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Evolution and Use of Dynamic Transmission Models for Measles and Rubella Risk and Policy Analysis

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  • Kimberly M. Thompson

Abstract

The devastation caused by periodic measles outbreaks motivated efforts over more than a century to mathematically model measles disease and transmission. Following the identification of rubella, which similarly presents with fever and rash and causes congenital rubella syndrome (CRS) in infants born to women first infected with rubella early in pregnancy, modelers also began to characterize rubella disease and transmission. Despite the relatively large literature, no comprehensive review to date provides an overview of dynamic transmission models for measles and rubella developed to support risk and policy analysis. This systematic review of the literature identifies quantitative measles and/or rubella dynamic transmission models and characterizes key insights relevant for prospective modeling efforts. Overall, measles and rubella represent some of the relatively simplest viruses to model due to their ability to impact only humans and the apparent life‐long immunity that follows survival of infection and/or protection by vaccination, although complexities arise due to maternal antibodies and heterogeneity in mixing and some models considered potential waning immunity and reinfection. This review finds significant underreporting of measles and rubella infections and widespread recognition of the importance of achieving and maintaining high population immunity to stop and prevent measles and rubella transmission. The significantly lower transmissibility of rubella compared to measles implies that all countries could eliminate rubella and CRS by using combination of measles‐ and rubella‐containing vaccines (MRCVs) as they strive to meet regional measles elimination goals, which leads to the recommendation of changing the formulation of national measles‐containing vaccines from measles only to MRCV as the standard of care.

Suggested Citation

  • Kimberly M. Thompson, 2016. "Evolution and Use of Dynamic Transmission Models for Measles and Rubella Risk and Policy Analysis," Risk Analysis, John Wiley & Sons, vol. 36(7), pages 1383-1403, July.
    • Handle: RePEc:wly:riskan:v:36:y:2016:i:7:p:1383-1403
    DOI: 10.1111/risa.12637
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    Cited by:

    1. Kimberly M. Thompson & Nima D. Badizadegan, 2017. "Modeling the Transmission of Measles and Rubella to Support Global Management Policy Analyses and Eradication Investment Cases," Risk Analysis, John Wiley & Sons, vol. 37(6), pages 1109-1131, June.
    2. Kimberly M. Thompson & Stephen L. Cochi, 2016. "Modeling and Managing the Risks of Measles and Rubella: A Global Perspective, Part I," Risk Analysis, John Wiley & Sons, vol. 36(7), pages 1288-1296, July.
    3. van Ackere, Ann & Schulz, Peter J., 2020. "Explaining vaccination decisions: A system dynamics model of the interaction between epidemiological and behavioural factors," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    4. Fatima‐Zohra Younsi & Salem Chakhar & Alessio Ishizaka & Djamila Hamdadou & Omar Boussaid, 2020. "A Dominance‐Based Rough Set Approach for an Enhanced Assessment of Seasonal Influenza Risk," Risk Analysis, John Wiley & Sons, vol. 40(7), pages 1323-1341, July.
    5. Duncan A. Robertson, 2019. "Spatial Transmission Models: A Taxonomy and Framework," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 225-243, January.
    6. Kimberly M. Thompson, 2017. "Modeling and Managing the Risks of Measles and Rubella: A Global Perspective Part II," Risk Analysis, John Wiley & Sons, vol. 37(6), pages 1041-1051, June.

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