Relevant bibliographies by topics / Public health surveillance – Indiana – Statistical methods

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters

Academic literature on the topic 'Public health surveillance – Indiana – Statistical methods'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Public health surveillance – Indiana – Statistical methods"

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Alder, S. C. "Monitoring the Health of Populations: Statistical Principles and Methods for Public Health Surveillance." American Journal of Epidemiology 161, no. 2 (2005): 205. http://dx.doi.org/10.1093/aje/kwi024.

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Sanner, Lindsey, Sean Grant, Heather Walter-McCabe, and Ross D. Silverman. "The Challenges of Conducting Intrastate Policy Surveillance: A Methods Note on County and City Laws in Indiana." American Journal of Public Health 111, no. 6 (2021): 1095–98. http://dx.doi.org/10.2105/ajph.2021.306227.

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Policy surveillance is critical in examining the ways law functions as a structural and social determinant of health. To date, little policy surveillance research has focused on examining intrastate variations in the structure and health impact of laws. Intrastate policy surveillance poses unique methodological challenges because of the complex legal architecture within states and inefficient curation of local laws. We discuss our experience with these intrastate policy surveillance challenges in Indiana, a state with 92 counties and several populous cities, a complicated history of home rule,
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Huang, Lan, Ted Guo, Jyoti N. Zalkikar, and Ram C. Tiwari. "A Review of Statistical Methods for Safety Surveillance." Therapeutic Innovation & Regulatory Science 48, no. 1 (2014): 98–108. http://dx.doi.org/10.1177/2168479013514236.

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Berke, Olaf. "Book Review: Monitoring the health of populations: statistical principles and methods for public health surveillance." Statistical Methods in Medical Research 15, no. 3 (2006): 301–2. http://dx.doi.org/10.1191/0962280206sm450br.

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Shook, Lisa M., Christina Bennett Farrell, Cami Mosley, Lori E. Crosby, and Charles T. Quinn. "Leveraging Project Echo Telementoring to Improve Sickle Cell Disease Care in the Midwest: Expanding Provider Education during a Pandemic." Blood 136, Supplement 1 (2020): 21. http://dx.doi.org/10.1182/blood-2020-140705.

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Introduction Approximately 15,000 individuals in the Midwest live with sickle cell disease (SCD), a lifelong, painful disorder with complications and comorbidities. Providers self-report limited knowledge and confidence in treating patients with SCD, leading to limited access to providers knowledgeable about evidence-based management and treatment guidelines and therefore poor health outcomes for patients. Sickle Treatment and Outcomes Research in the Midwest (STORM) is a regional sickle cell network, established to improve outcomes for individuals with SCD living in Indiana, Illinois, Michiga
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DiMaggio, Charles, Sandro Galea, and David Abramson. "Analyzing Postdisaster Surveillance Data: The Effect of the Statistical Method." Disaster Medicine and Public Health Preparedness 2, no. 2 (2008): 119–26. http://dx.doi.org/10.1097/dmp.0b013e31816c7475.

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ABSTRACTData from existing administrative databases and ongoing surveys or surveillance methods may prove indispensable after mass traumas as a way of providing information that may be useful to emergency planners and practitioners. The analytic approach, however, may affect exposure prevalence estimates and measures of association. We compare Bayesian hierarchical modeling methods to standard survey analytic techniques for survey data collected in the aftermath of a terrorist attack. Estimates for the prevalence of exposure to the terrorist attacks of September 11, 2001, varied by the method
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Okolo, Amanda, John M. Soucie, Scott D. Grosse, et al. "Surveillance of Hemophilia in Indiana: A Preliminary Report." Blood 132, Supplement 1 (2018): 3516. http://dx.doi.org/10.1182/blood-2018-99-118849.

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Abstract Background and objectives: Hemophilia is a rare heritable bleeding disorder resulting from missing or deficient levels of factor VIII or factor IX. Hemophilia related complications result in high utilization of health care resources and include severe, debilitating chronic joint disease. In 1998, Soucie et al. published the results of a six-year surveillance study investigating the incidence and prevalence of hemophilia in six U.S. states. The study also described the relationship between mortality and morbidity and each patient's primary source of hematologic care (i.e. whether each
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Oehmke, James Francis, Theresa B. Oehmke, Lauren Nadya Singh, and Lori Ann Post. "Dynamic Panel Estimate–Based Health Surveillance of SARS-CoV-2 Infection Rates to Inform Public Health Policy: Model Development and Validation." Journal of Medical Internet Research 22, no. 9 (2020): e20924. http://dx.doi.org/10.2196/20924.

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Background SARS-CoV-2, the novel coronavirus that causes COVID-19, is a global pandemic with higher mortality and morbidity than any other virus in the last 100 years. Without public health surveillance, policy makers cannot know where and how the disease is accelerating, decelerating, and shifting. Unfortunately, existing models of COVID-19 contagion rely on parameters such as the basic reproduction number and use static statistical methods that do not capture all the relevant dynamics needed for surveillance. Existing surveillance methods use data that are subject to significant measurement
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Rotejanaprasert, Chawarat, and Andrew Lawson. "Bayesian prospective detection of small area health anomalies using Kullback–Leibler divergence." Statistical Methods in Medical Research 27, no. 4 (2016): 1076–87. http://dx.doi.org/10.1177/0962280216652156.

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Early detection of unusual health events depends on the ability to rapidly detect any substantial changes in disease, thus facilitating timely public health interventions. To assist public health practitioners to make decisions, statistical methods are adopted to assess unusual events in real time. We introduce a surveillance Kullback–Leibler measure for timely detection of disease outbreaks for small area health data. The detection methods are compared with the surveillance conditional predictive ordinate within the framework of Bayesian hierarchical Poisson modeling and applied to a case stu
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Senterre, Christelle, Alain Levêque, Brigitte Vanthournout, and Michèle Dramaix. "472 Effect of siblings in a belgian surveillance system of child maltreatment: comparisons of several statistical methods." Injury Prevention 22, Suppl 2 (2016): A171.3—A172. http://dx.doi.org/10.1136/injuryprev-2016-042156.472.

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Dissertations / Theses on the topic "Public health surveillance – Indiana – Statistical methods"

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Reynolds, Sue Bath. "Statistical estimation and changepoint detection methods in public health surveillance." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54906.

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This thesis focuses on assessing and improving statistical methods implemented in two areas of public health research. The first topic involves estimation of national influenza-associated mortality rates via mathematical modeling. The second topic involves the timely detection of infectious disease outbreaks using statistical process control monitoring. For over fifty years, the Centers for Disease Control and Prevention has been estimating annual rates of U.S. deaths attributable to influenza. These estimates have been used to determine costs and benefits associated with influenza prevention
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Han, Sung Won. "Efficient change detection methods for bio and healthcare surveillance." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34828.

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For the last several decades, sequential change point problems have been studied in both the theoretical area (sequential analysis) and the application area (industrial SPC). In the conventional application, the baseline process is assumed to be stationary, and the shift pattern is a step function that is sustained after the shift. However, in biosurveillance, the underlying assumptions of problems are more complicated. This thesis investigates several issues in biosurveillance such as non-homogeneous populations, spatiotemporal surveillance methods, and correlated structures in regional data.
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Chadborn, T. R. "The integration of independent national HIV surveillance datasets and application of statistical methods to enhance their public health utility." Thesis, University College London (University of London), 2012. http://discovery.ucl.ac.uk/1388038/.

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The aims of this thesis were two-fold. Firstly, to develop a robust method to create a fully integrated, national surveillance dataset for human immunodeficiency virus (HIV) infections by linking records from three independent, national HIV case reporting systems. Secondly, to apply statistical techniques, more commonly used in cohort study research, to the integrated dataset to yield more of the potential from the constituent information and increase the public health utility of the data. This demonstrated that an integrated dataset can reduce missing information in each surveillance system a
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Chartree, Jedsada. "Monitoring Dengue Outbreaks Using Online Data." Thesis, University of North Texas, 2014. https://digital.library.unt.edu/ark:/67531/metadc500167/.

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Internet technology has affected humans' lives in many disciplines. The search engine is one of the most important Internet tools in that it allows people to search for what they want. Search queries entered in a web search engine can be used to predict dengue incidence. This vector borne disease causes severe illness and kills a large number of people every year. This dissertation utilizes the capabilities of search queries related to dengue and climate to forecast the number of dengue cases. Several machine learning techniques are applied for data analysis, including Multiple Linear Regressi
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Severns, Christopher Ray. "A comparison of geocoding baselayers for electronic medical record data analysis." Thesis, 2014. http://hdl.handle.net/1805/3841.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>Identifying spatial and temporal patterns of disease occurrence by mapping the residential locations of affected people can provide information that informs response by public health practitioners and improves understanding in epidemiological research. A common method of locating patients at the individual level is geocoding residential addresses stored in electronic medical records (EMRs) using address matching procedures in a geographic information system (GIS). While the process of geocoding is becoming more common in public hea
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Scarpino, Samuel Vincent. "Applying mathematical and statistical methods to the investigation of complex biological questions." Thesis, 2013. http://hdl.handle.net/2152/25994.

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The research presented in this dissertation integrates data and theory to examine three important topics in biology. In the first chapter, I investigate genetic variation at two loci involved in a genetic incompatibility in the genus Xiphophorus. In this genus, hybrids develop a fatal melanoma due to the interaction of an oncogene and its repressor. Using the genetic variation data from each locus, I fit evolutionary models to test for coevolution between the oncogene and the repressor. The results of this study suggest that the evolutionary trajectory of a microsatellite element in the proxim
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Books on the topic "Public health surveillance – Indiana – Statistical methods"

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Tokuhata, George Kazunari. Statewide epidemiologic surveillance: Concept and methodology. Division of Epidemiology Research, Pennsylvania Dept. of Health, 1990.

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M, Teutsch Steven, ed. Statistics in public health: Quantitative approaches to public health problems. Oxford University Press, 1998.

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Anne, Freedman Mary, and National Center for Health Statistics (U.S.), eds. Revisions to Healthy People 2000 baselines. Centers for Disease Control and Prevention, National Center for Health Statistics, 1993.

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On statistical surveillance: Issues of optimality and medical applications. Statistical Research Unit, Göteborg University, 2003.

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United States. General Accounting Office. National Security and International Affairs Division. Global health: Framework for infectious disease surveillance. The Office, 2000.

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United States. General Accounting Office. National Security and International Affairs Division. Global health: Framework for infectious disease surveillance. The Office, [2000], 2000.

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Division, United States General Accounting Office National Security and International Affairs. Global health: Framework for infectious disease surveillance. The Office, 2000.

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National Center for Health Statistics (U.S.), ed. Evaluating public health data systems: A practical approach. [U.S. Dept. of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Center for Health Statistics, 1995.

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Rogerson, Peter. Statistical detection and surveillance of geographic clusters. Chapman & Hall/CRC, 2009.

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Health, Fiji Ministry of. Second generation surveillance surveys of HIV, other STIs, and risk behaviours in 6 Pacific Island countries, 2004-2005. World Health Organization, Western Pacific Regional Office, 2006.

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Book chapters on the topic "Public health surveillance – Indiana – Statistical methods"

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Gan, Linmin, William H. Woodall, and John L. Szarka. "Adaptive Threshold Methods for Monitoring Rates in Public Health Surveillance." In Frontiers in Statistical Quality Control 10. Physica-Verlag HD, 2012. http://dx.doi.org/10.1007/978-3-7908-2846-7_10.

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Yasobant, Sandul, Kranti Suresh Vora, and Ashish Upadhyay. "Geographic Information System Applications in Public Health." In Effective Methods for Modern Healthcare Service Quality and Evaluation. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9961-8.ch007.

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Geographic information systems or geographic information science is a combination of computer-mapping capabilities with additional database management/data analysis tools. GIS is widely used in various sectors such as environmental science, urban planning, agricultural applications etc. Public health is another focus area, where GIS has been used for research and practice areas such as epidemic surveillance and monitoring, among others. The journey of use of GIS in public health spans more than a century and GIS application in public health has evolved from the simple maps to the higher level geostatistical analysis and interactive WebGIS in recent times. GIS is an analytical tool which differs from conventional computer-assisted mapping and any statistical analysis programs in its ability to analyze complex data and visual presentation of spatial data. Specialized GIS techniques such as network analysis, location-allocation models, site selection, transportation models, and geostatistical analysis are well established and used in many developed and developing nations. Unfortunately owing to the high cost of licensed software and specialized skills for advanced data analysis, use of these techniques is limited mainly for the research and by few experts. GIS is proved to be useful for various public health practices and research purposes including epidemiological surveys/investigation, implementation research, program/policy decision making and dissemination of information. The advantage of using GIS is that maps provide an added dimension to data analysis, which helps in visualizing the complex patterns and relationships of public health issues, thus many unanswered questions in public health, can be understood well through use of GIS techniques. Use of GIS in public health is an application area still in its infancy. Wider use of GIS for public health practice such as program planning, implementation and monitoring in addition to building evidence base for the policy making will help reduce inequities in health and provide universal healthcare. Overall, GIS is a helpful and efficient tool especially for public health professionals working in low resource settings. In the future with inclusion of advanced GIS technology like WebGIS can help reach the goal of optimal health care services globally.
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Yan Wong, Lap, Chun Kit Yip, Dao Shen Tan, and Wai Lim Ling. "Artificial Intelligence (AI) in Evidence-Based Approaches to Effectively Respond to Public Health Emergencies." In Evidence-Based Approaches to Effectively Respond to Public Health Emergencies [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.97499.

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Artificial intelligence (AI) techniques have been commonly used to track, predict early warning, forecast trends, and model and measure public health responses. Statistics have traditionally been used to track public health crises. AI-enabled methods, such as machine learning and deep learning–based models, have exploded in popularity recently, complementing statistical approaches. A wide range of medical fields have used various well-developed deep learning algorithms. Surveillance of public health emergencies is one region that has gained greatly from AI advancements in recent years. One of the examples of effectively reacting to public health emergencies is the need for developing AI evidence-based approaches to public health strategies for the scientific community’s response to the COVID-19 pandemic.
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