Using interviewer random effects to remove selection bias from HIV prevalence estimates

Background: Selection bias in HIV prevalence estimates occurs if non-participation in testing is correlated with HIV status. Longitudinal data suggests that individuals who know or suspect they are HIV positive are less likely to participate in testing in HIV surveys, in which case methods to correct for missing data which are based on imputation and observed characteristics will produce biased results. Methods: The identity of the HIV survey interviewer is typically associated with HIV testing participation, but is unlikely to be correlated with HIV status. Interviewer identity can thus be used as a selection variable allowing estimation of Heckman-type selection models. These models produce asymptotically unbiased HIV prevalence estimates, even when non-participation is correlated with unobserved characteristics, such as knowledge of HIV status. We introduce a new random effects method to these selection models which overcomes non-convergence caused by collinearity, small sample bias, and incorrect inference in existing approaches. Our method is easy to implement in standard statistical software, and allows the construction of bootstrapped standard errors which adjust for the fact that the relationship between testing and HIV status is uncertain and needs to be estimated. Results: Using nationally representative data from the Demographic and Health Surveys, we illustrate our approach with new point estimates and confidence intervals (CI) for HIV prevalence among men in Ghana (2003) and Zambia (2007). In Ghana, we find little evidence of selection bias as our selection model gives an HIV prevalence estimate of 1.4% (95% CI 1.2% – 1.6%), compared to 1.6% among those with a valid HIV test. In Zambia, our selection model gives an HIV prevalence estimate of 16.3% (95% CI 11.0% - 18.4%), compared to 12.1% among those with a valid HIV test. Therefore, those who decline to test in Zambia are found to be more likely to be HIV positive. Conclusions: Our approach corrects for selection bias in HIV prevalence estimates, is possible to implement even when HIV prevalence or non-participation is very high or very low, and provides a practical solution to account for both sampling and parameter uncertainty in the estimation of confidence intervals. The wide confidence intervals estimated in an example with high HIV prevalence indicate that it is difficult to correct statistically for the bias that may occur when a large proportion of people refuse to test.

The macroeconomic impact of non-communicable diseases in China and India: Estimates, projections, and comparisons

This study provides estimates of the macroeconomic impact of non-communicable diseases (NCDs) inChina and India for the period 2012–2030. Our estimates are derived using the World Health Organization’sEPIC model of economic growth, which focuses on the negative effects of NCDs on labor supply andcapital accumulation. We present results for the five main NCDs (cardiovascular disease, cancer, chronicrespiratory disease, diabetes, and mental health). Our undiscounted estimates indicate that the cost ofthe five main NCDs will total USD 23.03 trillion for China and USD 4.58 trillion for India (in 2010 USD).For both countries, the most costly domain is cardiovascular disease. Our analyses also reveal that thecosts are much larger in China than in India mainly because of China’s higher and steeper income trajectory,and to a lesser extent its older population. Rough calculations also indicate that WHO’s best buys foraddressing the challenge of NCDs are highly cost-beneficial

Ultra-Compact and Robust FPGA-Based PUF Identification Generator

Physically Unclonable Functions (PUFs), exploit inherent manufacturing variations and present a promising solution for hardware security. They can be used for key storage, authentication and ID generations. Low power cryptographic design is also very important for security applications. However, research to date on digital PUF designs, such as Arbiter PUFs and RO PUFs, is not very efficient. These PUF designs are difficult to implement on Field Programmable Gate Arrays (FPGAs) or consume many FPGA hardware resources. In previous work, a new and efficient PUF identification generator was presented for FPGA. The PUF identification generator is designed to fit in a single slice per response bit by using a 1-bit PUF identification generator cell formed as a hard-macro. In this work, we propose an ultra-compact PUF identification generator design. It is implemented on ten low-cost Xilinx Spartan-6 FPGA LX9 microboards. The resource utilization is only 2.23%, which, to the best of the authors' knowledge, is the most compact and robust FPGA-based PUF identification generator design reported to date. This PUF identification generator delivers a stable range of uniqueness of around 50% and good reliability between 85% and 100%.

