scholarly journals A TRANSPARENT, OPEN-SOURCE SIRD MODEL FOR COVID19 DEATH PROJECTIONS IN INDIA

2020 ◽  
Author(s):  
Ananye Agarwal ◽  
Utkarsh Tyagi
Keyword(s):  
Open Source ◽  
First Principles ◽  
Policy Decisions ◽  
Indian States ◽  
Social Distancing ◽  
Death Toll ◽  
Mobility Data ◽  
Novel Method

AbstractAs India emerges from the lockdown with ever higher COVID19 case counts and a mounting death toll, reliable projections of case numbers and deaths counts are critical in informing policy decisions. We examine various existing models and their shortcomings. Given the amount of uncertainty surrounding the disease we choose a simple SIRD model with minimal assumptions enabling us to make robust predictions. We employ publicly available mobility data from Google to estimate social distancing covariates which influence how fast the disease spreads. We further present a novel method for estimating the uncertainty in our predictions based on first principles. To demonstrate, we fit our model to three regions (Spain, Italy, NYC) where the peak has passed and obtain predictions for the Indian states of Delhi and Maharashtra where the peak is desperately awaited.

How Bad Is It? Elite Influence and the Perceived Seriousness of the Coronavirus Pandemic

2020 ◽  
pp. 1-14
Author(s):  
Philip Moniz
Keyword(s):  
The Political ◽  
Political Elites ◽  
Policy Decisions ◽  
Social Distancing ◽  
Global Impact ◽  
Death Toll ◽  
Perceived Seriousness ◽  
And Behaviors ◽  
Elite Influence

Abstract In spite of its immense global impact, Republicans and Democrats disagree on how serious a problem the coronavirus pandemic is. One likely reason is the political elites to whom partisans listen. As a means of shoring up support, President Trump has largely downplayed and but sometimes hyped the severity of the virus’s toll on American lives. Do these messages influence the perceived seriousness of the virus, how the president is evaluated as well as support for and compliance with social distancing guidelines? Results suggest that Republican identifiers had already crystallized their views on the virus’s seriousness, the president’s performance, and social distancing policies and behaviors. Unexpectedly, information critical of President Trump’s policy decisions produced a backlash causing people to show less concern about the virus’s death toll and rate the president’s performance even more highly.

scholarly journals Reduction in mobility and COVID-19 transmission

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Pierre Nouvellet ◽  
Sangeeta Bhatia ◽  
Anne Cori ◽  
Kylie E. C. Ainslie ◽  
Marc Baguelin ◽  
...  
Keyword(s):  
Predictive Ability ◽  
Control Measures ◽  
Social Distancing ◽  
Beneficial Effects ◽  
Mobility Data ◽  
Strict Control ◽  
Before And After ◽  
Proxy Measure ◽  
Lower Transmission ◽  
The Relationship

AbstractIn response to the COVID-19 pandemic, countries have sought to control SARS-CoV-2 transmission by restricting population movement through social distancing interventions, thus reducing the number of contacts. Mobility data represent an important proxy measure of social distancing, and here, we characterise the relationship between transmission and mobility for 52 countries around the world. Transmission significantly decreased with the initial reduction in mobility in 73% of the countries analysed, but we found evidence of decoupling of transmission and mobility following the relaxation of strict control measures for 80% of countries. For the majority of countries, mobility explained a substantial proportion of the variation in transmissibility (median adjusted R-squared: 48%, interquartile range - IQR - across countries [27–77%]). Where a change in the relationship occurred, predictive ability decreased after the relaxation; from a median adjusted R-squared of 74% (IQR across countries [49–91%]) pre-relaxation, to a median adjusted R-squared of 30% (IQR across countries [12–48%]) post-relaxation. In countries with a clear relationship between mobility and transmission both before and after strict control measures were relaxed, mobility was associated with lower transmission rates after control measures were relaxed indicating that the beneficial effects of ongoing social distancing behaviours were substantial.

scholarly journals Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Corentin Cot ◽  
Giacomo Cacciapaglia ◽  
Francesco Sannino
Keyword(s):  
Infection Rate ◽  
The United States ◽  
Strong Decrease ◽  
Social Distancing ◽  
Mobility Data ◽  
Actual Measure ◽  
The Us ◽  
The Impact ◽  
Political Decisions ◽  
Mobility Reduction

AbstractWe employ the Google and Apple mobility data to identify, quantify and classify different degrees of social distancing and characterise their imprint on the first wave of the COVID-19 pandemic in Europe and in the United States. We identify the period of enacted social distancing via Google and Apple data, independently from the political decisions. Our analysis allows us to classify different shades of social distancing measures for the first wave of the pandemic. We observe a strong decrease in the infection rate occurring two to five weeks after the onset of mobility reduction. A universal time scale emerges, after which social distancing shows its impact. We further provide an actual measure of the impact of social distancing for each region, showing that the effect amounts to a reduction by 20–40% in the infection rate in Europe and 30–70% in the US.

