A Systematic Examination of International Funding Flows for Ebola Virus and Zika Virus Outbreaks 2014 – 2019: Donors, Recipients and Funding Purposes

Original research

A systematic examination of BMJ Glob Health: first published as 10.1136/bmjgh-2020-003923 on 13 April 2021. Downloaded from international funding flows for Ebola virus and Zika virus outbreaks 2014– 2019: donors, recipients and funding purposes

1 2 2,3 Emily Jade Quirk ‍ ‍ , Adrian Gheorghe ‍ ‍ , Katharina Hauck

To cite: Quirk EJ, Gheorghe A, ABSTRACT Key questions Hauck K. A systematic Introduction There has been no systematic comparison examination of international of how the policy response to past infectious disease funding flows for Ebola virus What is already known? outbreaks and epidemics was funded. This study aims and Zika virus outbreaks ►► Low-income and middle-income countries are likely 2014–2019: donors, to collate and analyse funding for the Ebola epidemic to require donations from development actors and recipients and funding and Zika outbreak between 2014 and 2019 in order to high-income governments to manage the increased purposes. BMJ Global Health understand the shortcomings in funding reporting and healthcare demand due to the COVID-19 pandemic. 2021;6:e003923. doi:10.1136/ suggest improvements. ►► Outbreak funding contributions are documented in a bmjgh-2020-003923 Methods Data were collected via a literature review and variety of places, for example, specialised financial analysis of financial reporting databases, including both reporting databases, press releases, peer-reviewed Handling editor Edwine Barasa amounts donated and received. Funding information literature. ►► Additional material is from three financial databases was analysed: Institute of ►► Existing fund tracking mechanisms have been de- published online only. To view Health Metrics and Evaluation’s Development Assistance scribed as insufficient and significant data chal- please visit the journal online for Health database, the Georgetown Infectious Disease lenges face researchers trying to collate funding (http://dx. doi.org/ 10.1136/ Atlas and the United Nations Financial Tracking Service. information from many sources, but these difficulties bmjgh-2020- 003923). A systematic literature search strategy was devised and are poorly characterised. applied to seven databases: MEDLINE, EMBASE, HMIC, What are the new findings? Received 8 September 2020 Global Health, Scopus, Web of Science and EconLit. ►► A comprehensive and detailed list of donors and http://gh.bmj.com/ Funding information was extracted from articles meeting Revised 2 March 2021 recipients of Ebola and Zika funding has been pro- Accepted 7 March 2021 the eligibility criteria and measures were taken to avoid duced, highlighting a many discrepancies between double counting. Funding was collated, then amounts international funding for outbreaks. and purposes were compared within, and between, data ►► Total literature-reported funding is greater than that sources. in financial reporting databases and database-only Results Large differences between funding reported totals varied by $2.5–$3.2 billion for Ebola (with by different data sources, and variations in format $0.2 billion reported to have gone through the Ebola on April 14, 2021 by guest. Protected copyright. © Author(s) (or their and methodology, made it difficult to arrive at precise Multi-Partner Trust Fund) and $150–$180 million for employer(s)) 2021. Re-use estimates of funding amounts and purpose. Total Zika. permitted under CC BY. disbursements reported by the databases ranged from ►► Different data sources contained different fields (eg, Published by BMJ. $2.5 to $3.2 billion for Ebola and $150–$180 million for funding descriptions), in different formats (eg, trans- 1 School of Medicine, Imperial Zika. Total funding reported in the literature is greater action date) and managed data differently (eg, used College London Faculty of than reported in databases, suggesting that databases a different flow model). Medicine, London, UK may either miss funding, or that literature sources 2MRC Centre for Global Infectious Disease Analysis, overreport. Databases and literature disagreed on the Imperial College London School main purpose of funding for socioeconomic recovery INTRODUCTION of Public Health, London, UK versus outbreak response. One of the few consistent 3 The brunt of the impact of COVID-19 has Abdul Latif Jameel Institute findings across data sources and diseases is that the initially been taken by high-income countries for Disease and Emergency USA was the largest donor. Analytics, Imperial College Conclusion Implementation of several (HICs), in which the majority of deaths have London School of Public Health, 1 recommendations would enable more effective occurred, but the virus has also affected low/ London, UK 1–3 mapping and deployment of outbreak funding for middle-income countries (LMICs). Indirect Correspondence to response activities relating to COVID-19 and future impacts due to containment measures may be 4–7 Emily Jade Quirk; epidemics. more stark in less developed countries and emily .quirk16@imperial. ac.uk a significant lack of testing may be providing

Quirk EJ, et al. BMJ Global Health 2021;6:e003923. doi:10.1136/bmjgh-2020-003923 1 BMJ Global Health

flows is undertaken by combining a literature review BMJ Glob Health: first published as 10.1136/bmjgh-2020-003923 on 13 April 2021. Downloaded from Key questions with an analysis of financial information from multiple What do the new findings imply? databases. Such a comparative analysis will inform how ►► Changes to financial reporting mechanisms are needed to obtain reporting should be organised to plan urgently needed more reliable records of pandemic funding flows. international assistance in pandemic response. This will ►► Collating and maintaining a multitude of data sources hampers a contribute to more efficient and faster funding of public clear, systematic overview of funding flows. health interventions and potentially save many lives. ►► Producers and users of funding data should formulate clear aims, weigh the advantages and disadvantages of each source and pro- ceed cautiously with the analysis and interpretation of outbreak METHODS funding information. A two-pronged method was designed to capture international funding recorded in fund tracking databases as well as in published literature. Aid is referred to as a pledge, commitment or disbursements throughout to indi- a false sense of security.1 8 9 LMICs are also less equipped cate how certain the funding is: pledges are announce- to manage the patient with COVID-19 load—peak crit- ments of intent21; commitments are ‘a firm obligation, ical care demand in low-income countries is predicted to expressed in writing and backed by the necessary funds’22 exceed capacity by 25.4 times10 and increased worldwide and a disbursement is an actual monetary transfer.21 demand for personal protective equipment may reduce LMICs’ access11—creating the conditions in which health Analysis of financial data in databases systems are susceptible to collapse. Development actors can report the aid they have donated Implementing recommended measures to curb virus or received to one of the multiple fund tracking data- transmission3 5 10 12 requires sustained funding. Most bases. Three open-access databases containing financial HIC governments are able to self-fund these mitigation data for Ebola and/or Zika were identified in February measures, but LMICs often rely on international dona- 2020, all of which contain donor contributions or funding tions, loans and in-kind contributions (non-financial assis- obtained by recipients (table 1). The Development tance like the deployment of personnel and supplies). Assistance for Health (DAH) database contains Insti- The international community must now look outside tute of Health Metrics and Evaluation (IHME) funding their own borders as their case numbers and death estimates, disaggregated in Ebola and Zika subsets. tolls come down and assist less developed countries to The Georgetown Infectious Disease Atlas (GIDA) has a prevent substantial mortality. This also reduces the risk of financial tracking site recording global health security re-introduction of virus in countries that have it already funding. The United Nations Office for the Coordina- under control—illustrating how outbreak funding can be tion of Humanitarian Affairs (UN OCHA) manages the framed as a ‘global public good’.13 ‘Financial Tracking Service’ (FTS) in which actors report 14–16 Global health funding has been analysed extensively humanitarian funding. The FTS is the only database to http://gh.bmj.com/ but relatively little is known about how international include pledges and the DAH does not record commit- aid has been deployed in previous emergency outbreak ments. The Organisation for Economic Co-operation situations, by whom, where and when. Existing finan- and Development (OECD) Creditor Reporting System cial tracking resources have previously been described was considered for inclusion, but data would duplicate as ‘not fit for purpose’ due to inconsistent reporting by those in the IHME. The OECD system also does not 17 donors and are even said to have exacerbated financing disaggregate data by Ebola and Zika specifically, and it on April 14, 2021 by guest. Protected copyright. delays during the West Africa Ebola outbreak.18 Funding covers fewer funding sources than the IHME, such as amounts recorded by different data sources vary,17 19 and private foundations. researchers trying to combine funding information from Funding information from 2014 to 2019 was identi- these different sources face significant data challenges.17 fied, which includes the West Africa Ebola epidemic This lack of effective fund stream monitoring and a (2014–2015), three Democratic Republic of Congo (perceived) lack of accountability and fear of fraud20 Ebola outbreaks (2017, 2018 and 2018–ongoing) and may also hinder the international effort to raise donor the Zika outbreaks (2015–2017). In the GIDA database, support for the COVID-19 response. the transaction year was often a multi-year interval (eg, The aim of this paper is to understand the shortcom- 2014–2016), so any transactions including years outside ings in funding reporting and monitoring for previous the target time period (eg, 2013–2014) were excluded. outbreaks, and suggest improvements, so the interna- For the DAH database, information was only available tional community can put appropriate systems in place. until 2018. Ebola and Zika funding information was We systematically analyse and compare funding contri- already present as a separate field in the DAH database. butions and amounts and funding purposes received by The GIDA did not segregate funding by health focus, so bilateral, non-governmental and private organisations, the database was downloaded and searched manually during the Ebola epidemic and Zika outbreaks between in Excel to locate funding with ‘Ebola’ or ‘Zika’ in the 2014 and 2019. A comprehensive assessment of funding project name or description; and new Ebola-specific and

2 Quirk EJ, et al. BMJ Global Health 2021;6:e003923. doi:10.1136/bmjgh-2020-003923 BMJ Global Health

Table 1 Financial reporting database characteristics including funding definition, sources of database information, relevant BMJ Glob Health: first published as 10.1136/bmjgh-2020-003923 on 13 April 2021. Downloaded from subsets, time periods for which data were available and perceived strengths, weaknesses and differentiating factors Database Data Database Funding definition Data sources range* subsets Common features Differentiating features

Development Estimates of grants Project databases, 1990–2018 ►► Donor ►► Health focus area Assistance for Health and loans for health financial statements, ►► Recipient recorded (includes (DAH)58 projects in LMICs from annual reports, internal ►► Disbursed amount Ebola and Zika bilateral agencies only revenue service forms ►► Year of funding specific) and correspondence transfer‡ ►► Funding channel with agencies†59 ►► Downloadable recorded online (intermediate agency) ►► Global burden of disease and World Bank region recorded ►► Duplicate indicator field ►► Preliminary estimate field Perceived strength: intermediate agency reported Perceived weakness: non-government funding is not disaggregated by donor except for the Bill and Melinda Gates Foundation Georgetown Commitments and Funding tracking 2014–2020 ►► Committed amounts Infectious Disease disbursements for initiatives, financial recorded Atlas (GIDA) Global global health security reports, media ►► Donor and recipient Health Security statements, press type Tracking site60 releases, directly from ►► Financial and in-kind donors and funds†61 support recorded and indicated by field ►► Funding has an associated project name and description ►► Related IHR core capacity is recorded Perceived strength: related IHR core capacity is recorded Perceived weakness:

some funding lacked a http://gh.bmj.com/ description Financial Tracking Humanitarian funding Reported by 1980–2023 Incoming ►► Committed and Service (FTS)62 (paid contributions participating actors funds pledged amounts and commitments) recorded Internal ►► Funding source and funding destination described transfers by cluster, response Outgoing plan, objective, on April 14, 2021 by guest. Protected copyright. funds activity or project ►► Exact date of funding transfer is recorded ►► Usage year Perceived strength: includes exact dates of funding transfers Perceived weakness: relies on donor reporting alone

*Database range refers to the years the database has been established; only data from 2014 to 2019 was used for this analysis. †Full methods annex explaining participating actors and data sources on cited reference. ‡Some transactions have year ranges available instead of a single year for example, ‘2014–2016’. IHR, International Health Regulations; LMICs, low/middle-income countries.

