Implications of spatially heterogeneous vaccination coverage for the risk of congenital rubella syndrome in South Africa

Rubella is generally a mild childhood disease, but infection during early pregnancy may cause spontaneous abortion or congenital rubella syndrome (CRS), which may entail a variety of birth defects. Since vaccination at levels short of those necessary to achieve eradication may increase the average age of infection, and thus potentially the CRS burden, introduction of the vaccine has been limited to contexts where coverage is high. Recent work suggests that spatial heterogeneity in coverage should also be a focus of concern. Here, we use a detailed dataset from South Africa to explore the implications of heterogeneous vaccination for the burden of CRS, introducing realistic vaccination scenarios based on reported levels of measles vaccine coverage. Our results highlight the potential impact of country-wide reductions of incidence of rubella on the local CRS burdens in districts with small population sizes. However, simulations indicate that if rubella vaccination is introduced with coverage reflecting current estimates for measles coverage in South Africa, the burden of CRS is likely to be reduced overall over a 30 year time horizon by a factor of 3, despite the fact that this coverage is lower than the traditional 80 per cent rule of thumb for vaccine introduction, probably owing to a combination of relatively low birth and transmission rates. We conclude by discussing the likely impact of private-sector vaccination.

[1]  A. Puren,et al.  Measles Outbreak in South Africa: Epidemiology of Laboratory-Confirmed Measles Cases and Assessment of Intervention, 2009–2011 , 2013, PloS one.

[2]  J Lessler,et al.  Structured models of infectious disease: inference with discrete data. , 2012, Theoretical population biology.

[3]  D. Jamison,et al.  Measles control in Sub-Saharan Africa: South Africa as a case study. , 2012, Vaccine.

[4]  P. Klepac,et al.  Impact of birth rate, seasonality and transmission rate on minimum levels of coverage needed for rubella vaccination , 2012, Epidemiology and Infection.

[5]  H. Caswell,et al.  The stage-structured epidemic: linking disease and demography with a multi-state matrix approach model , 2011, Theoretical Ecology.

[6]  J. Goodson,et al.  Rubella epidemiology in Africa in the prevaccine era, 2002-2009. , 2011, The Journal of infectious diseases.

[7]  P. Strebel,et al.  Progress toward control of rubella and prevention of congenital rubella syndrome--worldwide, 2009. , 2011, The Journal of infectious diseases.

[8]  L. Fadnes,et al.  Vaccination coverage and timeliness in three South African areas: a prospective study , 2011, BMC public health.

[9]  A. King,et al.  Contact Network Structure Explains the Changing Epidemiology of Pertussis , 2010, Science.

[10]  M. Suchard,et al.  Phylodynamics and Human-Mediated Dispersal of a Zoonotic Virus , 2010, PLoS pathogens.

[11]  Matthew J Ferrari,et al.  Rural–urban gradient in seasonal forcing of measles transmission in Niger , 2010, Proceedings of the Royal Society B: Biological Sciences.

[12]  O. Bjørnstad,et al.  The epidemiology of rubella in Mexico: seasonality, stochasticity and regional variation , 2010, Epidemiology and Infection.

[13]  O. Bjørnstad,et al.  Rubella metapopulation dynamics and importance of spatial coupling to the risk of congenital rubella syndrome in Peru , 2010, Journal of The Royal Society Interface.

[14]  Cécile Viboud,et al.  Absolute Humidity and the Seasonal Onset of Influenza in the Continental United States , 2010, PLoS biology.

[15]  Cecile Viboud,et al.  Absolute Humidity and the Seasonal Onset of Influenza in the Continental US , 2009, PLoS currents.

[16]  C. Jessica E. Metcalf,et al.  Seasonality and comparative dynamics of six childhood infections in pre-vaccination Copenhagen , 2009, Proceedings of the Royal Society B: Biological Sciences.

[17]  L. Blumberg,et al.  Rubella in South Africa : an impending Greek tragedy? , 2009 .

