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Selected Publication:

Publication type: Diploma Thesis

Year: 2015

Author(s): Campei, Maria Lena

Title: Habitatmodelle zur geographischen Verbreitung von Infektionskrankheiten.

Other title: Habitat models for the geographical distribution of infectious diseases

Source: Diplomarbeit, Vet. Med. Univ. Wien, pp. 66.


Brugger Katharina
Rubel Franz

Vetmed Research Units:
Unit of Veterinary Public Health and Epidemiology

Graduation date: 18.03.16

Habitat models are increasingly used not only for modeling the spread of disease vectors and hosts, but also of complex disease transmission systems in terms of a black box. In this thesis an overview of habitat models for geographical spread of infectious diseases by means of a literature research is given. Thereby 137 studies were selected, dealing with 51 different pathogens. These studies include a total of 174 habitat models developed with nine different model algorithms. Machine learning methods were most frequently applied (76%), the second most used approaches were regression models (21%) and profile methods and BIOMOD account for the remaining 3%. The Maxent algorithmus was the most common application out of the machine learning methods (39% of all models). Over the years, the proportion of machine learning methods has increased markedly compared to regression models. The most models were created for zoonotic pathogens (total of 123), for human pathogens there are 16 models and for veterinary pathogens 35 models. With a total of 20 models avian influenza viruses (Avian influenza virus, H1N1, H5N1, H7N9 virus) were the most commonly modeled pathogens. Second place is taken by Batrachochytrium dendrobatidis , a fungal disease of amphibians (17 models) and in third place by the Hantavirus (14 models). In 13 studies projections for future distribution of pathogens using climate change scenarios were examined. By far the most frequently cited paper (803 citations) describes the global spread of dengue.

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