scholarly journals A modeling study to inform screening and testing interventions for the control of SARS-CoV-2 on university campuses

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ben Lopman ◽  
Carol Y. Liu ◽  
Adrien Le Guillou ◽  
Andreas Handel ◽  
Timothy L. Lash ◽  
...  
Keyword(s):  
Cumulative Incidence ◽  
Disease Surveillance ◽  
Control Strategies ◽  
Transmission Model ◽  
University Administrators ◽  
Modeling Framework ◽  
University Campuses ◽  
School Year ◽  
Flexible Modeling ◽  
Resource Requirements

AbstractUniversity administrators face decisions about how to safely return and maintain students, staff and faculty on campus throughout the 2020–21 school year. We developed a susceptible-exposed-infectious-recovered (SEIR) deterministic compartmental transmission model of SARS-CoV-2 among university students, staff, and faculty. Our goals were to inform planning at our own university, Emory University, a medium-sized university with around 15,000 students and 15,000 faculty and staff, and to provide a flexible modeling framework to inform the planning efforts at similar academic institutions. Control strategies of isolation and quarantine are initiated by screening (regardless of symptoms) or testing (of symptomatic individuals). We explored a range of screening and testing frequencies and performed a probabilistic sensitivity analysis. We found that among students, monthly and weekly screening can reduce cumulative incidence by 59% and 87%, respectively, while testing with a 2-, 4- and 7-day delay between onset of infectiousness and testing results in an 84%, 74% and 55% reduction in cumulative incidence. Smaller reductions were observed among staff and faculty. Community-introduction of SARS-CoV-2 onto campus may be controlled with testing, isolation, contract tracing and quarantine. Screening would need to be performed at least weekly to have substantial reductions beyond disease surveillance. This model can also inform resource requirements of diagnostic capacity and isolation/quarantine facilities associated with different strategies.

scholarly journals A model of COVID-19 transmission and control on university campuses

2020 ◽  
Author(s):  
Ben Lopman ◽  
Carol Y. Liu ◽  
Adrien Le Guillou ◽  
Timothy L. Lash ◽  
Alexander P. Isakov ◽  
...  
Keyword(s):  
Cumulative Incidence ◽  
Control Strategies ◽  
Transmission Model ◽  
Reproductive Number ◽  
Medium Size ◽  
University Administrators ◽  
Screening Assay ◽  
Modeling Framework ◽  
University Campuses ◽  
Resource Requirements

AbstractIn response to the COVID-19 pandemic, institutions of higher education in almost every nation closed in the first half of 2020. University administrators are now facing decisions about how to safely return students, staff and faculty to campus. To provide a framework to evaluate various strategies, we developed a susceptible-exposed-infectious-recovered (SEIR) type of deterministic compartmental transmission model of SARS-CoV-2 among students, staff and faculty. Our goals were to support the immediate pandemic planning at our own university, and to provide a flexible modeling framework to inform the planning efforts at similar academic institutions. We parameterized the model for our institution, Emory University, a medium-size private university in Atlanta, Georgia. Control strategies of isolation and quarantine are initiated by screening (regardless of symptoms) or testing (of symptomatic individuals). We explore a range of screening and testing frequencies and perform a probabilistic sensitivity analysis of input parameters. We find that monthly and weekly screening can reduce cumulative incidence by 42% and 80% in students, respectively, while testing with a 2-, 4- and 7-day delay results in an 88%, 79% and 67% reduction in cumulative incidence in students over the semester, respectively. Similar reductions are observed among staff and faculty. A testing strategy requires far fewer diagnostic assays to be implemented than a screening assay. Our intervention model is conservative in that we assume a fairly high reproductive number that is not reduced through social distancing measures. We find that community-introduction of SARS-CoV-2 infection onto campus can be controlled with effective testing, isolation, contract tracing and quarantine, but that cases, hospitalization, and (in some scenarios) deaths may still occur. In addition to estimating health impacts, this model can help to predict the resource requirements in terms of diagnostic capacity and isolation/quarantine facilities associated with different strategies.

scholarly journals A Dynamic Transmission Model to Evaluate the Effectiveness of Infection Control Strategies

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Karim Khader ◽  
Alun Thomas ◽  
W. Charles Huskins ◽  
Molly Leecaster ◽  
Yue Zhang ◽  
...  
Keyword(s):  
Transmission Rate ◽  
Control Strategies ◽  
Transmission Model ◽  
Modeling Framework ◽  
Intervention Effect ◽  
Rigorous Evaluation ◽  
Alternative Intervention ◽  
Statistical Framework ◽  
Dynamic Transmission Model ◽  
Original Analysis

