Participatory risk mapping of malaria vector exposure in northern South America using environmental and population data

Abstract

Malaria elimination remains a major public health challenge in many tropical regions, including large areas of northern South America. In this study, we present a new high spatial resolution (90 × 90 m) risk map for Colombia and surrounding areas based on environmental and human population data. The map was created through a participatory multi-criteria decision analysis in which expert opinion was solicited to determine key environmental and population risk factors, different fuzzy functions to standardize risk factor inputs, and variable factor weights to combine risk factors in a geographic information system. The new risk map was compared to a map of malaria cases in which cases were aggregated to the municipio (municipality) level. The relationship between mean municipio risk scores and total cases by muncípio showed a weak correlation. However, the relationship between pixel-level risk scores and vector occurrence points for two dominant vector species, Anopheles albimanus and An. darlingi, was significantly different (p < 0.05) from a random point distribution, as was a pooled point distribution for these two vector species and An. nuneztovari. Thus, we conclude that the new risk map derived based on expert opinion provides an accurate spatial representation of risk of potential vector exposure rather than malaria transmission as shown by the pattern of malaria cases, and therefore it may be used to inform public health authorities as to where vector control measures should be prioritized to limit human-vector contact in future malaria outbreaks.

Análisis Espacio-Temporal De La Malaria en Matina, Limón, Costa Rica

“…En un estudio de situación, para obtener información actualizada o para monitorear los cambios ocurridos en el tiempo, este instrumento es útil para el proceso de toma de decisiones. Estudios anteriores han utilizado los SIG para mapear y evaluar la malaria en distintos niveles geográficos (Fuller et al, 2014, Ngom y Siegmund 2014Nath et al, 2013, Hanafi-Bojd et al, 2012, Zayeri, Salehi y Pirhsseini, 2011, Lek-Uthai et al, 2010, Alegana et al, 2009.…”

“…Aún así, las escalas utilizadas y el uso de capas con distintas escalas se convierten en una limitante para el estudio ya que se podrían dejar de lado detalles que tal vez se estén relacionados con la distribución del vector y la incidencia de la enfermedad (Fuller et al, 2014).…”

Identifying High-Risk Populations of Tuberculosis Using Environmental Factors and Gis Based Multi-Criteria Decision Making Method

“…The integration of GIS and MCDM techniques in disease and health applications can assist related agencies to make a better decision for risk pollution and contamination (Torre et al, 2012;Liu et al, 2013), healthcare services (Diaby et al, 2013), hazard assessment (Alcorn et al, 2013;Satta et al, 2016) and epidemiology (Fuller et al, 2014). In general, these studies used common steps from original MCDM technique that applied by Malczewsski (2000) and Pfeiffer & Stevens (2015) for spatial epidemiology with appropriate local modifications (Fuller et al, 2014;Lahue et al, 2016), starting from an objective determination to map validation.…”

“…This study assumes that the proposed model can perform better as a disease spatially explicit decision support system (Fuller et al, 2014) and hypothesizes that the most potential cases might occur at high urban areas due to crowded places, rapid development, low socio-economic population and other triggering environmental factors.…”

“…It is a spatial multi-criteria decision making (MCDM) method for producing a risk map based on the index values (Chang, 2011;Malczewski, 2000) and environmental risk factors of local TB. A GIS-based MCDM model is generally applied for suitability and vulnerability exploration with cautious consideration of suitable criteria or factors (Chang, 2011), particularly in managing better environmental health decision making system (Alcorn et al, 2013;Fuller et al, 2014;Satta et al, 2016).…”