scholarly journals Framework for Prioritizing Contact Tracing and Mass Testing of COVID-19 Using Graph Theory

2021 ◽  
pp. 50-66
Author(s):  
Obed Appiah ◽  
Dominic Otoo ◽  
Christopher Bombie Ninfaakang
Keyword(s):  
Graph Theory ◽  
Simulated Data ◽  
Healthcare Systems ◽  
Contact Tracing ◽  
The Novel ◽  
Interaction Data ◽  
Treatment Results ◽  
Inaccurate Information ◽  
Selection For ◽  
Simple Interaction

Contact tracing has become one of the most useful tools for fighting the novel Corona Virus (COVID-19) pandemic worldwide. The underlining philosophy of contact tracing is determining people who have been in contact with infected persons and thus isolate them from becoming agents of onward transmission of the virus.  Slow tracing of contacts and inconsistent or inaccurate information provided by patients usually leads to the spread of the virus along a trajectory at the healthcare systems' blindside. This has led to the proposal of app-based contact tracing solutions.  This paper proposes an SQL-based framework that transforms simple interaction data entries into interaction graphs and applies graph theory to prioritize the contact tracing process. The framework returns nodes or individual IDs together with values called Risk_Points to enable individuals' selection for isolation and treatment. Results on simulated data show that the proposed framework can help slow the virus's rate of transmission.

scholarly journals A Mathematical Model of Contact Tracing during the 2014–2016 West African Ebola Outbreak

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 608
Author(s):  
Danielle Burton ◽  
Suzanne Lenhart ◽  
Christina J. Edholm ◽  
Benjamin Levy ◽  
Michael L. Washington ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Disease Management ◽  
Ebola Virus ◽  
Virus Disease ◽  
Infected Individual ◽  
Vital Role ◽  
West African ◽  
Contact Tracing ◽  
The Novel ◽  
Using Data

The 2014–2016 West African outbreak of Ebola Virus Disease (EVD) was the largest and most deadly to date. Contact tracing, following up those who may have been infected through contact with an infected individual to prevent secondary spread, plays a vital role in controlling such outbreaks. Our aim in this work was to mechanistically represent the contact tracing process to illustrate potential areas of improvement in managing contact tracing efforts. We also explored the role contact tracing played in eventually ending the outbreak. We present a system of ordinary differential equations to model contact tracing in Sierra Leonne during the outbreak. Using data on cumulative cases and deaths, we estimate most of the parameters in our model. We include the novel features of counting the total number of people being traced and tying this directly to the number of tracers doing this work. Our work highlights the importance of incorporating changing behavior into one’s model as needed when indicated by the data and reported trends. Our results show that a larger contact tracing program would have reduced the death toll of the outbreak. Counting the total number of people being traced and including changes in behavior in our model led to better understanding of disease management.

scholarly journals COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society

2021 ◽  
pp. 0272989X2110030
Author(s):  
Serin Lee ◽  
Zelda B. Zabinsky ◽  
Judith N. Wasserheit ◽  
Stephen M. Kofsky ◽  
Shan Liu
Keyword(s):  
Large City ◽  
Face Mask ◽  
School Closure ◽  
Contact Tracing ◽  
The Novel ◽  
Agent Based ◽  
Social Distancing ◽  
Variable Compliance ◽  
Novel Coronavirus ◽  
Nonpharmaceutical Interventions

As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021.

scholarly journals Digital Tracing during the COVID-19 Pandemic: User Appraisal, Emotion, and Continuance Intention

2021 ◽  
Vol 13 (2) ◽  
pp. 608
Author(s):  
Ayoung Suh ◽  
Mengjun Li
Keyword(s):  
Mobile Apps ◽  
Contact Tracing ◽  
The Novel ◽  
Personal Privacy ◽  
Continuance Intention ◽  
Infectious Disease Outbreak ◽  
Using Data ◽  
Novel Coronavirus ◽  
Technological Affordances ◽  
Method Approach

This study explores how people appraise the use of contact tracing apps during the novel coronavirus (COVID-19) pandemic in South Korea. Despite increasing attention paid to digital tracing for health disasters, few studies have empirically examined user appraisal, emotion, and their continuance intention to use contact tracing apps for disaster management during an infectious disease outbreak. A mixed-method approach combining qualitative and quantitative inquiries was employed. In the qualitative study, by conducting interviews with 25 people who have used mobile apps for contact tracing, the way users appraise contact tracing apps for COVID-19 was explored. In the quantitative study, using data collected from 506 users of the apps, the interplay among cognitive appraisal (threats and opportunities) and its association with user emotion, and continuance intention was examined. The findings indicate that once users experience loss emotions, such as anger, frustration, and disgust, they are not willing to continue using the apps. App designers should consider providing technological affordances that enable users to have a sense of control over the technology so that they do not experience loss emotions. Public policymakers should also consider developing measures that can balance public health and personal privacy.

