Table 2 Norms for sharing data in epidemics and pandemics
Norm | Definition | References |
|---|---|---|
Capacity development | Necessary skills and infrastructure should be developed. Requires immediate transfer of skills or to provide support systems to ensure that any locally produced health-related data can be rapidly generated and shared. Should guarantee equal infrastructure and resources to analyse the data. “Only this parity in means and capacities of data analysis could confer justice in the use of the collected data.” (da Costa and Leite [42]) | |
Priority to LMIC investigators, especially those closest to an epidemic | ||
Capturing diversity | Data collected and shared should not be limited to epidemiological factors but also capture socio-economic differences that are known to drive disparities in infection rates | [15] |
Data stewardship | Calls for gradual shift away from the culture of data ownership towards one of data stewardship for health-related datasets from human populations. Although countries are recognized to be the “key arbiters” of sharing data collected from their populations, “in times of emergency, the onus should be placed upon the stewards of population- and individual-level data to justify if and why they are unwilling to share data for the good of public health.” (Modjarrad et al. [25]) | [25] |
Equitable access to data | Data must be made available to all interested parties without cost or just at a level of recovering costs without profit | |
Equitable access may mean giving priority access to research data to LMIC researchers or researchers from the source country/region | ||
Fair benefits to data generators (researchers), data providers, study participants and communities, and source countries | Individuals and communities that participate in research should have access to research outputs (such as vaccines) which result from the use of their data. Those to whom the data and samples relate also should not bear an undue burden for the benefit of others. These ethical imperatives are more pronounced when samples and data collected from potentially vulnerable populations are shared | |
Benefit-sharing arrangements should ensure source countries can access any resulting vaccines or treatments | ||
Researchers (in LMICs) should have the same opportunities (as those in HICs) to derive benefits from the data and samples that they have acquired themselves | ||
Equitable global access to the benefits of research | The benefits of science are a global common good. Globally, there should be equitable access to research outputs such as vaccines. Outputs should not be hoarded by any one country or organisation. Concept of a “people’s vaccine” has been raised | |
Particular consideration should be given to the specific needs of LMICs | ||
International collaboration | Global collaboration and cooperation; data sharing across national borders | |
Secondary users of data should make best efforts to collaborate with representatives of the originating laboratory or research team responsible for obtaining the specimen(s) and involve them in analyses and further research using such data | ||
National sovereignty | Recognizes the sovereign right of States over pathogen data and biological resources and their authority to determine the terms and conditions for accessing such resources | |
Pre-publication and rapid review | Journals should support pre-publication data sharing and dissemination, and undertake rapid peer review | |
Open access | Journals should make articles with datasets and findings that might have value in combating the epidemic/pandemic available to all, free of charge, as soon as is feasibly possible | |
Rapid, real-time data sharing | Researchers should release research protocols, materials, datasets and results related to epidemic/pandemics and make them publicly available without waiting for publication in scientific journals | [41, 18, 23, 42, 25, 29,30,31, 40,41,42, 58, 54,55,56,57,58,59,60,61,62,63,64,65,66] |
“Researchers should be responsible for ensuring that shared results—even when preliminary—have undergone some quality control and are, therefore, sufficiently accurate.” (Modjarrad et al. [25]) | ||
Information critical for public health should be shared with the World Health Organization, public health officials, the study participants and affected population, and groups involved in wider international response efforts before publication. Journals should state that they will only publish data-driven research arising from a public health emergency if it is accompanied by an explicit statement from authors that they have shared data and results with authorities and legitimate bodies responding to the emergency at the earliest possible opportunity | ||
Recognition | Secondary users of data must acknowledge the contribution of the data generator and/or the origin of the data. Primary researchers and data contributors should be credited in publications: “Interviewees highlighted that agreed terms of use, collaboration and accreditation are especially needed for data generated during an active outbreak because those who are collecting the data and responding to the outbreak may have less time to be analysing data. If data is shared rapidly, the analysis may be completed by others before those who are treating patients have a chance to sit down at a computer, thus fostering inequity in opportunity to use shared data.” (Pisani et al. [41], p. 37) | |
Secondary users of data must also check whether data generators should be listed as authors—for example, some journals require authorship for anyone who designed, collected or analysed the paper’s intellectual content. LMIC researchers should get the authorship credit they deserve | ||
Academic institutions should implement policies that recognize data sharing as an aspect used to help determine professional advancements | ||
Journals should explore innovative ways of crediting significant intellectual input into research short of direct involvement in writing, and should consider publication policies that promote the inclusion of primary researchers in later re-analysis of their data |