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We argue that deliberative decision making that is inclusive, transparent and accountable can contribute to more trustworthy and legitimate decisions on difficult ethical questions and political trade-offs during the pandemic and beyond.
The limitations of using race in biomedicine are important to recognize because race is often afforded more biological value than can be scientifically justified — and less social value than it commands.
The Human Cell Atlas has been undergoing a massive effort to support global scientific equity. The co-leaders of its Equity Working Group share some lessons learned in the process.
With only a limited number of clinical trials of artificial intelligence in medicine thus far, the first guidelines for protocols and reporting arrive at an opportune time. Better protocol design, along with consistent and complete data presentation, will greatly facilitate interpretation and validation of these trials, and will help the field to move forward.
Many widely used health algorithms have been shown to encode and reinforce racial health inequities, prioritizing the needs of white patients over those of patients of color. Because automated systems are becoming so crucial to access to health, researchers in the field of artificial intelligence must become actively anti-racist. Here we list some concrete steps to enable anti-racist practices in medical research and practice.
Racism is a social determinant of health and negatively affects health outcomes. This Comment describes steps to take toward achieving equity and racial justice in medical training and addressing racism in clinical settings.
In the current COVID-19 pandemic, many researchers are applying to research ethics committees for deferred-consent procedures for protocols that aim either to test treatments or to obtain tissue or samples from research participants. However, the deferred-consent procedure has not been developed for pandemics. In this Comment, we interpret existing guidance documents and argue when and under which conditions deferred consent can be considered ethically acceptable in a pandemic.
Given the current trends in incidence and underlying healthcare systems vulnerabilities, Africa could become the next epicenter of the COVID-19 pandemic. As the pandemic transitions to more widespread community transmission, how can the lessons learned thus far be consolidated to effectively curb the spread of COVID-19 while minimizing social disruption and negative humanitarian and economic consequences?
Many actors in the response to COVID-19 are holding out for a vaccine to be developed. But in the meantime, tried and tested public-health measures for controlling outbreaks can be implemented. A scorecard can be used to assess governments’ responses to the outbreak.
COVID-19 has disrupted scientific productivity in unquantifiable ways. Unquestionably, the biggest disruption has been felt by junior faculty. However, these bright young minds do not have to be sacrificed.
We call upon the research community to standardize efforts to use daily self-reported data about COVID-19 symptoms in the response to the pandemic and to form a collaborative consortium to maximize global gain while protecting participant privacy.
Mobile apps provide a convenient source of tracking and data collection to fight against the spread of COVID-19. We report our analysis of 50 COVID-19-related apps, including their use and their access to personally identifiable information, to ensure that the right to privacy and civil liberties are protected.
As the COVID-19 pandemic escalates, teams around the world are now advocating for a new approach to monitoring transmission: tapping into cellphone location data to track infection spread and warn people who may have been exposed. Here we present data collected in Israel through this approach so far and discuss the privacy concerns, alternatives and different ‘flavors’ of cellphone surveillance. We also propose safeguards needed to minimize the risk for civil rights.
Testing drug safety in people who are pregnant remains a wicked problem, but in the transition toward big data and machine learning, target trials could afford a viable alternative to randomized, controlled trials.
Necessity has been the mother of invention in the response to the COVID-19 pandemic, triggering many an innovation, often without the luxury of time to test these makeshift solutions to pressing problems. But there is much to be learned from times of crisis for times of plenty.
In the USA and around the world, the COVID-19 pandemic arrived as the population was fighting a devastating opioid overdose epidemic. Urgent and decisive action is needed to protect particularly vulnerable populations, such as those with opioid use disorder, to prevent a compounding effect on public health.
Researchers starting clinical trials of prevention measures for COVID-19 have a unique window of opportunity for collecting blood from the participants, at baseline and at the end of the trial, to be able to incorporate critical data into their analysis once serological tests for the causative coronavirus become available.
