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This paper investigates how ancillary geographic data – in particular, information on land or assessor parcels – might be used to improve estimates for small area populations and population characteristics. It seeks to determine whether parcel land use codes can be used to reliably replicate population and housing distributions within small (subcounty) areas and whether other parcel attributes – in addition to land use – exhibit any explanatory power in replicating population and housing characteristics within these same places. The basis for this paper was Professor Barbara Buttenfield's service on the Census Scientific Advisory Committee, in which her working group explored the utility of administrative source data as an alternative or complement to federal survey data. This analysis highlights some of the benefits and complications of the incorporation of parcel data into geodemographic estimation, and the findings demonstrate that such a use is problematic but encouraging. [ABSTRACT FROM AUTHOR]

The present article is the first empirical investigation of attitudes towards immigration in Europe via small area estimation providing reliable regional estimates across European regions. Four dimensions of regional attitudes are considered, i.e., restrictive attitudes towards specific groups, restrictive attitudes towards acquired criteria, threat, and restrictive attitudes towards ascribed criteria. We produce maps of these, as well as validation outputs, demonstrating that our estimates are reliable, hence, have a strong potential in informing policy makers. We show that, although there is a large between-country variation of these attitudes, there are also large spatial differences between-region in some countries. Overall, Swedish public attitudes tend to be quite homogeneous across regions, and located towards the positive side, whereas Eastern European countries tend to show negative attitudes across all the dimensions apart from the acquired criteria. However, in these countries, we can see larger spatial differences across regions, especially in the ascribed criteria and attitudes towards specific groups indicator. In general, the threat dimension does not show a large between-region variability, compared to the other three dimensions. [ABSTRACT FROM AUTHOR]

Abstract Background The COVID-19 pandemic has led to major shocks in mortality trends in many countries. Yet few studies have evaluated the heterogeneity of the mortality shocks at the sub-national level, rigorously accounting for the different sources of uncertainty. Methods Using death registration data from Belgium, we first assess change in the heterogeneity of districts’ standardized mortality ratios in 2020, when compared to previous years. We then measure the shock effect of the pandemic using district-level values of life expectancy, comparing districts’ observed and projected life expectancy, accounting for all sources of uncertainty (stemming from life-table construction at district level and from projection methods at country and district levels). Bayesian modelling makes it easy to combine the different sources of uncertainty in the assessment of the shock. This is of particular interest at a finer geographical scale characterized by high stochastic variation in annual death counts. Results The heterogeneity in the impact of the pandemic on all-cause mortality across districts is substantial: while some districts barely show any impact, the Bruxelles-Capitale and Mons districts experienced a decrease in life expectancy at birth of 2.24 (95% CI:1.33–3.05) and 2.10 (95% CI:0.86–3.30) years, respectively. The year 2020 was associated with an increase in the heterogeneity of mortality levels at a subnational scale in comparison to past years, measured in terms of both standardized mortality ratios and life expectancies at birth. Decisions on uncertainty thresholds have a large bearing on the interpretation of the results. Conclusion Developing sub-national mortality estimates taking careful account of uncertainty is key to identifying which areas have been disproportionately affected.

Abstract Background The increased availability of data on health outcomes and risk factors collected at fine geographical resolution is one of the main reasons for the rising popularity of epidemiological analyses conducted at small-area level. However, this rich data setting poses important methodological issues related to modelling complexities and computational demands, as well as the linkage and harmonisation of data collected at different geographical levels. Methods This tutorial illustrated the extension of the case time series design, originally proposed for individual-level analyses on short-term associations with time-varying exposures, for applications using data aggregated over small geographical areas. The case time series design embeds the longitudinal structure of time series data within the self-matched framework of case-only methods, offering a flexible and highly adaptable analytical tool. The methodology is well suited for modelling complex temporal relationships, and it provides an efficient computational scheme for large datasets including longitudinal measurements collected at a fine geographical level. Results The application of the case time series for small-area analyses is demonstrated using a real-data case study to assess the mortality risks associated with high temperature in the summers of 2006 and 2013 in London, UK. The example makes use of information on individual deaths, temperature, and socio-economic characteristics collected at different geographical levels. The tutorial describes the various steps of the analysis, namely the definition of the case time series structure and the linkage of the data, as well as the estimation of the risk associations and the assessment of vulnerability differences. R code and data are made available to fully reproduce the results and the graphical descriptions. Conclusions The extension of the case time series for small-area analysis offers a valuable analytical tool that combines modelling flexibility and computational efficiency. The increasing availability of data collected at fine geographical scales provides opportunities for its application to address a wide range of epidemiological questions.

