Research priorities for COVID-19 sensor technology
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To the Editor — The COVID-19 pandemic has spurred efforts to develop sensor technology to manage the disease1,2,3. Most of these projects have been driven by medical researchers, scientists and engineers without explicit involvement and input from patients and the broader community. Here, we define sensor technology broadly to include physical, cellular and molecular platforms that produce signals to identify specific events associated with SARS-CoV-2 and/or its interaction with the host. The main applications of sensor technology in COVID-19 have been to detect fever using infrared sensing devices and the presence of viral RNA using polymerase chain reaction (PCR) tests1. However, a substantial proportion of individuals with COVID-19 never develop fever1. PCR tests have been developed to detect SARS-CoV-2 in nasopharyngeal samples, but to date they have been expensive, resource-intensive, cumbersome and relatively slow. Moreover, positive PCR tests do not imply a person is still infectious and thus have not provided information about transmissibility or virulence1,4,5, hampering the development of more effective action plans in the societal, economic and public health dimensions6.

Given the urgent need to better control the pandemic and its impact on the community, resources should be allocated in a strategic and targeted manner that takes into account community perspectives, through an explicit consensus-based process with equitable involvement of patients, the public, researchers and clinicians. Co-production in research specifically involving consumers or end-users is now widely advocated to improve the relevance, use and impact of the findings7,8. It requires partnership and collaboration between researchers and the broader community from the outset, beginning with priority-setting8. There have been few research priority-setting partnerships in COVID-19, with very few involving patients and the public, and none with a focus on sensor technology. Below, we describe the development and outcome of a process through which we identified the shared priorities of patients, the community, health professionals, scientists, engineers and policy makers for research in sensor technology to address COVID-19, the reasons for their priorities, and ideas for implementation.

This priority-setting project involved 83 patients with COVID-19, family members, the general public, scientists, engineers, health professionals (including specialist clinicians from multiple disciplines, such as infectious diseases, diagnostic pathology, cardiology or cardiovascular diseases, respiratory medicine, geriatrics, emergency medicine, critical care medicine, gastroenterology, hematology, pediatrics, infection prevention and control, and digital health), policy makers, industry representatives and funders.

We conducted an online survey to prioritize research statements in which respondents (n = 43) rated their importance using a 9-point Likert scale (7–9 indicating ‘critical importance’). The mean score, median and proportion of participants who rated the statement to be critically important are provided in Supplementary Table 1. Research statements that had a mean and median of ≥7 were discussed at a consensus workshop, conducted using Zoom videoconferencing on 20 August 2020, with the following goals: to achieve agreement on the research priorities, generate ideas for sensor technologies and discuss facilitators and barriers to implementation. To encourage diverse discussions, the 65 attendees were preassigned to six virtual breakout groups, with each group including patients who had been diagnosed previously with COVID-19 and/or family members, health professionals, scientists or engineers, and policymakers or funders. Each breakout group was managed by a facilitator and cofacilitator who moderated the discussion using the workshop question guide (Supplementary Table 2). All discussions were transcribed. We identified reasons for the priorities, ideas for sensor technologies (compounds, devices, general application), and the implementation of each (feasibility, usability, acceptability).

Of the 18 research statements, 8 had a mean and median score of 7 or more (Table 1). The top three priorities were the following: develop a point-of-care screening test for COVID-19; detect how contagious a person with COVID-19 is; and identify the level of immunity a person has to COVID-19. The reasons for priorities were summarized in four themes. First, ‘Enabling more efficient clinical decision-making’ was driven by the need to prevent delays in access to treatment, preserve finite resources (in terms of staffing, facilities for quarantine and personal protective equipment) and to provide prognostic information to inform patient care. Second, ‘Minimizing societal disruption’ was emphasized to enable a return to normal life and to reduce stigma and isolation. Third, ‘Protecting the community’ supported the need for sensor technology that could trigger contact tracing, establish safe environments, safeguard the vulnerable, gauge individual susceptibility to COVID-19, and manage the risk among healthcare workers. And finally, ‘Preparedness for the next phase of the pandemic’ required sensor technology to be relevant and responsive to the development of immunity and vaccines, and to help maintain the suppression phase over the long term. A detailed description with supporting quotations for each theme is provided in Supplementary Table 3.

Table 1 Suggestions and ideas for sensor technology to address COVID-19

For each of the top research priority statements, the specific suggestions for sensor technology (including compounds and devices) and its application are summarized in Table 1. The suggestions of ensuring feasibility, usability and acceptability of sensor technology and applications to address COVID-19 are outlined in Supplementary Table 4. These have been identified as essential attributes for an ideal sensor for pandemics in general, including accuracy, a fast response time, multiplexing capabilities, multiple sensing modes (sensor fusion and the use of artificial intelligence to detect signatures that reveal infection), disposability, long shelf life, ease of use, cost-effectiveness, manufacturability, and autonomy2. Particular emphasis was placed on the need for samples to be easy and safe to collect and the need for sensor devices to be non-invasive and their use regulated appropriately to ensure data privacy. The legal, ethical and privacy concerns surrounding the use of digital technology in COVID-19 are highly relevant given the need for public trust and engagement to ensure widespread uptake1.

