Unleashing the power of big data to guide precision medicine in China

Curated on Posted on by Stefaan Verhulst

Article by Yvaine Ye in Nature: “Precision medicine in China was given a boost in 2016 when the government included the field in its 13th five-year economic plan. The policy blueprint, which defined the country’s spending priorities until 2020, pledged to “spur innovation and industrial application” in precision medicine alongside other areas such as smart vehicles and new materials.

Precision medicine is part of the Healthy China 2030 plan, also launched in 2016. The idea is to use the approach to tackle some major health-care challenges the country faces, such as rising cancer rates and issues related to an ageing population. Current projections suggest that, by 2040, 28% of China’s population will be over 60 years old.

Following the announcement of the five-year plan, China’s Ministry of Science and Technology (MOST) launched a precision-medicine project as part of its National Key Research and Development Program. MOST has invested about 1.3 billion yuan (US$200.4 million) in more than 100 projects from 2016 to 2018. These range from finding new drug targets for chronic diseases such as diabetes to developing better sequencing technologies and building a dozen large population cohorts comprising hundreds of thousands of people from across China.

China’s population of 1.4 billion people means the country has great potential for using big data to study health issues, says Zhengming Chen, an epidemiologist and chronic-disease researcher at the University of Oxford, UK. “The advantage is especially prominent in the research of rare diseases, where you might not be able to have a data set in smaller countries like the United Kingdom, where only a handful of cases exist,” says Chen, who leads the China Kadoorie Biobank, a chronic-disease initiative that launched in 2004. It recruited more than 510,000 adults from 10 regions across China in its first 4 years, collecting data through questionnaires and by recording physical measurements and storing participants’ blood samples for future study. So far, the team has investigated whether some disease-related lifestyle factors that have been identified in the West apply to the Chinese population. They have just begun to dig into participants’ genetic data, says Chen.

Another big-data precision-medicine project launched in 2021, after Huijun Yuan, a physician who has been researching hereditary hearing loss for more than two decades, founded the Institute of Rare Diseases at West China Hospital in Chengdu, Sichuan province, in 2020. By 2025, the institute plans to set up a database of 100,000 people from China who have rare conditions, including spinal muscular atrophy and albinism. It will contain basic health information and data relating to biological samples, such as blood for gene sequencing. Rare diseases are hard to diagnose, because their incidences are low. But the development of technologies such as genetic testing and artificial intelligence driven by big data is providing a fresh approach to diagnosing these rare conditions, and could pave the way for therapies…(More)”.

How Covid Tracking Apps Are Pivoting for Commercial Profit

Curated on Posted on by Stefaan Verhulst

Article by Matt Reynolds and Morgan Meaker: “…At its peak, 2.4 million people tracked their symptoms using the Covid Symptom Tracker. It was one of three surveillance studies the UK government used to track and respond to new outbreaks. Data from the tracker led to the UK government adding loss of smell and taste to the official list of Covid-19 symptoms. Between August 2020 and March 2022, the app was funded with £5.1 million ($6.2 million) from the Department of Health and Social Care.

But in early May 2022, Zoe announced in an email to users that its Covid tracking app would no longer be just a place for people to report their Covid symptoms. The Covid Symptom Tracker was becoming the Zoe Health Study, which asks people to take 10 seconds a day to log their mental and physical health beyond Covid. People who agree to take part in this wider study are asked to establish their baseline health—reporting everything from hair loss to mouth ulcers—as well as providing daily health updates. The company says this data will be used to “fight the most important health issues of our time,” but that it might also be used to develop commercial health, nutrition, and lifestyle products. (Zoe also sells nutrition tests and subscriptions to a personalized nutrition platform.)

Zoe isn’t the only Covid app developer pivoting away from the pandemic. In Berlin, a contact-tracing app called Luca is reinventing itself as a payment system, while in northern Italy an app set up to track coronavirus cases now warns citizens about natural disasters. With the most urgent phase of the pandemic now over, developers are looking for ways to squeeze more value out of the users who have downloaded their apps. The great Covid-19 data pivot is well and truly underway…(More)”.

Public Health Struggles to Get Rid of Its Data Silos

Curated on Posted on by Stefaan Verhulst

Article by Carl Smith: “…In September 2019, before the first COVID-19 case was reported in the U.S., the Council of State and Territorial Epidemiologists (CSTE) published a report calling for a “public health data superhighway” capable of detecting health challenges and informing the response to them.

