scholarly journals Data-Driven Deep-Learning Algorithm for Asymptomatic COVID-19 Model with Varying Mitigation Measures and Transmission Rate

Epidemiologia ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 471-489
Author(s):  
K. D. Olumoyin ◽  
A. Q. M. Khaliq ◽  
K. M. Furati

Epidemiological models with constant parameters may not capture satisfactory infection patterns in the presence of pharmaceutical and non-pharmaceutical mitigation measures during a pandemic, since infectiousness is a function of time. In this paper, an Epidemiology-Informed Neural Network algorithm is introduced to learn the time-varying transmission rate for the COVID-19 pandemic in the presence of various mitigation scenarios. There are asymptomatic infectives, mostly unreported, and the proposed algorithm learns the proportion of the total infective individuals that are asymptomatic infectives. Using cumulative and daily reported cases of the symptomatic infectives, we simulate the impact of non-pharmaceutical mitigation measures such as early detection of infectives, contact tracing, and social distancing on the basic reproduction number. We demonstrate the effectiveness of vaccination on the transmission of COVID-19. The accuracy of the proposed algorithm is demonstrated using error metrics in the data-driven simulation for COVID-19 data of Italy, South Korea, the United Kingdom, and the United States.

2021 ◽  
Author(s):  
Marcelo Eduardo Borges ◽  
Leonardo Souto Ferreira ◽  
Silas Poloni ◽  
Ângela Maria Bagattini ◽  
Caroline Franco ◽  
...  

Among the various non–pharmaceutical interventions implemented in response to the Covid–19 pandemic during 2020, school closures have been in place in several countries to reduce infection transmission. Nonetheless, the significant short and long–term impacts of prolonged suspension of in–person classes is a major concern. There is still considerable debate around the best timing for school closure and reopening, its impact on the dynamics of disease transmission, and its effectiveness when considered in association with other mitigation measures. Despite the erratic implementation of mitigation measures in Brazil, school closures were among the first measures taken early in the pandemic in most of the 27 states in the country. Further, Brazil delayed the reopening of schools and stands among the countries in which schools remained closed for the most prolonged period in 2020. To assess the impact of school reopening and the effect of contact tracing strategies in rates of Covid–19 cases and deaths, we model the epidemiological dynamics of disease transmission in 3 large urban centers in Brazil under different epidemiological contexts. We implement an extended SEIR model stratified by age and considering contact networks in different settings – school, home, work, and elsewhere, in which the infection transmission rate is affected by various intervention measures. After fitting epidemiological and demographic data, we simulate scenarios with increasing school transmission due to school reopening. Our model shows that reopening schools results in a non–linear increase of reported Covid-19 cases and deaths, which is highly dependent on infection and disease incidence at the time of reopening. While low rates of within[&ndash]school transmission resulted in small effects on disease incidence (cases/100,000 pop), intermediate or high rates can severely impact disease trends resulting in escalating rates of new cases even if other interventions remain unchanged. When contact tracing and quarantining are restricted to school and home settings, a large number of daily tests is required to produce significant effects of reducing the total number of hospitalizations and deaths. Our results suggest that policymakers should carefully consider the epidemiological context and timing regarding the implementation of school closure and return of in-person school activities. Also, although contact tracing strategies are essential to prevent new infections and outbreaks within school environments, our data suggest that they are alone not sufficient to avoid significant impacts on community transmission in the context of school reopening in settings with high and sustained transmission rates.


Author(s):  
Yi-Tui Chen

Although vaccination is carried out worldwide, the vaccination rate varies greatly. As of 24 May 2021, in some countries, the proportion of the population fully vaccinated against COVID-19 has exceeded 50%, but in many countries, this proportion is still very low, less than 1%. This article aims to explore the impact of vaccination on the spread of the COVID-19 pandemic. As the herd immunity of almost all countries in the world has not been reached, several countries were selected as sample cases by employing the following criteria: more than 60 vaccine doses per 100 people and a population of more than one million people. In the end, a total of eight countries/regions were selected, including Israel, the UAE, Chile, the United Kingdom, the United States, Hungary, and Qatar. The results find that vaccination has a major impact on reducing infection rates in all countries. However, the infection rate after vaccination showed two trends. One is an inverted U-shaped trend, and the other is an L-shaped trend. For those countries with an inverted U-shaped trend, the infection rate begins to decline when the vaccination rate reaches 1.46–50.91 doses per 100 people.


