Evidence map›Paper›PMID 39030585›Full record

ArticleGlobalization and health2024

How feasible is it to mobilize $31 billion a year for pandemic preparedness and response? An economic growth modelling analysis.

Minahil Shahid, Marco Schäferhoff, Garrett Brown, Gavin Yamey

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Article in Globalization and health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Minahil ShahidCenter for Policy Impact in Global Health, Duke University, Durham, NC, USA. shahid.minahil@gmail.com.ORCID 0000-0001-8497-3202
Marco SchäferhoffOpen Consultants, Berlin, Germany.
Garrett BrownSchool of Politics and International Studies, University of Leeds, Leeds, UK.
Gavin YameyCenter for Policy Impact in Global Health, Duke University, Durham, NC, USA.

Funding

UK Economic and Social Research Council ES/X001482/1
6 · The paper itself

Abstract

backgroundCovid-19 has reinforced health and economic cases for investing in pandemic preparedness and response (PPR). The World Bank and World Health Organization (WHO) propose that low- and middle-income governments and donor countries should invest $31.1 billion each year for PPR. We analyse, based on the projected economic growth of countries between 2022 and 2027, how likely it is that low- and middle-income country governments and donors can mobilize the estimated funding.

methodsWe modelled trends in economic growth to project domestic health spending by low- and middle-income governments and official development assistance (ODA) by donors for years 2022 to 2027. We modelled two scenarios for countries and donors - a constant and an optimistic scenario. Under the constant scenario we assume that countries and donors continue to dedicate the same proportion of their health spending and ODA as a share of gross domestic product (GDP) and gross national income (GNI), respectively, as they did during baseline (the latest year for which data are available). In the optimistic scenario, we assume a yearly increase of 2.5% in health spending as a share of GDP for countries and ODA as a share of GNI for donors.

findingsOur analysis shows that low-income countries would need to invest on average 37%, lower-middle income countries 9%, and upper-middle income countries 1%, of their total health spending on PPR each year under the constant scenario to meet the World Bank WHO targets. Donors would need to allocate on average 8% of their total ODA across all sectors to PPR each year to meet their target.

conclusionsThe World Bank WHO targets for PPR will not be met unless low- and middle-income governments and donors spend a much higher share of their funding on PPR. Even under optimistic growth scenarios, low-income and lower-middle income countries will require increased support from global health donors. The donor target cannot be met using the yearly increase in ODA under any scenario. If the country and donor targets are not met, the highest-impact health security measures need to be prioritized for funding. Alternative sources of PPR financing could include global taxation (e.g., on financial transactions, carbon, or airline flights), cancelling debt, and addressing illicit financial flows. There is also a need for continued work on estimating current PPR costs and funding requirements in order to arrive at more enduring and reliable estimates.

Indexed as

COVID-19Developing CountriesEconomic DevelopmentModels, EconomicPandemicsGlobal HealthGross Domestic ProductHealth ExpendituresHumansPandemic PreparednessCOVID-19Health financingLow- and middle-income countriesPandemic preparedness and response

Identifiers

PMID39030585
PMCPMC11264850

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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.