Patients in particular emphasized the profound impacts of COVID-19 on mental health as a consequence of self-isolation and quarantine. Specifically, patients gave high priority to the detection of immunity and wanted assurance that they were no longer contagious because families and friends were avoiding them for an indefinite period of time (for some, over six months), given the fear and stigma attached to COVID-19. Developing sensor technology for the detection of protective immunity is also important, given the imminent distribution of vaccines and uncertainty regarding long-term immunity and reinfection3,9,10. Detection of immunity can further inform strategies to minimize societal and economic disruption. Of note, physiological monitoring was perceived to be lower in priority compared with rapid diagnosis and assessment of immunity, despite the possibility of its detecting early changes in clinical status that require rapid intervention or admission to hospital (that is, its potential as a screening tool).

The research priorities were motivated by personal and altruistic concerns. These included anxiety and concern about the need for urgency in diagnosis vis-à-vis impact of diagnostic delays on the severity and spread of COVID-19, a uniform preference for convenient sample types for testing, and the personal and public health need to be confident in the validity of markers of protective immunity and the duration of such immunity in response to either natural infection or vaccination. The high priority that patients gave to measuring infectivity and immunity to address stigma, fears and rejection they encountered from community members when told of their COVID-19 diagnosis would not have been considered without inclusion of this stakeholder group in the prioritization process.

Further work is required to identify the extent to which these priorities can be generalized globally or in specific settings, such as in low-resource settings or countries, where access to healthcare is limited. Furthermore, immediate research priorities may differ in countries, locations or cultures experiencing different stages of the pandemic. Nevertheless, collectively, such studies can help to formulate an equitable and coordinated international response to future pandemics and other global threats, including antimicrobial resistance, and mitigate the threat of such crises on people’s lives and the world’s economy (Fig. 1).

Fig. 1

A roadmap for research priorities for COVID-19 sensor technology.

Advances in nanotechnology and the Internet of things have stimulated the proliferation and ubiquity of sensor technology2. Traditionally, advances in sensor research have been the province of experts in smart technology and have not systematically and explicitly included the perspectives of the ultimate end users or beneficiaries. Although consideration is given to the end user in the design of sensor technology, the process is usually linear and between only two stakeholder groups. The inclusion of diverse stakeholder groups provides a more complete perspective to support uptake. Coproduction brings in the human context and attention to the areas of greatest importance, which are underpinned by social, ethical and human dimensions beyond just technical considerations. We believe this process provides a roadmap for the allocation of resources to purposefully advance sensor technology, which will strengthen the whole of society’s response to the COVID-19 pandemic and enhance preparedness for future pandemics.

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Acknowledgements

The project is funded by Sydney Nano. A.T. is supported by the University of Sydney Robinson Fellowship and a National Health and Medical Research Council Investigator Grant (1197324). The funding organizations had no role in the design and conduct of the study; collection, management, analysis and interpretation of the data; or preparation, review or approval of the manuscript. We acknowledge, with permission, all the attendees who participated in the research priority-setting workshop: Sarah Al-Horani, Tomas Andersen, Rodney Aggett, Lamiae Azizi, Andrew Baillie, Andrew Black, Celine Boehm, Philip Britton, Anthony Brown, Mitchell Burger, Corinne Caillaud, Alvaro Casas Bedoya, Steve Chadban, Elaine Chan, Nanda Sakaleshpura Chandrashekar, Gael Clerc, Wojciech Chrzanowski, Ben Eggleton, Simon Fleming, Gregory Fox, Luke Gordon, Nicholas Haskins, Anita Ho-Baillie, Martin Howell, Jun Huang, Nicholas Hunt, Owen Hutchings, Jonathan Iredell, Garry Jennings, Craig Jin, Omid Kavehei, Paris Kilham, Leonard Kritharides, Ben Kwan, Sergio Leon-Saval, Eugena Li, Steven Maguire, David Martinez-Martin, Annie McCluskey, Alistair McEwan, Nicholas McKay, Julian Morgans, Alice Motion, Stefano Palomba, Alan Pettigrew, Svetlana Postnova, Cathy Quinlan, James Rabeau, Katie Richmond, Damien Rothstein, Nicole Scholes-Robertson, Tim Shaw, Vitali Sintchenko, Thomas Snelling, Tania Sorrell, Allison Tong, Alessandro Tuniz, Pegah Varamini, Audrey Wang, Kailing Wang, Rex Wang, Alexander Witherden, Benjamin Wright, Wilson Yeung and Hans Zoellner. We acknowledge and pay respect to the Gadigal people of the Eora Nation, the traditional owners of the land on which we research, teach and collaborate at The University of Sydney.

