NATIONAL LABORATORY FOR HEALTH SECURITY, HUNGARY
The vision of the National Laboratory is to provide the scientific basis for data and analysis-based decision making in the fields of health, disease control and ecosystems in Hungary. The three areas are closely intertwined and new synergies will be created through surveillance, big data methods and modelling.
NEWS
A sensational Hungarian epidemic model has been created that could answer many of our questions
A new kind of data-driven epidemic model has been developed by Hungarian mathematicians to help better understand the impact of epidemics on society. While previous models have mainly considered the impact of age groups, the coronavirus epidemic has shown that, in addition to age, people's socio-economic status is a major determinant of transmission.
"Not as spectacular as a covid epidemic, but a huge problem" - the number of invasive species is growing rapidly
Nutria, harlequin ladybirds, red swamp crabs, tiger mosquitoes, or Spanish slugs - we increasingly encounter species that are not native to our country, and their presence is usually not good news for local ecosystems, but can often cause headaches in agriculture or even in health care. Can we live with species that are still considered invasive today?
New study on the presence of invasive species in areas of habitat restoration in Kiskunság
The loss of biodiversity on our planet is partly due to the presence and spread of alien invasive species. Once an invasive species has established in a new habitat, it can alter the structure and function of the ecosystem to such an extent that it has an impact even after removal, making it very difficult to control and eradicate. Ecological restoration, when carried out in an effective and sustainable way, contributes to biodiversity conservation and climate change
Divisions
Division of Mathematical Epidemiology
Our work integrates the competences of various disciplines through the application of mathematical methods for modelling infectious diseases: mathematics, epidemiology, biostatistics, data science, network science, medicine, systems biology, control theory, computer science, quantitative social sciences. We support preparedness, strategic planning, rapid response, and evidence informed decision making in health emergency through innovative surveillance systems and data guided analysis.
The goal the Division of Invasion Biology is to provide a coherent approach across disciplines to tackle the challenges of invasive species. With a particular focus on species that play a key nature conservation, economic or societal role, it will
i) document and continuously monitor invasion,
ii) understand the mechanisms behind invasion,
iii-iv) explore the ecological, social and economic impacts of invasion,
v) predict invasion processes, and
vi) test and develop methods for control of invasive species.
Division of Data-Driven Health
The Data-Driven Health Division is the domestic methodological hub for the globally trending shift to a data-driven healthcare paradigm.
Our primary objective is to promote the development of data-driven healthcare and artificial intelligence solutions in Hungary, with the driving force being our unique nationwide database integration solution on a global scale. Within our division, we focus on the development of artificial intelligence development, data mining frameworks, and on the establishment of decision support information systems. The collaborative social innovation work is implemented in partnership with Rényi Mathematical Research Institute and Neumann Not-for-profit Ltd.
Centre for Eco-Epidemiology
Our research aims to prevent infectious diseases emerging due to climate change and urbanization. We use the DAMA (Document, Assess, Monitor, Act) protocol to map the occurrence and risks of zoonotic pathogens spread by ticks in Hungary, and help prevent them. Our work ranges from ecological field activities to molecular biological technologies to sophisticated bioinformatics and epidemiological methods, but we also involve voluntary citizen science participants.
CONSORTIUM MEMBERS
