Environmental health investigations attempt to document the complex relationships between the environment and human health, and typically involve a multitude of disciplines and expertise. Interdisciplinary practice must be adopted to combine data, collected over different dimensions from both medical studies and environmental science.
Environmental health investigations typically need to consider data from individuals and populations over time and space, as well as collect data on exposure to a component(s) that potentially cause ill health. The latter, environmental part of the investigation, is arguably more challenging when symptoms of ill health are present but when there is no obvious environmental contaminant to correlate with symptom occurrence. To compound the problem, even when a correlation exists between the presence of an environmental contaminant(s) and symptoms of ill health, the likely mechanism of disease onset must be investigated through individual data informatics (such as toxicology) and gene-environment interactions must be considered. Hence, multivariate geospatial analysis and modeling is needed to consider the interactions between the environment and presence of disease. In an era of big data and open source health informatics, the possibilities for disease prediction, prevention and personalised treatment are better than ever, but they can only be realised through an intensive multiple-disciplinary approach, where the various relevant disciplines collaborate and complement each other.
Wardrop, N., Le Blond, J.S. 2015. Addressing correlations between geological hazards and health outcomes: Addressing complexity in medical geology. Environment International, 84, 90-93, doi:10.1016/j.envint.2015.07.016.
Kamel Boulos, M.N., Le Blond, J.S. 2016 . On the road to personalised and precision geomedicine: medical geology and a renewed call for interdiscplinarity. International Health Geographics, 15:5, doi:10.1186/s12942-016-0033-0.