Infant mortality and social environment in Georgia: an application of hotspot detection and prioritization

Recent years have witnessed the growth of new information technologies and their applications to various disciplines. The goal of this paper is to demonstrate how the two innovative methods, upper level set scan (ULS) hotspot detection and the multicriteria prioritization scheme, facilitate population health and break new ground in public health surveillance. It is believed that the social environment (i.e. social conditions and social capital) is one of the determinants of human health. Using infant health data and 10 additional indicators of social environment in the 159 counties of Georgia, ULS identified 52 counties that are in double jeopardy (high infant mortality and a high rate of low infant birth weight). The multicriteria ranking scheme suggested that there was no conspicuous spatial cluster of ranking orders, which improved the traditional decision making by visual geographic cluster. Both hotspot detection and ranking methods provided an empirical basis for re-allocating limited resources and several policy implications could be drawn from these analytic results.     

Upper level set scan statistic for detecting arbitrarily shaped hotspots

A declared need is around for geoinformatic surveillance statistical science and software infrastructure for spatial and spatiotemporal hotspot detection. Hotspot means something unusual, anomaly, aberration, outbreak, elevated cluster, critical resource area, etc. The declared need may be for monitoring, etiology, management, or early warning. The responsible factors may be natural, accidental, or intentional. This proof-of-concept paper suggests methods and tools for hotspot detection across geographic regions and across networks. The investigation proposes development of statistical methods and tools that have immediate potential for use in critical societal areas, such as public health and disease surveillance, ecosystem health, water resources and water services, transportation networks, persistent poverty typologies and trajectories, environmental justice, biosurveillance and biosecurity, among others. We introduce, for multidisciplinary use, an innovation of the health-area-popular circle-based spatial and spatiotemporal scan statistic. Our innovation employs the notion of an upper level set, and is accordingly called the upper level set scan statistic, pointing to a sophisticated analytical and computational system as the next generation of the present day popular SaTScan. Success of surveillance rests on potential elevated cluster detection capability. But the clusters can be of any shape, and cannot be captured only by circles. This is likely to give more of false alarms and more of false sense of security. What we need is capability to detect arbitrarily shaped clusters. The proposed upper level set scan statistic innovation is expected to fill this need     

Spatially constrained clustering and upper level set scan hotspot detection in surveillance geoinformatics

We discuss upper level set (ULS) scan as a type of spatially constrained clustering in relation to two ways of imposing the spatial constraint, retrospectively versus progressively. We show that ULS scan produces the same results both ways; whereas two popular clustering techniques, single-linkage and K-means, can yield different results when spatial constraints are imposed retrospectively versus progressively. The ULS scan approach examines spatially connected components of a tessellation as a threshold is moved from the highest level (value) in the data to the lowest level. When the variable of interest on the tessellation is a rate of incidence, then a significance test is available based on binomial or Poisson null models and Monte Carlo techniques. This is a common context for detecting hotspots of diseases in epidemiological work. We also discuss an approach for extending the univariate methodology to accommodate multivariate contexts. Received: September 2005 / Revised: February 2006 This material is based upon work supported by (i) the National Science Foundation under Grant No. 0307010, (ii) the United States Environmental Protection Agency under Grant No. CR-83059301 and (iii) the Pennsylvania Department of Health using Tobacco Settlement Funds under Grant No. ME 01324. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the agencies.     

Detection and delineation of critical areas using echelons and spatial scan statistics with synoptic cellular data

Geographical surveillance for hotspot detection and delineation has become an important area of investigation both in geospatial ecosystem health and in geospatial public health. In order to find critical areas based on synoptic cellular data, geospatial ecosystem health investigations apply recently discovered echelon tools. In order to find elevated rate areas based on synoptic cellular data, geospatial public health investigations apply recently discovered spatial scan statistic tools. The purpose of this paper is to conceptualize a joint role for these together in the spirit of a cross-disciplinary cross-fertilization to accomplish more effective and efficient geographical surveillance for hotspot detection and delineation, and early warning system.     

