Monday , October 19 2020

Amid the COVID-19 pandemic, experts are presenting a 10-point plan for a genomic revolution in public health

A phylogenetic tree is tracking the development of SARS-CoV-2, the virus that causes COVID-19, as it spreads throughout the United States. An orange dot in the lower left indicates WA-1, the first confirmed case in the United States to be found in Washington State. (Nextstrain / GISAID graphic)

Since the beginning of the coronavirus pandemic, genetic exploration has been at the forefront of global efforts to monitor SARS-CoV-2, the virus that causes COVID-19. By comparing the molecular fingerprints of various virus samples collected in the state of Washington, they were able to find the first signs of a spreading community in the United States.

In an article published today by Natural medicinesome of the pioneers of genomic epidemiology a 10-point plan to create a well-supported scientific ecosystem – not only to fight COVID-19, but also to ward off future pandemics.

"COVID has really accelerated the pace at which this work was done," he said Trevor Bedford, a computer biologist at the Fred Hutchinson Cancer Research Center in Seattle, who is co-author of the plan. "Now the church is trying to figure out how to buckle up in the long run."

Genomic epidemiology did not start with COVID-19: efforts to monitor the spread and development of the virus use tools and networks that have been created to combat other diseases polio to the Zika virus.

Bedford and his colleagues could Follow the pandemic in the United States. and other countries thanks to genomes working on existing projects like that Seattle flu study and Nextstrain.

The roots of today's call for action go back more than a year Meeting of bioinformatics experts and public health representatives This was convened at the Bill & Melinda Gates Foundation headquarters in Seattle. This meeting led to the creation of the Public Health Alliance for Genomic Epidemiologyor PHA4GE (pronounced like “phage”) a good two months before COVID-19 appeared in China.

In the past six months, more than 450 laboratories around the world have 45,000 SARS CoV-2 genomes GISAID database. Tracking the similarities and differences in these genomes can reveal the evolutionary relationships between them and lead to detailed maps of the virus flow.

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A lot was learned: The first analysis showed, for example, that the coronavirus had spread from one person to up to 1,500 people in Washington State by the end of February, when experts confirmed the transmission by the community. However, a later analysis based on additional genome data preferred a scenario with multiple transmission paths.

Bedford said that changing the way scientists looked at the origins of the pandemic highlighted the importance of simple and fast data exchange.

"Basically, none of this works if everything is isolated," he said. "If you only sequenced your data for the state of Washington and did not share it, you have no idea how it would connect to the rest of the world. Your ability to solve the epidemiological story really depends on the fact that you have different points together can connect. "

Another challenge concerns the software that was developed to analyze genome data for epidemiological purposes. "It's not too well maintained or well documented, and it's hard to use," said the study's lead author Allison Black, Epidemiologist with Fred Hutch and the University of Washington.

Black conducted dozens of interviews with epidemiologists around the world to get a feel for the challenges they faced and what she heard helped shape the 10 recommendations listed in the paper released today:

  • Support for data hygiene and interoperability by developing and adopting a consistent data model.
  • Strengthen the application programming interfaces.
  • Development of guidelines for the management and administration of genome data.
  • Make bioinformatics pipelines fully open source and generally accessible.
  • Development of modular pipelines for data visualization and exploration.
  • Improving the reproducibility of bioinformatics analysis.
  • Use cloud computing to improve the scalability and accessibility of bioinformatics analyzes.
  • Support new infrastructure and software development requirements with an expanded technical workforce.
  • Improving the integration of genomic epidemiology into traditional epidemiology.
  • Develop best practices to support open data exchange.

Black admitted that finding the resources to develop standardized analytics software and deploy cloud computing firepower is another big challenge. "The traditional funding mechanisms in the academic realm do not provide a real incentive for this work, so we will need new funding mechanisms to incentivize this work and build the ecosystem," she said. "I can't say exactly what that looks like."

One way could be to win the tech industry: In March, for example, the White House Office of Science and Technology Policy put together a high-performance COVID 19 computing consortium that Amazon, Microsoft, Google and other tech powerhouses brought together to support large companies -Data research projects related to the pandemic.

Another co-author of the study, Duncan MacCannell The Centers for Disease Control and Prevention emphasized the need to train researchers.

"Getting a bioinformatic workforce into public health is a huge challenge," he said. "You are competing against science, against the many aspects of the private sector, the biotech industry and the pharmaceutical industry."

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Despite the competition, MacCannell said the CDC grant program could generally hold its own.

"Typically, around 70% of our graduates stay in public health careers, either at federal or state levels," he said. "We can't necessarily compete based on salary, but we can compete based on fascinating and rewarding questions." And you really feel like you are making a difference. "

Looking to the future, Bedford said that genomic epidemiologists could work hand in hand with traditional epidemiologists to answer some of the crucial questions that have only recently emerged. For example is The new outbreak in Arizona mainly due to the reopening of the state or due to the reintroduction of the virus by infected visitors?

"Genomics could help understand in detail what really drives the spread of the epidemic," said Bedford. And these insights, in turn, could point to the best policy to contain a resurgent epidemic.

The researchers acknowledge that there are still many gaps in their 10-point plan. "I see this paper as a starting point for discussion," said Black. "I don't think we'll end up with the dream ecosystem overnight. We'll find out a lot more … and repeat it."

But Bedford said it was high time to have a plan to work with.

"We are here at this critical moment," he said. “COVID really accelerated things. Everyone runs so fast with this thing that coordination and cat keeping is really necessary. "

In addition to Black, MacCannell and Bedford, Fred Hutch researchers Thomas Sibley is co-author of the paper entitled Nature Medicine "Ten Recommendations to Support Genome Analysis of Open Pathogens in Public Health."

About Kylo Crowther

Kylo Crowther is a housewife who is fond of social media. She is also a blogger.

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