The role of uncertainty in infectious disease modelling

October 21, 2013
The role of uncertainty in infectious disease modelling
The study found that many models provided only cursory reference to the uncertainties of the information and data, or the parameters used.

Research by scientists at the University of Liverpool has found that greater consideration of the limitations and uncertainties in infectious disease modelling would improve its usefulness and value.

Infectious disease dynamical modelling plays a central role in planning for outbreaks of human and livestock diseases.  They forecast how they might progress and inform policy responses.

Informing policy decisions

Modelling is commissioned by governments or may be developed independently by researchers. It has been used to inform for human and animal diseases such as SARS, H1N1 swine influenza, foot-and-mouth disease and is being used to inform action in the campaign to control bovine TB.

In a study published in PLOS One, researchers analysed scientific papers, interviews, policies, reports and outcomes of previous infectious disease outbreaks in the UK to ascertain the role uncertainties played in previous models, and how these were understood by both the designers of the model and the users of the model.

They found that many models  provided only cursory reference to the uncertainties of the information and data or the parameters used.  Whilst the models were uncertain many still informed action.
Dr Rob Christley, from the University's Institute of Infection and Global Health, said:  "It is accepted that models will never be able to predict 100% the size, shape or form of an outbreak and it is recognised that a level of uncertainty always exists in modelling. However, modellers often fear detailed discussion of this uncertainty will undermine the model in the eyes of policy makers.

"This study found that the uncertainties and limitations of a model are sometimes hidden and sometimes revealed, and that which occurs is context dependent.

"Whilst it isn't possible to calculate the level of uncertainty, a better understanding and communication of the model's limitations is needed and could lead to better policy."

Uncertainty

Uncertainty can occur at all stages of the modelling process from weaknesses in the quality and type of data used, assumptions made about the infectious agent itself, and about the world in which the disease is circulating, all the way through to the technical aspects of the .

The research team comprised veterinary scientists and epidemiologists, sociologists, microbiologists and environmental scientists.

More information: www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0076277

Related Stories

Climate model to predict malaria outbreaks in India

April 2, 2012

Scientists from the University of Liverpool are working with computer modelling specialists in India to predict areas of the country that are at most risk of malaria outbreaks, following changes in monsoon rainfall.

Recommended for you

Experimental MERS vaccine shows promise in animal studies

July 28, 2015

A two-step regimen of experimental vaccines against Middle East respiratory syndrome (MERS) prompted immune responses in mice and rhesus macaques, report National Institutes of Health scientists who designed the vaccines. ...

Can social isolation fuel epidemics?

July 21, 2015

Conventional wisdom has it that the more people stay within their own social groups and avoid others, the less likely it is small disease outbreaks turn into full-blown epidemics. But the conventional wisdom is wrong, according ...

Lack of knowledge on animal disease leaves humans at risk

July 20, 2015

Researchers from the University of Sydney have painted the most detailed picture to date of major infectious diseases shared between wildlife and livestock, and found a huge gap in knowledge about diseases which could spread ...

IBD genetically similar in Europeans and non-Europeans

July 20, 2015

The first genetic study of inflammatory bowel disease (IBD) to include individuals from diverse populations has shown that the regions of the genome underlying the disease are consistent around the world. This study, conducted ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.