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Record W2616759249 · doi:10.1016/s2214-109x(17)30203-6

Financing of international collective action for epidemic and pandemic preparedness

2017· article· en· W2616759249 on OpenAlexaboutno aff
Gavin Yamey, Marco Schäferhoff, Ole Kristian Aars, Barry R. Bloom, Dennis Carroll, Mukesh Chawla, Victor J. Dzau, Ricardo Echalar, Indermit S. Gill, Tore Godal, Dean T. Jamison, Patrick Kelley, F. Kristensen, Ceci Mundaca-Shah, Ben Oppenheim, Julie A. Pavlin, Rodrigo Salvado, Peter Sands, Rocio Schmunis, Agnès Soucat, Lawrence H. Summers, Anas El Turabi, Ron Waldman, Ed Whiting

Bibliographic record

VenueThe Lancet Global Health · 2017
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsnot available
FundersHarvard UniversityCoalition for Epidemic Preparedness InnovationsWellcome TrustGeorge Washington UniversityUniversity of California, San FranciscoWorld Health OrganizationFairfield UniversityBill and Melinda Gates FoundationUnited States Agency for International Development
KeywordsPandemicPreparednessScopusOutbreakPolitical scienceEconomic impact analysisDevelopment economicsEconomic growthGeographyDiseaseCoronavirus disease 2019 (COVID-19)MedicineVirologyEconomicsMEDLINEInfectious disease (medical specialty)Law

