NEWS It is possible to forecast how different infectious diseases will spread across Europe in relation to global warming. This is made by using artificial intelligence and mathematical modelling of changing travel patterns and disease effects such as expected case fatalities of novel outbreaks. In this way, it will be possible to take countermeasures and build up preparedness. This is shown in a new doctoral thesis at Umeå University, Sweden.
Zia Farooq, doctoral student at the Department of Public Health and Clinical Medicine.
ImageMattias Pettersson"It will become increasingly important to predict how and where infectious diseases will spread. Several serious diseases are next in line to reach many countries in Europe as the climate changes and we also travel more. Through access to technology and data-driven forecasts, there is room to make decisions about capacity in healthcare and measures to curb the spread," says Zia Farooq, doctoral student at Umeå University.
In his thesis at the Department of Public Health and Clinical Medicine, Zia Farooq shows models that, by combining different types of data with artificial intelligence and mathematical modelling can predict the spread of infectious diseases. One example is the disease West Nile fever. The spread of this viral disease via host animals is partly driven by climate change with rising temperatures, longer springs and drier winters. If countermeasures are not taken, the risk of West Nile fever in Europe could increase up to fivefold, reaching northwestern Europe, putting 244 million people at risk.
The thesis shows that the forecast model that Zia Farooq and the research group he is part of would have been able to predict with good precision the latest and unusually large outbreak of West Nile fever in Europe in 2018. The methodology is based on applications of AI and machine learning algorithms that process disease occurrence data with climate and environmental, sociodemographic and trading data.
Another viral disease that is transmitted via mosquitoes is dengue fever. It can cause high fever, severe pain and life-threatening sequelae. Dengue fever was previously considered a tropical disease, but it is now spreading in Europe, mainly as a result of increased travelling and climate change. In his thesis, Zia Farooq shows that imports of dengue virus through infected travellers during the five-year period 2015–2019 increased by 588 percent compared to 20 years earlier. Effective imports require the presence of certain mosquito species in Europe that can carry dengue between human individuals, which is realized by increasing average temperatures in Europe. The fact that dengue fever can spread in this way means that human travel patterns are important in general for also other similar diseases, such as Zika fever, yellow fever and chikungunya.
"Of course, it is important to reduce emissions and thus limit climate change. But we may not entirely be able to escape this problem as climate change is already happening. This is why it's important to have tools to be prepared to face the challenges of climate sensitive and emergent infectious diseases," says Zia Farooq.
Zia Farooq holds a previous master's degree in applied mathematics from the Institute of Space Technology in Islamabad. He has also researched cell signalling using dynamic modelling and information theory techniques at the Polish Academy of Sciences in Warsaw. He researched epidemiological questions on Covid-19 during the pandemic. Zia is part of the Lancet Countdown Europe team that develops risk indicators for infectious diseases.
On Monday 3 June at 9.00 a.m., Zia Farooq will defend his doctoral thesis Navigating Epidemics: By leveraging data science and data-driven modelling. Principal supervisor Henrik Sjödin. Location: Room B, 9th floor, University Hospital, Umeå.