Zika-specific datasets were created. The FTS database be downloaded separately for pre-set fund groupings so allows funding sources and destinations to not only be a transactions from the (pre-set) Ebola-related groupings, country or organisation, but also an emergency, response detailed in online supplemental table A1, were down- plan, organisation or project.23 Data were only able to loaded and combined into one dataset.

Quirk EJ, et al. BMJ Global Health 2021;6:e003923. doi:10.1136/bmjgh-2020-003923 3 BMJ Global Health

As the GIDA was the only database to contain funding were assessed on a case-by-case basis and classed as a BMJ Glob Health: first published as 10.1136/bmjgh-2020-003923 on 13 April 2021. Downloaded from descriptions, it was also the only database allowing the pledge, commitment or disbursement. analysis of funding purposes. Transactions were classi- Two separate datasets were generated, one for donors fied as having one, or more, of five purposes: response, and one for recipients, henceforth referred to as ‘Liter- preparedness, socioeconomic recovery, research and ature by donor’ and ‘Literature by recipient’. This was unclassifiable. Online supplemental table A2 displays done by separating transactions into four different the classification criteria used. Further disaggregation groups, depending on whether they contained donor, of socioeconomic recovery funding was not possible, recipient or more general funding information: as GIDA funding descriptions did not contain enough 1. Articles that calculated/quoted a value for the total detail to enable this. pledged, committed or disbursed to Ebola or Zika by In some cases, the DAH database reports only prelimi- all actors in a certain timeframe. nary estimates—these were included in the analysis. The For example, the total amount disbursed towards the FTS separates fund transfers into data subsets (incoming 2014/2015 Ebola outbreak was… funds, internal transfers between UN agencies and 2. Amounts pledged, committed or disbursed from a outgoing funds) to prevent double counting.23 24 We named donor but with no recipient information. examined only incoming funds, which represent dona- For example, the UK disbursed £10 million GBP to tions made to Ebola-related activities. Duplicates were help fight Ebola. removed within each dataset and funding information 3. Amounts received in pledges, commitments or dis- was summarised by subgroups, including funding desti- bursements by named recipient but with no donor nation, source and year. information. Administrators of GIDA and DAH were contacted For example, Guinea received US$5 million to help in March 2020 for specific clarifications on data avail- combat Ebola. ability and sources, but GIDA did not respond and 4. Amounts pledged, committed or disbursed from a DAH answered in May 2020, after the analysis had been named donor to named recipient. completed. For example, the USA pledged US$1 million to the WHO Contingency Fund for Emergencies. Analysis of financial data in the literature Type 4 transactions were manipulated into both donor Academic literature containing financial amounts and recipient forms and included within type 2 and 3 donated or received for Ebola and Zika from 2014 to 2019 transaction groups. For example, China pledging $6 was sought. A systematic search strategy was devised and million to the World Food Programme would be included applied to seven databases: MEDLINE, EMBASE, HMIC, in the donor dataset as a pledge of $6 million to Ebola Global Health (all four searched via Ovid), Scopus, Web general and included in the recipient dataset as the of Science and EconLit. A full list of search terms is avail- World Food Programme receiving $6 million in pledges. able in online supplemental table A3. Type 1 transactions were kept separate and compared

Preferred Reporting Items for Systematic Reviews and only to each other. Total and actor-specific pledges, http://gh.bmj.com/ Meta-Analyses (PRISMA) guidelines were followed in commitments and disbursements were calculated for the the screening and exclusion of articles.25 Search results two datasets—online supplemental tables B1–B9 provide were exported to EndNote reference management soft- a full list of values and source articles. ware, duplicates were removed, and titles and abstracts Duplicate transactions with the exact same monetary were screened for relevance to aims. Included full-text value, purpose, donor or recipient and time frame within articles were then screened against eligibility criteria each dataset were excluded. Source articles were revis- on April 14, 2021 by guest. Protected copyright. (online supplemental table A4) by two reviewers and ited to clarify possible overlaps or double counting. For disagreements were resolved through discussion. Arti- example, one article stated that the USA had committed cles containing Ebola or Zika funding for measures that $5.4 billion26 while another publication gave a break- respond to, prepare for or aid recovery for outbreaks down of this amount into budget appropriations27—in were included, with no restrictions on study design or this case, only the information from the second article level of evidence. Non-English articles and articles with a was included, as it contained more specific information study period pre-2014 were excluded. about the funding destination. Funding information was extracted from eligible arti- Transactions with the same donor or recipient and cles, including transaction date, source of the financial purpose in an overlapping time frame were combined data, the names of donors and recipients and the funding into a new transaction, with the value depicted as a range. amount. The funding purpose was classified into one This accounts for both the possibility that the transactions or more transaction purpose types (see online supple- are actually the same funding and the possibility that mental table A2). Outside financial databases, alterna- they are different, preventing double counting as well as tive words to ‘pledge’, ‘commitment’ and ‘disbursement’ underestimation. For example, $163 million disbursed are often used to describe the certainty of transactions, between January and October 2014,19 was combined for example, ‘announcement’ or ‘provided’. When with $249 million disbursed by the same donor between extracting financial data from the literature, transactions September 2014 and January 201528 to make a collective

4 Quirk EJ, et al. BMJ Global Health 2021;6:e003923. doi:10.1136/bmjgh-2020-003923 BMJ Global Health

disbursement of $249–$412 million between January BMJ Glob Health: first published as 10.1136/bmjgh-2020-003923 on 13 April 2021. Downloaded from 2014 and January 2015. All financial values from the databases and literature were converted into constant 2019 US$, using conversion factors from a web-based tool29 that accounts for infla- tion and currency conversion. If the original transaction date was a range, the upper year was used for the original currency year.

Patient and public involvement It was not appropriate or possible to involve patients or the public in the design, or conduct, or reporting, or dissemination plans of our research. Figure 1 Total pledged, committed and disbursed to Ebola according to each data source. Minimum and maximum values are used to illustrate the discrepancies in reported RESULTS amounts between different source articles. *DAH data The three databases were found to have several common- only available from 2014 to 2018. DAH, Development alities but a notable degree of variation in terms of the Assistance for Health; FTS, Financial Tracking Service; GIDA, type of information recorded, data sources, relevant Georgetown Infectious Disease Atlas; Literature, articles containing Ebola and/or Zika funding donor contributions subsets, available time period and key fields for each (‘by donor’) and received funding (‘by recipient’) from 2014 database. These features and the perceived strengths and to 2019 identified in a search of MEDLINE, EMBASE, HMIC, weaknesses are displayed in table 1. Global Health, Scopus, Web of Science and EconLit. Nine hundred and ninety articles were identified in the literature search, of which 352 were duplicates (PRISMA 25 flow diagram in online supplemental figure C1). Two calculated the total amount provided by all donors for main types of publication were identified: articles with the DRC Ebola outbreak from August 2018 to December a primary aim of calculating funding totals; and arti- 2019 using a variety of publicly available information, cles quoting isolated numerical values alongside other mostly from OCHA and the WHO. information. There were also articles describing in-kind contributions from China30–32 and the USA.27 No infor- Individual actor funding mation regarding loans (eg, from the International Monetary Fund) was documented. As few transactions Eighty-two actors pledged funds to Ebola and 91 donors from named donors to named recipients were obtained, were documented to have actually disbursed funds, analysis showing funding flows between exact actors was according to articles identified in the literature search. unachievable. In most literature sources there was insuf- A full list of donors and their pledged, committed or ficient information to determine definitively if separately contributed amount is available in online supplemental http://gh.bmj.com/ quoted amounts represented the same transaction, there- tables B1–B3. The USA is the top donor by a large margin fore a large proportion of data is depicted as a range— according to the DAH and the literature (online supple- particularly for Ebola funding. mental figures C2 and C3). However, it appears some of this may be national spending, as according to the liter- Ebola funding ature, US agencies and jurisdictions received 23%–36%

Ebola funding information was extracted from 23 articles. of Ebola funding. The UK was the second highest donor on April 14, 2021 by guest. Protected copyright. From 2014 to 2019, total disbursements to Ebola ranged according to the DAH but the third highest according to from $2.5 billion to $13.1 billion (figure 1) depending on the literature, after the European Union. the data source being considered. Sierra Leone, Liberia and Guinea were the top direct Several articles calculated the total amounts pledged, recipient countries for Ebola for both data sources, but committed or disbursed in total for Ebola outbreaks the literature reported that the UN, the WHO and non- (online supplemental table C2). The total amount governmental organisations received high amounts as disbursed to the 2014–2015 Ebola outbreak according to well. The DRC received $0.8 million for Ebola according a UN report28 was almost six times the total calculated to the DAH database, though it is important to note that by Grépin,33 despite including data from fewer months. 2019 data is not included. The DRC also does not appear The total amount pledged according to Glassman19 34 as a recipient in the literature as no articles recording the and Grépin33 were fairly similar ($2.6–$3.8 billion) but receipt of Ebola funding post-2015 were identified. the UN report total was significantly higher, at over $9 Furthermore, the DAH database and the litera- billion.28 Two articles used the UN OCHA FTS to produce ture reported $885 million and $679 million of Ebola their totals19 33 and Glassman used data from UN OCHA, funding was disbursed to unrecorded recipients respec- but it was not clear whether this was the FTS.34 Other data tively and DAH recorded substantial contributions by sources used press releases,34 information requests and ‘Other’ donors and ‘Debt repayments’ for Ebola (online the Ebola Multi-Partner Trust Fund (MPTF).28 Moss35 supplemental figure C2). Also, in the literature, some

Quirk EJ, et al. BMJ Global Health 2021;6:e003923. doi:10.1136/bmjgh-2020-003923 5 BMJ Global Health BMJ Glob Health: first published as 10.1136/bmjgh-2020-003923 on 13 April 2021. Downloaded from

