Accepted paper:

Health facility data production on 'malaria' in rural Tanzania: exploring the clay feet of indicators as tools of global health governance


Rene Gerrets (University of Amsterdam)

Paper short abstract:

this paper investigates how contextual variations in the production of the category malaria in Tanzanian health facilities influence the generation of indicators aiming to represent the mosquito-borne affliction

Paper long abstract:

Mirroring the rise of the performance-based paradigm in global health, monitoring and evaluation (M&E) has become a central feature in contemporary malaria control and elimination efforts. These technologies of audit and performance evaluation are used to measure and assess the outputs of interventions and aim to promote their transparency and accountability. Indicators (along with targets) are at the core of M&E activities: used to measure and contrast the inputs, outputs and outcomes of interventions, indicators not only facilitate comparison and ranking of interventions but are also used to inform and justify policy decisions or funding allocation. Hence, attaining high indicator-based rankings is becoming increasingly important to institutions and countries, raising the question how the necessary data are generated especially in low-income countries where health information systems often manifest significant weaknesses. This paper draws on long-term ethnographic fieldwork in southern Tanzania to examine routine data production on malaria in the government health system. It traces how context-specific variations such as those involving human resources or diagnostic technologies profoundly shape knowledge practices at rural health facilities. These variable practices result in the production of ontologically diverse "malaria's" that are collapsed into a single category through routine recording practices, obfuscating its variable content and the wider contextual and structural issues that underlie this variability. This black-boxing raises questions about the content of the category malaria and the indicators generated from these data.

panel P03
Anthropology of health indicators and statistics