Skip to content

Understanding Why Tuberculosis Cases are Missed in Bangladesh

Published on:

In August 2017, a data analysis workshop was organised in Dhaka, Bangladesh, during which stakeholders from various Bangladeshi institutions – including BRAC, MSH and ICDDR Bangladesh – worked together to generate new hypotheses about where missing cases of TB are found, whom they may be, why they may be missed, and which solutions are needed to reach and care for them.  Building on the extensive knowledge of the KIT CASE team, maps were produced and presented to assess these questions. This followed KIT’s Bangkok workshop on its MATCH Approach to tuberculosis care in 2017.

Results

The maps demonstrated that each district in Bangladesh operates in a unique environment: with different TB burdens, levels of programme quality, socioeconomic conditions, and access to facility services. Comparing these different pieces of information by data triangulation can be useful to detect commonalities and inconsistencies in the data which in turn can be used for hypothesis generation.

Data triangulation & mapping

Triangulation is a powerful analytical technique which facilitates validation of data through cross verification of information from two or more analytical methods or data sources. By combining multiple data sources and filters through which we observe epidemiological processes, we can validate assumptions about possible interventions to improve prevention and care. An example of how triangulation is used to compare and validate assumptions regarding TB case detection in Bangladesh is shown in the maps above.

The maps on the top show the number of people tested for TB within the total population as well as the number of diagnosed TB patients being reported. These maps provide information regarding how many TB suspects are being identified and diagnosed. Since these outcomes depend largely on the coverage and access to services, assumptions regarding service availability need to be validated. The maps to the lower left show indicators of general health service delivery (immunisation) and coverage (microscopic diagnostics available). Finally the number of people who are at risk for TB and are accessing health care is strongly influenced by their socioeconomic status. The maps to the lower right show the literacy and poverty of populations in Bangladesh. Brought together these three thematic conceptualisations provide a practical and concise picture of localised TB epidemics and programme responses.

In addition to triangulating data, spatial statistics are used to identify patterns and anomalies in these data to improve the rigour of these analyses. For more insights into said spatial analyses, please refer to our MATCH Manual.

Related projects & resources

  • Bangkok Workshop on the MATCH Approach to Tuberculosis Care in South & South-East Asia

    • Institute
    • Project

    The Centre for Applied Spatial Epidemiology (CASE) of KIT Royal Tropical Institute provided training in the MATCH Approach to tuberculosis (TB) programme staff who use data to improve programme effectiveness. Funded by the Global Fund, The Stop TB Partnership and the WHO Global TB Program, the CASE team traveled to Bangkok to facilitate the “Regional […]

  • Addressing Drug-Resistant Tuberculosis in Kazakhstan

    • Institute
    • Project

    Kazakhstan is one of thirty countries prioritised by the WHO because of its high-burden of multi drug-resistant (MDR)-Tuberculosis (TB). Summary The Centre for Applied Spatial Epidemiology (CASE) of KIT Royal Tropical Institute was requested by The Global Fund to apply the MATCH Approach to tuberculosis care to support National Toxicology Programs in the Central Asian […]

  • Improving Urban Access to Tuberculosis Services in Pakistan

    • Institute
    • Project

    KIT’s Centre for Applied Spatial Epidemiology (CASE) supported Pakistan’s National TB Programme in the collection of data on TB diagnostic and treatment centers in Khairpur and Islamabad Capital Territory. Summary A number of countries that attended the Bangkok workshop on the KIT’s MATCH Approach to tuberculosis (TB) care subsequently requested continued support to either a) […]

  • Population Based National Tuberculosis Prevalence Survey among Adults (>15 Years) in Pakistan, 2010–2011

    • Institute
    • Publication

    Tuberculosis (TB) is a global health problem. In 2014, an estimated 9.6 million people developed TB and 1.5 million died from the disease Currently, 22 high burden countries account for over 80% of world’s TB cases. Notification data in these countries often do not reflect the actual number of cases in the country due to […]

  • MATCH: Mapping and Analysis for Tailored Disease Control and Health System Strengthening

    • Institute
    • Publication

    Manual This manual is an initiative of the Stop TB partnership, funded by the Global Fund to Fight AIDS, Tuberculosis, and Malaria, and written by the Centre for Applied Spatial Epidemiology (CASE) of KIT Royal Tropical Institute.

  • The KIT MATCH Approach for Enhancing TB Care Coverage

    • Institute
    • Project

    KIT Royal Tropical Institute proudly presents: the MATCH approach (Mapping and Analysis for Tailored disease Control and Health system strengthening) for National Tuberculosis Programmes. MATCH supports National Tuberculosis Programmes to more effectively use resources to treat populations with ongoing tuberculosis transmission. The MATCH approach begins by gathering many – often underused – sources of data, for example: geographic, temporal, and demographic data. The […]

Our services

  • Data mapping & visualisation

    At KIT Royal Tropical Institute we use innovative data mapping and visualisation techniques to support data-driven decision making in the fields of sustainable economic development and health care.

Do you want to know more?