A breakthrough study by a team of data scientists from Singapore has predicted that the COVID-19 global pandemic will end its life cycle by this December.
The virus has infected close to 3 million people worldwide, resulting in more than 200,000 deaths.
There is tremendous anxiety about the future of the pandemic, especially as most countries are under lockdowns that have brought the global economy to a halt.
A researcher from Singapore University of Technology and Design, Jianxi Luo, predicted in a research report on Monday, April 27, 2020, that the coronavirus (COVID-19) pandemic will likely subside by December 2020.
“The predictions were purely driven by personal curiosity regarding when COVID-19 will end in Singapore, where we live, and other countries,” Luo, who is the director of the Data-Driven Innovation Lab and the head of the research paper, said.
“Estimating the end dates have been subconscious for most people as it is mentally needed and an essential part of planning during the COVID-19 pandemic, but also naturally difficult to be done well due to the uncertainty of the future.”
He and his team created a susceptible-infected-recovered model through complex mathematical models, and using open-source codes from Milan Batista, as well as data from Our World in Data to “estimate the pandemic life cycle curves and predict when the pandemic might end in respective countries and the world.”
The study showed the virus’ life cycle for 131 countries, while others were visualized in a graph on the Data-Driven Innovation Lab webpage launched on April 18.
The data is updated daily and shows the inflection point and the final phase of the pandemic using a bell-curve graph for visualization.
China, which is where the virus first originated, and smaller nations such as Brunei and Liechtenstein are predicted to end their pandemic cycle as early as April.
The virus’ cycle is expected to fully end in countries such as Qatar and Bahrain by next February.
“The evolution of COVID-19 is not completely random,” Luo said, adding that the model-based and data-driven approach was made possible due to the existing knowledge of the historical pandemic process patterns.
He added that behavioral factors, such as individuals avoiding physical contact and government lockdowns in high-risk cities, as well as the natural limitation of the ecosystem played a part in understanding the pandemic life cycle.
“However, this could vary in countries, and different countries might be in different phases of the life cycles at a specific point in time.”
The study uses “predictive monitoring” to assess the data — the continual monitoring of predicted future events, such as the ending of the ongoing pandemic, using the latest data generated over time.
“If properly done (predictive monitoring), it may reduce anxiety and prepare us for the next phases of the epidemic evolution, irrespective of whether it’s going to improve or worsen,” he said, adding that governments and companies would be “future-informed,” and prepare for more proactive planning and decision-making.
Much of today’s data focused on the daily reporting of infections, recovery and death rate, which may lead to “reactive and passive policies and actions,” he warned.
The study has its limitations, however, due to the evolving nature of the pandemic and Luo emphasised that it was strictly for educational and research purposes.