Figure 3 Total pledged, committed and disbursed to Zika according to each data source. Minimum and maximum values are used to illustrate the discrepancies in reported amounts between different source articles. *DAH data only available 2014-2018. DAH, Development Assistance for Health; GIDA, Georgetown Infectious Disease Atlas; Literature, articles containing Ebola and/or Zika funding donor contributions (“by donor”) and received funding (“by recipient”) from 2014-2019 identified in a search of MEDLINE, EMBASE, HMIC, Global Health, Scopus, Web of Science and EconLit.

for patients with Ebola and buying of necessary protective equipment’.36

Zika funding Markedly less Zika outbreak funding information was Figure 2 Proportions of funding reported by the obtained, with information extracted from only eight Georgetown Infectious Disease Atlas (GIDA) received by articles. Most transactions were from 2016, with one the top 5 recipients for different purposes (a) Commitments transaction documented in 2017 and there were no arti- (b) Disbursements. Overall percentage of funding for each cles that calculated the total funding contributed to the http://gh.bmj.com/ purpose is stated in the legend. 2015–2017 outbreak. Total disbursements to Zika ranged from $154 million to $1.9 billion (figure 3), depending on the data source. recipients were non-specific groups or types of recipient for example, ‘Other NGO’. Individual actor funding

Funding purposes Relatively few donors and recipients were recorded for on April 14, 2021 by guest. Protected copyright. Funding purposes recorded in the GIDA database varied Zika according to the literature with seven develop- by source and recipient (figure 2). The majority of ment actors pledging funds and four disbursing funds funding received by Guinea, Liberia and Sierra Leone (a complete list can be found in online supplemental was earmarked for socioeconomic recovery—61% of tables B4 and B5). Though there was a greater presence commitments and 54% of disbursements. Seventeen per of research institutions and pharmaceutical compa- cent of funding disbursed was for preparedness, though nies compared with Ebola. The USA was the donor that almost all of this was disbursed to unnamed recipients, contributed the most, however, according to the litera- and little funding was designated for response. A third of ture, a startling 95% of this was received by US agencies all disbursed funding was ‘Unclassifiable’, most apparent and jurisdictions. in the DRC where unclassified funds constituted the A large portion of the funding did not have a named majority received. donor or recipient—92% of Zika funding was received by The proportion of Ebola funding reported for each ‘Global’ and ‘Unallocated/Unspecified’ according to the purpose in the literature was different to the GIDA- DAH database (online supplemental figure C3). reported purposes, with 97%–98% of ‘literature by donor’ disbursements designated for response and the Funding purposes remainder for research and preparedness. Response Analysis of specific funding purposes for Zika using GIDA funding was for purposes such as building ‘isolated wards data was unfeasible, as 39 of the 40 items of financial

6 Quirk EJ, et al. BMJ Global Health 2021;6:e003923. doi:10.1136/bmjgh-2020-003923 BMJ Global Health

information were unclassifiable due to vague or lacking it did in commitments for socioeconomic recovery and BMJ Glob Health: first published as 10.1136/bmjgh-2020-003923 on 13 April 2021. Downloaded from descriptions. The majority of Zika donor disbursements preparedness. In the literature, a notable amount of recorded in the literature were for response (66%) but a literature funding was designated for more than one greater proportion of the funding was for Zika research purpose, for example, $1.7–$2.6 billion was pledged for (13%) and preparedness/response (21%). Ebola preparedness/response/socioeconomic recovery. No multi-purpose transactions were present in the GIDA data. There also appeared to be less received for certain Pledges, commitments and disbursements purposes than was being pledged or donated by a donor, Funding commitments are not documented in the for example, there was nearly 60 times less funding for literature as much as pledges and disbursements—only Zika research received ($4 million) than was donated $1.3 billion was recorded to have been committed by ($251 million). donors for Ebola and no Zika funding commitments were recorded at all (figures 1–3). Pledges were greater than disbursements for Ebola, according to the litera- DISCUSSION ture, and commitments were greater than disbursements Summary of findings according to the GIDA and the FTS (figure 1). This is the Reported total disbursements over 2014–2019 ranged same for GIDA-recorded Zika funding, but the opposite from $2.5 to $13.1 billion for Ebola and between $154 for Zika literature transactions, with over $1 billion more million and $1.9 billion for Zika, depending on the data disbursed than pledged (figure 3). Also, $1.5 billion source. Considering only the databases, variability was less more is recorded in the ‘literature by donor’ subset than but still sizeable—$2.5–$3.2 billion for Ebola and $150– the ‘literature by recipient’ subset for Zika. Although for $180 million for Zika. The USA was consistently the top Ebola, the amounts may be more similar, depending on donor across multiple data sources, with the UK and the whether one considers the minimum or maximum values European Union also among the most generous contrib- for the two subsets. utors. The GIDA reports ‘socioeconomic recovery’ as the predominant funding purpose but response is more Comparing literature and database totals prominent in the literature. Significant discrepancies In the literature, the types of donors reporting funding were identified in total amounts and types of information include government agencies, financial institutions, foun- reported between, and within, different funding data dations, NGOs and UN agencies, whereas the DAH data- sources, which makes it difficult to reach consensus on base mainly only includes bilateral government funding the nature of the overall funding flows. (online supplemental figures C2 and C3). Our findings align with current literature that well The amounts pledged, committed and disbursed differ establishes the USA as the top donor for outbreaks19 28 33 35 by data source. For both diseases, the literature-reported and health generally.16 However, our observation that totals were markedly higher than the database totals—the much of this funding is received by US agencies or juris- 28 databases documented between $2.5 and $3.2 billion in dictions, has only been previously noted once. The http://gh.bmj.com/ disbursements for Ebola, whereas the literature recorded apparent unfulfillment of pledges and commitments at least twice this (figure 1). Out of the databases, the FTS with disbursements, found for Ebola, is aligned with reported the most disbursements for Ebola ($3.2 billion), previous findings,19 33 34 although the opposite was the followed by the DAH and then the GIDA. Whereas, for case for Zika. This may be as donors are disbursing Zika GIDA reported higher disbursements than DAH without first pledging, or that Zika funding pledges are

(figure 3). not being recorded. High proportions of funding for on April 14, 2021 by guest. Protected copyright. This discrepancy is also seen on an individual actor response (79%) and research and development (3%) level, with amount donated by actors according to have been found previously,28 supporting our literature- the literature consistently greater than DAH-reported reported findings. However, according to the GIDA, a funding (online supplemental figures C2 and C3). The much higher proportion of funding was for socioeco- largest difference is seen for Ebola funding contrib- nomic recovery or was unclassifiable. This was markedly uted by the USA, with between $1.6 and $5.7 billion different to previous findings, where only 18% of donor more reported in the literature than the DAH database. funding was designated for recovery and 3.6% recipient- Similarly, for Zika the literature-reported total amount reported expenditure was unclassifiable.28 donated by the USA is 10 times higher than the DAH This study is the first, to our knowledge, to not only database total. The amount received varies less, but still collate funding information from multiple outbreaks noticeably. Guinea received the least according to both using a literature review, but to report that the litera- data sources and Liberia received the most according ture totals are greater than the databases’ and that totals to the literature, but Sierra Leone the most according also vary between databases. Discrepancies between data to the DAH. sources for a single donor may be as high as $5.7 billion, There were also discrepancies between the amount significantly more than cited in previous literature committed and disbursed for certain purposes (figure 2), which states differences of only $100 million17 and $391 for example, Liberia received less in disbursements than million.19 A possible explanation for these differences is

Quirk EJ, et al. BMJ Global Health 2021;6:e003923. doi:10.1136/bmjgh-2020-003923 7 BMJ Global Health

double counting of funding disbursements from govern- United Nations Development Programme, but ulti- BMJ Glob Health: first published as 10.1136/bmjgh-2020-003923 on 13 April 2021. Downloaded from ments who use multilaterals as an intermediary—but it is mately decided to exclude it from the analysis because hard to know the degree of impact of this on the results. the amounts were much smaller compared with the other This suggests the databases may represent an incom- three databases. plete picture of the funding streams, that the literature The novel approach taken by this study, combining sources tend to overreport, or a combination of the two. financial values from articles identified in a literature If one considers that additional databases and interactive review, also has limitations. Almost all articles identi- dashboards tracking global health funding also exist,37 38 fied by the literature search were editorials, journal blog the disjointed and conflicting nature of outbreak fund posts or grey literature, meaning the level of evidence is tracking becomes increasingly apparent. weak. There was difficulty balancing between combining Monitoring funding is necessary to identify remaining transactions into ranges, to prevent double counting and funding requirements,39 ensure mutual account- keeping transactions separate to provide an accurate ability and to recognise the contributions of donors.40 picture of funding purposes. Furthermore, the literature COVID-19 response funding is being monitored by totals are still likely to include duplicate funding, as inter- various institutions41–46 but these mechanisms may mediate holders of funding are counted as both donors fall victim to the same shortcomings as Ebola and Zika and recipients. Additionally, much of the ‘literature by fund tracking methods. Inconsistencies between fund recipient’ funding information comes from donors, with reporting mechanisms may dissuade or delay donors disbursements not confirmed by recipients. So even from making contributions to the COVID-19 response, though the literature appears to show more funding was as there is little information on how infectious disease donated than received, actually, donors are not reporting outbreaks are funded, let alone evidence-based guidance the destination of the funding. Due to the wording of the on how to allocate funds effectively. Furthermore, recent literature, it was also often difficult to concretely classify political decisions may significantly effect global health something as a pledge, commitment or disbursement, donations, particularly from the USA, who recently and determining a single purpose was difficult as funding announced a termination of the global power’s relation- descriptions were often vague, for example, ‘to address ship with the WHO47—this appears to have already taken the Ebola outbreak’.28 effect, with only 4.2% of contributions to the COVID-19 appeal being from the USA.42 Their promises to reallo- Recommendations cate tremendous amounts of funding to ‘other worldwide For organisations managing databases and deserving, urgent global public health needs’ exem- Several modifications to financial tracking databases plify that effective fund tracking has never been more should be considered to enable more definitive, reliable important. Though in and of itself, data transparency will overviews of funding flows. Standardising the format of not resolve this problem fully—more analysis of funding information across the databases would mean that infor- impact would also be necessary. mation from different reporting systems can be collated

more effectively and efficiently. This could be done by http://gh.bmj.com/ Limitations increasing collaboration and communication between The few similarities between the format of the examined the organisations who manage these databases, as has databases invite caution when interpreting the results. begun to happen between the International Aid Trans- The funding date was given as a range of years, single year, parency Initiative and the UN OCHA FTS.50 Data collec- month or exact date in different databases. Fields were tion methods would not necessarily have to be the same, also dissimilar, for example, GIDA has funding descrip- just highlighted explicitly so that any efforts to combine on April 14, 2021 by guest. Protected copyright. tions, DAH reports the intermediate agency that funding data from multiple sources are less susceptible to double was transferred via and the FTS is the only database to counting. Existing donor reporting standards (eg, OECD record pledges. Database methodology also varied, with reporting standards51) would also have to be considered differing inclusion criteria, ways of accounting for dupli- when designing the standardised format. cates and actors types that report, for example, funding Beneficial characteristics would be having pledges, transfers from the US government to the department of commitments and disbursements (financial and in-kind) defence and human services do not appear in the FTS.19 all recorded at least monthly but ideally in real time, These variances are also prevalent in the literature, for enabling valuable comparisons with case numbers. example, Ravi et al48 reported relevant information but Having a flexible reporting format, as the FTS does,23 not at the appropriate granularity. These differences in to account for the reality that funding cannot always be reporting style, also discussed elsewhere,17 mean there reported in a generic donor to recipient format, may are many factors to consider when combining informa- mean the funding picture is more complete. Detailed tion and deciding which source’s values are ‘correct’. descriptions of funding purpose and the health focus Nevertheless, they do provide reasons for the discrep- should be included, as without this information it is ancies between reported amount, and purpose, found more difficult for researchers and policymakers to deter- in this study. We also examined the Ebola Response mine how funds were used and whether funding fulfils its Multi-Partner Trust Fund database maintained by the purpose. Additional features, such as a field highlighting

