scholarly journals Understanding the First and the Second Waves of the COVID-19 in Germany: Is our Social Behavior Enough to Protect us from the Pandemic?

2021 ◽  
Vol 18 (15) ◽  
Author(s):  
Muhamad KHAIRULBAHRI
Keyword(s):  
Young People ◽  
Computer Model ◽  
Health Workers ◽  
Public Spaces ◽  
Unknown Parameters ◽  
Behavioral Measures ◽  
Seir Model ◽  
Resource Needs ◽  
Second Wave ◽  
Death Cases

Like other European countries, Germany has experienced the 2nd wave of the COVID-19 amid obligations of social distancing and wearing of face masks in public spaces. Although Germany successfully contained the virus during the 1st wave, it has faced difficulties in controlling the COVID-19 during the 2nd wave. This study develops a computer model representing the COVID-19 flow in Germany by comparing the effects of the measures taken during the 1st and the 2nd waves. The computer model is based on the SEIR concept and the system dynamics (SD) approach in which some unknown parameters are estimated through the calibration process. Moreover, the SEIR computer model is developed by considering different cases in older and young people and the SEIR model successfully reproduces similar patterns of infected, recovered, and death cases in the 1st and the 2nd waves in Germany. The SEIR model also shows that the measures taken in the 1st wave have different efficacies than those in the 2nd wave, leading to higher infected cases during the 2nd wave. Since the SEIR model can successfully reproduce similar patterns, the SEIR model can be a basis for further studies in estimating other resource needs such as health workers, and bed capacities. HIGHLIGHTS The SEIR model estimates the efficacies of behavioral measures and lockdowns Behavioral measures are less effective than lockdowns Germany experienced higher infected cases in the first wave than in the second wave Relaxed lockdowns lead to higher infected cases in the second wave Lockdowns are the key to curb COVID-19 flow GRAPHICAL ABSTRACT

scholarly journals Modeling the flow of the COVID-19 in Germany: The efficacy of lockdowns and social behavior

2020 ◽  
Author(s):  
Muhamad Khairul Bahri
Keyword(s):  
Computer Simulation ◽  
Social Behavior ◽  
Young People ◽  
System Dynamics ◽  
Computer Model ◽  
Health Workers ◽  
Uncertain Parameters ◽  
Seir Model ◽  
The Given ◽  
Death Cases

AbstractThis study develops a computer simulation in understanding the flow of the COVID-19 in Germany between January 2020 and July 2020. This aims to analyze not only the flow of the COVID-19 but also the efficacy of taken measures during the given period. The computer model is based on the SEIR concept and it is based on the system dynamics approach in which some uncertain parameters are estimated through the calibration process. Moreover, the SEIR computer model is developed by considering different flows of COVID-19 cases in older and young people in Germany. This study successfully reproduces similar patterns of infected, recovered, and death cases. Moreover, as the SEIR model can successfully reproduce similar patterns, the SEIR model can be a basis to estimate other resources such as health workers, and bed capacities.

scholarly journals Modeling the COVID-19 transmission in Italy: The roles of asymptomatic cases, social distancing, and lockdowns in the first and the second waves

2021 ◽  
Author(s):  
Muhamad Khairul Bahri
Keyword(s):  
Behavioral Measures ◽  
Seir Model ◽  
Social Distancing ◽  
The World ◽  
Second Wave ◽  
Very High

AbstractThe SEIR model of COVID-19 is developed to investigate the roles of physical distancing, lockdowns and asymptomatic cases in Italy. In doing so, two types of policies including behavioral measures and lockdown measures are embedded in the model. Compared with existing models, the model successfully reproduces similar multiple observed outputs such as infected and recovered patients in Italy by July 2020. This study concludes that the first policy is important once the number of infected cases is relatively low. However, once the number of infected cases is very high so the society cannot identify infected and disinfected people, the second policy must be applied soon. It is thus this study suggests that relaxed lockdowns lead to the second wave of the COVID-19 around the world. It is hoped that the model can enhance our understanding on the roles of behavioral measures, lockdowns, and undocumented cases, so-called asymptomatic cases, on the COVID-19 flow.

