ABSTRACT
Several models have correlated COVID-19 spread with specific climatic, geophysical, and air pollution conditions, and early models had predicted the lowering of infection cases in Summer 2020. These approaches have been criticized for their coarse assumptions and because they could produce biases if used without considering dynamic factors such as human mobility and interaction. However, human mobility and interaction models alone have not been able to suggest more innovative recommendations than simple social distancing and lockdown, and would definitely need to include information about the base environmental suitability of a World area to COVID-19 spread. This scenario would benefit from a global-scale high-resolution environmental model that could be coupled with dynamic models for large-scale and regional analyses. This article presents a 0.1 degrees high-resolution global-scale probability map of low and high-infection-rates of COVID-19 that uses annual-average surface air temperature, precipitation, and CO2 as environmental parameters, and Italian provinces as training locations. A risk index calculated on this map correctly identifies 87% of theWorld countries that reported high infection rates in 2020 and 80% of the low and high infection-rate countries overall. Our model is meant to be used as an additional factor in other models for monthly weather and human mobility. It estimates the base environmental inertia that a geographical place opposes to COVID-19 when mobility restrictions are not in place and can support how much the monthly weather favors or penalizes infection increase. Its high resolution and extent make it consistently usable in global and regional-scale analyses, also thanks to the availability of our results as FAIR data and software as an Open Science-oriented Web service.
ABSTRACT
International scientific fishery survey programmes systematically collect samples of target stocks’ biomass and abundance and use them as the basis to estimate stock status in the framework of stock assessment models. The research surveys can also inform decision makers about Essential Fish Habitat conservation and help define harvest control rules based on direct observation of biomass at the sea. However, missed survey locations over the survey years are common in long-term programme data. Currently, modelling approaches to filling gaps in spatiotemporal survey data range from quickly applicable solutions to complex modelling. Most models require setting prior statistical assumptions on spatial distributions, assuming short-term temporal dependency between the data, and scarcely considering the environmental aspects that might have influenced stock presence in the missed locations. This paper proposes a statistical and machine learning based model to fill spatiotemporal gaps in survey data and produce robust estimates for stock assessment experts, decision makers, and regional fisheries management organizations. We apply our model to the SoleMon survey data in North-Central Adriatic Sea (Mediterranean Sea) for 4 stocks: Sepia officinalis, Solea solea, Squilla mantis, and Pecten jacobaeus. We reconstruct the biomass-index (i.e., biomass over the swept area) of 10 locations missed in 2020 (out of the 67 planned) because of several factors, including COVID-19 pandemic related restrictions. We evaluate model performance on 2019 data with respect to an alternative index that assumes biomass proportion consistency over time. Our model’s novelty is that it combines three complementary components. A spatial component estimates stock biomass-index in the missed locations in one year, given the surveyed location’s biomass-index distribution in the same year. A temporal component forecasts, for each missed survey location, biomass-index given the data history of that haul. An environmental component estimates a biomass-index weighting factor based on the environmental suitability of the haul area to species presence. Combining these components allows understanding the interplay between environmental-change drivers, stock presence, and fisheries. Our model formulation is general enough to be applied to other survey data with lower spatial homogeneity and more temporal gaps than the SoleMon dataset. Copyright © 2022 Coro, Bove, Armelloni, Masnadi, Scanu and Scarcella.
ABSTRACT
Introduction: COVID-19 outbreak represented an unprecedented event that led to a redefinition of health care systems worldwide. The impact of the emergency required a deviation of the care toward the assistance to COVID-19 patients, with reduction of resources for elective activities, including surgery. We aim to report the decrease of urological surgical activity during the first weeks from the beginning of the pandemic, aiming to highlight the prioritization we applied to select patients for surgery. Materials and methods: Thirty-three urological units with physicians affiliated to the AGILE group were involved in a survey. Urologists were asked to report the amount of surgical elective procedures week- by-week, from the beginning of the emergency to the following month. The type of surgery (oncologic, for urolithiasis, for benign prostate obstruction, other) was assessed as well. Results: The 33 hospitals involved in the study account, globally, for 22,945 beds and are distributed in 13/20 Italian regions. Before the outbreak, the involved urology units performed an overall amount of 1,213 procedures per week, half of which were oncological. By the 20 of March, the amount of surgery declined by 78%. Lombardy, the first region with positive-cases, experienced a 94% reduction. The decrease in oncological and non- oncological surgical activity was 35,9% and 89%, respectively. Among non-oncological procedures, stone surgery declined by 35,9% as well, whereas BPH and minor urological procedures completely dropped. Reassessing for surgical activity on 20, April, a slight trend toward surgical restoration (+11%) started to appear. Conclusions: Italy, the country with the highest fatality rate from COVID-19, had experienced a sudden decline in surgical activity;by the end of April, a current trend toward restoration of surgery started to appear. Criteria for prioritization were consistent with an urgent/ emergent principle, with trauma, tumours and septic conditions being the ones prioritized. The Italian experience can be helpful for future surgical pre-planning in other countries or pandemic settings. Smart Communications (SC1–SC28) Andrology