COVID-19: Forecasting short term hospital needs in France

1AbstractEurope is now considered as the epicenter of the SARS-CoV-2 pandemic, France being among the most impacted country. In France, there is an increasing concern regarding the capacity of the healthcare system to sustain the outbreak, especially regarding intensive care units (ICU). The aim of this study was to estimate the dynamics of the epidemic in France, and to assess its impact on healthcare resources for each French metropolitan Region. We developed a deterministic, age-structured, Susceptible-Exposed-Infectious-Removed (SEIR) model based on catchment areas of each COVID-19 referral hospitals. We performed one month ahead predictions (up to April 14, 2020) for three different scenarios (R0 = 1.5, R0 = 2.25, R0 = 3), where we estimated the daily number of COVID-19 cases, hospitalizations and deaths, the needs in ICU beds per Region and the reaching date of ICU capacity limits. At the national level, the total number of infected cases is expected to range from 22,872 in the best case (R0 = 1.5) to 161,832 in the worst case (R0 = 3), while the total number of deaths would vary from 1,021 to 11,032, respectively. At the regional level, all ICU capacities may be overrun in the worst scenario. Only seven Regions may lack ICU beds in the mild scenario (R0 = 2.25) and only one in the best case. In the three scenarios, Corse may be the first Region to see its ICU capacities overrun. The two other Regions, whose capacity will be overrun shortly after are Grand-Est and Bourgogne-Franche-Comté. Our analysis shows that, even in the best case scenario, the French healthcare system will very soon be overwhelmed. While drastic social distancing measures may temper our results, a massive reorganization leading to an expansion of French ICU capacities seems to be necessary to manage the coming wave of critically affected COVID-19 patients.

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Predicting the impact of COVID-19 on fertility in the Special Region of Yogyakarta, Indonesia

E3S Web of Conferences ◽

10.1051/e3sconf/202132506008 ◽

2021 ◽

Vol 325 ◽

pp. 06008

Author(s):

Muhammad Arif Fahrudin Alfana ◽

Hidayati Nur Rohmah ◽

Salma Nurulhuda ◽

Mohammad Isnaini Sadali

Keyword(s):

Descriptive Analysis ◽

Basic Data ◽

Contraceptive Methods ◽

Short Term ◽

Case Scenario ◽

Worst Case ◽

The Impact ◽

Number Of Births ◽

Pregnancy And Birth ◽

Special Region

The aim of this research is to explain the predicted impact of Covid-19 on fertility in the Special Region of Yogyakarta (DIY). The indicators used are the number of pregnancies and the number of births. To get pregnancy and birth predictions, various basic data were processed using the Spectrum program using the DemProj and Famplan modules, then analyzed by descriptive analysis. The basic data is collected from the Central Statistics Agency (BPS) and other relevant agencies. The result shows that birth and pregnancies in DIY will increase. This prediction is based on the decreasing use of short -term contraceptive methods during the pandemic. In the worst-case scenario, the rise in pregnancies between 2019-2020 would be 67,862 cases, meanwhile births are expected to increase by 37.56 thousand cases during the same period.

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Dynamics of SARS-CoV-2 with waning immunity in the UK population

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2020.0274 ◽

2021 ◽

Vol 376 (1829) ◽

pp. 20200274 ◽

Cited By ~ 1

Author(s):

Thomas Crellen ◽

Li Pi ◽

Emma L. Davis ◽

Timothy M. Pollington ◽

Tim C. D. Lucas ◽

...

Keyword(s):

Deterministic Model ◽

Herd Immunity ◽

Secondary Wave ◽

Daily Maximum ◽

Case Scenario ◽

Worst Case ◽

Policy Makers ◽

Contact Data ◽

Age Structured ◽

The Uk

The dynamics of immunity are crucial to understanding the long-term patterns of the SARS-CoV-2 pandemic. Several cases of reinfection with SARS-CoV-2 have been documented 48–142 days after the initial infection and immunity to seasonal circulating coronaviruses is estimated to be shorter than 1 year. Using an age-structured, deterministic model, we explore potential immunity dynamics using contact data from the UK population. In the scenario where immunity to SARS-CoV-2 lasts an average of three months for non-hospitalized individuals, a year for hospitalized individuals, and the effective reproduction number after lockdown ends is 1.2 (our worst-case scenario), we find that the secondary peak occurs in winter 2020 with a daily maximum of 387 000 infectious individuals and 125 000 daily new cases; threefold greater than in a scenario with permanent immunity. Our models suggest that longitudinal serological surveys to determine if immunity in the population is waning will be most informative when sampling takes place from the end of the lockdown in June until autumn 2020. After this period, the proportion of the population with antibodies to SARS-CoV-2 is expected to increase due to the secondary wave. Overall, our analysis presents considerations for policy makers on the longer-term dynamics of SARS-CoV-2 in the UK and suggests that strategies designed to achieve herd immunity may lead to repeated waves of infection as immunity to reinfection is not permanent. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.