scholarly journals Modeling the Effect of Asymptomatic Cases, Social Distancing, and Lockdowns in the First and Second waves of the COVID-19 Pandemic: A Case Study of Italy

2021 ◽  
Vol 3 (3) ◽  
pp. 265-273
Author(s):  
Muhamad Khairulbahri
Keyword(s):  
Full Text ◽  
Behavioral Measures ◽  
Seir Model ◽  
Social Distancing ◽  
The World ◽  
Second Wave

The SEIR model of COVID-19 is developed to investigate the roles of physical distancing, lockdowns, and asymptomatic cases in Italy. In doing so, two types of policies including behavioral measures and lockdown measures are embedded in the model. Compared with existing models, the model successfully reproduces similar multiple observed outputs such as infected and recovered patients in Italy by July 2020. This study concludes that the first policy is important once the number of infected cases is relatively low. However, once the number of infected cases is too high, so the society cannot identify infected and disinfected people, the second policy must be applied soon. It is thus this study suggests that relaxed lockdowns lead to the second wave of the COVID-19 around the world. It is hoped that the model can enhance our understanding of the roles of behavioral measures, lockdowns, and undocumented cases, so-called asymptomatic cases, on the COVID-19 flow. Doi: 10.28991/SciMedJ-2021-0303-8 Full Text: PDF

Machine Learning Approach for Confirmation of COVID-19 Cases: Positive, Negative, Death and Release (Preprint)

2020 ◽  
Author(s):  
Samir Bandyopadhyay Sr ◽  
SHAWNI DUTTA ◽  
SHAWNI DUTTA ◽  
SHAWNI DUTTA
Keyword(s):  
Machine Learning ◽  
Short Term Memory ◽  
Health Workers ◽  
Original Data ◽  
High Rate ◽  
Learning Approach ◽  
Good Decision ◽  
Number Of Patients ◽  
Machine Learning Approach ◽  
Death Cases

BACKGROUND In recent days, Covid-19 coronavirus has been an immense impact on social, economic fields in the world. The objective of this study determines if it is feasible to use machine learning method to evaluate how much prediction results are close to original data related to Confirmed-Negative-Released-Death cases of Covid-19. For this purpose, a verification method is proposed in this paper that uses the concept of Deep-learning Neural Network. In this framework, Long short-term memory (LSTM) and Gated Recurrent Unit (GRU) are also assimilated finally for training the dataset and the prediction results are tally with the results predicted by clinical doctors. The prediction results are validated against the original data based on some predefined metric. The experimental results showcase that the proposed approach is useful in generating suitable results based on the critical disease outbreak. It also helps doctors to recheck further verification of virus by the proposed method. The outbreak of Coronavirus has the nature of exponential growth and so it is difficult to control with limited clinical persons for handling a huge number of patients with in a reasonable time. So it is necessary to build an automated model, based on machine learning approach, for corrective measure after the decision of clinical doctors. It could be a promising supplementary confirmation method for frontline clinical doctors. The proposed method has a high prediction rate and works fast for probable accurate identification of the disease. The performance analysis shows that a high rate of accuracy is obtained by the proposed method. OBJECTIVE Validation of COVID-19 disease METHODS Machine Learning RESULTS 90% CONCLUSIONS The combined LSTM-GRU based RNN model provides a comparatively better results in terms of prediction of confirmed, released, negative, death cases on the data. This paper presented a novel method that could recheck occurred cases of COVID-19 automatically. The data driven RNN based model is capable of providing automated tool for confirming, estimating the current position of this pandemic, assessing the severity, and assisting government and health workers to act for good decision making policy. It could be a promising supplementary rechecking method for frontline clinical doctors. It is now essential for improving the accuracy of detection process. CLINICALTRIAL 2020-04-03 3:22:36 PM

scholarly journals Bayesian small-area modelling of COVID-19 cases and deaths in England and association with key risk factors: a combined space–time Susceptible-Exposed-Infected-Removed (SEIR) model

