Only a common public health infrastructure of AI, cloud computing, streaming, and the Internet of Things can marshal our data against pandemics

Pandemics are shocks to communities throughout the world. Each community’s response emerges from the countless changes that individuals make in their daily lives to protect themselves while trying to maintain a semblance of normality.

Grassroots responses often emerge first in such crises, but they may not be the most effective approach for slowing the contagion’s spread. From a technological standpoint, solutions invariably involve various blends of remote collaboration, contactless transactions, and replacement of manual processes with automated, robotic, and other human-free processes.

When a contagion is raging, grassroots responses can be counterproductive if everybody’s operating at cross-purposes. Lack of central coordination can confuse the situation for everybody, stoking a panic-driven infodemic that social media can exacerbate, drowning out guidance from public health officials and other reliable sources. To ensure effective orchestration of community-wide responses to a contagion, there is no substitute for authoritative data analytics to drive effective responses at all levels of society.

Going forward, we can expect to see more data-driven, top-down orchestration of pandemic preparedness and remediation among public, private, and nonprofit organizations. China’s experience is instructive in this regard. Though the outbreak’s inception in Wuhan was less than half a year ago, the country has responded rapidly with a top-down, nationwide approach to manage the crisis. Chinese authorities are orchestrating vast resources to save lives, control the spread of infection, and guide individuals for testing, treatment, and quarantining.

In contrast, the United States and other nations seem to be responding to the emergency in a chaotic, bottom-up fashion. The key elements in China’s response are impressive. Leveraging sophisticated data analytics and other digital tools, it has responded to COVID-19 through:

·         Self-service health screening: Self-service screening tools have reduced nonessential hospital visits and caregiver workloads in China while mitigating the risks of cross-infection. Within the country, Tencent, Alibaba, and vertical online healthcare platforms now offer remote medical services to the public. People consult with doctors online, conduct self-assessments, and decide whether to go to a hospital for further medical checks or remain at home.

·         Community outreach: China’s digital platforms allow volunteer teams of community residents to assist in disinfection and deliver supplies aided by digital community management and communication tools. Citizens receive a health QR code that lets them submit information regarding travel to major epidemic outbreak regions. It enables compilation of data on close contacts with infected people and other relevant matters, and it enables an assessment on a three-color scale that indicates a person’s recent virus-related health history.

·         Remote medicine: Digital technologies have allowed China’s healthcare professionals to apply their talents to a large number of COVID-19 cases over long distances. China’s 5G networks have allowed many Wuhan hospitals to connect with counterparts in Beijing, who provide real-time consultation based on transmission of ultra-high-definition medical images.

·         Supply-chain orchestration: China has used these same technologies, along with the Internet of Things, to rapidly orchestrate an entire manufacturing, logistics, and healthcare supply chain. This has enabled the country to coordinate thousands of domestic firms to build and equip hospitals for testing and treatment of COVID-19 patients. The country has been able to rapidly scale up the production of masks, protective clothing, and disinfectants.

·         Location matching: China has implemented a differentiated, location-specific response to limiting COVID-19 transmission. It uses big data analytics and artificial intelligence to estimate the probability that a particular neighborhood or individual was exposed to COVID-19. It matches the locations of smartphones to known locations of infected individuals or groups. It uses this information plus travel data to target government-mandated virus testing to high-risk individuals.

Likewise, neighboring Taiwan has put together a comprehensive program of technology-driven tactics for controlling COVID-19’s spread in the country. Distilling from those East Asian nations’ experiences, I’m proposing a new normal for every country; it involves the following data-driven pillars of top-down response to raging pandemics:

·         Counter-contagion nerve centers: In the new normal, most nations will institute counter-contagion nerve centers to coordinate societal responses to these threats. These operations will consolidate information from national health, immigration, customs, telecommunications, and travel databases. They will apply sophisticated AI to identify cases, generate real-tim;e alerts, and coordinate medical interventions. They will use real-time streaming apps to actively surveil and screen all ports into the country. These tools will provide the intelligence necessary to authoritatively close borders, certify which potential entrants are in good health, and quarantine or turn away people and animals that might be spreading contagion.

·         Quarantine orchestration: Painfully, the human race is learning from the COVID-19 crisis how to manage the quarantines, lockdowns, and closures that will be necessary in all future pandemics. In the future, public health authorities will use AI-driven predictive tools to rapidly plan and orchestrate these decisions in order to slow outbreaks while keeping the economy from crashing and minimizing community disruptions. Community contagion dashboards will give every person data-driven intelligence on how to adjust daily routines, based on conditions that currently impact their immediate environment. These and other sources of AI-driven intelligence will allow organizations to calculate the risk of having employees work in shared offices or from home, and to adjust their strategies day to day based on infection risk factors. When considering whether to bring employees back to the office while the pandemic is still going on, organizations base their decisions on data-driven analytics, as well as on site surveys informed by facility-embedded biosensors.

·         Social distancing: Going forward, we’re likely to see governments mandate AI-driven solutions for keeping people out of range of those who might be spreading infection. Proximity sensors will become ubiquitous in the aftermath of the current pandemic. Embedded in smartphones and wearables, they will feed personal digital assistants with real-time ambient intelligence on crowd conditions. Already, computer vision applications use AI to automate surveillance of people in public places, workplaces, stores, and elsewhere. Real-time AI tools will tell people if they’re standing too close to each other. Wait-time metering and crowd-limiting applications will become a standard feature of many public and private facilities. And we’ll see greater uptake of machine vision applications that can detect and optionally send “keep ‘em separated” alerts when someone moves too close to someone else.

·         Comprehensive biosensing: The COVID-19 emergency is accelerating the Internet of Things’ sensor revolution, and there’s little doubt that much of this will be built in to public infrastructure everywhere. The new normal is likely to proliferate biosensors for detecting viral pathogens in the air, water, soil, surfaces, and human and animal tissues. More commonly these biosensors will be wearables, connected socially to detect the potential spread of infections from person to person and to monitor a disease’s progression among large groups of people, such as hospital patients and nursing home residents. AI-driven service robots will interrogate passersby in public places to see if they show signs of the virus. To detect symptoms even before people realize they’re infected, automated environment sensing will use multimodal AI to monitor the environment (pairing facial recognition with temperature scanning and listening to audio of people coughing). Infrared thermal imaging will enable active surveillance and screening for infected and carrier persons at borders, airports, and elsewhere in each country. We can expect governments to mandate embedded contact-tracing apps on every mobile phone.

Putting this vision in place in the post-pandemic world will require a pervasive infrastructure of AI, cloud computing, streaming, and the Internet of Things. Managed as a common public health infrastructure, these capabilities will allow humanity to close ranks against the dread diseases that threaten us all.

James Kobielus is research director and lead analyst at Futurum Research.

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