Currently, one in four people worldwide is estimated to have the Tuberculosis (TB) infection and are as such at risk for developing the disease. Unfortunately, progress towards the UN’s 2018 global target for the number of people provided with preventive treatment by 2021 has been slow – only 42 percent of the people targeted have been treated.
TB REACH, a funding innovation by the Stop TB partnership, provides funding to organisations with pioneering approaches that will reach more people. TB REACH is now in the 10th wave.
The TB REACH Wave 10 projects aim to use new approaches to integrate the delivery of TB and other health services, expand TB preventive Treatment (TPT), and contribute to making healthcare systems stronger. In Indonesia, for example, YMAPI will train midwives in three districts in North Sumatra to conduct contact investigations and provide TPT to eligible individuals.
KIT supports YMAPI and other Wave 10 projects with monitoring, evaluation, and learning frameworks to identify bottlenecks early on and respond to them in time. We also analyse the effectiveness of these interventions and provide evidence of the project’s impact.
For instance, the project implemented by DAPP in Zambia aims to increase TPT among children between 0 and 14 years through comprehensive contact investigation, and the use of community health workers who will ensure the treatment is completed. KIT will work with the DAPP team to monitor their progress and evaluate their impact on TB control in the area.
Initiatives to usher in an era without TB
At the beginning of March, representatives of these organisations, including Advisors from KIT, Mirjam Bakker, Chantale Lakis, Nwanneka Okere, Christina Mergenthaler, Abdullah Latif, and Justine Umutesi got together in Bangkok to discuss how to best monitor and evaluate the TB REACH Wave 10 projects.
One of the tools that is used towards this goal is the MATCH AI framework KIT has developed with EPCON. The Dopasi Foundation, one of the Wave 10 projects, will use this framework to plan TB prevention treatment in Pakistan.
“We developed the MATCH AI framework to increase the efficiency of projects finding active tuberculosis cases, and now the framework will be used by Dopasi to identify areas so they can prioritise and target their preventive treatment. The results of these interventions will be fed back to the model to monitor the impact of the project and further optimise the model,” explains Mirjam.
A significant number of people will have access to preventative treatment in the intervention areas as a result of these projects. At the moment, access to treatment is often limited due to programmatic constraints and other barriers.
At the same time, because of these interventions we will also improve our knowledge on how best to expand TPT considerably. We believe, using this knowledge, if we collectively scale up initiatives like these, we can prevent and #End TB once and for all.