2020 ◽  
Author(s):  
Benn Sartorius ◽  
Andrew Lawson ◽  
Rachel L. Pullan
Keyword(s):  
Risk Factors ◽  
Small Area ◽  
Mortality Rates ◽  
Space Time ◽  
Spatiotemporal Variability ◽  
Population Mobility ◽  
Seir Model ◽  
Social Distancing ◽  
The Impact ◽  
Second Wave

Abstract Background: COVID-19 caseloads in England appear have passed through a first peak, with evidence of an emerging second wave. To ensure continued response to the epidemic is most effective, it is imperative to better understand both retrospectively and prospectively the geographical evolution of COVID-19 caseloads and deaths, identify localised areas in space-time at significantly higher risk, quantify the impact of changes in localised population mobility (or movement) on caseloads, identify localised risk factors for increased mortality and project the likely course of the epidemic at small-area resolution in coming weeks.Methods: We applied a Bayesian space–time SEIR model to assess the spatiotemporal variability of COVID-19 caseloads (transmission) and deaths at small-area scale in England (Middle Layer Super Output Area [MSOA], 6791 units) and by week (using observed data from week 5 to 34), including key determinants, the modelled transmission dynamics and spatial-temporal random effects. We also estimate the number of cases and deaths at small-area resolution with uncertainty projected forward in time by MSOA (up to week 51 of 2020), the impact mobility reductions (and subsequent easing) have had on COVID-19 caseloads and quantify the impact of key socio-demographic risk factors on COVID-19 related mortality risk by MSOA.Results: Reductions in population mobility due the course of the first lockdown had a significant impact on the reduction of COVID-19 caseloads across England, however local authorities have had a varied rate of reduction in population movement which our model suggest has substantially impacted the geographic heterogeneity in caseloads at small-area scale. The steady gain in population mobility, observed from late April, appears to have contributed to a slowdown in caseload reductions towards late June and subsequent steady increase signalling the start of the second wave. MSOA with higher proportions of elderly (70+ years of age) and elderly living in deprivation, both with very distinct geographic distributions, have a significantly elevated COVID-19 mortality rates.Conclusions: While non-pharmaceutical interventions (that is, reductions in population mobility and social distancing) had a profound impact on the trajectory of the first wave of the COVID-19 outbreak in England, increased population mobility appears to have contributed to the current increase signalling the start of the second wave. A number of contiguous small-areas appear to be at a significant elevated risk of high COVID-19 transmission, many of which are also at increased risk for higher mortality rates. A geographically staggered re-introduction of intensified social distancing measures is advised and limited cross MSOA movement if the magnitude and geographic extent of the second wave is to be reduced.

scholarly journals KAJIAN MENGENAI RUMAH KOPI SEBAGAI RUANG PUBLIK DI KERAMAIAN KOTA KAWASAN BLOK M

2020 ◽  
Vol 1 (2) ◽  
pp. 829
Author(s):  
Alfredo Wijaya Putera
Keyword(s):  
Public Space ◽  
Millennial Generation ◽  
American Culture ◽  
Public Spaces ◽  
Lifestyle Changes ◽  
Urban Life ◽  
Urban Spaces ◽  
Previous Generation ◽  
Definition Of ◽  
Second Wave

