Enhancing participation to health screening campaigns by group interactions.

Raffaella Burioni,Alessandro Vezzani,Cecilia Vernia,Micaela Fedele,Pierluigi Contucci

doi:10.1038/srep09904

Abstract

Improving the prevention efficacy of health screening campaigns by increasing their attendance rate represents a challenge that calls for new strategies. This paper analyzes the response to a Pap test screening campaign of 155,000 women over the last decade. Using a mathematical model of statistical physics origins we derive a quantitative estimate of the mutual influence between participating groups. Different scenarios and possible actions are studied from the cost-benefit perspective. The performance of alternative strategies to improve participation are forecasted and compared. The results show that the standard strategies with incentives concentrated toward the low participating groups are outperformed by those toward pivotal groups with higher influence power. Our method provides a flexible tool useful to support policy maker decisions while complying with ethical regulations on privacy and confidentiality.

Highlights

Correspondence and requests for materials should be addressed to Enhancing participation to health screening campaigns by group interactions
Improving the prevention efficacy of health screening campaigns by increasing their attendance rate represents a challenge that calls for new strategies
This paper analyzes the response to a Papanicolaou smear (Pap) test screening campaign of 155,000 women over the last decade

Summary

Introduction

Correspondence and requests for materials should be addressed to Enhancing participation to health screening campaigns by group interactions. Screening campaigns are usually devised within health systems to detect anticipatory signs of serious, life threatening, illnesses by preliminary tests with the purpose to prevent them or deal with them at early, nonlethal, stages[1,2,3]. Their overall efficacy depends both on a wide adhesion of the screenable population[4] and on a statistically fair participation of all the different social groups involved. In this paper we present a possible approach to improve screening campaigns that fulfills those requirements and has the ability to infer a minimal model to make useful predictions

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