Evaluating strategies to improve rotavirus vaccine impact during the second year of life in Malawi
Science Translational Medicine • 14 Aug 2019 • Vol 11, Issue 505 • DOI: 10.1126/scitranslmed.aav6419
Examining disparity in protection against rotavirus
The rotavirus vaccine is less effective in low-income countries compared to high-income countries, although the reasons for this are unknown. Pitzer et al. used mathematical modeling to analyze infection data in Malawian children before and after the introduction of a rotavirus vaccine to examine the nature of vaccine-induced immunity. They found that endemic infection increased the protection observed in the clinical study control arm, reducing the apparent efficacy of the vaccine arm. The authors also determined that a booster dose at 9 months is unlikely to lead to substantially improved protection and suggest that efforts may be better placed into developing a more immunogenic vaccine.
Abstract
Rotavirus vaccination has substantially reduced the incidence of rotavirus-associated gastroenteritis (RVGE) in high-income countries, but vaccine impact and estimated effectiveness are lower in low-income countries for reasons that are poorly understood. We used mathematical modeling to quantify rotavirus vaccine impact and investigate reduced vaccine effectiveness, particularly during the second year of life, in Malawi, where vaccination was introduced in October 2012 with doses at 6 and 10 weeks. We fitted models to 12 years of prevaccination data and validated the models against postvaccination data to evaluate the magnitude and duration of vaccine protection. The observed rollout of vaccination in Malawi was predicted to lead to a 26 to 77% decrease in the overall incidence of moderate-to-severe RVGE in 2016, depending on assumptions about waning of vaccine-induced immunity and heterogeneity in vaccine response. Vaccine effectiveness estimates were predicted to be higher among 4- to 11-month-olds than 12- to 23-month-olds, even when vaccine-induced immunity did not wane, due to differences in the rate at which vaccinated and unvaccinated individuals acquire immunity from natural infection. We found that vaccine effectiveness during the first and second years of life could potentially be improved by increasing the proportion of infants who respond to vaccination or by lowering the rotavirus transmission rate. An additional dose of rotavirus vaccine at 9 months of age was predicted to lead to higher estimated vaccine effectiveness but to only modest (5 to 16%) reductions in RVGE incidence over the first 3 years after introduction, regardless of assumptions about waning of vaccine-induced immunity.
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Supplementary Material
Summary
Materials and Methods
Fig. S1. Diagram of compartmental models for vaccination with and without waning of vaccine-induced immunity.
Fig. S2. Vaccine coverage through time among rotavirus-negative diarrheal cases.
Fig. S3. Observed and model-predicted vaccine impact by age group and year since vaccine introduction.
Fig. S4. Observed and predicted vaccine impact by age and vaccination status.
Fig. S5. Relationship between the proportion of infants who respond to each vaccine dose, the basic reproductive number (R0), and vaccine effectiveness estimates for model 1.
Fig. S6. Relationship between the proportion of infants who respond to each vaccine dose and the predicted vaccine effectiveness assuming heterogeneity in vaccine response.
Fig. S7. Relationship between the proportion of infants who respond to each vaccine dose, the basic reproductive number (R0), and the model-predicted indirect effect.
Fig. S8. Proportion of the population with natural or vaccine-induced immunity by age.
Fig. S9. Proportion of the population with natural or vaccine-induced immunity by age for the period from January 2018 to December 2019.
Fig. S10. Model-predicted vaccine effectiveness with and without the addition of a third dose of rotavirus vaccine administered at 9 months of age.
Fig. S11. Predicted impact of strategies to improve the proportion of infants responding to vaccination and to reduce the transmission rate of rotavirus.
Fig. S12. Variation in the average number of rotavirus-negative cases through time for the pre- and postvaccination surveillance periods.
Fig. S13. Prior and posterior distributions of the model parameters estimated by fitting to the prevaccination data.
Fig. S14. Trace plots and posterior distributions of estimated vaccination parameters.
Fig. S15. Posterior distributions of estimated vaccination parameters for models 1 and 2 fitted to the postvaccination data.
Fig. S16. Relationship between the relative infectiousness of subsequent infections and the estimated basic reproductive number (R0).
Fig. S17. Model-predicted overall vaccine impact and vaccine effectiveness for different assumptions regarding the relative infectiousness of subsequent infections.
Fig. S18. Model-predicted overall vaccine impact and vaccine effectiveness for short-lived complete immunity after infection.
Table S1. Fixed and estimated parameter values.
Table S2. Estimated basic reproductive number for different values of the relative infectiousness of subsequent infections duration of complete immunity.
Table S3. Comparison of model fits to the postvaccination data.
Table S4. Model-predicted indirect vaccine effectiveness.
Table S5. Model-predicted vaccine impact for the models with and without indirect effects.
Resources
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Information & Authors
Information
Published In
Science Translational Medicine
Volume 11 | Issue 505
August 2019
August 2019
Copyright
Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
This is an article distributed under the terms of the Science Journals Default License.
Submission history
Received: 5 October 2018
Accepted: 25 July 2019
Acknowledgments
This work was supported by grant R01AI112970 from the U.S. NIH/National Institute of Allergy and Infectious Diseases to V.E.P. Rotavirus surveillance in Blantyre, Malawi was supported by a Wellcome Trust Programme Grant to N.A.C. (number 091909/Z/10/Z). A.B. was the recipient of a Wellcome Trust Clinical PhD Fellowship (number 102466/Z/13/A). K.C.J. was supported by a Wellcome Trust Public Health and Tropical Medicine Training Fellowship (number 201945/Z/16/Z). Author contributions: V.E.P. and N.A.C. conceived and designed the study. V.E.P. developed models. A.B., N.B.-Z., K.C.J., and N.A.C. collected data. V.E.P., A.B., N.B.-Z., and N.A.C. analyzed data. B.A.L., J.A.L., and U.D.P. helped to interpret the results. All authors wrote the manuscript. Competing interests: V.E.P. is a member of the WHO Immunization and Vaccine-related Implementation Research Advisory Committee (IVIR-AC) and has received reimbursement from Merck for travel expenses to attend a Scientific Input Engagement unrelated to rotavirus vaccines. N.B.-Z. and K.C.J. have received research grant support from GlaxoSmithKline Biologicals for work on rotavirus vaccines. N.B.Z. also reports income from Takeda Pharmaceuticals. B.A.L. reports personal fees from Takeda Pharmaceuticals, personal fees from the CDC Foundation, and personal fees from Hall Booth Smith PC, all unrelated to rotavirus vaccines. J.A.L. has received research grants and consulting fees from Merck and Pfizer, unrelated to the current work. N.A.C. has received research grant support and honoraria for participation in rotavirus vaccine Independent Data Monitoring Committee meetings from GlaxoSmithKline Biologicals. Data and materials availability: All data associated with this manuscript are present in the paper or the Supplementary Materials. Model code and data necessary to reproduce the results of the study are available at DOI: 10.5281/zenodo.3336499.
Authors
Funding Information
Wellcome Trust: 091909/Z/10/Z
Wellcome Trust: 102466/Z/13/A
Wellcome Trust: 201945/Z/16/Z
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