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Determination of the Area Affected by Agricultural Burning

Atmosphere ◽

10.3390/atmos10060312 ◽

2019 ◽

Vol 10 (6) ◽

pp. 312 ◽

Cited By ~ 2

Author(s):

Daniel F. Prato ◽

Jose I. Huertas

Keyword(s):

Burning Rate ◽

Dispersion Model ◽

Point Of View ◽

Short Term ◽

Case Scenario ◽

Worst Case ◽

Area Source ◽

Influence Area ◽

Agricultural Burning ◽

Area Of Influence

Agricultural burning is still a common practice around the world. It is associated with the high emission of air pollutants, including short-term climate change forcing pollutants such as black carbon and PM2.5. The legal requirements to start any regulatory actions to control them is the identification of its area of influence. However, this task is challenging from the experimental and modeling point of view, since it is a short-term event with a moving area source of pollutants. In this work, we assessed this agricultural burning influence-area using the US Environmental authorities recommended air dispersion model (AERMOD). We considered different sizes and geometries of burning areas located on flat terrains, and several crops burning under the worst-case scenario of meteorological conditions. The influence area was determined as the largest area where the short-term concentrations of pollutants (1 h or one day) exceed the local air quality standards. We found that this area is a band around the burning area whose size increases with the burning rate but not with its size. Finally, we suggested alternatives of public policy to regulate this activity, which is based on limiting the burning-rate in the way that no existing households remain inside the resulting influence-area. However, this policy should be understood as a transition towards a policy that forbids agricultural burning.

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Prediction of Future Natural Suitable Areas for Rice under Representative Concentration Pathways (RCPs)

Sustainability ◽

10.3390/su13031580 ◽

2021 ◽

Vol 13 (3) ◽

pp. 1580

Author(s):

Peng Su ◽

Anyu Zhang ◽

Ran Wang ◽

Jing’ai Wang ◽

Yuan Gao ◽

...

Keyword(s):

Climate Change ◽

Crop Production ◽

Extreme Temperature ◽

Temperature Sensitive ◽

Medium Term ◽

Short Term ◽

Case Scenario ◽

Intergovernmental Panel ◽

Worst Case ◽

Maxent Model

Extreme temperature events, which are part of global climate change, are a growing threat to crop production, especially to such temperature-sensitive crops as rice. As a result, the traditional rice-growing areas are also likely to shift. The MaxEnt model was used for predicting the areas potentially suitable for rice in the short term (2016–2035) and in the medium term (2046–2065) and under two scenarios developed by the Intergovernmental Panel on Climate Change, namely representative concentration pathway (RCP) 4.5 (the intermediate scenario) and RCP 8.5 (sometimes referred to as the worst-case scenario). The predictions, on verification, were seen to be highly accurate: the AUC—area under the curve—value of the MaxEnt model was > 0.85. The model made the following predictions. (1) Areas highly suitable for rice crops will continue to be concentrated mainly in the current major rice-production areas, and areas only marginally suitable will be concentrated mainly in the rainforest region. (2) Overall, although the current pattern of the distribution of such areas would remain more or less unchanged, their extent will mainly decrease in the subtropics but increase in the tropics and in high-latitude regions. (3) The extent of such areas will decrease in the short term but increase in the medium term.

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Implications of the COVID-19 pandemic

EUROPOLITY CONTINUITY AND CHANGE IN EUROPEAN GOVERNANCE ◽

10.25019/europolity.2020.14.2.2 ◽

2020 ◽

Vol 14 (2) ◽

Author(s):

Ioan Mircea PAȘCU ◽

◽

Alexandra NUNWEILLER-BĂLĂNESCU

Keyword(s):

International System ◽

National Level ◽

World Order ◽

Lessons Learned ◽

Case Scenario ◽

Worst Case ◽

Recent Developments ◽

Multiple Challenges ◽

International Power ◽

The Impact

The global order was facing multiple challenges even before the pandemic, so it is very likely – based on the evolutions recorded since the beginning of 2020 – that these challenges will further amplify. On the impact of COVID-19 on the world order, opinions of political scientists vary greatly, from reserved optimism to worst-case scenario, from treating it as a simple inflexion point to forecasting the transformative changes it will entail. In this article we argue that this current pandemic will only accelerate previous trends by deepening international power competition, thus accelerating the transition towards a more realist world order. This working hypothesis disregards potential non-linear events that might occur from this point on and that could impact all forecasts. In this article we discuss the structure of the current international system and we analyze recent developments, thus trying to determine which specific trends will be accelerated. Furthermore, we examine the „lessons” learned so far and try to determine what can be done to limit the consequences of the pandemic, at least at the national level.

