Inter- and Intrapersonal variation in destination choice

This paper examines spatial-temporal inter- and intrapersonal variation in destination choice, based on longitudinal smartphone data for the Netherlands. Mixed logit destination choice models were estimated using two years of data (2014 and 2015) from the Dutch Mobile Mobility Panel, in which over 68,000 trips for 442 respondents were recorded with a smartphone app during an annual four-week measurement period. A distinction was made between trips to compulsory activities (such as work) and trips for discretionary purposes (such as recreation) as they are associated with different trip characteristics. Discrete destination alternatives were defined based on individuals’ behaviour in terms of repeatedly visited destinations and the statistical distribution of a spatial repetition index. The model results show that intrapersonal variation in destination choice, departure time and mode choice was relatively high for less frequently visited locations, which indicates novelty-seeking behaviour in destination choice. Furthermore, we found a strong connection between activity, departure time, and destination choice. And, mode choice and departure time choice were highly repetitive for destinations visited repetitively (e.g. work), but not for discretionary activities

Automated measurement of penile curvature using deep learning-based novel quantification method

ObjectiveDevelop a reliable, automated deep learning-based method for accurate measurement of penile curvature (PC) using 2-dimensional images.Materials and methodsA set of nine 3D-printed models was used to generate a batch of 913 images of penile curvature (PC) with varying configurations (curvature range 18° to 86°). The penile region was initially localized and cropped using a YOLOv5 model, after which the shaft area was extracted using a UNet-based segmentation model. The penile shaft was then divided into three distinct predefined regions: the distal zone, curvature zone, and proximal zone. To measure PC, we identified four distinct locations on the shaft that reflected the mid-axes of proximal and distal segments, then trained an HRNet model to predict these landmarks and calculate curvature angle in both the 3D-printed models and masked segmented images derived from these. Finally, the optimized HRNet model was applied to quantify PC in medical images of real human patients and the accuracy of this novel method was determined.ResultsWe obtained a mean absolute error (MAE) of angle measurement <5° for both penile model images and their derivative masks. For real patient images, AI prediction varied between 1.7° (for cases of ∼30° PC) and approximately 6° (for cases of 70° PC) compared with assessment by a clinical expert.DiscussionThis study demonstrates a novel approach to the automated, accurate measurement of PC that could significantly improve patient assessment by surgeons and hypospadiology researchers. This method may overcome current limitations encountered when applying conventional methods of measuring arc-type PC

Healthcare Access and Quality Index based on mortality from causes amenable to personal health care in 195 countries and territories, 1990-2015 : a novel analysis from the Global Burden of Disease Study 2015

Background National levels of personal health-care access and quality can be approximated by measuring mortality rates from causes that should not be fatal in the presence of effective medical care (ie, amenable mortality). Previous analyses of mortality amenable to health care only focused on high-income countries and faced several methodological challenges. In the present analysis, we use the highly standardised cause of death and risk factor estimates generated through the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to improve and expand the quantification of personal health-care access and quality for 195 countries and territories from 1990 to 2015. Methods We mapped the most widely used list of causes amenable to personal health care developed by Nolte and McKee to 32 GBD causes. We accounted for variations in cause of death certification and misclassifications through the extensive data standardisation processes and redistribution algorithms developed for GBD. To isolate the effects of personal health-care access and quality, we risk-standardised cause-specific mortality rates for each geography-year by removing the joint effects of local environmental and behavioural risks, and adding back the global levels of risk exposure as estimated for GBD 2015. We employed principal component analysis to create a single, interpretable summary measure-the Healthcare Quality and Access (HAQ) Index-on a scale of 0 to 100. The HAQ Index showed strong convergence validity as compared with other health-system indicators, including health expenditure per capita (r= 0.88), an index of 11 universal health coverage interventions (r= 0.83), and human resources for health per 1000 (r= 0.77). We used free disposal hull analysis with bootstrapping to produce a frontier based on the relationship between the HAQ Index and the Socio-demographic Index (SDI), a measure of overall development consisting of income per capita, average years of education, and total fertility rates. This frontier allowed us to better quantify the maximum levels of personal health-care access and quality achieved across the development spectrum, and pinpoint geographies where gaps between observed and potential levels have narrowed or widened over time. Findings Between 1990 and 2015, nearly all countries and territories saw their HAQ Index values improve; nonetheless, the difference between the highest and lowest observed HAQ Index was larger in 2015 than in 1990, ranging from 28.6 to 94.6. Of 195 geographies, 167 had statistically significant increases in HAQ Index levels since 1990, with South Korea, Turkey, Peru, China, and the Maldives recording among the largest gains by 2015. Performance on the HAQ Index and individual causes showed distinct patterns by region and level of development, yet substantial heterogeneities emerged for several causes, including cancers in highest-SDI countries; chronic kidney disease, diabetes, diarrhoeal diseases, and lower respiratory infections among middle-SDI countries; and measles and tetanus among lowest-SDI countries. While the global HAQ Index average rose from 40.7 (95% uncertainty interval, 39.0-42.8) in 1990 to 53.7 (52.2-55.4) in 2015, far less progress occurred in narrowing the gap between observed HAQ Index values and maximum levels achieved; at the global level, the difference between the observed and frontier HAQ Index only decreased from 21.2 in 1990 to 20.1 in 2015. If every country and territory had achieved the highest observed HAQ Index by their corresponding level of SDI, the global average would have been 73.8 in 2015. Several countries, particularly in eastern and western sub-Saharan Africa, reached HAQ Index values similar to or beyond their development levels, whereas others, namely in southern sub-Saharan Africa, the Middle East, and south Asia, lagged behind what geographies of similar development attained between 1990 and 2015. Interpretation This novel extension of the GBD Study shows the untapped potential for personal health-care access and quality improvement across the development spectrum. Amid substantive advances in personal health care at the national level, heterogeneous patterns for individual causes in given countries or territories suggest that few places have consistently achieved optimal health-care access and quality across health-system functions and therapeutic areas. This is especially evident in middle-SDI countries, many of which have recently undergone or are currently experiencing epidemiological transitions. The HAQ Index, if paired with other measures of health-systemcharacteristics such as intervention coverage, could provide a robust avenue for tracking progress on universal health coverage and identifying local priorities for strengthening personal health-care quality and access throughout the world. Copyright (C) The Author(s). Published by Elsevier Ltd.Peer reviewe

