scholarly journals Optimal national prioritization policies for hospital care during the SARS-CoV-2 pandemic

2021 ◽  
Author(s):  
Josh C. D’Aeth ◽  
Shubhechyya Ghosal ◽  
Fiona Grimm ◽  
David Haw ◽  
Esma Koca ◽  
...  
Keyword(s):  
Hospital Care ◽  
Large Scale ◽  
Ad Hoc ◽  
National Level ◽  
Years Of Life Lost ◽  
Discrete Optimization Problem ◽  
Computationally Efficient ◽  
Health Gains ◽  
Life Saving ◽  
Efficient Approximation

AbstractIn response to unprecedented surges in the demand for hospital care during the SARS-CoV-2 pandemic, health systems have prioritized patients with COVID-19 to life-saving hospital care to the detriment of other patients. In contrast to these ad hoc policies, we develop a linear programming framework to optimally schedule elective procedures and allocate hospital beds among all planned and emergency patients to minimize years of life lost. Leveraging a large dataset of administrative patient medical records, we apply our framework to the National Health Service in England and show that an extra 50,750–5,891,608 years of life can be gained compared with prioritization policies that reflect those implemented during the pandemic. Notable health gains are observed for neoplasms, diseases of the digestive system, and injuries and poisoning. Our open-source framework provides a computationally efficient approximation of a large-scale discrete optimization problem that can be applied globally to support national-level care prioritization policies.

scholarly journals MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning

Entropy ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 551 ◽  
Author(s):  
Diego Granziol ◽  
Binxin Ru ◽  
Stefan Zohren ◽  
Xiaowen Dong ◽  
Michael Osborne ◽  
...  
Keyword(s):  
Machine Learning ◽  
Maximum Entropy ◽  
Large Scale ◽  
Maximum Entropy Method ◽  
Entropy Method ◽  
Variational Inference ◽  
Learning Problems ◽  
Computationally Efficient ◽  
Information Theoretic ◽  
Efficient Approximation

Efficient approximation lies at the heart of large-scale machine learning problems. In this paper, we propose a novel, robust maximum entropy algorithm, which is capable of dealing with hundreds of moments and allows for computationally efficient approximations. We showcase the usefulness of the proposed method, its equivalence to constrained Bayesian variational inference and demonstrate its superiority over existing approaches in two applications, namely, fast log determinant estimation and information-theoretic Bayesian optimisation.

Cloud-Based Multimedia Content Protection System

2020 ◽  
pp. 164-169
Author(s):  
B. Aparna ◽  
S. Madhavi ◽  
G. Mounika ◽  
P. Avinash ◽  
S. Chakravarthi
Keyword(s):  
Large Scale ◽  
Protection System ◽  
Multimedia Content ◽  
Computationally Efficient ◽  
Content Protection ◽  
Protection Systems ◽  
Multimedia Content Protection ◽  
High Scalability ◽  
Cloud Infrastructures ◽  
Rapid Deployment

We propose a new design for large-scale multimedia content protection systems. Our design leverages cloud infrastructures to provide cost efficiency, rapid deployment, scalability, and elasticity to accommodate varying workloads. The proposed system can be used to protect different multimedia content types, including videos, images, audio clips, songs, and music clips. The system can be deployed on private and/or public clouds. Our system has two novel components: (i) method to create signatures of videos, and (ii) distributed matching engine for multimedia objects. The signature method creates robust and representative signatures of videos that capture the depth signals in these videos and it is computationally efficient to compute and compare as well as it requires small storage. The distributed matching engine achieves high scalability and it is designed to support different multimedia objects. We implemented the proposed system and deployed it on two clouds: Amazon cloud and our private cloud. Our experiments with more than 11,000 videos and 1 million images show the high accuracy and scalability of the proposed system. In addition, we compared our system to the protection system used by YouTube and our results show that the YouTube protection system fails to detect most copies of videos, while our system detects more than 98% of them.