Background: The increased availability of data on health outcomes and risk factors collected at fine geographical resolution is one of the main reasons for the rising popularity of epidemiological analyses conducted at small-area level. However, this rich data setting poses important methodological issues related to modelling complexities and computational demands, as well as the linkage and harmonisation of data collected at different geographical levels.Methods: This tutorial illustrated the extension of the case time series design, originally proposed for individual-level analyses on short-term associations with time-varying exposures, for applications using data aggregated over small geographical areas. The case time series design embeds the longitudinal structure of time series data within the self-matched framework of case-only methods, offering a flexible and highly adaptable analytical tool. The methodology is well suited for modelling complex temporal relationships, and it provides an efficient computational scheme for large datasets including longitudinal measurements collected at a fine geographical level.Results: The application of the case time series for small-area analyses is demonstrated using a real-data case study to assess the mortality risks associated with high temperature in the summers of 2006 and 2013 in London, UK. The example makes use of information on individual deaths, temperature, and socio-economic characteristics collected at different geographical levels. The tutorial describes the various steps of the analysis, namely the definition of the case time series structure and the linkage of the data, as well as the estimation of the risk associations and the assessment of vulnerability differences. R code and data are made available to fully reproduce the results and the graphical descriptions.Conclusions: The extension of the case time series for small-area analysis offers a valuable analytical tool that combines modelling flexibility and computational efficiency. The increasing availability of data collected at fine geographical scales provides opportunities for its application to address a wide range of epidemiological questions. [ABSTRACT FROM AUTHOR]

This brief presents a low-power asynchronous 10-bit 2-then-1b/cycle successive approximation register (SAR) analog-to-digital converter (ADC). With partial adoption of 2b/cycle mode only for higher-order bit conversions, additional area and power consumption could be minimized while maintaining fast conversion rate. Moreover, unlike the previous 2b/cycle conversion architecture, where two capacitive digital-to-analog converters (C-DACs) and multiple analog comparators are unavoidable, the proposed 2-then-1b/cycle conversion is implemented with only one C-DAC and one analog comparator by utilizing a digital-based time-domain reference. The speed of 1b/cycle conversion for lower-order bits is improved with a dual-mode comparator. With the aforementioned techniques, the prototype 10-bit SAR ADC is fabricated in 65 nm CMOS process. The ADC core occupies an active area of 0.0142 mm2 and consumes power of 3.8 $\boldsymbol{\mu }\text{W}$ at 0.5 V supply voltage and 3 MS/s conversion rate. The SNDR measured at a Nyquist-rate input frequency is 56.41 dB, resulting in a figure of merit (FoM) is 2.33 fJ/c.-s. [ABSTRACT FROM AUTHOR]

A hybrid charge pump was developed in a 0.13- $\mu \text{m}$ Bipolar-CMOS-DMOS (BCD) process which utilised high drain-source voltage MOS devices and low-voltage integrated metal-insulator-metal (MIM) capacitors. The design consisted of a zero-reversion loss cross-coupled stage and a new self-biased serial-parallel charge pump design. The latter has been shown to have an area reduction of 60% in comparison to a Schottky diode-based Dickson charge pump operating at the same frequency. Post-layout simulations were carried out which demonstrated a peak efficiency of 38% at the output voltage of 18.5 V; the maximum specified output voltage of 27 V was also achieved. A standalone serial-parallel charge pump was shown to have a better transient response and a flatter efficiency curve; these are preferable for time-sensitive applications with a requirement of a broader range of output currents. These findings have significant implications for reducing the total area of implantable high-voltage devices without sacrificing charge pump efficiency or maximum output voltage.

Abstract Background Hepatitis C virus (HCV) is the most common blood-borne viral infection in the United States. Previously, we used data from the National Health and Nutrition Examination Survey (NHANES) and mortality data from the National Vital Statistics System (NVSS) to estimate the prevalence of HCV antibodies (anti-HCV) and HCV RNA among all U.S. states. However, demographic differences in HCV burden at the state-level have not been systematically described. This analysis quantified the HCV burden stratified by sex and race (and associated disparities) for each U.S. state. Methods Building on our previous method, we used three publicly available data sources to estimate HCV RNA prevalence among noninstitutionalized adults stratified by sex and race group. We used a small-area estimation approach that included direct standardization of NHANES demographic data with logistic regression modeling of HCV-related mortality data as an adjustment factor to estimate the state-level prevalence and total persons with chronic HCV infection for sex and race groups in all U.S. states. Results Nationally, males had an estimated HCV RNA prevalence of 1.56% (95% CI: 1.37–1.84%) and females had a prevalence of 0.75% (95% CI: 0.63–0.96%). Stratified by race, national estimated prevalence of HCV RNA was highest among non-Hispanic black (2.43, 95% CI: 2.10–2.90%), followed by non-Hispanic white (1.05, 95% CI: 0.90–1.27%) and Hispanic/other (0.74, 95% CI: 0.59–1.04%). Males in most jurisdictions (41/51) have an HCV RNA prevalence that is between 1.5 and 2.5 times higher than their female counterparts. Conclusions HCV infection disparities by sex are mostly consistent across the country. However, race differences in HCV infection differ by state and tailored prevention and treatment efforts specific to the local HCV epidemic are needed to reduce race disparities.

