Trends in parameterization, economics and host behaviour in influenza pandemic modelling: a review and reporting protocol

Abstract

BackgroundThe volume of influenza pandemic modelling studies has increased dramatically in the last decade. Many models incorporate now sophisticated parameterization and validation techniques, economic analyses and the behaviour of individuals.MethodsWe reviewed trends in these aspects in models for influenza pandemic preparedness that aimed to generate policy insights for epidemic management and were published from 2000 to September 2011, i.e. before and after the 2009 pandemic.ResultsWe find that many influenza pandemics models rely on parameters from previous modelling studies, models are rarely validated using observed data and are seldom applied to low-income countries. Mechanisms for international data sharing would be necessary to facilitate a wider adoption of model validation. The variety of modelling decisions makes it difficult to compare and evaluate models systematically.ConclusionsWe propose a model Characteristics, Construction, Parameterization and Validation aspects protocol (CCPV protocol) to contribute to the systematisation of the reporting of models with an emphasis on the incorporation of economic aspects and host behaviour. Model reporting, as already exists in many other fields of modelling, would increase confidence in model results, and transparency in their assessment and comparison.

Influenza-like Illness, the Time to Seek Healthcare, and Influenza Antiviral Receipt During the 2010–2011 Influenza Season—United States

“…As such, they may also help better define the assumptions of mathematical models describing the transmission and spread of influenza. Because data describing differences in healthcare seeking, time to seek healthcare, and antiviral treatment by demographic groups have been largely unavailable, mathematical models frequently utilized assumptions that may not have been validated with epidemiological or laboratory data from seasonal or pandemic influenza [22]. The results of this study, including the important behavioral information, may help provide some of this missing information.…”

Beyond crystal balls: crosscutting solutions in global health to prepare for an unpredictable future

“…seasonal dynamics) to predicting the features of rare events, such as the magnitude, duration, location or time when a pandemic might emerge [ 30 ]. Although predictive models of influenza pandemics abound, important aspects such as transmission dynamics and behavioral factors are often missing (reviewed in [ 31 ]). Additionally, given the rare nature of these events, modeling outcomes are rarely validated [ 31 ] and parameter choices are often based on past studies, not on independent data [ 31 ].…”

“…Although predictive models of influenza pandemics abound, important aspects such as transmission dynamics and behavioral factors are often missing (reviewed in [ 31 ]). Additionally, given the rare nature of these events, modeling outcomes are rarely validated [ 31 ] and parameter choices are often based on past studies, not on independent data [ 31 ]. Importantly, the ability to specify the dynamics of putative future pandemics appropriately is further hindered when we consider that emergence of new viral strains is inherently unpredictable [ 32 , 33 ].…”

Evaluation of Border Entry Screening for Infectious Diseases in Humans

“…It is probable that entry screening with a low rate of detection of incoming cases would also be unlikely to significantly delay the commencement of an epidemic or reduce the total number of cases. The models had also not been validated using data from an influenza pandemic ( 26 ). Now that data from the influenza A(H1N1)pdm09 virus pandemic are available, there is an opportunity to validate the models examine the efficacy of border measures.…”