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

## TL;DR

This paper introduces a new method to estimate death rates in humanitarian crises by using social networks, tested in the Democratic Republic of the Congo.

## Contribution

The novel network survival method uses social network data to estimate death rates in settings where traditional methods are impractical.

## Key findings

- Network-based estimates yielded 0.44 deaths per 10,000 person-days.
- Household surveys estimated a higher crude death rate of 0.81 deaths per 10,000 person-days.
- Both methods are considered equally plausible but require further validation.

## 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 (n = 5311), a setting where reliable estimates of crude death rates (CDR) are in high demand. Qualitative fieldwork suggested testing 2 different types of personal networks as the basis for CDR estimates: deaths among immediate neighbors and deaths among kin. We compare our network-based estimates (0.44 deaths per 10 000 person-days) against a standard retrospective household mortality survey, which estimated a CDR nearly twice as high (0.81 deaths per 10 000 person-days). Given that both methods are equally plausible, our findings highlight the need for further validation and development of both methods.