My research has spanned a wide range of topics with a concentration on geohealth and how climate can change health risks directly through extreme weather events but also indirectly through the relationship between a disease agent and pathogen with the environment. One of the challenges that we continue to face is how to communicate our findings so that they provide insights and can help with the decision-making and planning process.

GeoTalk: Talking and communicating through maps and visualisations

Health outcomes are shaped by complex interactions between climate, environment, a disease agent, and human behaviour—interactions that unfold across space and time as captured in my book (Blanford, 2024) and much of my work. Now that we live in a highly data-driven AI world, we also need to transition our approaches to integrated geospatial infrastructures capable of combining a multitude of information that range from well organised data sources such as the environment, climate, to less structured and intermittent data that includes biological and social data. These are needed to develop actionable insights communicated using intuitive (geo)visualisations to policymakers, decision-makers and the public. See Blanford (2024) - Managing vector-borne diseases in a geoAI-enabled society. Malaria as an example - for an overview of what is possible. Achieving this has many challenges, one of which is related to communication and what data summaries and visualisations are needed. Maps provide one form of visualisation however, often to truly gain insights of what is taking place may require a suite of visualisations. Furthermore, creating effective visualisations is hard as there are many factors to consider.

Some questions

• What forms of geovisualisation and cartographies are needed that best support rapid understanding and action for different user-groups (e.g. doctors, nurses, general public, tourists, emergency responders, climate scientists)?

• How can Digital Earth concepts be operationalised to create dynamic, multi‑scale digital health representations that support health professionals, policymakers, and the public? 

• What is realistic for anticipatory actions in regular and emergency situations?

• What is needed to create a Digital Earth–enabled health intelligence framework that integrates Earth observation, in‑situ sensing, mobility data, and health information into a coherent, actionable system?

We use a mix of data, technology and methods from the data sciences, AI sciences, social sciences and GISciences to explore these questions. Topics range from health topics, climate-health and other disaster-health topics.

GeoSpatial Health Intelligence, GeoHealth, Planetary Health, Global Health, Public Health, Disaster Health, Climate Health, One Health?

Climate Health, Disaster Health

GeoHealth, Planetary Health, Global Health, Public Health, Climate Health, Disaster Health, One Health?

Climate change is the single biggest health threat facing humanity that will affect the health and well-being of the population. Now more than ever we need to understand what changes are taking place in our environment spatially and temporally, locally and globally. 

Many health challenges are complex crossing social-ecological systems (SES) that are comprised of a number of different components distributed across scales, often compounded by different socio-economic and environmental drivers operating non-linearly. The circulation, transmission and evolution of diseases are driven by a range of factors such as those that relate to the environment, the host, and the pathogen and how they interact in space and time. The outcome of these interactions can be further mitigated or exacerbated by confounding factors that may be related to socio-economic and lifestyle factors (and other vulnerabilities), coping capacity of the individual or community, and the intensity and type of hazard and exposure. 

Thus, disasters act as a catalyst, often accelerating health outcomes by altering the factors that influence the disease triangle (Environment - Host - Agent/pathogen).

Healthr+o = ((A ∩ H ∩ E )+((HE) x V x CC)))t

                    Health Risk and Outcomes = ((Agent - Host - Environment)+(Hazard x Exposure) x Vulnerability x  (lack of ) Coping Capacity) * time

Geographic Information Systems (GIS) approaches for public health and epidemiology enable us to take an integrated health approach to address a range of local and global health challenges that cross social-ecological systems. 

We do this by integrating a variety of data (some novel, some volunteered, some authoritative, some big and messy) in a GIS and use a mix of spatial analysis, data science, social science and machine learning/GeoAI methods with mathematical, statistical and geocomputational models to address applied research questions across a wide range of health topics. 

Our work centers around three main facets that essentially capture exposure pathways, vulnerability factors and health system capacity and resilience:

• understanding the ecology of disease/health risks and outcomes across space and time. Our work integrates host-pathogen-environment interactions (aka disease triangle/epidemiological triad) in dynamically changing environments so that we can understand what this means for health risks and outcomes;

• how to respond. It is not enough to just understand disease and health risks and outcomes but also to think about how to respond so that we can minimize further risks both now and in the future;

• what to communicate how. With the availability of different technologies we are now able to communicate through a variety of channels and in many different ways including geovisualisations. Knowing where and when risks are and how to respond is important for reducing health risks and outcomes.

