Assistant Professor (fulltime) In Modelling space-time dynamics of health risks using...

Sixty percent of all human infectious diseases are transmitted from animals, and microbes of animal origin cause 75% of emerging infectious diseases. These microbes 'spill over' due to increasing contact among wildlife, livestock, and people driven by exponentially growing anthropogenic changes caused by human activities and the impacts of these activities on the environment. Over the past ten years, several outbreaks and pandemics occurred with varying duration and intensity. Between 2012 and 2017, the World Health Organisation (WHO) recorded more than 1,200 outbreaks in 168 countries, with a further 352 infectious disease events in 2018. Some of these have been localized, while others have spread globally in a short period. The risk of pandemics is increasing rapidly, with more than five new diseases emerging in people every year, any one of which has the potential to spread and become pandemic. The advances in genomic sequencing and the increasing availability of these data make it more feasible to map disease distribution and changing risks. We are looking for a motivated colleague interested in the combination of Spatial science and health to complement our existing strengths in geohealth.

The circulation and evolution of diseases are driven by a range of factors (environmental factors, host-related factors and the pathogen itself) and how they interact in space and time. By developing models and analytical techniques to combine genetic information of diseases with geographic information we can detect where diseases are prevalent, and where sources of disease infections are located. By developing spatial-temporal models these changes we can assess how diseases are circulating, where changes are taking place and how diseases may be diffusing and evolving. Furthermore, by integrating different geographies we can explore what may be driving patterns of disease and changes in these patterns and the pathogen.

You will use a variety of statistical, machine learning and geo visualization and spatial analysis methods to map and model diseases over space and time. This may also require the development of new geo computational methods to integrate different types of data, visualize outputs and determine changes in risk over time.

Outputs will be useful for providing policy-relevant knowledge, designing interventions and fine-tuning disease and outbreak response plans.

You will:

• Establish a research line on geophylogenetics with a focus on understanding the source of infection, mobility, connectivity between geographic locations and the circulation and changes in diseases and what this means for monitoring and managing health risks both now and in the future.
• Develop spatial-temporal statistical and machine learning models to determine risk factors, and model changes in risk over time.
• Identify relevant research and capacity building opportunities related to the use of geospatial information in monitoring and managing health risks.
• Based on the identified opportunities, pursue and attract funding that builds on ITC's geospatial expertise and intersects with health.
• Contribute to the definition and development of geohealth data, and services that may be published in a geoportal or contribute to existing geoportals (e.g. nextstrain).
• Publish results in scientific journals, where you embrace Open Science and principles of FAIR data, and focus on creating impact beyond the pure academic process.
• Actively contribute to the development of educational materials and teach classes in face-to-face and online education.
• Actively work towards strengthening our national network as this position is part of furthering the national earth and environmental sciences domain.