Adjusting HIV Prevalence Estimates for Non-participation: an Application to Demographic Surveillance

Introduction: HIV testing is a cornerstone of efforts to combat the HIV epidemic, and testing conducted as part of surveillance provides invaluable data on the spread of infection and the effectiveness of campaigns to reduce the transmission of HIV. However, participation in HIV testing can be low, and if respondents systematically select not to be tested because they know or suspect they are HIV positive (and fear disclosure), standard approaches to deal with missing data will fail to remove selection bias. We implemented Heckman-type selection models, which can be used to adjust for missing data that are not missing at random, and established the extent of selection bias in a population-based HIV survey in an HIV hyperendemic community in rural South Africa.

Methods: We used data from a population-based HIV survey carried out in 2009 in rural KwaZulu-Natal, South Africa. In this survey, 5565 women (35%) and 2567 men (27%) provided blood for an HIV test. We accounted for missing data using interviewer identity as a selection variable which predicted consent to HIV testing but was unlikely to be independently associated with HIV status. Our approach involved using this selection variable to examine the HIV status of residents who would ordinarily refuse to test, except that they were allocated a persuasive interviewer. Our copula model allows for flexibility when modelling the dependence structure between HIV survey participation and HIV status.

Results: For women, our selection model generated an HIV prevalence estimate of 33% (95% CI 27–40) for all people eligible to consent to HIV testing in the survey. This estimate is higher than the estimate of 24% generated when only information from respondents who participated in testing is used in the analysis, and the estimate of 27% when imputation analysis is used to predict missing data on HIV status. For men, we found an HIV prevalence of 25% (95% CI 15–35) using the selection model, compared to 16% among those who participated in testing, and 18% estimated with imputation. We provide new confidence intervals that correct for the fact that the relationship between testing and HIV status is unknown and requires estimation.

Conclusions: We confirm the feasibility and value of adopting selection models to account for missing data in population-based HIV surveys and surveillance systems. Elements of survey design, such as interviewer identity, present the opportunity to adopt this approach in routine applications. Where non-participation is high, true confidence intervals are much wider than those generated by standard approaches to dealing with missing data suggest.

An efficient and robust case sorting for algorithm for transient stability assessment

An efficient and robust case sorting algorithm based on Extended Equal Area Criterion (EEAC) is proposed in this paper for power system transient stability assessment (TSA). The time-varying degree of an equivalent image system can be deduced by comparing the analysis results of Static EEAC (SEEAC) and Dynamic EEAC (DEEAC), the former of which neglects all time-varying factors while the latter partially considers the time-varying factors. Case sorting rules according to their transient stability severity are set combining the time-varying degree and fault messages. Then a case sorting algorithm is designed with the “OR” logic among multiple rules, based on which each case can be identified into one of the following five categories, namely stable, suspected stable, marginal, suspected unstable and unstable. The performance of this algorithm is verified by studying 1652 contingency cases from 9 real Chinese provincial power systems under various operating conditions. It is shown that desirable classification accuracy can be achieved for all the contingency cases at the cost of very little extra computational burden and only 9.81% of the whole cases need to carry out further detailed calculation in rigorous on-line TSA conditions.

Design and deployment of secure, robust, and resilient SDN Controllers

The scale of the Software-Defined Network (SDN) Controller design problem has become apparent with the expansion of SDN deployments. Initial SDN deployments were small-scale, single controller environments for research and usecase testing. Today, enterprise deployments requiring multiple controllers are gathering momentum e.g. Google’s backbone network, Microsoft’s public cloud, and NTT’s edge gateway. Third-party applications are also becoming available e.g. HP SDN App Store. The increase in components and interfaces for the evolved SDN implementation increases the security challenges of the SDN controller design. In this work, the requirements of a secure, robust, and resilient SDN controller are identified, stateof-the-art open-source SDN controllers are analyzed with respect to the security of their design, and recommendations for security improvements are provided. This contribution highlights the gap between the potential security solutions for SDN controllers and the actual security level of current controller designs.

