Table 1

Overview of Chinese aid for health estimates

CharacteristicDetailChina’s distinctive engagement in global health11China’s engagement with development assistance for health in Africa12China’s role as a global health donor in Africa: what can we learn from studying under reported resource flows?13China’s silk road and global health14Tracking development assistance for health from China, 2007–201715
Definition and scope of health aid*
FlowOfficial development assistance (ODA)- likeNYYYN
Other official finance (OOF)-likeNYYYN
Vague (cannot be determined as ODA or OOF)NYYYN
Official investmentNNNYN
OtherRefers to ‘health aid’ although no definition providedNNNDsbursement of in-kind or financial resources (grants, interest-free/concessional loans) to low-income or middle-income countries
Flow typeDisbursementsUnclearY†Y†UnclearY
CommitmentsUnclearNYUnclearN
PledgesUnclearYNUnclearN
SectorHealthUnclearYYYUnclear
Population and reproductive healthUnclearYYYUnclear
Water, sanitation and hygieneUnclearYYNUnclear
OtherUnclearKey word search conducted to identify health projects in other sectors (eg, government and civil society)All social sector projects were manually inspected for health-related projectsNIncluded flows that were for the ‘primary purposes of improving or maintaining health’
ChannelBilateralYYYYY
MultilateralUnclearNNYY
Time and geographic scope
Time period2007–20112000–20132000–20122008–20132007–2017
GeographyAfricaAfricaAfricaGlobalGlobal
Results: level of disaggregation
Project countYYYYN
Recipient countryYYYNY
Health typeFocus area (eg, diseases)NYYNY
Activity (eg, surveillance)YYYYY
Source of information‡
AidDataNY (uses one of AidData’s Chinese Official Finance datasets)N
Government data: budget/financial accounts, yearbook statistics, information systems, websites, and/or reportsYYY
Recipient country information systemNYN
Academic literatureNYN
Media reportsYYN
InterviewsYNNNN
Data use
Source verification processNotes that inconsistencies were double checked but process used unclearAidData database adopts a ‘health of record score’ to signal which projects have the most complete and reliable data, in part based on a verification and triangulation processNo process identified
Ranking system of sourcesNo process identifiedAidData database adopts a ranking system based on resource types, with official government sources at the top and media reports and social media at the lowest levelN/A only Chinese government data used
Attempt to fill missing financial valuesNo process identifiedNo process identifiedNot attempted; focused on project counts instead of exact financial estimationSubstitutes median value of the same type of project for missing valuesUses a variety of estimation and regression models to fill in gaps
  • *This category attempts to align with key dimensions of the OECD Creditor Reporting System Aid Activity Database (CRS). Additionally, selected categories were also based on common categorizations used by datasets, like AidData’s Chinese Official Finance dataset. Three of the five studies in the table used an AidData dataset. AidData also attempts to align with OECD CRS standards, although to do so, some additional terminology unique to AidData, such as ‘vague’ finance or ‘pledges’, is included.

  • †Projects that are ‘in implementation’ or ‘completed’ are included in this analysis. Inclusion of these two project types could be considered a proxy for disbursements. This study uses one of AidData’s Chinese Official Finance datasets, which tracks a project’s status but does not explicitly track disbursements. In this dataset, a project is considered to be ‘in implementation’ if any portion of the intended amount has been disbursed. A project that is ‘completed’ assumes all committed finances have been disbursed.

  • ‡Three of the five studies used a common data source (AidData’s Chinese Official Finance). To report consistently across categories, when a source was not specifically mentioned in an estimate, we defaulted to using AidData’s description of their source data. Some studies opted to include additional data to supplement their studies (eg, multilateral contributions data).