scholarly journals Network assessment and modeling the management of an epidemic on a college campus with testing, contact tracing, and masking

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257052
Author(s):  
Gregg Hartvigsen
Keyword(s):  
Disease Transmission ◽  
Liberal Arts ◽  
Transmission Probability ◽  
College Campus ◽  
Contact Tracing ◽  
Random Networks ◽  
Course Enrollment ◽  
Residential College ◽  
Testing Frequency ◽  
Path Lengths

There remains a great challenge to minimize the spread of epidemics, especially in high-density communities such as colleges and universities. This is particularly true on densely populated, residential college campuses. To construct class and residential networks data from a four-year, residential liberal arts college with 5539 students were obtained from SUNY College at Geneseo, a rural, residential, undergraduate institution in western NY, USA. Equal-sized random networks also were created for each day. Different levels of compliance with mask use (none to 100%), mask efficacy (50% to 100%), and testing frequency (daily, or every 2, 3, 7, 14, 28, or 105 days) were assessed. Tests were assumed to be only 90% accurate and positive results were used to isolate individuals. The effectiveness of contact tracing, and the effect of quarantining neighbors of infectious individuals, was tested. The structure of the college course enrollment and residence networks greatly influenced the dynamics of the epidemics, as compared to the random networks. In particular, average path lengths were longer in the college networks compared to random networks. Students in larger majors generally had shorter average path lengths than students in smaller majors. Average transitivity (clustering) was lower on days when students most frequently were in class (MWF). Degree distributions were generally large and right skewed, ranging from 0 to 719. Simulations began by inoculating twenty students (10 exposed and 10 infectious) with SARS-CoV-2 on the first day of the fall semester and ended once the disease was cleared. Transmission probability was calculated based on an R0 = 2.4. Without interventions epidemics resulted in most students becoming infected and lasted into the second semester. On average students in the college networks experienced fewer infections, shorter duration, and lower epidemic peaks when compared to the dynamics on equal-sized random networks. The most important factors in reducing case numbers were the proportion masking and the frequency of testing, followed by contact tracing and mask efficacy. The paper discusses further high-order interactions and other implications of non-pharmaceutical interventions for disease transmission on a residential college campus.

scholarly journals Network assessment and modeling the management of an epidemic on a college campus with testing, contact tracing, and masking

2021 ◽  
Author(s):  
Gregg Hartvigsen
Keyword(s):  
Disease Transmission ◽  
Liberal Arts ◽  
Transmission Probability ◽  
College Campus ◽  
Contact Tracing ◽  
Random Networks ◽  
Residential College ◽  
Testing Frequency ◽  
Disease Agent ◽  
Path Lengths

There remains a great challenge to minimize the spread of epidemics. This may be particularly true on densely populated, residential college campuses. To construct class and residential networks I used data from a four-year, residential liberal arts college with 5539 students. Equal-sized random networks also were created for each day. Different levels of compliance with mask use (none to 100%), mask efficacy (50% to 100%), and testing frequency (daily, or every 2, 3, 7, 14, 28, or 105 days) were assessed. Tests were assumed to be only 90% accurate and positive results were used to isolate individuals. I also tested the effectiveness of contact tracing and subsequent quarantining of neighbors of infectious individuals. I used class enrollment and residence data from a college with 5539 students to analyze network structure and test the epidemic potential of the infectious disease agent SARS-CoV-2. Average path lengths were longer in the college networks compared to random networks. Students in larger majors generally had shorter average path lengths. Average transitivity (clustering) was lower on days when students most frequently were in class (MWF). Degree distributions were generally large and right skewed, ranging from 0 to 719. Simulations began by inoculating twenty students (10 exposed and 10 infectious) with SARS-CoV-2 on the first day of the fall semester and ended once the disease was cleared. Transmission probability was calculated based on an R0 = 2:4. Without interventions epidemics resulted in most students becoming infected and lasted into the second semester. On average students in the college networks experienced fewer infections, shorter duration, and lower epidemic peaks that occurred compared to dynamics on equal-sized random networks. The most important factors in reducing case numbers were the proportion masking and the frequency of testing, followed by contact tracing and mask efficacy. The paper discusses further high-order interactions and other implications of non-pharmaceutical interventions for disease transmission on a residential college campus.

