How to identify epistemic injustice in global health research funding practices: a decolonial guide.

Epistemic injustice is a growing area of study for researchers and practitioners working in the field of global health. Theoretical development and empirical research on epistemic injustice are crucial for providing more nuanced understandings of the mechanisms and structures leading to the exclusion of local and marginalised groups in research and other knowledge practices. Explicit analysis of the potential role of epistemic injustice in policies and practices is currently limited with the absence of methodological starting points. This paper aims to fill this gap in the literature by providing a guide for individuals involved in the design and review of funding schemes wishing to conduct epistemic injustice analysis of their processes using a decolonial lens. Placing contemporary concerns in a wider historical, political and social context and building from the intertwined issues of coloniality of power, coloniality of knowledge and coloniality of being that systematically exclude non-Western epistemic groups, this practice paper presents a three-step decolonial approach for understanding the role and impact of epistemic injustices in global health research funding. It starts with an understanding of how power operates in setting the aim of a call for research proposals. Then, the influence of pose and gaze in the review process is analysed to highlight the presence of epistemological colonisation before discussing methods to address the current funding asymmetries by supporting new ways of being and doing focused on knowledge plurality. Expanding research on how epistemic wrongs manifest in global health funding practices will generate key insights needed to address underlying drivers of inequities within global health project conception and delivery.

Excess mortality during the COVID-19 pandemic: a geospatial and statistical analysis in Aden governorate, Yemen.

BACKGROUND: The burden of COVID-19 in low-income and conflict-affected countries remains unclear, largely reflecting low testing rates. In parts of Yemen, reports indicated a peak in hospital admissions and burials during May-June 2020. To estimate excess mortality during the epidemic period, we quantified activity across all identifiable cemeteries within Aden governorate (population approximately 1 million) by analysing very high-resolution satellite imagery and compared estimates to Civil Registry office records. METHODS: After identifying active cemeteries through remote and ground information, we applied geospatial analysis techniques to manually identify new grave plots and measure changes in burial surface area over a period from July 2016 to September 2020. After imputing missing grave counts using surface area data, we used alternative approaches, including simple interpolation and a generalised additive mixed growth model, to predict both actual and counterfactual (no epidemic) burial rates by cemetery and across the governorate during the most likely period of COVID-19 excess mortality (from 1 April 2020) and thereby compute excess burials. We also analysed death notifications to the Civil Registry office over the same period. RESULTS: We collected 78 observations from 11 cemeteries. In all but one, a peak in daily burial rates was evident from April to July 2020. Interpolation and mixed model methods estimated ≈1500 excess burials up to 6 July, and 2120 up to 19 September, corresponding to a peak weekly increase of 230% from the counterfactual. Satellite imagery estimates were generally lower than Civil Registry data, which indicated a peak 1823 deaths in May alone. However, both sources suggested the epidemic had waned by September 2020. DISCUSSION: To our knowledge, this is the first instance of satellite imagery being used for population mortality estimation. Findings suggest a substantial, under-ascertained impact of COVID-19 in this urban Yemeni governorate and are broadly in line with previous mathematical modelling predictions, though our method cannot distinguish direct from indirect virus deaths. Satellite imagery burial analysis appears a promising novel approach for monitoring epidemics and other crisis impacts, particularly where ground data are difficult to collect.