Abstract

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The global pandemic response has typically followed cycles of panic followed by neglect. We are now, once again, in a phase of neglect, leaving the world highly vulnerable to massive loss of life and economic shocks from natural or human-made epidemics and pandemics. Quantifying the size of the losses caused by large-scale outbreaks is challenging because the epidemiological and economic research in this field is still at an early stage. Research on the 1918 influenza H1N1 pandemic and recent epidemics and pandemics has shown a range of estimated losses (panel).1Taubenberger JK Morens DM 1918 influenza: the mother of all pandemics.Emerg Infect Dis. 2006; 12: 15-22Crossref PubMed Scopus (24) Google Scholar, 2Madhav N, Oppenheim B, Gallivan M, et al. Pandemics: risk, impacts, and mitigation. In: Jamison DT, Nugent R, Gelband H, et al, eds. Disease Control Priorities, 3rd edn, Volume 9. Washington, DC: World Bank (in press).Google Scholar, 3Centers for Disease Control and PreventionFact sheet: basic information about SARS.https://www.cdc.gov/sars/about/fs-sars.pdfGoogle Scholar, 4Lee J-W McKibbin WJ Estimating the global economic costs of SARS.in: Knobler S Mahmoud A Lemon S Institute of Medicine Forum on Microbial Threats. National Academies Press, Washington, DC2004Google Scholar, 5World Bank2014–2015 West Africa Ebola crisis: impact update.http://pubdocs.worldbank.org/en/297531463677588074/Ebola-Economic-Impact-and-Lessons-Paper-short-version.pdfGoogle Scholar, 6PAHOZika cases and congenital syndrome associated with Zika virus reported by countries and territories in the Americas, 2015–2017 cumulative cases.http://www.paho.org/hq/index.php?option=com_docman&task=doc_view&Itemid=270&gid=38164&lang=enGoogle Scholar, 7World BankThe short-term economic costs of Zika in Latin America and the Caribbean (LCR). World Bank Group, Washington, DC2016Google ScholarPanelHealth and economic impacts of epidemics and pandemicsH1N1 influenza (1918)•50 million deaths;1Taubenberger JK Morens DM 1918 influenza: the mother of all pandemics.Emerg Infect Dis. 2006; 12: 15-22Crossref PubMed Scopus (24) Google Scholar gross domestic product (GDP) loss of 3% in Australia, 15% in Canada, 17% in the UK, and 11% in the USA2Madhav N, Oppenheim B, Gallivan M, et al. Pandemics: risk, impacts, and mitigation. In: Jamison DT, Nugent R, Gelband H, et al, eds. Disease Control Priorities, 3rd edn, Volume 9. Washington, DC: World Bank (in press).Google ScholarSevere acute respiratory syndrome (SARS) (2003)•774 deaths;3Centers for Disease Control and PreventionFact sheet: basic information about SARS.https://www.cdc.gov/sars/about/fs-sars.pdfGoogle Scholar global economic loss of US$52·2 billion4Lee J-W McKibbin WJ Estimating the global economic costs of SARS.in: Knobler S Mahmoud A Lemon S Institute of Medicine Forum on Microbial Threats. National Academies Press, Washington, DC2004Google ScholarEbola (2013)•10 600 deaths and a GDP loss of US$2·8 billion across Guinea, Liberia, and Sierra Leone5World Bank2014–2015 West Africa Ebola crisis: impact update.http://pubdocs.worldbank.org/en/297531463677588074/Ebola-Economic-Impact-and-Lessons-Paper-short-version.pdfGoogle ScholarZika (2015–16)•20 deaths6PAHOZika cases and congenital syndrome associated with Zika virus reported by countries and territories in the Americas, 2015–2017 cumulative cases.http://www.paho.org/hq/index.php?option=com_docman&task=doc_view&Itemid=270&gid=38164&lang=enGoogle Scholar and an expected loss of US$3·5 billion in the Latin American and Caribbean region7World BankThe short-term economic costs of Zika in Latin America and the Caribbean (LCR). World Bank Group, Washington, DC2016Google Scholar H1N1 influenza (1918) •50 million deaths;1Taubenberger JK Morens DM 1918 influenza: the mother of all pandemics.Emerg Infect Dis. 2006; 12: 15-22Crossref PubMed Scopus (24) Google Scholar gross domestic product (GDP) loss of 3% in Australia, 15% in Canada, 17% in the UK, and 11% in the USA2Madhav N, Oppenheim B, Gallivan M, et al. Pandemics: risk, impacts, and mitigation. In: Jamison DT, Nugent R, Gelband H, et al, eds. Disease Control Priorities, 3rd edn, Volume 9. Washington, DC: World Bank (in press).Google Scholar Severe acute respiratory syndrome (SARS) (2003) •774 deaths;3Centers for Disease Control and PreventionFact sheet: basic information about SARS.https://www.cdc.gov/sars/about/fs-sars.pdfGoogle Scholar global economic loss of US$52·2 billion4Lee J-W McKibbin WJ Estimating the global economic costs of SARS.in: Knobler S Mahmoud A Lemon S Institute of Medicine Forum on Microbial Threats. National Academies Press, Washington, DC2004Google Scholar Ebola (2013) •10 600 deaths and a GDP loss of US$2·8 billion across Guinea, Liberia, and Sierra Leone5World Bank2014–2015 West Africa Ebola crisis: impact update.http://pubdocs.worldbank.org/en/297531463677588074/Ebola-Economic-Impact-and-Lessons-Paper-short-version.pdfGoogle Scholar Zika (2015–16) •20 deaths6PAHOZika cases and congenital syndrome associated with Zika virus reported by countries and territories in the Americas, 2015–2017 cumulative cases.http://www.paho.org/hq/index.php?option=com_docman&task=doc_view&Itemid=270&gid=38164&lang=enGoogle Scholar and an expected loss of US$3·5 billion in the Latin American and Caribbean region7World BankThe short-term economic costs of Zika in Latin America and the Caribbean (LCR). World Bank Group, Washington, DC2016Google Scholar A limitation in assessing the economic costs of outbreaks is that they only capture the impact on income. Fan and colleagues8Fan VY Jamison DT Summers LH The inclusive cost of pandemic influenza risk.http://www.nber.org/papers/w22137Google Scholar recently addressed this limitation by estimating the “inclusive” cost of pandemics: the sum of the cost in lost income and a dollar valuation of the cost of early death. They found that for Ebola and severe acute respiratory syndrome (SARS), the true (“inclusive”) costs are two to three times the income loss. For extremely serious pandemics such as that of influenza in 1918, the inclusive costs are over five times income loss. The inclusive costs of the next severe influenza pandemic could be US$570 billion each year or 0·7% of global income (range 0·4–1·0%)8Fan VY Jamison DT Summers LH The inclusive cost of pandemic influenza risk.http://www.nber.org/papers/w22137Google Scholar—an economic threat similar to that of global warming, which is expected to cost 0·2–2·0% of global income annually. Given the magnitude of the threat, we call for scaled-up financing of international collective action for epidemic and pandemic preparedness. Two planks of preparedness must be strengthened. The first is public health capacity—including