Abstract Background The advancement of knowledge about control of antibiotic resistance depends on the rigorous evaluation of alternative intervention strategies. The STAR*ICU trial examined the effects of active surveillance and expanded barrier precautions on acquisition of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE) in intensive care units. We report a reanalyses of the STAR*ICU trial using a Bayesian transmission modeling framework. Methods The data included admission and discharge times and surveillance test times and results. Markov chain Monte Carlo stochastic integration was used to estimate the transmission rate, importation, false negativity, and clearance separately for MRSA and VRE. The primary outcome was the intervention effect, which when less than (or greater than) zero, indicated a decreased (or increased) transmission rate attributable to the intervention. Results The transmission rate increased in both arms from pre- to postintervention (by 20% and 26% for MRSA and VRE). The estimated intervention effect was 0.00 (95% confidence interval [CI], −0.57 to 0.56) for MRSA and 0.05 (95% CI, −0.39 to 0.48) for VRE. Compared with MRSA, VRE had a higher transmission rate (preintervention, 0.0069 vs 0.0039; postintervention, 0.0087 vs 0.0046), higher importation probability (0.22 vs 0.17), and a lower clearance rate per colonized patient-day (0.016 vs 0.035). Conclusions Transmission rates in the 2 treatment arms were statistically indistinguishable from the pre- to postintervention phase, consistent with the original analysis of the STAR*ICU trial. Our statistical framework was able to disentangle transmission from importation and account for imperfect testing. Epidemiological differences between VRE and MRSA were revealed.

scholarly journals Quantifying the dynamics of pig movements improves targeted disease surveillance and control plans

2019 ◽  
Author(s):  
Gustavo Machado ◽  
Jason Ardila Galvis ◽  
Francisco Paulo Nunes Lopes ◽  
Joana Voges ◽  
Antônio Augusto Rosa Medeiros ◽  
...  
Keyword(s):  
Disease Control ◽  
Disease Surveillance ◽  
Control Strategies ◽  
Disease Spread ◽  
Growth Stages ◽  
Case Scenario ◽  
Modeling Framework ◽  
Worst Case ◽  
Movement Data ◽  
The Impact

SummaryTracking animal movements over time can fundamentally determine the success of disease control interventions throughout targeting farms that are tightly connected. In commercial pig production, animals are transported between farms based on growth stages, thus it generates time-varying contact networks that will influence the dynamics of disease spread. Still, risk-based surveillance strategies are mostly based on a static network. In this study, we reconstructed the static and temporal pig networks of one Brazilian state from 2017 to 2018, comprising 351,519 movements and 48 million transported pigs. The static networks failed to capture time-respecting movement pathways. Therefore, we propose a time-dependent network susceptible-infected (SI) model to simulate the temporal spread of an epidemic over the pig network globally through the temporal movement of animals among farms, and locally with a stochastic compartmental model in each farm, configured to calculate the minimum number of target farms needed to achieve effective disease control. In addition, we propagated disease on the pig temporal network to calculate the cumulative contacts as a proxy of epidemic sizes and evaluated the impact of network-based disease control strategies. The results show that targeting the first 1,000 farms ranked by degree would be sufficient and feasible to diminish disease spread considerably. Our finding also suggested that assuming a worst-case scenario in which every movement transmit disease, pursuing farms by degree would limit the transmission to up to 29 farms over the two years period, which is lower than the number of infected farms for random surveillance, with epidemic sizes of 2,593 farms. The top 1,000 farms could benefit from enhanced biosecurity plans and improved surveillance, which constitute important next steps in strategizing targeted disease control interventions. Overall, the proposed modeling framework provides a parsimonious solution for targeted disease surveillance when temporal movement data is available.

scholarly journals Size matters: Sample size assessments for chronic wasting disease surveillance using an agent-based modeling framework

MethodsX ◽  
2020 ◽  
Vol 7 ◽  
pp. 100953
Author(s):  
Aniruddha Belsare ◽  
Matthew Gompper ◽  
Barbara Keller ◽  
Jason Sumners ◽  
Lonnie Hansen ◽  
...  
Keyword(s):  
Sample Size ◽  
Disease Surveillance ◽  
Chronic Wasting Disease ◽  
Agent Based Modeling ◽  
Modeling Framework ◽  
Wasting Disease ◽  
Agent Based

scholarly journals Investigating the effects of accelerated partner therapy (APT) on chlamydia transmission in Britain: a mathematical modelling study

2020 ◽  
Author(s):  
Christian L Althaus ◽  
Catherine H Mercer ◽  
Jackie A Cassell ◽  
Claudia S Estcourt ◽  
Nicola Low
Keyword(s):  
Sexual Activity ◽  
Control Strategies ◽  
Controlled Trial ◽  
Partner Notification ◽  
Cluster Randomised Controlled Trial ◽  
Credible Interval ◽  
Population Based ◽  
Transmission Model ◽  
Transmitted Infection ◽  
Potential Increase

