|Is your organization legally registered in your country:
|If yes, please enter your registration number:
|Organization Type - Primary:
|Organization Type - Secondary:
|Mission: Using innovation and spatially enabled technology EPCON wants to help find all presumed TB patients, assist in diagnoses, monitor and drive their wellbeing, identify hotspots and also predict future focus areas.
Focus: Using artificial intelligence and bayesian reasoning our system can analyse cause and effect patterns and aims to increase program effectiveness and optimise country resource allocation. IoT methods will help us reach patients, community health workers and healthcare facilities.
Why? With over 1,6 million death/year we are convinced that technology can play a role in identifying and preventing this los.
Country specific and socio demographic challenges in many TB outbreak regions require different and innovative approaches to help identify, monitor and evaluate patients ... this is our speciality.
|Do you know about the UNHLM declaration:
Other Organization Information
|Total number of staff in your organization:
11 - 25
|Number of full-time staff who are directly involved with TB:
1 - 5
|Number of part-time staff who are directly involved with TB:
6 - 10
|Number of volunteers who are directly involved with TB:
|How did you hear about the Stop TB Partnership:
Attendance at a TB related event
|If you were informed or referred by another partner of the Stop TB Partnership please tell us who:
||Jackie Huh / StopTB
|Why do you wish join the Stop TB Partnership:
Involvement in Stop TB Working Groups
|Are you a member of a Stop TB national partnership:
|Are you in contact with your national TB programme:
|Please tell us how your organization is contributing to your country's national TB control plan:
|In 2016 one of our founding companies Riskscape in South Africa was requested to investigate the impact of TB in the mining industry in Southern Africa.
This study has contributed to the believe that combining spatial contextual data (eg population density, migration, occupational information, etc) with Artificial Intelligence will help us in a more direct and effective way to identify hotspot regions, and use aggregated (real time) data from field programs to monitor, evaluate and steer country TB programs.
This will contribute to better optimised country resource allocations and help push the information up to the community health worker.
In Belgium we receive support through a participation from IMEC NV (a strong global research organisation with focus on ehealth)
|Which country is your headquarters located in:
|Which countries do you do operate in:
(This includes countries you are conducting activities in)
Central African Republic
Democratic Republic of the Congo
Iran (Islamic Republic of)
Lao People's Democratic Republic
Libyan Arab Jamahiriya
Sao Tome and Principe
United Republic of Tanzania