A multi-resolution ensemble model of three decision-tree-based algorithms to predict daily NO2 concentration in France 2005-2022.

Understanding and managing the health effects of Nitrogen Dioxide (NO2) requires high resolution spatiotemporal exposure maps. Here, we developed a multi-stage multi-resolution ensemble model that predicts daily NO2 concentration across continental France from 2005 to 2022. Innovations of this work include the computation of daily predictions at a 200 m resolution in large urban areas and the use of a spatio-temporal blocking procedure to avoid data leakage and ensure fair performance estimation. Predictions were obtained after three cascading stages of modeling: (1) predicting NO2 total column density from Ozone Monitoring Instrument satellite; (2) predicting daily NO2 concentrations at a 1 km spatial resolution using a large set of potential predictors such as predictions obtained from stage 1, land-cover and road traffic data; and (3) predicting residuals from stage 2 models at a 200 m resolution in large urban areas. The latter two stages used a generalized additive model to ensemble predictions of three decision-tree algorithms (random forest, extreme gradient boosting and categorical boosting). Cross-validated performances of our ensemble models were overall very good, with a ten-fold cross-validated R2 for the 1 km model of 0.83, and of 0.69 for the 200 m model. All three basis learners participated in the ensemble predictions to various degrees depending on time and space. In sum, our multi-stage approach was able to predict daily NO2 concentrations with a relatively low error. Ensembling the predictions maximizes the chance of obtaining accurate values if one basis learner fails in a specific area or at a particular time, by relying on the other learners. To the best of our knowledge, this is the first study aiming to predict NO2 concentrations in France with such a high spatiotemporal resolution, large spatial extent, and long temporal coverage. Exposure estimates are available to investigate NO2 health effects in epidemiological studies.

Validating and Comparing Highly Resolved Commercial "Off the Shelf" PM Monitoring Sensors with Satellite Based Hybrid Models, for Improved Environmental Exposure Assessment.

Particulate matter is a common health hazard, and under certain conditions, an ecological threat. While many studies were conducted in regard to air pollution and potential effects, this paper serves as a pilot scale investigation into the spatial and temporal variability of particulate matter (PM) pollution in arid urban environments in general, and Beer-Sheva, Israel as a case study. We explore the use of commercially off the shelf (COTS) sensors, which provide an economical solution for spatio-temporal measurements. We started with a comparison process against an A-grade meteorological station, where it was shown that under specific climatic conditions, a number of COTS sensors were able to produce robust agreement (mean R2=0.93, average SD=17.5). The second stage examined the COTS sensors that were proven accurate in a mobile measurement campaign. Finally, data collected was compared to a validated satellite prediction model. We present how these tests and COTS sensor-kits could then be used to further explain the continuity and dispersion of particulate matter in similar areas.

Spatiotemporal distribution of autism spectrum disorder prevalence among birth cohorts during 2000-2011 in Israel.

PURPOSE: Studies indicate an apparent sharp increasing trend in autism spectrum disorder (ASD) incidence and prevalence worldwide. This nationwide study aims at depicting ASD prevalence distribution in Israel in both space and time. METHODS: Based on data from Israel National Insurance Institute, the study population included all children born in Israel 2000-2011 (n = 1,786,194), of whom 11,699 (0.655%) were subsequently diagnosed with ASD (until December 31, 2016). Prevalence was calculated and mapped by dividing the number of ASD cases within each year of birth by the number of births during that year, for each spatial unit, and similarly for several spatiotemporal levels of aggregation. RESULTS: ASD prevalence varies substantially across different geographic areas in Israel, with considerably higher prevalence concentrated in central Israel. Strong associations were found between locality-level socioeconomic index, ethnicity, and peripherality and ASD prevalence, and even after adjustment for them, excess prevalence for ASD still persisted in certain localities. No spatial dependence of prevalence, with and without adjustment for the locality-level variables, was found (Moran's I = -0.000546, -0.00335, respectively). CONCLUSIONS: Our findings provide important insights regarding health disparities affecting ASD diagnosis, directing further health policy intervention and further research.

Evidence for the expansion of adult cochlear implant candidacy.

OBJECTIVES: The primary objective of this study was to determine whether a revision and/or expansion of current audiologic cochlear implant candidacy criteria is warranted. DESIGN: The study design was a retrospective review of postoperative speech perception performance for 22 adult cochlear implant recipients who demonstrated preoperative Consonant Nucleus Consonant word recognition scores of 30% or higher in the best-aided condition. This criterion was chosen to exceed that specified by the North American clinical trial of the Nucleus Freedom cochlear implant system. RESULTS: The mean preoperative best-aided monosyllabic word score for the 22 patients was 41% correct. The degree of postoperative benefit for the best postoperative condition (electric only or bimodal) ranged from 10 to 68 percentage points with a mean benefit of 27 percentage points for the electric-only condition and 40 percentage points for the bimodal condition. Statistical analyses revealed highly significant differences between preoperative-aided, implant-only, and bimodal performance on Consonant Nucleus Consonant monosyllabic word recognition performance. That is, both postoperative scores--electric only and bimodal--were significantly different from one another and from the preoperative best-aided performance. CONCLUSIONS: The current results suggest that a large-scale reassessment of manufacturer and Medicare preoperative audiologic candidacy criteria for adults is warranted to allow more hearing-impaired individuals to take advantage of the benefits offered by cochlear implantation.