Understanding the effects of partner notification (PN) on the transmission of chlamydia, the most prevalent bacterial sexual transmitted infection worldwide, is critical for implementing optimal control strategies. Accelerated partner therapy (APT) aims to increase the numbers of partners treated and reduce the time to partner treatment. Our objective was to study the effects of APT interventions on partner treatment and chlamydia transmission in order to better understand the results of LUSTRUM, an APT cross-over cluster randomised controlled trial in the UK. We developed a novel deterministic, population-based chlamydia transmission model including the process of PN. We considered a population aged 16-34 years and calibrated the model to sexual behaviour data between people of the opposite-sex and chlamydia prevalence data reported by 3,671 participants in Britain's third National Survey of Sexual Attitudes and Lifestyles (Natsal-3, 2010-2012) using Approximate Bayesian Computation (ABC). We investigated the potential effects of APT on chlamydia transmission by increasing the number of treated partners and reducing the time to partner treatment compared to standard PN. The median prevalence of chlamydia in the model was 1.84% (95% credible interval, CrI: 1.60%-2.62%) in women and 1.78% (95% CrI: 1.13%-2.14%) in men. Chlamydia positivity was highest in partners of symptomatic index cases with low sexual activity. Infected partners were typically asymptomatic and belonged to the high sexual activity group, i.e., are naturally those infected individuals that will contribute most to onward transmission. Reducing the time to partner treatment without achieving higher numbers of partners treated had only minor effects on reducing chlamydia prevalence. In contrast, the model predicts that a potential increase in the number of partners treated from current levels in Britain (0.51, 95% CrI: 0.21-0.80) by 25% would reduce chlamydia prevalence by 18% (95% CrI: 5%-44%) in both women in men within 5 years. These results suggest that APT, through a potential increase in the proportion of partners treated, would be an effective method to reduce ongoing chlamydia transmission in Britain.

scholarly journals Hepatitis B virus infection in Nigeria: a systematic review and meta-analysis of data published between 2010 and 2019

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Busayo I. Ajuwon ◽  
Isabelle Yujuico ◽  
Katrina Roper ◽  
Alice Richardson ◽  
Meru Sheel ◽  
...  
Keyword(s):  
Systematic Review ◽  
Hepatitis B Virus ◽  
Hepatitis B ◽  
Disease Surveillance ◽  
Control Strategies ◽  
Meta Analysis ◽  
Population Based ◽  
North West ◽  
B Virus ◽  
The Impact

Abstract Background Hepatitis B virus (HBV) is an infectious disease of global significance, causing a significant health burden in Africa due to complications associated with infection, such as cirrhosis and liver cancer. In Nigeria, which is considered a high prevalence country, estimates of HBV cases are inconsistent, and therefore additional clarity is required to manage HBV-associated public health challenges. Methods A systematic review of the literature (via PubMed, Advanced Google Scholar, African Index Medicus) was conducted to retrieve primary studies published between 1 January 2010 and 31 December 2019, with a random-effects model based on proportions used to estimate the population-based prevalence of HBV in the Nigerian population. Results The final analyses included 47 studies with 21,702 participants that revealed a pooled prevalence of 9.5%. A prevalence estimate above 8% in a population is classified as high. Sub-group analyses revealed the highest HBV prevalence in rural settings (10.7%). The North West region had the highest prevalence (12.1%) among Nigeria’s six geopolitical zones/regions. The estimate of total variation between studies indicated substantial heterogeneity. These variations could be explained by setting and geographical region. The statistical test for Egger’s regression showed no evidence of publication bias (p = 0.879). Conclusions We present an up-to-date review on the prevalence of HBV in Nigeria, which will provide critical data to optimise and assess the impact of current prevention and control strategies, including disease surveillance and diagnoses, vaccination policies and management for those infected.

scholarly journals Effectiveness of Screening Hospital Admissions to Detect Asymptomatic Carriers of Clostridium difficile: A Modeling Evaluation

2014 ◽  
Vol 35 (8) ◽  
pp. 1043-1050 ◽  
Author(s):  
Cristina Lanzas ◽  
Erik R. Dubberke
Keyword(s):  
Clostridium Difficile ◽  
Hospital Admissions ◽  
Control Strategies ◽  
Turnaround Time ◽  
Current Control ◽  
Hospital Ward ◽  
Transmission Model ◽  
Baseline Scenario ◽  
Asymptomatic Carriers ◽  
Contact Precautions