The technology to accomplish this already exists, CSTE noted. But even so, “public health departments struggle to take advantage of these advancements and continue to rely on sluggish, manual processes like paper records, phone calls, spreadsheets, and faxes requiring manual data entry.”

The limitations of this data ecosystem became a considerable liability when public health officials ran up against a virus that had never been seen before, working to both understand and control it at the same time. “There were mixed messages, and the pandemic made us look like our data was not adequate to the task,” says Gail C. Christopher, executive director of the National Collaborative for Health Equity.

This provided an opening for political or social actors to push anti-public health campaigns that continue to fuel public distrust of public health leaders, workers and guidelines. Reliable and timely data could help heal some of the harm that has been done, says Christopher.

“I think every health department has aspects of a complete data system,” says Brian Castrucci, president and CEO of the DeBeaumont Foundation, which funded the CSTE report. “But we need to articulate what a complete data system looks like — right now, we don’t even know what the destination is, so it’s hard to tell when we’re lost.”

A Data Modernization Movement

Data systems improvement is one of three major topics that recur in discussions about rebuilding public health, along with workforce expansion and regaining public trust, says Michael Fraser, executive director of the Association of State and Territorial Health Officials (ASTHO). “A major finding from all the conversations that we’ve had about COVID is that data systems need to be modernized.”

In recent years, there has been considerable effort by the public health community to find ways to move away from “silo-based” or disease-based surveillance between states and the federal government to an enterprise-wide system, says Fraser. “During COVID, a lot of states had a hard time sharing data, and there are many parts of this country where people go back and forth between multiple states on any given day — it’s not just the ability for states to share data with the federal government, but for states to share amongst themselves.”

The CDC’s Data Modernization Initiative, launched in 2020, is a $1.2 billion effort to address this challenge, envisioning resilient, connected systems that could “solve problems before they happen and reduce the harm caused by the problems that do happen.” The CSTE campaign “Data: Elemental to Health” is working to ensure sustained public funding for this work…(More)”.

AI Can Predict Potential Nutrient Deficiencies from Space

Curated on Posted on by Stefaan Verhulst

Article by Rachel Berkowitz: “Micronutrient deficiencies afflict more than two billion people worldwide, including 340 million children. This lack of vitamins and minerals can have serious health consequences. But diagnosing deficiencies early enough for effective treatment requires expensive, time-consuming blood draws and laboratory tests.

New research provides a more efficient approach. Computer scientist Elizabeth Bondi and her colleagues at Harvard University used publicly available satellite data and artificial intelligence to reliably pinpoint geographical areas where populations are at high risk of micronutrient deficiencies. This analysis could potentially pave the way for early public health interventions.

Existing AI systems can use satellite data to predict localized food security issues, but they typically rely on directly observable features. For example, agricultural productivity can be estimated from views of vegetation. Micronutrient availability is harder to calculate. After seeing research showing that areas near forests tend to have better dietary diversity, Bondi and her colleagues were inspired to identify lesser-known markers for potential malnourishment. Their work shows that combining data such as vegetation cover, weather and water presence can suggest where populations will lack iron, vitamin B12 or vitamin A.

The team examined raw satellite measurements and consulted with local public health officials, then used AI to sift through the data and pinpoint key features. For instance, a food market, inferred based on roads and buildings visible, was vital for predicting a community’s risk level. The researchers then linked these features to specific nutrients lacking in four regions’ populations across Madagascar. They used real-world biomarker data (blood samples tested in labs) to train and test their AI program….(More)”.

How Period-Tracker Apps Treat Your Data, and What That Means if Roe v. Wade Is Overturned

Curated on Posted on by Stefaan Verhulst

Article by Nicole Nguyen and Cordilia James: “You might not talk to your friends about your monthly cycle, but there’s a good chance you talk to an app about it. And why not? Period-tracking apps are more convenient than using a diary, and the insights are more interesting, too. 

But how much do you know about the ways apps and trackers collect, store—and sometimes share—your fertility and menstrual-cycle data?

The question has taken on new importance following the leak of a draft Supreme Court opinion that would overturn Roe v. Wade. Roe established a constitutional right to abortion, and should the court reverse its 1973 decision, about half the states in the U.S. are likely to restrict or outright ban the procedure.

Phone and app data have long been shared and sold without prominent disclosure, often for advertising purposes. HIPAA, aka the Health Insurance Portability and Accountability Act, might protect information shared between you and your healthcare provider, but it doesn’t typically apply to data you put into an app, even a health-related one. Flo Health Inc., maker of a popular period and ovulation tracker, settled with the Federal Trade Commission in 2021 for sharing sensitive health data with Facebook without making the practice clear to users.