TBE in Italy

2020 ◽  
Keyword(s):  
Surveillance System ◽  
Ad Hoc ◽  
National Level ◽  
Case Series ◽  
Incidence Rates ◽  
Mountainous Regions ◽  
North East ◽  
The North ◽  
Tick Borne Encephalitis ◽  
Low Incidence

Italy is considered a low-incidence country for tick-borne encephalitis (TBE) in Europe.1 Areas at higher risk for TBE in Italy are geographically clustered in the forested and mountainous regions and provinces in the north east part of the country, as suggested by TBE case series published over the last decade.2-5 A national enhanced surveillance system for TBE has been established since 2017.6 Before this, information on the occurrence of TBE cases at the national level in Italy was lacking. Both incidence rates and the geographical distribution of the disease were mostly inferred from endemic areas where surveillance was already in place, ad hoc studies and international literature.1

HOME VISITS DURING THE FIRST MONTH OF DELIVERY FOR RECENTLY DELIVERED WOMEN IN UTTAR PRADESH, INDIA

2020 ◽  
Vol 6 (5) ◽  
pp. 1183-1189
Author(s):  
Dr. Tridibesh Tripathy ◽  
Dr. Umakant Prusty ◽  
Dr. Chintamani Nayak ◽  
Dr. Rakesh Dwivedi ◽  
Dr. Mohini Gautam
Keyword(s):  
Large Scale ◽  
National Level ◽  
Uttar Pradesh ◽  
Life Time ◽  
Structured Interview ◽  
The Other ◽  
Registration System ◽  
Action Group ◽  
Current Article ◽  
The Impact

The current article of Uttar Pradesh (UP) is about the ASHAs who are the daughters-in-law of a family that resides in the same community that they serve as the grassroots health worker since 2005 when the NRHM was introduced in the Empowered Action Group (EAG) states. UP is one such Empowered Action Group (EAG) state. The current study explores the actual responses of Recently Delivered Women (RDW) on their visits during the first month of their recent delivery. From the catchment area of each of the 250 ASHAs, two RDWs were selected who had a child in the age group of 3 to 6 months during the survey. The response profiles of the RDWs on the post- delivery first month visits are dwelled upon to evolve a picture representing the entire state of UP. The relevance of the study assumes significance as detailed data on the modalities of postnatal visits are available but not exclusively for the first month period of their recent delivery. The details of the post-delivery first month period related visits are not available even in large scale surveys like National Family Health Survey 4 done in 2015-16. The current study gives an insight in to these visits with a five-point approach i.e. type of personnel doing the visit, frequency of the visits, visits done in a particular week from among those four weeks separately for the three visits separately. The current study is basically regarding the summary of this Penta approach for the post- delivery one-month period.     The first month period after each delivery deals with 70% of the time of the postnatal period & the entire neonatal period. Therefore, it does impact the Maternal Mortality Rate & Ratio (MMR) & the Neonatal Mortality Rates (NMR) in India and especially in UP through the unsafe Maternal & Neonatal practices in the first month period after delivery. The current MM Rate of UP is 20.1 & MM Ratio is 216 whereas the MM ratio is 122 in India (SRS, 2019). The Sample Registration System (SRS) report also mentions that the Life Time Risk (LTR) of a woman in pregnancy is 0.7% which is the highest in the nation (SRS, 2019). This means it is very risky to give birth in UP in comparison to other regions in the country (SRS, 2019). This risk is at the peak in the first month period after each delivery. Similarly, the current NMR in India is 23 per 1000 livebirths (UNIGME,2018). As NMR data is not available separately for states, the national level data also hold good for the states and that’s how for the state of UP as well. These mortalities are the impact indicators and such indicators can be reduced through long drawn processes that includes effective and timely visits to RDWs especially in the first month period after delivery. This would help in making their post-natal & neonatal stage safe. This is the area of post-delivery first month visit profile detailing that the current article helps in popping out in relation to the recent delivery of the respondents.   A total of four districts of Uttar Pradesh were selected purposively for the study and the data collection was conducted in the villages of the respective districts with the help of a pre-tested structured interview schedule with both close-ended and open-ended questions.  The current article deals with five close ended questions with options, two for the type of personnel & frequency while the other three are for each of the three visits in the first month after the recent delivery of respondents. In addition, in-depth interviews were also conducted amongst the RDWs and a total 500 respondents had participated in the study.   Among the districts related to this article, the results showed that ASHA was the type of personnel who did the majority of visits in all the four districts. On the other hand, 25-40% of RDWs in all the 4 districts replied that they did not receive any visit within the first month of their recent delivery. Regarding frequency, most of the RDWs in all the 4 districts received 1-2 times visits by ASHAs.   Regarding the first visit, it was found that the ASHAs of Barabanki and Gonda visited less percentage of RDWs in the first week after delivery. Similarly, the second visit revealed that about 1.2% RDWs in Banda district could not recall about the visit. Further on the second visit, the RDWs responded that most of them in 3 districts except Gonda district did receive the second postnatal visit in 7-15 days after their recent delivery. Less than half of RDWs in Barabanki district & just more than half of RDWs in Gonda district received the third visit in 15-21 days period after delivery. For the same period, the majority of RDWs in the rest two districts responded that they had been entertained through a home visit.

