Periodic Reporting for period 1 - EARLY-ADAPT (Signs of Early Adaptation to Climate Change)
Okres sprawozdawczy: 2021-02-01 do 2022-07-31
EARLY-ADAPT (“Signs of Early Adaptation to Climate Change”) is a European Research Council (ERC) Consolidator Grant (CoG), whose overarching aim is to jointly analyse the environmental (climate variability, air pollution, desert dust and winter infectious diseases) and socioeconomic (macroeconomy, ageing, inequality and gender gap) drivers of recent trends in public health, especially focusing on human mortality, but also on hospital admissions, occupational and road accidents and maternal and child health.
Societal Challenge
Environmental factors kill hundreds of thousands of Europeans every year. Climate change is an additional threat for public health, and adaptation an essential strategy to increase importance. Societies are devoting efforts to adaptation, but evidence of effectiveness is still lacking. A unified framework integrating disciplines is the solution to understand the ongoing societal response to climate change.
Hypothesis and Aim
The driving hypothesis of EARLY-ADAPT is that European societies are starting to adapt to climate change, but the effectiveness of early adaptation is heterogeneous between populations and through time. The project will allow us to detect, understand and quantify the drivers and inequalities of human adaptation between countries, regions, cities and social groups.
Methodological Approach
EARLY-ADAPT will integrate multiple health outcomes and environmental and socioeconomic factors to perform a numerically-intensive, epidemiological analysis between daily spatiotemporal datasets. The project will use different layers of data, and multiscale local regression techniques, to analyse the scales and spatiotemporal heterogeneity of the drivers of early adaptation.
Research Plan
After creating a homogeneous, continental-wide database of human health in Europe (WP1), EARLY-ADAPT will model the relationship between health and the environment, and then quantify the modifying effect of the societal factors (WP2). Finally, the project will perform a predictability analysis to determine the most realistic adaptation scenarios for the projections of future health (WP3).
Impact in Science
The continental-wide, multi-factor, multi-scale framework of EARLY-ADAPT will connect a range of disciplines to reveal the drivers, and the inequalities, of the early adaptation response to climate change. But beyond that, the project will create knowledge by developing a novel, integrated method for environmental health in Europe, which will stimulate new research ideas in a range of disciplines.
Societal Challenge
Environmental factors kill hundreds of thousands of Europeans every year. Climate change is an additional threat for public health, and adaptation an essential strategy to increase importance. Societies are devoting efforts to adaptation, but evidence of effectiveness is still lacking. A unified framework integrating disciplines is the solution to understand the ongoing societal response to climate change.
Hypothesis and Aim
The driving hypothesis of EARLY-ADAPT is that European societies are starting to adapt to climate change, but the effectiveness of early adaptation is heterogeneous between populations and through time. The project will allow us to detect, understand and quantify the drivers and inequalities of human adaptation between countries, regions, cities and social groups.
Methodological Approach
EARLY-ADAPT will integrate multiple health outcomes and environmental and socioeconomic factors to perform a numerically-intensive, epidemiological analysis between daily spatiotemporal datasets. The project will use different layers of data, and multiscale local regression techniques, to analyse the scales and spatiotemporal heterogeneity of the drivers of early adaptation.
Research Plan
After creating a homogeneous, continental-wide database of human health in Europe (WP1), EARLY-ADAPT will model the relationship between health and the environment, and then quantify the modifying effect of the societal factors (WP2). Finally, the project will perform a predictability analysis to determine the most realistic adaptation scenarios for the projections of future health (WP3).
Impact in Science
The continental-wide, multi-factor, multi-scale framework of EARLY-ADAPT will connect a range of disciplines to reveal the drivers, and the inequalities, of the early adaptation response to climate change. But beyond that, the project will create knowledge by developing a novel, integrated method for environmental health in Europe, which will stimulate new research ideas in a range of disciplines.
During the first 18 months of the project, the ISGlobal team performed the following tasks:
* We hired 5 people from different disciplines, from climate and environmental sciences to epidemiology and social sciences. We also hired a software engineer, two data technicians and a part-time project manager.
* We created the project website, https://early-adapt.eu/ where we disseminate and communicate our research and outreach activities.
* We obtained 93 health datasets from various national agencies for statistics. 82 of the datasets are from European countries, and the remaining 11 are from non-European countries.
* We interacted with the agencies providing the health datasets to understand the legal terms of the collected data, and with the legal department of the host institution to prepare and sign the data transfer agreements. Also, we implemented additional data access protocols to protect the data collected.
* We collected and pre-processed environmental data (satellite, reanalysis and ground-level data) to estimate the exposures, including climate variables and air pollution concentrations.
* We formatted the design and created the initial database of human health variables, together with climate, air pollution, socioeconomic and demographic data.
* We designed and implemented harmonisation protocols for a successful integration of the health and environmental data. These protocols take into account the heterogeneity of the data formats (e.g. grids and variables) and any expected update of the initial database.
* We designed protocols and generated subroutines to automatically integrate and post-process new datasets or any eventual change in the format of the existing ones.
* We used epidemiological models to estimate the risk associations between exposures and health variables at continental, regional and local scales.
* We developed predictive models to evaluate the predictability of weather forecasting-driven heat-health early warning systems.
* We published 13 scientific papers.
* We disseminated the results obtained so far in scientific conferences, workshops and the media.
* We hired 5 people from different disciplines, from climate and environmental sciences to epidemiology and social sciences. We also hired a software engineer, two data technicians and a part-time project manager.
* We created the project website, https://early-adapt.eu/ where we disseminate and communicate our research and outreach activities.
* We obtained 93 health datasets from various national agencies for statistics. 82 of the datasets are from European countries, and the remaining 11 are from non-European countries.
