Evaluating the burden of climate-related respiratory disease using high resolution spatiotemporal models
Lead Research Organisation:
Imperial College London
Department Name: School of Public Health
Abstract
The average global temperature has increased by about 0.8C since 1880. Contributors to this temperature change include greenhouse gas emissions from agriculture and land, sea, and air transportation. The impact of climate change on health-in particular respiratory diseases-can be direct or indirect. Direct impact refers to an increasing number of deaths and hospitalizations due to extreme temperature events, heatwaves, while indirect impact involves promoting factors such as air pollution that are known to increase deaths or hospitalizations for respiratory disease. According to climate modelers, temperatures will continue to increase unless we implement strategies to decrease greenhouse gas and other pollutant emissions. The aim of this project is to develop comprehensive statistical models and quantify the effect of extreme temperatures with respect to respiratory health. To do this, I will first use nationwide data in the UK and also focus on the four most populous cities which, due to high buildings, overcrowding, and poor air quality are known to experience higher temperatures than neighboring rural areas. Using different emissions scenarios, I will predict future respiratory hospitalization due to climate change, and also quantify corresponding costs. I will also examine how increasing the land area of green spaces in cities, for example by planting trees, can help decrease future respiratory deaths and hospitalizations. Finally, I will make my results publicly available by creating a website with maps of future respiratory hospitalization and related costs due to climate change. The proposed research will take place at MRC Centre for Environment and Health under the supervision of Prof Blangiardo. This international interdisciplinary project includes a health economist (Prof Baio), statisticians (Prof Schuhmacher, Dr Gasparrini, and Dr Bhatt), epidemiologists (Dr Vicedo-Cabrera and Dr Minelli) and a climate change modeller (Dr Ballester). This work will be one of the first such projects to provide an integrated framework to quantify the health effects and costs of temperature changes in the UK on a nationwide level at a small-area scale. I will pay particular attention to communicating the results among public health experts and the general public via a website. This methodology will be transferable to other drivers of disease affected by climate change such as infectious diseases in more vulnerable areas such as developing countries.
Technical Summary
The Earth's climate is changing and temperature levels across the globe are rising as anthropogenic factors including greenhouse gas (GHG) emissions from transportation, power generation and other uses of fossil fuels warm the planet. Changes in temperature could aggravate respiratory diseases directly or by exacerbating the effects of factors such as ozone that are associated with these diseases. Recent projections of future GHG emissions predict a mean temperature increase between 1.1 and 6.4C by the end of the 21st century. Most previous studies have focused on mortality using aggregated data. They employed time series models using temperature projections at low geographical resolution, ignoring local temperature fluctuations such as the effect of urban heat islands in which urban areas are warmer than their surroundings. In addition, the health impact and costs of climate-sensitive diseases have received hardly any attention so far. The aim of this project is to develop a framework of analysis based on high-resolution Bayesian spatiotemporal models and economics to estimate the climate-related respiratory disease burden. In particular, I will use nationwide respiratory health data and daily spatially-resolved temperature to estimate the effect of extreme temperatures on respiratory health in the UK. I will also quantify the future burden of temperature-related respiratory health using Bayesian evidence synthesis methods, while propagating the different sources of uncertainty, such as future GHG emission scenarios. Lastly, I will develop a web application to communicate the resulting maps and costs to public health experts and stakeholders. The impact of the project is manifold: it provides a better understanding of the climate-related respiratory disease burden, proposes a methodology that can be extended to other drivers of global disease and pays particular attention to disseminating the results through user-friendly web-applications.
Planned Impact
The rapid increase in the availability of high spatiotemporal resolution temperature projections and simultaneous advances in computational power both offer opportunities and pose challenges to epidemiological research in relation to climate change. Often overlooking the spatial dimension, most epidemiological studies have focused on the temporal component. The work I am proposing will provide a toolbox to explore both temporal and spatial dimensions of health risk in relation to climate change. Within this framework, investigators can derive maps of future risk projections which provide insights on the potential drivers of vulnerability. The proposed methodology, coupled with economic evaluations, will provide a comprehensive framework for estimating the financial and public health burden of climate-related diseases. This project will also be one of the first to provide nationwide estimates and maps of future temperature-related respiratory health impacts in the UK.
