Modeling the Impact of Alternative Immunization Strategies: Using Matrices as Memory Lanes.

Tuesday, 3rd of November 2015

The impact of immunization policies can be measured using a new modelling that considers variables at Micro and Macro levels. A very informative study on impact of the different vaccination policies and their overall impact on measles elimination.
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PLoS One. 2015 Oct 28;10(10):e0141147. doi: 10.1371/journal.pone.0141147. eCollection 2015.

Modeling the Impact of Alternative Immunization Strategies: Using Matrices as Memory Lanes.

Alonso WJ¹ Rabaa MA² Giglio R³ Miller MA⁴ Schuck-Paim C⁵.

Abstract

Existing modeling approaches are divided between a focus on the constitutive (micro) elements of systems or on higher (macro) organization levels. Micro-level models enable consideration of individual histories and interactions but can be unstable and subject to cumulative errors. Macro-level models focus on average population properties but may hide relevant heterogeneity at the micro-scale. We present a framework that integrates both approaches through the use of temporally structured matrices that can take large numbers of variables into account. Matrices are composed of several bidimensional (time×age) grids each representing a state (e.g. physiological immunological socio-demographic). Time and age are primary indices linking grids. These matrices preserve the entire history of all population strata and enable the use of historical events parameters and states dynamically in the modeling process. This framework is applicable across fields but particularly suitable to simulate the impact of alternative immunization policies. We demonstrate the framework by examining alternative strategies to accelerate measles elimination in 15 developing countries. The model recaptured long-endorsed policies in measles control showing that where a single routine measles-containing vaccine is employed with low coverage any improvement in coverage is more effective than a second dose. It also identified an opportunity to save thousands of lives in India at attractively low costs through the implementation of supplementary immunization campaigns. The flexibility of the approach presented enables estimating the effectiveness of different immunization policies in highly complex contexts involving multiple and historical influences from different hierarchical levels.