8 Quirk EJ, et al. BMJ Global Health 2021;6:e003923. doi:10.1136/bmjgh-2020-003923 BMJ Global Health

duplicate transactions (as the DAH has) and separating would enable reliable overviews of funding flows to be BMJ Glob Health: first published as 10.1136/bmjgh-2020-003923 on 13 April 2021. Downloaded from funding into incoming funds, internal fund transfers and determined more easily. Increased communication and outgoing funds (as the FTS does) may prevent double collaboration between the databases and further research counting. to characterise the differences would help achieve this. These policy changes may facilitate more accurate and For donors definitive mapping of the complex funding landscape, Donors should continue to be urged to report their finan- ultimately leading to better spending that could save lives cial donations, as databases can only provide complete and protect livelihoods from the COVID-19 pandemic and accurate information if there is similarly accurate and the inevitable future damaging epidemics. and diligent reporting. Recording responsibility should Acknowledgements KH acknowledges joint Centre funding from the Abdul be placed to a greater extent on donors than on recip- Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), the National ients, as disease-affected countries are often managing Institute for Health Research Health Protection Research Unit (NIHR HPRU), Grant/ humanitarian crises alongside outbreaks,35 and their Award Number: HPRU‐2012‐10080, and from the UK Medical Research Council health systems are under immense pressure—in such and Department for International Development, MRC Centre for Global Infectious Disease Analysis, reference MR/R015600. circumstances, having a single database to report to, Contributors All authors contributed to the design, analysis and writing of the with clear, rehearsed reporting protocols could improve manuscript. KH and AG supervised the research and EJQ carried out most of the the quality of reported data. Also, developing countries implementation of the methodology and analysis. often lack the resources to manage the large amounts Disclaimer 19 "The views expressed are those of the authors and not necessarily of funding they receive from abroad. Donors may be those of the United Kingdom (UK) Department of Health and Social Care, the National averse to reporting due to the time lag between work Health Service, the National Institute for Health Research (NIHR), or Public Health completion and funding payments, preferring to report England (PHE)". only commitments—but both pieces of information Competing interests None declared. are required for a complete picture.17 Furthermore, Patient consent for publication Not required. researchers and database-managing organisations often Provenance and peer review Not commissioned; externally peer reviewed. categorise funding purpose subjectively or using string Data availability statement Data are available in a public, open access 52 search terms, so if donors classify the intended use of repository. All data relevant to the study are included in the article or uploaded funds themselves, the purpose will likely be more accu- as supplementary information. Data used in this study have been sourced from rate. publicly available databases. The newly generated datasets underpinning the analysis are included in the supplementary material. Additional information will be provided by the corresponding author upon reasonable request. For future research Supplemental material This content has been supplied by the author(s). It has Our findings warrant a future comprehensive compar- not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been ison of all financial reporting databases for outbreaks. peer-reviewed. Any opinions or recommendations discussed are solely those Comparisons of funding estimates, trends and methods of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and have been already been made for reproductive, maternal responsibility arising from any reliance placed on the content. Where the content 53 includes any translated material, BMJ does not warrant the accuracy and reliability and child health. Qualitative accounts from organisa- of the translations (including but not limited to local regulations, clinical guidelines, http://gh.bmj.com/ tions managing databases would be valuable, as they may terminology, drug names and drug dosages), and is not responsible for any error provide a more detailed insight into the methodology and/or omissions arising from translation and adaptation or otherwise. and format of databases as well as the perceived feasibility Open access This is an open access article distributed in accordance with the of changes and collaboration. Despite attempts to contact Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any these organisations, this was not possible in this study. purpose, provided the original work is properly cited, a link to the licence is given, Determining the views of donors and recipients would and indication of whether changes were made. See: https://creativecommons.org/ on April 14, 2021 by guest. Protected copyright. further highlight the strengths and weaknesses of fund licenses/by/ 4.0/. reporting mechanisms and may help determine reasons ORCID iDs for missing data. Available studies have looked at general Emily Jade Quirk http://orcid. org/0000- 0002-1969- 8117 health system funding54 and its determinants,55 and it Adrian Gheorghe http://orcid. org/0000- 0002-0517- 8807 would be constructive to explore this in an outbreak context. Funding from other sectors related to outbreak response, such as food safety, animal health and the military, could also be investigated.56 57 REFERENCES 1 Schellekens P, Sourrouille D. The unreal dichotomy in COVID-19 Conclusion mortality between high-income and developing countries. Brookings future development. Weblog. Available: https://www.brookings. This study identified considerable differences in reported edu/blog/future-development/2020/05/05/the-unreal-dichotomy-in- values and purposes of international funding for Ebola covid-19-mortality-between-high-income-and-developing-countries/ and Zika outbreaks. It also highlighted the challenges in [Accessed 28 June 2020]. 2 Wisniewska A, Tilford C, Harlow M. Coronavirus tracked: the latest constructing a comprehensive, high-resolution picture figures as countries start to reopen. Available: https://www.ft.com/ of global funding flows for outbreak preparedness, content/a26fbf7e-48f8-11ea-aeb3-955839e06441 [Accessed 28 June 2020]. response and recovery. Standardisation of reporting data- 3 World Health Organization Regional Office for Africa. Weekly Bulletin base formats and in-depth comparison of methodology on outbreaks and other emergencies. Report number: 25, 2020.

Quirk EJ, et al. BMJ Global Health 2021;6:e003923. doi:10.1136/bmjgh-2020-003923 9 BMJ Global Health

4 Simba J, Sinha I, Mburugu P, et al. Is the effect of COVID-19 on 29 The Campbell and Cochrane Economics Methods Group,. CCEMG), children underestimated in low- and middle- income countries? Acta evidence for policy and practice information and coordinating centre BMJ Glob Health: first published as 10.1136/bmjgh-2020-003923 on 13 April 2021. Downloaded from Paediatr 2020;109:1930-1931. (EPPI-Centre). implied conversion factors and implied Inflaction 5 Cash R, Patel V. Has COVID-19 subverted global health? Lancet factors. CCEMG - EPPI-Centre Cost Converter 2019 https://eppi.ioe. 2020;395:1687–8. ac.uk/costconversion/default.aspx 6 Roberton T, Carter ED, Chou VB, et al. Early estimates of the indirect 30 Tambo E, Ugwu CE, Guan Y, et al. China-Africa health development effects of the COVID-19 pandemic on maternal and child mortality in initiatives: benefits and implications for shaping innovative and low-income and middle-income countries: a modelling study. Lancet evidence-informed National health policies and programs in sub- Glob Health 2020;8:e901–8. Saharan African countries. Int J MCH AIDS 2016;5:119–33. 7 Mamun MA, Ullah I. COVID-19 suicides in Pakistan, dying off not 31 Huang Y. China's response to the 2014 Ebola outbreak in West COVID-19 fear but poverty? - The forthcoming economic challenges Africa. Glob Chall 2017;1:1600001. for a developing country. Brain Behav Immun 2020;87:163–6. 32 Fan H-J, Gao H-W , Ding H, et al. The Ebola threat: China's 8 BBC. Yemen: Coronavirus aid loss 'harming millions of children', response to the West African epidemic and national development 2020. Available: https://www.bbc.co.uk/news/world-middle-east- of prevention and control policies and infrastructure. Disaster Med 53191438 [Accessed 28 June 2020]. Public Health Prep 2015;9:64–5. 9 Burn-Mur doch J, Romei V, Giles C. Global coronavirus death 33 Grépin KA. International donations to the Ebola virus outbreak: too toll could be 60% higher than reported. Financial Times, 2020. little, too late? BMJ 2015;350:h376. Available: https://www.ft.com/content/6bd88b7d-3386-4543-b2e9- 34 Glassman A, Ebola A. Finance & Development, 2016. Available: 0d5c6fac846c?shar eType=nongift [Accessed 28 June 2020]. https://www.imf.org/external/pubs/ft/fandd/2016/06/glassman.htm 10 Walker PG, Whittaker C, Watson O. The global impact of COVID-19 [Accessed 27 Apr 2020]. and strategies for mitigation and suppression. Report number: 12, 35 Moss K, Michaud J, Kates J. Data note: donor funding for the 2020. current Ebola response in the DRC. KFF: global health policy. 11 Bong C-L, Brasher C, Chikumba E, et al. The COVID-19 pandemic: Weblog. Available: https://www.kff.org/global-health-policy/issue- effects on low- and middle-income countries. Anesth Analg brief/data-note-donor-funding-for-the-current-ebola-response-in- 2020;131:86–92. the-drc/ [Accessed 27 Apr 2020]. 12 World Health Assembly. International health regulations (2005). 3rd 36 Waheed Y. Ebola in West Africa: an international medical emergency. edn. Geneva: World Health Organization, 2016. Asian Pac J Trop Biomed 2014;4:673–4. 13 Sandler T. Understanding global public goods. OECD observer, 37 Georgetown Global Health Security Tracking. Funding MAP. 2001. Available: https://oecdobserver.org/news/fullstory.php/aid/ Available: https://tracking.ghscosting.org/explore/map [Accessed 7 540/Understanding_global_public_goods.html [Accessed 27 Apr May 2020]. 2020]. 38 Institute for Health Metrics and Evaluation. Flows of global health 14 Schäferhoff M, Chodavadia P, Martinez S, et al. International funding financing. Available: http://vizhub.healthdata.org/fgh [Accessed 7 for global common goods for health: an analysis using the Creditor May 2020]. reporting system and G-FINDER databases. Health Syst Reform 39 Georgetown Global Health Security Tracking. Background. Available: 2019;5:350–65. https://tracking.ghscosting.org/about/background [Accessed 27 15 Chang AY, Cowling K, Micah AE, et al. Past, present, and future April 2020]. of global health financing: a review of development assistance, 40 Katz R, Graeden E, Kerr J, et al. Tracking the flow of funds in global government, out-of- pocket, and other private spending on health for health security. Ecohealth 2019;16:298–305 https://link.springer. 195 countries, 1995-2050. Lancet 2019;393:2233–60. com/article/ 16 Dieleman JL, Schneider MT, Haakenstad A, et al. Development 41 The Economist Intelligence Unit. The COVID-19 health funding assistance for health: past trends, associations, and the future of Tracker. Available: https://covidfunding.eiu. com/ [Accessed 12 July international financial flows for health. Lancet 2016;387:2536–44. 2020]. 17 Grabowski A, Hohlfelder E. When losing track means losing lives: 42 World Health Organization. COVID-19 contributions tracker. accountability lessons from the Ebola crisis. Lancet Glob Health Available: https://www.who.int/emergencies/diseases/novel- https://marlin-prod.literatumonline.com/pb-assets/Lancet/langlo/ coronavirus-2019/donors-and-partners/funding [Accessed 12 July TLGH_Blogs_2013-2018.pdf 2020]. 18 Bali SR, Carletto AL, Clark JP. Lessons Learned in Financing 43 International Monetary Fund. COVID-19 financial assistance and Rapid Response to Recent Epidemics in West and Central debt service relief. Available: https://www.imf.org/en/Topics/imf-and- Africa : A Qualitative Study. Washington, D.C: World Bank covid19/COVID-Lending-Tracker [Accessed 12 July 2020]. http://gh.bmj.com/ Group, 2019. http://documents.worldbank.org/curated/en/ 44 Devex. Funding the response to COVID-19: analysis of funding 241811559646029471/Lessons-Learned-in-Financing-Rapid- opportunities, 2020. Available: https://public.tableau.com/views/ Response-to-Recent-Epidemics-in-West-and-Central-Africa-A- COVIDFundingvisualisation/COVID-19funding?%3Aembed=y&% Qualitative-Study 3Atoolbar=no&%3Adisplay_count=no&%3AshowVizHome=no 19 Glassman A, Raghavan S. How much is actually being spent on [Accessed 12 July 2020]. Ebola? center for global development. Weblog. Available: https:// 45 Moss K. Donor funding for the global novel coronavirus response. www.cgdev.org/blog/how-much-actually-being-spent-ebola KFF. Weblog, 2020. Available: https://www.kff.org/coronavirus-covid-

