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.


Should we be afraid of feline and canine coronavirus?

A macska- (Feline coronavirus, FCoV) és kutya- (Canine coronavirus, CCoV) koronavírusok, ahogy nevük is mutatja, elsősorban macskákban és kutyákban okoznak fertőzéseket, nyilatkozta a Qubitnek Szentiványi Tamara, a HUN-REN Ökológiai Kutatóközpont Ökológiai és Botanikai Intézetének tudományos munkatársa, az Egészségbiztonság Nemzeti Laboratórium Invázióbiológiai Divíziójának kutatója. Tovább (Kép: Jewel Samad/AFP)

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.

Agrártudományi Kutatóközpont
Centre for Agricultural Research
Állatorvostudományi Egyetem
University of Veterinary Medicine Budapest
Álllatorvostudományi Kutatóintézet
Veterinary Medical Research Institute
Eötvös Loránd Tudományegyetem
Eötvös Loránd University
Magyar Agrár- és Élettudományi Egyetem
Hungarian University of Agriculture and Life Sciences
Neumann János Nonprofit Közhasznú Korlátolt Felelősségű Társaság
Neumann Nonprofit Ltd.
Óbudai Egyetem
Óbuda University
Ökológiai Kutatóközpont
Centre for Ecological Research
Pázmány Péter Katolikus Egyetem
Pázmány Péter Catholic University
Pécsi Tudományegyetem
University of Pécs
Rényi Alfréd Matematikai Kutatóintézet
Alfréd Rényi Institute of Mathematics
Semmelweis Egyetem
Semmelweis University
Számítástechnikai és Automatizálási Kutatóintézet
Institute for Computer Science and Control
Szegedi Biológiai Kutatóközpont
Biological Research Centre, Szeged
Szegedi Tudományegyetem
University of Szeged
Társadalomtudományi Kutatóközpont
Centre for Social Sciences