Workshops
WORKSHOP NUMBER: PCW 01
TITLE: The Role of Implementation Science in Global Environmental Public Health
PRESENTERS: Dr. Lindsey Martin (Durham NC, United States), Dr. Gila Neta (Rockville MD, United States)
HALL: Parallel Hall 6 (MC 3.3)
DURATION: 14:00-17:30 EEST (3.5 hours) NEW TIME
FEE: 30 EUR (Half-Day Pre-Conference Workshop) – Please register through the online bookings form
FORMAT: Hybrid (in-person or virtual)
ATTENDANCE LIMITATIONS: None (hall capacity limited to 40 seated for in-person attendance)
ABSTRACT (SN 94):
Implementation science (IS), defined as the study of methods to promote the adoption and integration of evidence-based interventions (e.g., programs, practices, and policies) into routine health care, community, and public health settings, closes the research to practice gap and can lead to actionable change across individual, community, organizational and societal levels. IS holds potential to improve global environmental public health through the adaptation, uptake, sustainment and spread of environmental health interventions that prevent or mitigate harmful exposures and support environmental health equity. Recognizing the need to build capacity in IS in environmental health, the National Institute of Environmental Health Sciences hosted the Advancing Environmental Health Equity through Implementation Science virtual workshop in February 2022 that drew a global audience. Workshop survey results highlight the need for more training in IS and its application to environmental health issues. To help address this need, this half-day workshop will provide a more in-depth overview of IS through a series of eight interconnected modules: (1) defining IS and how it can be applied to environmental health issues in the United States (e.g., greening interventions) and globally (e.g., clean cookstove uptake and scale-up in low- and middle-income countries); (2) common IS theories and frameworks; (3) IS study designs and methods; (4) implementation strategies; (5) implementation outcomes; (6) policy IS; (7) tips for writing IS grant applications and (8) an overview of current IS funding opportunities from the National Institutes of Health. Participants are encouraged to bring example(s) of their current or planned research to this workshop where they will have the opportunity to engage with the facilitators to identify potential IS research questions. After attending this workshop, participants will be able to (1) describe IS and how it differs from effectiveness research and (2) identify possible IS questions in their own work.
WORKSHOP NUMBER: PCW 02
TITLE: Practical guidance and tools to recover and restore environments impacted by chemical incidents
PRESENTER: Dr. Antonio Peña-Fernández (Leicester, United Kingdom)
HALL: Parallel Hall 4 (MC 2)
DURATION: 10:30-13:30 EEST (3 hours)
FEE: 30 EUR (Half-Day Pre-Conference Workshop) – Please register through the online bookings form
FORMAT: Hybrid (in-person or virtual)
ATTENDANCE LIMITATIONS: Maximum 50 delegates
ABSTRACT (SN 45):
The release of chemical substances into the environment, either deliberately or involuntarily, can affect multiple countries simultaneously, with serious implications for human health and the environment. Although rare, recent attacks with the highly toxic Novichok nerve agent in Salisbury (UK), have put the spotlight on the importance of having appropriate capacity, capabilities and trained personnel, to quickly respond to these events to protect humans and the environment. Thus, technical guidance and resources should be available as part of the preparedness and planning that all governments should establish, so first responders (central government departments; emergency response personnel; local authorities) can tailor robust recovery strategies to minimise the number of people exposed and remediate the environment to avoid future exposures to the hazards released.
The aim of this workshop is to introduce participants to the practical, evidence-based guidance and innovative six-step decision framework for tailoring an effective protection and recovery strategy following a chemical incident developed by Public Health England (PHE) in collaboration with other UK Government Departments and Agencies and local authorities.
The session will involve a mix of mini-lectures and case based scenarios on the practical guidance and tools developed, which are freely downloadable in the PHE website: https://www.gov.uk/government/collections/recovery-remediation-and-environmental-decontamination
The workshop will cover:
Relevance of chemical incidents.
Introduction to the PHE guidance (UK Recovery Handbook for Chemical Incidents) and tool (Chemical Recovery Record Form).
Factors influencing recovery and restoration following a chemical incident.
Intervention: two real-world/developed scenarios involving emerging chemical pollutants will be provided. Using the available PHE recovery tools, individuals or small groups will tailor a recovery intervention to get the impacted environment (food production systems, inhabited areas and open water systems) back to normal.