[Accessed 27 Apr 2020]. 19/issue-brief/donor-funding-for-the-global-novel-coronavirus- on April 14, 2021 by guest. Protected copyright. 20 García PJ. Corruption in global health: the open secret. Lancet response/ [Accessed 12 July 2020]. 2019;394:2119–24. 46 UN OCHA Financial Tracking Service. COVID-19 global humanitarian 21 Organisation for Economic Co-operation and Development (OECD). response plan (humanitarian response plan). Available: https://fts. DAC glossary of key terms and concepts. Available: https://www. unocha.org/appeals/952/summary [Accessed 12 July 2020]. oecd.org/dac/dac-glossary.htm [Accessed 27 Apr 2020]. 47 Hoffman J, Vazquez M. Trump announces end of US relationship 22 United Nations Office for the Coordination of Humanitarian Affairs with World Health organization. CNN. Available: https://www.cnn. (UN OCHA). Glossary. Available: https://fts.unocha.org/glossary com/2020/05/29/politics/donald-trump-world-health-organization/ [Accessed 27 Apr 2020]. index.html [Accessed 12 July 2020]. 23 UNOCHAFTS. FTS: Flow model introduction. [Video], 2016. 48 Ravi SJ, Snyder MR, Rivers C. Review of international efforts to Available: https://www.youtube.com/watch?v=Dlh9mQnFlLM&t= strengthen the global outbreak response system since the 2014-16 3s%29 [Accessed 19 May 2020]. West Africa Ebola epidemic. Health Policy Plan 2019;34:47–54. 24 Office for the Coordination of Humanitarian Affairs (OCHA). Financial 49 United Nations Development Programme Multi-Partner Trust Fund tracking service. about FTS/ who reports to FTS? Available: https:// Office. Trust Fund Factsheet - Ebola Response MPTF. Available: fts.unocha.org/content/faqs-all-funding [Accessed 27 Apr 2020]. http://mptf.undp.org/factsheet/fund/EBO00 [Accessed 27 Apr 2020]. 25 Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for 50 Flower S. Centre for Humdata. lessons from connecting IATI and systematic reviews and meta-analyses: the PRISMA statement. FTS. Weblog. Available: https://centre.humdata.org/lessons-from- PLoS Med 2009;6:e1000097. connecting-iati-and- fts/ [Accessed 27 Apr 2020]. 26 Zika response must not drain research funds. Nature 2016;537:7. 51 OECD. Development finance standards. Available: http://www.oecd. 27 Fischer LS, Santibanez S, Jones G, et al. How is CDC funded to org/dac/financing-sustainable-development/development-finance- respond to public health emergencies? federal Appropriations and standards/ [Accessed 21 Jan 2021]. budget execution process for Non-Financial experts. Health Secur 52 Georgetown Infectious Disease Atlas. Georgetown infectious 2017;15:307–11. disease atlas (GIDA) technical appendix, 2020. Available: https:// 28 Office of the United Nations Special Envoy on Ebola. Resources for tracking.ghscosting.org/export/GIDA%20Technical%20Appendix. results V. United Nations. Report number 5, 2016. pdf [Accessed 27 Apr 2020].

10 Quirk EJ, et al. BMJ Global Health 2021;6:e003923. doi:10.1136/bmjgh-2020-003923 BMJ Global Health

53 Pitt C, Grollman C, Martinez-Alvarez M, et al. Tracking aid for global 58 Institute for Health Metrics and Evaluation (IHME. Development BMJ Glob Health: first published as 10.1136/bmjgh-2020-003923 on 13 April 2021. Downloaded from health goals: a systematic comparison of four approaches applied assistance for health database 1990-2018, 2019. Available: http:// to reproductive, maternal, newborn, and child health. Lancet Glob ghdx.healthdata.org/record/ihme-data/development-assistance- Health 2018;6:e859–74. health-database- 1990- 2018 [Accessed 4 Feb 2020]. 54 Warren AE, Wyss K, Shakarishvili G, et al. Global health Initiative 59 Institute for Health Metrics and Evaluation. Financing Global Health investments and health systems strengthening: a content analysis of global fund investments. Global Health 2013;9:30. 2018 - Countries and Programs in Transition: Supplementary 55 Fan VY, Tsai F-JJ, Shroff ZC, et al. Dedicated health systems Methods Annex. IHME, 201923 April. strengthening of the global fund to fight AIDS, tuberculosis, and 60 Georgetown University Center for Global Health Science & Security. malaria: an analysis of grants. Int Health 2017;9:50–7. Georgetown infectious disease atlas (GIDA) global health security 56 Boland S. Centre on global health security roundtable summary: the tracking site, 2020. Available: https://tracking.ghscosting.org/data next Ebola: considering the role of the military in future epidemic [Accessed 4 Feb 2020]. response. London: Chatham House, 2017. 61 Georgetown Global Health Security Tracking. Data sources. 57 World Health Organization (WHO), Food and Agriculture Organization Available: https://tracking.ghscosting.org/about/data [Accessed 27 of the United Nations (FAO), World Organisation for Animal Health (OIE). Taking a Multisectoral, one health approach: a tripartite guide Apr 2020]. to addressing zoonotic disease in countries, 2019. Available: https:// 62 United Nations Office for the Coordination of Humanitarian Affairs. www.oie.int/fileadmin/Home/eng/Media_Center/docs/EN_Triparti Financial tracking service, 2020. Available: https://fts. unocha. org/ teZoonosesGuide_webversion.pdf [Accessed 20 May 2020]. data-sear ch [Accessed 25 Feb 2020]. http://gh.bmj.com/ on April 14, 2021 by guest. Protected copyright.

Quirk EJ, et al. BMJ Global Health 2021;6:e003923. doi:10.1136/bmjgh-2020-003923 11 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) BMJ Global Health

A SYSTEMATIC EXAMINATION OF INTERNATIONAL FUNDING FLOWS FOR EBOLA VIRUS AND ZIKA VIRUS OUTBREAKS 2014 – 2019: DONORS, RECIPIENTS AND FUNDING PURPOSES

Supplementary Material

Quirk EJ, et al. BMJ Global Health 2021; 6:e003923. doi: 10.1136/bmjgh-2020-003923 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) BMJ Global Health

Supplement 1 – Methods

Table A1. Pre-set groupings downloaded and analysed from the United Nations Office for the Coordination of Humanitarian Affairs (UN OCHA) Financial Tracking Service (FTS).

Grouping type Groupings used

Emergency - DR Congo - Ebola Outbreak 2018 – 2019 - Ebola - WEST AFRICA - July 2015 - Ebola Virus Outbreak - WEST AFRICA - April 2014 Organisation - Ebola Response Multi-Partner Trust Fund - Global Ebola Response Coalition - UN Mission for Ebola Emergency Response Plan - Ebola Virus Outbreak - Overview of Needs and Requirements (Inter-agency plan for Guinea, Liberia, Sierra Leone, Region) - October 2014 - June 2015 Project - EBOLA-14/H/71120/122 - EBOLA-14/CSS/72256/561 - EBOLA-14/F/71114/561 - EBOLA-14/H/71122/99

Table A2. Funding purpose classification criteria.*

Purpose Description

Response Immediate or short-term activities often in the form of medical equipment, vaccines, medication, diagnostics and personnel. Humanitarian assistance and distribution of essentials such as food, water and shelter were also included. Staff training was included if it was short-term to deal with the current crisis.

Preparedness Health system strengthening, improved surveillance, contributions to emergency funding pots like the WHO Contingency Fund for Emergencies, long-term staff training.

Socioeconomic To help rebuild damaged economies and long-term support to recovery businesses and individuals.

Research Immediate, short-term and long-term financial support to research institutions, laboratories and pharmaceutical companies to develop new treatments, vaccines or to increase the knowledge about the disease.

Unclassifiable Non-English description, lacked a description or had an ambiguous description that meant a clear purpose could not be determined. *This classification was only applicable for the Georgetown Infectious Disease Atlas funding database.

