Since the outbreak of the COVID-19 pandemic, cloud computing, big data, artificial
intelligence (AI) and other technologies have been widely applied in Shenzhen, south China’s
Guangdong province, helping improve the efficiency of Shenzhen’s response to public health
emergencies and inter-department collaboration capabilities of the city during its
implementation of the dynamic zero-COVID policy.
To ensure efficient epidemiological investigation, contact tracing, and prompt action for the
virus prevention and control, Shenzhen Center for Disease Control and Prevention (Shenzhen
CDC), together with China’s tech giant Tencent, developed and implemented a digital system
for epidemiological investigation.
Information collection in epidemiological investigation is considered the most time-
consuming and arduous task in the containment of the spread of the pandemic.
During the process, epidemiological investigators often need to hold a phone in one hand to
ask individuals who are at risk of infection and close contacts of COVID patients about their
information, and write down the information with a pen in the other hand. Each investigator is
responsible for entering a vast volume of handwritten data into electronic documents on a
daily basis.
It happens a lot when the objects of epidemiological investigation hang up the phone or
simply don’t answer phone calls from an unknown number; more often than not, investigators
need to call the same person over and over again.
The digital system, which integrates AI technologies including Voice over Internet
Protocol (VoIP), speech recognition and natural language processing (NLP), enables
epidemiological investigators to speak with the callees via computer and headset. This
eliminates the need for them to hold the phone throughout the discussion and allows for easier
recording of the information, ensuring an efficient flow of information and aiding in the city’s
epidemic response.
To assure citizens of the credibility of the calls for epidemiological investigation, the system
has labeled their caller ID as Shenzhen CDC and sends a message to citizens to encourage
them to answer the phone for epidemiological investigation.
Besides, the system can automatically process the information collected during the
epidemiological investigation, saving investigators a huge amount of time they would have
spent on reorganizing the handwritten information.
With the adoption of AI technologies, the system can automatically generate text based on the
telephone conversations, and intelligently identify and extract core information and
automatically fill it in the investigation form.
For example, if the person under epidemiological investigation says that he/she has taken
Shenzhen Metro Line 5, the system will automatically display all the stations along the metro
line. All the investigator needs to do is to check the boxes of relevant stations the person
mentioned, and the information will be automatically filled in the investigation form.
After the conversation is over, the system will, based on a standard template, automatically
export a table about the investigated person’s core information, a list of the key places he/she
has been to, his/her close and indirect contacts and a preliminary epidemiological
investigation report, buying more time for the follow-up management of key places and
groups of people involved.
The digitalized information collection process has greatly improved the efficiency of
epidemiological investigation.
The digital system includes a webwork platform on the PC terminal and a mobile app. After
epidemiological investigators identify the places and people that have been exposed to
infection through phone calls, on-site responses will immediately be set in motion.
On-site epidemiological investigators, who can track their tasks in real-time via the mobile
app of the digital system, arrive at relevant places immediately for confirmation of the places’
risks, hygiene and people investigation, close contact screening, etc.
At the same time, the sampling team comes to collect samples at these places to see whether
the virus exists on human bodies, objects, and the environment after receiving their
assignments at the mobile app, while the terminal disinfection team completes its disinfection
tasks in every relevant link in a timely manner according to the location and time designated
by the system.
Through multi-party collaboration on-site and real-time cooperation between investigators
working on the PC and mobile terminals, the system guarantees a prompt response to the
epidemic.
All of the information collected on-site is uploaded and reported via the mobile app, making it
instantly available to epidemiological investigators working on the PC terminal, who can
quickly make a judgment about the situation, provide guidance and add new information.
While addressing pain points including delays in offline information transmission, low
inefficient integration of fragmented information, and errors and omissions in information
delivery, the system provides a smooth information-based workflow for epidemiological
investigation and makes possible broader, deeper, faster and closed-loop investigation work.
