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AccessMod 3.0: computing geographic coverage and accessibility to health care services using anisotropic movement of patients.

Ray N, Ebener S - Int J Health Geogr (2008)

Bottom Line: Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available.By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities.This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.

View Article: PubMed Central - HTML - PubMed

Affiliation: Information, Evidence and Research, World Health Organization, 20 av, Appia, 1211 Geneva 27, Switzerland. nicolas.ray@zoo.unibe.ch

ABSTRACT

Background: Access to health care can be described along four dimensions: geographic accessibility, availability, financial accessibility and acceptability. Geographic accessibility measures how physically accessible resources are for the population, while availability reflects what resources are available and in what amount. Combining these two types of measure into a single index provides a measure of geographic (or spatial) coverage, which is an important measure for assessing the degree of accessibility of a health care network.

Results: This paper describes the latest version of AccessMod, an extension to the Geographical Information System ArcView 3.x, and provides an example of application of this tool. AccessMod 3 allows one to compute geographic coverage to health care using terrain information and population distribution. Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available. In addition to integrating travelling time, population distribution and the population coverage capacity specific to each health facility in the network, AccessMod can incorporate the influence of landscape components (e.g. topography, river and road networks, vegetation) that impact travelling time to and from facilities. Topographical constraints can be taken into account through an anisotropic analysis that considers the direction of movement. We provide an example of the application of AccessMod in the southern part of Malawi that shows the influences of the landscape constraints and of the modes of transportation on geographic coverage.

Conclusion: By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities. This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.

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Structure of isotropic and anisotropic graph in ArcView and AccessMod. (A) Isotropic analysis case based on slopes derived from a DEM (values are in meters and cell width is 1 km). The largest slope between one cell and all its neighboring cells is attributed to the focal cell. The lines linking pairs of cells depict the direction of largest slope. The "travelling time without slope consideration" is obtained by considering a walking individual travelling at 5 km/h on flat ground. The "travelling time using largest slope" uses the largest slope values and correct travelling speeds through the Tobler formula (see text). (B) In the anisotropic analysis, slopes are computed between each cell and all its neighbors, and slope values are attributed to the arcs linking all pairs of cells. The directional slopes shown in the graph are computed from the center cell to its eight neighbors (using the same DEM than in (A)). The travelling times using directional slopes are derived using the Tobler formula, and can be either computed "from" the center cell or "toward" the center cell. (C) DEM used in the example; (D) population grid used in the example; (E) extent of a catchment area computed through four different ways of considering slopes. Numbers in brackets specify the population covered by each corresponding catchment.
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Figure 4: Structure of isotropic and anisotropic graph in ArcView and AccessMod. (A) Isotropic analysis case based on slopes derived from a DEM (values are in meters and cell width is 1 km). The largest slope between one cell and all its neighboring cells is attributed to the focal cell. The lines linking pairs of cells depict the direction of largest slope. The "travelling time without slope consideration" is obtained by considering a walking individual travelling at 5 km/h on flat ground. The "travelling time using largest slope" uses the largest slope values and correct travelling speeds through the Tobler formula (see text). (B) In the anisotropic analysis, slopes are computed between each cell and all its neighbors, and slope values are attributed to the arcs linking all pairs of cells. The directional slopes shown in the graph are computed from the center cell to its eight neighbors (using the same DEM than in (A)). The travelling times using directional slopes are derived using the Tobler formula, and can be either computed "from" the center cell or "toward" the center cell. (C) DEM used in the example; (D) population grid used in the example; (E) extent of a catchment area computed through four different ways of considering slopes. Numbers in brackets specify the population covered by each corresponding catchment.

Mentions: In the classical costDistance function available in ArcView, each cell within the cost surface used as the input grid contains a single value representing the cost of movement across that location (cell) in any direction. It is a purely isotropic approach, with no consideration of the direction of movement. Moreover, when slopes are derived from a DEM and use as impediment to movement, only the largest slope value among the eight neighboring cells is kept and assigned to the focal cell (see Figure 4A). The graph structure that we have implemented in MAPA allows us no only to take into account the direction of movement in an anisotropic way, but also permits the computation and use of slopes in all directions to control how travelling time is computed between adjacent cells (see Figure 4B).