Three-dimensional porous carbon nanofiber networks decorated with cobalt-based nanoparticles: A robust electrocatalyst for efficient water oxidation

Electrochemical water splitting used for generating hydrogen has attracted increasingly attention due to energy and environmental issues. It is a major challenge to design an efficient, robust and inexpensive electrocatalyst to achieve preferable catalytic performance. Herein, a novel three-dimensional (3D) electrocatalyst was prepared by decorating nanostructured biological material-derived carbon nanofibers with in situ generated cobalt-based nanospheres (denoted as CNF@Co) through a facile approach. The interconnected porous 3D networks of the resulting CNF@Co catalyst provide abundant channels and interfaces, which remarkably favor both mass transfer and oxygen evolution. The as-prepared CNF@Co shows excellent electrocatalytic activity towards the oxygen evolution reactions with an onset potential of about 0.445 V vs. Ag/AgCl. It only needs a low overpotential of 314 mV to achieve a current density of 10 mA/cm² in 1.0 M KOH. Furthermore, the CNF@Co catalyst exhibits excellent stability towards water oxidation, even outperforming commercial IrO<inf>2</inf> and RuO<inf>2</inf> catalysts.

Largest Matching Areas for Illumination and Occlusion Robust Face Recognition

In this paper, we introduce a novel approach to face recognition which simultaneously tackles three combined challenges: 1) uneven illumination; 2) partial occlusion; and 3) limited training data. The new approach performs lighting normalization, occlusion de-emphasis and finally face recognition, based on finding the largest matching area (LMA) at each point on the face, as opposed to traditional fixed-size local area-based approaches. Robustness is achieved with novel approaches for feature extraction, LMA-based face image comparison and unseen data modeling. On the extended YaleB and AR face databases for face identification, our method using only a single training image per person, outperforms other methods using a single training image, and matches or exceeds methods which require multiple training images. On the labeled faces in the wild face verification database, our method outperforms comparable unsupervised methods. We also show that the new method performs competitively even when the training images are corrupted.

Robust implantable antenna for in-body communications

A compact implantable printed meandered folded dipole antenna with a volume of 101.8 mm3 and robust performance is presented for operation in the 2.4 GHz medical ISM bands. The implant antenna is shown to maintain its return loss performance in the 2360???2400 MHz, 2400???2483.5 MHz and 2483.5???2500 MHz frequency bands, simulated in eleven different body tissue types with a broad range of electrical properties. Bandwidth and resonant frequency changes are reported for the same antenna implanted in high water content tissues such as muscle and skin as well as low water content tissues such as subcutaneous fat and bone. The antenna was also shown to maintain its return loss performance as it was moved towards a tissue boundary within a simulated phantom testbed.

Immunohistochemistry should undergo robust validation equivalent to that of molecular diagnostics

Immunohistochemistry (IHC) is a widely available and highly utilised tool in diagnostic histopathology and is used to guide treatment options as well as provide prognostic information. IHC is subjected to qualitative and subjective assessment, which has been criticised for a lack of stringency, while PCR-based molecular diagnostic validations by comparison are regarded as very rigorous. It is essential that IHC tests are validated through evidence-based procedures. With the move to ISO15189 (2012), not just of the accuracy, specificity and reproducibility of each test need to be determined and managed, but also the degree of uncertainty and the delivery of such tests. The recent update to ISO 15189 (2012) states that it is appropriate to consider the potential uncertainty of measurement of the value obtained in the laboratory and how that may impact on prognostic or predictive thresholds. In order to highlight the problems surrounding IHC validity, we reviewed the measurement of Ki67and p53 in the literature. Both of these biomarkers have been incorporated into clinical care by pathology laboratories worldwide. The variation seen appears excessive even when measuring centrally stained slides from the same cases. We therefore propose in this paper to establish the basis on which IHC laboratories can bring the same level of robust validation seen in the molecular pathology laboratories and the principles applied to all routine IHC tests.

Robust Room Temperature Hysteresis in an FeIII Spin Crossover Metallomesogen

The high temperature magnetic and structural properties of an amphiphilic iron(III) spin crossover complex are reported. Thermal cycling reveals a scan rate-dependent 20 K thermal hysteresis in the mT vs. T data close to room temperature. A fast scan rate is essential for the hysteresis but it is robust and reproducible after multiple thermal cycles. Differential scanning calorimetry and cross polarized microscopy are used to show that the magnetic switching aligns with a material state change from solid to ordered liquid phase on warming.