[18]  Rouslan Karimov,et al.  WHO and UNICEF estimates of national infant immunization coverage: methods and processes. , 2009, Bulletin of the World Health Organization.

[19]  M. McMorrow,et al.  Measles outbreak in South Africa, 2003-2005. , 2009, South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde.

[20]  Bryan T. Grenfell,et al.  Hazards, spatial transmission and timing of outbreaks in epidemic metapopulations , 2008, Environmental and Ecological Statistics.

[21]  Benjamin M. Bolker,et al.  Ecological Models and Data in R , 2008 .

[22]  Deborah Balk,et al.  The Global Distribution of Infant Mortality: A subnational spatial view. , 2008, Population, space and place.

[23]  R. Mikolajczyk,et al.  Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases , 2008, PLoS medicine.

[24]  Paul Beier,et al.  Circuit theory predicts gene flow in plant and animal populations , 2007, Proceedings of the National Academy of Sciences.

[25]  C. Paddy Farrington,et al.  Contact Surface Models for Infectious Diseases , 2005 .

[26]  Ingemar Nåsell,et al.  A new look at the critical community size for childhood infections. , 2005, Theoretical population biology.

[27]  K Glass,et al.  Interpreting time-series analyses for continuous-time biological models--measles as a case study. , 2003, Journal of theoretical biology.

[28]  E. Vynnycky,et al.  The predicted impact of private sector MMR vaccination on the burden of Congenital Rubella Syndrome. , 2003, Vaccine.

[29]  Bryan T Grenfell,et al.  A stochastic model for extinction and recurrence of epidemics: estimation and inference for measles outbreaks. , 2002, Biostatistics.

[30]  O. Bjørnstad,et al.  Dynamics of measles epidemics: Estimating scaling of transmission rates using a time series sir model , 2002 .

[31]  O. Bjørnstad,et al.  Travelling waves and spatial hierarchies in measles epidemics , 2001, Nature.

[32]  D. Nokes,et al.  Sero-epidemiology of rubella in the urban population of Addis Ababa, Ethiopia , 2000, Epidemiology and Infection.

[33]  D. Earn,et al.  A simple model for complex dynamical transitions in epidemics. , 2000, Science.

[34]  T. Panagiotopoulos,et al.  Increase in congenital rubella occurrence after immunisation in Greece: retrospective survey and systematic review. , 1999, BMJ.

[35]  N. Gay Modeling Measles, Mumps, and Rubella: Implications for the Design of Vaccination Programs , 1998, Infection Control & Hospital Epidemiology.

[36]  A. J. Hall Infectious diseases of humans: R. M. Anderson & R. M. May. Oxford etc.: Oxford University Press, 1991. viii + 757 pp. Price £50. ISBN 0-19-854599-1 , 1992 .

[37]  R M May,et al.  Vaccination against rubella and measles: quantitative investigations of different policies , 1983, Journal of Hygiene.

[38]  J. Best,et al.  STRATEGY FOR RUBELLA VACCINATION , 1983, The Lancet.

[39]  Gregg Nm Congenital defects associated with maternal rubella. , 1947 .

[40]  G. Chowell,et al.  Spatial and Temporal Dynamics of Rubella in Peru, 1997–2006: Geographic Patterns, Age at Infection and Estimation of Transmissibility , 2009 .

[41]  A. Hinman,et al.  Economic analyses of rubella and rubella vaccines: a global review. , 2002, Bulletin of the World Health Organization.

[42]  多賀 厳太郎,et al.  Dynamical Systems Approach , 2001 .

[43]  Bärbel Finkenstädt,et al.  Time series modelling of childhood diseases: a dynamical systems approach , 2000 .

[44]  Mark Bartlett,et al.  The Critical Community Size for Measles in the United States , 1960 .

[45]  M. Bartlett Measles Periodicity and Community Size , 1957 .

[46]  N. Gregg Congenital defects associated with maternal rubella. , 1947, The Australian hospital.