My current focus is on improving understanding of space-time dynamics of disease and using new geovisual analytics methods to explore these dynamics. One projects utilizes geographic information, network analysis and visualisation techniques to acquire an improved understanding of transmission potential routes, in a data-poor environment, such as Niger. This requires mining of data, from a variety of sources (i.e. news articles, blogs, RSS feeds and social networks (i.e. Twitter)) to distinguish modes and methods of disease transmission (see Measles in Niger). In conjunction with this, I am investigating accessibility of health facilities in Niger and how health services may be enhanced or restricted throughout the country using different modes of transportation (foot vs. local vehicles) at different times of the year (wet vs. dry season).

I am also building on the work I did for my PhD looking at host-pathogen interactions. Using a large dataset made available from a state agency I am analysing West Nile Virus incidence across Pennsylvania, comparing similarities and differences of species in different geographic locations and how environment may play a role in diversity.  In addition, and in a malaria-vector context I am investigating what temporal scale of climate data is suitable to capture transmission potential of vector-borne diseases. 

Modelling and evaluating risk in all the aforementioned cases is important, but so too is understanding information gathered from a variety of sources can be overwhelming and requires a number of key elements that may involve collecting and synthesizing information to gain knowledge needed to help improve understanding about a phenomenon. Visual analytics satisfies this task by combining “automated analysis techniques with interactive visualisations for an effective understanding, reasoning and decision making on the basis of very large and complex datasets" (Keim et al., 2011) and is summarized in Figure 1.  Essentially this is an iterative process of information retrieval and processing that was used to improve our understanding of movement in Niger using "Sense of Place' tools developed at GeoVISTA (see Measles in Niger point (3)).

Figure 1 illustrates an amendment to the visual analytics process and automatic data analysis methods used to discover knowledge (based on Keim et al., 2011). The visual analytics process is an iterative process that is an interaction between information, visualisations, and models about the data, to aid users in knowledge discovery.

Thus effective visualization and clear,concise maps are necessary. This requires effective symbolization of maps through standardization of common symbols and sharing of these symbols between agencies (see Symbology). This is critical for crisis management and emergency mapping when communication is paramount.   

Measles in Niger
For the Vaccine Modeling Initiative (VMI) with the Centre for Infectious Disease Dynamics (CIDD). As part of this project we are currently investigating Measles in Niger.  I am currently involved with

1. the investigation of the occurrence of disease in space and time through the application of visualisation methods through interactive map animation (see C.A. McCabe).

2. trying to improve understanding of accessibility throughout Niger to help  (a) determine how to deliver a vaccine more effectively - that is when/whether to take the vaccine to the people or try to get the people to the vaccine, and (b) determine who has access to health facilities by looking at how accessible current facilities are to Nigeriens by investigating (i) how movement may be enhanced or restricted throughout the country using different modes of transportation and (ii) at different times of the year.

3. trying to improve knowledge of patterns of human movement between locations in Niger as well as between locations in Niger and the surrounding countries through the use of new information seeking methods, such as gathering information through news articles and blogs on the web using SensePlace Tool (see demo video) and published article Tomaszewski, B., Blanford, J.I, Ross, K., Pezanowski, S. & MacEachren A.M. (2011) Supporting Geographically-aware WebDocument Foraging and Sensemaking. Computers, Environment and Urban Systems.35:192-207)

Figure 3.1 is reproduced from Fig 6 of Tomaszewski et al., 2011. The map illustrates the main travel routes throughout Niger and the surrounding countries. Migrants will enter/depart Niger through a variety of routes along the border of the country (black lines). Once they have reached Agadez, Arlit or Dirkou they will take the main Transit Routes (blue lines) to Europe via Algeria/Morocco or Libya. Seasonal migration is circular and exists throughout the region with mainly a North–South movement (illustrated through the red lines). Migrants will move through the different livelihood zones (FEWSNET) either to agricultural or pastoral areas. High out-migration occurs in three main areas Loga, Ouallam and Tahoua. During the dry season movement can be to feeding centers (purple crosses), mining areas, larger towns/cities in Niger (e.g. Niamey, Maradi, Zinder, Agadez) and Northern Nigeria (e.g. Kano, Sokoto, Maiduguri) as far as Abidjan (Cote D’Ivoire).

SensePlace2

I am also involved with SensePlace2  which forages place-time-attribute information from the Twitterverse that can support crisis management.

Malaria in Africa

Currently working with the Thomas Lab looking at how malaria will be affected with changes in temperature. In particular, I am modeling transmission potential of malaria using different climate resolutions to understand what temporal scale is necessary to model vector-borne diseases both currently and in the future using downscaled data.

West Nile Virus in Pennsylvania