The DOI matches its Crossref record; 151 of the 151 references it cites were found in a registry or an index.
Behavioural change models for infectious disease transmission: a systematic review (2010–2015)
Open accessAbstract
We review behavioural change models (BCMs) 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.
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Cites
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & for the PRISMA Group (2009) · BMJ · doi:10.1136/bmj.b2535 · Cited by 83,823
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.
(2009) · PubMed Central · Cited by 44,859
Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & the PRISMA Group* (2009) · Annals of Internal Medicine · doi:10.7326/0003-4819-151-4-200908180-00135 · Cited by 37,554
Cochrane Handbook for Systematic Reviews of Interventions: Cochrane Book Series
(2008) · doi:10.1002/9780470712184 · Cited by 25,048
Social Learning Theory and the Health Belief Model
Rosenstock, I. M., Strecher, V. J., & Becker, M. H. (1988) · Health Education Quarterly · doi:10.1177/109019818801500203 · Cited by 5,564 · cited 1×
“More promising sources of information include: survey data using, for instance, the HBM framework (also see [191, 195, 196] ) or time-use surveys [3, 14, 23, 24, 45, 48, 60, 72, 85, 127, 183] or digital sources such as social media [25, 60, 66, 146, 197] .”
BackgroundSocial Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases
Mossong, J., Hens, N., Jit, M., Beutels, P., Auranen, K., Mikolajczyk, R., Massari, M., Salmaso, S., Tomba, G. S., Wallinga, J., et al. (2008) · PLoS Medicine · doi:10.1371/journal.pmed.0050074 · Cited by 2,900
Self-citationModelling the influence of human behaviour on the spread of infectious diseases: a review
Funk, S., Salathé, M., & Jansen, V. A. A. (2010) · Journal of The Royal Society Interface · doi:10.1098/rsif.2010.0142 · Cited by 1,314
Rubin, G. J., Amlot, R., Page, L., & Wessely, S. (2009) · BMJ · doi:10.1136/bmj.b2651 · Cited by 1,106
Gibbons, R. S. (1992) · Cited by 743
Saving Human Lives: What Complexity Science and Information Systems can Contribute
Helbing, D., Brockmann, D., Chadefaux, T., Donnay, K., Blanke, U., Woolley-Meza, O., Moussaid, M., Johansson, A., Krause, J., Schutte, S., et al. (2015) · Journal of Statistical Physics · doi:10.1007/s10955-014-1024-9 · Cited by 615
Cited by
Systematic Literature Review on the Spread of Health-related Misinformation on Social Media
Wang, Y., McKee, M., Torbica, A., & Stuckler, D. (2019) · Social Science & Medicine · doi:10.1016/j.socscimed.2019.112552 · Cited by 1,806
“However, this is still in its infancy and one recent systematic review of behavioural change models found that most papers investigating spread of health-related information and behavioural changes are theoretical, failing to use real-life social media data (Verelst et al., 2016).”
The impact of unplanned school closure on children’s social contact: rapid evidence review
Brooks, S. K., Smith, L. E., Webster, R. K., Weston, D., Woodland, L., Hall, I., & Rubin, G. J. (2020) · Eurosurveillance · doi:10.2807/1560-7917.es.2020.25.13.2000188 · Cited by 159
“Recent reviews of the incorporation of human behaviour into infectious disease models have advocated the use of appropriate, detailed, real-world behavioural data within infectious disease modelling [44,45].”
Schnyder, S. K., Molina, J. J., Yamamoto, R., & Turner, M. S. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2409362122 · Cited by 12
Metadata
- Authors
- Verelst, F., Willem, L., & Beutels, P.
- Venue
- Journal of The Royal Society Interface
- Publisher
- The Royal Society
- Published
- 2016-12
- Volume
- 13
- Issue
- 125
- Pages
- 20160820
- ISSN
- 1742-5662 (ISSN-L)
- 1742-5689
- OpenAlex
- W2563950034
- Cited by
- 382
- References
- 151
- FWCI
- 3.03
- Type
- journal article
- Language
- en
- Open access
- green
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