The role of uncertainty in infectious disease modelling

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%3… journal.pone.0076277

Related Stories

Recommended for you

First case of Ebola diagnosed in US

1 hour ago

The United States has diagnosed its first case of the deadly Ebola virus in a man who became infected in Liberia and traveled to Texas, US health officials said Tuesday.

Study finds acupuncture does not improve chronic knee pain

2 hours ago

Among patients older than 50 years with moderate to severe chronic knee pain, neither laser nor needle acupuncture provided greater benefit on pain or function compared to sham laser acupuncture, according to a study in the ...

Ebola outbreak nears end in Nigeria

2 hours ago

The Ebola outbreak in Nigeria is almost over, US health officials said Tuesday, in a rare sign of authorities turning the tide on the highly contagious disease that has killed more than 3,000 in West Africa.

Diuretics in proton pump inhibitor-associated hypomagnesemia

3 hours ago

Proton pump inhibitor (PPI) therapy is associated with hospitalization for hypomagnesemia, particularly among patients also receiving diuretics, according to research published this week in PLOS Medicine. The study, conduc ...

User comments