This activity concerns map sequences \u2013 the creation of a set of maps showing infectious disease distribution through time. Such sequences are a useful exploratory technique that can help identify anomalous data in a time series, seasonal patterns or foci for disease outbreaks. Sequences can be based on individual cases, disease rates within regions, or rates of change. Traditionally, such sequences have been created using a static series of \u2018snapshots\u2019 through time, which may then be placed side by side and compared. All maps within a sequence share a common cartographic design for ease of comparison. Since the early 1990s, animation of maps (\u2018map movies\u2019) has become more common as an alternative to such static displays. However, the advantages of such animations in helping interpret patterns of disease spread remain a subject of research.<\/p>\n
Google Earth has a time function that is particularly useful for this type of map animation and this has been used for some examples of this type of data visualisation.\u00a0 Within ArcGIS, the time animation toolbar performs a similar function.<\/p>\n
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The healthmaps site provides spatio-temporal visualisations of georeferenced, validated reports of disease outbreaks, such as for Ebola: https:\/\/www.healthmap.org\/ebola\/#timeline<\/a><\/p>\n * Cifuentes, E., Hernandez, J. E., Venczel, L., and Hurtado, M. (1999) Panorama of acute diarrhoeal diseases in Mexico. Health and Place<\/em> 5, 247-255.<\/p>\n