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Analysis of environmental drivers of infectious disease

Research project Environmental factors are significant drivers of infectious diseases. Land‐use patterns, such as intensive agriculture, deforestation, irrigation or road construction, and climate variability and change, are important determinants of infectious disease spread. Decision makers need predictive models of disease to underpin their strategies and decisions to prevent and control outbreaks

Merging environmental, satellite, demographic, etc data sets and integrating their data requirements would allow for the analysis of complex interactions and generate essential information that increases our understanding of these systems. Identifying long‐term projections would build the evidence base for strategic public health action while identifying short‐term events linked to environmental conditions would help improve and accelerate early warning and response capability. This tender aims to support the European Environment and Epidemiology (E3) Network with epidemiologic modeling of environmental drivers of infectious diseases.

Head of project

Joacim Rocklöv
Professor
E-mail
Email

Project overview

Project period:

2014-10-01 2016-12-31

Funding

ECDC, 2014: SEK 1,821,000

Participating departments and units at Umeå University

Department of Public Health and Clinical Medicine

Research area

Clinical medicine, Public health and health care science

Project description

Environmental factors are significant drivers of infectious diseases. Land‐use patterns, such as intensive agriculture, deforestation, irrigation or road construction, are important determinants of infectious disease spread. Urbanization and urban sprawl have encroached agricultural and semi‐natural areas in Europe, and the trend is expected to continue. One consequence is that wildlife may increasingly need to find new habitats, sometimes in urban or abandoned environments which have a bearing on exposure to infectious pathogens. Climatic conditions are also significant drivers of infectious diseases and climate change can shift the distribution of infectious diseases.

Merging environmental, satellite, demographic, etc data sets and integrating their data requirements would allow for the analysis of complex interactions and generate essential information that increases our understanding of these systems. Identifying long‐term projections would build the evidence base for strategic public health action while identifying short‐term events linked to environmental conditions would help improve and accelerate early warning and response capability. The European Centre for Disease Prevention and Control (ECDC) has recognised the need to develop an infrastructure coined the European Environment and Epidemiology (E3) Network to help monitor environmental conditions related to infectious disease threats2. The hub is designed as a data repository that would support data exchanges and sustained collaborations between member states, researchers, and other authorised users across geographical and political boundaries. Such a network would promote Europe‐wide quality standards for environmental data, leverage existing investments, and increase the use of available data sets. The E3 Network could provide technical support for the reporting, monitoring, analysis, and mapping of data and enhance the analytical capacity of existing resources in Europe. Results could then be disseminated to policy makers, public health practitioners, European Union and international agencies, other governmental sectors, and non‐governmental organisations. In recognition of the above, we acknowledge the health threat from climate change, referring to it as one of three priority areas for ensuring health security. This tender aims to support the European Environment and Epidemiology (E3) Network with epidemiologic modelling of environmental drivers of infectious diseases. The purpose is to provide mathematical models of infectious disease transmission dynamics related to climate change and alterations in habitat/ecosystems. These epidemiologic models should be used to delineate areas of risk and help with the development of early warning systems.