Using GIS to manage and monitor disease
Many datasets can be spatially referenced and this can provide a wealth of information to those making management decisions. When it comes to disease outbreaks or epidemics, GIS can provide an excellent basis for analyzing epidemiological data and displaying trends and relationships between different factors (1). Visual representation is a very effective way of telling a story and conveying information. Geographical information systems (GIS) are all about place and space, therefore we can use this to investigate the what, where and why of disease outbreaks (2). We can answer questions like, where is this disease found? How does the disease relate to the environment around? Where are disease rates higher or lower? Or even, how far is it to the nearest healthcare facility to seek treatment? It has applications for understanding both chronic disease and infectious disease occurrence and dynamics.
Chronic disease, infectious disease and GIS
Chronic diseases are generally not considered to be influenced by geographical factors and the management of these is not the same as monitoring the spread of infectious diseases. As such, monitoring the incidence of chronic disease with GIS is relatively new (3). In comparison, using GIS to monitor and manage infectious disease is widely known and used. Infectious diseases are caused by organisms like bacteria, viruses, fungi or parasites and can be spread person to person, or from direct contact with the infectious organism. Due to the nature of spread with infectious diseases, visual representation and spatial analysis can provide valuable information. GIS is of vital importance for health professionals in predicting outbreaks, detecting clustering and analyzing spread patterns of infectious diseases (4). Halting the spread and vector pathways of infectious diseases is critical to preventing it developing into an epidemic in local communities or a global pandemic (4).
As well as giving healthcare professionals a visual representation of where and when cases of chronic disease are identified and in turn a better understanding of disease dynamics. GIS also enables us to generate quality maps and data reports for project development, community outreach, and policy design purposes (3). For example, the American Center for Disease Control and Prevention (CDC) is a world leader in publishing geospatial data on US county-level morbidity and mortality data for heart disease and stroke (3).
Heart disease and stroke by postcode
The American Center for Disease Control and Prevention have built an Interactive Atlas of Heart Disease and Stroke incidences and this has revealing interesting information (5). Most people wouldn’t have thought where you lived had any impact on your risk of heart disease or stroke, but this information shows otherwise (5). The more records added to the dataset over the years has drawn a clear picture, that for those under the age of 75, the risk of death from cardiovascular disease increases in some postcodes (5). The team that compiled this hope that by providing this data in a spatial, visual format it will be easier to see where cardiovascular disease is more prevalent, and which population groups are at higher risk (5). This information can also be used by governments and health departments in order to improve health care systems in areas of greater need and create healthy places to live (5). By making this information public and incorporated into education campaigns, people can then make their own healthy lifestyle choices.
Understanding infectious disease spread
Understanding the factors that lead to infectious disease spread is essential to preventing spread and therefore managing an outbreak. If used in real time during the early stages of an epidemic, GIS can be used to monitor and enhance understanding of the transmission dynamics of an infectious agent (6). This then forms the basis for designing, implementing and evaluating intervention strategies.
The first known maps for the management of infectious disease outbreaks date back to the plague in Italy in 1694, when maps were used to indicate the link between place and disease (4). An even more well-known historical record is that of the Broad Street cholera outbreak in London, 1854. The thinking at the time was that cholera was spread via airborne particles. However, local anesthetist John Snow mapped cases and was able to find a common link, being a water pump on Broad Street (7). The pump was removed from use, cases of cholera then abated and thus the benefits of mapping infectious disease epidemics were understood.
Measles virus is a highly contagious virus of which cases worldwide have been decreasing year by year, due to effective vaccination campaigns. The disease was declared eliminated in the US in 2000, but since then there have been pockets of infection arising. In 2000, GIS analysis of rapidly growing measles outbreaks were linked to pockets of unvaccinated children (8). This information then meant health services were able to be better placed to cater to those high-risk areas and get on top of the outbreak faster (8).
