The Use of Spatial Video to Map Dynamic and Challenging Environments: A Case Study of Cholera Risk in the Mujoga Relief Camp, D.R.C.

Abstract

In this paper, we provide an overview of how spatial video data collection enriched with contextual mapping can be used as a universal tool to investigate sub-neighborhood scale health risks, including cholera, in challenging environments. To illustrate the method’s flexibility, we consider the life cycle of the Mujoga relief camp set up after the Nyiragongo volcanic eruption in the Democratic Republic of Congo on 22 May 2021. More specifically we investigate how these methods have captured the deteriorating conditions in a camp which is also experiencing lab-confirmed cholera cases. Spatial video data are collected every month from June 2021 to March 2022. These coordinate-tagged images are used to make monthly camp maps, which are then returned to the field teams for added contextual insights. At the same time, a zoom-based geonarrative is used to discuss the camp’s changes, including the cessation of free water supplies and the visible deterioration of toilet facilities. The paper concludes by highlighting the next data science advances to be made with SV mapping, including machine learning to automatically identify and map risks, and how these are already being applied in Mujoga.

Geospatial Health (GeoHealth): Current Trends, Methods, and Applications

“…The evidence suggested the existence of an association between tuberculosis and drug addiction within the investigated hotspot regions [ 11 ]. The use of geospatial videos to map environments with cholera risk in Congo was conducted by Curtis et al, highlighting the use of data science and machine learning to detect infectious diseases in health-risk regions [ 12 ]. Nyandwi et al also detected the spatial distribution of parasitic helminth diseases in Rwanda and associated the parasite incidence with soil characteristics, rainfall, wetlands, population density, and proportion of the rural disease burden [ 13 ].…”