Composite Indicator Approach Research Articles

Assessing the social vulnerability to malaria in Rwanda.

BackgroundSince 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.MethodsA 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.ResultsThe 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.ConclusionsThe 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.

Assessing the sustainability of small wastewater treatment systems: A composite indicator approach

The assessment of the sustainability of wastewater treatment (WWT) systems has gained interest in recent years. However, most previous studies have focused on environmental and/or economic dimensions ignoring social aspects. Moreover, they tend to be based on sets of indicators rather than providing a holistic assessment. To overcome this limitation, this paper proposes an innovative methodology to assess the sustainability of WWT systems based on the development of a composite indicator embracing economic, environmental and social issues. Subsequently, the global sustainability of seven WWT technologies for secondary treatment in small communities is compared. The joint application of the analytical hierarchical process (AHP) to assign weights to each indicator allows the incorporation of the preferences of experts. Initially, the global sustainability of the WWT technologies evaluated is quite similar. However, a scenario analysis illustrates that constructed wetlands technology is the most sustainable in five out of the seven scenarios evaluated. Moreover, extended aeration and rotating biological contactors are identified as the technologies with the lowest variability in their sustainability. Hence, in an uncertain context, they might be considered the preferred options. The proposed approach contributes to ease of interpretation of a complex problem such as the selection of the most sustainable WWT alternative.

A composite threat indicator approach to monitor vegetation condition in the Wet Tropics, Queensland, Australia

Many indicators and indices have been previously developed to report biodiversity condition at a regional scale. However, none have specifically focused on vegetation condition as a surrogate for biodiversity, and also incorporated threats at multiple scales. Using five indicators (forest cover fragmentation, urbanisation, weeds, feral animals and road density) identified from the scientific literature and selected in collaboration with natural resource management (NRM) stakeholders to reflect the state of vegetation condition in the World Heritage-listed Wet Tropics Bioregion of Queensland, Australia, we constructed a simple composite threat index which allowed the spatial display of information at the regional and subregional scale. Using this approach we identified that the overall vegetation condition of the Wet Tropics in the period 2003–2007 was ‘good’, but at a finer scale five of the bioregions nine subregions had ‘moderate’ condition, and only four had ‘good’ condition. The primary threat contributing to the ‘moderate’ condition was vegetation fragmentation due to clearing for agriculture, housing and related transport infrastructure. The composite threat index approach provided managers with a report card for the Wet Tropics landscape which allows rapid assessment of vegetation condition and contributory threats, and thus prioritization for the allocation of limited resources to threatening processes at the subregional scale.

An Optimization‐based Composite Indicators Approach to Performance Assessment

AbstractComposite indicators (CIs) approach has been widely accepted as a useful tool for assessing system performance at macro level. Several recent studies have shown that the weighted product (WP) method, a multiple criteria decision analysis method, may be a good choice in constructing CIs. However, a problem in its application is the subjectivity in determining the weights for sub‐indicators. This paper extends the WP method and proposes an optimization‐based approach to constructing CIs. The proposed approach requires no prior knowledge of the weights for sub‐indicators. The weights used can be generated by solving a series of multiplicative DEA type models that can be transformed into equivalent linear programs. Additional information on the weights can be easily incorporated into the proposed models. A case study on assessing the performance of APEC economies towards sustainable energy development is finally presented to illustrate the use of the approach.

Aggregating physical intensity indicators: results of applying the composite indicator approach to the Canadian industrial sector

Issues surrounding the development, application and interpretation of energy intensity indicators are a continuing source of debate in the field of energy policy analysis. Although economic energy intensity indicators still dominate intensity/efficiency studies, the use of physical energy intensity indicators is on the rise. In the past, physical energy intensity indicators were not employed since it was often impossible to develop aggregate (sector-level or nation-wide) measures of physical energy intensity due to the difficulties associated with adding diverse physical products. This paper presents the results of research conducted specifically to address this “aggregation” problem. The research focused on the development of the Composite Indicator Approach, a simple, practical, alternative method for calculating aggregate physical energy intensity indicators. In this paper, the Composite Indicator Approach is used to develop physical energy intensity indicators for the Canadian industrial and manufacturing sectors, and is then compared to other existing methods of aggregation. The physical composite indicators developed using this approach are also evaluated in terms of their reliability and overall usefulness. Both comparisons suggest that the Composite Indicator Approach can be a useful, and ultimately suitable, way of addressing the aggregation problem typically associated with heterogeneous sectors of the economy.