scholarly journals Analysis of 220 Years of Floodplain Population Dynamics in the US at Different Spatial Scales

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 141
Author(s):  
Firoza Akhter ◽  
Maurizio Mazzoleni ◽  
Luigia Brandimarte
Keyword(s):  
Population Dynamics ◽  
Large Scale ◽  
Spatial Scales ◽  
National Level ◽  
State Level ◽  
Economic Activities ◽  
Protection Measures ◽  
Management Planning ◽  
The Us ◽  
Over Time

In this study, we explore the long-term trends of floodplain population dynamics at different spatial scales in the contiguous United States (U.S.). We exploit different types of datasets from 1790–2010—i.e., decadal spatial distribution for the population density in the US, global floodplains dataset, large-scale data of flood occurrence and damage, and structural and nonstructural flood protection measures for the US. At the national level, we found that the population initially settled down within the floodplains and then spread across its territory over time. At the state level, we observed that flood damages and national protection measures might have contributed to a learning effect, which in turn, shaped the floodplain population dynamics over time. Finally, at the county level, other socio-economic factors such as local flood insurances, economic activities, and socio-political context may predominantly influence the dynamics. Our study shows that different influencing factors affect floodplain population dynamics at different spatial scales. These facts are crucial for a reliable development and implementation of flood risk management planning.

scholarly journals GIANA allows computationally-efficient TCR clustering and multi-disease repertoire classification by isometric transformation

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hongyi Zhang ◽  
Xiaowei Zhan ◽  
Bo Li
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Large Scale ◽  
Cell Receptor ◽  
Alignment Algorithm ◽  
Computationally Efficient ◽  
Antigen Specificity ◽  
Non Invasive ◽  
Isometric Transformation ◽  
Specific Receptors

AbstractSimilarity in T-cell receptor (TCR) sequences implies shared antigen specificity between receptors, and could be used to discover novel therapeutic targets. However, existing methods that cluster T-cell receptor sequences by similarity are computationally inefficient, making them impractical to use on the ever-expanding datasets of the immune repertoire. Here, we developed GIANA (Geometric Isometry-based TCR AligNment Algorithm) a computationally efficient tool for this task that provides the same level of clustering specificity as TCRdist at 600 times its speed, and without sacrificing accuracy. GIANA also allows the rapid query of large reference cohorts within minutes. Using GIANA to cluster large-scale TCR datasets provides candidate disease-specific receptors, and provides a new solution to repertoire classification. Querying unseen TCR-seq samples against an existing reference differentiates samples from patients across various cohorts associated with cancer, infectious and autoimmune disease. Our results demonstrate how GIANA could be used as the basis for a TCR-based non-invasive multi-disease diagnostic platform.

