scholarly journals A network-based group testing strategy for colleges

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Alex Zhao ◽  
Kavin Kumaravel ◽  
Emanuele Massaro ◽  
Marta Gonzalez
Keyword(s):  
Group Testing ◽  
Local Information ◽  
Data Driven ◽  
Disease Spread ◽  
Transmission Network ◽  
Testing Strategy ◽  
Vital Importance ◽  
Testing Method ◽  
College Towns ◽  
Testing Strategies

AbstractGroup testing has recently become a matter of vital importance for efficiently and rapidly identifying the spread of Covid-19. In particular, we focus on college towns due to their density, observability, and significance for school reopenings. We propose a novel group testing strategy which requires only local information about the underlying transmission network. By using cellphone data from over 190,000 agents, we construct a mobility network and run extensive data-driven simulations to evaluate the efficacy of four different testing strategies. Our results demonstrate that our group testing method is more effective than three other baseline strategies for reducing disease spread with fewer tests.

scholarly journals Evaluation of Group Testing for SARS-CoV-2 RNA

2020 ◽  
Author(s):  
Nasa Sinnott-Armstrong ◽  
Daniel L. Klein ◽  
Brendan Hickey
Keyword(s):  
Rna Extraction ◽  
Group Testing ◽  
Disease Status ◽  
Behavioral Changes ◽  
Limiting Factor ◽  
Testing Strategy ◽  
Pooled Testing ◽  
Testing Strategies ◽  
Test Kit ◽  
Testing Protocols

AbstractDuring the current COVID-19 pandemic, testing kit and RNA extraction kit availability has become a major limiting factor in the ability to determine patient disease status and accurately quantify prevalence. Current testing strategies rely on individual tests of cases matching restrictive diagnostic criteria to detect SARS-CoV-2 RNA, limiting testing of asymptomatic and mild cases. Testing these individuals is one effective way to understand and reduce the spread of COVID-19.Here, we develop a pooled testing strategy to identify these low-risk individuals. Drawing on the well-studied group testing literature, modeling suggests practical changes to testing protocols which can reduce test costs and stretch a limited test kit supply. When most tests are negative, pooling reduces the total number of tests up to four-fold at 2% prevalence and eight-fold at 0.5% prevalence. At current SARS-CoV-2 prevalence, randomized group testing optimized per country could double the number of tested individuals from 1.85M to 3.7M using only 671k more tests.This strategy is well-suited to supplement testing for asymptomatic and mild cases who would otherwise go untested, and enable them to adopt behavioral changes to slow the spread of COVID-19.

scholarly journals Pooled testing with replication as a mass testing strategy for the COVID-19 pandemics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Julius Žilinskas ◽  
Algirdas Lančinskas ◽  
Mario R. Guarracino
Keyword(s):  
Real Time ◽  
Real Time Pcr ◽  
Group Testing ◽  
Testing Strategy ◽  
Testing Technique ◽  
Testing Procedures ◽  
Pooled Testing ◽  
Replication Scheme ◽  
Speed Up ◽  
Multiple Patients

AbstractDuring the COVID-19 pandemic it is essential to test as many people as possible, in order to detect early outbreaks of the infection. Present testing solutions are based on the extraction of RNA from patients using oropharyngeal and nasopharyngeal swabs, and then testing with real-time PCR for the presence of specific RNA filaments identifying the virus. This approach is limited by the availability of reactants, trained technicians and laboratories. One of the ways to speed up the testing procedures is a group testing, where the swabs of multiple patients are grouped together and tested. In this paper we propose to use the group testing technique in conjunction with an advanced replication scheme in which each patient is allocated in two or more groups to reduce the total numbers of tests and to allow testing of even larger numbers of people. Under mild assumptions, a 13 ×  average reduction of tests can be achieved compared to individual testing without delay in time.

scholarly journals Data-driven Tracing Method of Overload of Transmission Network Equipment

2020 ◽  
Vol 546 ◽  
pp. 052001
Author(s):  
Meng Li ◽  
Wei Wu ◽  
Yi Lin ◽  
Tongyu Yan ◽  
Pingfa Huang ◽  
...  
Keyword(s):  
Data Driven ◽  
Transmission Network ◽  
Network Equipment ◽  
Tracing Method

scholarly journals False Negative Mitigation in Group Testing for COVID-19 Screening

2021 ◽  
Vol 8 ◽  
Author(s):  
Amir Reza Alizad Rahvar ◽  
Safar Vafadar ◽  
Mehdi Totonchi ◽  
Mehdi Sadeghi
Keyword(s):  
Viral Load ◽  
False Negative ◽  
Group Testing ◽  
False Negative Rate ◽  
Screening Strategy ◽  
Web Interface ◽  
Rt Pcr ◽  
Promising Candidate ◽  
Testing Method ◽  
High False Negative Rate

