Our mission is to develop innovative epidemiological methods to study the impact of environmental stressors on human health.
We are a research team with complementary expertise in biostatistics, epidemiology, data science and climatology, based at the London School of Hygiene & Tropical Medicine.
The Environment and Health Modelling Lab is a team of researchers based in the Department of Public Health, Environments and Society at the London School of Hygiene & Tropical Medicine. We have multi-disciplinary expertise spanning biostatistics, environmental epidemiology, data science, statistical computing and climatology.
Our research aims to improve understanding of how environmental factors affect human health. Our work has a strong methodological focus and has contributed to the development of new study designs, statistical methods and modelling techniques for epidemiological analyses. We are exploring and pioneering the use of biostatistical tools and modern computing and data technologies to advance research in these fields.
Our research outputs cover a wide range of areas, including epidemiological studies on health risks associated with non-optimal temperature and air pollution, spatio-temporal modelling and environmental exposures, health impact projections under climate change scenarios and the use of new data technologies for environmental health studies.

Antonio
Gasparrini
Professor

Malcolm
Mistry
Assistant Professor

Pierre
Masselot
Research Fellow

Francesco
Sera
Research Fellow

Jacopo
Vanoli
Research Assistant

Arturo
de la Cruz
Research Assistant
Imran Ali
Project Coordinator

Ellie
Darbey
Professional Services
Our research covers a wide range of topics, including: methodologies, global health modelling, climate change and health, air pollution, and spatio-temporal modelling.
Focus areas:
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Statistical Methodologies
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Distributed lag linear and non-linear models
Distributed lag models (DLMs) represent an elegant methodology for describing lagged association in time series data. Originally developed in econometrics, they are now frequently used in epidemiological analysis. Pioneering work by Ben Armstrong extended them to distributed lag non-linear models (DLNMs) for non-linear temperature-mortality relationships.
We proposed a unified statistical framework for the DLM/DLNM class, based on the definition of a cross-basis, a bi-dimensional space of functions that describes the association simultaneously along the space of predictor and lag. Later, we generalised the methodology beyond time series data, allowing applications in various epidemiological fields. Finally, we extended their statistical definition to penalised DLNM, implemented through generalised additive models (GAM). Other specific extensions implemented first the reduction of DLNMs to uni-dimensional summaries, useful to combine results from multi-location analyses, and then the computation of attributable risk measures. The framework has been formally assessed in a simulation study to model lagged associations in environmental time series data. The DLM/DLNM methodology is implemented in the R package dlnm.
An extended meta-analytical framework
Standard methods for meta-analysis are limited to pooling associations represented by a single effect size estimated from a set of independent studies. However, this setting can be too restrictive for modern meta-analytical applications.
The EHM-Lab has first contributed to developing multivariate meta-analytical methods for pooling multiparameter estimates representing complex associations. We then developed a general framework for meta-analysis based on linear mixed-effects models that includes, as special cases, multivariate, network, multilevel, dose-response, and longitudinal meta-analysis and meta-regression. Applications of these meta-analytical developments have been described in a tutorial on extended two-stage designs for environmental epidemiology. The methodology has been implemented in the R packages mvmeta and mixmeta.
- Study Designs
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The case time series design
Modern linkage methods and data technologies provide a way to reconstruct detailed longitudinal profiles of health outcomes and predictors. This rich data setting, however, poses important methodological and computational problems that traditional epidemiological methods are not well suited to address.
Research by the EHM-Lab has led to the development of the case time series (CTS) design, a novel methodology that combines the longitudinal structure typical of aggregated time series with the individual-level self-matched methods. The modelling framework is highly adaptable to various outcome and exposure definitions, and it is based on efficient methods that make it suitable for the analysis of highly informative longitudinal data resources.
The main article introduced the CTS design and illustrated applications in case studies using environmental and clinical data. A following tutorial article adapted the CTS methodology for the analysis of small-area data. The statistical framework is based on conditional regression models, presented in a methodological article.
Small-area analysis of environmental risks
The increased availability of data on health outcomes and risk factors collected at fine geographical resolution makes possible conducting small-area epidemiological studies. However, this setting poses important methodological and computational issues, related to modelling complexities and data linkage.