The company completed an independent privacy audit earlier this year. “We remain committed to ensuring the utmost privacy for our users and want to make it clear that Flo does not share health data with any company,” a spokeswoman said.

In a scenario where Roe is overturned, your digital breadcrumbs—including the kind that come from period trackers—could be used against you in states where laws criminalize aiding in or undergoing abortion, say legal experts.

“The importance of menstrual data is not merely speculative. It has been relevant to the government before, in investigations and restrictions,” said Leah Fowler, research director at University of Houston’s Health Law and Policy Institute. She cited a 2019 hearing where Missouri’s state health department admitted to keeping a spreadsheet of Planned Parenthood abortion patients, which included the dates of their last menstrual period.

Prosecutors have also obtained other types of digital information, including text messages and search histories, as evidence for abortion-related cases…(More)”.

Smartphone apps in the COVID-19 pandemic

Curated on Posted on by Stefaan Verhulst

Paper by Jay A. Pandit, Jennifer M. Radin, Giorgio Quer & Eric J. Topol: “At the beginning of the COVID-19 pandemic, analog tools such as nasopharyngeal swabs for PCR tests were center stage and the major prevention tactics of masking and physical distancing were a throwback to the 1918 influenza pandemic. Overall, there has been scant regard for digital tools, particularly those based on smartphone apps, which is surprising given the ubiquity of smartphones across the globe. Smartphone apps, given accessibility in the time of physical distancing, were widely used for tracking, tracing and educating the public about COVID-19. Despite limitations, such as concerns around data privacy, data security, digital health illiteracy and structural inequities, there is ample evidence that apps are beneficial for understanding outbreak epidemiology, individual screening and contact tracing. While there were successes and failures in each category, outbreak epidemiology and individual screening were substantially enhanced by the reach of smartphone apps and accessory wearables. Continued use of apps within the digital infrastructure promises to provide an important tool for rigorous investigation of outcomes both in the ongoing outbreak and in future epidemics…(More)”.

Data saves lives: reshaping health and social care with data

Curated on Posted on by Stefaan Verhulst

UK Government Policy Paper: “…Up-to-date information about our health and care is critical to ensuring we can:

  • plan and commission services that provide what each local area needs and support effective integrated care systems
  • develop new diagnostics, treatments and insights from analysing information so the public have the best possible care and can improve their overall wellbeing
  • stop asking the public to repeat their information unnecessarily by having it available at the right time
  • assess the safety and quality of care to keep the public safe, both for their individual care and to improve guidance and regulations
  • better manage public health issues such as COVID-19, health and care disparities, and sexual health
  • help the public make informed decisions about their care, including choosing clinicians, such as through patient-reported outcome measures (PROMs) that assess the quality of care delivered from a patient’s perspective

When it comes to handling personal data, the NHS has become one of the most trusted organisations in the UK by using strict legal, privacy and security controls. Partly as a consequence of this track record, the National Data Guardian’s recent report Putting Good Into Practice found that participants were supportive of health and social care data being used for public benefit. This reflects previous polls, which show most respondents would trust the NHS with data about them (57% in July 2020 and 59% in February 2020).

During the pandemic, we made further strides in harnessing the power of data:

However, we cannot take the trust of the public for granted. In the summer of 2021, we made a mistake and did not do enough to explain the improvements needed to the way we collect general practice data. The reasons for these changes are to improve data quality, and improve the understanding of the health and care system so it can plan better and provide more targeted services. We also need to do this in a more cost-effective way as the current system using ad hoc collection processes is more expensive and inefficient, and has been criticised by the National Audit Office and the House of Commons Public Accounts Committee.

Not only did we insufficiently explain, we also did not listen and engage well enough. This led to confusion and anxiety, and created a perception that we were willing to press ahead regardless. This had the unfortunate consequence of leading to an increase in the rate of individuals opting out of sharing their data. Of course, individual members of the public have the right to opt out and always will. But the more people who opt out, the greater the risk that the quality of the data is compromised….

