Animated Map Timeline, Syria
Sandra Arlinghaus, Salma Haidar, and Mark Wilson
The University of Michigan

Adjunct Professor of Mathematical Geography and Population-Environment Dynamics,
School of Natural Resources and Environment and College of Architecture and Urban Planning;
Ph.D. Candidate, School of Public Health;
Associate Professor, Department of Ecology and Evolutionary Biology (College of Literature, Science and the Arts) and Department of Epidemiology (School of Public Health) and Director, Global Health Program.

Cartographic evidence can often be used to find pattern in large sets of data that are widely scattered in time and space.  Thus, when co-author Haidar considered spreadsheets with many thousands of entries, it seemed useful to map the data in her quest to look for pattern in incidence of the disease, Leishmaniasis, in Syria.  She wished to view the data by Syrian province over a period of eight years, on a monthly basis. (See Figure 1 for a map of "Syria: By Province.")  In that way she hoped to be able to see, at a glance, variation in incidence from north to south in a seasonal framework.  The animated map offered one approach to that task.

To create the sequence of animated maps below (Figure 2), monthly thematic maps are shaded, in a GIS, according to standard deviations above (red) and below (blue) the mean (white) of data (incidence of Leishmaniasis) for each year.  Intervals are 0.25 standard deviations.  The deeper the color the farther from the mean.  The calendar below the group of maps is also animated to coordinate with the changes in the maps. Thumbnail-sized maps are aligned below to show general contrast in cyclical pattern between north and south and in annual variation of disease incidence.  For a more detailed view, click on small maps to see enlarged maps, one at a time.  To get the benefit of map coordination, the display must be viewed on a high-speed connection or downloaded and viewed on a CD (for example).

Figure 1.  Provinces of Syria.  Source:  Community Systems Foundation.









Figure 2.  Animated map sequence showing changing pattern of Leishmaniasis incidence, over time, in Syria (by province).

There are a number of questions one might ask, based on observing this set of maps.  If some of the questions have known answers then this display might be calibrated as a "model" after which one might then consider other questions with unknown answers.  A few natural observations might be:
  • From 1995 on, the province of Damascus is always below the mean; prior to 1995, it was not and exhibited apparent seasonal variation, with values above the mean (for the most part) in Oct., Nov., Dec., Jan., and Feb.  What did Damascus do in 1994/95; was some sort of disease control measure implemented?  If so, it may be working.  What is the lesson, therefore,  for Aleppo which always appears above the mean?  The controls applied in Damascus may require certain climatic/rainfall regimes or presence or absence of vegetation.  Whatever the requirements, is the environment of Aleppo conducive to using the same sorts of control procedure that Damascus has employed?
  • From 1995 on, provinces to the east of Aleppo begin to appear above the mean in a consistent pattern; why is this (some in 1994) the case?  The variation appears seasonal with high values in (Nov), Dec., Jan, Feb, and March and in that regard is similar to the situation in Damascus (1990-94); is that mere coincidence?  What happened in 1994 to shove incidence to the east on an apparently persistent basis?  Is there a relation to the Euphrates River Valley and to water projects to the north, in Turkey?
  • Aleppo is almost always above the mean.  The provinces to the west of Aleppo come in and out of the picture; is there some explanation for the pattern that appears?
  • From 1995 on, Al Quneitera (the Golan Heights) appears not to be synchronized with the rest of the southern region as it had been before; why is this?
  • The year 1994 seems a bit unusual, as if it were a transition point of some sort; what happened in 1994?  Sometimes it appears to fit with the new grouping from 1995 on, and at other times it seems to fit with the old grouping from 1990-1993.
Animated maps, that view spatial change over time, can generate quick sets of questions.  For a full view of the health-related substance of this topic the reader is referred to author Haidar's forthcoming dissertation.

Animap papers published in previous volumes of Solstice are listed below, and linked to the article, for the interested reader; please also refer to other related articles in the current issue: