Estimating death rates in complex humanitarian emergencies using the network survival method

Casey Breen, Saeed Rahman, Christina Kay, Joeri Smits, Abraham Azar, Steve Ahuka-Mundeke and Dennis Feehan

No 4efdt, SocArXiv from Center for Open Science

Abstract: Reliable estimates of death rates in complex humanitarian emergencies are critical for assessing the severity of a crisis and for effectively allocating resources. However, in many humanitarian settings, logistical and security concerns make conventional methods for estimating death rates infeasible. We develop and test a new method for estimating death rates in humanitarian emergencies using reports of deaths in survey respondents’ social networks. To test our method, we collected original data in Tanganyika Province of the Democratic Republic of the Congo, a setting where reliable estimates of death rates are in high demand. Qualitative fieldwork suggested testing two different types of personal networks as the basis for death rate estimates: deaths among immediate neighbors and deaths among kin. We benchmarked our network estimates against a standard retrospective household mortality survey, which estimated a crude death rate nearly twice as high as our network-based methods. Given both methods are equally plausible, our findings underscore the need for further validation and development of both methods.

Date: 2024-10-24
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:4efdt

DOI: 10.31219/osf.io/4efdt

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