A review and agenda for integrated disease models including social and behavioural factors

Bedson, Jamie; Skrip, Laura; Pedi, Danielle; Abramowitz, Sharon; Carter, Simone; Jalloh, Mohamed F.; Funk, Sebastian; Gobat, Nina; Giles‐Vernick, Tamara; Chowell, Gerardo; Almeida, João Rangel de; Elessawi, Rania; Scarpino, Samuel V.; Hammond, Ross A.; Briand, Sylvie; Epstein, Joshua M.; Hébert‐Dufresne, Laurent; Althouse, Benjamin M.

doi:10.1038/s41562-021-01136-2

Cited by 124 publications

(95 citation statements)

References 155 publications

(180 reference statements)

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“…Modeling the interplay of human behavior and disease spread is one of the grand challenges of infectious disease modeling. While not being the first to model behavioral adaptation [17,[51][52][53][54][55], we incorporate data-driven insights into our modeling framework, inspiring the explicit functional dependency between risk and health-protective behavior as well as vaccine hesitancy in the context of the COVID-19 pandemic. Thereby, we can incorporate self-regulation mechanisms into our scenario analysis, which best qualitatively describe what is to be expected in the future or in the event of the emergence of novel SARS-CoV-2 VOCs, such as the Omicron variant.…”

Section: Discussionmentioning

confidence: 99%

Interplay Between Risk Perception, Behavior, and COVID-19 Spread

et al. 2022

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Pharmaceutical and non-pharmaceutical interventions (NPIs) have been crucial for controlling COVID-19. They are complemented by voluntary health-protective behavior, building a complex interplay between risk perception, behavior, and disease spread. We studied how voluntary health-protective behavior and vaccination willingness impact the long-term dynamics. We analyzed how different levels of mandatory NPIs determine how individuals use their leeway for voluntary actions. If mandatory NPIs are too weak, COVID-19 incidence will surge, implying high morbidity and mortality before individuals react; if they are too strong, one expects a rebound wave once restrictions are lifted, challenging the transition to endemicity. Conversely, moderate mandatory NPIs give individuals time and room to adapt their level of caution, mitigating disease spread effectively. When complemented with high vaccination rates, this also offers a robust way to limit the impacts of the Omicron variant of concern. Altogether, our work highlights the importance of appropriate mandatory NPIs to maximise the impact of individual voluntary actions in pandemic control.

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Section: Discussionmentioning

confidence: 99%

Interplay Between Risk Perception, Behavior, and COVID-19 Spread

et al. 2022

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“…A challenge for modellers is known as “data integration” [9] . It hypothesises that combining different sources of data can reveal information that would be inaccessible using a single data source.…”

Section: A Deluge Of Datamentioning

confidence: 99%

Challenges for mathematical epidemiological modelling

Crépey¹,

Noël²,

Alizon³

2022

Anaesthesia Critical Care & Pain Medicine

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“…This includes fear (and overcompliance) or epidemic fatigue (and a lack of compliance), which spread in social networks independently from disease prevalence. 13 Since ABMs model interactions in social networks, they are also able to capture the emergence of pockets of behaviour and new communities. However, capturing the behaviour of individuals, their activities and social networks, requires much more detailed data inputs and greater computing power than compartmental approaches.…”

Section: Introductionmentioning

confidence: 99%

Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward

et al. 2022

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The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world’s most vulnerable populations at risk. Epidemiological modelling is vital to guiding evidence-informed or data-driven decision making. In forced displacement contexts, and in particular refugee and internally displaced people (IDP) settlements, it meets several challenges including data availability and quality, the applicability of existing models to those contexts, the accurate modelling of cultural differences or specificities of those operational settings, the communication of results and uncertainties, as well as the alignment of strategic goals between diverse partners in complex situations. In this paper, we systematically review the limited epidemiological modelling work applied to refugee and IDP settlements so far, and discuss challenges and identify lessons learnt from the process. With the likelihood of disease outbreaks expected to increase in the future as more people are displaced due to conflict and climate change, we call for the development of more approaches and models specifically designed to include the unique features and populations of refugee and IDP settlements. To strengthen collaboration between the modelling and the humanitarian public health communities, we propose a roadmap to encourage the development of systems and frameworks to share needs, build tools and coordinate responses in an efficient and scalable manner, both for this pandemic and for future outbreaks.

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A review and agenda for integrated disease models including social and behavioural factors

Cited by 124 publications

References 155 publications

Interplay Between Risk Perception, Behavior, and COVID-19 Spread

Interplay Between Risk Perception, Behavior, and COVID-19 Spread

Challenges for mathematical epidemiological modelling

Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward

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