Communication: participants will communicate their interventions using the Chemical Recovery Record form.
Attendees are invited to bring their own laptops/tablets.
WORKSHOP NUMBER: PCW 03
TITLE: Advanced two-stage methods in environmental epidemiology – Study designs, statistical models, and software
PRESENTERS: Dr. Francesco Sera (Florence, Italy), Dr. Ana Maria Vicedo-Cabrera (Bern, Switzerland), Prof. Antonio Gasparrini (London, United Kingdom)
HALL: Parallel Hall 6 (MC 3.3)
DURATION: 10:30-13:30 EEST (3 hours)
FEE: 30 EUR (Half-Day Pre-Conference Workshop) – Please register through the online bookings form
FORMAT: In-person only (not available for virtual attendees)
ATTENDANCE LIMITATIONS: Maximum 25 delegates allowed
ABSTRACT (SN 44):
Two-stage designs have become standard tools in environmental epidemiology, where data from multiple locations are analyzed separately and then pooled using meta-analytical methods. Typical applications are represented by multi-city time series studies or pooled cohort or case-control studies. The basic meta-analytical designs assume the simple case in which single and independent risk effect estimates are collected from different locations. However, this prevents more complex applications that are becoming common in modern epidemiological analyses, for instance when estimates refer to multiple risk effects, when they are clustered within regions, when they are collected at multiple times or for different levels of exposures or modifiers, or when they are spatially correlated.
This workshop will illustrate a unified framework and software for meta-analysis that flexibly extends the two-stage design. This is based on a general mixed-effects model that allows multivariate, hierarchical, longitudinal, and spatial meta-analysis and meta-regression, thus covering the special cases mentioned above. The methodology will be illustrated using a mix of lectures and practical case studies, using data from multi-location studies on the health effects of environmental factors. These will cover examples of meta-analyses of multiple outcomes, estimates of cities nested within regions, measures collected at multiple times or exposure/modifiers levels, or spatially correlated. The analyses will be performed using the new R package mixmeta, with data and R code made available for future study.
The definition of a unified framework for meta-analysis, along with a freely-available software, will provide researchers with a flexible tool for addressing non-standard pooling problems in two-stage designs applied to environmental studies.
WORKSHOP NUMBER: PCW 04
TITLE: How to Conduct Systematic Reviews and Meta-Analyses to Improve Environmental Health Policy and Decision-Making
PRESENTERS: Dr. Chartres Nicholas (San Francisco CA, United States), Prof. Tracey Woodruff (San Francisco CA, United States), Dr. Paul Whaley (Lancaster, United Kingdom), Prof. Juleen Lam (Hayward CA, United States), Dr. Barbara Hudson-Hanley (Corvallis OR, United States)
HALL: Parallel Hall 7 (MC 3.4)
DURATION: 10:30-13:30 & 14:30-17:30 EEST (6 hours)
FEE: 50 EUR (Full-Day Pre-Conference Workshop) – Please register through the online bookings form
FORMAT: Hybrid (in-person or virtual)
ATTENDANCE LIMITATIONS: None (hall capacity limited to 55 seated for in-person attendance)
ABSTRACT (SN 66):
Background
Over the past 25 years, decision-making in the clinical arena has relied on systematic reviews (SR) as a source of trusted, evidence-based advice for patients and to inform billions of dollars of healthcare spending. To bridge between SR in environmental health (EH) and the clinical sciences, authoritative bodies, U.S. agencies, and academic scientists developed and implemented validated, peer-reviewed SR methods including the UCSF PRHE Navigation Guide and the U.S. National Toxicology Program’s OHAT.
Significance
Systematic reviews have been adapted from clinical medicine, where data is largely from randomized, controlled trials. Environmental health SRs often rely on data from human epidemiological studies to inform the relationship between exposures and adverse health outcomes. While there has been an increase in SR use in EH over the last decade, there is divergent approaches to key elements of the SR process, including assessing risk of bias (ROB) and evaluation of the quality of the body of evidence.
It is, therefore, critical that the SR methods implemented in EH adhere to best practices and do not inappropriately exclude or downgrade environmental epidemiological studies, while using methods such as meta-analyses that can help increase the statistical power and strengthen the findings from these studies by producing quantitative estimates of risk.
