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Modelling the Influence of Human Behaviour on the Spread of Infectious Diseases: A Review

The Royal Society
Journal of the Royal Society Interface
Authors:
Sebastian Funk at London School of Hygiene and Tropical Medicine
Sebastian Funk
Marcel Salathé
Marcel Salathé
Marcel Salathé
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Vincent A A Jansen at Royal Holloway University of London
Vincent A A Jansen
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Abstract

Human behaviour plays an important role in the spread of infectious diseases, and understanding the influence of behaviour on the spread of diseases can be key to improving control efforts. While behavioural responses to the spread of a disease have often been reported anecdotally, there has been relatively little systematic investigation into how behavioural changes can affect disease dynamics. Mathematical models for the spread of infectious diseases are an important tool for investigating and quantifying such effects, not least because the spread of a disease among humans is not amenable to direct experimental study. Here, we review recent efforts to incorporate human behaviour into disease models, and propose that such models can be broadly classified according to the type and source of information which individuals are assumed to base their behaviour on, and according to the assumed effects of such behaviour. We highlight recent advances as well as gaps in our understanding of the interplay between infectious disease dynamics and human behaviour, and suggest what kind of data taking efforts would be helpful in filling these gaps.
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REVIEW
Modelling the influence of human
behaviour on the spread of infectious
diseases: a review
Sebastian Funk1, Marcel Salathe
´2,* and Vincent A. A. Jansen1
1
School of Biological Sciences, Royal Holloway, University of London,
Egham TW20 0EX, UK
2
Department of Biological Sciences, Stanford University, Stanford,
CA 94305, USA
Human behaviour plays an important role in the spread of infectious diseases, and under-
standing the influence of behaviour on the spread of diseases can be key to improving
control efforts. While behavioural responses to the spread of a disease have often been
reported anecdotally, there has been relatively little systematic investigation into how behav-
ioural changes can affect disease dynamics. Mathematical models for the spread of infectious
diseases are an important tool for investigating and quantifying such effects, not least because
the spread of a disease among humans is not amenable to direct experimental study. Here, we
review recent efforts to incorporate human behaviour into disease models, and propose that
such models can be broadly classified according to the type and source of information which
individuals are assumed to base their behaviour on, and according to the assumed effects of
such behaviour. We highlight recent advances as well as gaps in our understanding of the
interplay between infectious disease dynamics and human behaviour, and suggest what
kind of data taking efforts would be helpful in filling these gaps.
Keywords: epidemiology; infectious diseases; behaviour; vaccination
1. INTRODUCTION
Recent outbreaks of infectious diseases have brought
pictures of empty streets and people wearing face
masks to television screens and front pages, as fear of
diseases of unknown fatality swept around the globe.
Arguably one of the most striking aspects of these out-
breaks were the reactions to the disease. During the
outbreak of influenza A (H1N1) in 2009, the effect on
societies, partly through public measures but also
through personal and uncoordinated responses, has
been noticeable. The public reaction to this disease
was sustained and widespread, and, interestingly, part
of this reaction resulted from individual behavioural
responses to the presence of the disease.
Historically, human behaviour has been intricately
linked with the spread of infectious diseases (McNeill
1976). In medieval times, the lethality of the bubonic
plague caused people to ‘shun and flee from the sick
and all that pertained to them, and thus doing, each
thought to secure immunity for himself’, as Boccaccio
vividly records in the Decameron. Equally compelling
are the accounts of the citizens of the Yorkshire village
of Eyam, who voluntarily quarantined themselves to
prevent spread of the plague from the village (Scott &
Duncan 2001). More recently, during the influenza pan-
demic of the early twentieth century, people eventually
stayed away from congregated places (Crosby 1990). In
1995, a presumed outbreak of bubonic plague in Surat,
India, caused widespread panic and flight of hundreds
of thousands of people (Campbell & Hughes 1995).
When severe acute respiratory syndrome broke out in
the early twenty-first century, the usage of face masks
became widespread in affected areas, and many chan-
ged their travelling behaviour (Lau et al. 2005).
Prevalence-elastic behaviour, i.e. protective behaviour
which is seen increasingly as a disease becomes more
prevalent, has been observed in the context of both
measles (Philipson 1996) and HIV (Ahituv et al. 1996).
While behavioural responses to the spread of a dis-
ease have frequently been reported anecdotally, there
has been relatively little systematic investigation into
their nature, or the effect they can have on the spread
of the disease. Behavioural changes are sometimes
cited in the interpretation of outbreak data to explain
drops in the transmission rate (Riley et al. 2003;
Nishiura 2007), yet rarely is it detailed how these reac-
tions can be quantified and captured in a systematic
*Author for correspondence (salathe@stanford.edu).
J. R. Soc. Interface (2010) 7, 1247–1256
doi:10.1098/rsif.2010.0142
Published online 26 May 2010
Received 9 March 2010
Accepted 4 May 2010 1247 This journal is #2010 The Royal Society
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