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Assessing the social vulnerability to malaria in Rwanda
AuthorBizimana, Jean-Pierre ; Twarabamenye, Emmanuel ; Kienberger, Stefan
Published in
Malaria Journal, London, 2015, Vol. 14, Issue 2, page 1-21
PublishedBioMed Central, 2015
Document typeJournal Article
Keywords (EN)Malaria / Social vulnerability / Composite indicator / Sensitivity analysis / Rwanda
URNurn:nbn:at:at-ubs:3-3580 Persistent Identifier (URN)
 The work is publicly available
Assessing the social vulnerability to malaria in Rwanda [3.41 mb]
Abstract (English)

Background: Since 2004, malaria interventions in Rwanda have resulted in substantial decline of malaria incidence. However, this achievement is fragile as potentials for local malaria transmissions remain. The risk of getting malaria infection is partially explained by social conditions of vulnerable populations. Since vulnerability to malaria is both influenced by social and environmental factors, its complexity cannot be measured by a single value. The aim of this paper is, therefore, to apply a composite indicator approach for assessing social vulnerability to malaria in Rwanda. This assessment informs the decision-makers in targeting malaria interventions and allocating limited resources to reduce malaria burden in Rwanda. Methods: A literature review was used to conceptualize the social vulnerability to malaria and to select the appropriate vulnerability indicators. Indicators used in the index creation were classified into susceptibility and lack of resilience vulnerability domains. The main steps followed include selection of indicators and datasets, imputation of missing values, descriptive statistics, normalization and weighting of indicators, local sensitivity analysis and indicators aggregation. Correlation analysis helped to empirically evidence the association between the indicators and malaria incidence. Results: The high values of social vulnerability to malaria are found in Gicumbi, Rusizi, Nyaruguru and Gisagara, and low values in Muhanga, Nyarugenge, Kicukiro and Nyanza. The most influential susceptibility indicators to increase malaria are population change (r = 0.729), average number of persons per bedroom (r = 0.531), number of households affected by droughts and famines (r = 0.591), and area used for irrigation (r = 0.611). The bed net ownership (r = 0.398) and poor housing wall materials (0.378) are the lack of resilience indicators that significantly correlate with malaria incidence. Conclusions: The developed composite index social vulnerability to malaria indicates which indicators need to be addressed and in which districts. The results from this study are salient for public health policy- and decision makers in malaria control in Rwanda and timely support the national integrated malaria initiative. Future research development should focus on spatial explicit vulnerability assessment by combining environmental and social drivers to achieve an integrated and complete assessment of vulnerability to malaria.

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