A capture-recapture model with heterogeneity and behavioural response

We develop the non-parametric maximum likelihood estimator (MLE) of the full M_bh capture-recapture model which utilizes both initial capture and recapture data and permits both heterogeneity (h) between animals and behavioural (b) response to capture. Our MLE procedure utilizes non-parametric maximum likelihood estimation of mixture distributions (Lindsay, 1983; Lindsay and Roeder, 1992) and the EM algorithm (Dempsteret al., 1977). Our MLE estimate provides the first non-parametric estimate of the bivariate capture-recapture distribution.Since non-parametric maximum likelihood estimation exists for submodels M_h (allowing heterogeneity only), Mb (allowing behavioural response only) and M₀ (allowing no changes), we develop maximum likelihood-based model selection, specifically the Akaike information criterion (AIC) (Akaike, 1973). The AIC procedure does well in detecting behavioural response but has difficulty in detecting heterogeneity.     

Continuous dose-response modeling and risk analysis with the gamma and reciprocal gamma distributions

Kodell and West (1993) describe two methods for calculating pointwise upper confidence limits on the risk function with normally distributed responses and using a certain definition of adverse quantitative effect. But Banga et al. (2000) have shown that these normal theory methods break down when applied to skew data. We accordingly develop a risk analysis model and associated likelihood-based methodology when the response follows either a gamma or reciprocal gamma distribution. The model supposes that the shape (index) parameter k of the response distribution is held fixed while the logarithm of the scale parameter is a linear model in terms of the dose level. Existence and uniqueness of the maximum likelihood estimates is established. Asymptotic likelihood-based upper and lower confidence limits on the risk are solutions of the Lagrange equations associated with a constrained optimization problem. Starting values for an iterative solution are obtained by replacing the Lagrange equations by the lowest order terms in their asymptotic expansions. Three methods are then compared for calculating confidence limits on the risk: (i) the aforementioned starting values (LRAL method), (ii) full iterative solution of the Lagrange equations (LREL method), and (iii) bounds obtained using approximate normality of the maximum likelihood estimates with standard errors derived from the information matrix (MLE method). Simulation is used to assess coverage probabilities for the resulting upper confidence limits when the log of the scale parameter is quadratic in the dose level. Results indicate that coverage for the MLE method can be off by as much as 15% points and converges very slowly to nominal coverage levels as the sample size increases. Coverage for the LRAL and LREL methods, on the other hand, is close to nominal levels unless (a) the sample size is small, say N < 25, (b) the index parameter is small, say k 1, and (c) the direction of adversity is to the left for the gamma distribution or to the right for the reciprocal gamma distribution.     

Genetic diversity of aerobic anoxygenic photosynthetic bacteria in open ocean surface waters and upper twilight zones

Aerobic anoxygenic phototrophic bacteria (AAPB) represent a widespread mixotrophic bacterial group in marine ecosystems. Here we investigated AAPB genetic diversity in the surface waters and upper twilight zones of the central Pacific, Atlantic, and Indian oceans by amplifying an AAPB marker gene (pufM, encoding photosynthetic reaction center small subunit) directly from bacterioplankton community DNA. Phylogenetic and statistical analysis of 267 pufM partial sequences in six clone libraries revealed a high diversity pattern in open ocean AAPB communities. Various AAPB subgroups belonging to Alpha- and Gamma-proteobacteria were found in both surface and upper twilight zone waters. In most samples, subgroups in which no pure culture was isolated as yet were predominant. By sampling a wide size range of bacterioplankton (0.22–200 μm) and introducing nested PCR to amplification, we retrieved abundant pufM fragments (136 sequences in 37 OTUs) directly from upper twilight zone samples. AAPB populations in upper twilight zones covered major subgroups found in surface waters and had a slightly lower diversity, higher dominance, and lower GC and GC₃ contents in pufM genes than those in surface AAPB populations. These diversity data combined with previous BChl.a data in upper twilight zones support the hypothesis that AAPB may be present below euphotic zones based on the speculation that AAPB can utilize the dim light in twilight zones as a supplement to energy supply in their heterotrophic lives.     

Local multiplicity adjustments for spatial cluster detection

The spatial scan statistic is a widely applied tool for cluster detection. The spatial scan statistic evaluates the significance of a series of potential circular clusters using Monte Carlo simulation to account for the multiplicity of comparisons. In most settings, the extent of the multiplicity problem varies across the study region. For example, urban areas typically have many overlapping clusters, while rural areas have few. The spatial scan statistic does not account for these local variations in the multiplicity problem. We propose two new spatially-varying multiplicity adjustments for spatial cluster detection, one based on a nested Bonferroni adjustment and one based on local averaging. Geographic variations in power for the spatial scan statistic and the two new statistics are explored through simulation studies, and the methods are applied to both the well-known New York leukemia data and data from a case–control study of breast cancer in Wisconsin.     

