Trends in Parasitology
Volume 32, Issue 1, January 2016, Pages 19-29
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Review
Progress and Challenges in Infectious Disease Cartography

https://doi.org/10.1016/j.pt.2015.09.006Get rights and content

Trends

Infectious disease cartography is not only a powerful field of research in disease modelling, but also useful for communicating results to the public.

Our understanding of the interaction of environmental, socioeconomic, and behavioural factors, and disease presence has improved as more data become available.

Human connectivity is a central driver of disease spread globally as humans become more mobile.

Challenges remain in developing automated tools that allow the rapid detection and dissemination of disease maps, particularly in outbreak situations.

Quantitatively mapping the spatial distributions of infectious diseases is key to both investigating their epidemiology and identifying populations at risk of infection. Important advances in data quality and methodologies have allowed for better investigation of disease risk and its association with environmental factors. However, incorporating dynamic human behavioural processes in disease mapping remains challenging. For example, connectivity among human populations, a key driver of pathogen dispersal, has increased sharply over the past century, along with the availability of data derived from mobile phones and other dynamic data sources. Future work must be targeted towards the rapid updating and dissemination of appropriately designed disease maps to guide the public health community in reducing the global burden of infectious disease.

Section snippets

Recent Trends in Infectious Disease Cartography

Infectious disease cartography (or infectious disease mapping) describes the quantitative spatial prediction of disease transmission risk. It has been facilitated by the rapid increases in computing power over the past three decades and the increasing availability of spatially continuous data on environmental risk factors for diseases, such as satellite imagery. Therefore, high-resolution spatial data representing both environmental and socioeconomic predictors of disease transmission 1, 2 and

Approaches for Mapping Infectious Disease

Historically, disease mapping was confined to simply drawing case numbers on physical maps. Over the past decades, the world has been mapped out digitally and information about disease outbreaks is recorded from numerous data sources. Major approaches to disease mapping today involve deterministic, correlative, and geostatistical modelling techniques (see details in Figure 1 and Table 1). For policy makers to translate these maps into action, levels of confidence must be assigned to them, which

Infectious Diseases and Global Connectivity

In tandem with the unprecedented increases in human population over the past 50 years, connectivity among human populations has increased rapidly. Increasing urbanization, economic growth, improvements in transport infrastructure, and changing trade and immigration policies 19, 26, 27 have led to populations in each successive generation becoming more mobile than the last, with regular international travel now the norm for a significant fraction of the global population.

For many zoonotic and

New Frontiers in Mapping Diseases: Opportunities From Big Data

Increasing volumes of data from a variety of sources, and the technology to rapidly collate and organise them, offer enormous opportunities for improving disease surveillance and control in the near future [65]. Several digital resources for disease detection data have been established to collate data from online resources [65], including ProMED-mail [66], the Global Public Health Intelligence Network (GPHIN), HealthMap, and BioCaster 65, 67. These online resources can fill gaps in public

Public Health Implications and Ways Forward

Spatial information about infectious diseases has broad implications for targeted public health interventions. For example, the targeted distribution of insecticide-treated mosquito nets (ITN) to key risk areas of high malaria prevalence has been shown to not only protect individuals from becoming infected, but also have wider implications in terms of spatial spillover effects 72, 73. Understanding population interconnectedness helps identify key individuals, risk groups, or regions in a

Concluding Remarks

Technological advances over the past decade have transformed infectious disease cartography from providing visualisations of spatial data and qualitative descriptions of disease risk into a framework for providing robust, quantified predictive maps to guide public health policy. The rapid pace of global change over the same time period has brought socioeconomic factors and global connectivity to the forefront as factors governing global disease risk (see Outstanding Questions). Infectious

Disclaimer

Funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Acknowledgements

M.U.G.K. is funded by the German Academic Exchange Service (DAAD) through a graduate scholarship. S.I.H. is funded by a Senior Research Fellowship from the Wellcome Trust (#095066). S.I.H. and D.L.S. also acknowledge funding support from the RAPIDD program of the Science and Technology Directorate, Department of Homeland Security, and the Fogarty International Center (FIC), National Institutes of Health (NIH). S.I.H. and G.R.W.W. acknowledge funding from the International Research Consortium on

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