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Dynamics of SARS-CoV-2 with Waning Immunity in the UK Population

10.1101/2020.07.24.20157982 ◽

2020 ◽

Author(s):

Thomas Crellen ◽

Li Pi ◽

Emma Davis ◽

Timothy M Pollington ◽

Tim C D Lucas ◽

...

Keyword(s):

Deterministic Model ◽

Herd Immunity ◽

Secondary Peak ◽

Daily Maximum ◽

Case Scenario ◽

Worst Case ◽

Antibody Titres ◽

Contact Data ◽

Age Structured ◽

The Uk

The dynamics of immunity are crucial to understanding the long-term patterns of the SARS-CoV-2 pandemic. While the duration and strength of immunity to SARS-CoV-2 is currently unknown, specific antibody titres to related coronaviruses SARS-CoV and MERS-CoV have been shown to wane in recovered individuals, and immunity to seasonal circulating coronaviruses is estimated to be shorter than one year. Using an age-structured, deterministic model, we explore different potential immunity dynamics using contact data from the UK population. In the scenario where immunity to SARS-CoV-2 lasts an average of three months for non-hospitalised individuals, a year for hospitalised individuals, and the effective reproduction number (Rt) after lockdown is 1.2 (our worst case scenario), we find that the secondary peak occurs in winter 2020 with a daily maximum of 409,000 infectious individuals; almost three-fold greater than in a scenario with permanent immunity. Our models suggests that longitudinal serological surveys to determine if immunity in the population is waning will be most informative when sampling takes place from the end of the lockdown until autumn 2020. After this period, the proportion of the population with antibodies to SARS-CoV-2 is expected to increase due to the secondary peak. Overall, our analysis presents considerations for policy makers on the longer term dynamics of SARS-CoV-2 in the UK and suggests that strategies designed to achieve herd immunity may lead to repeated waves of infection if immunity to re-infection is not permanent.

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Reducing Probabilistic Weather Forecasts to the Worst Case Scenario: Anchoring Effects

PsycEXTRA Dataset ◽

10.1037/e527312012-643 ◽

2008 ◽

Author(s):

Sonia Savelli ◽

Susan Joslyn ◽

Limor Nadav-Greenberg ◽

Queena Chen

Keyword(s):

Case Scenario ◽

Worst Case ◽

Weather Forecasts ◽

Worst Case Scenario ◽

Anchoring Effects

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EXPEDITION TO MALI, 2020

Journal of the Institute of Oriental Studies RAS ◽

10.31696/2618-7302-2020-3-12-28 ◽

2020 ◽

pp. 12-28

Author(s):

D. V. Vaniukova ◽

◽

P. A. Kutsenkov ◽

Keyword(s):

Mass Murder ◽

The State ◽

Case Scenario ◽

Worst Case ◽

Traditional Art ◽

Peter The Great ◽

State Museum ◽

Bobo Dioulasso ◽

Oriental Studies ◽

The Village

The research expedition of the Institute of Oriental studies of the Russian Academy of Sciences has been working in Mali since 2015. Since 2017, it has been attended by employees of the State Museum of the East. The task of the expedition is to study the transformation of traditional Dogon culture in the context of globalization, as well as to collect ethnographic information (life, customs, features of the traditional social and political structure); to collect oral historical legends; to study the history, existence, and transformation of artistic tradition in the villages of the Dogon Country in modern conditions; collecting items of Ethnography and art to add to the collection of the African collection of the. Peter the Great Museum (Kunstkamera, Saint Petersburg) and the State Museum of Oriental Arts (Moscow). The plan of the expedition in January 2020 included additional items, namely, the study of the functioning of the antique market in Mali (the “path” of things from villages to cities, which is important for attributing works of traditional art). The geography of our research was significantly expanded to the regions of Sikasso and Koulikoro in Mali, as well as to the city of Bobo-Dioulasso and its surroundings in Burkina Faso, which is related to the study of migrations to the Bandiagara Highlands. In addition, the plan of the expedition included organization of a photo exhibition in the Museum of the village of Endé and some educational projects. Unfortunately, after the mass murder in March 2019 in the village of Ogossogou-Pel, where more than one hundred and seventy people were killed, events in the Dogon Country began to develop in the worst-case scenario: The incessant provocations after that revived the old feud between the Pel (Fulbe) pastoralists and the Dogon farmers. So far, this hostility and mutual distrust has not yet developed into a full-scale ethnic conflict, but, unfortunately, such a development now seems quite likely.

