Reposted by Hampton Gaddy
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Hampton Gaddy @hggaddy.bsky.social will discuss missing data, Indigenous mortality during the 1918 flu, and the Alaskan census 📊
Hampton Gaddy
@hggaddy.bsky.social
2.5K followers 567 following 143 posts
Demographer | Postdoc @magdalenoxford.bsky.social | Assistant Director, callevacentre.org | Usually working on the 1918 flu | he/him | hggaddy.github.io
![Call for papers for a special issue of Population Studies – a journal of demography
‘How do we estimate excess mortality? Current problems and methodological solutions’
Guest editors:
Hampton Gaddy (University of Oxford, UK)
Victoria Knutson (University of Washington, USA)
Maarten van Wijhe (Roskilde University, Denmark)
José Manuel Aburto (London School of Hygiene & Tropical Medicine, UK)
Alyson van Raalte (Max Planck Institute for Demographic Research, Germany)
Motivation:
In the last 20 years, excess mortality estimation has become a widespread technique for quantifying the demographic and social impacts of contemporary and historical mortality crises. However, there is surprisingly little systematic methodological work on the topic, and the work that has been published has shown that excess mortality estimates can be highly sensitive to the theoretical and practical foundation of the underlying models, as well as issues of data availability (e.g. Andreasen & Simonsen, 2011; Chandra & Christensen, 2019; Nepomuceno et al., 2022; Duerst & Schöley, 2024; Wakefield & Knutson, 2025). The effect of these issues is that, for example, in the context of its official assessment of the Covid-19 pandemic in Norway, the Norwegian Institute of Public Health declared that there is simply
‘no gold standard for calculating excess mortality’ (Knudsen et al., 2023).
In May 2026, the London School of Economics hosted a two-day workshop, aimed at demonstrating the need for consensus about the use of excess mortality methods and at scoping out the key areas of methodological disagreement (full programme here). One presentation outlined the preliminary results from the ‘One Epidemic, Many Estimates (1EME)’ challenge, in which 22 teams of researchers
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![estimation, as well as thoughtful methodological papers that suggest solutions to the outstanding problems and disagreements relating to how to estimate excess mortality.
The descriptive reading of the title will be fulfilled by a series of commissioned articles that speak to the current practice and long history of excess mortality estimation. The guest editors plan for this to include the 1EME paper; an essay by historians of medicine; an essay on the ethics of how (excess) mortality estimation is commonly practised; and a commentary on how excess mortality estimation has been transformed in recent years.
To fulfil the perspective reading of the title, the guest editors are making an open call for contributions relating to the methodology of excess mortality estimation. The objective of the special issue is not to establish a single preferred method for estimating excess mortality—in particular, because different excess mortality analyses have different
explicit or implicit different estimands in mind—but rather to clarify the methodological choices that drive variation in estimates, identify areas of agreement and disagreement, and provide researchers with a clearer framework for selecting and evaluating methods,
conditional on their estimand of interest (see Lundberg et al., 2021). To that end, submissions to the open call should identify a specific methodological question or problem to be addressed; offer an answer or solution to that methodological issue; and outline the conditions under which that approach is valid.
Pre-submission enquiries for submitting to the issue are mandatory and due by 1 December 2026. Enquiries should take the form of a proposed title and abstract, and should be submitted to hampton.gaddy@magd.ox.ac.uk.
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!["The population costs of this deal will be the excess deaths that can be avoided if the resources required are not devoted to paying more for new medicines. These are called the “health opportunity costs” (fig 2). They are estimated by combining the published causal estimates with projected NHS expenditure and local mortality data from 2024-25. [ref 16]"](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:lvo45tc2jcwhui5ibx4364el/bafkreidnslqlythbckmskoh7sdadt6ini7titkcpuu54rd3c33iu4euzoe)
