Predictive Validation of an Influenza Spread Model

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2013 Jun 12

PMID 23755236

Citations 11

Authors

Ayaz Hyder

David L Buckeridge

Brian Leung

Affiliations

Soon will be listed here.

Abstract

Background: Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread.

Methods And Findings: We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998-1999). Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type). Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic.

Conclusions: Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers) with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve their predictive ability.

Citing Articles

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Petropoulos F, Makridakis S, Stylianou N Int J Forecast. 2020; 38(2):439-452.

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Evaluation of mechanistic and statistical methods in forecasting influenza-like illness.

Kandula S, Yamana T, Pei S, Yang W, Morita H, Shaman J J R Soc Interface. 2018; 15(144).

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Designing an Agent-Based Model Using Group Model Building: Application to Food Insecurity Patterns in a U.S. Midwestern Metropolitan City.

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Silva W, Das T, Izurieta R BMC Public Health. 2017; 17(1):898.

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