This work is a collaboration among the MRC Centre for Environment and Health, the National Health & Lung Institute, the MRC Centre for Global Infectious Disease Analysis, University College London (UCL), and the London School of Hygiene and Tropical Medicine, as well as involve ISGlobal in Barcelona and the Institute of Social and Preventive Medicine in Bern. The overall aim of the project-understanding spatiotemporal trends of respiratory health in relation to environmental exposures, and in particular climate change-is well suited to the multidisciplinary MRC Centre for Environment and Health. Its links with King's College London and Public Health England offer a unique opportunity to collaborate with public health scientists and translate the results into future adaptation strategies. The project also focuses on health economics, a research priority of Imperial College London, and it pays particular attention to communicating results either through peer-reviewed publications and scientific conferences or through Shiny apps of the statistical software R. All work will be also publicly available through either open access publishers or pre-prints. Finally, I will disseminate the methodological framework through online tutorials, courses, and R-code.
The applications of this framework go beyond temperature-related respiratory health. The framework can be extended to other drivers of global disease burdens such as vector-borne infections, HIV, neglected tropical diseases, and emerging infectious diseases in regions that are more vulnerable to climate change or extreme events such as wildfires and droughts.
This work is a collaboration among the MRC Centre for Environment and Health, the National Health & Lung Institute, the MRC Centre for Global Infectious Disease Analysis, University College London (UCL), and the London School of Hygiene and Tropical Medicine, as well as involve ISGlobal in Barcelona and the Institute of Social and Preventive Medicine in Bern. The overall aim of the project-understanding spatiotemporal trends of respiratory health in relation to environmental exposures, and in particular climate change-is well suited to the multidisciplinary MRC Centre for Environment and Health. Its links with King's College London and Public Health England offer a unique opportunity to collaborate with public health scientists and translate the results into future adaptation strategies. The project also focuses on health economics, a research priority of Imperial College London, and it pays particular attention to communicating results either through peer-reviewed publications and scientific conferences or through Shiny apps of the statistical software R. All work will be also publicly available through either open access publishers or pre-prints. Finally, I will disseminate the methodological framework through online tutorials, courses, and R-code.
The applications of this framework go beyond temperature-related respiratory health. The framework can be extended to other drivers of global disease burdens such as vector-borne infections, HIV, neglected tropical diseases, and emerging infectious diseases in regions that are more vulnerable to climate change or extreme events such as wildfires and droughts.
Organisations
People |
ORCID iD |
Garyfallos Konstantinoudis (Principal Investigator / Fellow) |
Publications
Bucyibaruta G
(2022)
Community-level characteristics of COVID-19 vaccine hesitancy in England: A nationwide cross-sectional study.
in European journal of epidemiology
Chasapis CT
(2020)
Protein isoelectric point distribution in the interactomes across the domains of life.
in Biophysical chemistry
Folly CL
(2021)
Bayesian spatial modelling of terrestrial radiation in Switzerland.
in Journal of environmental radioactivity
Heydari S
(2021)
Effect of the COVID-19 pandemic on bike-sharing demand and hire time: Evidence from Santander Cycles in London.
in PloS one
Konstantinoudis G
(2022)
A framework for estimating and visualising excess mortality during the COVID-19 pandemic
Konstantinoudis G
(2022)
Ambient heat exposure and COPD hospitalisations in England: a nationwide case-crossover study during 2007-2018.
in Thorax
Konstantinoudis G
(2022)
Regional excess mortality during the 2020 COVID-19 pandemic in five European countries.
in Nature communications
Konstantinoudis G
(2020)
Bayesian spatial modelling of childhood cancer incidence in Switzerland using exact point data: a nationwide study during 1985-2015.
in International journal of health geographics
Konstantinoudis G
(2021)
Long-term exposure to air-pollution and COVID-19 mortality in England: A hierarchical spatial analysis.