In this data strategy, which differs from the draft we published last year, we are putting public trust and confidence front and centre of the safe use and access to health and social care data. The data we talk about is not an abstract thing: there is an individual, a person, a name behind each piece of data. That demands the highest level of confidence. It is their data that we hold in trust and, in return, promise to use safely to provide high-quality care, help improve our NHS and adult social care, develop new treatments, and, as a result, save lives…(More)”

Forecasting hospital-level COVID-19 admissions using real-time mobility data

Curated on Posted on by Stefaan Verhulst

Paper by Brennan Klein et al: “For each of the COVID-19 pandemic waves, hospitals have had to plan for deploying surge capacity and resources to manage large but transient increases in COVID-19 admissions. While a lot of effort has gone into predicting regional trends in COVID-19 cases and hospitalizations, there are far fewer successful tools for creating accurate hospital-level forecasts. At the same time, anonymized phone-collected mobility data proved to correlate well with the number of cases for the first two waves of the pandemic (spring 2020, and fall-winter 2021). In this work, we show how mobility data could bolster hospital-specific COVID-19 admission forecasts for five hospitals in Massachusetts during the initial COVID-19 surge. The high predictive capability of the model was achieved by combining anonymized, aggregated mobile device data about users’ contact patterns, commuting volume, and mobility range with COVID hospitalizations and test-positivity data. We conclude that mobility-informed forecasting models can increase the lead-time of accurate predictions for individual hospitals, giving managers valuable time to strategize how best to allocate resources to manage forthcoming surges…(More)”.

Impediment of Infodemic on Disaster Policy Efficacy: Insights from Location Big Data

Curated on Posted on by Stefaan Verhulst

Paper by Xiaobin Shen, Natasha Zhang Foutz, and Beibei Li: “Infodemics impede the efficacy of business and public policies, particularly in disastrous times when high-quality information is in the greatest demand. This research proposes a multi-faceted conceptual framework to characterize an infodemic and then empirically assesses its impact on the core mitigation policy of a latest prominent disaster, the COVID-19 pandemic. Analyzing a half million records of COVID-related news media and social media, as well as .2 billion records of location data, via a multitude of methodologies, including text mining and spatio-temporal analytics, we uncover a number of interesting findings. First, the volume of the COVID information incurs an inverted-U-shaped impact on individuals’ compliance with the lockdown policy. That is, a smaller volume encourages the policy compliance, whereas an overwhelming volume discourages compliance, revealing negative ramifications of excessive information about a disaster. Second, novel information boosts policy compliance, signifying the value of offering original and distinctive, instead of redundant, information to the public during a disaster. Third, misinformation exhibits a U-shaped influence unexplored by the literature, deterring policy compliance until a larger amount surfaces, diminishing informational value, escalating public uncertainty. Overall, these findings demonstrate the power of information technology, such as media analytics and location sensing, in disaster management. They also illuminate the significance of strategic information management during disasters and the imperative need for cohesive efforts across governments, media, technology platforms, and the general public to curb future infodemics…(More)”.

Citizen power mobilized to fight against mosquito borne diseases

Curated on Posted on by Stefaan Verhulst

GigaBlog: “Just out in GigaByte is the latest data release from Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes, and is part of our WHO-sponsored series on vector borne human diseases. Presenting 13,700 new database records in the Global Biodiversity Information Facility (GBIF) repository, all linked to photographs submitted by citizen volunteers and validated by entomological experts to determine if it provides evidence of the presence of any of the mosquito vectors of top concern in Europe. This is the latest of a new special issue of papers presenting biodiversity data for research on human diseases health, incentivising data sharing to fill important particular species and geographic gaps. As big fans of citizen science (and Mosquito Alert), its great to see this new data showcased in the series.

Vector-borne diseases account for more than 17% of all infectious diseases in humans. There are large gaps in knowledge related to these vectors, and data mobilization campaigns are required to improve data coverage to help research on vector-borne diseases and human health. As part of these efforts, GigaScience Press has partnered with the GBIF; and has been supported by TDR, the Special Programme for Research and Training in Tropical Diseases, hosted at the World Health Organization. Through this we launched this “Vectors of human disease” thematic series. Incentivising the sharing of this extremely important data, Article Processing Charges have been waived to assist with the global call for novel data. This effort has already led to the release of newly digitised location data for over 600,000 vector specimens observed across the Americas and Europe.

While paying credit to such a large number of volunteers, creating such a large public collection of validated mosquito images allows this dataset to be used to train machine-learning models for vector detection and classification. Sharing the data in this novel manner meant the authors of these papers had to set up a new credit system to evaluate contributions from multiple and diverse collaborators, which included university researchers, entomologists, and other non-academics such as independent researchers and citizen scientists. In the GigaByte paper these are acknowledged through collaborative authorship for the Mosquito Alert Digital Entomology Network and the Mosquito Alert Community…(More)”.