Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Geography 734: GIS and Society

COURSE OBJECTIVE: Geographic Information Systems (GIS) is widely used in a range of disciplines, and in public and private sector. Due to its popularity, it is a multibillion dollar global business. In order to be proficient in it, one not only needs to understand the technology, but also the science behind the technology. This course explores a primary research agenda in GIScience, that of GIS and Society. This research agenda explores the interconnected relationship between the society and GIS, and explores the implications and impacts of such a relationship. Within the GIS and Society body of literature (as highlighted by the University Consortium of Geographic Information Science), the following questions have been raised: In what ways will GIS actually affect and alter the society it is intended to represent and serve? How can various conceptions and representations of space, not based on traditional map formats or geometric views, be embedded within a GIS? Is GIS more appropriate for some cultures than others? Can GIS be developed to reflect complex and ambiguous perceptions of social and physical space? How will GIS affect the relationships among and within government agencies, and between them and the various citizen groups concerned with the environment, property rights, and advocating the needs of local communities? What are the interpersonal implications of GIS? Can GIS provide citizens with an increased ability to monitor and hold government accountable for proposals and actions? Will GIS provide citizens with an understanding of their rights and interests in land? How accessible will spatial data and related GIS analysis tools be to all parts of society? Can GIS be used to increase participation in public decision making? (http://www.ucgis.org). This course aims to answer some of these questions and intends to create a critical awareness of the hidden implications within GIS technology. This course is organized as a seminar, with weekly readings and reflection papers

Politics of scale and networks of association in public participation GIS

The public participation geographic information systems (PPGIS) research agenda has explored the issue of equitable access and use of geographic information systems (GIS) and spatial data among traditionally marginalized citizens, in order to facilitate effective citizen participation in inner-city revitalization activities. However, prior research indicates that PPGIS is a complex process, with uneven outcomes. The author contends that such unevenness can be explained by use of a new theoretical framework drawn from the literature of politics of scale and networks. The author contends that the PPGIS process occurs in ‘spaces of dependence’, containing localized social relations and place-specific conditions. The politics of securing this space leads to the creation of ‘spaces of engagement’ at multiple scales. Within these spaces, networks of association evolve to connect multiple actors from public and private sectors with community organizations. Such networks can contain structural inequities, hierarchical dominance, and fluctuating resources. But these networks also transcend political boundaries and are dynamic and flexible, enabling individuals to manipulate and modify them. In trying to control the revitalization agendas and the material resources required, the actors and community organizations construct politics of scale. For some community organizations, such scalar politics and creative alliances with critical actors allow them to navigate territorially scaled networks of power skillfully in order to gain an effective voice in decisionmaking activities. But other community organizations lag behind, and are not able to form relationships in order to secure their urban space. By the use of new empirical data, coupled with a new theoretical framework, the author aims to contribute both to greater theorization and to better understanding of the uneven and contradictory nature of PPGIS processes.

Spatial Analysis of Disinformation in COVID-19 Related Tweets

COVID-19 has emerged as a global pandemic caused by its highly transmissible nature during the incubation period. In the absence of vaccination, containment is seen as the best strategy to stop virus diffusion. However, public awareness has been adversely affected by discourses in social media that have downplayed the severity of the virus and disseminated false information. This article investigates COVID-19 related Twitter activity in May 2020 to examine the origin and nature of disinformation and its relationship with the COVID-19 incidence rate at the state and county level. A geodatabase of all geotagged COVID-19 related tweets was compiled. Multiscale Geographically Weighted Regression was employed to examine the association between social media activity, population, and the spatial variability of disease incidence. Findings suggest that MGWR could explain 96.7% of the variations, and content analysis indicates a strong spatial relationship between social media activity and known cases of Covid-19. Discourse analysis was conducted on tweets to index tweets downplaying the pandemic or disseminating disinformation. Findings suggest that states where twitter users spread more disinformation and showed more resistance to pandemic management measures in May, have experienced a surge in the number of cases in July

Geospatial analysis of misinformation in COVID-19 related tweets

COVID-19 has emerged as a global pandemic caused by its highly transmissible nature during the incubation period. In the absence of vaccination, containment is seen as the best strategy to stop virus diffusion. However, public awareness has been adversely affected by discourses in social media that have downplayed the severity of the virus and disseminated false information. This article investigates COVID-19 related Twitter activity in May and June 2020 to examine the origin and nature of misinformation and its relationship with the COVID-19 incidence rate at the state and county level. A geodatabase of all geotagged COVID-19 related tweets was compiled. Multiscale Geographically Weighted Regression was employed to examine the association between social media activity and the spatial variability of disease incidence. Findings suggest that MGWR could explain 80% of the COVID-19 incidence rate variations indicating a strong spatial relationship between social media activity and spread of the Covid-19 virus. Discourse analysis was conducted on tweets to index tweets downplaying the pandemic or disseminating misinformation. Findings indicate that sites of Twitter misinformation showed more resistance to pandemic management measures in May and June 2020 later experienced a rise in the number of cases in July

Impact of the COVID-19 Pandemic on Opioid Overdose Deaths: a Spatiotemporal Analysis

The effects of the opioid crisis have varied across diverse and socioeconomically defined urban communities, due in part to widening health disparities. The onset of the COVID-19 pandemic has coincided with a spike in drug overdose deaths in the USA. However, the extent to which the impact of the pandemic on overdose deaths has varied across different demographics in urban neighborhoods is unclear. We examine the influence of COVID-19 pandemic on opioid overdose deaths through spatiotemporal analysis techniques. Using Milwaukee County, Wisconsin as a study site, we used georeferenced opioid overdose data to examine the locational and demographic differences in overdose deaths over time (2017–2020). We find that the pandemic significantly increased the monthly overdose deaths. The worst effects were seen in the poor, urban neighborhoods, affecting Black and Hispanic communities. However, more affluent, suburban White communities also experienced a rise in overdose deaths. A better understanding of contributing factors is needed to guide interventions at the local, regional, and national scales