With the most dominant number, millennial generation is one generation which it has high income compared to the previous generation. This change has an impact on lifestyle, where one of  the  lifestyles  that  are  studied  and  understood  is  the  lifestyle   of   drinking   coffee. These lifestyle changes how community enjoying coffee, so coffee houses that exist especially in Jakarta try to adapt to this activity. Apart from that, the adaptation of coffee houses in Jakarta is also more oriented towards American culture, where its role is in the entry of coffee houses in Jakarta, especially in the era of the second wave. So the question is whether the changes in coffee houses in Jakarta are in accordance with the definition of public spaces in cities where they can contribute to providing life, especially in urban spaces. To find out more about this, type of coffee houses studied especially in Jakarta, and get results coffee houses in Jakarta as a public space specifically providing ‘life’ only in building and forget about his role as public space in urban. Considered this problem, studied about type of coffee house in the European region, which can solve about giving a urban life. From these results, type about coffee house in European tried to be rearranged and combined with type coffee houses in Jakarta, which can contribute a urban life in Jakarta. AbstrakDengan jumlah yang paling dominan saat ini, generasi milenial adalah salah satu generasi dimana mempunyai pendapatan yang tinggi dibandingkan dengan generasi sebelumnya. Perubahan ini berdampak dalam gaya hidup, dimana salah satu gaya hidup yang dikaji dan dibatasi adalah gaya hidup ngopi. Perubahan gaya hidup ini mempengaruhi perubahan aktifitas masyarakat dalam menikmati kopi, sehingga rumah kopi yang ada khususnya di Jakarta mencoba beradaptasi dengan aktifitas ini. Terlepas dari itu, adaptasi rumah kopi yang ada di Jakarta juga lebih berorientasi pada budaya Amerika, dimana perannya pada masuknya rumah kopi di Jakarta khususnya pada era the second wave. Sehingga yang menjadi pertanyaan adalah apakah perubahan rumah kopi yang ada di Jakarta sesuai dengan definisi ruang publik dalam kota dimana dapat berkontribusi dalam memberikan kehidupan, khususnya dalam ruang kota. Sehingga untuk mempelajari lebih lanjut mengenai permasalahan tersebut, maka disini dicoba di pelajari bagaimana tipe rumah kopi yang ada khususnya di Jakarta, dan didapatkan hasil bahwa rumah kopi yang ada di Jakarta dijadikan ruang publik yang lebih hidup bersifat ‘kedalam’ bangunan saja, menyampingkan sebagai fungsi ruang publik khususnya memberikan kehidupan dalam ruang kota. Sehingga dengan demikian dicoba di pelajari tipe rumah kopi khususnya yang ada di bagian daerah Eropa, dimana mempunyai ciri khusus dapat berkontribusi dalam memberikan kehidupan khususnya pada ruang kota yang di tempatinya. Dari hasil ini kemudian dicoba disusun ulang dan dikombinasikan dengan tipe rumah kopi yang ada di Jakarta, sehingga diharapkan tipe rumah kopi yang ada di Jakarta dapat berperan memberikan kehidupan khususnya pada ruang kota.

scholarly journals Policing Visible Sexual/Gender Diversity as a Program of Governance

2012 ◽  
Vol 1 (1) ◽  
pp. 14-26 ◽  
Author(s):  
Angela Dwyer
Keyword(s):  
Young People ◽  
Gender Diversity ◽  
Public Spaces ◽  
Gender And Sexuality ◽  
Interview Data ◽  
Same Sex ◽  
The Public ◽  
Sexuality And Gender ◽  
And Gender ◽  
Police Interactions

Using interview data on LGBT young people’s policing experiences, I argue policing and security works as a program of government (Dean 1999; Foucault 1991; Rose 1999) that constrains the visibilities of diverse sexuality and gender in public spaces. While young people narrated police actions as discriminatory, the interactions were complex and multi-faceted with police and security working to subtly constrain the public visibilities of ‘queerness’. Same sex affection, for instance, was visibly yet unverifiably (Mason 2002) regulated by police as a method of governing the boundaries of proper gender and sexuality in public. The paper concludes by noting how the visibility of police interactions with LGBT young people demonstrates to the public that public spaces are, and should remain, heterosexual spaces.

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