Generalized index for spatial data sets as a measure of complete spatial randomness

Spatial data sets, generated from a wide range of physical systems can be analyzed by counting the number of objects in a set of bins. Previous work has been limited to equal-sized bins, which are inappropriate for some domains (e.g., circular). We consider a nonequal size bin configuration whereby overlapping or nonoverlapping bins cover the domain. A generalized index, defined in terms of a variance between bin counts, is developed to indicate whether or not a spatial data set, generated from exclusion or nonexclusion processes, is at the complete spatial randomness (CSR) state. Limiting values of the index are determined. Using examples, we investigate trends in the generalized index as a function of density and compare the results with those using equal size bins. The smallest bin size must be much larger than the mean size of the objects. We can determine whether a spatial data set is at the CSR state or not by comparing the values of a generalized index for different bin configurations—the values will be approximately the same if the data is at the CSR state, while the values will differ if the data set is not at the CSR state. In general, the generalized index is lower than the limiting value of the index, since objects do not have access to the entire region due to blocking by other objects. These methods are applied to two applications: (i) spatial data sets generated from a cellular automata model of cell aggregation in the enteric nervous system and (ii) a known plant data distribution.Emily J. Hackett-Jones, Kale J. Davies, Benjamin J. Binder, and Kerry A. Landma

A mechanistic spatio-temporal framework for modelling individual-to-individual transmission—With an application to the 2014-2015 West Africa Ebola outbreak

In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015). Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature, while revealing a significantly shorter distance of transmission. More importantly, in contrast to existing approaches, we are able to perform a more general model prediction that takes into account the susceptible population. Finally, our results show that, given reasonable scenarios, the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging

Scenario Planning for Restorative Justice in Lakeland

Final project for URSP708: Community Planning Studio (Fall 2022). University of Maryland, College Park.This report begins with a discussion of the concept of restorative justice and the three themes that guided and organized our work — community infrastructure, housing and land use, and climate change adaptation and mitigation. Following this introduction of the three guiding themes, the report contains a summary of our analysis of existing conditions, including a review of different planning sectors, a brief history of Lakeland, and a summary of plans and policies that have influenced the course of Lakeland. The next section of the report is a summary of the findings of our various community engagement approaches, including recommendations for future best practices for the city and the Restorative Justice Commission as they continue this work. Finally, we present the three planning scenarios — Status Quo, Reform, and Revolutionary — that envision various alternative futures for Lakeland.City of College Par

Long-Range Autocorrelations of CpG Islands in the Human Genome

In this paper, we use a statistical estimator developed in astrophysics to study the distribution and organization of features of the human genome. Using the human reference sequence we quantify the global distribution of CpG islands (CGI) in each chromosome and demonstrate that the organization of the CGI across a chromosome is non-random, exhibits surprisingly long range correlations (10 Mb) and varies significantly among chromosomes. These correlations of CGI summarize functional properties of the genome that are not captured when considering variation in any particular separate (and local) feature. The demonstration of the proposed methods to quantify the organization of CGI in the human genome forms the basis of future studies. The most illuminating of these will assess the potential impact on phenotypic variation of inter-individual variation in the organization of the functional features of the genome within and among chromosomes, and among individuals for particular chromosomes

Estimating Dengue Transmission Intensity from Case-Notification Data from Multiple Countries

Despite being the most widely distributed mosquito-borne viral infection, estimates of dengue transmission intensity and associated burden remain ambiguous. With advances in the development of novel control measures, obtaining robust estimates of average dengue transmission intensity is key for assessing the burden of disease and the likely impact of interventions.We estimated the force of infection (λ) and corresponding basic reproduction numbers (R0) by fitting catalytic models to age-stratified incidence data identified from the literature. We compared estimates derived from incidence and seroprevalence data and assessed the level of under-reporting of dengue disease. In addition, we estimated the relative contribution of primary to quaternary infections to the observed burden of dengue disease incidence. The majority of R0 estimates ranged from one to five and the force of infection estimates from incidence data were consistent with those previously estimated from seroprevalence data. The baseline reporting rate (or the probability of detecting a secondary infection) was generally low (<25%) and varied within and between countries.As expected, estimates varied widely across and within countries, highlighting the spatio-temporally heterogeneous nature of dengue transmission. Although seroprevalence data provide the maximum information, the incidence models presented in this paper provide a method for estimating dengue transmission intensity from age-stratified incidence data, which will be an important consideration in areas where seroprevalence data are not available

The Framingham Heart Study 100K SNP genome-wide association study resource: overview of 17 phenotype working group reports

Background: The Framingham Heart Study (FHS), founded in 1948 to examine the epidemiology of cardiovascular disease, is among the most comprehensively characterized multi-generational studies in the world. Many collected phenotypes have substantial genetic contributors; yet most genetic determinants remain to be identified. Using single nucleotide polymorphisms (SNPs) from a 100K genome-wide scan, we examine the associations of common polymorphisms with phenotypic variation in this community-based cohort and provide a full-disclosure, web-based resource of results for future replication studies. Methods: Adult participants (n = 1345) of the largest 310 pedigrees in the FHS, many biologically related, were genotyped with the 100K Affymetrix GeneChip. These genotypes were used to assess their contribution to 987 phenotypes collected in FHS over 56 years of follow up, including: cardiovascular risk factors and biomarkers; subclinical and clinical cardiovascular disease; cancer and longevity traits; and traits in pulmonary, sleep, neurology, renal, and bone domains. We conducted genome-wide variance components linkage and population-based and family-based association tests. Results: The participants were white of European descent and from the FHS Original and Offspring Cohorts (examination 1 Offspring mean age 32 ± 9 years, 54% women). This overview summarizes the methods, selected findings and limitations of the results presented in the accompanying series of 17 manuscripts. The presented association results are based on 70,897 autosomal SNPs meeting the following criteria: minor allele frequency ≥ 10%, genotype call rate ≥ 80%, Hardy-Weinberg equilibrium p-value ≥ 0.001, and satisfying Mendelian consistency. Linkage analyses are based on 11,200 SNPs and short-tandem repeats. Results of phenotype-genotype linkages and associations for all autosomal SNPs are posted on the NCBI dbGaP website at http:// www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007. Conclusion: We have created a full-disclosure resource of results, posted on the dbGaP website, from a genome-wide association study in the FHS. Because we used three analytical approaches to examine the association and linkage of 987 phenotypes with thousands of SNPs, our results must be considered hypothesis-generating and need to be replicated. Results from the FHS 100K project with NCBI web posting provides a resource for investigators to identify high priority findings for replication.Molecular and Cellular Biolog

withdrawn 2017 hrs ehra ecas aphrs solaece expert consensus statement on catheter and surgical ablation of atrial fibrillation

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