Modelling approaches to policy issues in public health

Dr Philippe GiabbanelliPublic Health Modelling group

14 November 2014

What is modelling?

Modelling is articulating a set of hypotheses about a phenomenon.

All people model. But most run implicit, rather than explicit models.

What is modelling?

Implicit models Explicit modelsvs

• Hide underlying hypotheses • Show testable hypotheses

• Don’t test internal consistency

• Unknown relation to data

• Check for consistency

• Incorporate data

What is modelling?

There are different ways to do modelling.

Mathematical model Statistical model Computational model

None is systematically better. They address different needs.

Conceptual model

When do computational models help?

Computational models have a strong track-record in supporting decision making in complex situations.

information is never complete, comes in incrementally – but there is constant pressure to arrive at conclusions

When do computational models help?

“The high cost to eradicate poliomyelitis in 4 endemic areas has led some to suggest switching from eradication to a policy of control.”

Modelling

Wavering commitment leads to a failure to eradicate, greater cumulative costs, and a much larger number of cases.

Case#1: Eradicating, or controlling?

Closing schools during the 2009 H1N1 influenza epidemic would have:↓ transmission (hence deaths and health care costs)

↑ costs of childcare needs↓ productivity of school employees

Modelling

Closing schools could have resulted in substantial costs to society.

When do computational models help?

Case#2: Closing schools or not?

When do computational models help?

When do computational models help?

• interdisciplinary • rich and accessible data

• usable model • scenarios informed by policymakers

• method selected based on the problem

Modelling food behaviours

How would food behaviours respond if we started changing prices?

Modelling food behaviours

Tax

Published in the American Journal of

Public Health

Modelling food behaviours

Previous computational models assume that:

the relationship between the food environment “foodscape”) and food consumption can be captured by looking at the

foodscape around the home or work environment

Proximity hypothesis

…but people navigate a multiplicity of environments

and it depends on food preferences, socio-demographics, etc.

Modelling food behaviours

Agent-based model

Portfolio of policy interventions

Maximum density of takeaways minimum distance of takeaways from schools

preference for healthy foods

Indicators

Utilization per type of food outlet F&V intake Obesity

Conclusion

For more information about the Public Health Modelling group, visit:http://www.cedar.iph.cam.ac.uk/research/modelling/

Modelling can support decision making in complex situations but it has to follow a transparent and interdisciplinary process using good

quality data to investigate credible scenarios.