A poisson regression approach for modelling spatial autocorrelation between geographically referenced observations

Abstract Background Analytic methods commonly used in epidemiology do not account for spatial correlation between observations. In regression analyses, omission of that autocorrelation can bias parameter estimates and yield incorrect standard error estimates. Methods We used age standardised incidence ratios (SIRs) of esophageal cancer (EC) from the Babol cancer registry from 2001 to 2005, and extracted socioeconomic indices from the Statistical Centre of Iran. The following models for SIR were used: (1) Poisson regression with agglomeration-specific nonspatial random effects; (2) Poisson regression with agglomeration-specific spatial random effects. Distance-based and neighbourhood-based autocorrelation structures were used for defining the spatial random effects and a pseudolikelihood approach was applied to estimate model parameters. The Bayesian information criterion (BIC), Akaike's information criterion (AIC) and adjusted pseudo R2, were used for model comparison. Results A Gaussian semivariogram with an effective range of 225 km best fit spatial autocorrelation in agglomeration-level EC incidence. The Moran's I index was greater than its expected value indicating systematic geographical clustering of EC. The distance-based and neighbourhood-based Poisson regression estimates were generally similar. When residual spatial dependence was modelled, point and interval estimates of covariate effects were different to those obtained from the nonspatial Poisson model. Conclusions The spatial pattern evident in the EC SIR and the observation that point estimates and standard errors differed depending on the modelling approach indicate the importance of accounting for residual spatial correlation in analyses of EC incidence in the Caspian region of Iran. Our results also illustrate that spatial smoothing must be applied with care.</p

Ecological Determinants of Highly Pathogenic Avian Influenza (H5N1) Outbreaks in Bangladesh

BACKGROUND: The agro-ecology and poultry husbandry of the south Asian and south-east Asian countries share common features, however, with noticeable differences. Hence, the ecological determinants associated with risk of highly pathogenic avian influenza (HPAI-H5N1) outbreaks are expected to differ between Bangladesh and e.g., Thailand and Vietnam. The primary aim of the current study was to establish ecological determinants associated with the risk of HPAI-H5N1 outbreaks at subdistrict level in Bangladesh. The secondary aim was to explore the performance of two different statistical modeling approaches for unmeasured spatially correlated variation. METHODOLOGY/PRINCIPAL FINDINGS: An ecological study at subdistrict level in Bangladesh was performed with 138 subdistricts with HPAI-H5N1 outbreaks during 2007-2008, and 326 subdistricts with no outbreaks. The association between ecological determinants and HPAI-H5N1 outbreaks was examined using a generalized linear mixed model. Spatial clustering of the ecological data was modeled using 1) an intrinsic conditional autoregressive (ICAR) model at subdistrict level considering their first order neighbors, and 2) a multilevel (ML) model with subdistricts nested within districts. Ecological determinants significantly associated with risk of HPAI-H5N1 outbreaks at subdistrict level were migratory birds' staging areas, river network, household density, literacy rate, poultry density, live bird markets, and highway network. Predictive risk maps were derived based on the resulting models. The resulting models indicate that the ML model absorbed some of the covariate effect of the ICAR model because of the neighbor structure implied in the two different models. CONCLUSIONS/SIGNIFICANCE: The study identified a new set of ecological determinants related to river networks, migratory birds' staging areas and literacy rate in addition to already known risk factors, and clarified that the generalized concept of free grazing duck and duck-rice cultivation interacted ecology are not significant determinants for Bangladesh. These findings will refine current understanding of the HPAI-H5N1 epidemiology in Bangladesh

The spatial distribution of esophageal and gastric cancer in Caspian region of Iran: An ecological analysis of diet and socio-economic influences

Recent studies have suggested a systematic geographic pattern of esophageal cancer (EC) and gastric cancer (GC) incidence in the Caspian region of Iran. The aims of this study were to investigate the association between these cancers and the region's dietary and socioeconomic risk factors and to map EC and GC after adjustment for the risk factors and the removal of random and geographic variations from area specific age standardised incidence ratios (SIRs)