The EHM-Lab has developed cutting-edge study designs for the analysis of small-area data. These methods allow the use of finely disaggregated health data linked with high-resolution environmental exposure measurements through GIS techniques. The framework offers the opportunity to study local variations in risk and the role of area-level characteristics in modifying the vulnerability to environmental stressors. We provided a methodological description of the design in a tutorial article, and an application to study small-area temperature-related risks.
Extensions of two-stage designs
The two-stage design has become a standard tool in environmental epidemiology to model multi-location data. The EHM-Lab has recently proposed multiple design extensions of the classical two-stage design structure, all implemented within a unified analytical framework based on linear mixed-effects models.
The extended two-stage methodology, described in a recent tutorial article, permits the analysis of associations characterised by combinations of multivariate outcomes, hierarchical geographical structures, repeated measures, and/or longitudinal settings. We have applied it in various epidemiological analyses, including for quantifying mortality impacts of heat and cold, investigating air pollution effects clustered at multiple geographical levels, assessing differential risks by age and geographical areas, quantifying excess mortality during the COVID-19 outbreak, and estimating the role of air conditioning in attenuating heat-related mortality.
Interrupted time series design
Interrupted time series (ITS) analysis is a valuable study design for evaluating the public health interventions. Its quasi-experimental nature allows quantifying effects of policies or events using a pre-post comparison while controlling for temporal trends.
We first illustrated the application of the ITS method for epidemiological analysis in a tutorial article that discussed design features and assumptions. Specific methodological contributions focused instead on model selection and the use of controls. The EHM-Lab has contributed to several applications of the ITS design, for instance for assessing the association between smoking bans and cardiovascular risk, the effect of the financial crisis on suicides, the impact of media coverage on the use of statins, the relationship between self-defence laws on firearm-related homicides, the effect of taxation on the sales of sugar-sweetened beverages, the impact of healthcare reforms on hospital care, and the excess mortality during the COVID-19 outbreak.
- The MCC Study
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The EHM-Lab coordinates the Multi-Country Multi-City (MCC) Collaborative Research Network, an international collaboration of research teams aiming to produce epidemiological evidence on associations between environmental stressors, climate, and health. The research program benefits from the use of the largest dataset ever assembled for this purpose, including information on environmental exposures, health outcomes, and climate projections from hundreds of locations within several countries around the world.
Through MCC, we have led epidemiological analyses in several research areas. Initial studies focused on temperature-related risks, with the quantification of health impacts of heat and cold, the analysis of long-term and seasonal variation in risks, the role of humidity and inter/intra-day variability, long-term effects, and the minimum-risk temperature. Further studies first projected the mortality burden under future scenarios and for global temperature thresholds, and then quantified the impact of climate change in the historical period. More recent investigations assessed short-term risks of air pollutants in the largest multi-country analyses ever published, including studies on particulate matter (PM10 and PM2.5, as well as PM2.5-10), ozone (O3), nitrogen dioxide (NO2), sulphur dioxide (SO2), and carbon monoxide (CO), in addition to the analysis of risks by pollution components. The MCC Network has also contributed research on COVID-19, specifically about the role of methodological factors on the SARS-CoV-2 transmission.
- Climate and health
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Temperature and mortality
Non-optimal outdoor temperature is one of the leading causes of health burden attributed to environmental factors, with both heat and cold associated with substantial impacts on mortality and morbidity. The EHM-Lab has led this research topic by developing state-of-the-art statistical framework and study designs, and then applying them in substantive studies.
A seminal article by the EHM-Lab first presented a multi-country analysis of excess mortality due to heat and cold, while other contributions assessed long-term effects of temperature and related risks for cause-specific mortality. The modelling framework has been extended in recent years, as illustrated in a more recent analysis of 854 urban areas across Europe, and in a small-area study of temperature-related risks. Parallel work has focused on the study of the optimal temperature across populations, first with a methodological contribution and then with a global analysis on the minimum mortality temperature (MMT). Another analysis evaluated the use of excess winter deaths as an impact measure for public health.
Analysis of vulnerability and adaptation factors
Health impacts of environmental and climate stressors vary dramatically both geographically and temporally, due to changes in vulnerability within and between populations. The issue is of primary interest for the definition of public health policies, in particular for identifying effective adaptation pathways to reduce the impact of climate change.
