Eisenfeld, J. De Lise, C, eds. Mathematics and computers in biomedical applications. Amsterdam: Elsevier, 1985: 283–6.Google Scholar
9.Hethcote, Hw. Optimal ages of vaccination for measles. Math Biosci 1988; 89: 29–52.CrossRefGoogle Scholar
10.Grenfell, BT, Anderson, RM. The estimation of age-related rates of infection from case notification and serological data. J Hyg 1985; 95: 419–36.CrossRefGoogle ScholarPubMed
11.Massad, E, Raimundo, SM, Silveira, ASB. A continuous function model for the age-related force of infection. Math Comp Model 1990; 13: 101–12.CrossRefGoogle Scholar
12.Pannuti, CS, Moraes, JC. Souza, VAUF, Camargo, MCC, Hildago, NTR, and Dicve, SP. Measles antibody prevalence after mass vaccination in São Paulo, Brazil. Bull WHO 1991: 69: 557–60.Google ScholarPubMed
13. Centro de Informações de Saúde. Boletim: Módulo de Acompanhamento de Doenças– SNDI–R003. Ministry of Health, Brazil, 1991.Google Scholar
14.Azevedo, Neto RS, Silveira, ASB, Nokes, DJ et al. , Rubella seroepidemiology in a nonimmunized population of São Paulo State, Brazil, 1993. Epidemiol Infect. Submitted.Google Scholar
15.Griffel, DH. Applied functional analysis. Chichester: Ellis Horwood, 1981.Google Scholar
16.Abramowitz, M, Stegun, IA. Handbook of mathematical functions. New York: Dover. 1970.Google Scholar
17.Muench, H. Catalytic models in epidemiology. Cambridge, MA: Harvard University Press, 1959.CrossRefGoogle Scholar
18.Thacker, Sb. Millar, JD. Mathematical modeling and attempts to eliminate measles: a tribute to the late Professor George Macdonald. Am J Epidemiol 1991; 136: 517–25.CrossRefGoogle Scholar