Jonas Brock

Research

I am a PhD Student within the Ecological Epidemiology project group at Helmholtz Center for Environmental Research. In the framework of my dissertation I am developing a stochastic individual-based simulation model to study the dynamics of the spread of Infectious Bovine Rhinotracheitis (IBR) within cattle populations in Ireland. IBR is a highly contagious, infectious respiratory disease that is caused by Bovine Herpesvirus-1 (BHV-1). The disease is reflected in several clinical signs and can lead to long-term ill-health and even death. While many countries in the EU have successfully eradicated BHV-1, Ireland is still making efforts to eradicate the virus, thereby suffering from severe economic losses. In my research I aim to give decision-makers valuable insights into the risk and economic consequences of IBR and to assess the effectiveness of various control strategies (e.g. vaccination campaigns). My research project is greatly supported and funded by Animal Health Ireland (AHI), a world-class non-for-profit organization that provides knowledge and coordination to establish effective control programmes for non-regulated diseases of livestock.

My research interests are:
- quantitative epidemiology
- epidemiological modeling
- data science challenges
- machine-learning techniques
- algorithm automation

Publications

 

• Brock, J., Lange, M., Guelbenzu-Gonzalo, M., Meunier, N., Vaz, A.M., Tratalos, J.A., Dittrich, P., Gunn, M., More, S.J., Graham, D., Thulke, H.-H., (2020):
  Epidemiology of age-dependent prevalence of Bovine Herpes Virus Type 1 (BoHV-1) in dairy herds with and without vaccination
  Vet. Res. 51 , art. 124
  full text (doi)
• Brock, J., Lange, M., More, S.J., Graham, D., Thulke, H.-H., (2020):
  Reviewing age-structured epidemiological models of cattle diseases tailored to support management decisions: Guidance for the future
  Prev. Vet. Med. 174 , art. 104814
  full text (doi)
• Brock, J., Schratz, P., Petschko, H., Muenchow, J., Micu, M., Brenning, A., (2020):
  The performance of landslide susceptibility models critically depends on the quality of digital elevations models
  Geomat. Nat. Hazards Risk 11 (1), 1075 - 1092
  full text (doi)
• Muenchow, J., Dieker, P., Böttcher, T., Brock, J., Didenko, G., Fremout, T., Jakubka, D., Jentsch, A., Nüst, D., Richter, M., Rodríguez, E.F., Rodríguez, R.A., Rollenbeck, R., Zarsosa, P.S., Schratz, P., Brenning, A., (2020):
  Monitoring and predictive mapping of floristic biodiversity along a climatic gradient in ENSO's terrestrial core region, NW Peru
  Ecography
  full text (doi)

CV

Apr. 2018 - current	PhD student at Helmholtz Centre for Environmental Research
Apr. 2018 - current	Scientific associate at Animal Health Ireland
Oct. 2015 - Mar. 2018	M.Sc. in Geoinformatics at Friedrich Schiller University Thesis: Assessing the effects of DEM products on statistical and machine-learning models of landslide susceptibility
Oct. 2012 - Sep. 2015	B.Sc. in geographical Sciences Thesis: Fluvial morphological investigations in the upper Krom Antonies Valley, South Africa

Links