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Risk-Based Robust Bidding Strategies for EVs’ Aggregators in Day-ahead Markets with Uncertainty

10.36227/techrxiv.12771257 ◽

2020 ◽

Author(s):

Ahmed Abdelmoaty ◽

Wessam Mesbah ◽

Mohammad A. M. Abdel-Aal ◽

Ali T. Alawami

Keyword(s):

Robust Optimization ◽

Electricity Market ◽

Real Life ◽

Optimization Approach ◽

Case Scenario ◽

Worst Case ◽

Bidding Strategies ◽

Wind Generators ◽

Proposed Model ◽

Optimal Bidding

In the recent electricity market framework, the profit of the generation companies depends on the decision of the operator on the schedule of its units, the energy price, and the optimal bidding strategies. Due to the expanded integration of uncertain renewable generators which is highly intermittent such as wind plants, the coordination with other facilities to mitigate the risks of imbalances is mandatory. Accordingly, coordination of wind generators with the evolutionary Electric Vehicles (EVs) is expected to boost the performance of the grid. In this paper, we propose a robust optimization approach for the coordination between the wind-thermal generators and the EVs in a virtual<br>power plant (VPP) environment. The objective of maximizing the profit of the VPP Operator (VPPO) is studied. The optimal bidding strategy of the VPPO in the day-ahead market under uncertainties of wind power, energy<br>prices, imbalance prices, and demand is obtained for the worst case scenario. A case study is conducted to assess the e?effectiveness of the proposed model in terms of the VPPO's profit. A comparison between the proposed model and the scenario-based optimization was introduced. Our results confirmed that, although the conservative behavior of the worst-case robust optimization model, it helps the decision maker from the fluctuations of the uncertain parameters involved in the production and bidding processes. In addition, robust optimization is a more tractable problem and does not suffer from<br>the high computation burden associated with scenario-based stochastic programming. This makes it more practical for real-life scenarios.<br>

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A Thermally Conductive Pt/AAO Catalyst for Hydrogen Passive Autocatalytic Recombination

Catalysts ◽

10.3390/catal11040491 ◽

2021 ◽

Vol 11 (4) ◽

pp. 491

Author(s):

Alina E. Kozhukhova ◽

Stephanus P. du Preez ◽

Aleksander A. Malakhov ◽

Dmitri G. Bessarabov

Keyword(s):

Electron Microscopy ◽

Particle Size ◽

Combustion Temperature ◽

Volume Fraction ◽

Morphological Characteristics ◽

Al Alloy ◽

Impregnation Method ◽

Case Scenario ◽

Worst Case ◽

Thermal Distribution

In this study, a Pt/anodized aluminum oxide (AAO) catalyst was prepared by the anodization of an Al alloy (Al6082, 97.5% Al), followed by the incorporation of Pt via an incipient wet impregnation method. Then, the Pt/AAO catalyst was evaluated for autocatalytic hydrogen recombination. The Pt/AAO catalyst’s morphological characteristics were determined by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The average Pt particle size was determined to be 3.0 ± 0.6 nm. This Pt/AAO catalyst was tested for the combustion of lean hydrogen (0.5–4 vol% H2 in the air) in a recombiner section testing station. The thermal distribution throughout the catalytic surface was investigated at 3 vol% hydrogen (H2) using an infrared camera. The Al/AAO system had a high thermal conductivity, which prevents the formation of hotspots (areas where localized surface temperature is higher than an average temperature across the entire catalyst surface). In turn, the Pt stability was enhanced during catalytic hydrogen combustion (CHC). A temperature gradient over 70 mm of the Pt/AAO catalyst was 23 °C and 42 °C for catalysts with uniform and nonuniform (worst-case scenario) Pt distributions. The commercial computational fluid dynamics (CFD) code STAR-CCM+ was used to compare the experimentally observed and numerically simulated thermal distribution of the Pt/AAO catalyst. The effect of the initial H2 volume fraction on the combustion temperature and conversion of H2 was investigated. The activation energy for CHC on the Pt/AAO catalyst was 19.2 kJ/mol. Prolonged CHC was performed to assess the durability (reactive metal stability and catalytic activity) of the Pt/AAO catalyst. A stable combustion temperature of 162.8 ± 8.0 °C was maintained over 530 h of CHC. To confirm that Pt aggregation was avoided, the Pt particle size and distribution were determined by TEM before and after prolonged CHC.

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