Despite improvements in cancer survival across many developed countries, it is unclear how survival is changing over time in small areas. This study investigated changes in breast and colorectal cancer survival across 478 areas over 11 years (2001–2011), and the influence of early diagnosis on changes. Queensland Cancer Registry data were analysed using an introduced Bayesian spatio-temporal flexible parametric relative survival model. All areas showed survival improvements between 2001–2003 and 2008–2011. The median absolute 5-year survival improvement for localised breast cancer was small (1.8%), compared to advanced (4.8%) and unknown (7.9%) breast cancer, as well as localised (2.6%), advanced (5.0%) and unknown (4.8%) colorectal cancers. Improvements in non-diagnostic factors, such as patient treatment and management, appear to be the main influence on recent survival increases for breast and colorectal cancers. Important inequalities in cancer survival between small areas remain. [ABSTRACT FROM AUTHOR]

There has long been a demand for cancer incidence data at a fine geographic resolution for use in etiologic hypothesis generation and testing, methodological evaluation and teaching. In this paper we describe a public domain dataset containing data for 23 anatomic sites of cancer diagnosed in New York State, USA between 2005 and 2009 at the census block group level. The dataset includes 524,503 tumours distributed across 13,823 block groups with an average population of about 1400. In addition, the data have been linked with race/ethnicity and with socioeconomic indicators such as income, educational attainment and language proficiency. We demonstrate the application of the dataset by confirming two well-established relationships: that between breast cancer and median household income and that between stomach cancer and Asian race. We foresee that this dataset will serve as the basis for a wide range of spatial analyses and as a benchmark for evaluating spatial methods in the future.

Long-term exposure to primary traffic pollutants may be harmful for health but few studies have investigated effects on mortality. We examined associations for six primary traffic pollutants with all-cause and cause-specific mortality in 2003–2010 at small-area level using linear and piecewise linear Poisson regression models. In linear models most pollutants showed negative or null association with all-cause, cardiovascular or respiratory mortality. In the piecewise models we observed positive associations in the lowest exposure range (e.g. relative risk (RR) for all-cause mortality 1.07 (95% credible interval (CI) = 1.00–1.15) per 0.15 μg/m 3 increase in exhaust related primary particulate matter ≤2.5 μm (PM 2.5 )) whereas associations in the highest exposure range were negative (corresponding RR 0.93, 95% CI: 0.91–0.96). Overall, there was only weak evidence of positive associations with mortality. That we found the strongest positive associations in the lowest exposure group may reflect residual confounding by unmeasured confounders that varies by exposure group. [ABSTRACT FROM AUTHOR]

Evidence on the effects of long-term exposure to traffic pollution on health is inconsistent. In Greater London we examined associations between traffic pollution and emergency hospital admissions for cardio-respiratory diseases by applying linear and piecewise linear Poisson regression models in a small-area analysis. For both models the results for children and adults were close to unity. In the elderly, linear models found negative associations whereas piecewise models found non-linear associations characterized by positive risks in the lowest and negative risks in the highest exposure category. An increased risk was observed among those living in areas with the highest socioeconomic deprivation. Estimates were not affected by adjustment for traffic noise. The lack of convincing positive linear associations between primary traffic pollution and hospital admissions agrees with a number of other reports, but may reflect residual confounding. The relatively greater vulnerability of the most deprived populations has important implications for public health. [ABSTRACT FROM AUTHOR]