PP469 From Theory To Practice: Which Value Framework Is Applied For Onco-Hematology Therapies In Italy? A 5-year Retrospective Analysis

2020 ◽  
Vol 36 (S1) ◽  
pp. 37-37
Author(s):  
Americo Cicchetti ◽  
Rossella Di Bidino ◽  
Entela Xoxi ◽  
Irene Luccarini ◽  
Alessia Brigido
Keyword(s):  
Real World ◽  
Ad Hoc ◽  
Grey Literature ◽  
National Level ◽  
Pharmaceutical Products ◽  
European Medicines Agency ◽  
The Real ◽  
R Process ◽  
The One ◽  
The Impact

IntroductionDifferent value frameworks (VFs) have been proposed in order to translate available evidence on risk-benefit profiles of new treatments into Pricing & Reimbursement (P&R) decisions. However limited evidence is available on the impact of their implementation. It's relevant to distinguish among VFs proposed by scientific societies and providers, which usually are applicable to all treatments, and VFs elaborated by regulatory agencies and health technology assessment (HTA), which focused on specific therapeutic areas. Such heterogeneity in VFs has significant implications in terms of value dimension considered and criteria adopted to define or support a price decision.MethodsA literature research was conducted to identify already proposed or adopted VF for onco-hematology treatments. Both scientific and grey literature were investigated. Then, an ad hoc data collection was conducted for multiple myeloma; breast, prostate and urothelial cancer; and Non Small Cell Lung Cancer (NSCLC) therapies. Pharmaceutical products authorized by European Medicines Agency from January 2014 till December 2019 were identified. Primary sources of data were European Public Assessment Reports and P&R decision taken by the Italian Medicines Agency (AIFA) till September 2019.ResultsThe analysis allowed to define a taxonomy to distinguish categories of VF relevant to onco-hematological treatments. We identified the “real-world” VF that emerged given past P&R decisions taken at the Italian level. Data was collected both for clinical and economical outcomes/indicators, as well as decisions taken on innovativeness of therapies. Relevant differences emerge between the real world value framework and the one that should be applied given the normative framework of the Italian Health System.ConclusionsThe value framework that emerged from the analysis addressed issues of specific aspects of onco-hematological treatments which emerged during an ad hoc analysis conducted on treatment authorized in the last 5 years. The perspective adopted to elaborate the VF was the one of an HTA agency responsible for P&R decisions at a national level. Furthermore, comparing a real-world value framework with the one based on the general criteria defined by the national legislation, our analysis allowed identification of the most critical point of the current national P&R process in terms ofsustainability of current and future therapies as advance therapies and agnostic-tumor therapies.

scholarly journals Allometric Equations for Estimating Biomass and Carbon Stocks in Afforested Open Woodlands with Black Spruce and Jack Pine, in the Eastern Canadian Boreal Forest

Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 59
Author(s):  
Olivier Fradette ◽  
Charles Marty ◽  
Pascal Tremblay ◽  
Daniel Lord ◽  
Jean-François Boucher
Keyword(s):  
Large Scale ◽  
Ad Hoc ◽  
Black Spruce ◽  
Tree Height ◽  
Jack Pine ◽  
Carbon Stocks ◽  
Allometric Equations ◽  
C Stocks ◽  
The Difference ◽  
Canadian Boreal Forest