After lifting the COVID-19 lockdown restrictions and opening businesses, screening is essential to prevent the spread of the virus. Group testing could be a promising candidate for screening to save time and resources. However, due to the high false-negative rate (FNR) of the RT-PCR diagnostic test, we should be cautious about using group testing because a group's false-negative result identifies all the individuals in a group as uninfected. Repeating the test is the best solution to reduce the FNR, and repeats should be integrated with the group-testing method to increase the sensitivity of the test. The simplest way is to replicate the test twice for each group (the 2Rgt method). In this paper, we present a new method for group testing (the groupMix method), which integrates two repeats in the test. Then we introduce the 2-stage sequential version of both the groupMix and the 2Rgt methods. We compare these methods analytically regarding the sensitivity and the average number of tests. The tradeoff between the sensitivity and the average number of tests should be considered when choosing the best method for the screening strategy. We applied the groupMix method to screening 263 people and identified 2 infected individuals by performing 98 tests. This method achieved a 63% saving in the number of tests compared to individual testing. Our experimental results show that in COVID-19 screening, the viral load can be low, and the group size should not be more than 6; otherwise, the FNR increases significantly. A web interface of the groupMix method is publicly available for laboratories to implement this method.

scholarly journals Estimating infection-related human mobility networks based on time series data of COVID-19 infection in Japan

2021 ◽  
Author(s):  
Tetsuya Yamada ◽  
Shoi Shi
Keyword(s):  
Time Series ◽  
Infectious Diseases ◽  
Time Series Data ◽  
Human Mobility ◽  
Emerging Infectious Diseases ◽  
Human Movement ◽  
Data Driven ◽  
Disease Spread ◽  
Series Data ◽  
Data Infrastructure

Comprehensive and evidence-based countermeasures against emerging infectious diseases have become increasingly important in recent years. COVID-19 and many other infectious diseases are spread by human movement and contact, but complex transportation networks in 21 century make it difficult to predict disease spread in rapidly changing situations. It is especially challenging to estimate the network of infection transmission in the countries that the traffic and human movement data infrastructure is not yet developed. In this study, we devised a method to estimate the network of transmission of COVID-19 from the time series data of its infection and applied it to determine its spread across areas in Japan. We incorporated the effects of soft lockdowns, such as the declaration of a state of emergency, and changes in the infection network due to government-sponsored travel promotion, and predicted the spread of infection using the Tokyo Olympics as a model. The models used in this study are available online, and our data-driven infection network models are scalable, whether it be at the level of a city, town, country, or continent, and applicable anywhere in the world, as long as the time-series data of infections per region is available. These estimations of effective distance and the depiction of infectious disease networks based on actual infection data are expected to be useful in devising data-driven countermeasures against emerging infectious diseases worldwide.

scholarly journals Data driven transfer functions and transmission network parameters for GIC modelling

2020 ◽  
Vol 188 ◽  
pp. 106546
Author(s):  
M.J. Heyns ◽  
C.T. Gaunt ◽  
S.I. Lotz ◽  
P.J. Cilliers
Keyword(s):  
Transfer Functions ◽  
Data Driven ◽  
Transmission Network ◽  
Network Parameters

scholarly journals When past is not a prologue: Adapting informatics practice during a pandemic

2020 ◽  
Vol 27 (7) ◽  
pp. 1142-1146 ◽  
Author(s):  
Thomas G Kannampallil ◽  
Randi E Foraker ◽  
Albert M Lai ◽  
Keith F Woeltje ◽  
Philip R O Payne
Keyword(s):  
Predictive Models ◽  
Past History ◽  
Lessons Learned ◽  
Data Driven ◽  
Disease Spread ◽  
Delivery Of Care ◽  
The Past ◽  
History Of ◽  
Models Of Disease ◽  
Fundamental Shift

Abstract Data and information technology are key to every aspect of our response to the current coronavirus disease 2019 (COVID-19) pandemic—including the diagnosis of patients and delivery of care, the development of predictive models of disease spread, and the management of personnel and equipment. The increasing engagement of informaticians at the forefront of these efforts has been a fundamental shift, from an academic to an operational role. However, the past history of informatics as a scientific domain and an area of applied practice provides little guidance or prologue for the incredible challenges that we are now tasked with performing. Building on our recent experiences, we present 4 critical lessons learned that have helped shape our scalable, data-driven response to COVID-19. We describe each of these lessons within the context of specific solutions and strategies we applied in addressing the challenges that we faced.

scholarly journals Pooled testing with replication: a mass testing strategy for the COVID-19 pandemics

2020 ◽  
Author(s):  
Julius Žilinskas ◽  
Algirdas Lančinskas ◽  
Mario R. Guarracino
Keyword(s):  
Real Time ◽  
Real Time Pcr ◽  
Group Testing ◽  
Antiviral Drugs ◽  
Testing Strategy ◽  
Testing Procedures ◽  
Pooled Testing ◽  
Replication Scheme ◽  
Speed Up ◽  
Multiple Patients

AbstractIn absence of a vaccine or antiviral drugs for the COVID-19 pandemic, it becomes urgent to test for positiveness to the virus as many people as possible, in order to detect early outbreaks of the infection. Present testing solutions are based on the extraction of RNA from patients using oropharyngeal (OP) and nasopharyngeal (NP) swabs, and then testing with real-time PCR for the presence of specific RNA filaments identifying the virus. This approach is limited by the availability of reactants, trained technicians and laboratories. To speed up the testing procedures, some attempts have been done on group testing, which means that the swabs of multiple patients are grouped together and tested. Here we propose to use this technique in conjunction with a combinatorial replication scheme in which each patient is allocated in two or more groups to reduce total numbers of tests and to allow testing of even larger numbers of people. Under mild assumptions, a 13× average reduction of tests can be achieved.

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