Author information

Affiliations

  1. Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia

    Allison Tong

  2. Marie Bashir Institute for Infectious Disease and Biosecurity, The University of Sydney and Westmead Institute for Medical Research, Sydney, NSW, Australia

    Tania C. Sorrell

  3. Sydney Medical School, The University of Sydney, Sydney, NSW, Australia

    Tania C. Sorrell

  4. Westmead Living Lab, The University of Sydney, Sydney, NSW, Australia

    Andrew J. Black

  5. Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia

    Corinne Caillaud & Wojciech Chrzanowski

  6. The University of Sydney Nano Institute (Sydney Nano), The University of Sydney, Sydney, NSW, Australia

    Corinne Caillaud, Wojciech Chrzanowski, Eugena Li, David Martinez-Martin, Alistair McEwan, Rex Wang, Alice Motion, Alvaro Casas Bedoya, Jun Huang, Lamiae Azizi & Benjamin J. Eggleton

  7. School of Medical Sciences, The University of Sydney, Sydney, NSW, Australia

    Corinne Caillaud

  8. School of Biomedical Engineering, The University of Sydney, Sydney, NSW, Australia

    David Martinez-Martin, Alistair McEwan & Jun Huang

  9. School of Chemistry, The University of Sydney, Sydney, NSW, Australia

    Alice Motion

  10. School of Physics, University of Sydney, Sydney, NSW, Australia

    Alvaro Casas Bedoya & Benjamin J. Eggleton

  11. School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia

    Lamiae Azizi

  12. University of Technology, Ultimo, NSW, Australia

    Sarah Al-Horani

  13. The University of Sydney, Camperdown, NSW, Australia

    Tomas Andersen, Lamiae Azizi, Alexandra Barratt, Andrew Black, Celine Boehm, Corinne Caillaud, Alvaro Casas Bedoya, Clara Chow, Wojciech Chrzanowski, Benjamin Eggleton, Simon Fleming, Gregory Fox, Luke Gordon, Anita Ho-Baillie, Martin Howell, Ian Hickie, Jun Huang, Nicholas Hunt, Craig Jin, Kristina Kairaitis, Omid Kavehei, Leonard Kritharides, Sergio Leon-Saval, Eugena Li, Richard Lindley, Steven Maguire, David Martinez-Martin, Annie McCluskey, Alistair McEwan, Nicholas McKay, Alice Motion, Stefano Palomba, Alan Pettigrew, Svetlana Postnova, James Rabeau, Mark Rees, Katie Richmond, Nicole Scholes-Robertson, Ian Seppelt, Tim Shaw, Vitali Sintchenko, Tania Sorrell, Armando Teixeira-Pinto, Euan Tovey, Alessandro Tuniz, Pegah Varamini, Audrey P. Wang, Kailing Wang, Rex Wang, Steven Wise & Hans Zoellner

  14. Sydney, NSW, Australia

    Rodney Aggett, Chris Douglas, Paris Kilham & Damien Rothstein

  15. The University of Sydney, Sydney Local Health District, Camperdown, NSW, Australia

    Andrew Baillie

  16. The University of Sydney, The Children’s Hospital at Westmead, Westmead, NSW, Australia

    Philip Britton, Thomas Snelling & Allison Tong

  17. Health Consumers NSW, Sydney, NSW, Australia

    Anthony Brown

  18. Sydney Local Health District, Sydney, NSW, Australia

    Mitchell Burger

  19. The University of Sydney, Royal Prince Alfred Hospital, Camperdown, NSW, Australia

    Steve Chadban

  20. Westmead Hospital, Westmead, NSW, Australia

    Elaine Chan, Nicky Gilroy & Kavita Varshney

  21. eHealth NSW, Sydney, NSW, Australia

    Nanda Sakaleshpura Chandrashekar & Wilson Yeung

  22. Bepatient, Sydney, NSW, Australia

    Gael Clerc

  23. NSW Smart Sensing Network, Sydney, NSW, Australia

    Nicholas Haskins

  24. Royal Prince Alfred Hospital, Camperdown, NSW, Australia

    Owen Hutchings

  25. The University of Sydney, NSW Health Pathology, Westmead Institute for Medical Research, Westmead, NSW, Australia

    Jonathan Iredell

  26. Sydney Health Partners, Camperdown, NSW, Australia

    Garry Jennings

  27. eHealth NSW, Chatswood, NSW, Australia

    Peter Kennedy

  28. Sutherland Hospital, Caringbah, NSW, Australia

    Ben Kwan

  29. Jonze Society, Brisbane, QLD, Australia

    Deena Lynch

  30. The University of Sydney, Westmead Hospital, Westmead, NSW, Australia

    Geoffrey Mifsud

  31. Vice, Melbourne, VIC, Australia

    Julian Morgans

  32. The University of Sydney, ACRF Image X Institute, Camperdown, NSW, Australia

    Joseph Prinable

  33. Royal Children’s Hospital, Parkville, Victoria, Australia

    Cathy Quinlan

  34. Adionatech, Sydney, NSW, Australia

    Richard Savoie

  35. Camperdown, NSW, Australia

    Alexander Witherden

  36. Nanosonics Ltd, Sydney, NSW, Australia

    Benjamin Wright

Consortia

The COVID-19 Sensor Research Priority-Setting Investigators

Corresponding author

Correspondence to
Allison Tong.

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Competing interests

The authors declare no competing interests.

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