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Jeffery C.,Monitoring and Evaluation Technical Assistance and Research Group | Ozonoff A.,Boston Childrens Hospital | White L.F.,Boston University | Pagano M.,Harvard University
International Journal of Biostatistics | Year: 2013

In this article, we consider the problem of comparing the distribution of observations in a planar region to a pre-specified null distribution. Our motivation is a surveillance setting where we map locations of incident disease, aiming to monitor these data over time, to locate potential areas of high/low incidence so as to direct public health actions. We propose a non-parametric approach to distance-based disease risk mapping inspired by tomographic imaging. We consider several one-dimensional projections via the observed distribution of distances to a chosen fixed point; we then compare this distribution to that expected under the null and average these comparisons across projections to compute a relative-risk-like score at each point in the region. The null distribution can be established from historical data. Scores are displayed on the map using a color scale. In addition, we give a detailed description of the method along with some desirable theoretical properties. To further assess the performance of this method, we compare it to the widely used log ratio of kernel density estimates. As a performance metric, we evaluate the accuracy to locate simulated spatial clusters superimposed on a uniform distribution in the unit disk. Results suggest that both methods can adequately locate this increased risk but each relies on an appropriate choice of parameters. Our proposed method, distancebased mapping (DBM), can also generalize to arbitrary metric spaces and/or high-dimensional data.

Valadez J.J.,Monitoring and Evaluation Technical Assistance and Research Group | Jeffery C.,Monitoring and Evaluation Technical Assistance and Research Group | Davis R.,Monitoring and Evaluation Technical Assistance and Research Group | Ouma J.,Management science for Health | And 2 more authors.
PLoS ONE | Year: 2014

A major strategy for preventing transmission of HIV and other STIs is the consistent use of condoms during sexual intercourse. Condom use among youths is particularly important to reduce the number of new cases and the national prevalence. Condom use has been often promoted by the Uganda National AIDS Commission. Although a number of studies have established an association between condom use at one's sexual debut and future condom use, few studies have explored this association over time, and whether the results are generalizable across multiple locations. This multi time point, multi district study assesses the relationship between sexual debut and condom use and consistent use of condoms thereafter. Uganda has used Lot Quality Assurance Sampling surveys since 2003 to monitor district level HIV programs and improve access to HIV health services. This study includes 4518 sexually active youths interviewed at five time points (2003-2010) in up to 23 districts located across Uganda. Using logistic regression, we measured the association of condom use at first sexual intercourse on recent condom usage, controlling for several factors including: age, sex, education, marital status, age at first intercourse, geographical location, and survey year. The odds of condom use at last intercourse, using a condom at last intercourse with a non-regular partner, and consistently using a condom are, respectively, 9.63 (95%WaldCI = 8.03-11.56), 3.48 (95%WaldCI = 2.27-5.33), and 11.12 (95%WaldCI = 8.95-13.81) times more likely for those individuals using condoms during their sexual debut. These values did not decrease by more than 20% when controlling for potential confounders. The results suggest that HIV prevention programs should encourage condom use among youth during sexual debut. Success with this outcome may have a lasting influence on preventing HIV and other STIs later in life. © 2014 Valadez et al.

Jeffery C.,Monitoring and Evaluation Technical assistance and Research group | Ozonoff A.,Harvard University | Pagano M.,Harvard University
International Journal of Health Geographics | Year: 2014

Background: Spatial data on cases are available either in point form (e.g. longitude/latitude), or aggregated by an administrative region (e.g. zip code or census tract). Statistical methods for spatial data may accommodate either form of data, however the spatial aggregation can affect their performance. Previous work has studied the effect of spatial aggregation on cluster detection methods. Here we consider geographic health data at different levels of spatial resolution, to study the effect of spatial aggregation on disease mapping performance in locating subregions of increased disease risk.Methods: We implemented a non-parametric disease distance-based mapping (DBM) method to produce a smooth map from spatially aggregated childhood leukaemia data. We then simulated spatial data under controlled conditions to study the effect of spatial aggregation on its performance. We used an evaluation method based on ROC curves to compare performance of DBM across different geographic scales.Results: Application of DBM to the leukaemia data illustrates the method as a useful visualization tool. Spatial aggregation produced expected degradation of disease mapping performance. Characteristics of this degradation, however, varied depending on the interaction between the geographic extent of the higher risk area and the level of aggregation. For example, higher risk areas dispersed across several units did not suffer as greatly from aggregation. The choice of centroids also had an impact on the resulting mapping.Conclusions: DBM can be implemented for continuous and discrete spatial data, but the resulting mapping can lose accuracy in the second setting. Investigation of the simulations suggests a complex relationship between performance loss, geographic extent of spatial disturbances and centroid locations. Aggregation of spatial data destroys information and thus impedes efforts to monitor these data for spatial disturbances. The effect of spatial aggregation on cluster detection, disease mapping, and other useful methods in spatial epidemiology is complex and deserves further study. © 2014 Jeffery et al.; licensee BioMed Central Ltd.

Olanrewaju A.D.,Monitoring and Evaluation Technical Assistance and Research Group | Jeffery C.,Monitoring and Evaluation Technical Assistance and Research Group | Crossland N.,Monitoring and Evaluation Technical Assistance and Research Group | Valadez J.J.,Monitoring and Evaluation Technical Assistance and Research Group
PLoS ONE | Year: 2015

Objectives: This study estimates the proportion of Orphans and Vulnerable Children (OVC) attending school in 89 districts of Uganda from 2011-2013 and investigates the factors influencing OVC access to education among this population. Methods: This study used secondary survey data from OVCs aged 5-17 years, collected using Lot Quality Assurance Sampling in 87 Ugandan districts over a 3-year period (2011-2013). Estimates of OVC school attendance were determined for the yearly time periods. Logistic regression was used to investigate the factors influencing OVC access to education. Results: 19,354 children aged 5-17 were included in the analysis. We estimated that 79.1% (95% CI: 78.5% - 79.7%) of OVCs attended school during the 3-year period. Logistic regression revealed the odds of attending school were lower among OVCs from Western (OR 0.88; 95% CI: 0.79-0.99) and Northern (OR 0.64; 95% CI: 0.56-0.73) regions compared to the Central region. Female OVCs had a significantly higher odds of attending school (OR 1.09; 95% CI: 1.02-1.17) compared to their male counterparts. When adjusting for all variables simultaneously, we found the odds of school attendance reduced by 12% between 2011 and 2012 among all OVCs (OR 0.88; 95% CI: 0.81-0.97). Conclusion: Our findings reinforce the need to provide continuing support to OVC in Uganda, ensuring they have the opportunity to attain an education. The data indicate important regional and gender variation that needs to be considered for support strategies and in social policy. The results suggest the need for greater local empowerment to address the needs of OVCs. We recommend further research to understand why OVC access to education and attendance varies between regions and improvement of district level mapping of OVC access to education, and further study to understand the particular factors impacting the lower school attendance of male OVCs. Copyright: © 2015 Olanrewaju et al.

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