Traffic Information Interface Development in Route Choice Decision

"jats:p"In this paper, a method has been developed based on historic traffic data (vehicle speed), which helps the commuters to choose routes by their intelligence knowing the traffic conditions in Google maps. Data has been collected on basis of video analysis from several segments between Tuker Bazar and Bandar Bazar route. For each of the video footage, a reference length has been recorded with measurement tape for use in video analysis. Software has been also developed based on Java language to get the traffic information from historic data, which shows the output as images consisting of traffic speed details on the available routes by giving day and time limit as inputs. The developed models provide useful insights and helpful for the policy makers that can lead to the reduction of traffic congestion and increase the scope of intelligence of the road users, at least for the underdeveloped or developing country where navigation is still unavailable. Document type: Articl

Using panel data for modelling duration dynamics of outdoor leisure activities

This paper examines the effects of socioeconomic characteristics, trip characteristics and life events on outdoor leisure activities and leisure duration in the Netherlands, based on 14 554 observations from three waves of data from The Netherlands Mobility Panel (in Dutch: MobiliteitsPanel Nederland). A standard mixed logit as well as a ‘zero-leisure’ scaled model was estimated to cover interpersonal and intrapersonal heterogeneity, The model was estimated for weekends, weekdays, transport mode choice of the activity, and specific leisure activity. The results show that travel time and transport mode choice for leisure trips have significant links with activity duration. Walking and cycling are dominant modes for short-duration activities and public transport for long-duration activities, and activity duration increases with travel time. The probability of short-duration leisure activities is higher on workdays. Certain life events positively affect the duration of leisure activities, whereas accessibility and bicycle ownership have no effect on leisure activity duration. The scaled model shows that the utility of any duration is about 10% larger for respondents who reported at least one day without leisure activities (‘zero leisure’). Leisure activities undertaken during the same week are significantly correlated, representing significant intrapersonal variation. The paper highlights the importance of analysing duration of activities for different activity types and days of the week and underlines the strong link of temporal (week, year) and spatial (activity type location) dimensions with transport mode choice

Comparing tariff and medical assistant assigned causes of death from verbal autopsy interviews in Matlab, Bangladesh: implications for a health and demographic surveillance system

Abstract Background Deaths in developing countries often occur outside health facilities, making it extremely difficult to gather reliable cause of death (COD) information. Automated COD assignment using a verbal autopsy instrument (VAI) has been proposed as a reliable and cost-effective alternative to traditional physician-certified verbal autopsy, but its performance is still being evaluated. The purpose of this study was to compare the similarity of diagnosis by Medical Assistants (MA) in the Matlab Health and Demographic Surveillance System (HDSS) with the SmartVA Analyze 1.2 (Tariff 2.0) diagnosis. Methods This study took place between January 2011 and April 2014 in Matlab, Bangladesh. MA with 3 years of medical training assigned COD to Matlab residents by reviewing the information collected using the Population Health Metrics Research Consortium (PHMRC) long-form VAI. Smart VA Analyze 1.2 automatically assigned COD using the same questionnaire. COD agreement and cause-specific mortality fractions (CSMFs) were compared for MA and Tariff. Results Of the 4969 verbal autopsy cases reviewed, 4328 were adults, 296 were children, and 345 were neonates. Cohen’s kappa was 0.38 (0.36, 0.40) for adults, 0.43 (0.38, 0.49) for children, and 0.27 (0.22, 0.33) for neonates. For adults, the top two COD for MA were stroke (29.6%) and ischemic heart diseases (IHD) (14.2%) and for Tariff these were stroke (32.0%) and IHD (14.0%). For children, the top two COD for MA were drowning (33.5%) and pneumonia (13.2%) and for Tariff these were also drowning (36.8%) and pneumonia (12.4%). For neonates, the top two COD for MA were birth asphyxia (41.2%) and meningitis/sepsis (22.3%) and for Tariff these were birth asphyxia (37.0%) and preterm delivery (30.9%). Conclusion The CSMFs for Tariff and MA showed very close agreement across all age categories but some differences were observed for neonate preterm delivery and meningitis/sepsis. Given the known advantages of automated methods over physician certified verbal autopsy, the SmartVA software, incorporating the shortened VAI questionnaire and Tariff 2.0, could serve as a cost-effective alternative to Matlab MA to routinely collect and analyze verbal autopsy data in a HDSS to generate essential population level COD data for planning

Additional file 1: of Comparing tariff and medical assistant assigned causes of death from verbal autopsy interviews in Matlab, Bangladesh: implications for a health and demographic surveillance system

ICD-10 codes to text COD mapping. Three separate tables that provide mapping from ICD-10 codes to text causes of death for adults, children, and neonates. (DOCX 14 kb

Additional file 3: of Comparing tariff and medical assistant assigned causes of death from verbal autopsy interviews in Matlab, Bangladesh: implications for a health and demographic surveillance system

Cause-specific mortality fractions for medical assistants and reallocated Tariff by age group. Bar graphs that mirror Table 1 by comparing the cause-specific mortality fraction for medical assistants to reallocated Tariff with the addition of indicating statistical significance at the 0.05 significance level. (PNG 72 kb