Social Distancing Using AI and Deep Learning

2021 ◽  
Vol 9 (VII) ◽  
pp. 1816-1822
Author(s):  
Mr. Kiran Mudaraddi
Keyword(s):  
Deep Learning ◽  
Object Detection ◽  
Open Source ◽  
Suggested Method ◽  
Video Frame ◽  
Social Distancing ◽  
The Social ◽  
The Impact

The paper presents a deep learning-based methodology for detecting social distancing in order to assess the distance between people in order to mitigate the impact of the coronavirus pandemic. The input was a video frame from the camera, and the open-source object detection was pre-trained. The outcome demonstrates that the suggested method is capable of determining the social distancing measures between many participants in a video.

Disparity and Dynamics of Social Distancing Behaviors in Japan: An Investigation of mobile phone mobility data (Preprint)

2021 ◽  
Author(s):  
Zeyu Lyu ◽  
Hiroki Takikawa
Keyword(s):  
Large Scale ◽  
Age Groups ◽  
Mitigation Strategies ◽  
Social Distancing ◽  
Demographic Groups ◽  
Fine Grained ◽  
Mobility Data ◽  
The Social ◽  
The Government ◽  
Over Time

BACKGROUND The availability of large-scale and fine-grained aggregated mobility data has allowed researchers to observe the dynamic of social distancing behaviors at high spatial and temporal resolutions. Despite the increasing attentions paid to this research agenda, limited studies have focused on the demographic factors related to mobility and the dynamics of social distancing behaviors has not been fully investigated. OBJECTIVE This study aims to assist in the design and implementation of public health policies by exploring the social distancing behaviors among various demographic groups over time. METHODS We combined several data sources, including mobile tracking data and geographical statistics, to estimate visiting population of entertainment venues across demographic groups, which can be considered as the proxy of social distancing behaviors. Then, we employed time series analyze methods to investigate how voluntary and policy-induced social distancing behaviors shift over time across demographic groups. RESULTS Our findings demonstrate distinct patterns of social distancing behaviors and their dynamics across age groups. The population in the entertainment venues comprised mainly of individuals aged 20–40 years, while according to the dynamics of the mobility index and the policy-induced behavior, among the age groups, the extent of reduction of the frequency of visiting entertainment venues during the pandemic was generally the highest among younger individuals. Also, our results indicate the importance of implementing the social distancing policy promptly to limit the spread of the COVID-19 infection. However, it should be noticed that although the policy intervention during the second wave in Japan appeared to increase the awareness of the severity of the pandemic and concerns regarding COVID-19, its direct impact has been largely decreased could only last for a short time. CONCLUSIONS At the time we wrote this paper, in Japan, the number of daily confirmed cases was continuously increasing. Thus, this study provides a timely reference for decision makers about the current situation of policy-induced compliance behaviors. On the one hand, age-dependent disparity requires target mitigation strategies to increase the intention of elderly individuals to adopt mobility restriction behaviors. On the other hand, considering the decreasing impact of self-restriction recommendations, the government should employ policy interventions that limit the resurgence of cases, especially by imposing stronger, stricter social distancing interventions, as they are necessary to promote social distancing behaviors and mitigate the transmission of COVID-19. CLINICALTRIAL None

scholarly journals Do-it-yourself networks: a novel method of generating weighted networks

2017 ◽  
Vol 4 (11) ◽  
pp. 171227 ◽  
Author(s):  
D. W. Shanafelt ◽  
K. R. Salau ◽  
J. A. Baggio
Keyword(s):  
Social Sciences ◽  
Open Source ◽  
Network Theory ◽  
Source Code ◽  
Ecological Systems ◽  
Species Dispersal ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Novel Method ◽  
Do It Yourself

Network theory is finding applications in the life and social sciences for ecology, epidemiology, finance and social–ecological systems. While there are methods to generate specific types of networks, the broad literature is focused on generating unweighted networks. In this paper, we present a framework for generating weighted networks that satisfy user-defined criteria. Each criterion hierarchically defines a feature of the network and, in doing so, complements existing algorithms in the literature. We use a general example of ecological species dispersal to illustrate the method and provide open-source code for academic purposes.

