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Most mathematical models have focused on direct health impacts, neglecting the economic costs of control measures. Here, we introduce a framework that captures both health and economic costs and compare the expected aggregate costs of alternative strategies across a range of epidemiological and economic parameters. We find that for diseases with low severity, mitigation tends to be the most cost-effective option. For more severe diseases, suppression tends to be most cost-effective if the basic reproduction number R0 is relatively low, while elimination tends to be more cost-effective if R0 is high. We use the example of New Zealand's response to the COVID-19 pandemic in 2020 to anchor our framework to a real-world case study. We find that parameter estimates for COVID-19 in New Zealand put it close to or above the threshold at which elimination becomes more cost-effective than mitigation. We conclude that our proposed framework holds promise as a decision-support tool for pandemic threats, with further work needed to account for population heterogeneity and other factors relevant to decision-making.<\/jats:p>","DOI":"10.1098\/rsif.2026.0098","type":"journal-article","created":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T00:09:12Z","timestamp":1787098152000},"source":"Crossref","is-referenced-by-count":0,"title":["Joint economic and epidemiological modelling of alternative pandemic response strategies"],"prefix":"10.1098","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7539-3465","authenticated-orcid":false,"given":"Michael John","family":"Plank","sequence":"first","affiliation":[{"name":"School of Mathematics and Statistics, University of Canterbury 1 , Christchurch, Canterbury, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Megan","family":"Sushames","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, University of Canterbury 1 , Christchurch, Canterbury, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy","family":"Fisher-Taylor","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, University of Canterbury 1 , Christchurch, Canterbury, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amin","family":"Afshari","sequence":"additional","affiliation":[{"name":"Department of Biological Sciences, Simon Fraser University 2 , Burnaby, British Colombia, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8545-5212","authenticated-orcid":false,"given":"Robin N.","family":"Thompson","sequence":"additional","affiliation":[{"name":"Mathematical Institute, University of Oxford 3 , Oxford, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6461-5686","authenticated-orcid":false,"given":"Amy","family":"Hurford","sequence":"additional","affiliation":[{"name":"Biology Department and Department of Mathematics and Statistics, Memorial University of Newfoundland 4 , Saint John's, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3468-6517","authenticated-orcid":false,"given":"Shaun","family":"Hendy","sequence":"additional","affiliation":[{"name":"School of Science in Society, Victoria University of Wellington 5 , Wellington, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"175","published-online":{"date-parts":[[2026,8,19]]},"reference":[{"key":"2026081820090845900_bib1","doi-asserted-by":"crossref","first-page":"85","DOI":"10.3201\/eid1901.120124","article-title":"Novel framework for assessing epidemiologic effects of influenza epidemics and pandemics","volume":"19","author":"Reed","year":"2013","journal-title":"Emerg. 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