Elevated dry-season malaria prevalence associated with fine-scale spatial patterns of environmental risk: a case–control study of children in rural Malawi

Abstract Background Understanding the role of local environmental risk factors for malaria in holo-endemic, poverty-stricken settings will be critical to more effectively implement- interventions aimed at eventual elimination. Household-level environmental drivers of malaria risk during the dry season were investigated in rural southern Malawi among children < five years old in two neighbouring rural Traditional Authority (TA) regions dominated by small-scale agriculture. Methods Ten villages were randomly selected from TA Sitola (n = 6) and Nsamala (n = 4). Within each village, during June to August 2011, a census was conducted of all households with children under-five and recorded their locations with a geographic position system (GPS) device. At each participating house, a nurse administered a malaria rapid diagnostic test (RDT) to children under five years of age, and a questionnaire to parents. Environmental data were collected for each house, including land cover within 50-m radius. Variables found to be significantly associated with P. falciparum infection status in bivariate analysis were included in generalized linear models, including multivariate logistic regression (MLR) and multi-level multivariate logistic regression (MLLR). Spatial clustering of RDT status, environmental factors, and Pearson residuals from MLR and MLLR were analysed using the Getis-Ord Gi* statistic. Results Of 390 children enrolled from six villages in Sitola (n = 162) and four villages in Nsamala (n = 228), 45.6% tested positive (n = 178) for Plasmodium infection by RDT. The MLLR modelled the statistical relationship of Plasmodium positives and household proximity to agriculture ( 2.58, p < 0.01) predominantly within TA Sitola, while residuals from MLLR showed no such clustering. Conclusion This study provides evidence for significant, dry-season heterogeneity of malaria prevalence strongly linked to peridomestic land use, and particularly of elevated risk associated with nearby crop production.http://deepblue.lib.umich.edu/bitstream/2027.42/112703/1/12936_2013_Article_3017.pd

Intraurban variations in adult mortality in a large Latin American City

Abstract Urbanization is high and growing in low- and middle-income countries, but intraurban variations in adult health have been infrequently examined. We used spatial analysis methods to investigate spatial variation in total, cardiovascular disease, respiratory disease, and neoplasm adult mortality in Buenos Aires, Argentina, a large city within a middle-income country in Latin America. Conditional autoregressive models were used to examine the contribution of socioeconomic inequalities to the spatial patterning observed. Spatial autocorrelation was present in both men and women for total deaths, cardiovascular deaths, and other causes of death (Moran’s Is ranging from 0.15 to 0.37). There was some spatial autocorrelation for respiratory deaths, which was stronger in men than in women. Neoplasm deaths were not spatially patterned. Socioeconomic disadvantage explained some of this spatial patterning and was strongly associated with death from all causes except respiratory deaths in women and neoplasms in men and women [relative rates (RR) for 90th vs 10th percentile of percent of adults with incomplete high school and 95% confidence intervals: 1.23 and 1.09–1.39 vs 1.24 and 1.08–1.42 for total deaths in men and women, respectively; 1.36 and 1.15–1.60 vs 1.22 and 1.01–1.47 for cardiovascular deaths; 1.21 and 0.97–1.52 vs 1.07 and 0.85–1.34 for respiratory deaths; 0.94 and 0.85–1.04 vs 1.03 and 0.87–1.22 for neoplasms; and 1.49 and 1.20–1.85 vs 1.63 and 1.31–2.03 for other deaths].There is substantial intraurban variation in risk of death within cities. This spatial variability was present for multiple causes of death and is partly explained by the spatial patterning of socioeconomic disadvantage. Our results highlight the pervasive role of space and social inequalities in shaping life and death within large cities.http://deepblue.lib.umich.edu/bitstream/2027.42/57778/1/Intraurban variations in Adult Mortality in a large Latin American City.pd

Risk mapping of Rinderpest sero-prevalence in Central and Southern Somalia based on spatial and network risk factors