We examine how changes in environments may result in different outcomes and lead to risks.  We look at this from a variety of angles since risks are complex and multi-dimensional and require different perspectives, time and spatial views so as to inform policy and decision-making. Topics include:

• Climate+health effects -  How climate or changes in climate, whether seasonal or extreme, impact different populations. Examples include

  • • Heatwaves and floods: how these affect health risks and outcomes in different populations. 

    • Healthy food environments: the effect of frost-freeze events on the environment in intense agricultural cropping systems; OR when and where biopesticides can be used for controlling agricultural pests.

    • Disaster events: We look at where disease risks and events occur before, during and after an event. This can examine potential health and other infrastructure impacts, coping capacity, or lack there of, within populations.

    • Mobility: climate-drivers and how they contribute to mobility and disease circulation and transmission.

    • Communication: Communication and warnings for enhancing early warning.

• Accessibility of health care and services - Since accessibility is multi-dimensional we examine accessibility from different angles: 

  • • Change in availability of health services: determine change in availability of services due to seasonal effects that may alter physical accessibility; 

    • Gaps in service: examine the spatial distribution of health services and how these are accessed using different modes of transport. 

    • Mass vaccination, vaccination campaigns: and physical accessibility: whether rolling out vaccines during a disaster (e.g. pandemic and other forms of disasters); or to delivery routine vaccinations, an important component is getting people to the locations where vaccines or other treatments can be delivered efficiently.  By looking at how geography, climate and different modes of transportation can affect how people access essential services, we can determine where the gaps are and where to best place services whether temporary or permanent.

• Vector-borne diseases - We conduct a variety of analyses on mosquito and tick-vectored diseases examining spatial and temporal distribution, hotspots and conduct climate-based modeling to determine potential areas of risk.

  • • Mosquito-vectored diseases: have included dengue and malaria

    • Tick-vectored diseases: have included Tick-borne encephalitis (TBE) and Lyme; 

• GeoHealth education and training - Many public health curriculum still do not offer a course in GIS. To fill this gap and make GIS accessible to health professionals, the Geohealth course was developed. This is a short course that covers the essentials from data to advanced geospatial analysis. 

• Communication - through static and interactive maps, visualisations and dashboards, essential health information and risks can be communicated to help mitigate future health risks.

To learn more about the work we do visit the topics highlighted below.

Education and Education Projects 

See some of the education projects we run and past courses and workshops we have hosted.  Follow this link for courses in geospatial4health (geohealth or gis4health). 

• Justine Blanford (2024) Geographic information, geospatial technologies and spatial data science for health. Pp376. CRC Taylor & Francis.

• Blanford, J.I. (2024) Managing vector-borne diseases in a geoAI-enabled society. Malaria as an example. Journal of Acta Tropica. 260, 107406 https://www.sciencedirect.com/science/article/pii/S0001706X24002870

justine blanford GIS Geography GIScience Health Disaster planetary health geohealth vaccination malaria geoAI  klass

Justine Blanford

We contribute to 

Disaster Resilience: Disasters affect the population in many different ways before, during and often long after an event has occurred. By taking preventative actions ahead of time or shortly after an event can reduce the populations at risk. We are working on this in different ways that include how to respond through communication and warnings, anticipatory actions and modelling of different risks.

Urban Futures: Built environments can affect the populations in many different ways. This can be through inadequate access to necessary infrastructure services such as electricity, running water, sanitation, formalised housing, schools, fresh food and so on. Since much of the world's population now resides in an urban landscapes affect different populations is important. We do this through a variety of work in formal and informal settlements among others.

GeoAI: The development of new methods to sift through large geographic areas and vast amounts of data to extract meaningful information, conduct pattern analysis, trend analysis, forecasting and development of models for improved prediction of risk and outcomes.

Resource Security: Healthy environments result in reduced health risks and outcomes. By understanding the ecology of disease within the natural environment we can better understand how changes in the environment may affect outcomes. This may be due to changes in the quality of food due to a rise in vectors and the diseases they transmit or a response to a disaster event or create a disaster (e.g. sinkholes).