scholarly journals Stochastic Models of Emerging Infectious Disease Transmission on Adaptive Random Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Navavat Pipatsart ◽  
Wannapong Triampo ◽  
Charin Modchang
Keyword(s):  
Infectious Disease ◽  
Disease Transmission ◽  
Random Network ◽  
Network Models ◽  
Transmission Probability ◽  
Stochastic Simulations ◽  
Random Networks ◽  
Cumulative Number ◽  
Network Adaptation ◽  
Infectious Disease Dynamics

We presented adaptive random network models to describe human behavioral change during epidemics and performed stochastic simulations of SIR (susceptible-infectious-recovered) epidemic models on adaptive random networks. The interplay between infectious disease dynamics and network adaptation dynamics was investigated in regard to the disease transmission and the cumulative number of infection cases. We found that the cumulative case was reduced and associated with an increasing network adaptation probability but was increased with an increasing disease transmission probability. It was found that the topological changes of the adaptive random networks were able to reduce the cumulative number of infections and also to delay the epidemic peak. Our results also suggest the existence of a critical value for the ratio of disease transmission and adaptation probabilities below which the epidemic cannot occur.

COVID-19 Testing: Frequency Wins over Sensitivity in Control of Disease Transmission

Nano LIFE ◽  
2020 ◽  
pp. 2030002
Author(s):  
Francois Berthiaume
Keyword(s):  
Infection Control ◽  
Disease Transmission ◽  
Lessons Learned ◽  
Contact Tracing ◽  
Severe Illness ◽  
Sensitivity Threshold ◽  
Rt Pcr ◽  
Emerging Viruses ◽  
Sensitivity Testing ◽  
Testing Frequency

Emerging pathogens have no known therapies or vaccines and therefore can only be controlled via traditional methods of contact tracing, quarantine and isolation that require rapid and widespread testing. The most recent outbreak from an emerging pathogen is due to the highly transmissible SARS-CoV-2 virus causing COVID-19 disease, which is associated with no symptoms or mild symptoms in 80–90% of the infected individuals, while in the remainder of the patients it exhibits severe illness that can be lethal or persist for several weeks to months after infection. The first tests to diagnose infection by SARS-CoV-2 were developed soon after the genome of the virus became known, and use probes to measure viral RNA by reverse transcriptase-polymerase chain reaction (RT-PCR). These tests are highly sensitive and specific but can require several days to return results, which makes contact tracing and more generally efforts to control the spread of the infection very difficult. Furthermore, the sensitivity threshold is orders of magnitude below the viral load necessary for transmission; therefore, individuals recovering from the infection may still be have a positive test and be required to isolate unnecessarily while they are no longer infectious. Antigen tests were subsequently developed that use antibodies mostly targeted to the nucleocapsid protein of the virus. These tests are about 100 times less sensitive than RT-PCR, yes they detect viral loads that are about 1/10 that needed for transmission. Furthermore, such tests are potentially much cheaper than RT-PCR and yield results in 15 min or less. Antibody, also known as serological testing, is available and can provide useful information to understand the extent to which a population has been exposed to the virus; however, it is not a good indicator of current infection and not useful for infection control. Viral transmission models that incorporate testing and contact tracing show that infection control is much more readily achieved by increasing testing frequency than by using higher sensitivity testing. For example, compared to no testing at all, testing once every other week has a marginal benefit, while testing weekly can decrease the number of infections to 20–40%, and testing twice weekly or more can bring about a 95%[Formula: see text] reduction in infections. These lessons learned from dealing from the COVID-19 pandemic should guide future planning against potential emerging viruses.

scholarly journals Still a Small World? University Course Enrollment Networks before and during the COVID-19 Pandemic