Table A3. Literature search terms applied to each database. m.p. = key word in abstract, title, original title, broad terms, heading words, identifiers, cabicodes / = subject heading

Database(s) Search terms

MEDLINE 1. ebola.mp. OR (ebola adj1 virus).mp. OR Ebola Global Health haemorrhagic fever/ OR ebolavirus/ OR Zika fever/ OR zika.mp. OR (zika adj1 virus).mp. OR Zika Virus Infection/ 2. financ*.mp. OR fund*.mp.OR funding/ OR finance/ OR

spend*.mp. OR expenditure.mp. OR grant*.mp. OR loan*.mp. 3. Foundations/ OR "Organisation for Economic Co-Operation and Development"/ OR Red Cross/ OR United Nations/ OR unesco/ OR World Health Organization/ OR Pan American Health Organization/ OR global fund.mp. OR World Bank.mp. OR NGO*.mp. OR non-governmental organi?ation*.mp. OR non-government organi?ation*.mp. OR national government*.mp. OR government*.mp. OR IMF.mp. OR International monetary fund.mp. OR Global Health Security Agenda.mp. OR World Health Organi?ation.mp. OR International Working Group on Financing Preparedness.mp. OR United Nations.mp. OR charit*.mp. 4. 1 AND 2 AND 3 EMBASE 1. ebola.mp. OR (ebola adj1 virus).mp. OR Ebola haemorrhagic fever/ OR ebolavirus/ OR Zika fever/ OR zika.mp. OR (zika adj1 virus).mp. OR Zika Virus Infection/ 2. financ*.mp. OR fund*.mp.OR funding/ OR finance/ OR spend*.mp. OR expenditure.mp. OR grant*.mp. OR loan*.mp. OR health care financing/ 3. Foundations/ OR "Organisation for Economic Co-Operation and Development"/ OR Red Cross/ OR United Nations/ OR unesco/ OR World Health Organization/ OR Pan American Health Organization/ OR global fund.mp. OR World Bank.mp. OR NGO*.mp. OR non-governmental organi?ation*.mp. OR non-government organi?ation*.mp. OR national government*.mp. OR government*.mp. OR IMF.mp. OR International monetary fund.mp. OR Global Health Security Agenda.mp. OR World Health Organi?ation.mp. OR International Working Group on Financing Preparedness.mp. OR United Nations.mp. OR charit*.mp. 4. 1 AND 2 AND 3 Health Management 1. ebola.mp. OR (ebola adj1 virus).mp. OR Ebola Information Consortium haemorrhagic fever/ OR ebolavirus/ OR Zika fever/ OR (HMIC) zika.mp. OR (zika adj1 virus).mp. OR Zika Virus Infection/ 2. financ*.mp. OR fund*.mp.OR funding/ OR finance/ OR spend*.mp. OR expenditure.mp. OR grant*.mp. OR loan*.mp. 5. 1 AND 2

Scopus 1. ebola* OR ebola AND virus OR ebola AND infection* OR ebola AND haemorrhagic AND fever* OR ebola AND hemorrhagic AND fever* OR zika* OR zika AND virus OR zika AND infection* 2. fund* OR financ* OR expenditure OR spend* OR grant* OR loan* 3. united AND nations OR un OR world AND health AND organisation OR world AND health AND organization OR non-government AND organisation OR non-governmental AND organisation OR non-government AND organization OR non-governmental AND organization OR charit* OR world AND bank OR imf OR international AND monetary AND fund OR global AND health AND security AND agenda OR foundation* OR ghsa OR global AND fund 4. 1 AND 2 AND 3 Web of Science 1. ebola OR (ebola AND virus*) OR (ebola AND infection*) OR (ebola AND haemorrhagic AND fever*) OR (ebola AND hemorrhagic AND fever) OR zika OR (zika AND virus*) OR (zika AND infection*) 2. financ* OR fund* OR expenditure OR spend* OR grant* OR loan* 3. (United AND Nations) OR (World AND Health AND Organisation) OR (World AND Health AND Organization) OR (non-government AND organisation) OR (non- governmental AND organisation) OR (non-government AND organization) OR (non-governmental AND organization) OR (Global AND Fund) OR (International AND Monetary AND Fund) OR IMF OR (World AND Bank) OR NGO* OR (Global AND Health AND Security AND Agenda) OR GHSA OR charit* OR foundation* OR government* OR (national AND government) 4. 1 AND 2 AND 3 EconLit 1. TX (( ebola OR ebola virus* OR ebola infection* OR ebola haemorrhagic fever* OR ebola hemorrhagic fever OR zika OR zika infection* OR zika virus*) 2. TX ( financ* OR fund* OR expenditure OR loan* OR grant* OR spend*) 3. TX ((United AND Nations) OR (World AND Health AND Organisation) OR (World AND Health AND Organization) OR (non-government AND organisation) OR (non- governmental AND organisation) OR (non-government AND organization) OR (non-governmental AND organization) OR (Global AND Fund) OR (International AND Monetary AND Fund) OR IMF OR (World AND Bank) OR NGO* OR (Global AND Health AND Security AND Agenda) OR GHSA OR charit* OR foundation* OR government* OR (national AND government)) 4. 1 AND 2 AND 3

Table A4. Inclusion and exclusion criteria for the literature review.

Inclusion Exclusion

Related to Ebola and Publishing date, study focus period or data range are pre-2014 /or Zika from 2014 - 2019 Non-English

Not Open Access or accessible through Imperial College Contains financial London Library amounts donated or received by any actor - Predictive modelling - Estimations of economic losses due to the outbreaks - Calls for funding or recommendations for future action or Funding for measures policy to respond to, prepare - Estimations of funding need (e.g. vaccine) for or assist in the - Funding requests to congress recovery for the - Total funding raised by a charity campaign* Ebola/Zika funding combined with funding for another outbreaks - disease - In-kind contributions with no corresponding monetary value

*excluded as donations collected from the public are not necessarily equal to funding given to the implementing actor

Supplement 2 - Literature data sources

Literature by donor dataset

Table B1. Ebola donor pledged* amounts and data sources.

Donor Amount pledged 2019 USD Data source African Development Bank $248,727,200 - $411,267,200 (1,2) African Union $1,083,600 - $2,048,490 (2,3) AU Staff Association $107,210 (2) Australia $32,173,721 - $47,344,121 (1,2) Austria $3,269,905 (2) Belgium $60,198,415 (2) Benin $428,840 (2) Bill and Melinda Gates (1,2) Foundation $62,567,756 - $116,747,756 Bolivia $1,072,100 (2) Brazil $13,068,899 (2) Burkina Faso $128,652 (2) Canada $103,725,675 - $250,011,675 (1,2,4) Central Emergency (1) Response Fund $16,254,000 Chad $21,442 (2) Children's Investment Fund (1,2) Foundation $21,672,000 - $43,114,000 Chile $321,630 (2) China $134,334,130 - $332,632,930 (1,2,5) Colombia $107,210 (2) Cote d'Ivoire $1,072,100 (2) Cyprus $10,721 (2) Czech Republic $225,141 (2) Denmark $32,313,094 (2) Estonia $53,605 (2) Ethiopia $321,630 (2) European Union $1,007,055,693 - $1,348,124,893 (1-4) Finland $12,168,335 - $23,004,335 (1,2) France $203,270,160 - $351,723,360 (2,4) Gambia $536,050 (2) Georgia $32,163 (2) Germany $419,362,636 - $734,690,236 (1,2,4) Google/Larry Page Family (2) Foundation $26,802,500 Guyana $53,605 (2) India $14,086,800 - $24,807,800 (1,2) International Monetary Fund $461,003,000 - $921,930,953 (2,6)

Ireland $40,450,333 (2) Islamic Development Bank $637,899,500 (2) Israel $9,380,875 (2) Italy $35,979,676 (2) Japan $198,188,406 - $245,866,806 (1,2) Kazakhstan $375,235 (2) Kenya $1,072,100 (2) Latvia $53,605 (2) Luxembourg $3,034,043 (2) Malaysia $107,210 (2) Mali $214,420 (2) Malta $64,326 (2) Mark Zuckerberg and Pricilla (1) Chan $27,090,000 Mauritania $321,630 (2) Mauritius $21,442 (2) Mexico $1,072,100 (2) Montenegro $10,721 (2) Namibia $1,072,100 (2) Netherlands $8,544,739 - $182,817,939 (1,2,4) New Zealand $2,648,087 (2) Niger $182,257 (2) Nigeria $4,824,450 (2) Norway $61,645,750 (2) Paul G. Allen Family (1,2,4) Foundation $108,360,000 - $307,366,055 Phillippines $2,176,363 (2) Portugal $32,163 (2) Republic of Korea $18,868,960 (2) Romania $42,884 (2) Royal Charity Organisation of (2) Bahrain $1,072,100 Russia $21,442,000 (2) Saudi Arabia $37,523,500 (2) Senegal $1,072,100 (2) Sierra Leone $18,690,000 (7) Silicon Valley Community (2) Foundation $26,802,500 Spain $14,677,049 (2) Sweden $84,520,800 - $174,417,310 (1,2,4) Switzerland $35,454,347 (2) Togo $2,144 (2) Turkey $1,929,780 (2) United Kingdom $1,072,368,025 - $1,632,589,225 (1,2,4) UN Foundation $139,373 (2)

US Biomedical Advanced (8) Research and Development Authority (BARDA) $45,836,280 $2,534,551,610 - (1,2,4,8,9) United States $11,528,431,610 Venezuela $5,360,500 (2) Volvo Group $1,404,451 (2) Wellcome Trust $5,634,720 (10) West African Economic and (2) Monetary Union $4,824,450 World Bank $2,034,657,800 - $2,934,045,800 (1,2,4,11,12) *Pledge = announcement of funding intent

Table B2. Ebola donor commitments* and data sources.

Donor Amount committed 2019 USD Data source European Union $1,321,400,000 (13) *Commitment = agreed funding obligation, usually in writing

Table B3. Ebola donor disbursements* and data sources.