The emergence of severe acute respiratory syndrome (SARS) in 2003 was at the time, the first major new disease outbreak of the 21st century, and much like Covid-19, it’s spread was facilitated by global air travel (9). Online maps played a crucial part in monitoring and responding to spread quickly, however deeper analysis showed that SARS was highly localized and therefore only moderately transmissible (6). In turn contact tracing and quarantine systems could be formed around this information.
Covid-19 pandemic and geospatial analysis
In 2020 when the world became aware of a rapidly spreading coronavirus, the geospatial community banded together rapidly to apply their skills to pandemic data management. Since the onset of the pandemic there has been a wealth of knowledge available to map the cases, map the spread, map vulnerable populations, map capacity and communicate with maps (10). Applications and maps began to pop up helping citizens and authorities to understand where the vulnerable communities are, infection rates in communities or hospital capacity (10). In Singapore the National Parks Board even developed an app to help residents identify the least crowded parks to visit and maintain social distancing (10).
Various organizations have developed these real-time dashboards tracking case numbers, deaths and other important statistics, however there has been limited geospatial analysis of the Covid pandemic (11). One study looked at of internationally reported cases and mobility data to project the impact of travel limitations on both national and international spread of the virus. (11). This revealed that the initial travel restrictions placed on Wuhan only hindered the overall epidemic spread within China by 3 to 5 days, but had a significant influence on the international scale dispersion (11). These learnings could be applied to future contagious disease outbreaks, and hopefully, avoid another global pandemic.
GIS for improving HIV intervention in Malawi
Malawi has some of the highest rates of HIV prevalence in the world and understanding the geographical variation and the drivers for that is crucial to successful intervention strategies (12). Despite the high rates of HIV in Malawi, the country has seen a dramatic decrease in new cases and more importantly a decline in death rates from HIV (12).
GIS is increasingly being used to analyze HIV rates in Africa, but few studies have looked at spatial clustering down to the district level (12). It’s not surprising that recent research has shown there are diverse socio-economic, demographic, cultural, historical, and geographic factors affecting the vulnerability of particular groups of men and women to HIV infection (12). They identified the HIV epidemic in Malawi to be several spatially defined sub-epidemics - national, regional, urban, rural, and local clusters (12). This means that existing policies and intervention strategies aren’t suitable for each cluster. It was however, clearly obvious that the urbanized south of Malawi had become a transmission hub. The south is not only more densely populated, but also has the highest levels of rural poverty (12). There was also a positive correlation between HIV prevalence and distance to a main road, which is also the case in other studies in southern Africa (12). This information can help to inform improved public health strategies and clinic placement.
GIS for public health communication
Information can be absorbed and learned in a variety of ways, but many people identify wholly or in part as visual learners. Meaning they take in far more information when it’s presented visually. The mapping of diseases and health outcomes is an important part of public health education and prevention efforts in many countries (13). Maps also inform health workers where to focus intervention work such as reducing the spread of HIV among adolescents in specific areas, or addressing and limiting the spread of childhood lead poisoning (13). Health outcomes are often linked to environmental factors, and geospatial information is intrinsically linked to environmental features. For example, GIS can process satellite imagery to allow information like temperature, soil types and land use to be integrated, and the correlations between those risk factors and the occurrence of disease easily identified (1). By using GIS that enables the combination of scientific knowledge and technology leading to improved disease prevention protocols and best practice development (13). This education influences behavior, leading to a proven change in health status and health literacy (13).
GIS can provide enormous gains to health workers and the general public, both for chronic disease management and for the surveillance of infectious diseases. The fast access to large amounts of data and the powerful analysis tools are invaluable in the rapid management of contagious diseases. If policies and procedures are being formulated to factor in what we learn from the spatial dynamics of a disease, we also need to be able to effectively communicate this to relevant communities. GIS then provides dynamic maps for easy visual communication. Without the addition of effective communication applied to the disease intervention strategies, they ultimately may not be as effective.