2021 ◽  
Author(s):  
Kim A Weeden ◽  
Benjamin Cornwell ◽  
Barum Park
Keyword(s):  
Short Path ◽  
Small World ◽  
College Campus ◽  
Instructional Model ◽  
Small World Network ◽  
Network Ties ◽  
Course Enrollment ◽  
Cornell University ◽  
Path Lengths ◽  
University Course

In normal times, the network ties that connect students on a college campus are an asset; during a pandemic, they can become a liability. Using pre-pandemic data from Cornell University, Weeden and Cornwell showed how co-enrollment in classes creates a “small world” network with high clustering, short path lengths, and multiple independent pathways connecting students. In this paper, we show how the structure of the enrollment network changed as Cornell, like many American colleges and universities, shifted to a hybrid instructional model with some courses online and others in person. Under this model, about half of students are disconnected from the in-person co-enrollment network. In this network, paths lengthened, the share of student pairs connected by three or fewer degrees of separation declined, and clustering increased, with a greater share of ties occurring between students in the same field. The small world became both less connected and more fragmented. (Corrected page proofs. Paper is forthcoming in Sociological Science.)

scholarly journals Modeling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil

2021 ◽  
Author(s):  
Marcelo Eduardo Borges ◽  
Leonardo Souto Ferreira ◽  
Silas Poloni ◽  
Ângela Maria Bagattini ◽  
Caroline Franco ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Transmission Rate ◽  
Disease Incidence ◽  
Demographic Data ◽  
School Closure ◽  
Mitigation Measures ◽  
Contact Tracing ◽  
School Closures ◽  
Infection Transmission ◽  
The Impact

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.

scholarly journals The Small World Network of College Classes: Implications for Epidemic Spread on a University Campus

2020 ◽  
Author(s):  
Kim A Weeden ◽  
Benjamin Cornwell
Keyword(s):  
Liberal Arts ◽  
Small World ◽  
University Campus ◽  
Epidemic Spread ◽  
Small Worlds ◽  
American University ◽  
Gateway Courses ◽  
Path Lengths ◽  
College Classes ◽  
Novel Coronavirus

To slow the spread of the novel coronavirus, many universities shifted to online instruction and now face the question of whether and how to resume in-person instruction. This article uses transcript data from a medium-sized American university to describe three enrollment networks that connect students through classes, and in the process create social conditions for the spread of infectious disease: an university-wide network, an undergraduate-only network, and a liberal arts college network. All three networks are “small worlds” characterized by high clustering, short average path lengths, and multiple independent paths connecting students. Students from different majors cluster together, but gateway courses and distributional requirements create cross-major integration. Connectivity declines when large courses of 100 students or more are removed from the network, as might be the case if some courses are taught online, but moderately sized courses must also be removed before less than half of student-pairs are connected in three steps and less than two-thirds in four steps. In all simulations, most students are connected through multiple independent paths. Hybrid models of instruction can reduce but not eliminate the potential for epidemic spread through the small worlds of course enrollments.

scholarly journals How effective was Newfoundland & Labrador’s travel ban to prevent the spread of COVID-19? An agent-based analysis

2021 ◽  
Author(s):  
Dionne M. Aleman ◽  
Benjamin Z. Tham ◽  
Sean J. Wagner ◽  
Justin Semelhago ◽  
Asghar Mohammadi ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Spatial Location ◽  
Contact Tracing ◽  
Infection Rates ◽  
Case Scenario ◽  
Agent Based ◽  
Individual Level ◽  
Transmission Rates ◽  
Imported Cases ◽  
The Uk