in Environment international
Description | Estimating the heat-related burden of diabetes and health co-benefits of climate policy. |
Amount | £250,000 (GBP) |
Organisation | Imperial College London |
Sector | Academic/University |
Country | United Kingdom |
Start | 09/2023 |
End | 10/2027 |
Description | Evaluating the burden of climate-related respiratory diseaseusing high resolution spatiotemporal models. (funded extension) |
Amount | £24,326 (GBP) |
Organisation | United Kingdom Research and Innovation |
Sector | Public |
Country | United Kingdom |
Start | 09/2022 |
End | 03/2023 |
Description | IJERPH 2021 Travel Awards |
Amount | SFr. 500 (CHF) |
Organisation | MDPI |
Sector | Private |
Country | Switzerland |
Start | 07/2021 |
End | 08/2021 |
Title | Bayesian spatiotemporal model for COVID19 and air-pollution |
Description | I developed a Bayesian spatiotemporal model to evaluate the effect of long-term air-pollution exposure (NO2 and PM2.5) on COVID-19 mortality. The toolbox uses the coarse geographical resolution of the residential addresses of COVID-19 deaths, and after using information about age, sex and ethnicity, provides a much more precise representation of the geography of COVID-19 deaths. After this it fits a model to evaluate the effect of air-pollution, while propagating the uncertainty yielded from the above-mentioned procedure. The model is online available here (https://github.com/gkonstantinoudis/COVID19AirpollutionEn). |
Type Of Material | Computer model/algorithm |
Year Produced | 2020 |
Provided To Others? | Yes |
Impact | The methodology and the results received considerable attention, as were one of the first suggesting lack of evidence of an association between long term airpollution exposure and COVID-19 mortality, including vivid discussions across different researchers. An example include the commentary by Goldberg and Villeneuve (https://doi.org/10.1016/j.envint.2021.106422) and our response (https://doi.org/10.1016/j.envint.2021.106427) in Environmental International. |
URL | https://github.com/gkonstantinoudis/COVID19AirpollutionEn |
Title | Bayesian spatiotemporal model for cervical cancers |
Description | I developed a spatiotemporal model to assess the spatial and temporal trends of cervical cancer among HIV positive women during 2004-2014 on South Africa. The toolbox examines also the effect of deprivation and identifies health inequalities due to limited resources and access to health facilities. The toolbox together with the data for the analysis are available here (https://github.com/gkonstantinoudis/CervixHIVRSA) |
Type Of Material | Computer model/algorithm |
Year Produced | 2020 |
Provided To Others? | Yes |
Impact | The results were communicated to the national cancer registry in South Africa and they are discussing increasing the number of health facilities in municipalities with limitted access to health. |
URL | https://github.com/gkonstantinoudis/CervixHIVRSA |
Title | Calculate COVID-19 mortality |
Description | This is a model we developed for the following publication: https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003189. The model uses online available data on Hubei and some EU countries and estimates COVID-19 mortality in the early stages of the epidemic. |
Type Of Material | Computer model/algorithm |
Year Produced | 2020 |
Provided To Others? | Yes |
Impact | The model can be found here: https://github.com/jriou/covid_adjusted_cfr. As described in a different section, this model provides robust estimates that were used from CDC to inform public health policies regarding COVID-19. |
URL | https://github.com/jriou/covid_adjusted_cfr |
Title | Online NIMBLE tutorials |
Description | I have provided a set of tutorials to show how to fit spatial and spatiotemporal models with NIMBLE. NIMBLE is a recent open access software for Bayesian inference. I have also provided a set of tutorials on spatiotemporal models with integrated nested laplace approximation (INLA) for quick Bayesian inference. |
Type Of Material | Computer model/algorithm |
Year Produced | 2020 |
Provided To Others? | Yes |
Impact | I have received several email from different researchers with questions and modification of my original code. I am aware of one publication that will be submitted shortly that based the analysis on the code I provided online. |
URL | https://gkonstantinoudis.github.io/teaching/ |
Title | Regional excess mortality during the 2020 COVID-19 pandemic in five European countries |