human and animal disease surveillance—as a first line of defence.9Sands PS Mundaca-Shah Dzau VJ The neglected dimension of global security—a framework for countering infectious-disease crises.N Engl J Med. 2016; 374: 1281-1287Crossref PubMed Scopus (154) Google Scholar Animal surveillance is important since most emerging infectious diseases with outbreak potential originate in animals. Rigorous external assessment of national capabilities is critical; WHO developed the Joint External Evaluation (JEE) tool specifically for this purpose.10WHOJoint external evaluation tool: International Health Regulations.http://apps.who.int/iris/handle/10665/204368Date: 2005Google Scholar Financing for this first plank will largely be through domestic resources, but supplementary donor financing to low-income, high-risk countries is also needed. The second plank is financing global efforts to accelerate research and development (R&D) of vaccines, drugs, and diagnostics for outbreak control, and to strengthen the global and regional outbreak preparedness and response system. These two international collective action activities are underfunded.11Schäferhoff M Fewer S Kraus J et al.How much donor financing for health is channelled to global versus country-specific aid functions?.Lancet. 2015; 386: 2436-2441Summary Full Text Full Text PDF PubMed Scopus (32) Google Scholar Medical countermeasures against many emerging infectious diseases are currently missing. We need greater investment in development of vaccines, therapeutics, and diagnostics to prevent potential outbreaks from becoming humanitarian crises. The new Coalition for Epidemic Preparedness Innovations (CEPI), which aims to mobilise $1 billion over 5 years, is developing vaccines against known emerging infectious diseases as well as platforms for rapid development of vaccines against outbreaks of unknown origin. The WHO R&D Blueprint for Action to Prevent Epidemics12WHOR&D Blueprint for Action to Prevent Epidemics.http://www.who.int/csr/research-and-development/blueprint/en/Google Scholar is a new mechanism for coordinating and prioritising the development of drugs and diagnostics for emerging infectious diseases. Consolidating and enhancing donor support for these new initiatives would be an efficient way to channel resources aimed at improving global outbreak preparedness and response. Crucial components of the global and regional system for outbreak control include surge capacity (eg, the ability to urgently deploy human resources); providing technical guidance to countries in the event of an outbreak; and establishing a coordinated, interlinked global, regional, and national surveillance system. These activities are the remit of several essential WHO financing envelopes that all face major funding shortfalls. The Contingency Fund for Emergencies finances surge outbreak response for up to 3 months. The fund has a capitalisation target of $100 million of flexible voluntary contributions, which needs to be replenished with about $25–50 million annually, depending on the extent of the outbreak in any given year. However, as of April 30, 2017, only $37·65 million had been contributed, with an additional $4 million in pledges.13WHOContingency Fund for Emergencies income and allocations.http://www.who.int/about/who_reform/emergency-capacities/contingency-fund/contribution/en/Google Scholar The WHO Health Emergencies and Health Systems Preparedness Programmes face an annual shortfall of $225 million in funding their epidemic and pandemic prevention and control activities.14WHOProgress report on the development of the WHO Health Emergencies Programme.http://www.who.int/about/who_reform/emergency-capacities/who-health-emergencies-programme-progress-report-march-2016.pdf?ua=1Date: 30 March 2016Google Scholar Previous health emergencies have shown that it can take time to organise global collective action and provide financing to the national and local level. In such situations, a global mechanism should offer a rapid injection of liquidity to affected countries. The World Bank's Pandemic Emergency Financing Facility (PEF) is a proposed global insurance mechanism for pandemic emergencies.15World BankPandemic Emergency Facility: frequently asked questions.http://www.worldbank.org/en/topic/pandemics/brief/pandemic-emergency-facility-frequently-asked-questionsGoogle Scholar It aims to provide surge funding for response efforts to help respond to rare, high-burden disease outbreaks, preventing them from becoming more deadly and costly pandemics. The PEF currently proposes a coverage of $500 million for the insurance window; increasing the current coverage will require additional donor commitments. In addition, the PEF has a $50–100 million replenishable cash window. As the world's health ministers meet this month for the World Health Assembly, we propose five key ways to help prevent mortality and economic shocks from disease outbreaks. First, to accelerate development of new technologies to control outbreaks, donors should expand their financing for CEPI and support the WHO R&D Blueprint for Action to Prevent Epidemics. Second, funding gaps in the WHO Contingency Fund for Emergencies and the WHO Health Emergencies Programme should be urgently filled and the PEF should be fully financed. Third, all nations should support their own and other countries' national preparedness efforts, including committing to the JEE process. Fourth, we believe it would be valuable to create and maintain a regional and country-level pandemic risk and preparedness index. This index could potentially be used as a way to review preparedness in International Monetary Fund article IV consultations (regular country reports by staff to its Board). Finally, we call for a new global effort to develop long-term national, regional, and global investment plans to create a world secure from the threat of devastation from outbreaks. This article summarises the recommendations of a workshop held at the National Academy of Medicine, Washington, DC, USA, co-hosted by the Center for Policy Impact in Global Health at Duke University, Durham, NC, USA and the Coalition for Epidemic Preparedness Innovations, Oslo, Norway. Participants' travel and accommodation were supported by the Center for Policy Impact in Global Health. BO is a consultant to Metabiota, a private company engaged in infectious disease risk modelling and analytical services. In this capacity, he has led the development of an index measuring national capacity to respond to epidemic and pandemic disease outbreaks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.477
GPT teacher head0.559
Teacher spread0.082 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations69
Published2017
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