Difference between revisions of "Call to action"
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We have investigated how mHealth can contribute in containing the pandemic. We've identified several domains where mobile technology can be useful: in health promotion, through epidemiological surveillance or in supporting the healthcare system or government policy. In our analysis we have taken into account societal, legal and ethical perspectives. In our assessment model we suggest how these perspectives can be transformed into concrete requirements and how we can assess aspiring solutions. |
We have investigated how mHealth can contribute in containing the pandemic. We've identified several domains where mobile technology can be useful: in health promotion, through epidemiological surveillance or in supporting the healthcare system or government policy. In our analysis we have taken into account societal, legal and ethical perspectives. In our assessment model we suggest how these perspectives can be transformed into concrete requirements and how we can assess aspiring solutions. |
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| − | A lot of attention went to contact tracing, the most visible part of the COVID-19 mHealth iceberg. |
+ | A lot of attention went to contact tracing, the most visible part of the COVID-19 mHealth iceberg. There are other alternatives however that were overlooked in the debate between privacy and effectiveness. This crucial trade-off cannot be resolved within this narrow scope of contact tracing. We observe that there is insufficient evidence on current working solutions striking this balance right. To the contrary, current solutions in place are either obviously not privacy-preserving (see practices in China, South-Korea) or have not convincingly contributed to a successful lifting of coarse-grained measures while containing the spread of the virus (see Singapore). |
We acknowledge that this lack of evidence makes it impossible to safely suggest mass roll-out of any known proposed solution. Either because the privacy and ethical safeguards are not proven, or because of the unproven effectiveness of privacy-preserving solutions and the resulting false sense of security. Nevertheless a number of solutions are promising and merit further exploration. We would like to invite the reader to contribute both to the assessment model and to the solution landscape we have laid out. While we attempted to paint the broad strokes, neither are complete, which is why we have opted for the wiki format. |
We acknowledge that this lack of evidence makes it impossible to safely suggest mass roll-out of any known proposed solution. Either because the privacy and ethical safeguards are not proven, or because of the unproven effectiveness of privacy-preserving solutions and the resulting false sense of security. Nevertheless a number of solutions are promising and merit further exploration. We would like to invite the reader to contribute both to the assessment model and to the solution landscape we have laid out. While we attempted to paint the broad strokes, neither are complete, which is why we have opted for the wiki format. |
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All sections are open for comment and contribution, but we also created a 'challenges' section identifying specific topics to contribute to. |
All sections are open for comment and contribution, but we also created a 'challenges' section identifying specific topics to contribute to. |
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| + | We would like to ask aspiring contributors to send a short e-mail with their name and background to info@appiaplus.eu. After validation we will provide an account to this wiki. |
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Latest revision as of 14:53, 20 May 2020
We have investigated how mHealth can contribute in containing the pandemic. We've identified several domains where mobile technology can be useful: in health promotion, through epidemiological surveillance or in supporting the healthcare system or government policy. In our analysis we have taken into account societal, legal and ethical perspectives. In our assessment model we suggest how these perspectives can be transformed into concrete requirements and how we can assess aspiring solutions.
A lot of attention went to contact tracing, the most visible part of the COVID-19 mHealth iceberg. There are other alternatives however that were overlooked in the debate between privacy and effectiveness. This crucial trade-off cannot be resolved within this narrow scope of contact tracing. We observe that there is insufficient evidence on current working solutions striking this balance right. To the contrary, current solutions in place are either obviously not privacy-preserving (see practices in China, South-Korea) or have not convincingly contributed to a successful lifting of coarse-grained measures while containing the spread of the virus (see Singapore).
We acknowledge that this lack of evidence makes it impossible to safely suggest mass roll-out of any known proposed solution. Either because the privacy and ethical safeguards are not proven, or because of the unproven effectiveness of privacy-preserving solutions and the resulting false sense of security. Nevertheless a number of solutions are promising and merit further exploration. We would like to invite the reader to contribute both to the assessment model and to the solution landscape we have laid out. While we attempted to paint the broad strokes, neither are complete, which is why we have opted for the wiki format.
All sections are open for comment and contribution, but we also created a 'challenges' section identifying specific topics to contribute to. We would like to ask aspiring contributors to send a short e-mail with their name and background to info@appiaplus.eu. After validation we will provide an account to this wiki.
