References Database from Behavioural change models for infectious disease transmission: a systematic review (2010–2015)

We review behavioural change models (BCM) for infectious disease transmission in humans. Following the Cochrane collaboration guidelines and the PRISMA statement, our systematic search and selection yielded 178 papers covering the period 2010–2015. We observe an increasing trend in published BCMs, frequently coupled to (re)emergence events, and propose a categorization by distinguishing how information translates into preventive actions. Behaviour is usually captured by introducing information as a dynamic parameter (76/178) or by introducing an economic objective function, either with (26/178) or without (37/178) imitation. Approaches using information thresholds (29/178) and exogenous behaviour formation (16/178) are also popular. We further classify according to disease, prevention measure, transmission model (with 81/178 population, 6/178 metapopulation and 91/178 individual-level models) and the way prevention impacts transmission. We highlight the minority (15%) of studies that use any real-life data for parametrization or validation and note that BCMs increasingly use social media data and generally incorporate multiple sources of information (16/178), multiple types of information (17/178) or both (9/178). We conclude that individual-level models are increasingly used and useful to model behaviour changes. Despite recent advancements, we remain concerned that most models are purely theoretical and lack representative data and a validation process

Boxplots representing the exploration of the variation of selected outputs (rows) according to the range of variation of each uncertain factor (columns).

<p>The first column corresponds to the variation of the factor “between-batch transmission rate through the airborne route <i>β</i>_<i>air</i>”, with 6 variation levels. The second corresponds to “the duration of the active immunity period <i>σ</i>_<i>1</i>”, with 6 variation levels and the third column corresponds to “the susceptibility to reinfection <i>φ</i>”, with 3 variation levels. Different letters within panel (a, b, c, d and e) represent statistically different distributions (Kruskal-Wallis test).</p

Parameter values used in the metapopulation dynamics model reared in a 7-batch rearing system (from: [34,35]).

<p>Parameter values used in the metapopulation dynamics model reared in a 7-batch rearing system (from: [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0163672#pone.0163672.ref034" target="_blank">34</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0163672#pone.0163672.ref035" target="_blank">35</a>]).</p

Survival analysis of swIAV within-herd persistence according to the level of susceptibility to infection for MDA-positive piglets.

<p>100 simulations per scenario, χ² Log rank test = 8.48, <i>p</i>-value = .004.</p

MOESM1 of Control of endemic swine flu persistence in farrow-to-finish pig farms: a stochastic metapopulation modeling assessment

Additional file 1. Survival analysis of swIAV fade-out in breeding sows reared in the 5- (A) or 20-BR system (B) according to the vaccination scheme (batch-to-batch or mass vaccination every 3 or 4 months). 200 simulations per scenario, χ2 Log rank test = 121, 3 df, p < 0.001

Parameter values used in the swIAV infection dynamics model.

<p>Parameter values used in the swIAV infection dynamics model.</p

Equations determining the transition probabilities for each health state transition (illustrated in Fig 2) in each facility type.

<p>Equations determining the transition probabilities for each health state transition (illustrated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0163672#pone.0163672.g002" target="_blank">Fig 2</a>) in each facility type.</p

Facilities modelled in the farrow-to-finish pig herd.

<p>Facilities modelled in the farrow-to-finish pig herd.</p

swIAV infection states.

<p><i>M</i>: Animals with MDAs; <i>S</i>₁: Naïve animals; <i>I</i>₁: Infected; <i>R</i>₁: Recovered; <i>S</i>₂: Susceptible to reinfection; <i>I</i>₂: Re-infected; <i>R</i>₂: Recovered after reinfection. Full transition rates (TR₁ → TR₃₂) are developed in Equations (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0163672#pone.0163672.t003" target="_blank">Table 3</a>).</p

Characteristics of the epidemics within batches according to the prevalence of MDA-positive piglets.

<p>A. Duration of the epidemics within batch. B. Number of shedding piglets at the epidemic peak. C. Age of the piglets at infection-time.</p