EnvDis: Environment and Diseases: A general method linking Mechanism and Phenomenology

         Start: October 2019

         Duration: 3 years

         Research Domain: Foodborne Zoonoses

         Members: University of Surrey- UK, PHE- UK

         Contact: Dr Giovanni Lo Iacono

The Project

Foodborne diseases remain an important cause of morbidity, mortality, and healthcare costs worldwide. For instance, in 2015 diarrhea alone caused more than 1.3 million deaths and 71·59 million DALY globally. The problem is expected to be exacerbated by population growth and the rising of resistance to antibiotics. Furthermore, anthropogenic activities are constantly changing the environment (here and throughout we refer to weather, climate, land use and also socio-economics factors as ‘environment’ or ‘environmental factors’) which is a well-recognized driver of diseases. The environment can affect pathogen abundance, survival, and virulence, host susceptibility to infection as well as human behaviour. It is thought that the accelerating rate of global climate and other environmental change will impact the distribution, frequency and patterns of established diseases as well as the emergence and re-emergence of new and old ones. As a society, it is our duty to be prepared.

Our ultimate goal is to develop a tool to assess the public health risk of foodborne zoonosis based on information of relevant environmental factors. Accordingly, we are interested in the following over-arching questions:

  • Can we identify the key environmental processes triggering and propagating foodborne zoonoses?
  • Can we disentangle the role of animal, human (including socio-economic factors) and environmental factors in foodborne zoonoses?
  • Can we identify the delay between variations in the environment (e.g. increase in the temperature or behavioural change) and the occurrence of a foodborne outbreak?
  • How can we quantify their impact on Public Health?

We will focus on Salmonella, for which the mechanism of transmission is relatively well known (e.g. effects of temperature and water activity), which will help in validating our approach.




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