LONDON, 22 August 2012 (IRIN): Researchers in Canada are combining mathematics with “social learning” to predict how epidemics are affected by fears – usually unfounded – that a vaccine can harm, so as to improve the design of vaccination campaigns.
Social learning – how behaviours are learnt and decisions are made in group settings – has long been examined in economics and now, increasingly, in healthcare.
“We are giving 110-120 million courses of vaccine out every year around the globe, but how much do we know about why people take these up?” asked John Edmunds, of the London School of Hygiene and Tropical Medicine and contributor in a forthcoming book on modelling and disease control.
“How much do we invest in understanding what drives mothers to accept these vaccines, and sometimes not to?” added he.
Payoffs and penalties Chris Bauch and colleagues at the University of Guelph in Ontario, Canada, set out to create a mathematical model that would show how much a person’s decision to be vaccinated was influenced by disease prevalence (udbredelse), and how much by peer (ligemænd/jævnaldrende) pressure.
They tested the model using data from a 1990s measles-mumps-rubella (MMR) vaccine scare and a 1970s pertussis (kighoste) vaccine scare in England and Wales to see how well their model predicted vaccine coverage and disease outbreaks in those instances.
The researchers grouped people into “vaccinator” and “non-vaccinator” categories.
The mathematical formula tried to calculate how people judged a vaccine’s risks and rewards. The risk was the perceived chances of getting infected, multiplied by the cost of infection – the cost of medicine and doctors or clinic visits, being unable to work and perhaps losing income, and the discomfort of being ill.
The perceived “payoff” (fordel) was whether a person judged the vaccine would do more good than harm.
Social learning was included by measuring how often people switched from one group to the other, based on observing others’ vaccine decisions and whether their health improved.
Bauch reported that their model did well in foretelling disease outbreaks and vaccination coverage for both MMR and pertussis.
More scares?
Læs videre på http://www.irinnews.org/Report/96150/How-to-Predict-vaccine-coverage-by-modelling
