C-SEMA LEGITIMATE CALLS USE CASE

DATA USE STORY FOR LEGITIMATE CALLS RECORDED BY C-SEMA

Background

C-SEMA is an organization focused on providing social welfare services and working on issues such as child health, education, nutrition and justice. It focuses its work around children in the age group of 7-18 years and it implements monitoring through toll-free “National Helpline” (116).

C-SEMA works with children, parents, communities and local government to provide child protection and care services. Anyone bearing witness to actions against children rights and protection are obligated to report through “National Helpline” where they are connected to C-SEMA counselors who record and evaluate cases and strive for resolution that may include providing advice, forwarding the incident to other government agencies, or assign specialized C-SEMA staff to follow up.

All reported incidents are recorded in a decentralized (excel based) standalone system that C-SEMA shares with the government. C-SEMA uses this data to capture analytics around (1) legitimate vs non-legitimate calls (2) case load analysis (3) categorize and analyze cases under Violence, Abuse, Neglect and Exploitation (VANE).

 

Problem

Over the years C-SEMA has been grouping the calls in two major groups – (1) those dealing with child Violence Abuse Neglect and Exploitation (VANE) incidences and (2) Non-VANE incidences. In generating reports for VANE incidences, C-SEMA faced challenges in accurately and seamlessly monitoring where the incidences occur, how effective is the community reporting on those incidences and for better monitoring and decision support, represent the information via a geo-spatial distribution of abuse incidences by age, sex and abuser profile.

 

Solution

C-SEMA wants to exploit data aggregation, manipulation, and visualization skills so they can generate analyses of their disaggregated data in form of maps, line graphs and other charts that will easily help them monitor the trends and show the prevalence of VANE incidences.

 

PROCESS

Based on 2013 – 2016 C-SEMA data for VANE call records, the following outputs were generated

  • Datasets for all VANE calls from 2013 to 2016.

 

  • Data from decentralized excel based system was exported into CSV and JSON file formats that were then combined to form “master files” for legitimate and non-legitimate calls.

 

  • Data analysis and visualization showing the performance of counselors by legitimate calls
    • There were several visualizations generated from the master files that provide information on the efficiency of the counselors in handling VANE calls and how C-SEMA as an organization is dealing with child protection issues.

 

  • Integrating regions population data and shape file, and districts shape file from National Bureau of Statistics (NBS) to show distribution of incidences geographically.

 

  • There are records for legitimate calls missing location details, children sex, appropriate C-SEMA work hours, children age and having age ranges beyond the boundaries of C-SEMA service coverage brought challenges in correct interpreting the data to reflect the work C-SEMA is doing in providing child protection.

 

  • Population projections data for 2013-16 aggregated at regional and national level depicting the impact of VANE incidents at districts level

 

  • In early days C-SEMA had unique codes for each counselor (ANG, CMW, FKA, JFL, MMA, TCD, VTP) but in late 2014 C-SEMA use of unique codes for each counselor was phased out and more than one counselor was using new codes (XX1, XX2, XX3, …) and this was a challenge in later evaluating performance of an individual counselor beyond November 2014.

OUTCOMES & IMPACTS

Based on the work done thus far, C-SEMA will be able to;

  • Identify and monitor trends linked to child abuse

 

  • Geospatial representation of incidences across regions on a map

 

  • Monitor child protection program impact, through evaluation of trends of different VANE incidences over time.

 

  • Evaluate the prevalence of VANE incidences annually and in different regions. As it is shown the rate was 0.85, 1.1, 0.17 and 0.18 per 100,000 in the years 2013, 2014, 2015 and 2016 respectively, and the leading regions in the year 2014 were Kagera, Mara, Arusha, Dar es Salaam and Kilimanjaro, with rates of higher than 1 per 100,000 population.

 

KEY COLLABORATOR

Key collaborators for this project are as follows;

C-SEMA: Is the main project monitor and implementer, they run the children helpline service in Tanzania mainland.

M-CEMA

Tanzania Data Lab (dLab): A national data hub to promote data innovations, literacy, data use and multi-stakeholder data collaborators.

dlab

Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC): They are the first beneficiary of the interventions conducted by C-SEMA as C-SEMA reports to the ministry on the successes, failures and statuses of the initiative.

 National Emblame

DESCRIPTORS:

C-SEMA: C-SEMA is an organization focused in providing social welfare services and working on issues such as child health, education, nutrition and justice. Its focus groups are children of between 7 and 18 years old and it implements the monitoring through toll-free “National Helpline” (116)

dLab:  A national data hub to promote data innovations, literacy, data use and multi-stakeholder data collaborations.

MoHCDGEC: Committed to facilitate the provision of basic health services that are good, quality, equitable, accessible, affordable & sustainable and gender sensitive.

 

CONTACT INFORMATION:

C-Sema | 8th Floor | Posta House |
Plot No. 6&7 Ohio Street/Ghana Avenue
P.O. Box 75267
Dar es Salaam Tanzania

+255-22-2135819

info@sematanzania.org

www.sematanzania.org

The dLab is promoting innovation and data literacy through a premier center of excellencehttp://www.dlab.or.tz

This seems to be mixed up from 1? Check for generic intro only

Mixed up from 1? Check for generic intro only

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