Relationship between presentations
The first presentation will discuss the evolution of SR in EH and how they have evolved from the clinical sciences. Next, participants will learn the key steps to conducting best practice SRs, including problem identification, protocol development, study search strategy, risk of bias assessment and evidence synthesis. The final two presentations will be practical training sessions. Firstly, participants will learn how to conduct ROB assessments, including a discussion on the important biases to consider in environmental epidemiological studies. Secondly, they will learn to synthesize epidemiological studies, including the use of meta-analysis when appropriate, into a bottom-line and actionable summary of the evidence.
WORKSHOP NUMBER: PCW 05
TITLE: Climate Change and Health in LMICs: Toward Equitable, Transdisciplinary Research in Environmental Epidemiology
AUTHORS: Dr. Josh Rosenthal (Bethesda MD, United States), Dr. Aubrey Miller (Bethesda MD, United States), Dr. Alan Dangour (London, United Kingdom), Dr. Diarmid Campbell-Lendrum (Geneva, Switzerland), Dr. Wilfran Moufouma-Okia (Geneva, Switzerland), Dr. Stella Hartinger-Pena (Lima, Peru), Dr. Poornima Prabhakaran (Gurgaon, India), Dr. Adeladza Kofi Amegah (Cape Coast, Ghana)
HALL: Parallel Hall 3 (MC 3)
DURATION: 14:30-17:30 EEST (3 hours)
FEE: 30 EUR Half-Day Pre-Conference Workshop) – Please register through the online bookings form
FORMAT: Hybrid (in-person or virtual)
ATTENDANCE LIMITATIONS: 10-75 delegates
ABSTRACT (SN 47):
In response to growing health threats posed by the global climate change crisis, the US National Institutes of Health (NIH) has developed a new Strategic Framework to guide climate change and health research and capacity building. The Wellcome Trust has recently launched its new Challenge area on Climate and Health and will be able to share its strategic objectives and plans going forward. The NIH framework is anchored in four themes: Health Effects Research, Health Equity, Intervention Research, and Training and Capacity Building. It also identifies nine key areas of supporting science for climate change and health research, including epidemiology, predictive modeling, and data integration. There is a growing understanding in the scientific community that solutions-oriented research and capacity building in low and middle income countries (LMICs) must be accelerated to support health objectives in climate actions, including adaptation and mitigation. This workshop aims to deepen the discussion regarding priority research and capacity building needs in LMIC settings including the increasing risks associated with extreme weather events, wildfires, changing disease patterns, threats to coastal communities, and food and water security.
The workshop will be organized around brief presentations from the NIH, Wellcome Trust, the WHO, the WMO, and environmental epidemiologists from three LMICs. These will lay the groundwork for structured discussions with all participants on key areas of interest:
1) Community engagement approaches at national and local levels
2) Forecasting and modeling
3) Measurement and communications technologies
4) Data management and integration
5) Roles for observational, experimental and implementation science
Aims of the discussion will be to identify approaches to address these and other central issues to enable the highest quality science and most effective development of public health services in the face of extreme challenges to health and well-being posed by climate change today and in the future.
WORKSHOP NUMBER: PCW 06
TITLE: Causal Mediation analysis and its application in environmental epidemiology
PRESENTERS: Dr. Chen Chen (La Jolla CA, United States), Dr. Tarik Benmarhnia (La Jolla CA, United States)
HALL: Parallel Hall 4 (MC 2)
DURATION: 14:30-17:30 EEST (3 hours)
FEE: 30 EUR (Half-Day Pre-Conference Workshop) – Please register through the online bookings form
FORMAT: Hybrid (in-person or virtual)
ATTENDANCE LIMITATIONS: Maximum 40 delegates
ABSTRACT (SN 06):
Identification of modifiable risk factors of adverse health outcomes and underlying mechanisms to support informed decisions to protect public health has been a major target in environmental epidemiology. In the recent decade, we have witnessed an increasing interest in using mediation analysis to study the pathways and mechanisms behind the associations between environmental determinants and various disease outcomes. The study of mediation could improve our understanding of the disease etiology or drivers of social inequalities in health (e.g., environmental injustice), and help identifying possible intervention points. Knowledge of mediation is also central for the assessment of public health interventions since they help to better predict the circumstances under which interventions will work.
Traditional approaches to mediation analysis are based on adjusting for the mediator in standard regression models, which has been proven to be biased under circumstances common in environmental epidemiology studies, such as the presence of mediator-outcome confounding, exposure-mediator interaction, multiple mediators, and intermediate confounding. Recent epidemiological literature proposed different approaches to deal with such methodological challenges under the potential outcomes framework, while their application in environmental epidemiology is still limited.