The Somali livestock production system is oriented towards domestic trade and export with seasonal movement patterns of herds/flocks in search of water and pasture and towards export points. The objective of the study is to develop a predictive spatial model of presence of rinderpest.Habka loo diyaariyo xoola soomaliyeed ee loogu talagalay in lagu iibiyo dalka gudihiisa ama dibaddiisa, iyagoo xoolahaas loo kaxaynaayo hadba meeshi biyo iyo baad leh iyo goobtii laga dhoofinayaba. Qasdiga daraasaadkaani wuxuu yahay sidii loo hormarin lahaa habka looga hortegi lahaa cudurrada faafa ee lo'da.Il sistema di produzione di bestiame somalo è orientato verso il commercio interno e l'esportazione con movimenti stagionali delle mandrie/greggi in cerca di acqua e pascoli e verso i luoghi di esportazione. L'obiettivo dello studio è quello di sviluppare un modello spaziale predittivo della presenza di peste bovina

Risk mapping of Rinderpest sero-prevalence in Central and Southern Somalia based on spatial and network risk factors

<p>Abstract</p> <p>Background</p> <p>In contrast to most pastoral systems, the Somali livestock production system is oriented towards domestic trade and export with seasonal movement patterns of herds/flocks in search of water and pasture and towards export points. Data from a rinderpest survey and other data sources have been integrated to explore the topology of a contact network of cattle herds based on a spatial proximity criterion and other attributes related to cattle herd dynamics. The objective of the study is to integrate spatial mobility and other attributes with GIS and network approaches in order to develop a predictive spatial model of presence of rinderpest.</p> <p>Results</p> <p>A spatial logistic regression model was fitted using data for 562 point locations. It includes three statistically significant continuous-scale variables that increase the risk of rinderpest: home range radius, herd density and clustering coefficient of the node of the network whose link was established if the sum of the home ranges of every pair of nodes was equal or greater than the shortest distance between the points. The sensitivity of the model is 85.1% and the specificity 84.6%, correctly classifying 84.7% of the observations. The spatial autocorrelation not accounted for by the model is negligible and visual assessment of a semivariogram of the residuals indicated that there was no undue amount of spatial autocorrelation. The predictive model was applied to a set of 6176 point locations covering the study area. Areas at high risk of having serological evidence of rinderpest are located mainly in the coastal districts of Lower and Middle Juba, the coastal area of Lower Shabele and in the regions of Middle Shabele and Bay. There are also isolated spots of high risk along the border with Kenya and the southern area of the border with Ethiopia.</p> <p>Conclusions</p> <p>The identification of point locations and areas with high risk of presence of rinderpest and their spatial visualization as a risk map will be useful for informing the prioritization of disease surveillance and control activities for rinderpest in Somalia. The methodology applied here, involving spatial and network parameters, could also be applied to other diseases and/or species as part of a standardized approach for the design of risk-based surveillance activities in nomadic pastoral settings.</p

A review of methods for modelling both Gaussian and Non-Gaussian longitudinal data with application.

M. Sc. University of KwaZulu-Natal, Pietermaritzburg 2015.The study of longitudinal data plays an integral role in medicine, epidemiology, social science, biomedical and health sciences research where repeated measurements are obtained over time for each individual. Generally, the interest is in the dependence of the outcome variable on the covariates. The analysis of the data from longitudinal studies requires special techniques, which take into account the fact that the repeated measurements within one individual are correlated. In review of this work, we explore modern developments in the area of linear and nonlinear generalized mixed-effects regression models and various alternatives including generalized estimating equations for analysis of longitudinal data and correspondence analysis (CA). Methods are described for continuous and normally distributed as well as categorical variables. We apply this theory to the analysis of complete longitudinal data from National Institute of Environment Health Sciences (NIEHS) focusing on the relationship between blood lead levels (PbB) and some associated covariates. The results show that Placebo-treated children had a gradual (occuring) decrease in blood lead level. Succimer-treated children had an abrupt (unexpected) drop in blood lead level, followed by rebound. The average mean blood lead level of the succimer-treated children after initiation of treatment was 19.14 μg/dL lower than that of placebo-treated children. After randomization, blood lead levels had fallen by similar amounts in both chelated and placebo children, despite the immediate drops in the chelated group; there was no association between change in blood lead level and change in cognitive test score. Blood lead levels continued to fall