Donor Amount disbursed 2019 USD Data source African Development Bank $120,539,150 (2,14) African Union $964,890 (2) AU Staff Association $107,210 (2) Australia $32,573,721 (2,14) Austria $3,269,905 (2) Belgium $55,459,733 (2) Benin $428,840 (2) Bill and Melinda Gates (2,14) Foundation $62,231,645 Bolivia $1,072,100 (2) Brazil $13,068,899 (2) Burkina Faso $128,652 (2) Canada $194,116,621 - $278,637,421 (2,4,14,15) CDC's Epidemiology and (16) Laboratory for Infectious Diseases (ELC) $107,210,000 Chad $0 (2) Children's Investment Fund (2) Foundation $21,442,000 Chile $321,630 (2) China $144,068,280 - $194,997,480 (2,5,14) Colombia $107,210 (2) Cote d'Ivoire $0 (2) Cyprus $10,721 (2)

Czech Republic $225,141 (2) Denmark $37,113,094 (2,14) Estonia $53,605 (2) Ethiopia $321,630 (2) European Union $819,916,390 - $901,186,390 (2,4,14) Finland $12,168,335 (2) France $118,028,800 - $221,593,660 (2,4,14) Gambia $536,050 (2) Georgia $32,163 (2) Germany $182,276,000 - $326,248,309 (2,4,14) Global Alliance for Vaccines (14) and Immunisation (GAVI) $26,500,000 Google/Larry Page Family (2) Foundation $0 Guyana $53,605 (2) India $10,721,000 (2) International Monetary Fund $460,927,953 - $870,528,753 (2,17) Ireland $43,850,333 (2,14) Islamic Development Bank $13,755,043 (2) Israel $9,380,875 (2) Italy $14,151,156 (2,14) Japan $203,288,406 (2,14) Kazakhstan $375,235 (2) Kenya $0 (2) Latvia $53,605 (2) Luxembourg $3,634,043 (2,14) Malaysia $107,210 (2) Mali $214,420 (2) Malta $64,326 (2) Mauritania $321,630 (2) Mauritius $21,442 (2) Mexico $1,072,100 (2) Montenegro $10,721 (2) Namibia $0 (2) Netherlands $85,768,000 - $150,784,000 (2,4) New Zealand $2,648,087 (2) NGOs $8,000,000 (18) Niger $182,257 (2) Nigeria $12,678,120 - $17,502,570 (2,3)(2,3) Norway $65,145,750 (2,14) Paul G. Allen Family (2,4,14) Foundation $76,551,075 - $136,149,075 Philippines $2,176,363 (2) Portugal $32,163 (2) Republic of Korea $18,868,960 (2) Romania $42,884 (2)

Royal Charity Organisation of $1,072,100 (2) Bahrain Russia $21,442,000 (2) Saudi Arabia $0 (2) Senegal $0 (2) Silicon Valley Community $0 (2) Foundation South Korea $1,000,000 (14) Spain $13,401,250 (2) Susan T.Buffet Foundation $5,000,000 (14) Sweden $87,637,200 - $97,178,890 (2,4,14) Switzerland $36,854,347 (2,14) Togo $2,144 (2) Turkey $321,630 (2) UK $632,407,675 - $959,654,875 (2,4,14) UN Central Emergency (14) Response Fund (CERF) $12,600,000 UN Foundation $139,373 (2) UN OCHA/DRC Humanitarian (14) Fund $10,000,000 UNICEF $300,000 (14) US Biomedical Advanced (19) Research and Development Authority (BARDA) $26,981,640 United States $2,786,951,610 - $6,951,197,170 (2,4,8,9,14,18,20) Venezuela $5,360,500 (2) Volvo Group $1,404,451 (2) Wellcome Trust $4,200,000 (14) West African Economic and (2) Monetary Union $4,824,450 WHO Contingency Fund for (14,21) Emergencies (CFE) $75,135,600 World Bank $573,101,776 - $699,882,976 (2,4) World Bank International (14) Development Association (IDA) $120,000,000 World Bank Pandemic (14) Emerency Financing Facility (PEF) $50,000,000 World Food Programme $500,000 (14) *Disbursement = an actual transfer of money

Table B4. Zika donor pledged* amounts and data sources.

Donor Amount pledged 2019 USD Data source Brazil $259,426,500 (22) European Union $29,992,000 - $45,687,400 (23,24) Governments $29,257,200 (25) United Kingdom $7,953,750 (23) US Department of Health and (26) Human Services $85,900,500 (16) United States $371,175,000 World Health Organization $59,388,000 (27) *Pledge = announcement of funding intent

Table B5. Zika donor disbursements and data sources.

Donor Amount disbursed 2019 USD Data source Brazil $59,081,670 (22) United Kingdom $6,938,685 (28) US Centers for Disease (29) Control and Prevention (CDC) $41,359,500 United States $1,781,640,000 (23,26,29) *Disbursement = an actual transfer of money

Literature by recipient dataset

Table B6. Ebola pledges* received and data sources.

Recipient Amount received in pledges Data source 2019 USD ACDI/VOCA $19,297,800 (2) African Union $22,996,545 (2) American Refugee Committee $8,180,123 (2) Benin $557,492 (2) Burkina Faso $21,442 (2) Burundi $21,442 (2) Cameroon $428,840 (2) Catholic Relief Services $15,084,447 (2) Concern $7,301,001 (2) Cote D'Ivoire $63,789,950 (2) Ebola MPTF $144,797,826 (2) FAO $8,265,891 (2) Gabon $96,489 (2) Ghana $6,797,114 (2) Global Communities $36,494,284 (2) GOAL $17,368,020 (2)

Guinea $895,407,199 (2) IFRC $120,965,043 (2) International Medical Corps $71,241,045 (2) International Rescue Committee $45,703,623 (2) IOM $76,001,169 (2) Jhpiego $9,327,270 (2) Liberia $716,259,289 (2) Mali $3,398,557 (2) Mapp Pharmaceuticals $45,836,280 (8) Medicine San Frontieres $20,938,113 (2) Mercy Corps $35,347,137 (2) Netherlands Ministry of Defence $7,772,725 (2) Niger $21,442 (2) Nigeria $32,163 (2) Not specified $2,422,206,251 (2) Other government institutions $38,381,180 (2) Other NGO $466,020,428 (2) Other other $72,205,935 (2) Partners in Health $37,705,757 (2) Project Concern International $20,788,019 (2) Research Institutions (Various) $235,937,047 (2) Samaritan's Purse $10,431,533 (2) Save the Children $33,803,313 (2) Senegal $4,910,218 (2) Sierra Leone $816,822,269 (2) Swedish Civil Contingencies Agency $1,543,824 (2) UN OCHA $7,526,142 (2) UN Women $1,093,542 (2) UNDP $28,056,857 (2) UNFPA $20,337,737 (2) UNHCR $7,354,606 (2) UNICEF $335,245,670 (2) UNOPS $58,118,541 (2) Unspecified government $224,294,041 (2) US Assistant Secretary for Preparedness and Response (ASPR) $954,169,000 (30) US Biomedical Advanced Research and Development Authority (BARDA) $62,181,800 (30) US Centers for Disease Control and Prevention (CDC) $1,929,780,000 - $4,733,478,136 (2,16,30)

US Centres for Disease Control Foundation $19,287,079 (2) US Department of Defence $797,385,096 (2,30) US Food and Drug Administration (FDA) $26,802,500 (30) US National Institute of Health (NIH) $255,159,800 (30) US State Department and USAID $2,787,460,000 (30) WFP $323,956,457 (2) WHO $381,710,484 (2) World Bank $53,658,605 (2) World Food Programme (WFP) $6,501,600 (5) World Vision $7,086,581 (2) *Pledge = announcement of funding intent

Table B7. Ebola disbursements* received and data sources.

Recipient Amount received 2019 USD Data source ACDI/VOCA $19,297,800 (2) African Union $20,530,715 (2) American Refugee Committee $8,180,123 (2) Benin $557,492 (2) Burkina Faso $21,442 (2) Burundi $21,442 (2) Cameroon $428,840 (2) Catholic Relief Services $15,084,447 (2) Concern $7,301,001 (2) Cote D'Ivoire $63,789,950 (2) Ebola MPTF $138,440,273 - $144,941,873 (2,5) FAO $6,657,741 (2) Gabon $96,489 (2) Ghana $19,791,151 (2,4) Global Communities $36,494,284 (2) GOAL $17,368,020 (2) Guinea $364,278,138 - $616,811,118 (2,4,5) IFRC $123,859,713 (2) International Medical Corps $69,954,525 (2) International Rescue Committee $45,703,623 (2) IOM $76,001,169 (2) Ivory Coast $23,839,200 (4) Jhpiego $9,327,270 (2)

Liberia $955,735,200 - $1,506,151,340 (2,4) Mali $15,178,784 (2,4) Mapp Pharmaceuticals $26,981,640 (19) Medicine San Frontieres $19,222,753 (2) Mercy Corps $35,347,137 (2) Netherlands Ministry of Defence $7,772,725 (2) Niger $21,442 (2) Nigeria $17,012,520 - $17,044,683 (2-4) Not specified $678,864,441 (2) Other government institutions $19,490,778 (2) Other NGO $442,455,670 (2) Other other $61,313,399 (2) Partners in Health $37,705,757 (2) Project Concern International $20,788,019 (2) Research Institutions (Various) $291,000,103 (2) Samaritan's Purse $10,431,533 (2) Save the Children $33,267,263 (2) Senegal $7,517,758 (2,4) Sierra Leone $501,706,800 - $951,388,424 (2,4) Swedish Civil Contingencies Agency $1,543,824 (2) UN OCHA $6,443,321 (2) UN Women $1,093,542 (2) UNDP $28,056,857 (2) UNFPA $20,337,737 (2) UNHCR $7,354,606 (2) UNICEF $335,245,670 (2) United Nations $1,500,940,000 (31) UNOPS $44,867,385 (2) Unspecified government $7,912,098 (2) US Centers for Disease Control and Prevention (CDC) $1,917,972,000 - $2,771,535,136 (2,9) US Centres for Disease Control Foundation $18,214,979 (2) US Department of Defence $677,309,896 (2) US jurisdictions $107,210,000 (16) World Food Programme $322,359,028 (2) WHO $436,891,471 - $444,476,671 (2,4,15) World Bank $53,658,605 (2) World Vision $7,086,581 (2) *Disbursement = an actual transfer of money

Table B8. Zika pledges* received and data sources.

Recipient Amount received in pledges Data source 2019 USD Brazil Armed Forces $37,443,000 (22) Brazil Ministry of Health (22) (MoH) $160,470,000 Brazil $61,513,500 (22) *Pledge = announcement of funding intent

Table B9. Zika disbursements* received and data sources.

Recipient Amount received 2019 USD Data source Excivion Ltd $759,700 (28) Jenner Institute, Oxford (28) University $757,983 Prokarium Ltd $599,262 (28) Puerto Rico Science, (29) Technology, and Research Trust $14,847,000 Stabilitech Limited $325,562 (28) Themis Ltd $1,518,154 (28) US Centers for Disease (29) Control and Prevention (CDC) $371,175,000 US jurisdictions $26,512,500 (29) *Disbursement = an actual transfer of money Table B10. Ebola disbursements by donor for each actor type.

Type Amount disbursed 2019 USD

Government $4,855,622,177 – $9,809,484,246 Multilateral $2,289,311,835 – $£2,906,963,835 National agency $134,191,640

Private $170,829,171 – $230,427,171 NGO $9,072,100 *Disbursement = an actual transfer of money

Literature data source references

(1) Glassman A, Raghavan S. How Much Is Actually Being Spent on Ebola? Center For Global Development. Weblog. Available from: https://www.cgdev.org/blog/how-much- actually-being-spent-ebola [Accessed 27th April 2020].

(2) Office of the United Nations Special Envoy on Ebola. Resources for Results V. United Nations. Report number: 5, 2016.

(3) Waheed Y. Ebola in West Africa: an international medical emergency. Asian Pacific Journal of Tropical Biomedicine. 2014;4(9):673-674. Available from: doi:10.12980/APJTB.4.201414B389

(4) Grépin KA. International donations to the Ebola virus outbreak: too little, too late? BMJ. 2015;350:h376. Available from: doi:10.1136/bmj.h376

(5) Huang Y. China's Response to the 2014 Ebola Outbreak in West Africa. Global Challenges. 2017;1(2):1600001. Available from: doi:10.1002/gch2.201600001

(6) Kentikelenis A, King L, McKee M, Stuckler D. The International Monetary Fund and the Ebola outbreak. The Lancet Global Health. 2015;3(2):e69-e70. Available from: doi:10.1016/S2214-109X(14)70377-8

(7) O'Carroll L. A third of Sierra Leone's Ebola budget unaccounted for, says report. The Guardian. February 16, 2015. Available from: http://www.theguardian.com/world/2015/feb/16/ebola-sierra-leone-budget-report [Accessed 5th May 2020].