Allometric equations use easily measurable biometric variables to determine the aboveground and belowground biomasses of trees. Equations produced for estimating the biomass within Canadian forests at a large scale have not yet been validated for eastern Canadian boreal open woodlands (OWs), where trees experience particular environmental conditions. In this study, we harvested 167 trees from seven boreal OWs in Quebec, Canada for biomass and allometric measurements. These data show that Canadian national equations accurately predict the whole aboveground biomass for both black spruce and jack pine trees, but underestimated branches biomass, possibly owing to a particular tree morphology in OWs relative to closed-canopy stands. We therefore developed ad hoc allometric equations based on three power models including diameter at breast height (DBH) alone or in combination with tree height (H) as allometric variables. Our results show that although the inclusion of H in the model yields better fits for most tree compartments in both species, the difference is minor and does not markedly affect biomass C stocks at the stand level. Using these newly developed equations, we found that carbon stocks in afforested OWs varied markedly among sites owing to differences in tree growth and species. Nine years after afforestation, jack pine plantations had accumulated about five times more carbon than black spruce plantations (0.14 vs. 0.80 t C·ha−1), highlighting the much larger potential of jack pine for OW afforestation projects in this environment.

scholarly journals Sensor System: A Survey of Sensor Type, Ad Hoc Network Topology and Energy Harvesting Techniques

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 219
Author(s):  
Phuoc Duc Nguyen ◽  
Lok-won Kim
Keyword(s):  
Energy Harvesting ◽  
Large Scale ◽  
Ad Hoc ◽  
Sensor Nodes ◽  
Sensor System ◽  
Wireless Sensor ◽  
The Internet ◽  
Original Research ◽  
Energy Scavenging ◽  
Term Operation

People nowadays are entering an era of rapid evolution due to the generation of massive amounts of data. Such information is produced with an enormous contribution from the use of billions of sensing devices equipped with in situ signal processing and communication capabilities which form wireless sensor networks (WSNs). As the number of small devices connected to the Internet is higher than 50 billion, the Internet of Things (IoT) devices focus on sensing accuracy, communication efficiency, and low power consumption because IoT device deployment is mainly for correct information acquisition, remote node accessing, and longer-term operation with lower battery changing requirements. Thus, recently, there have been rich activities for original research in these domains. Various sensors used by processing devices can be heterogeneous or homogeneous. Since the devices are primarily expected to operate independently in an autonomous manner, the abilities of connection, communication, and ambient energy scavenging play significant roles, especially in a large-scale deployment. This paper classifies wireless sensor nodes into two major categories based the types of the sensor array (heterogeneous/homogeneous). It also emphasizes on the utilization of ad hoc networking and energy harvesting mechanisms as a fundamental cornerstone to building a self-governing, sustainable, and perpetually-operated sensor system. We review systems representative of each category and depict trends in system development.

Current State of (Dis)Integration: Public Health and Fusion Centers

2020 ◽  
Vol 17 (2) ◽  
Author(s):  
Cody Minks ◽  
Anke Richter
Keyword(s):  
Public Health ◽  
Law Enforcement ◽  
Information Sharing ◽  
Homeland Security ◽  
Large Scale ◽  
Ad Hoc ◽  
Limiting Factor ◽  
Fusion Centers ◽  
Public Health Emergencies ◽  
Public Health Information

AbstractObjectiveResponding to large-scale public health emergencies relies heavily on planning and collaboration between law enforcement and public health officials. This study examines the current level of information sharing and integration between these domains by measuring the inclusion of public health in the law enforcement functions of fusion centers.MethodsSurvey of all fusion centers, with a 29.9% response rate.ResultsOnly one of the 23 responding fusion centers had true public health inclusion, a decrease from research conducted in 2007. Information sharing is primarily limited to information flowing out of the fusion center, with little public health information coming in. Most of the collaboration is done on a personal, informal, ad-hoc basis. There remains a large misunderstanding of roles, capabilities, and regulations by all parties (fusion centers and public health). The majority of the parties appear to be willing to work together, but there but there is no forward momentum to make these desires a reality. Funding and staffing issues seem to be the limiting factor for integration.ConclusionThese problems need to be urgently addressed to increase public health preparedness and enable a decisive and beneficial response to public health emergencies involving a homeland security response.

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