The EHM-Lab has provided several contributions to characterise differential vulnerability to heat and cold and to study potential adaptation strategies. We first assessed long-term variations in mortality and then acclimatation processes leading to changes in risks within a season. We then investigated adaptive mechanisms related to heat and cold in a changing climate. Furthermore, we evaluated vulnerability factors responsible for differential risks of heat and cold, and the specifically assessed the role of air conditioning in decreasing heat impacts. We also linked large scale climatic teleconnections to annual variations in heat-related deaths. Finally, we explored ways to determine real-time health impacts for national heatwave plans.
Health impact projections of climate change
Climate change is the defining global issue of our time. A critical step in climate change research is to project impacts under different scenarios of greenhouse gas emissions, which should in turn inform alternative adaptation and mitigation policies. The EHM-Lab has contributed substantially to this topic.
We first developed a modelling framework for health impact projections, illustrated in a tutorial article that described the various steps and methodologies. We then applied such framework in applied studies to quantify the excess mortality due to heat and cold, both under various emission scenarios along the 21st century and then for global mean temperature thresholds. A more recent study assessed the contribution of anthropogenic emissions to heat-related excess mortality in the historical period.
Assessment of weather-related risks
The assessment of climate-related health impacts requires the analysis of various weather indices. In addition to daily measures of dry-bulb temperature, the scientific literature includes studies on various indicators, which can inform both the definition of specific physiological pathways and the better characterisation of susceptibility profiles.
The EHM-Lab has led various epidemiological analyses on various weather indices, including assessment on the role of humidity in enhancing mortality risks, associations with alternative measures such as inter/intra-day variability, and composite indicators such as the universal thermal climate index (UTCI). Another important contribution was the assessment of climate reanalysis data for performing epidemiological studies on temperature-related risks.
- Air pollution
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Further details coming soon
- Spatio-temporal modelling
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Further details coming soon
[Dataset] Temperature-related mortality exposure-response functions for 854 cities in Europe
This repository provides exposure-response functions by five age groups for most cities with more than 50,000 inhabitants in Europe. It includes coefficients and variance-covariance of B-spline bases to reconstruct the curves, simulations to represent uncertainty as well as city-specific temperature percentile.
Access the dataset on Zenodo
Read the publication
Further resources
We provide the code for our analysis so our work can be applied elsewhere. Visit the links below:
A new report published by the UK's Office for National Statistics (ONS) analysing climate-related mortality and hospital admissions in England and Wales from 1980-2022, found that all regions showed increased mortality risk for temperatures greater than 22 degrees Celsius. Prof Antonio Gasparrini from the EHM-Lab at LSHTM who worked on this research provides commentary, stating that "the report shows the high impact that non-optimal temperature has had in England and Wales...with London being the most impacted for heat-related deaths". He warns that "this will become the norm due to climate change, and it makes even more urgent the need to implement adequate climate and public health measures."
Read the full expert comment, or article featured in the Guardian.
Antonio Gasparrini, Professor of Biostatistics and Epidemiology in the EHM-Lab at LSHTM, provides commentary on the impacts of the recent UK heatwaves on health in an article by the Mail Online. Professor Gasparrini warns that even though temperatures are remaining below 40°C, 'heat-related mortality starts increasing well below such extreme temperatures, and it can be expected that a noticeable increase in deaths will occur even at ranges predicted in the current heatwave', noting that the true scale of the problem will only emerge in the months to come as deaths are officially recorded and analysed. Professor Gasparrini highlights that all members of the population including healthy and relatively young people are at risk during heatwaves, and while tips for coping with heat are welcome, actions to improve Britain's infrastructure to keep the public cool are needed.
New study published in Nature Communications analysed heat-related mortality relationships in 748 locations from 47 countries, using historical data to predict the impact of future extreme summer seasons. Previous research describes how heat-mortality will be affected by global temperature rise, but not specifically by summer heatwaves which could become more frequent and intense. This analyses, co-authored by Prof Antonio Gasparrini from the EHM-Lab at LSHTM, found a rapid increase in heat-related mortality risk over the past 20 years, and projected even greater increase under future global warming scenarios. Authors emphasise the urgent need for mitigation and adaptation to reduce the impacts of climate change on human mortality.