* We interacted with the agencies providing the health datasets to understand the legal terms of the collected data, and with the legal department of the host institution to prepare and sign the data transfer agreements. Also, we implemented additional data access protocols to protect the data collected.
* We collected and pre-processed environmental data (satellite, reanalysis and ground-level data) to estimate the exposures, including climate variables and air pollution concentrations.
* We formatted the design and created the initial database of human health variables, together with climate, air pollution, socioeconomic and demographic data.
* We designed and implemented harmonisation protocols for a successful integration of the health and environmental data. These protocols take into account the heterogeneity of the data formats (e.g. grids and variables) and any expected update of the initial database.
* We designed protocols and generated subroutines to automatically integrate and post-process new datasets or any eventual change in the format of the existing ones.
* We used epidemiological models to estimate the risk associations between exposures and health variables at continental, regional and local scales.
* We developed predictive models to evaluate the predictability of weather forecasting-driven heat-health early warning systems.
* We published 13 scientific papers.
* We disseminated the results obtained so far in scientific conferences, workshops and the media.
The ambition of EARLY-ADAPT is to explore the major determinants of human mortality across a range of relevant scales and disciplines, including several environmental, socioeconomic and demographic factors. Human vulnerability, for example, depends on air quality, the expansion-recession cycles, a myriad of microscale socioeconomic factors, the ageing of European societies, the gender gap or the seasonal incidence and spread of infectious diseases, among many others. Moreover, all these factors are relevant at preferential levels, e.g. atmospheric pollution is more important at the local scale, near the sources of the pollutants, while the impact of economic recessions is better seen at the national or regional levels. State-of-the-art projects analyse, at most, one single country, or ensembles of cities with no spatially detailed information at the neighbourhood level, and they hardly integrate data from different disciplines.
The main innovation of the project during the first 18 months has been the creation of an unprecedented pan-European, multi-scale, multi-factor database. Data scarcity, fragmentation and format heterogeneity are major limiting factors for the study of human mortality, vulnerability and adaptation in Europe. The National Morbidity, Mortality, and Air Pollution Study (NMMAPS) contains basic sociodemographic data and daily high-quality mortality, climate and air pollution values by cause of death and age in over 100 major cities in the United States. This database, with a unified data format and collection process, represents an excellent tool for health assessment, but unfortunately no equivalent continental database exists for Europe. Some outstanding ongoing initiatives are currently coordinating, albeit not unifying, existing datasets, such as the Multi-City Multi-Country Collaborative Research Network (https://mccstudy.lshtm.ac.uk/). Despite the extraordinary value of this initiative, sources are largely heterogeneous in space (mostly subsets of cities) and time (partially overlapping periods), with little information by age, sex and cause of death, and only including data for a subset of European countries. Other previous outstanding initiatives, such as the PHEWE, EUROHEAT and CIRCE projects, explored the effects of air pollutants and meteorological variables on mortality, but analyses were restricted to a limited number of representative cities. Here, we have generated the most complete database of human health available to date in Europe, with a unique multidisciplinary structure specially designed for the objectives of EARLY-ADAPT. It provides updated long-term daily counts of death and other health outcomes for different subdomains and spatial resolutions, including data for countries, regions, cities and neighbourhoods, together with the best available climate, air pollution, influenza, socioeconomic and demographic datasets.
Our work during the first 18 months of the project has focused on the creation of the database, and less time has been devoted to research. In the upcoming months, we will put the emphasis on beyond state-of-the-art scientific questions by modelling the relationship between human mortality and all these major determinants, with particular focus on the most vulnerable population groups. This is going to require an integrated analysis through spatial scales, which compares, at each layer, and between layers, the extent to which populations are reducing their vulnerability.
The main innovation of the project during the first 18 months has been the creation of an unprecedented pan-European, multi-scale, multi-factor database. Data scarcity, fragmentation and format heterogeneity are major limiting factors for the study of human mortality, vulnerability and adaptation in Europe. The National Morbidity, Mortality, and Air Pollution Study (NMMAPS) contains basic sociodemographic data and daily high-quality mortality, climate and air pollution values by cause of death and age in over 100 major cities in the United States. This database, with a unified data format and collection process, represents an excellent tool for health assessment, but unfortunately no equivalent continental database exists for Europe. Some outstanding ongoing initiatives are currently coordinating, albeit not unifying, existing datasets, such as the Multi-City Multi-Country Collaborative Research Network (https://mccstudy.lshtm.ac.uk/). Despite the extraordinary value of this initiative, sources are largely heterogeneous in space (mostly subsets of cities) and time (partially overlapping periods), with little information by age, sex and cause of death, and only including data for a subset of European countries. Other previous outstanding initiatives, such as the PHEWE, EUROHEAT and CIRCE projects, explored the effects of air pollutants and meteorological variables on mortality, but analyses were restricted to a limited number of representative cities. Here, we have generated the most complete database of human health available to date in Europe, with a unique multidisciplinary structure specially designed for the objectives of EARLY-ADAPT. It provides updated long-term daily counts of death and other health outcomes for different subdomains and spatial resolutions, including data for countries, regions, cities and neighbourhoods, together with the best available climate, air pollution, influenza, socioeconomic and demographic datasets.
Our work during the first 18 months of the project has focused on the creation of the database, and less time has been devoted to research. In the upcoming months, we will put the emphasis on beyond state-of-the-art scientific questions by modelling the relationship between human mortality and all these major determinants, with particular focus on the most vulnerable population groups. This is going to require an integrated analysis through spatial scales, which compares, at each layer, and between layers, the extent to which populations are reducing their vulnerability.