AccessMod 3.0: computing geographic coverage and accessibility to health care services using anisotropic movement of patients.

Ray N, Ebener S - Int J Health Geogr (2008)

Structure of isotropic and anisotropic graph in ArcView and AccessMod. (A) Isotropic analysis case based on slopes derived from a DEM (values are in meters and cell width is 1 km). The largest slope between one cell and all its neighboring cells is attributed to the focal cell. The lines linking pairs of cells depict the direction of largest slope. The "travelling time without slope consideration" is obtained by considering a walking individual travelling at 5 km/h on flat ground. The "travelling time using largest slope" uses the largest slope values and correct travelling speeds through the Tobler formula (see text). (B) In the anisotropic analysis, slopes are computed between each cell and all its neighbors, and slope values are attributed to the arcs linking all pairs of cells. The directional slopes shown in the graph are computed from the center cell to its eight neighbors (using the same DEM than in (A)). The travelling times using directional slopes are derived using the Tobler formula, and can be either computed "from" the center cell or "toward" the center cell. (C) DEM used in the example; (D) population grid used in the example; (E) extent of a catchment area computed through four different ways of considering slopes. Numbers in brackets specify the population covered by each corresponding catchment.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2651127&req=5

Figure 4: Structure of isotropic and anisotropic graph in ArcView and AccessMod. (A) Isotropic analysis case based on slopes derived from a DEM (values are in meters and cell width is 1 km). The largest slope between one cell and all its neighboring cells is attributed to the focal cell. The lines linking pairs of cells depict the direction of largest slope. The "travelling time without slope consideration" is obtained by considering a walking individual travelling at 5 km/h on flat ground. The "travelling time using largest slope" uses the largest slope values and correct travelling speeds through the Tobler formula (see text). (B) In the anisotropic analysis, slopes are computed between each cell and all its neighbors, and slope values are attributed to the arcs linking all pairs of cells. The directional slopes shown in the graph are computed from the center cell to its eight neighbors (using the same DEM than in (A)). The travelling times using directional slopes are derived using the Tobler formula, and can be either computed "from" the center cell or "toward" the center cell. (C) DEM used in the example; (D) population grid used in the example; (E) extent of a catchment area computed through four different ways of considering slopes. Numbers in brackets specify the population covered by each corresponding catchment.
Mentions: In the classical costDistance function available in ArcView, each cell within the cost surface used as the input grid contains a single value representing the cost of movement across that location (cell) in any direction. It is a purely isotropic approach, with no consideration of the direction of movement. Moreover, when slopes are derived from a DEM and use as impediment to movement, only the largest slope value among the eight neighboring cells is kept and assigned to the focal cell (see Figure 4A). The graph structure that we have implemented in MAPA allows us no only to take into account the direction of movement in an anisotropic way, but also permits the computation and use of slopes in all directions to control how travelling time is computed between adjacent cells (see Figure 4B).

Bottom Line: Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available.By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities.This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.

View Article: PubMed Central - HTML - PubMed

Affiliation: Information, Evidence and Research, World Health Organization, 20 av, Appia, 1211 Geneva 27, Switzerland. nicolas.ray@zoo.unibe.ch

ABSTRACT

Background: Access to health care can be described along four dimensions: geographic accessibility, availability, financial accessibility and acceptability. Geographic accessibility measures how physically accessible resources are for the population, while availability reflects what resources are available and in what amount. Combining these two types of measure into a single index provides a measure of geographic (or spatial) coverage, which is an important measure for assessing the degree of accessibility of a health care network.

Results: This paper describes the latest version of AccessMod, an extension to the Geographical Information System ArcView 3.x, and provides an example of application of this tool. AccessMod 3 allows one to compute geographic coverage to health care using terrain information and population distribution. Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available. In addition to integrating travelling time, population distribution and the population coverage capacity specific to each health facility in the network, AccessMod can incorporate the influence of landscape components (e.g. topography, river and road networks, vegetation) that impact travelling time to and from facilities. Topographical constraints can be taken into account through an anisotropic analysis that considers the direction of movement. We provide an example of the application of AccessMod in the southern part of Malawi that shows the influences of the landscape constraints and of the modes of transportation on geographic coverage.

Conclusion: By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities. This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.

Show MeSH
Related in: MedlinePlus