| Literature DB >> 31272443 |
Carly Jackson1, Jennifer L Gardy2,3, Hedieh C Shadiloo1, Diego S Silva4,5.
Abstract
BACKGROUND: Emerging genomic technologies promise more efficient infectious disease control. Whole genome sequencing (WGS) is increasingly being used in tuberculosis (TB) diagnosis, surveillance, and epidemiology. However, while the use of WGS by public health agencies may raise ethical, legal, and socio-political concerns, these challenges are poorly understood.Entities:
Keywords: Empirical ethics; Qualitative; Surveillance; Trust; Tuberculosis; Whole genome sequencing
Mesh:
Year: 2019 PMID: 31272443 PMCID: PMC6610958 DOI: 10.1186/s12910-019-0380-z
Source DB: PubMed Journal: BMC Med Ethics ISSN: 1472-6939 Impact factor: 2.652
Fig. 1Map of relationships between key concerns in relation to trust. → concept flows from previous concept. ↔ concepts have endogenous relationship, influencing each other.⇢concept has indirect relationship with connecting concept
Summary table of terms used in Fig. 1 with illustrative participant quotes
| Item | Definition/ Operationalized Description | Illustrative Quote | |||
|---|---|---|---|---|---|
| 1 | Trust | Trust is an perception or attitude one holds regarding another actor’s trustworthiness in their behaviour; here ‘trustworthiness’ being the honesty and integrity of the actor’s actual behaviour. This trust may be built on relationships in which both parties have proven their trustworthiness or, in other cases, may be blind trust in those with the power over the data. Regardless, trust suggest that one party is vulnerable and dependent upon others to act in the right manner according to the particular situation, including taking the trustee’s interest into account (McLeod, 2015). In the context of WGS for TB surveillance, issues around trust (or lack thereof) may be present in many relationships including, but not limited to: 1) between health care workers and laboratory staff, 2) the public and the medical community and 3) for concerns of data protection for both privacy and confidentiality purposes, as well as academic. |
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| Issues of trust in relation to new technologies previously discussed in the literature | 2 | Data sharing and profitting from surveillance | Fear of the potential that profits may be derived from data acquired through surveillance activities. In conjunction with data sharing concerns previously detailed in the literature, this encompasses the fear that if data is shared with international surveillance databases, the data can then be used to developed new diagnostics and/or drugs that will then be sold back to countries at high, potentially unaffordable, prices. Fear of the potential that profits may be derived from data acquired through surveillance activities. In conjunction with data sharing concerns previously detailed in the literature, this encompasses the fear that if data is shared with international surveillance databases, the data can then be used to developed new diagnostics and/or drugs that will then be sold back to countries at high, potentially unaffordable, prices. |
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| 3 | Access and Who Benefits | Which regions (e.g. LMICs vs. HICs) are actually able to implement WGS technology - including the sequencing itself and the data analysis - and how we avoid situations where these lower-resourced settings are being ‘used’ by other researchers who derive benefit in the form of papers/scientific stature, while the sequences and the resulting data may not ever feed back into meaningful change in TB policy and practice in the study setting. Which regions (e.g. LMICs vs. HICs) are actually able to implement WGS technology - including the sequencing itself and the data analysis - and how we avoid situations where these lower-resourced settings are being ‘used’ by other researchers who derive benefit in the form of papers/scientific stature, while the sequences and the resulting data may not ever feed back into meaningful change in TB policy and practice in the study setting. |
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| 4 | Power of Public Health | Actors within the framework of public health can have immense powers which, while working in the public interest, could result in the undermining of various rights and civil liberties. |
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| Emerging concerns in relation to whole genome sequencing, flowing from and mapping back to issues of trust | Bioinformatic challenges | 5 | Utility | In the context of WGS for TB surveillance, utility is the usefulness or benefit WGS contributes to TB programs both nationally and globally for surveillance, diagnostic and TB care purposes. The utility of WGS within individual TB programs appears to depend on a number of factors including (but not limited to): access to the technology, bioinformatic and human analytic capabilities and engagement with public health workers. The utility of WGS appears to be strongest when it is supported with strong epidemiological data. |
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| 6 | Analytics | Analytics encompasses many bioinformatic challenges that arise from the use of WGS in TB surveillance and care, including: 1) analytic capabilities of both the technology and the professionals working with it; and 2) standardized processes for standard outputs. |
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| 7 | Capacity | Capacity is the ability of countries to actually implement WGS technology into their local TB programs. The high cost of the machine, the sequencing and/or the analytic software may pose challenges to countries, either alone or in conjunction. |