A spatial scan statistic for zero-inflated Poisson process

The scan statistic is widely used in spatial cluster detection applications of inhomogeneous Poisson processes. However, real data may present substantial departure from the underlying Poisson process. One of the possible departures has to do with zero excess. Some studies point out that when applied to data with excess zeros, the spatial scan statistic may produce biased inferences. In this work, we develop a closed-form scan statistic for cluster detection of spatial zero-inflated count data. We apply our methodology to simulated and real data. Our simulations revealed that the Scan-Poisson statistic steadily deteriorates as the number of zeros increases, producing biased inferences. On the other hand, our proposed Scan-ZIP and Scan-ZIP+EM statistics are, most of the time, either superior or comparable to the Scan-Poisson statistic.     

Setting of the American oyster Crassostrea virginica in the James River,Virginia, USA: temporal and spatial distribution

Setting of larvae of the oyster Crassostrea virginica was monitored in the James River, Virginia, USA from 1963 to 1980. Setting patterns were similar in two ways to those described prior to 1960 (before the onset of the oyster pathogen Haplosporidium nelsoni (MSX) in Chesapeake Bay): (1) setting intensity (average number of spat per shell) was greater at stations in the lower than upper estuary, and (2) on the average, 60 to 80% of the total annual set at each station occurred during a 6-week period from mid-August through September. However, annual setting intensity from 1963–1980 was lower than previously recorded, and annual sets occurred as a series of discrete pulses rather than continuously throughout the season. Pulses were each approximately 1 to 2 weeks in duration and separated by a period of diminished or no setting. Cross-correlation analysis of annual setting patterns among stations revealed three zones in the James River: the upper estuary and entire southwest side, the lower estuary, and a mid-estuary transition zone. Setting pulses tended to be synchronous at stations within each zone, but occurred 1 to 2 weeks later at stations in downriver than in upriver zones. The location of zones is related to known aspects of water circulation in the James River estuary. Moreover, pulse setting itself may be related to the absence of strong vertical salinity gradients accompanying the fortnightly stratification-destratification process.Contribution No. 1213 from the Virginia Institute of Marine Science, School of Marine Science, The College of William and Mary     

Spatial and space-time scan statistics to detect low rate clusters of sex ratio

Whether general environmental exposures to endocrine disrupting chemicals (including pesticides and dioxin) might induce decreased sex ratios (male/female ratio at birth) is discussed. To address this issue, the authors looked for a space-time clustering test which could detect local areas of significantly low risk, assuming a Bernoulli distribution. As a matter of fact, if the endocrine disruptor hypothesis holds true, and if the sex ratio is a sentinel health event indicative of new reproductive hazards ascribed to environmental factors, then in a given region, either a cluster of low male/female ratio among newborn babies would be expected in the vicinity of polluting municipal solid waste incinerators (MSWIs) (supporting the dioxin hypothesis), or local clusters would be expected in some rural areas where large amounts of pesticides are sprayed. Among cluster detection tests, the spatial scan statistic has been widely used in various applications to scan for areas with high rates, and rarely (if ever) with low rates. Therefore, the goal of this paper was to check the properties of the scan statistics under a given scenario (Bernoulli distribution, search for clusters with low rates) and to assess its added value in addressing the sex ratio issue. This study took place in the Franche-Comté region (France), mainly rural, comprising three main MSWIs, among which only one had high dioxin emissions level in the past. The study population consisted of 192,490 boys and 182,588 girls born during the 1975–1999 period. On the whole, the authors conclude that: (i) spatial and space-time scan statistics provide attractive features to address the sex ratio issue; (ii) sex ratio is not markedly affected across space and does not provide a reliable screening measure for detecting reproductive hazards ascribed to environmental factors.     