(8) Nature Biotechnology. Outpaced by an outbreak. Nature Biotechnology. 2014;32(11):1067-1067. Available from: doi:10.1038/nbt.3074

(9) Standley CJ, MacDonald PDM, Attal-Juncqua A, Barry AM, Bile EC, Collins DL, et al. Leveraging Partnerships to Maximize Global Health Security Improvements in Guinea, 2015-2019. Health Security. 2020;18(S1):S34-S42. Available from: doi:10.1089/hs.2019.0089

(10) Gulland A. Clinical trials of Ebola treatment to start in Africa. BMJ. 2014;349(g5838) Available from: doi:10.1136/bmj.g5838

(11) Green A. WHO and partners launch Ebola response plan. The Lancet. 2014;384(9942): 481. Available from: doi:10.1016/S0140-6736(14)61322-2

(12) Jonas O. Pandemic bonds: designed to fail in Ebola. Nature. 2019;572(7769):285- 285. Available from: doi:10.1038/d41586-019-02415-9

(13) Galpin C. Chronology: The European Union in 2014. JCMS: Journal of Common Market Studies. 2015;53(S1):230-236. Available from: doi:10.1111/jcms.12258

(14) Moss K, Michaud J, Kates J. Data Note: Donor Funding for the Current Ebola Response in the DRC. KFF: Global Health Policy. Weblog. Available from: https://www.kff.org/global-health-policy/issue-brief/data-note-donor-funding-for-the- current-ebola-response-in-the-drc/ [Accessed 27th April 2020].

(15) Plummer FA, Jones SM. The story of Canada’s Ebola vaccine. CMAJ. 2017;189(43):E1326-E1327. Available from: doi:10.1503/cmaj.170704

(16) Fischer LS, Santibanez S, Jones G, Anderson B, Merlin T. How Is CDC Funded to Respond to Public Health Emergencies? Federal Appropriations and Budget Execution Process for Non–Financial Experts. Health Security. 2017;15(3):307-311. Available from: doi:10.1089/hs.2017.0009

(17) Cangul M, Sdralevich C, Sian I. Beating Back Ebola. Finance & Development. June 2017. Available from: https://www.imf.org/external/pubs/ft/fandd/2017/06/cangul.htm [Accessed 5th May 2020].

(18) Nature. To contain Ebola, the United States must fulfil its promise to the World Health Organization. Nature. 2019; 571 (7764): 145-145. Available from: doi:10.1038/d41586-019-02118-1

(19) McCarthy M. US signs contract with ZMapp maker to accelerate development of the Ebola drug . BMJ. 2014; 349 (g5488): Available from: doi:10.1136/bmj.g5488

(20) Glassman A. After Ebola. Finance & Development. June 2016. Available from: https://www.imf.org/external/pubs/ft/fandd/2016/06/glassman.htm [Accessed 27th April 2020].

(21) Yaqub F. 2018: a year in review. The Lancet. 2018;392(10165):2669-2670. Available from: doi: 10.1016/S0140-6736(18)33244-6

(22) Gómez EJ, Perez FA, Ventura D. What explains the lacklustre response to Zika in Brazil? Exploring institutional, economic and health system context. BMJ Global Health. 2018;3(5):e000862. Available from: https://gh.bmj.com/content/3/5/e000862 [Accessed 27th April 2020]

(23) Shuchman M. Canada’s support lags for research on Zika. CMAJ : Canadian Medical Association Journal. 2016;188(10):E203-E204. Available from: doi:10.1503/cmaj.109-5284

(24) Goodridge K, Reveiz L, Elias V. An overview of financial sources being utilized to support Zika Virus published research. PLoS ONE. 2017;12(8):e0183134. Available from: doi:10.1371/journal.pone.0183134

(25) Gostin LO, Hodge JG. Is the United States Prepared for a Major Zika Virus Outbreak? JAMA. 2016;315(22):2395-2396. Available from: doi:10.1001/jama.2016.4919

(26) Morabito KM, Graham BS. Zika Virus Vaccine Development. The Journal of Infectious Diseases. 2017;216(suppl_10):S957-S963. Available from: doi:10.1093/infdis/jix464

(27) McCarthy M. WHO sets out $56m Zika virus response plan. BMJ. 2016;352(i1042) Available from: doi:10.1136/bmj.i1042

(28) UK Department of Health and Social Care. UK Zika research awarded share of £120 million vaccine fund. Available from: https://www.gov.uk/government/news/uk-zika- research-awarded-share-of-120-million-vaccine-fund [Accessed 5th May 2020].

(29) Murthy BP, Vagi S, Desamu-Thorpe R, Avchen R. Morbidity and Mortality Weekly Report: Assessment of State, Local, and Territorial Zika Planning and Preparedness Activities — United States, June 2016–July 2017. US Centers for Disease Control and Prevention. Report number: 67, 2018.

(30) Boddie C, Sell TK, Watson M. Federal Funding for Health Security in FY2016. Health Security. 2015;13(3):186-206. Available from: doi:10.1089/hs.2015.0017

(31) Standley CJ, Sorrell EM, Kornblet SA, Fischer JE, Katz R. Linking funds to actions for global health emergencies. Science. 2015; 348 (6236): 762-763. Available from: doi:10.1126/science.aaa5521

Supplement 3 – Results

DonatedDonated Received United States 1,208 846 Sierra Leone United Kingdom 445 727 Liberia Other 170 717 Unallocated/Unspecified** Germany 143 276 Guinea Japan 127 168 Global Debt repayments 95 50 Cote d'Ivoire Sweden 83 18 Ghana Private other 74 8 Mali Netherlands 70 5 Burkina Faso BMGF 53 5 Guinea-Bissau Donors outside top 10 380 29 Recipients outside top 10

0 200 400 600 800 1,000 1,200 1,400 1,000 800 600 400 200 0

Donor United States 2,787 - 6,951 1,918 - 2,772 United States CDC

European Union 820 - 901 1,501 United Nations Recipient United Kingdom 632 - 960 956 - 1,506 Liberia World Bank 573 - 700 679 Not specified IMF 461 - 870 677 United States DoD Japan 203 502 - 951 Sierra Leone Canada 194 - 279 442 Other NGO Germany 182 - 326 437 - 444 WHO China 144 - 195 364 - 617 Guinea African Development Bank 121 335 UNICEF Donors outside top 10 1,341 - 1,584 1,932 - 1,938 Recipients outside top 10

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 4,000 3,000 2,000 1,000 0

Figure C1. Totals disbursed by the top 10 donors and received by the top 10 recipients according to the DAH database and the literature for Ebola. DAH = Development Assistance for Health; BMGF = Bill and Melinda Gates Foundation; NGO = Non-governmental organisation; IMF = International Monetary Fund; CDC = Centers for Disease Control and Prevention; DoD = Department of Defence; WHO = World Health Organization; UNICEF = United Nations Children’s Fund. Other = interest, transfer of funds, refunds and miscellaneous income. *DAH data only available 2014-2018

**The OECD CRS defines unspecified funding as” non-country programmable aid such as administrative costs, refugees in donor country and research costs” and unallocated funding as funding that “cannot be classified in any of the other non-country programmable aid categories[1]. It is not clear whether these definitions are applicable to all DAH data. [1] OECD. Country programmable aid (CPA): Frequently asked questions. Available from: https://www.oecd.org/development/effectiveness/countryprogrammableaidcpafrequentlyaskedquestions.htm [Accessed 28th February 2021]

Disbursed Received United States 116.8 80.3 Global

BMGF 17.3 53.0 Unallocated/Unspecified

Australia 3.7 5.5 Brazil

United Kingdom 3.5 2.5 Indonesia

Private other 1.6 1.1 Colombia

Canada 0.8 0.8 Haiti

Japan 0.3 0.7 Tonga

Sweden 0.2 0.4 Nicaragua

Germany 0.2 0.2 Fiji

France 0.1 0.1 Tokelau

Donors outside top 10 0.5 0.2 Recipients outside top 10

0 20 40 60 80 100 120 100 80 60 40 20 0

Donor Recipient United States 1,781.6 371.2 U U Brazil 59.1 26.5 P United States CDC 41.4 14.8 …

UnnitedUnn Kingdom 6.9 1.5 T

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 0.8 E J 0.8

0.6 P

0.3 S

400 200 0

Figure C2. Total disbursed by the top 10 donors and received by the top 10 recipients according to the DAH database and the literature for Zika. DAH=Development Assistance for Health; BMGF = Bill and Melinda Gates Foundation; CDC = Centers for Disease Control and Prevention *DAH data only available 2014-2018

Table C1. Total amount disbursed, funded and committed, and pledged to Ebola, as calculated by existing published articles. UN = United Nations; OCHA = Office for the Coordination of Humanitarian Affairs; MPTF = Multi-Partner Trust Fund; DRC = Democratic Republic of the Congo; WHO = World Health Organization; USAID = United States Agency for International Development; CERF = Central Emergency Response Fund *Only the top 20 donors **OCHA amounts include commitments and disbursements

2014 – 2015 Ebola outbreak First author Year published Data source(s) Dates Amount 2019 USD Disbursements Grépin[24] 2015 UN OCHA FTS Up until 31/12/2014 $1,083,600,000 Office of the United Nations 2016 Information requests; Ebola MPTF Sept 2014 - Jan 2015 $6,325,390,000 Special Envoy on Ebola[23] Funded and committed combined Glassman*[20] 2014 UN OCHA FTS Jan 2014 - Oct 2014 $1,517,040,000 Pledges Glassman[22] 2016 UN OCHA 2014 - 2015 $3,881,002,000 Grépin[24] 2015 UN OCHA FTS Up until 31/12/2014 $3,131,604,000 Glassman*[20] 2014 Press releases Jan 2014 - Oct 2014 $2,600,640,000 Office of the United Nations 2016 Information requests; Ebola MPTF Sept 2014 - Jan 2015 $9,541,690,000 Special Envoy on Ebola[23]

2018 – 2019 Democratic Republic of Congo Ebola outbreak First author Year published Data source Dates Amount 2019 USD Disbursements Moss[25] 2019 DRC/Partners SRP 3; WHO; OCHA**; Aug 2018 - Dec 2019 $734,000,000 European Union; UK; USAID; Gavi; DRC/Partners SRP 2; U.N. CERF; World Bank

Quirk EJ, et al. BMJ Global Health 2021; 6:e003923. doi: 10.1136/bmjgh-2020-003923