Description | In this work I proposed a method for estimating and visualising excess mortality during the COVID-19 pandemic using subregonal level data in 5 European countries. |
Type Of Material | Computer model/algorithm |
Year Produced | 2022 |
Provided To Others? | Yes |
Impact | N/A |
URL | https://www.nature.com/articles/s41467-022-28157-3 |
Title | Terrestrial radiation map in Switzerland |
Description | Together with collaborators in Switzerland, we have developed a Bayesian spatial model to evaluate terrestrial radiation levels in Switzerland. The model together with the data are online available (https://github.com/FollyCh/TerrMapCH). |
Type Of Material | Computer model/algorithm |
Year Produced | 2020 |
Provided To Others? | Yes |
Impact | The terrestrial radiation maps are currently used to examine the effect of terrestrial radiation on childhood cancer incidence in Switzerland. This is work in progress. |
URL | https://github.com/FollyCh/TerrMapCH |
Description | Childhood cancers and environmental factors in Switzerland |
Organisation | University of Basel |
Country | Switzerland |
Sector | Academic/University |
PI Contribution | This project is a continuation of my postdoc in Switzerland, where I supervised Christophe Folly and Antonella Mazzei during their PhD. During this collaboration, I supervised remotely the PhD students together with Dr Ben Spycher. My main contributions on this project were: 1. Develop a statistical methodology that uses precise geolocations to create continuous terrestrial radiation maps in Switzerland. The methodology falls in the Bayesian framework that I currently use for modelling the climate-related respiratory disease burden. 2. Develop an algorithm to calculate the residential proximity of childhood cancer cases to petrol stations. In both project I worked closely with the PhD students, had monthly meetings and helped writing both papers. 3. Run part of the analysis on a project identifying association of certian birth characteristics with childhood leukaemia. |
Collaborator Contribution | Christophe Folly, Antonella Mazzei and Dr Judith Lupatsch were the first authors of these 3 papers. They cleaned the data, ran (most of) the analysis and wrote the first draft of the paper. Dr Ben Spycher was the principal investigator of the project and provided the financial resources for this study. The collaboration was multidisciplinary and the role of the clinicians (Prof Claudia Kuehni, University of Bern, Prof Marc Ansari, University hospital of Geneva) essential to interpret the results and communicate findings with other paediatric oncologists (through the annual Swiss Paediatric Oncology Group conference). |
Impact | - Papers: Folly CL, Konstantinoudis G, Mazzei-Abba A, Kreis C, Bucher B, Furrer R, Spycher BD. Bayesian spatial modelling of terrestrial radiation in Switzerland. arXiv preprint arXiv:2010.00534. 2020 Oct 1.(accepted Journal of Environmental Radioactivity) Lupatsch JE, Kreis C, Konstantinoudis G, Ansari M, Kuehni C, Spycher B. Birth characteristics and childhood leukemia in Switzerland: a register-based case-control study. Submitted to Cancer Causes and Control 2020. Mazzei A, Konstantinoudis G, Kreis C, Diezi M, Ammann R, Zwahlen M, Kuehni C, Spycher B. Childhood cancer and residential proximity to petrol stations: a nationwide registry-based case-control study in Switzerland. Submitted to Occupational and Environmental Medicine. - Bayesian model to calculate terrestrial radiation in Switzerland: https://github.com/FollyCh/TerrMapCH |
Start Year | 2019 |
Description | Childhood cancers and environmental factors in Switzerland |
Organisation | University of Bern |
Department | Institute of Social and Preventive Medicine |
Country | Switzerland |
Sector | Academic/University |
PI Contribution | This project is a continuation of my postdoc in Switzerland, where I supervised Christophe Folly and Antonella Mazzei during their PhD. During this collaboration, I supervised remotely the PhD students together with Dr Ben Spycher. My main contributions on this project were: 1. Develop a statistical methodology that uses precise geolocations to create continuous terrestrial radiation maps in Switzerland. The methodology falls in the Bayesian framework that I currently use for modelling the climate-related respiratory disease burden. 2. Develop an algorithm to calculate the residential proximity of childhood cancer cases to petrol stations. In both project I worked closely with the PhD students, had monthly meetings and helped writing both papers. 3. Run part of the analysis on a project identifying association of certian birth characteristics with childhood leukaemia. |