ObjectiveBoth asymptomatic and symptomatic Clostridium difficile carriers contribute to new colonizations and infections within a hospital, but current control strategies focus only on preventing transmission from symptomatic carriers. Our objective was to evaluate the potential effectiveness of methods targeting asymptomatic carriers to control C. difficile colonization and infection (CDI) rates in a hospital ward: screening patients at admission to detect asymptomatic C. difficile carriers and placing positive patients into contact precautions.MethodsWe developed an agent-based transmission model for C. difficile that incorporates screening and contact precautions for asymptomatic carriers in a hospital ward. We simulated scenarios that vary according to screening test characteristics, colonization prevalence, and type of strain present at admission.ResultsIn our baseline scenario, on average, 42% of CDI cases were community-onset cases. Within the hospital-onset (HO) cases, approximately half were patients admitted as asymptomatic carriers who became symptomatic in the ward. On average, testing for asymptomatic carriers reduced the number of new colonizations and HO-CDI cases by 40%–50% and 10%–25%, respectively, compared with the baseline scenario. Test sensitivity, turnaround time, colonization prevalence at admission, and strain type had significant effects on testing efficacy.ConclusionsTesting for asymptomatic carriers at admission may reduce both the number of new colonizations and HO-CDI cases. Additional reductions could be achieved by preventing disease in patients who are admitted as asymptomatic carriers and developed CDI during the hospital stay.

What Administrators Do

2011 ◽  
Author(s):  
Benjamin Ginsberg
Keyword(s):  
Planning Process ◽  
Fund Raising ◽  
University Administrators ◽  
Senior Managers ◽  
University Campuses ◽  
College And University ◽  
For Profit ◽  
Actual Contribution ◽  
The One ◽  
The University

The Number of administrators and staffers on university campuses has increased so rapidly in recent years that often there is simply not enough work to keep all of them busy. I have spent time in university administrative suites and in the corridors of public agencies. In both settings I am always struck by the fact that so many well-paid individuals have so little to do. To fill their time, administrators engage in a number of make-work activities. They attend meetings and conferences, they organize and attend administrative and staff retreats, and they participate in the strategic planning processes that have become commonplace on many campuses. While these activities are time consuming, their actual contribution to the core research and teaching missions of the university is questionable. Little would be lost if all pending administrative retreats and conferences, as well as four of every five staff meetings (these could be selected at random), were canceled tomorrow. And, as to the ubiquitous campus planning exercises, as we shall see below, the planning process functions mainly to enhance the power of senior managers. The actual plans produced after the investment of thousands of hours of staff time are usually filed away and quickly forgotten. There is, to be sure, one realm in which administrators as-a-class have proven extraordinarily adept. This is the general domain of fund-raising. College and university administrators have built a massive fund-raising apparatus that, every year, collects hundreds of millions of dollars in gifts and bequests mainly, though not exclusively, from alumni whose sense of nostalgia or obligation make them easy marks for fund-raisers’ finely-honed tactics. Even during the depths of the recession in 2009, schools were able to raise money. On the one hand, the donors who give selflessly to their schools deserve to be commended for their beneficence. At the same time, it should still be noted that, as is so often the case in the not-for-profit world, university administrators appropriate much of this money to support—what else?— more administration.

scholarly journals Reactive school closure weakens the network of social interactions and reduces the spread of influenza

2019 ◽  
Vol 116 (27) ◽  
pp. 13174-13181 ◽  
Author(s):  
Maria Litvinova ◽  
Quan-Hui Liu ◽  
Evgeny S. Kulikov ◽  
Marco Ajelli
Keyword(s):  
Social Interactions ◽  
Influenza Season ◽  
School Closure ◽  
Transmission Model ◽  
Modeling Framework ◽  
School Closures ◽  
Student Absenteeism ◽  
Contact Survey ◽  
Closure Policy ◽  
The Impact

School-closure policies are considered one of the most promising nonpharmaceutical interventions for mitigating seasonal and pandemic influenza. However, their effectiveness is still debated, primarily due to the lack of empirical evidence about the behavior of the population during the implementation of the policy. Over the course of the 2015 to 2016 influenza season in Russia, we performed a diary-based contact survey to estimate the patterns of social interactions before and during the implementation of reactive school-closure strategies. We develop an innovative hybrid survey-modeling framework to estimate the time-varying network of human social interactions. By integrating this network with an infection transmission model, we reduce the uncertainty surrounding the impact of school-closure policies in mitigating the spread of influenza. When the school-closure policy is in place, we measure a significant reduction in the number of contacts made by students (14.2 vs. 6.5 contacts per day) and workers (11.2 vs. 8.7 contacts per day). This reduction is not offset by the measured increase in the number of contacts between students and nonhousehold relatives. Model simulations suggest that gradual reactive school-closure policies based on monitoring student absenteeism rates are capable of mitigating influenza spread. We estimate that without the implemented reactive strategies the attack rate of the 2015 to 2016 influenza season would have been 33% larger. Our study sheds light on the social mixing patterns of the population during the implementation of reactive school closures and provides key instruments for future cost-effectiveness analyses of school-closure policies.

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