ArticleJournal of the Royal Society, Interface2014
Epidemic cycles driven by host behaviour.
Article in Journal of the Royal Society, Interface, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Behavioural change models for infectious disease transmission: a systematic review (2010-2015).Journal of the Royal Society, Interface · 2016Pooled it
- Tracking Dynamics of Superspreading Through Contacts, Exposures, and Transmissions in Edge-Based Network Epidemics.Bulletin of mathematical biology · 2026Article
- Rates of SARS-CoV-2 transmission and vaccination impact the fate of vaccine-resistant strains.Scientific reports · 2021Article
- Localization, epidemic transitions, and unpredictability of multistrain epidemics with an underlying genotype network.PLoS computational biology · 2021Article
- Adaptive social contact rates induce complex dynamics during epidemics.PLoS computational biology · 2021Article
- Dynamics of beneficial epidemics.Scientific reports · 2019Article
- A stochastic SIR network epidemic model with preventive dropping of edges.Journal of mathematical biology · 2019Article
- Bursting endemic bubbles in an adaptive network.Physical review. E · 2018Article
- Asymmetric percolation drives a double transition in sexual contact networks.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
- Dynamics of epidemic diseases on a growing adaptive network.Scientific reports · 2017Article
- Eradicating infectious disease using weakly transmissible vaccines.Proceedings. Biological sciences · 2016Article
- European Neolithic societies showed early warning signals of population collapse.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Syphilis: Re-emergence of an old foe.Microbial cell (Graz, Austria) · 2016Review
- The determinant of periodicity in Mycoplasma pneumoniae incidence: an insight from mathematical modelling.Scientific reports · 2015Article
- Syphilis in the economic center of South China: results from a real-time, web-based surveillance program.BMC infectious diseases · 2015Article
- Asymptomatic transmission and the resurgence of Bordetella pertussis.BMC medicine · 2015Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Host immunity and demographics (the recruitment of susceptibles via birthrate) have been demonstrated to be a key determinant of the periodicity of measles, pertussis and dengue epidemics. However, not all epidemic cycles are from pathogens inducing sterilizing immunity or are driven by demographics. Many sexually transmitted infections are driven by sexual behaviour. We present a mathematical model of disease transmission where individuals can disconnect and reconnect depending on the infectious status of their contacts. We fit the model to historic syphilis (Treponema pallidum) and gonorrhea (Neisseria gonorrhoeae) incidence in the USA and explore potential intervention strategies against syphilis. We find that cycles in syphilis incidence can be driven solely by changing sexual behaviour in structured populations. Our model also explains the lack of similar cycles in gonorrhea incidence even if the two infections share the same propagation pathways. Our model similarly illustrates how sudden epidemic outbreaks can occur on time scales smaller than the characteristic demographic time scale of the population and that weaker infections can lead to more violent outbreaks. Behaviour also appears to be critical for control strategies as we found a bigger sensitivity to behavioural interventions than antibiotic treatment. Thus, behavioural interventions may play a larger role than previously thought, especially in the face of antibiotic resistance and low intervention efficacies.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.