An Open-Access Data Platform: Global Nutrition and Health Atlas (GNHA).

The rapid development of nutrition science is embracing digital transformation to generate large amounts of data. Precision nutrition and "Big Data" place increasing demand for data repositories and visualization, which enhances the digital transformation. We defined the need for an integrated nutrition data platform as a web-based platform that can collect, store, track, analyze, monitor, and visually display key metrics in nutrition and health while allowing users to interact with visuals and download data provided in the platform. Interactive dashboards create new opportunities for scholars and practitioners to generate and test hypotheses. We present the development and implementation of the Global Nutrition and Health Atlas (GNHA; https://sites.tufts.edu/gnha/), an open-access online platform covering nutrition and health data with 26 themes and 500+ indicators from 190+ countries up to 30 y. We view GNHA as an interactive tool aiming to share information and perspectives and foster collaborations and innovations.

Food and Nutrition Systems Dashboards: A Systematic Review.

The rapid expansion of food and nutrition information requires new ways of data sharing and dissemination. Interactive platforms integrating data portals and visualization dashboards have been effectively utilized to describe, monitor, and track information related to food and nutrition; however, a comprehensive evaluation of emerging interactive systems is lacking. We conducted a systematic review on publicly available dashboards using a set of 48 evaluation metrics for data integrity, completeness, granularity, visualization quality, and interactivity based on 4 major principles: evidence, efficiency, emphasis, and ethics. We evaluated 13 dashboards, summarized their characteristics, strengths, and limitations, and provided guidelines for developing nutrition dashboards. We applied mixed effects models to summarize evaluation results adjusted for interrater variability. The proposed metrics and evaluation principles help to improve data standardization and harmonization, dashboard performance and usability, broaden information and knowledge sharing among researchers, practitioners, and decision makers in the field of food and nutrition, and accelerate data literacy and communication.

Evaluating Completeness of Foodborne Outbreak Reporting in the United States, 1998-2019.

Public health agencies routinely collect time-referenced records to describe and compare foodborne outbreak characteristics. Few studies provide comprehensive metadata to inform researchers of data limitations prior to conducting statistical modeling. We described the completeness of 103 variables for 22,792 outbreaks publicly reported by the United States Centers for Disease Control and Prevention's (US CDC's) electronic Foodborne Outbreak Reporting System (eFORS) and National Outbreak Reporting System (NORS). We compared monthly trends of completeness during eFORS (1998−2008) and NORS (2009−2019) reporting periods using segmented time series analyses adjusted for seasonality. We quantified the overall, annual, and monthly completeness as the percentage of outbreaks with blank records per our study period, calendar year, and study month, respectively. We found that outbreaks of unknown genus (n = 7401), Norovirus (n = 6414), Salmonella (n = 2872), Clostridium (n = 944), and multiple genera (n = 779) accounted for 80.77% of all outbreaks. However, crude completeness ranged from 46.06% to 60.19% across the 103 variables assessed. Variables with the lowest crude completeness (ranging 3.32−6.98%) included pathogen, specimen etiological testing, and secondary transmission traceback information. Variables with low (<35%) average monthly completeness during eFORS increased by 0.33−0.40%/month after transitioning to NORS, most likely due to the expansion of surveillance capacity and coverage within the new reporting system. Examining completeness metrics in outbreak surveillance systems provides essential information on the availability of data for public reuse. These metadata offer important insights for public health statisticians and modelers to precisely monitor and track the geographic spread, event duration, and illness intensity of foodborne outbreaks.

Can collaborative innovation constrain ecological footprint? Empirical evidence from Guangdong-Hong Kong-Macao Greater Bay Area, China.

Collaborative innovation can promote scientific productivity and the development of clean technology and thus has a great potential in constraining the ecological footprint. However, current studies on the impact of collaborative innovation on ecological footprint are insufficient, and results remain controversial. To better understand these impacts, this paper took Guangdong-Hong Kong-Macao Greater Bay Area of China as a case, estimated the ecological footprint at the municipal level from 2008 to 2018, measured collaborative innovation both from four dimensions and from a composite approach, then applied threshold regression models to compare the impact of collaborative innovation on the ecological footprint across different economic intervals. The findings showed that: the ecological footprint of the Greater Bay Area displayed an overall upward trend with prominent spatial heterogeneity. The impact of collaborative innovation on the ecological footprint presented a double-threshold effect when examined with different indicators. Among which, the flow of scientific personnel and capital boosted the ecological footprint, which intensified with economic development, while collaboration in technology exerted significant inhibitory effects on ecological footprint, and the influence of inter-city knowledge collaboration was limited. Overall, collaborative innovation inhibited ecological footprint when measured by a composite index. This might inspire policymakers to adopt sustainable strategies depending on the type of collaborative innovation and the economic status of the city to constrain growth of the ecological footprint, thus minimizing the pressures of human activities on the environment and moving towards a more carbon neutral society.

Retinal Imaging Using a Confocal Scanning Laser Ophthalmoscope-Based High-Magnification Module.

PURPOSE: To evaluate the usefulness of a high-magnification module (HMM) lens to visualize retinal photoreceptors, retinal nerve fiber layer (RNFL), and superficial retinal vasculature in physiologic and pathologic retinal conditions. DESIGN: Observational descriptive study. PARTICIPANTS: Thirty-two participants with normal and pathologic retina examination results. METHODS: Normal and pathologic maculae were imaged in vivo using still and video HMM lens modes, with fixation and contrast adjustments to enhance visualization. The HMM images were classified qualitatively based on structures identified as either good (photoreceptors seen), average (photoreceptor mosaic cannot be visualized clearly, retinal vessels and other retinal changes can be seen), or poor (no identifiable structures). Selected eyes were imaged with fundus photography, OCT, OCT angiography, indocyanine green angiography, and fluorescein angiography for comparison with the pathologic maculae. MAIN OUTCOMES MEASURES: Description of HMM module-obtained macula images. RESULTS: From 32 eyes imaged (16 normal and 16 pathologic retinas), 12 of 16 normal and 11 of 16 pathologic retinas demonstrated at least average image quality, in which retinal vasculature and landmarks could be visualized. The mosaic pattern of hexagonal shapes representing photoreceptors could not be resolved in most pathologic retinas. For the retinas in which the photoreceptor mosaics were visualized (12 of 16 normal and 2 of 16 pathologic retinas), parafoveal mosaic patterns appeared denser with better image quality for all participants compared with foveal photoreceptors. Difficulty in resolving the photoreceptors in the umbo, fovea, and perifovea was encountered, similar to what has been reported with adaptive optics devices. The RNFL was seen as arcuate hyperreflective bundles. Flow was observed in the macular microvasculature. Poorly resolved photoreceptors and scattered hyperreflective foci were correlated with changes in the retinal pigment epithelium in eyes with age-related macular degeneration or central serous chorioretinopathy. Macular striae were seen in eyes with epiretinal membrane. CONCLUSIONS: In most eyes, regardless of whether retinal pathologic features were present, it was challenging to obtain average quality (or better) images. In the few participants with good-quality imaging, the parafoveal photoreceptor mosaic, vascular flow, and various features of pathologic eyes could be visualized.