scholarly journals Will You Come Back to Contribute? Investigating the Inactivity of OSS Core Developers in GitHub

2021 ◽  
Author(s):  
Fabio Calefato ◽  
Marco Aurelio Gerosa ◽  
Giuseppe Iaffaldano ◽  
Filippo Lanubile ◽  
Igor Fabio Steinmacher
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
State Transition ◽  
Active State ◽  
State Model ◽  
Novel Method ◽  
To Come ◽  
One Year ◽  
The Individual ◽  
To Receive

Abstract Several Open-Source Software (OSS) projects depend on the continuity of their development communities to remain sustainable. Understanding how developers become inactive or why they take breaks can help communities prevent abandonment and incentivize developers to come back. In this paper, we propose a novel method to identify developers’ inactive periods by analyzing the individual rhythm of contributions to the projects. Using this method, we quantitatively analyze the inactivity of core developers in 18 OSS organizations hosted on GitHub. We also survey core developers to receive their feedback about the identified breaks and transitions. Our results show that our method was effective for identifying developers’ breaks. About 94% of the surveyed core developers agreed with our state model of inactivity; 71% and 79% of them acknowledged their breaks and state transition, respectively. We also show that all core developers take breaks (at least once) and about a half of them (~ 45%) have completely disengaged from a project for at least one year. We also analyzed the probability of transitions to/from inactivity and found that developers who pause their activity have a ~ 35 to ~ 55% chance to return to an active state; yet, if the break lasts for a year or longer, then the probability of resuming activities drops to ~ 21–26%, with a ~ 54% chance of complete disengagement. These results may support the creation of policies and mechanisms to make OSS community managers aware of breaks and potential project abandonment.

scholarly journals COVID surveillance robot: Monitoring social distancing constraints in indoor scenarios

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0259713
Author(s):  
Adarsh Jagan Sathyamoorthy ◽  
Utsav Patel ◽  
Moumita Paul ◽  
Yash Savle ◽  
Dinesh Manocha
Keyword(s):  
Mobile Robot ◽  
Closed Circuit ◽  
Healthcare Personnel ◽  
Depth Camera ◽  
Autonomous Mobile Robot ◽  
Thermal Camera ◽  
Social Distancing ◽  
Novel Method ◽  
Indoor Scenarios ◽  
Cctv Camera

Observing social/physical distancing norms between humans has become an indispensable precaution to slow down the transmission of COVID-19. We present a novel method to automatically detect pairs of humans in a crowded scenario who are not maintaining social distancing, i.e. about 2 meters of space between them using an autonomous mobile robot and existing CCTV (Closed-Circuit TeleVision) cameras. The robot is equipped with commodity sensors, namely an RGB-D (Red Green Blue—Depth) camera and a 2-D lidar to detect social distancing breaches within their sensing range and navigate towards the location of the breach. Moreover, it discreetly alerts the relevant people to move apart by using a mounted display. In addition, we also equip the robot with a thermal camera that transmits thermal images to security/healthcare personnel who monitors COVID symptoms such as a fever. In indoor scenarios, we integrate the mobile robot setup with a static wall-mounted CCTV camera to further improve the number of social distancing breaches detected, accurately pursuing walking groups of people etc. We highlight the performance benefits of our robot + CCTV approach in different static and dynamic indoor scenarios.

scholarly journals Epidemiological trend of COVID-19 in Nepal and the importance of social distancing to contain the virus

2020 ◽  
Vol 1 (1) ◽  
pp. 15-25
Author(s):  
Amod K. Pokhrel ◽  
Yadav P. Joshi ◽  
Sopnil Bhattarai
Keyword(s):  
Mitigation Measures ◽  
Contact Tracing ◽  
Limited Information ◽  
Social Distancing ◽  
Mobility Data ◽  
Epidemiological Trend ◽  
Reproduction Numbers ◽  
The Government ◽  
Testing Case ◽  
The Impact

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.

Software and seeds: Open source methods

First Monday ◽  
2005 ◽  
Author(s):  
Margaret Kipp
Keyword(s):  
Intellectual Property ◽  
Open Source ◽  
Policy Decisions ◽  
Public And Private ◽  
Private Interests

Open source methodologies used in software are interrogated and then compared to the methods used in farmers’ rights groups. The use of open source methods in other contexts illustrates increasing interest in grassroots democratic movements participating in the continuing process of balance between public and private interests. These efforts provide a possible alternate framework for policy decisions concerning intellectual property.

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