The goal of this workshop is to highlight key methodological challenges that arise when assessing mediation and to provide an overview of different modern methods that can be used to deal with these challenges. Specifically, we will provide a theoretical overview of the mediation analysis methods and related identification assumptions, discuss potential methodological challenges with traditional methods, and introduce alternative modern analytical methods (e.g., inverse probability weighting, inverse odds ratio weighting) that can deal with such challenges. We will also discuss settings with multiple mediators and exposure-mediator interactions. In the second part of this workshop, we will cover multiple analytical methods using R programming language with examples from environmental epidemiology to facilitate translation to real-world data analysis.
WORKSHOP NUMBER: PCW 07
TITLE: Strategies for enhancing peer review as a reviewer and author
PRESENTER: Dr. Sabah Quraishi (United States) NEW
HALL: Parallel Hall 3 (MC 3)
DURATION: 10:30-13:30 EEST (3 hours) NEW TIME
FEE: 30 EUR (Half-Day Pre-Conference Workshop) – Please register through the online bookings form
FORMAT: In-person only
ATTENDANCE LIMITATIONS: Maximum 55 delegates
ABSTRACT (SN 16):
Peer review is a critical quality control mechanism in the advancement of science. However, few researchers receive any formal training on how to effectively review and critique a scientific manuscript. We intend to provide workshop participants with knowledge, skills, and strategies to maximize the quality and utility of their reviews. Learning about the review process and how to provide better reviews can also help authors improve their own manuscripts.
We will familiarize participants with the overall peer review process: the purpose, potential biases, and ethical dilemmas of peer review, conducting and writing the review itself, and responding to reviews as an author. Participants will learn key elements of a reviewer report and what to include in private comments to the editor. Techniques to convey comments politely and constructively and the journal decisions and appeals process will be discussed. The session will feature interactive examples of responses to reviewer reports and case studies. Participants will be encouraged to share their own experiences and perspectives.
All members of ISEE may benefit from this session, however, we anticipate the greatest interest from early-career researchers and members from low- and middle-income countries. After the session, participants will have a clearer understanding of the peer review process, how to write useful reviews, and how to successfully respond to reviewer comments on their own work.
WORKSHOP NUMBER: PCW 08
TITLE: The case time series design for environmental epidemiology
PRESENTERS: Prof. Antonio Gasparrini (London, United Kingdom), Dr. Ana Maria Vicedo-Cabrera (Bern, Switzerland), Dr. Francesco Sera (Florence, Italy)
HALL: Parallel Hall 5 (MC 3.2)
DURATION: 14:30-17:30 EEST (3 hours)
FEE: 30 EUR (Half-Day Pre-Conference Workshop) – Please register through the online bookings form
FORMAT: In-person only
ATTENDANCE LIMITATIONS: Maximum 25 delegates
ABSTRACT (SN 19):
Environmental research has been transformed by new data technologies, such as electronic health records linkage, wearables and remote sensing. These tools provide the opportunity to perform large population-based studies, with the longitudinal collection of small-area or individual-level outcomes and exposure profiles finely reconstructed over space and time. However, these studies require innovative analytical methods.
This workshop will illustrate a new study design, called case time series, for investigating transient health risks associated with time-varying exposures. This design combines modelling features typical of aggregated time series with design aspects of self-matched methods such as the case-crossover. The modelling framework is highly adaptable to various outcome and exposure definitions, and it is based on efficient estimation and computational methods that make it suitable for the analysis of highly-informative longitudinal data resources.
The methodology will be illustrated with real-data examples of applications in small-area and individual-level analyses of environmental risks. A first case study will present an analysis of mortality risks associated with non-optimal temperature, using data from multiple small-area administrative units and high-resolution modelled exposure measurements. A second case study will show an individual-level analysis that assessed the association between multiple environmental exposures and allergic symptoms, using real-time measurements from a smartphone study.
The case time series design represents a general and flexible tool that is particularly suited for exploiting novel data technologies and resources in epidemiological analyses. This workshop will provide the attendants with a thorough overview of the designs framework of the case time series methodology, and with practical examples of its application in various contexts. The material will include data and R code to replicate the illustrative analyses.
