Page Comparison

L'analyse de la couverture géographique vous permet de prendre en compte la disponibilité des services (c'est-à-dire la capacité des structures de santé à accueillir des patients) et d'en tenir compte en plus des contraintes d'accessibilité physique, afin de définir l'aire de captage associée à chaque structure de santé.

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1. scenario processed class: Table contenant le scénario de voyage qui a été traité.
2. result geographic coverage analysis class: Table containing the results of the geographic coverage analysisTable contenant les résultats de l'analyse de couverture géographique.
3. zonal coverage class: Table containing the results of the zonal statistics analysis in case this option has been checkedTable contenant les résultats de l'analyse de statistiques zonales au cas où cette option a été cochée.
4. population on barriers class: Raster format layer containing the spatial distribution of the target population on barriersCouche de format raster contenant la distribution spatiale de la population cible sur des barrières.
5. population residual class: Raster format layer containing the spatial distribution of the residual populationCouche de format raster contenant la distribution spatiale de la population résiduelle.
6. catchment class: Vector format layer containing the extent of the catchment area for each facility.

Next, just as you did above for the first part of the exercise, you now need to archive the results, export and unzip them in order to open and visualize the results. All of this can be done in the "Data" module (see Section 5.4).

We will describe here only the new types of output generated by AccessMod compared to the previous analytical step. Let us start with the geospatial data that have been generated.

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1. Couche de format vectoriel contenant l'étendue de l'aire de captage pour chaque structure de santé.

Ensuite, comme vous l'avez fait ci-dessus pour la première partie de l'exercice, vous devez maintenant archiver les résultats, les exporter et les décompresser afin d'ouvrir et de visualiser les résultats. Tout cela peut être fait dans le module "Données" (voir chapitre 5.4).

Nous décrirons ici uniquement les nouveaux types de sortie générés par AccessMod par rapport à l'étape analytique précédente. Commençons par les données géospatiales générées.

Le premier type de données est la couche de format vectoriel contenant l'étendue des zones de captage (polygones) rattachées à chaque structure de santé. Cette couche, située dans le dossier "shape_catchment_geographic_analysis_120m" folder, should be opened in a GIS software and would appear as below:

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Each catchment area can be linked to the corresponding health facility through the unique identifier indicated in the attribute table of both layers. Please just note that the header of the column containing the unique identifier in the attribute table of the catchment area layer contains "_join" at the end of it ("cat_join" in the case of the present exercise as per the screenshot below) compare to the header of the column containing that same identifier in the attribute table of the health facility layer ("cat" in the case of the present exercise).

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The raster format residual population layer stored in the , devrait être ouverte dans un logiciel SIG et devrait apparaître comme suit:

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Chaque aire de captage peut être liée au centre de santé correspondant via l'identifiant unique indiqué dans la table attributaire des deux couches. Veuillez noter que l'en-tête de la colonne contenant l'identificateur unique dans la table attributaire de la couche des aires de captage contient "_join" à la fin de celle-ci ("cat_join" dans le cas du présent exercice, comme illustré ci-dessous), semblable à l'en-tête de la colonne contenant ce même identifiant dans la table attributaire de la couche des structures de santé ("cat" dans le cas du présent exercice).

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La couche de population résiduelle au format raster stockée dans le dossier "raster_population_residual_geographic_analysis_120m" folder contains the spatial distribution of the target population that remains uncovered after performing of the analysis. This layer can, for example, be used as an input for the scaling up analysis (see Section 5.5.7), and it looks like this once open in a GIS softwarecontient la distribution spatiale de la population cible qui reste non couverte après l'analyse. Cette couche peut, par exemple, être utilisée comme entrée pour l'analyse de mise à l'échelle (voir section 5.5.7). Elle ressemble à ceci une fois ouvert dans un logiciel SIG:

The geographic analysis also generates two additional Excel files compared to the accessibility analysis, namely:

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• cat: unique identifier of the health facility as per to the field selected from the attribute table of the health facility layer.
• name: name of the health facility as per the field selected from the attribute table of the health facility layer
• capacity: maximum coverage capacity of the health facility expressed as the number of people that the facility can serve (as per the field selected from the attribute table of the health facility layer).
• amRankValues_capacity: values for the parameter used to define the processing order. In the present exercise, this column contains the maximum coverage capacity of each facility as this is the option that was selected above. Please see the boxed note below for more information regarding the label and content of this column when using the other options.
• amRankComputed: processing order applied during the analysis based on the content of the "amRankValues_capacity" field and the direction of processing (ascending or descending), as selected by the user.
• amTravelTimeMax: maximum travel time in minutes, as set by the user for the analysis.
• amPopTravelTimeMax: total population located within the maximum travel time set for the analysis (amTravelTimeMax).
• amCorrPopTime: Pearson correlation coefficient between the set of travelling times (t, from 0 to the maximum travel time) and the corresponding covered population within this time step (i.e. the sum of population in all cells that are located between t and t+1 of travelling time). This correlation measure gives a rough estimate of how the population is distributed through space as we move outward from the health facility. As an example, a large positive value (e.g. 0.707 in the third line of the above table) means that the population is relatively uniformly distributed as you expand outwards from the facility. A strong negative correlation would mean that there is more population close to the health facility than there is far away from it. A correlation close to zero means that there is no specific tendency in how the population is spread within the catchment. This correlation should really just be used as a relative indicator, as we do not provide the statistical significance of the correlation (you should use proper GIS analysis outside AccessMod if you need statistical insights about how the population is spatially located within the catchments).
• amTravelTimeCatchment: travel time to reach the maximum extent of the catchment area attached to the health facility. This value is either:
  • Equal to the maximum travel time set for the analysis (amTravelTimeMax) when the maximum coverage capacity of the facility has not been reached within the set time (120 minutes in this example). In the current exercise, this is the case for the Queen Elizabeth Hospital.
  • Smaller than the maximum travel time set for the analysis (amTravelTimeMax) when the maximum coverage capacity of the facility is reached before reaching amTravelTimeMax. This is the case of The Medka Health Centre in the exercise.
• amPopCatchmentTotal: population located within the catchment area for the travel time reported in the amTravelTimeCatchment field
• amCapacityRealised: part of the maximum coverage capacity of the health facility that is being used (realized) based on the total population located in the catchment area for the given travel time. This value is:
  • Equal to the maximum coverage capacity of the health facility (capacity) when this value is reached before the maximum travel time (amTravelTimeMax). An example is the Medka Health Centre in the present exercise.
  • Smaller than the maximum coverage capacity of the health facility (capacity) when such capacity is not reached within the maximum travel time (amTravelTimeMax). An example is the Chiradzulu District Hospital is in this the present exercise.
• amCapacityResidual: part of the maximum coverage capacity of the health facility that is not being used. This value is calculated by making the difference between the maximum coverage capacity (capacity) and the realized capacity (amCapacityRealised). This value is therefore equal to 0 when the maximum coverage capacity is being reached within the given travel time.
• amPopCatchmentDiff: Part of the total population located in the final catchment area (amPopCatchmentTotal) which does not experience facility coverage by lack of sufficient coverage capacity in the health facility. This value is calculated by making the difference between the total population in the catchment area (amPopCatchmentTotal) and the realized capacity (amCapacityRealised). This value is therefore:
  • Equal to 0 when the maximum coverage capacity is not reached within the given travel time
  • Greater than 0 when the maximum coverage capacity is reached within the given travel time
• amPopCoveredPercent: cumulative geographic coverage expressed as a percentage. This value corresponds to the percentage of the initial population distribution grid (i.e. the layer selected in the "Select population layer (raster)" field) that has been covered after having processes the health facility in question.
  
  
  

The header of the columns containing the unique identifier, the name, and the maximum coverage capacity of each health facility in the resulting table will be the same as the header of the field you have selected from the attribute table of the health facility layer.

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