Author(s):  
Funda Hatice Sezgin ◽  
Yilmaz Bayar ◽  
Laura Herta ◽  
Marius Dan Gavriletea

This study explores the impact of environmental policies and human development on the CO2 emissions for the period of 1995–2015 in the Group of Seven and BRICS economies in the long run through panel cointegration and causality tests. The causality analysis revealed a bilateral causality between environmental stringency policies and CO2 emissions for Germany, Japan, the United Kingdom, and the United States of America, and a unilateral causality from CO2 emissions to the environmental stringency policies for Canada, China, and France. On the other hand, the analysis showed a bilateral causality between human development and CO2 emissions for Germany, Japan, the United Kingdom, and the United States of America, and unilateral causality from CO2 emissions to human development in Brazil, Canada, China, and France. Furthermore, the cointegration analysis indicated that both environmental stringency policies and human development had a decreasing impact on the CO2 emissions.


2018 ◽  
Vol 146 (4) ◽  
pp. 1197-1218
Author(s):  
Michèle De La Chevrotière ◽  
John Harlim

This paper demonstrates the efficacy of data-driven localization mappings for assimilating satellite-like observations in a dynamical system of intermediate complexity. In particular, a sparse network of synthetic brightness temperature measurements is simulated using an idealized radiative transfer model and assimilated to the monsoon–Hadley multicloud model, a nonlinear stochastic model containing several thousands of model coordinates. A serial ensemble Kalman filter is implemented in which the empirical correlation statistics are improved using localization maps obtained from a supervised learning algorithm. The impact of the localization mappings is assessed in perfect-model observing system simulation experiments (OSSEs) as well as in the presence of model errors resulting from the misspecification of key convective closure parameters. In perfect-model OSSEs, the localization mappings that use adjacent correlations to improve the correlation estimated from small ensemble sizes produce robust accurate analysis estimates. In the presence of model error, the filter skills of the localization maps trained on perfect- and imperfect-model data are comparable.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Qian Huang ◽  
Xue Wen Li

Big data is a massive and diverse form of unstructured data, which needs proper analysis and management. It is another great technological revolution after the Internet, the Internet of Things, and cloud computing. This paper firstly studies the related concepts and basic theories as the origin of research. Secondly, it analyzes in depth the problems and challenges faced by Chinese government management under the impact of big data. Again, we explore the opportunities that big data brings to government management in terms of management efficiency, administrative capacity, and public services and believe that governments should seize opportunities to make changes. Brainlike computing attempts to simulate the structure and information processing process of biological neural network. This paper firstly analyzes the development status of e-government at home and abroad, studies the service-oriented architecture (SOA) and web services technology, deeply studies the e-government and SOA theory, and discusses this based on the development status of e-government in a certain region. Then, the deep learning algorithm is used to construct the monitoring platform to monitor the government behavior in real time, and the deep learning algorithm is used to conduct in-depth mining to analyze the government's intention behavior.


Nowadays researchers are focused on processing the multi-media data for classifying the queries of end users by using search engines. The hybrid combination of a powerful classifier and deep feature extractor are used to develop a robust model, which is performed in a high dimensional space. In this research, a three different types of algorithms are combined to attain a stochastic belief space policy, where these algorithms include generative adversary modelling, maximum entropy Reinforcement Learning (RL) and belief space planning which leads to develop a multi-model classification algorithm. In the simulation framework, different adversarial behaviours are used to minimize the agent's action predictability, which has resulted the proposed method to attain robustness, while comparing with unmodelled adversarial strategies. The proposed reinforcement based Deep Learning (DL) algorithm can be used as multi-model classification purpose. The single neural network algorithm can perform the classification on text data and image data. The RL learns the appropriate belief space policy from the feature extracted information of the text and image data, the belief space policy is generated based on the maximum entropy computation


2021 ◽  
Author(s):  
Karine Bastos Leal ◽  
Luís Eduardo de Souza Robaina ◽  
André de Souza De Lima

Abstract An increase in the global mean sea is predicted during the 21st century as a consequence of global average temperature projections. In addition, changes in the strength of atmospheric cyclonic storms may alter the development of storm surges, exacerbating the risks to coastal communities. Based on the fact that the interest and range of papers are growing on this topic, this study aims to present the global scientific production status of studies that have correlated climate change and the impact of storm surges on the coastal zone leading to erosion and flooding (inundation) via a bibliometric analysis. We analyzed 429 papers published in journals between 1991 and February 2021 from the Scopus database. Through the VOSviewer and Bibliometrix R package, we describe the most relevant countries, affiliations, journals, authors, and keywords. Our results demonstrate that there has been an exponential growth in the research topic, and that authors from the United States and the United Kingdom are the most prolific. Among the 1454 authors found, 10 researchers published at least 5 papers on the topic and obtained at least 453 citations in the period. The most represented journals were the Journal of Coastal Research, Climatic Change, and Natural Hazards. We also found, and discuss, the lack of standardization in the choice of keywords, of which climate change, storm surge, and sea level rise are the most frequent. Finally, we have written a guide to facilitate the authors' bibliographic review.


