Contact patterns and their implied basic reproductive numbers: An illustration for varicella-zoster virus

Epidemiology and Infection

Volumn 137, Issue 1, 2009, Pages 48-57

  Van Effelterre, T ^a   Shkedy, Z ^a   Aerts, M ^a   Molenberghs, G ^a   Van Damme, P ^b   Beutels, P ^b,c  

^a HASSELT UNIVERSITY   (Belgium)

^b UNIVERSITY OF ANTWERP   (Belgium)

^c UNIVERSITY OF SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

VARICELLA ZOSTER VACCINE;

AGE; ARTICLE; BELGIUM; HERPES ZOSTER; HUMAN; MATHEMATICAL MODEL; SEROPREVALENCE; VACCINATION; VARICELLA ZOSTER VIRUS; VIRUS REPLICATION; VIRUS TRANSMISSION;

ADOLESCENT; ADULT; BASIC REPRODUCTION NUMBER; BELGIUM; CHICKENPOX; CHILD; CHILD, PRESCHOOL; HUMANS; INFANT; MODELS, THEORETICAL; SEROEPIDEMIOLOGIC STUDIES;

EID: 57649121694     PISSN: 09502688     EISSN: 14694409     Source Type: Journal    
DOI: 10.1017/S0950268808000563     Document Type: Article

References (18)

1. Anderson RM, May RM. Infectious Diseases of Humans, Dynamic and Control. Oxford University Press, 1991.
2. Halloran ME, Watelet L, Struchiner CJ. Epidemiologic effects of vaccinations with complex direct effects in age-structured population. Mathematical Biosciences 1994; 121: 193-225.
3. Anderson RM, May RM. Age-related changes in the rate of disease transmission : Implication for the design of vaccination programmes. Journal of Hygiene (Cambridge) 1985; 94: 365-436.
4. Farrington CP, Kanaan MN, Gay NJ. Estimation of the basic reproduction number for infectious diseases from age-stratified serological survey data (with Discussion). Journal of the Royal Statistical Society, Series C: Applied Statistics 2001; 50: 251-292.
5. Greenhalgh D, Dietz K. Some bounds on estimation for reproductive ratios derived from the age-specific force of infection. Mathematical Biosciences 1994; 124: 9-57.
6. Wallinga J, et al. Estimation for measles reproduction ratios and prospects for elimination of measles by vaccination in some western european countries. Epidemiology and Infection 2001; 127: 281-295.
7. Greenhalgh, D. Discussion in Farrington et al. (2001), Estimation of the basic reproduction number for infectious diseases from age-stratified serological survey data. Journal of the Royal Statistical Society, Series C: Applied Statistics 2001; 50: 251-292.
8. Keiding N. Age-specific incidence and prevalence : A statistical perspective. Journal of the Royal Statistical Society, Series A 1991; 154: 371-412.
9. Shkedy Z, et al. Modeling hepatitis A force of infection using monotone local polynomials. Journal of the Royal Statistical Society, Series C: Applied Satistics 2003; 52: 469-485.
10. Grenfell BT, Anderson RM. The estimation of age-related rates of infection from case notification and serological data. Journal of Hygiene (Cambridge) 1985; 95: 419-436.
11. Farrington CP. Modeling forces of infection for measles, mumps and rubella. Statistics in Medicine 1990; 9: 953-967.
12. Keiding N, et al. Estimation from current status data in continuous time. Lifetime Data Analysis 1996; 2: 119-129.
13. Shkedy Z, et al. Modeling age dependent force of infection from prevalence data using fractional polynomials. Statistics in Medicine 2006; 25: 1577-1591.
14. Thiry N, et al. The seroepidemiology of primary varicella-zoster virus infection in Flanders (Belgium). European Journal of Pediatrics 2002; 161: 588-593.
15. Royston P, Altman DG. Regression using fractional polynomials of continuous covariates : Parsimonious parametric modeling. Applied Statistics 1994; 43: 429-467.
16. Whitaker HJ, Farrington CP. Infections with varying contact rates : Application to varicella. Biometrics 2004; 60: 615-623.
17. Edmunds WJ, O'Callahgan CJ, Nokes DJ. Who mixes with whom? A method to determine the contact patterns of adults that may lead to the spread of airborne infections. Proceedings of the Royal Society of London, Series B 1997; 264: 949-957.
18. Beutels P, et al. Social mixing patterns for transmission models of close contact infections : Exploring self-evaluation and diary-based data collection through a web-based interface. Epidemiology and Infection 2006; 134: 1158-1166.