The system provides analyses on the disease threats and countries’ response abilities at

Tran Xuan Bach, project leader, said the system was based on research results issued by an international network of experts on epidemiology and disease control as well as updated data released by reputable databases.

Global COVID-19 early warning system

Besides counting infections, deaths and recoveries, it uses artificial intelligence to analyze and evaluate threats which may lead to outbreaks in different areas of the world in accordance with characteristics of the novel coronavirus (SARS-CoV-2), collective behavior and ecological factors.

“There are many factors, such as the number of people currently confirmed in each area, the level of interaction and mobility, population density, weather, responsiveness and disease control capacity in each country,” said Bach.

Input data allows the system to quantify the risks and speed of disease transmission. For example, it forecasts that risks outside China will outnumber those from mainland China.

Bach said research results were a dependable source of information for policymakers to discuss and closely collaborate with the group to come up with the most optimal control strategies.

Head of IPMPH Le Thi Huong expressed her hopes of the system as an innovative approach to fighting COVID-19.

According to the system, new infections may appear in Vietnam in March with the cities of Da Nang, Hanoi, HCM and Nha Trang among the most vulnerable areas. The chances have been rated at 21 percent, including 13 percent caused by risks from outside China.

Bach said response plans had to be developed for different locations, paying attention to local human resources, facilities and promoting civic engagement.

The institute is encouraging people to update the site.

From 59 cases reported in China in December 2019, the number of confirmed COVID-19 cases has jumped to nearly 91,000, causing over 3,100 deaths in more than 60 countries and territories.

The global early warning system can be tracked online with a system developed by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University at and

Source: VNA