The health-trash nexus in challenging environments: A spatial mixed methods analysis of Accra, Ghana

Bempah, Sandra; Curtis, Andrew; Awandare, Gordon A.; Ajayakumar, Jayakrishnan; Nyakoe, Nancy

doi:10.1016/j.apgeog.2022.102701

Cited by 7 publications

(6 citation statements)

References 49 publications

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“…One of the challenges of urbanisation is increasing waste generation as this has consequences on the health of urban residents. Good waste management practices such as regular trash disposal reduce the risk of malaria as there would be less mosquito breeding, clogging and flooding 72 .…”

Section: Discussionmentioning

confidence: 99%

Identifying childhood malaria hotspots and risk factors in a Nigerian city using geostatistical modelling approach

Bayode,

Siegmund

2024

Sci Rep

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Malaria ranks high among prevalent and ravaging infectious diseases in sub-Saharan Africa (SSA). The negative impacts, disease burden, and risk are higher among children and pregnant women as part of the most vulnerable groups to malaria in Nigeria. However, the burden of malaria is not even in space and time. This study explores the spatial variability of malaria prevalence among children under five years (U5) in medium-sized rapidly growing city of Akure, Nigeria using model-based geostatistical modeling (MBG) technique to predict U5 malaria burden at a 100 × 100 m grid, while the parameter estimation was done using Monte Carlo maximum likelihood method. The non-spatial logistic regression model shows that U5 malaria prevalence is significantly influenced by the usage of insecticide-treated nets—ITNs, window protection, and water source. Furthermore, the MBG model shows predicted U5 malaria prevalence in Akure is greater than 35% at certain locations while we were able to ascertain places with U5 prevalence > 10% (i.e. hotspots) using exceedance probability modelling which is a vital tool for policy development. The map provides place-based evidence on the spatial variation of U5 malaria in Akure, and direction on where intensified interventions are crucial for the reduction of U5 malaria burden and improvement of urban health in Akure, Nigeria.

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Section: Discussionmentioning

confidence: 99%

Identifying childhood malaria hotspots and risk factors in a Nigerian city using geostatistical modelling approach

Bayode,

Siegmund

2024

Sci Rep

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“…These monthly maps would display key locations such as tents, toilets, and water sources ( Figure 1 ) using similar cartographic approaches developed in Ghana, Haiti, and Kenya [ 22 , 23 , 34 , 35 ]. In addition, other environmental features pertinent to enteric diseases, such as drainage and slope were also to be digitized.…”

Section: Methodsmentioning

confidence: 99%

“…While these camps may have an initial advantage of government or NGO funding and oversight, including building access to WASH features, the on-the-ground situation varies between camps and can change over time. Soon the same questions posed in an SIS will arise; where are there environmental risks such as standing water or mud, especially after rains [ 22 ]? Where does trash accumulation pose health risks, such as water pooling suitable for mosquito breeding [ 23 ]?…”

Section: Introductionmentioning

confidence: 99%

“…While SV mapping data enrich our understanding of SIS-type environments, adding in a simultaneously collected commentary dramatically improves the final map by adding local context. Instead of being able to see, and then map, the local drainage channel, a local or expert voice can tell how the trash being dumped is the cause of local flooding [ 22 ], or how there are still mosquito clouds in the dry season because of the trapped standing water, or why residents distrust the local hospital [ 34 ]. In Colombia, these geonarratives helped explain localized patterns of dengue [ 36 ], and also the connected issue of violence [ 39 ].…”

Section: Introductionmentioning

confidence: 99%

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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.

et al. 2022

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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.

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“…Being able to collect the right data that can reveal spatial and temporal variations in this landscape of risk is vital, not only to understand where and why risk changes, but also to be able to provide early warning systems if a particular water access point becomes unsafe [ 9 , 10 ]. Previous work by the authors in the area of mobile data collection using spatial video (SV) and its geonarrative variants have advanced the science of gaining a contextualized understanding of localized risk [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. However, though some of this work has previously been used to characterize the nature of risk around and in water points in Haiti [ 13 ], an identified deficiency has been the flexibility to reveal space–time patterns in these locations.…”

Section: Introductionmentioning

confidence: 99%

Spatial Video and EpiExplorer: A Field Strategy to Contextualize Enteric Disease Risk in Slum Environments

Ajayakumar

Curtis

Rouzier

et al. 2022

IJERPH

Self Cite

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Disease risk associated with contaminated water, poor sanitation, and hygiene in informal settlement environments is conceptually well understood. From an analytical perspective, collecting data at a suitably fine scale spatial and temporal granularity is challenging. Novel mobile methodologies, such as spatial video (SV), can complement more traditional epidemiological field work to address this gap. However, this work then poses additional challenges in terms of analytical visualizations that can be used to both understand sub-neighborhood patterns of risk, and even provide an early warning system. In this paper, we use bespoke spatial programming to create a framework for flexible, fine-scale exploratory investigations of simultaneously-collected water quality and environmental surveys in three different informal settlements of Port-au-Prince, Haiti. We dynamically mine these spatio-temporal epidemiological and environmental data to provide insights not easily achievable using more traditional spatial software, such as Geographic Information System (GIS). The results include sub-neighborhood maps of localized risk that vary monthly. Most interestingly, some of these epidemiological variations might have previously been erroneously explained because of proximate environmental factors and/or meteorological conditions.

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The health-trash nexus in challenging environments: A spatial mixed methods analysis of Accra, Ghana

Cited by 7 publications

References 49 publications

Identifying childhood malaria hotspots and risk factors in a Nigerian city using geostatistical modelling approach

Identifying childhood malaria hotspots and risk factors in a Nigerian city using geostatistical modelling approach

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.

Spatial Video and EpiExplorer: A Field Strategy to Contextualize Enteric Disease Risk in Slum Environments

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