Spatial analysis and mapping of georeferenced, individual-level data can help identify important geographical patterns or lead to knowledge significant for dealing with specific social issues in a particular area. However, given the need to protect personal privacy when using geospatial data, the possibility for undertaking geographical analysis on certain types of individual-level data is becoming increasingly circumscribed. This article addresses the need to protect geoprivacy while making georeferenced, individual-level data available in such a way that analytical results are not significantly affected. The effectiveness of three geographical masks with different perturbation radii (r) is examined using a data set for lung-cancer deaths in Franklin County, Ohio, in 1999. The findings reveal a rather consistent trade-off between data confidentiality and accuracy of analytical results. There seems to be a threshold r-value at which the results of analyses on masked data become substantially different from the original results. An r that produces an area about the average size of the study-area census-block groups achieves a desirable optimum trade-off between privacy protection and accuracy of results. The study shows that implementing appropriate geographical masks may help data managers or researchers establish the desirable trade-off, in a particular context, between privacy protection and accuracy of geographic information.

BackgroundOver 5 million stillbirths and neonatal deaths occur annually. Limited and imprecise information on the cause of these deaths hampers progress in achieving global health targets. Complete diagnostic autopsies (CDAs)—the gold standard for cause of death determination—are difficult to perform in most high-burden settings. Therefore, validation of simpler and more feasible methods is needed.Methods and findingsIn this observational study, the validity of a minimally invasive autopsy (MIA) method in determining the cause of death was assessed in 18 stillbirths and 41 neonatal deaths by comparing the results of the MIA with those of the CDA. Concordance between the categories of diseases obtained by the 2 methods was assessed by the Kappa statistic, and the sensitivity, specificity, positive, and negative predictive values of the MIA diagnoses were calculated. A cause of death was identified in 16/18 (89%) and 15/18 (83%) stillborn babies in the CDA and the MIA, respectively. Fetal growth restriction accounted for 39%, infectious diseases for 22%, intrapartum hypoxia for 17%, and intrauterine hypoxia for 11% of stillborn babies. Overall, the MIA showed in this group a substantial concordance with the CDA (Kappa = 0.78, 95% CI [0.56–0.99]). A cause of death was identified in all (100%) and 35/41 (85%) neonatal deaths in the CDA and the MIA, respectively. In this group, the majority of deaths were due to infectious diseases (66%). The overall concordance of the MIA with the CDA in neonates was moderate (Kappa = 0.40, 95% CI [0.18–0.63]). A high percentage of accuracy was observed for the MIA in all the diagnostic categories in both stillbirths and neonates (>75%). The main limitation of this study is that some degree of subjective interpretation is inherent to cause-of-death attribution in both the MIA and the CDA; this is especially so in stillbirths and in relation to fetal growth restriction.ConclusionsThe MIA could be a useful tool for cause-of-death determination in stillbirths and neonatal deaths. These findings may help to accelerate progress towards meeting global health targets by obtaining more accurate information on the causes of death in these age groups, which is essential in guiding the design of new interventions and increasing the effectiveness of those already implemented.

BackgroundAs a result of changes in climatic conditions and greater resistance to insecticides, many regions across the globe, including Colombia, have been facing a resurgence of vector-borne diseases, and dengue fever in particular. Timely information on both (1) the spatial distribution of the disease, and (2) prevailing vulnerabilities of the population are needed to adequately plan targeted preventive intervention. We propose a methodology for the spatial assessment of current socioeconomic vulnerabilities to dengue fever in Cali, a tropical urban environment of Colombia.MethodsBased on a set of socioeconomic and demographic indicators derived from census data and ancillary geospatial datasets, we develop a spatial approach for both expert-based and purely statistical-based modeling of current vulnerability levels across 340 neighborhoods of the city using a Geographic Information System (GIS). The results of both approaches are comparatively evaluated by means of spatial statistics. A web-based approach is proposed to facilitate the visualization and the dissemination of the output vulnerability index to the community.ResultsThe statistical and the expert-based modeling approach exhibit a high concordance, globally, and spatially. The expert-based approach indicates a slightly higher vulnerability mean (0.53) and vulnerability median (0.56) across all neighborhoods, compared to the purely statistical approach (mean = 0.48; median = 0.49). Both approaches reveal that high values of vulnerability tend to cluster in the eastern, north-eastern, and western part of the city. These are poor neighborhoods with high percentages of young (i.e., < 15 years) and illiterate residents, as well as a high proportion of individuals being either unemployed or doing housework.ConclusionsBoth modeling approaches reveal similar outputs, indicating that in the absence of local expertise, statistical approaches could be used, with caution. By decomposing identified vulnerability “hotspots” into their underlying factors, our approach provides valuable information on both (1) the location of neighborhoods, and (2) vulnerability factors that should be given priority in the context of targeted intervention strategies. The results support decision makers to allocate resources in a manner that may reduce existing susceptibilities and strengthen resilience, and thus help to reduce the burden of vector-borne diseases.

BackgroundIn recent decades, the world has witnessed unprecedented progress in child survival. However, our knowledge of what is killing nearly 6 million children annually in low- and middle-income countries remains poor, partly because of the inadequacy and reduced precision of the methods currently utilized in these settings to investigate causes of death (CoDs). The study objective was to validate the use of a minimally invasive autopsy (MIA) approach as an adequate and more acceptable substitute for the complete diagnostic autopsy (CDA) for pediatric CoD investigation in a poor setting.Methods and findingsIn this observational study, the validity of the MIA approach in determining the CoD was assessed in 54 post-neonatal pediatric deaths (age range: ≥1 mo to 15 y) in a referral hospital of Mozambique by comparing the results of the MIA with those of the CDA. Concordance in the category of disease obtained by the two methods was evaluated by the Kappa statistic, and the sensitivity, specificity, and positive and negative predictive values of the MIA diagnoses were calculated.A CoD was identified in all cases in the CDA and in 52/54 (96%) of the cases in the MIA, with infections and malignant tumors accounting for the majority of diagnoses. The MIA categorization of disease showed a substantial concordance with the CDA categorization (Kappa = 0.70, 95% CI 0.49–0.92), and sensitivity, specificity, and overall accuracy were high. The ICD-10 diagnoses were coincident in up to 75% (36/48) of the cases. The MIA allowed the identification of the specific pathogen deemed responsible for the death in two-thirds (21/32; 66%) of all deaths of infectious origin. Discrepancies between the MIA and the CDA in individual diagnoses could be minimized with the addition of some basic clinical information such as those ascertainable through a verbal autopsy or clinical record. The main limitation of the analysis is that both the MIA and the CDA include some degree of expert subjective interpretation.ConclusionsThe MIA showed substantial concordance with CDA for CoD identification in this series of pediatric deaths in Mozambique. This minimally invasive approach, simpler and more readily acceptable than the more invasive CDA, could provide robust data for CoD surveillance, especially in resource-limited settings, which could be helpful for guiding child survival strategies in the future.