Residential radon concentration in the Abruzzo region (Italy): a different perspective for identifying radon prone areas

Indoor radon is an important risk factor for human health. Indeed radon inhalation is considered the second cause of lung cancer after smoking. During the last decades, in many countries huge efforts have been made in order to measuring, mapping and predicting radon levels in dwellings. Various researches have been devoted to identify those areas within the country where high radon concentrations are more likely to be found. Data collected through indoor radon surveys have been analysed adopting various statistical approaches, among which hierarchical Bayesian models and geostatistical tools are worth noting. The essential goal of this paper regards the identification of high radon concentration areas (the so-called radon prone areas) in the Abruzzo Region (Italy). In order to accurately pinpoint zones deserving attention for mitigation purpose, we adopt spatial cluster detection techniques, traditionally employed in epidemiology. As a first step, we assume that indoor radon measurements do not arise from a continuous spatial process; thus the geographic locations of dwellings where the radon measurements have been taken can be viewed as a realization of a spatial point process. Following this perspective, we adopt and compare recent cluster detection techniques: the simulated annealing scan statistic, the case event approach based on distance regression on the selection order and the elliptic spatial scan statistic. The analysis includes data collected during surveys carried out by the Regional Agency for the Environment Protection of Abruzzo (ARTA) in 1,861 random sampled dwellings across 277 municipalities of the Abruzzo region. The radon prone areas detected by the selected approaches are provided along with the summary statistics of the methods. Finally, the methodologies considered in this paper are tested on simulated data in order to evaluate their power and the precision of cluster location detection.     

Direct calculation of likelihood-based benchmark dose levels for quantitative responses

A benchmark dose (BMD) for quantitative responses is a lower confidence limit (LCL) on the effective dose corresponding to a specified risk level r. A commonly adopted method for calculating the BMD is to obtain a pointwise upper confidence curve U(d) on the risk function and then invert this relationship by solving the equation U(d)=r. The solution d is taken to be the BMD. Sciullo et al. (2000) have shown that the coverage achieved by this inversion method is at least as great as the coverage achieved by U (·) but that there is otherwise no general relationship between the two coverage probabilities. The present paper develops a method for direct calculation of the BMD based on the asymptotic distribution of the likelihood ratio statistic. It is further shown that the direct method and the inversion method are equivalent when U (·) is also based on the likelihood ratio. Since the direct method is known to be asymptotically correct, it follows that the LR-based inversion method is also asymptotically correct. However, the direct method is computationally faster and easier to program. Finally, some simulation studies are conducted to assess the small sample coverage probabilities of the direct method when responses follow either a normal or a gamma distribution.     

Community structure and vertical distribution of cyclopoid copepods in the Red Sea

The species abundance, vertical distribution and diurnal vertical migration of cyclopoid copepods was analyzed in the central Red Sea in October–November 1980. Samples were taken to a depth of 450 m with a multiple opening — closing plankton net with 0.1-mm mesh-size. Selected important species were allocated to five different groups according to their depth distributions during daytime. The greatest number of species (9) was found in the lower epipelagic zone (40 to 100 m), below the strong seasonal thermocline. The lowest number of species (1) occurred in the upper part of the upper mesopelagic zone (100 to 250 m), which is characterized by a strong dissolved oxygen gradient. Five species had a bimodal vertical distribution, with dual peak abundances in the epipelagic and upper mesopelagic zones. Distinct differences in distribution patterns were noted between sexes and/or developmental stages. The vertical range of diurnally migrating species was small, usually less than 50 to 100 m. Characteristic diurnal changes in the vertical succession of dominant species occur within the epipelagic zone (0 to 100 m). Species-specific vertical distribution patterns are compared with published data from other areas. A conspicuous difference in the proportion of carcasses was noted between species: small species (<0.5 mm in length) had a much higher proportion of carcasses, usually between 20 and 40% of the total standing stock, than larger ones (<5%). The potential causes of this phenomenon, which may be due to (1) methodological bias, (2) a lower sinking velocity of small carcasses, or (3) a higher mortality rate of small species, are discussed.     