Author(s):  
A.V. Goncharenko ◽  
T.O. Safonova

The article investigates the impact of Great Britain on the evolution of colonialism in the late ХІХ and early ХХ centuries. It is analyzed the sources and scientific literature on the policy of the United Kingdom in the colonial question in the late ХІХ – early ХХ century. The reasons, course and consequences of the intensification of British policy in the colonial problem are described. The process of formation and implementation of London’s initiatives in the colonial question during the period under study is studied. It is considered the position of Great Britain on the transformation of the colonial system in the late XIX – early XX centuries. The resettlement activity of the British and the peculiarities of their mentality, based on the idea of racial superiority and the new national messianism, led to the formation of developed resettlement colonies. The war for the independence of the North American colonies led to the formation of a new state on their territory, and the rest of the “white” colonies of Great Britain had at the turn of the XIX-XX centuries had to build a new policy of relations, taking into account the influence of the United States on them, and the general decline of economic and military-strategic influence of Britain in the world, and the militarization of other leading countries. As a result, a commonwealth is formed instead of an empire. With regard to other dependent territories, there is also a change in policy towards the liberalization of colonial rule and concessions to local elites. In the late ХІХ – early ХІХ centuries the newly industrialized powers (Germany, Italy, and Japan) sought to seize the colonies to reaffirm their new status in the world, the great colonial powers of the past (Spain, Portugal, and the Netherlands) sought to retain what remained to preserve their international prestige, and Russia sought to expand. The largest colonial empires, Great Britain and France, were interested in maintaining the status quo. In the colonial policy of the United Kingdom, it is possible to trace a certain line related to attempts to preserve the situation in their remote possessions and not to get involved in conflicts and costly measures where this can be avoided. In this sense, the British government showed some flexibility and foresight – the relative weakening of the military and economic power of the empire due to the emergence of new states, as well as the achievement of certain self-sufficiency, made it necessary to reconsider traditional foreign policy. Colonies are increasingly no longer seen as personal acquisitions of states, and policy toward these territories is increasingly seen as a common deal of the international community and even its moral duty. The key role here was to be played by Great Britain, which was one of the first to form the foundations of a “neocolonial” system that presupposes a solidarity policy of Western countries towards the rest of the world under the auspices of London. Colonial system in the late ХІХ – early ХІХ century underwent a major transformation, which was associated with a set of factors, the main of which were – the emergence of new industrial powers on the world stage, the internal evolution of the British Empire, changes in world trade, the emergence of new weapons, general growth of national and religious identity and related with this contradiction. The fact that the First World War did not solve many problems, such as Japanese expansionism or British marinism, and caused new ones, primarily such as the Bolshevik coup in Russia and the coming to power of the National Socialists in Germany, the implementation of the above trends stretched to later moments.


2020 ◽  
Vol 1 (1) ◽  
pp. 15-25
Author(s):  
Amod K. Pokhrel ◽  
Yadav P. Joshi ◽  
Sopnil Bhattarai

There is limited information on the epidemiology and the effects of mitigation measures on the spread of COVID-19 in Nepal. Using publicly available databases, we analyzed the epidemiological trend, the people's movement trends at different intervals across different categories of places and evaluated implications of social mobility on COVID-19. We also estimated the epidemic peak. As of June 9, 2020, Provinces 2 and 5 have most of the cases. People between 15 and 54 years are vulnerable to becoming infected, and more males than females are affected. The cases are growing exponentially. The growth rate of 0.13 and >1 reproduction numbers (R0) over time (median: 1.48; minimum: 0.58, and maximum: 3.71) confirms this trend. The case doubling time is five days. Google's community mobility data suggest that people strictly followed social distancing measures for one month after the lockdown. By around the 4th week of April, the individual's movement started rising, and social contacts increased. The number of cases peaked on May 12, with 83 confirmed cases in one day. The Susceptible-Exposed-Infectious-Removed (SEIR) model suggests that the epidemic will peak approximately on day 41 (July 21, 2020), and start to plateau after day 80. To contain the spread of the virus, people should maintain social distancing. The Government needs to continue active surveillance, more PCR-based testing, case detection, contact tracing, isolation, and quarantine. The Government should also provide financial support and safety-nets to the citizen to limit the impact of COVID-19.


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