Call for papers:
Online session at this year’s RGS-IBG conference

Geographies of COVID-19: from individual to social recovery.

This session, supported by the Quantitative Methods Research Group and by the Population Geography Research Group focuses upon the use of data and of data models to communicate, measure and to understand the geographies of COVID-19, and the people and places that they impact at a range of scale, in the UK or beyond. The full session description is below.

Paper abstracts are invited by the deadline of Friday March 18th, to [log in to unmask] These should consist of a title (max. 50 words), abstract (max. 300 words), 5 key words, your title, first name, last name, email address, institution and country. This information is required for us to upload the abstract to the conference’s portal. Please also indicate whether you are planning to attend the conference in-person or online. Please note, however, that this session will be held online. Further details about the conference can be found at https://www.rgs.org/research/annual-international-conference

Please do forward this call for papers to others who may be interested in participating.
With thanks,
Richard Harris, University of Bristol, [log in to unmask]
Karyn Morrissey, Technical University of Denmark, [log in to unmask]
Mark Green, University of Liverpool, [log in to unmask]

About the session:
Through Government dashboards, online portals and other sources of administrative, survey and ‘big’ data, the COVID-19 pandemic has provided historically unparalleled monitoring of which places and populations are most infected by the virus at cross- and sub-national scales. These data shed light on the structural inequalities and socio-economic geographies that shape who is more at risk from the virus, as well as revealing where vaccine uptake has been greatest and where the roll-out has been slower, whether that be due to supply (which populations are prioritised) or demand (e.g., anti-vaccine skepticism). This session invites papers measuring, modelling or mapping such data to aid understanding of the syndemic nature of the disease – what Horton (2020), after Singer et al. (2017) describes as the biological and social interactions that are important for prognosis, treatment, and health policy: for social not just individual recovery. Topics include but are not limited to geographical communication of who the disease is in-/affecting, when and where; measuring the scale of the disease and evidencing whether spatial context matters; applications of machine learning, statistical models or novel approaches to illuminate the spatial patterns in the data; modelling spatial diffusion; and shedding light on social behaviours and attitudes, such as anti-vax sentiment and conspiracy belief. Underpinning the session is a belief that understanding the geographies of COVID-19 evidences associated socio-spatial inequalities that have to be tackled alongside other health interventions if a post-COVID geography of recovery is to be fully achieved.

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