AbstractBackgroundTo prevent the spread of COVID-19 in Newfoundland & Labrador (NL), NL implemented a wide travel ban in May 2020. We estimate the effectiveness of this travel ban using a customized agent-based simulation (ABS).MethodsWe built an individual-level ABS to simulate the movements and behaviors of every member of the NL population, including arriving and departing travellers. The model considers individual properties (spatial location, age, comorbidities) and movements between environments, as well as age-based disease transmission with pre-symptomatic, symptomatic, and asymptomatic transmission rates. We examine low, medium, and high travel volume, traveller infection rates, and traveller quarantine compliance rates to determine the effect of travellers on COVID spread, and the ability of contact tracing to contain outbreaks.ResultsInfected travellers increased COVID cases by 2-52x (8-96x) times and peak hospitalizations by 2-49x (8-94x), with (without) contact tracing. Although contact tracing was highly effective at reducing spread, it was insufficient to stop outbreaks caused by travellers in even the best-case scenario, and the likelihood of exceeding contact tracing capacity was a concern in most scenarios. Quarantine compliance had only a small impact on COVID spread; travel volume and infection rate drove spread.InterpretationNL’s travel ban was likely a critically important intervention to prevent COVID spread. Even a small number of infected travellers can play a significant role in introducing new chains of transmission, resulting in exponential community spread and significant increases in hospitalizations, while outpacing contact tracing capabilities. With the presence of more transmissible variants, e.g., the UK variant, prevention of imported cases is even more critical.

scholarly journals COVID-19 and its threat to refugees in Africa

2021 ◽  
Vol 11 (3) ◽  
pp. 263-266
Author(s):  
Emery Manirambona ◽  
Laura Wilkins ◽  
Don Eliseo Lucero-Prisno III
Keyword(s):  
Gender Equity ◽  
Disease Transmission ◽  
Contact Tracing ◽  
Gender Inequalities ◽  
Host Countries ◽  
Governmental Organizations ◽  
Refugee Community ◽  
Non Governmental Organizations ◽  
Equal Importance ◽  
Data Driven Decisions

Although it is widely accepted that coronavirus disease 2019 (COVID-19) has adversely affected the Global South’s most vulnerable refugee communities, they have received little attention. There have been gaps in testing, which is fundamental to treat and isolate patients and make data-driven decisions to protect the refugee community. Therefore, it is imperative to holistically implement policies to curtail COVID-19 in refugee camps to ensure that refugees are safe and protected from the pandemic. Processes for timely diagnosis and treatment, quick isolation and contact tracing are essential to keep refugees safe. Furthermore, it is crucial to encourage protective behaviours and raise awareness about hygiene and social prevention to dampen disease transmission. Refugees in the Global South have been disproportionately affected by the consequences of the COVID-19 pandemic, facing financial hardship and social injustice throughout. Refugees in Africa have also faced threats to their security, being subjected to torture, disappearance, or even killings in their host countries. The pandemic has exposed gender inequalities, with females being the most affected, and health inequities in the refugee community in Africa. There is a need for international organizations like the African Union, United Nations (UN) agencies, non-governmental organizations (NGOs), and other stakeholders to take serious action regarding the refugee situation in Africa. Food aid for refugees in Africa should be increased as quickly as possible and refugees’ security must be guaranteed. Of equal importance, there must be justice for the death or disappearance of refugees. It is imperative to end discrimination against refugees and support the promotion of gender equity.

The Liberal Arts, the Campus, and the Biosphere

1990 ◽  
Vol 60 (2) ◽  
pp. 205-217 ◽  
Author(s):  
David Orr
Keyword(s):  
Higher Education ◽  
Liberal Arts ◽  
Natural World ◽  
Colleges And Universities ◽  
College Campus ◽  
Environmental Concerns ◽  
Liberal Arts Institutions ◽  
College Youth ◽  
Curricular Innovations ◽  
Allan Bloom

Where does the campus fit into the biosphere? What role should universities play in the struggle to save the environment? Although critics, such as Allan Bloom, have recently accused liberal arts institutions of failing to educate college youth properly, few have addressed the question of how colleges and universities might make students more aware and responsible about their place in the natural world. In this article David Orr offers a rationale for incorporating environmental concerns into the curricula of higher education and suggests examples of curricular innovations, including programs for restructuring the ways colleges procure food, deal with waste, and use energy. Orr shows us how a focus on the ecosystem of the college campus can broaden students' visions of the natural world in which they live.

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