Rotavirus is the leading cause of childhood diarrheal disease, responsible for an estimated 146,000 annual deaths across the globe. A large majority of these deaths occur in low-resource settings where life-saving rehydration therapy is often inaccessible. A challenge to mitigating this burden arises from the reduced efficacy and durability of rotavirus vaccines observed in low-resource settings compared to high-resource settings. Proposed explanations include the higher force of infection in these settings, host factors such as poor nutrition or intestinal co-morbidities, and interference from maternal antibodies or the concomitantly administered oral poliovirus vaccine. These mechanisms may not be mutually exclusive. Depending on the contribution of each potential factor, optimization of the vaccination schedule, through addition of an age-based booster dose, a seasonal booster, or a delay in the initiation of the primary vaccine series, could improve vaccine protection. Each proposed schedule change carries advantages and trade-offs. An age-based booster would have straightforward roll-out within existing infrastructure, while a seasonal booster may have greater impact on incidence. Seasonal boosters may be particularly effective if maternal antibody interference is heightened for infants born during or following the peak of the rotavirus season. Delayed series initiation could improve vaccine protection for older infants, but may extend the period during which infants are susceptible to primary infection. To inform policy development based on these potential interventions, mathematical modeling and cost-effectiveness analyses are tools to evaluate their relative epidemiological and economic impacts. I will use data-driven mathematical modeling to optimize the rotavirus vaccination strategy for Mali based on anticipated health benefits and associated costs, through the following aims: (1) Characterize seasonal variation in maternal and infant antibody titers. Using pairs of mother and infant sera collected by CVD-Mali prior to rotavirus vaccine introduction, I will compare titers during high and low exposure seasons to identify differences in anti-rotavirus IgA and rotavirus neutralizing antibody levels. (2) Analyze rotavirus vaccine efficacy and waning. I will build a dynamic rotavirus transmission model explicitly parameterized and validated for the Malian context. Among other key factors, I will incorporate any seasonal trends in maternal antibody interference identified in Aim 1. (3) Optimize rotavirus vaccination schedule. Applying the transmission model developed in Aim 2, I will compare severe rotavirus incidence under the status quo three-dose (primary) schedule against four proposed schedule changes: delayed primary series initiation, introduction of a booster for 9-month-olds, seasonal booster for children aged 6 through 18 months, and the replacement of the third primary dose with a dose for older children. I will incorporate programmatic and disease costs to predict the cost-effectiveness of each strategy and identify the optimal schedule from both societal and individual perspectives.

Public Health Relevance

Rotavirus causes over 146,000 deaths each year, and unfortunately protection from rotavirus vaccines appears to be reduced in the low-resource settings where most of these deaths occur. My proposed research will examine potential causes of this reduced protection in Mali, and then compare the expected health and economic impact of vaccine schedule changes on rotavirus disease. Results will be communicated to policymakers in Mali and to international public health decision-makers, providing an evidence base for the optimal rotavirus vaccination schedule in Mali and throughout sub-Saharan Africa.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01AI141576-02
Application #
9830583
Study Section
Microbiology and Infectious Diseases B Subcommittee (MID)
Program Officer
Alarcon, Rodolfo M
Project Start
2018-12-01
Project End
2023-11-30
Budget Start
2019-12-01
Budget End
2020-11-30
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Maryland Baltimore
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
188435911
City
Baltimore
State
MD
Country
United States
Zip Code
21201