The active grandparent hypothesis: Physical activity and the evolution of extended human healthspans and lifespans

2021 ◽  
Vol 118 (50) ◽  
pp. e2107621118
Author(s):  
Daniel E. Lieberman ◽  
Timothy M. Kistner ◽  
Daniel Richard ◽  
I-Min Lee ◽  
Aaron L. Baggish
Keyword(s):  
Physical Activity ◽  
Physical Inactivity ◽  
Disease Risk ◽  
Energy Allocation ◽  
Noncommunicable Diseases ◽  
The Novel ◽  
Physically Active ◽  
Proximate Mechanisms ◽  
Aging Populations ◽  
Selection For

The proximate mechanisms by which physical activity (PA) slows senescence and decreases morbidity and mortality have been extensively documented. However, we lack an ultimate, evolutionary explanation for why lifelong PA, particularly during middle and older age, promotes health. As the growing worldwide epidemic of physical inactivity accelerates the prevalence of noncommunicable diseases among aging populations, integrating evolutionary and biomedical perspectives can foster new insights into how and why lifelong PA helps preserve health and extend lifespans. Building on previous life-history research, we assess the evidence that humans were selected not just to live several decades after they cease reproducing but also to be moderately physically active during those postreproductive years. We next review the longstanding hypothesis that PA promotes health by allocating energy away from potentially harmful overinvestments in fat storage and reproductive tissues and propose the novel hypothesis that PA also stimulates energy allocation toward repair and maintenance processes. We hypothesize that selection in humans for lifelong PA, including during postreproductive years to provision offspring, promoted selection for both energy allocation pathways which synergistically slow senescence and reduce vulnerability to many forms of chronic diseases. As a result, extended human healthspans and lifespans are both a cause and an effect of habitual PA, helping explain why lack of lifelong PA in humans can increase disease risk and reduce longevity.

Contact Tracing Applications Against COVID-19: A Systematic Review (Preprint)

2021 ◽  
Author(s):  
Ahmad Nabeel ◽  
Salman AlSabah ◽  
Eliana Al Haddad ◽  
Hutan Ashrafian
Keyword(s):  
Systematic Review ◽  
Critical Mass ◽  
Population Level ◽  
Ease Of Use ◽  
Contact Tracing ◽  
The Novel ◽  
Scientific Databases ◽  
Manual Methods ◽  
Novel Coronavirus ◽  
Transmission Of Disease

BACKGROUND The novel coronavirus 2019 (COVID-19) pandemic has triggered public anxiety around the world. So far, the evidence suggests that prevention on a public scale is the most effective health measure for thwarting the progress of COVID-19. Another critical aspect of preventing COVID-19 is contact tracing. OBJECTIVE We aimed to investigate the effectiveness of contact tracing applications currently available in the context of the COVID-19 pandemic. METHODS We undertook a systematic review and narrative synthesis of all literature relating to contact tracing applications in the context of COVID-19. We searched 3 major scientific databases. Only articles that were published in English and were available as full-text articles were selected for review. Data were extracted and narrative syntheses conducted. RESULTS Five studies relating to COVID-19 were included in the review. Our results suggest that digitalized contact tracing methods can be beneficial for impeding the progress of COVID-19. Three key themes were generated from this systematic review. First, the critical mass of application adoption must be attained at the population level before the sensitivity and positive predictive value of the solution can be increased. Second, usability factors such as access, ease of use and the elimination of barriers are essential in driving this uptake. Third, privacy must be ensured where possible as it is the single most significant barrier against achieving critical mass. CONCLUSIONS The COVID-19 pandemic has claimed more than 2 million lives globally, with over 100 million confirmed cases. Contact tracing can rapidly identify potentially infected individuals before the emergence of severe or critical symptoms, and it can also prevent the subsequent transmission of disease from secondary cases when implemented efficiently. Contact tracing methods have proved to be beneficial for impeding the progress of COVID-19 as compared to older, more labor intensive manual methods.

