Next Article in Journal
Characterisation, Recovery and Recycling Potential of Solid Waste in a University of a Developing Economy
Next Article in Special Issue
Using Disaster Outcomes to Validate Components of Social Vulnerability to Floods: Flood Deaths and Property Damage across the USA
Previous Article in Journal
Promoting Sustainable Development of Cultural Assets by Improving Users’ Perception through Space Configuration; Case Study: The Industrial Heritage Site
Previous Article in Special Issue
Vulnerability Assessment and Adaptation Strategies for the Impact of Climate Change on Agricultural Land in Southern Taiwan
Article

Mapping the Structure of Social Vulnerability Systems for Malaria in East Africa

Paris-Lodron-University of Salzburg, Interfaculty Department of Geoinformatics—Z_GIS, Schillerstr. 30, 5020 Salzburg, Austria
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(12), 5112; https://doi.org/10.3390/su12125112
Received: 30 April 2020 / Revised: 12 June 2020 / Accepted: 17 June 2020 / Published: 23 June 2020
(This article belongs to the Special Issue Climate Risk and Vulnerability Mapping)
Millions of people fall ill with malaria every year—most of them are located in sub-Saharan Africa. The weight of the burden of malaria on a society is determined by a complex interplay of environmental and social factors, including poverty, awareness and education, among others. A substantial share of the affected population is characterized by a general lack of anticipation and coping capacities, which renders them particularly vulnerable to the disease and its adverse side effects. This work aims at identifying interdependencies and feedback mechanisms in the malaria social vulnerability system and their variations in space by combining concepts, methods and tools from Climate Change Adaptation, Spatial Analysis, and Statistics and System Dynamics. The developed workflow is applied to a selected set of social, economic and biological vulnerability indicators covering five East-African Nations. As the study areas’ local conditions vary in a multitude of aspects, the social vulnerability system is assumed to vary accordingly throughout space. The study areas’ spatial entities were therefore aggregated into three system-regions using correlation-based clustering. Their respective correlation structures are displayed as Causal Loop Diagrams (CLDs). While the three resulting CLDs do not necessarily display causal relations (as the set of social vulnerability indicators are likely linked through third variables and parts of the data are proxies), they give a good overview of the data, can be used as basis for discussions in participatory settings and can potentially enhance the understanding the malaria vulnerability system. View Full-Text
Keywords: malaria; vulnerability; integrated spatial modeling; East Africa; system dynamics; geons concept; relationships and dependencies; system relations malaria; vulnerability; integrated spatial modeling; East Africa; system dynamics; geons concept; relationships and dependencies; system relations
Show Figures

Figure 1

MDPI and ACS Style

Menk, L.; Neuwirth, C.; Kienberger, S. Mapping the Structure of Social Vulnerability Systems for Malaria in East Africa. Sustainability 2020, 12, 5112. https://doi.org/10.3390/su12125112

AMA Style

Menk L, Neuwirth C, Kienberger S. Mapping the Structure of Social Vulnerability Systems for Malaria in East Africa. Sustainability. 2020; 12(12):5112. https://doi.org/10.3390/su12125112

Chicago/Turabian Style

Menk, Linda; Neuwirth, Christian; Kienberger, Stefan. 2020. "Mapping the Structure of Social Vulnerability Systems for Malaria in East Africa" Sustainability 12, no. 12: 5112. https://doi.org/10.3390/su12125112

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop