Analysing and Monitoring Surveillance Data of Mumps in Bulgaria

2000 Mathematics Subject Classification: 62P10.

Legibility, privacy and creativity:linked data in a surveillance society

This paper looks at the issue of privacy and anonymity through the prism of Scott's concept of legibility i.e. the desire of the state to obtain an ever more accurate mapping of its domain and the actors in its domain. We argue that privacy was absent in village life in the past, and it has arisen as a temporary phenomenon arising from the lack of appropriate technology to make all life in the city legible. Cities have been the loci of creativity for the major part of human civilisation. There is something specific about the illegibility of cities which facilitates creativity and innovation. By providing the technology to catalogue and classify all objects and ideas around us, this leads to a consideration of semantic web technologies, Linked Data and the Internet of Things as unwittingly furthering this ever greater legibility. There is a danger that the over description of a domain will lead to a loss in creativity and innovation. We conclude by arguing that our prime concern must be to preserve illegibility because the survival of some form, any form, of civilisation depends upon it.

Introduction to this special issue on geoinformatics for environmental surveillance

Editorial

Biologically inspired features for scene classification in video surveillance

Inspired by human visual cognition mechanism, this paper first presents a scene classification method based on an improved standard model feature. Compared with state-of-the-art efforts in scene classification, the newly proposed method is more robust, more selective, and of lower complexity. These advantages are demonstrated by two sets of experiments on both our own database and standard public ones. Furthermore, occlusion and disorder problems in scene classification in video surveillance are also first studied in this paper. © 2010 IEEE.

A Bayesian neural network algorithm identifies patients in whom post-EVAR surveillance may be unnecessary

Lifelong surveillance is not cost-effective after endovascular aneurysm repair (EVAR), but is required to detect aortic complications which are fatal if untreated (type 1/3 endoleak, sac expansion, device migration). Aneurysm morphology determines the probability of aortic complications and therefore the need for surveillance, but existing analyses have proven incapable of identifying patients at sufficiently low risk to justify abandoning surveillance. This study aimed to improve the prediction of aortic complications, through the application of machine-learning techniques. Patients undergoing EVAR at 2 centres were studied from 2004–2010. Aneurysm morphology had previously been studied to derive the SGVI Score for predicting aortic complications. Bayesian Neural Networks were designed using the same data, to dichotomise patients into groups at low- or high-risk of aortic complications. Network training was performed only on patients treated at centre 1. External validation was performed by assessing network performance independently of network training, on patients treated at centre 2. Discrimination was assessed by Kaplan-Meier analysis to compare aortic complications in predicted low-risk versus predicted high-risk patients. 761 patients aged 75 +/− 7 years underwent EVAR in 2 centres. Mean follow-up was 36+/− 20 months. Neural networks were created incorporating neck angu- lation/length/diameter/volume; AAA diameter/area/volume/length/tortuosity; and common iliac tortuosity/diameter. A 19-feature network predicted aor- tic complications with excellent discrimination and external validation (5-year freedom from aortic complications in predicted low-risk vs predicted high-risk patients: 97.9% vs. 63%; p < 0.0001). A Bayesian Neural-Network algorithm can identify patients in whom it may be safe to abandon surveillance after EVAR. This proposal requires prospective study.

Digital surveillance based on video CODEC System-on-a-Chip (SoC) platforms

Today, most conventional surveillance networks are based on analog system, which has a lot of constraints like manpower and high-bandwidth requirements. It becomes the barrier for today's surveillance network development. This dissertation describes a digital surveillance network architecture based on the H.264 coding/decoding (CODEC) System-on-a-Chip (SoC) platform. The proposed digital surveillance network architecture includes three major layers: software layer, hardware layer, and the network layer. The following outlines the contributions to the proposed digital surveillance network architecture. (1) We implement an object recognition system and an object categorization system on the software layer by applying several Digital Image Processing (DIP) algorithms. (2) For better compression ratio and higher video quality transfer, we implement two new modules on the hardware layer of the H.264 CODEC core, i.e., the background elimination module and the Directional Discrete Cosine Transform (DDCT) module. (3) Furthermore, we introduce a Digital Signal Processor (DSP) sub-system on the main bus of H.264 SoC platforms as the major hardware support system for our software architecture. Thus we combine the software and hardware platforms to be an intelligent surveillance node. Lab results show that the proposed surveillance node can dramatically save the network resources like bandwidth and storage capacity.

Biopolitical Implications of the Surveillance, Spectacle, and Performance of AIDS Education in Rural China

This conceptual study explores China’s reaction to the AIDS crisis using a Foucauldian concept of biopolitics in order to theorize the implications of AIDS education in the culture of rural China in terms of the surveillance, spectacle, and discipline of biopolitics.

Epidemiologic Features of Vulvovaginal Candidiasis among Reproductive-Age Women in India

Background. Vulvovaginal candidiasis is characterized by curd-like vaginal discharge and itching, and is associated with considerable health and economic costs. Materials and Methods. We examined the incidence, prevalence, and risk factors for vulvovaginal candidiasis among a cohort of 898 women in south India. Participants completed three study visits over six months, comprised of a structured interview and a pelvic examination. Results. The positive predictive values for diagnosis of vulvovaginal candidiasis using individual signs or symptoms were low (<19%). We did not find strong evidence for associations between sociodemographic characteristics and the prevalence of vulvovaginal candidiasis. Women clinically diagnosed with bacterial vaginosis had a higher prevalence of vulvovaginal candidiasis (Prevalence 12%, 95% CI 8.2, 15.8) compared to women assessed to be negative for bacterial vaginosis (Prevalence 6.5%, 95% 5.3, 7.6); however, differences in the prevalence of vulvovaginal candidiasis were not observed by the presence or absence of laboratory-confirmed bacterial vaginosis. Conclusions. For correct diagnosis of vulvovaginal candidiasis, laboratory confirmation of infection with Candida is necessary as well as assessment of whether the discharge has been caused by bacterial vaginosis. Studies are needed of women infected with Candida yeast species to determine the risk factors for yeast’s overgrowth.

Psychosocial morbidity in women with abnormal cervical cytology managed by cytological surveillance or initial colposcopy : longitudinal analysis from the TOMBOLA randomised trial

We are grateful for the co-operation and assistance that we received from NHS staff in the co-ordinating centres and clinical sites. We thank the women who participated in TOMBOLA. The TOMBOLA trial was supported by the Medical Research Council (G9700808) and the NHS in England and Scotland. The TOMBOLA Group comprises the following: Grant-holders: University of Aberdeen and NHS Grampian, Aberdeen, Scotland: Maggie Cruickshank, Graeme Murray, David Parkin, Louise Smart, Eric Walker, Norman Waugh (Principal Investigator 2004–2008) University of Nottingham and Nottingham NHS, Nottingham, England: Mark Avis, Claire Chilvers, Katherine Fielding, Rob Hammond, David Jenkins, Jane Johnson, Keith Neal, Ian Russell, Rashmi Seth, Dave Whynes University of Dundee and NHS Tayside, Dundee, Tayside: Ian Duncan, Alistair Robertson (deceased) University of Ottawa, Ottawa, Canada: Julian Little (Principal Investigator 1999–2004) National Cancer Registry, Cork, Ireland: Linda Sharp Bangor University, Bangor, Wales: Ian Russell University of Hull, Hull, England: Leslie G Walker Staff in clinical sites and co-ordinating centres Grampian Breda Anthony, Sarah Bell, Adrienne Bowie, Katrina Brown (deceased), Joe Brown, Kheng Chew, Claire Cochran, Seonaidh Cotton, Jeannie Dean, Kate Dunn, Jane Edwards, David Evans, Julie Fenty, Al Finlayson, Marie Gallagher, Nicola Gray, Maureen Heddle, Alison Innes, Debbie Jobson, Mandy Keillor, Jayne MacGregor, Sheona Mackenzie, Amanda Mackie, Gladys McPherson, Ike Okorocha, Morag Reilly, Joan Rodgers, Alison Thornton, Rachel Yeats Tayside Lindyanne Alexander, Lindsey Buchanan, Susan Henderson, Tine Iterbeke, Susanneke Lucas, Gillian Manderson, Sheila Nicol, Gael Reid, Carol Robinson, Trish Sandilands Nottingham Marg Adrian, Ahmed Al-Sahab, Elaine Bentley, Hazel Brook, Claire Bushby, Rita Cannon, Brenda Cooper, Ruth Dowell, Mark Dunderdale, Dr Gabrawi, Li Guo, Lisa Heideman, Steve Jones, Salli Lawson, Zoë Philips, Christopher Platt, Shakuntala Prabhakaran, John Rippin, Rose Thompson, Elizabeth Williams, Claire Woolley Statistical analysis Seonaidh Cotton, Kirsten Harrild, John Norrie, Linda Sharp External Trial Steering Committee Nicholas Day (chair, 1999–2004), Theresa Marteau (chair 2004-), Mahesh Parmar, Julietta Patnick and Ciaran Woodman.

Genetic-epidemiologic analysis of X-inactivation skewing in human females : suggestive evidence for two distinct traits

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

An Automated Surveillance Strategy to Identify Infectious Complications After Cardiac Implantable Electronic Device Procedures.

Background.  The optimum approach for infectious complication surveillance for cardiac implantable electronic device (CIED) procedures is unclear. We created an automated surveillance tool for infectious complications after CIED procedures. Methods.  Adults having CIED procedures between January 1, 2005 and December 31, 2011 at Duke University Hospital were identified retrospectively using International Classification of Diseases, 9th revision (ICD-9) procedure codes. Potential infections were identified with combinations of ICD-9 diagnosis codes and microbiology data for 365 days postprocedure. All microbiology-identified and a subset of ICD-9 code-identified possible cases, as well as a subset of procedures without microbiology or ICD-9 codes, were reviewed. Test performance characteristics for specific queries were calculated. Results.  Overall, 6097 patients had 7137 procedures. Of these, 1686 procedures with potential infectious complications were identified: 174 by both ICD-9 code and microbiology, 14 only by microbiology, and 1498 only by ICD-9 criteria. We reviewed 558 potential cases, including all 188 microbiology-identified cases, 250 randomly selected ICD-9 cases, and 120 with neither. Overall, 65 unique infections were identified, including 5 of 250 reviewed cases identified only by ICD-9 codes. Queries that included microbiology data and ICD-9 code 996.61 had good overall test performance, with sensitivities of approximately 90% and specificities of approximately 80%. Queries with ICD-9 codes alone had poor specificity. Extrapolation of reviewed infectious rates to nonreviewed cases yields an estimated rate of infection of 1.3%. Conclusions.  Electronic queries with combinations of ICD-9 codes and microbiologic data can be created and have good test performance characteristics for identifying likely infectious complications of CIED procedures.

Assessing Surveillance Elements of the Zanzibar Malaria Elimination Program to Support Malaria Elimination in Zanzibar

Though significant progress has been made through control efforts in recent years, malaria remains a leading cause of morbidity and mortality throughout the world, with 3.2 billion people at risk of developing the disease. Zanzibar is currently pursuing malaria elimination through the Zanzibar Malaria Elimination Program (ZAMEP), and is working toward a goal of no locally acquired malaria cases by 2018. A comprehensive and well functioning malaria surveillance program is central to achieving this goal. Under ZAMEP’s current surveillance strategy, District Malaria Surveillance Officers (DMSOs) respond to malaria case notifications through the reactive case detection (RACD) system. Three malaria screening and treatment strategies are undertaken in response to this system, including household-level (HSaT), focal-level (FSaT), and mass-level (MSaT). Each strategy is triggered by a different case threshold and tests different-sized populations. The aims of this study were to (1) assess the cost effectiveness of three malaria screening and treatment strategies; (2) assess the timeliness and completeness of ZAMEP’s RACD system; (3) and qualitatively explore the roles of DMSOs.

Screening disposition and budget information for 2014 screening and treatment strategies was analyzed to determine prevalence rates in screened populations and the cost effectiveness of each strategy. Prevalence rates within the screened population varied by strategy: 6.1 percent in HSaT, 1.2 percent in FSaT, and 0.9 percent in MSaT. Of the various costing scenarios considering cost per person screened, MSaT was the most cost-effective, with costs ranging from $9.57 to $12.57 per person screened. Of the various costing scenarios considering cost per case detected, HSaT was the most cost-effective, at $385.51 per case detected.

Case data from 2013 through mid-2015 was used to assess the timeliness and completeness of the RACD system. The average number of RACD activities occurring within 48 hours of notification improved slightly between 2013 and the first half of 2015, from 90.7 percent to 93.1 percent. The average percentage of household members screened during RACD also increased over the same time period, from 84 percent in 2013 to 89.9 percent in the first half of 2015.

Interviews with twenty DMSOs were conducted to gain insights into the challenges to malaria elimination both from the health system and the community perspectives. Major themes discussed in the interviews include the need for additional training, inadequate information capture at health facility, resistance to household testing, transportation difficulties, inadequate personnel during the high transmission season, and community misinformation.

Zanzibar is now considered a low transmission setting, making elimination feasible, but also posing new challenges to achieving this goal. The findings of this study provide insight into how surveillance activities can be improved to support the goal of malaria elimination in Zanzibar. Key changes include reevaluating the use of MSaT activities, improving information capture at health facilities, hiring additional DMSOs during the high transmission season, and improving community communication.

Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

Genetic-epidemiologic analysis of X-inactivation skewing in human females : suggestive evidence for two distinct traits

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Metabarcoding approach for non-indigenous species surveillance in marine coastal waters

In this study, high-throughput sequencing (HTS) metabarcoding was applied for the surveillance of plankton communities within the southeastern (SE) Baltic Sea coastal zone. These results were compared with those from routine monitoring survey and morphological analyses. Four of five nonindigenous species found in the samples were identified exclusively by metabarcoding. All of them are considered as invasive in the Baltic Sea with reported impact on the ecosystem and biodiversity. This study indicates that, despite some current limitations, HTS metabarcoding can provide information on the presence of exotic species and advantageously complement conventional approaches, only requiring the same monitoring effort as before. Even in the currently immature status of HTS, this combination of HTS metabarcoding and observational records is recommended in the early detection of marine pests and delivery of the environmental status metrics of nonindigenous species.