Collaborator Contribution | Christophe Folly, Antonella Mazzei and Dr Judith Lupatsch were the first authors of these 3 papers. They cleaned the data, ran (most of) the analysis and wrote the first draft of the paper. Dr Ben Spycher was the principal investigator of the project and provided the financial resources for this study. The collaboration was multidisciplinary and the role of the clinicians (Prof Claudia Kuehni, University of Bern, Prof Marc Ansari, University hospital of Geneva) essential to interpret the results and communicate findings with other paediatric oncologists (through the annual Swiss Paediatric Oncology Group conference). |
Impact | - Papers: Folly CL, Konstantinoudis G, Mazzei-Abba A, Kreis C, Bucher B, Furrer R, Spycher BD. Bayesian spatial modelling of terrestrial radiation in Switzerland. arXiv preprint arXiv:2010.00534. 2020 Oct 1.(accepted Journal of Environmental Radioactivity) Lupatsch JE, Kreis C, Konstantinoudis G, Ansari M, Kuehni C, Spycher B. Birth characteristics and childhood leukemia in Switzerland: a register-based case-control study. Submitted to Cancer Causes and Control 2020. Mazzei A, Konstantinoudis G, Kreis C, Diezi M, Ammann R, Zwahlen M, Kuehni C, Spycher B. Childhood cancer and residential proximity to petrol stations: a nationwide registry-based case-control study in Switzerland. Submitted to Occupational and Environmental Medicine. - Bayesian model to calculate terrestrial radiation in Switzerland: https://github.com/FollyCh/TerrMapCH |
Start Year | 2019 |
Description | Childhood cancers and environmental factors in Switzerland |
Organisation | University of Geneva |
Country | Switzerland |
Sector | Academic/University |
PI Contribution | This project is a continuation of my postdoc in Switzerland, where I supervised Christophe Folly and Antonella Mazzei during their PhD. During this collaboration, I supervised remotely the PhD students together with Dr Ben Spycher. My main contributions on this project were: 1. Develop a statistical methodology that uses precise geolocations to create continuous terrestrial radiation maps in Switzerland. The methodology falls in the Bayesian framework that I currently use for modelling the climate-related respiratory disease burden. 2. Develop an algorithm to calculate the residential proximity of childhood cancer cases to petrol stations. In both project I worked closely with the PhD students, had monthly meetings and helped writing both papers. 3. Run part of the analysis on a project identifying association of certian birth characteristics with childhood leukaemia. |
Collaborator Contribution | Christophe Folly, Antonella Mazzei and Dr Judith Lupatsch were the first authors of these 3 papers. They cleaned the data, ran (most of) the analysis and wrote the first draft of the paper. Dr Ben Spycher was the principal investigator of the project and provided the financial resources for this study. The collaboration was multidisciplinary and the role of the clinicians (Prof Claudia Kuehni, University of Bern, Prof Marc Ansari, University hospital of Geneva) essential to interpret the results and communicate findings with other paediatric oncologists (through the annual Swiss Paediatric Oncology Group conference). |
Impact | - Papers: Folly CL, Konstantinoudis G, Mazzei-Abba A, Kreis C, Bucher B, Furrer R, Spycher BD. Bayesian spatial modelling of terrestrial radiation in Switzerland. arXiv preprint arXiv:2010.00534. 2020 Oct 1.(accepted Journal of Environmental Radioactivity) Lupatsch JE, Kreis C, Konstantinoudis G, Ansari M, Kuehni C, Spycher B. Birth characteristics and childhood leukemia in Switzerland: a register-based case-control study. Submitted to Cancer Causes and Control 2020. Mazzei A, Konstantinoudis G, Kreis C, Diezi M, Ammann R, Zwahlen M, Kuehni C, Spycher B. Childhood cancer and residential proximity to petrol stations: a nationwide registry-based case-control study in Switzerland. Submitted to Occupational and Environmental Medicine. - Bayesian model to calculate terrestrial radiation in Switzerland: https://github.com/FollyCh/TerrMapCH |
Start Year | 2019 |
Description | Childhood cancers and environmental factors in Switzerland |
