July 11, 2020
In a previous blog post, we explored how voluntary contact self-tracing can assist other contact tracing techniques in alerting people who may have been exposed to the COVID-19 virus. This technique enables participants to log interactions with others so that they can discover if they are in a chain of contacts originating with someone, often a stranger, who subsequently tests positive for the virus. These contacts could include friends at a barbeque, grocery checkers, hairdressers, restaurant waitstaff, taxi drivers, or other interactions.
In contrast to highly publicized, proximity-based contact tracing by using mobile devices, voluntary self-tracing avoids security and privacy issues that have threatened widespread adoption. It also adds human judgment to the process so that the chain of contacts captures only potentially risky interactions. This is accomplished in advance of a positive test, enabling immediate notifications when the need arises.
Voluntary self-tracing offers huge value in connecting strangers who otherwise would not be notified about the need for testing without arduous manual contact tracing. However, it imposes the burden that everyone participates in a common tracing system and consistently makes the effort to log interactions. While this might restrict its appeal for public use, it could be readily adopted by companies, which have well-known, slowly changing populations and established working relationships and protocols.
Consider a company that has multiple departments distributed across several locations. As employees come back to work, they typically interact closely with colleagues in the same department. If anyone in the department tests positive for COVID-19, it’s likely that all of these colleagues have been exposed and need to get tested. In addition, employees occasionally interact with colleagues in other departments, both at the same site and at remote sites. These interactions also need to be tracked to contain exposure within the organization, as illustrated in the following diagram:
Voluntary contact self-tracing can handle the most common scenarios by using the company’s employee database to automatically connect colleagues who work in the same department and interact daily. Employees need only manually log contacts they make with employees in other departments. These interactions are relatively infrequent and tracked for a limited period of time (typically two weeks). This approach streamlines the work required to track contacts, while enabling the company to immediately identify all employees who need to be notified, tested, and possibly isolated after one person tests positive.
In addition, employees can manually track information about contacts they make while on business travel, such as during airline flights, taxi rides, and meals at restaurants. That way, when an employee tests positive, these external contacts can be immediately alerted of possible exposure. This enables companies to assist their communities in contact tracing and help contain the spread of COVID-19.
Many large companies have tens of thousands of employees and need to perform fast, efficient contact tracing. They require both immediate notifications and up-to-the-moment statistics that identify emerging trends, such as hot spots at one of their offices. To make this possible, a technology called in-memory computing can be used to track contacts and immediately alert all affected employees (and community touchpoints, such as restaurants) when anyone tests positive and alerts the system. Using a mobile app connected to a cloud service, it creates and maintains a dynamic web of contacts that evolves as interactions occur and time passes.
For example, when an employee tests positive and alerts the system, all colleagues in the same department are quickly notified, as are employees in other departments with whom interactions have occurred. The contact tracing system follows the chain of contacts across departments at all locations within the company. It also notifies community contacts, such as airlines and taxi companies, of possible exposures so that they can take the appropriate action.
Within the cloud service, the in-memory computing system maintains a software-based real-time digital twin for each employee. This software twin records and maintains all contacts for the employee, as well as all community contacts. It also removes non-recurring contacts after sufficient time passes and exposure is no longer likely. When an employee tests positive, the mobile app notifies the corresponding real-time digital twin in the cloud. This sets off the chain of communication that alerts all connected twins to the exposure and notifies their real-world counterparts.
Real-time digital twins contain a wealth of dynamic, up-to-the-minute information that can be tapped to help managers maintain situational awareness about rapidly evolving exposures and ongoing progress to contain them. In-memory computing technology can aggregate this data and visually present the results to help immediately spot outbreaks and identify significant problem areas. For example, the following chart, which can be updated every few seconds, shows the number of employees who have just tested positive at each site within a company:
The chart shows a jump in cases for employees at the Florida site. Managers can then investigate the source of the outbreak by department at this site:
Not surprisingly, most cases are occurring in the Retail department, most likely because of its large number of interactions with customers, and this department needs to take additional steps to limit exposure. With real-time aggregate analytics, managers can also track other important indicators, such as the number of employees and sites affected by an outbreak, the average number of interconnected contacts, and the percentage of affected employees who have received notifications and taken action.
As companies strive to restore to a normal working environment, managers recognize the need to carefully track the occurrence of COVID-19 in the workplace and minimize its propagation throughout an organization. Immediately notifying and isolating all affected employees helps to limit the size of an outbreak, while analyzing the sources and evolution of incidents assists managers in the moment and as they develop new policies and strategies. With its ability to track and analyze fast-changing data in real time, in-memory computing technology offers a powerful and flexible toolset for contact tracing, helping employees get back to work safely.
