New Detections

Map of Cases to Follow up

Leprosy Case Detection (last 5 years)

Trend of Cases among New (last 5 years)

Authorization to DHIS2:

Instruction

1. Log in to HMIS/DHIS2 here

We will not retain any sensitive or HMIS credential information on this platform.

2. Select the monthly period from the [Actin Box].

Only one-month period is allowed.

3. Select your health facilities (mulitiples are allowed).

Please select the same health facilities STRICTLY according to your access permission on HMIS/DHIS2.

4.Click [Preview] to view the data values and then click [Send] to send to HMIS/DHIS2 server.

Defining a Cluster:

  • Method of Cluster Detection:

  • DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a clustering algorithm used to identify groups of cases based on their spatial proximity.

  • The algorithm works by defining clusters as areas where a minimum number of cases (points) are within a specified distance (radius) from each other. This means that a cluster is formed if there are enough cases close to each other within the defined radius.

  • This method is particularly useful for detecting clusters of varying shapes and sizes in spatial data and can also identify outliers, or noise, which are points that do not belong to any cluster.

Defining Contact Tracing Zone (radius of cases):

Map of Case Clustering and Contact Tracing Zone

Action

Clustering Summary

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