Face masks are an essential tool to mitigate the ongoing SARS-CoV-2 pandemic: a call to action

2020 ◽  
Vol 3 (3) ◽  
pp. 157-159
Author(s):  
P. Dehgani-Mobaraki ◽  
A. Kamber Zaidi ◽  
J.M. Levy ◽  
Keyword(s):  
Upper Airway ◽  
World Health ◽  
Contact Tracing ◽  
The Novel ◽  
Call To Action ◽  
Public Health Emergencies ◽  
Current Spread ◽  
The World ◽  
Health And Disease ◽  
Novel Coronavirus

Over the past several months, an increasing volume of infor- mation has expanded awareness regarding the transmission of SARS-CoV-2, the novel coronavirus associated with COVID-19. Following the pandemic declaration by the World Health Orga- nization (WHO), global authorities immediately took measures to reduce the transmission and subsequent morbidity associa- ted with this highly contagious disease. However, despite initial success in “flattening the curve” of viral transmission, many areas of the world are currently experiencing an increase in com- munity transmission, threatening to replicate the early public health emergencies experienced by Italy (1,2). In addition, the possibility of contact tracing through geosocial applications and public service platforms have been met with variable interest (3). Given current spread and the upcoming influenza season, it is essential that we use our voices as experts in upper airway health and disease to educate and encourage all communities to adopt appropriate protective measures, including the routine use of facemasks.

Dose Selection for Optimal Treatment Results and Avoidance of Complications

2008 ◽  
pp. 11-19
Author(s):  
Hisato Nagano ◽  
Satoshi Nakayama ◽  
Takashi Shuto ◽  
Hiroyuki Asada ◽  
Shigeo Inomori
Keyword(s):  
Optimal Treatment ◽  
Treatment Results ◽  
Dose Selection ◽  
Selection For

THE POLITICS OF FOOD DISTRIBUTION DURING THE COVID-19 LOCK DOWN IN UGANDA.

2020 ◽  
Vol 8 (7) ◽  
pp. 221-234
Author(s):  
Madinah Nabukeera
Keyword(s):  
Task Force ◽  
Food Distribution ◽  
Contact Tracing ◽  
Local Elections ◽  
The Novel ◽  
Food Items ◽  
Attempted Murder ◽  
The World ◽  
The Government ◽  
At Home

In face of the Novel Covid-19 pandemic that has swept the world, Ugandan President Yoweri Museveni issued clear rules; stay at home unless it’s an emergency, wash your hands, sanitize, report any related cases for contact tracing and testing. In his directive all passenger services were stopped including private vehicles and imposed a curfew 7 pm until 6:30 a.m., which made stay at home orders mandatory. Majority of Ugandan urban dwellers are hand-to -mouth and live off their capability to move to town centers daily a small interruption in their routine means many went hungry. The government of Uganda broadcasted measures to distribute relief food items to troubled and vulnerable population mainly in the towns since those in the country sides are able to grow food and provide for their families. This article articulates the politics in the food in Wakiso and Kampala districts in Uganda why there was bias. The study used the selected all documents related to food distribution using content analysis and results indicated that anyone found distributing food outside the national covid-19 task force will be charged with attempted murder hence stopped politicians from strategizing ahead of 2021 parliamentary, presidential and local elections which implied that Covid-19 disrupted over 134 districts in the country in line with the preparation of elections and left majority hungry.

CLUSTERING-BASED APPROACH FOR PREDICTING MOTIF PAIRS FROM PROTEIN INTERACTION DATA

2009 ◽  
Vol 07 (04) ◽  
pp. 701-716 ◽  
Author(s):  
HENRY CHI-MING LEUNG ◽  
MAN-HUNG SIU ◽  
SIU-MING YIU ◽  
FRANCIS YUK-LUN CHIN ◽  
KEN WING-KIN SUNG
Keyword(s):  
Lower Bound ◽  
Protein Interaction ◽  
Scoring Function ◽  
Simulated Data ◽  
Protein Sequences ◽  
Protein Interaction Data ◽  
P Value ◽  
Interaction Data ◽  
Motif Pair ◽  
Data Set

Predicting motif pairs from a set of protein sequences based on the protein–protein interaction data is an important, but difficult computational problem. Tan et al. proposed a solution to this problem. However, the scoring function (using χ2 testing) used in their approach is not adequate and their approach is also not scalable. It may take days to process a set of 5000 protein sequences with about 20,000 interactions. Later, Leung et al. proposed an improved scoring function and faster algorithms for solving the same problem. But, the model used in Leung et al. is complicated. The exact value of the scoring function is not easy to compute and an estimated value is used in practice. In this paper, we derive a better model to capture the significance of a given motif pair based on a clustering notion. We develop a fast heuristic algorithm to solve the problem. The algorithm is able to locate the correct motif pair in the yeast data set in about 45 minutes for 5000 protein sequences and 20,000 interactions. Moreover, we derive a lower bound result for the p-value of a motif pair in order for it to be distinguishable from random motif pairs. The lower bound result has been verified using simulated data sets. Availability:

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