Background Globally and in the United States, smoking and obesity are leading causes of death and disability. Reliable estimates of prevalence for these risk factors are often missing variables in public health surveillance programs. This may limit the capacity of public health surveillance to target interventions or to assess associations between other environmental risk factors (e.g., air pollution) and health because smoking and obesity are often important confounders. Objectives To generate prevalence estimates of smoking and obesity rates over small areas for the United States (i.e., at the ZIP code and census tract levels). Methods We predicted smoking and obesity prevalence using a combined approach first using a lasso-based variable selection procedure followed by a two-level random effects regression with a Poisson link clustered on state and county. We used data from the Behavioral Risk Factor Surveillance System (BRFSS) from 1991 to 2010 to estimate the model. We used 10-fold cross-validated mean squared errors and the variance of the residuals to test our model. To downscale the estimates we combined the prediction equations with 1990 and 2000 U.S. Census data for each of the four five-year time periods in this time range at the ZIP code and census tract levels. Several sensitivity analyses were conducted using models that included only basic terms, that accounted for spatial autocorrelation, and used Generalized Linear Models that did not include random effects. Results The two-level random effects model produced improved estimates compared to the fixed effects-only models. Estimates were particularly improved for the two-thirds of the conterminous U.S. where BRFSS data were available to estimate the county level random effects. We downscaled the smoking and obesity rate predictions to derive ZIP code and census tract estimates. Conclusions To our knowledge these smoking and obesity predictions are the first to be developed for the entire conterminous U.S. for census tracts and ZIP codes. Our estimates could have significant utility for public health surveillance. [ABSTRACT FROM AUTHOR]

Abstract: CMOS pixel sensors (CPS) have demonstrated performances meeting the specifications of the International Linear Collider (ILC) vertex detector (VTX). This paper presents a low-power and small-area 4-bit column-level analog-to-digital converter (ADC) for CMOS pixel sensors. The ADC employs a self-timed trigger and completes the conversion by performing a multi-bit/step approximation. As in the outer layers of the ILC vertex detector hit density is of the order of a few per thousand, in order to reduce power consumption, the ADC is designed to work in two modes: active mode and idle mode. The ADC is fabricated in a 0.35μm CMOS process with a pixel pitch of 35μm. It is implemented with 48 columns in a sensor prototype. Each column ADC covers an area of 35 ×545μm2. The measured temporal noise and Fixed Pattern Noise (FPN) are 0.96mV and 0.40mV, respectively. The power consumption, for a 3V supply and 6.25MS/s sampling rate, is 486μW during idle time, which is by far the most frequently employed one. This value rises to 714μW in the case of the active mode. The measured differential nonlinearity (DNL) and integral nonlinearity (INL) are 0.49/−0.28 LSB and 0.29/−0.20 LSB, respectively. [Copyright &y& Elsevier]

Abstract: The index of multiple deprivations (IMD) is an established method in western market economies for measuring the level of social disadvantage in small areas so as to allocate public resources and target area-based regeneration policies. The method has seldom been used in emerging economies such as China. This article applies the method to the city of Guangzhou and attempts to develop an index that is suitable to the local context. Using the fifth population census, 13 indicators are selected into 5 domains of deprivation, which are measured in the finest resolution of 1632 residents' committees (RCs). The method is useful to show urban–rural disparity and the extensive distribution of deprived areas in outer suburbs. [Copyright &y& Elsevier]

In this paper, a novel level shifter design with ultra-low leakage power and an extremely compact area is proposed. The presented structure is composed of an input inverter, a Wilson-like current mirror, and an output inverter. To minimize the leakage power, a super-cut-off pull-down network and a stacked pull-up network are proposed in our structure. Moreover, the novel architecture employs the multi-threshold CMOS (MTCMOS) and sizing technology to minimize the layout area. The prototype has been fabricated by the SMIC 55 nm MTCMOS technology with an area of 5.614 μ m 2 . Experimental results show that the average leakage of our level shifter is extremely 21.62 pW low power when converting a 0.3 V input to 1.2 V output. At the same time, the average propagation delay and the average energy per transition of the presented structure are 24.06 ns and 4.42 fJ, respectively. [ABSTRACT FROM AUTHOR]

A 32 kbit OTP (one-time programmable) memory for MCUs (micro-controller units) used in remote controllers was designed. This OTP memory is used for program and data storage. It is required to apply 5.5 V to BL (bit-line) and 11 V to WL (word-line) for a OTP cell of 0.35 μm ETOX (EEPROM tunnel oxide) type by MagnaChip. We use 5 V transistors on column data paths to reduce the area of column data paths since they require small areas. In addition, we secure device reliability by using HV (high-voltage) transistors in the WL driver. Furthermore, we change from a static logic to a dynamic logic used for the WL driver in the core circuit. Also, we optimize the WD (write data) switch circuit. Thus, we can implement them with a small-area design. In addition, we implement the address predecoder with a small-area logic circuit. The area of the designed 32 kbit OTP with 5 V and HV devices is 674.725 μm×258.75 μm (=0.1745 mm) and is 56.3% smaller than that using 3.3 V devices. [ABSTRACT FROM AUTHOR]