Organisation | University of Zurich |
Country | Switzerland |
Sector | Academic/University |
PI Contribution | This project is a continuation of my postdoc in Switzerland, where I supervised Christophe Folly and Antonella Mazzei during their PhD. During this collaboration, I supervised remotely the PhD students together with Dr Ben Spycher. My main contributions on this project were: 1. Develop a statistical methodology that uses precise geolocations to create continuous terrestrial radiation maps in Switzerland. The methodology falls in the Bayesian framework that I currently use for modelling the climate-related respiratory disease burden. 2. Develop an algorithm to calculate the residential proximity of childhood cancer cases to petrol stations. In both project I worked closely with the PhD students, had monthly meetings and helped writing both papers. 3. Run part of the analysis on a project identifying association of certian birth characteristics with childhood leukaemia. |
Collaborator Contribution | Christophe Folly, Antonella Mazzei and Dr Judith Lupatsch were the first authors of these 3 papers. They cleaned the data, ran (most of) the analysis and wrote the first draft of the paper. Dr Ben Spycher was the principal investigator of the project and provided the financial resources for this study. The collaboration was multidisciplinary and the role of the clinicians (Prof Claudia Kuehni, University of Bern, Prof Marc Ansari, University hospital of Geneva) essential to interpret the results and communicate findings with other paediatric oncologists (through the annual Swiss Paediatric Oncology Group conference). |
Impact | - Papers: Folly CL, Konstantinoudis G, Mazzei-Abba A, Kreis C, Bucher B, Furrer R, Spycher BD. Bayesian spatial modelling of terrestrial radiation in Switzerland. arXiv preprint arXiv:2010.00534. 2020 Oct 1.(accepted Journal of Environmental Radioactivity) Lupatsch JE, Kreis C, Konstantinoudis G, Ansari M, Kuehni C, Spycher B. Birth characteristics and childhood leukemia in Switzerland: a register-based case-control study. Submitted to Cancer Causes and Control 2020. Mazzei A, Konstantinoudis G, Kreis C, Diezi M, Ammann R, Zwahlen M, Kuehni C, Spycher B. Childhood cancer and residential proximity to petrol stations: a nationwide registry-based case-control study in Switzerland. Submitted to Occupational and Environmental Medicine. - Bayesian model to calculate terrestrial radiation in Switzerland: https://github.com/FollyCh/TerrMapCH |
Start Year | 2019 |
Description | Excess deaths in Greece |
Organisation | Hellenic Statistical Authority |
Country | Greece |
Sector | Public |
PI Contribution | This is an ongoing collaboration with the Hellenic statistical authority to calculate the excess deaths in Greece in 2020. The total death toll of COVID-19 in 2020 is affected by the baseline characteristics of the Greek population (age, sex, ethnicity etc), the timing of the implementation of public health policies to interrupt COVID-19 transmission and the preparedness of the health and social care systems. My role on this collaboration is to develop the toolbox to analyse the data, run the analysis and write the paper. This collaboration gives me the opportunity to extend the methodology developed as part of the current grant and apply it to a timely public health problem. There is also the potential to extend this collaboration with Italy, Portugal and Spain and report excess deaths in 2020 in the Mediterranean region. |
Collaborator Contribution | The contributions of the collaborators is to provide and clean the mortality data during 2015-2020 in Greece. |
Impact | There is no output published so far. |
Start Year | 2021 |
Description | MetOffice |
Organisation | Meteorological Office UK |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Apart from the online available tools, MetOffice provided me with the AQUM data. The AQUM is a global model for estimating airpollution concentration. The results are not online available but can be readily available after request. I collaborated with Dr Paul Agnew and Dr Pedro Molina-Jimenez to obtain this PM2.5 and O3 data in England at 2km grid during 2007-2019. |
Collaborator Contribution | The collaborators prepared and cleaned the air-pollution data. |
Impact | This is an on-going collaboration and the results obtain so far are preliminary. I expect a publication by the end of the summer 2021. |
Start Year | 2020 |