Childhood TB is a major issue, infecting up to one million children each year. The good news is that there are several effective diagnostic, treatment, and prevention strategies that can have a major impact on decreasing the burden of childhood TB and mortality. These include interventions like contact tracing, fixed-dose medication, and rapid testing. We must consider however, that not every strategy is going to be equally effective in every context. What works well in Kenya may not be as effective in India and vice-versa. With limited resources at our disposal, how do we decide which intervention approach to invest our efforts in? How do we make sure that the options we select will have the best evidence-based impact on child TB morbidity and mortality in the country we’re working in?
Thinking through these questions and making decisions about resource allocations can be challenging. To help with this, TB Alliance and RTI International, with funding from UNITAID, have been working together to develop a tool that provides decision makers, advocates, and other stakeholders the data they need to make more informed decisions on child TB prevention methods and drive the development and adoption of new interventions.
MAP-IT — the Model for Assessment of Pediatric Interventions for Tuberculosis — is a free and easy-to-use web-based decision tool that estimates the potential impact of different interventions on child TB morbidity and mortality in specific countries. MAP-IT also allows users to combine interventions to see the potential impact of intervention synergies.
Examples of questions that the MAP-IT model could help answer include:
MAP-IT was developed with input from the World Health Organization modeling staff and third-party childhood TB experts. The data behind the model are reliable, with primary sources including the WHO and World Bank. Each time you run a scenario in the tool, a list of all the citations and references used to generate specific results is provided to ensure transparency on the data sources and assumptions.
MAP-IT now provides data for ten countries: Nigeria, South Africa, Kenya, India, Pakistan, Philippines, Ethiopia, Democratic Republic of Congo, Bangladesh, and Papua New Guinea, with the potential to include additional countries and updated interventions as data become available.
Users can explore MAP-IT by visiting http://www.mapit4pedstb.org/. A tutorial video on how to use the model is available here: http://www.mapit4pedstb.org/help.
Source: Science Speaks