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| 8 | Understanding Science | WGS is a rapidly advancing technology that is often progressing at a rate faster than those working with the technology (either indirectly or directly) are able to adapt. As a result, epidemiologists and other public health workers (i.e.. clinicians and nurses) are often left reliant on the lab staff and others with the niched knowledge of the technology to analyze and interpret the output data. This has the potential to have negative impacts on the overall utility of WGS in public health practice. |
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| Data protection and stewardship regarding metadata | 9 | Metadata | Metadata is the individual patient-level data, including administrative data and health records. Question arise regarding whether or not this data should be linked to sequenced genomic isolates being collected for surveillance purposes and who should have access to this data. |
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| a. Linked Metadata | When metadata databases are linked to the sequenced genomic data produced through WGS, it becomes much more powerful tool for tracking outbreak transmission patterns, at risk case identification and potential diagnostic developments. However, it also raises many questions and concerns regarding privacy and confidentiality of patient level data, as well as data protection responsibilities. | ||||
| b. Unlinked Metadata | Not linking at least some metadata to the genomic isolates essentially renders the sequenced genomic data produced through WGS useless from a public health perspective as traditional epidemiological activities, such as contact tracing, would still be required to make the data actionable for public health actors. |
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| Consequences and/or implications to data protection responsibilities | 10 | Stigma | Communities affected by TB tend to already be among marginalized communities. Concerns of further marginalization and stigma arise from the use of WGS for TB surveillance, especially when metadata is linked to the sequenced genomic data. Some of these concerns include: 1) being discriminated against if their identity is discovered through genomic data; 2) public misinterpretation from the media in the reporting of disease outbreaks; and 3) issues of discrimination regarding immigration and care seeking behaviours. |
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| 11 | Community Engagement | In Canada, the USA and England, TB tends to be disproportionately concentrated within migrant communities, particularly those newly immigrated, and other communities experiencing poverty (i.e.. homeless populations). In Canada, TB is also highly prevalent within Indigenous and First Nations communities. Engagement and transparent communication with these affected communities when reporting out disease outbreaks can help to mitigate some stigma and help ensure that any reports are culturally appropriate and sensitive to the needs of the community. |
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| Challenges assocaited with implementing TB surveillance systems using WGS | 12 | Implementation/Roll-out | Successful implementation/roll-out of WGS into TB programs for surveillance and care requires that countries have the capacity to implement it, proper analytic systems in place, individuals that understand the science of the technology and the interpretation and finally, buy-in from health care workers that can appropriately communicate it to patients. Additionally, successful implementation of WGS technology depends on: 1) buy-in from state-level and federal administrations; 2) transparency and clear communication strategies for the public and other jurisdictions; and 3) appropriate training systems in place for new professionals working with the technology. | ||
| 13 | Jurisdictional Issues | Given greater global connections, TB cases are seldom restricted to one geographic region. Consequently, issues of jurisdiction may occur at the local, state, federal or international level. Issues of jurisdiction may include (but are not limited to): 1) differences in analytic capacity between jurisdiction; 2) ‘ownership’ over the case and responsibility for investigation; 3) communication across jurisdictions and; 4) potential impacts on affected communities including stigma and/or immigration concerns. Consideration of these issues will impact how successfully WGS technologies are implemented into TB surveillance programs. |
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| 14 | Communication with non-community stakeholders | Non-community stakeholders includes health care workers (i.e.. clinicians and nurses), laboratory professionals and government officials at state and federal levels. Gaining buy-in and understanding of WGS technology from these stakeholders is vital for successful implementation of this technology. Appropriate messaging of outbreak transmission patterns and WGS technology from TB stakeholders to affected communities should also occur as a result of this. |
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Participant Demographics
| Regional Representation | Canada | United States | United Kingdom | International Organizations | Totals |
|---|---|---|---|---|---|
| Governance and Policya | 5 | 2 | 0 | 1 | 8 |
| Public Health | 4 | 3 | 1 | 0 | 8 |
| Laboratory | 1 | 1 | 1 | 3 | 6 |
| Totals: | 10 | 6 | 2 | 4 | – |
a Includes government officials and individuals in governance roles within public health institutions