Multiple antibiotic resistance patterns of rhizospheric bacteria isolated from Phragmites australis growing in constructed wetland for distillery effluent treatment

Susceptibility patterns of 12 different antibiotics were investigated against rhizospheric bacteria isolated from Phragmites australis from three different zones i.e. upper (0-5 cm), middle (5-10 cm), lower (10-15 cm) in constructed wetland system with and without distillery effluent. The major pollutants of distillery effluent were phenols, sulphide, heavy metals, and higher levels of biological oxygen demand (BOD), chemical oxygen demand (COD) etc. The antibiotic resistance properties of bacteria were correlated with the heavy metal tolerance (one of distillery pollutant). Twenty-two species from contaminated and seventeen species from non-contaminated site were tested by agar disc-diffusion method. The results revealed that more than 63% of total isolates were resistance towards one or more antibiotics tested from all the three different zones of contaminated sites. The multiple-drug resistance property was shown by total 8 isolates from effluent contaminated region out of which 3 isolates were from upper zone, 3 isolates from middle zone and 2 isolates were from lower zone. Results indicated that isolates from contaminated rhizosphere were found more resistant to antibiotics than isolates from non-contaminated rhizosphere. Further this study produces evidence suggesting that tolerance to antibiotics was acquired by isolates for the adaptation and detoxification of all the pollutants present in the effluent at contaminated site. This consequently facilitated the phytoremediation of effluent, which emerges the tolerance and increases resistance to antibiotics.     

Effectiveness of management zoning designed for flagship species in protecting sympatric species

Flagship species have been used widely as umbrella species (i.e., species with large home range whose protection often provides protection for sympatric species) in the management of China's nature reserves. This conflation of flagship and umbrella species is best represented by the giant panda (Ailuropoda melanoleuca) and other large, endangered mammals designated as conservation targets in site selection and planning of reserves. Few empirical studies have tested the effectiveness of flagship species as surrogates for a broader range of sympatric species. Using extensive camera-trap data, we examined the effectiveness of management zones designated to protect flagship (target) species in conserving sympatric species in 4 wildlife reserves (Gutianshan, Changqing, Laohegou, and Wolong). We tested whether the progression from peripheral to core zones was associated with an increasing habitat association for both target and sympatric species. The distribution patterns of the study species across the zones in each reserve indicated a disparity between management zones and the species’ habitat requirements. Management zone was included in the final model for all target species, and most of them had higher occurrence in core zones relative to less-protected zones, but zone was not a predictor for most of the sympatric species. When management zone was associated with the occurrence of sympatric species, threatened species generally had higher detections in core zones, whereas common species had higher detections outside of the core zone. Our results suggested that reserve planning based on flagship species does not adequately protect sympatric species due to their specialized habitat requirements. We recommend re-examining the effectiveness of management zoning and urge a multispecies and reserve-wide monitoring plan to improve protection of China's wildlife.     

江苏盐城国家级珍禽自然保护区调整及其驱动力分析

在确定了盐城国家级珍禽自然保护区调整原则基础上,提出了该保护区的范围调整和功能区划调整方案.调整后,整个保护区范围由调整前的45.30×104 hm2减至28.42×104 hm2,核心区由调整前的1.74×104 hm2增至2.19×104 hm2,占保护区总面积的7.71%,缓冲区和实验区分别由调整前的4.67×104、38.89×104 hm2变为5.57×104、20.66×104 hm2.从自然条件改变、区域种群动态以及保护区与周边地区协调发展3个方面分析了盐城保护区调整的驱动力.     

Types of larval development in Littorinidae (Gastropoda: Prosobranchia) of the World Ocean,and ecological patterns of their distribution

Relationships between the types of larval development in 4 species of Littorina from British shores and their inhabitancy of different tidal levels were established by Woodward (1909). His data have led to the view that the Littorinidae present a “text-book” example illustrating obligate interrelationships between the distribution of marine bottom invertebrates in certain biotopes and the possession by them of definite types of larval development. Analysis of data describing larval development of 39 species of littorinids from various regions of the World Ocean covering all its climatic zones, from the tropics to the Arctic, accumulated in the literature (Tables 1-5) demonstrates, however, that there exists only a relationship between viviparity and the inhabitancy of supralittoral zones, and between direct development and the inhabitancy of littoral zones. In 34 out of 39 littorinid species studied pelagic development, in various modifications, is present at all tidal levels; it is most common in the supralittoral zone, but not in the sublittoral zone, as has been generally assumed. The data presented in Tables 1-5 confirm the author's opinion (Mileikovsky, 1971, 1973) that the concept of obligate interrelationships between definite types of larvel development in marine benthic invertebrate and their existence in definite biotopes, based on Woodward's scheme, is false and must be rejected.