Research co-authored by Prof Antonio Gasparrini from the EHM-Lab at LSHTM compared mortality data during hot weather (defined as mean temperature >35°C over a 3-day lag) in non-indigenous and indigenous communities in the Northern Territory of Australia, from 1980-2019. The study, published in The Lancet Planetary Health, found no significant difference in susceptibility to heat mortality between both communities, despite marked socioeconomic inequity. This research points to the potential of cultural and social adaptations to increasing hot weather as powerful mechanisms for protecting human health, and the importance of understanding sociocultural practices from past and ancient societies.
New research published in The Lancet Planetary Health analysed daily mortality and temperature data from 14 countries that experienced at least one tropical cyclone day between 1980 - 2019. The study, co-authored by Dr Pierre Masselot and Prof Antonio Gasparrini from the EHM-Lab at LSHTM and the MCC Collaborative Research Network, found that tropical cyclone exposure was associated with an overall 6% increase in mortality in the first 2 weeks following a cyclone, but this mortality burden varied both temporally and spatially. The authors recommend further detailed exploration of tropical cyclone epidemiology for those countries and regions with greatest mortality risk from cyclones, to better inform the development and implementation of targeted actions against the health impacts of tropical cyclones in the face of climate change.
Dr Malcolm Mistry, Assistant Professor in Climate and Geo-spatial Modelling in LSHTM's Environment and Health Modelling Lab, provides commentary on the driving forces behind the extreme heat conditions in parts of Europe, the US and Asia, and the impacts on health and the environment. Dr Mistry explains that "Currently, the jet stream from North America to Europe is stuck in a position south of the English Channel. To put it differently, we have a "traffic jam" in the upper atmosphere over these regions causing a stalled, rather warm, weather pattern".
Higher rates of admission for patients with kidney stones and acute kidney injury shows an association with higher ambient temperatures, but it is unclear whether there is also an association with faster loss of kidney function in patients with established chronic kidney disease (CKD). This research, co-authored by the EHM Lab at LSHTM, analysed data from a CKD clinicial trial and publicly available climate data in 21 countries. Authors found that higher ambient heat exposure is associated with a more rapid decline in kidney function for CKD patients, and efforts to reduce exposure of CKD patients to heat should be tested in an attempt to slow the progression of kidney disease.
A study published in Environmental Health Perspectives, co-authored by Antonio Gasparrini from the EHM Lab at LSHTM, estimated the effects of hot nights on the mortality risk across Japan in a nationwide assessment from 1973-2015. Hot nights were defined as days with a minimum temperature of more than 25°C, and a minimum temperature of over 95% of the usual temperature range for that region. Analysis found that nationally, mortality rates increased by 9-10% during hot nights in comparison with nonhot nights, and the strength of this association varied by region and time of summer. These findings could be useful for future research evaluating the health effects of climate change, and have implications for developing and implementing public health policy to protect from the impacts of heatwaves.
New research from LSHTM's Environment and Health Modelling Lab and the Barcelona Institute for Global Health (ISGlobal) calls for greater utilisation of heat stress indices to better communicate the impact of dangerous heatwaves. Besides temperature, these indices take into account other meteorological factors such as humidity. The study assessed recent record-breaking heatwaves in Europe, North America and Asia, and found that the areas where the heat indices revealed the highest risk of heat stress did not necessarily coincide witht the regions with the highest recorded temperatures. Heat indices should be communicated to the public regularly, and authorities must act promptly to ensure the sufficient emergency response.
Read the publication
Dr Pierre Masselot, Research Fellow in Environmental Epidemiology and Statistics at LSHTM's Environment and Health Modelling Lab, comments on research assessing the impacts of heat and cold on mortality in 854 European cities, which showed that heat-related mortality risk among people aged 85 and over was higher in Paris than any other European city included in the study.
Read the article in Le Figaro, or the study published in The Lancet Planetary Health
A new published study, led by the EHM-Lab in collaboration with the MCC Collaborative Research Network and the EXHAUSTION project, has performed the most comprehensive analysis of heat and cold-related mortality in Europe. The researchers applied cutting-edge study designs and statistical methods and identified important geographical and age disparities in temperature impacts, indicating higher risks of heat and cold in older age groups and in Eastern Europe.
Full results and exposure-response functions derived for this study for 5 age groups in 854 European are publicly available in a Zenodo repository, with a semi-reproducible R code available on Github. See the Resources section for details.
Read the article
A new study by the MCC Collaborative Research Network, led by the EHM-Lab at LSHTM, investigated sulphur dioxide (SO2) mortality relationships in 399 cities across 23 countries in the period 1980-2019. The analysis revealed that short-term exposure to SO2 levels is linked with a measurable risk, and associated with substantial excess mortality even at levels below the current WHO daily limit (40 µg/m3).
Read the publication.
A new study using data from 93 European cities led by researchers from the Barcelona Institute for Global Health (ISGlobal) and LSHTM's Environment and Health Modelling Lab, showed that over four percent of deaths in cities during the summer months are due to urban heat islands, and one third of these deaths could be prevented by reaching a tree cover of 30%.
Researchers at the London School of Hygiene & Tropical Medicine are pioneering a new era of public health in the context of climate change and environmental degradation. In this video, Professor Antonio Gasparrini, Environment and Health Modelling Lab team lead, explains how mapping heat-related mortality can help improve understanding of the impacts of extreme heat and inform action to mitigate consequences.
New risk estimates suggest London and other urban areas had the highest heat-related mortality rate, while cold-related deaths were highest in Northern England, Wales and the South West.
Each year in England and Wales, there were on average nearly 800 excess deaths associated with heat and over 60,500 associated with cold between 2000 and 2019, according to a new study published in The Lancet Planetary Health.
Read more about the study.
Ammonium is one of the specific components of fine particulate matter (PM2.5), that has been linked to a higher risk of death compared to other chemicals found in it, according to a new study in the journal Epidemiology.
Find out more about the largest global analysis on air pollution.
Wildfire smoke is causing significant excess deaths globally, with the highest impacts in South-East Asia and Central America, according to the largest study of its kind in the Lancet Planetary Health.
Read more about the impact of wildfire smoke.
Between 1991 and 2018, more than a third of all deaths in which heat played a role were attributable to human-induced global warming, according to a new study in Nature Climate Change.
Read more on the study on global warming.
A novel method that combines artificial intelligence with remote sensing satellite technologies has produced the most detailed coverage of air pollution in Britain to date.
Read more about the ground-breaking technique.
Researchers from the Environment and Health Modelling Lab team teach LSHTM programme modules, as well as providing training and workshops internationally in a range of different research areas. Below is a list of LSHTM programmes and upcoming courses:
LSHTM MSc Courses
Swiss Epidemiology Winter School
Advanced Methods in Climate Change Epidemiology
Date: 15-17 January 2024
This course aims to provide a comprehensive overview of the latest developments in environmental epidemiology applied to climate change research. The course will cover state-of-the-art study designs such as multi-location time series analyses and small-area assessments, advanced methodologies such as distributed lag models and GIS data linkage, and applications such as health impact projection studies and health attribution analysis.
Course leads: Dr. Antonio Gasparrini, London School of Hygiene & Tropical Medicine, London, UK; Dr. Ana Maria Vicedo-Cabrera, University of Bern, Bern, Switzerland
Preliminary registration for this course will be open from 24 August - 4 September 2023, following which participants will be informed if they are allocated a place.
European Educational Programme in Epidemiology: Residential Summer Course
Modern time series methods for public health and epidemiology (5 day course)
Date: 8-12 July 2024
This course will offer a thorough overview of established approaches and recent advancements in methods using time series data for health research, including a theoretical introduction as well as practical examples in public health, environmental, clinical, cancer, and pharmaco-epidemiology.
Course leads: Dr. Antonio Gasparrini, London School of Hygiene & Tropical Medicine, London, UK; Dr. Ana Maria Vicedo-Cabrera, University of Bern, Bern, Switzerland; and Dr. Francesco Sera, University of Florence, Florence, Italy
Upcoming events
Please check back at a later date
Past events
The Multi-Country Multi-City (MCC) Collaborative Research Network: an international collaboration for global studies on environmental risks, climate change, and health, 34th Conference of the International Society for Environmental Epidemiology. 18–21 September 2022, Athens, Greece.