Dr. Lauren Cipriano is a Professor in Management Science at the Ivey Business School where she is the Canada Research Chair in Healthcare Analytics, Management, and Policy. She holds cross appointments in the Department of Medicine and the Department of Epidemiology and Biostatistics at the Schulich School of Medicine & Dentistry at Western University.
Dr. Cipriano specializes in applying statistics, decision analysis, economics, and operations research to health policy problems. Her research focuses on the economic evaluation of clinical diagnostics and innovative therapeutics, resource allocation, and infectious disease policy.
She has provided consulting services to prominent organizations including the World Health Organization, US Veterans Health Administration, US Centers for Medicare and Medicaid Services, the US Institute for Clinical and Economic Review, and Canada's Drug Agency (formerly, the Canadian Agency for Drugs and Technologies in Health (CADTH)). During the pandemic, Dr. Cipriano served on the Ontario COVID-19 Science Advisory Table’s Modelling Consensus Table.
Dr. Cipriano is an Investigator with the Toronto Health Economics and Technology Assessment (THETA) Collaborative and a Research Affiliate with the Center for Health Economics of Treatment Interventions for Substance Use Disorder, HCV, and HIV (CHERISH). From 2019 to 2023, she served on the Health Economics Methods Advisory Committee for Canada's Drug Agency and was awarded the Dr. Maurice McGregor Award for Health Technology Assessment in 2019.
Dr. Cipriano is the Deputy Editor of the journals Medical Decision Making and MDM Policy & Practice.
Dr. Cipriano earned her MS in Statistics and PhD in Management Science and Engineering from Stanford University. She previously worked at the Institute for Technology Assessment at Massachusetts General Hospital.
At Ivey, Dr. Cipriano teaches undergraduate Decision Making with Analytics and graduate courses in Business Analytics and Statistics.
Recent Publications
Ghamat S, Araghi M, Cipriano LE, Silverman M. Influencing primary care antibiotic prescription behavior using financial incentives. Production and Operations Management. 2024; 33(10): 2051—2072. [link]
Goldhaber-Fiebert JD, Cipriano LE. Pricing treatments cost-effectively when they have multiple indications: not just a simple threshold analysis. Medical Decision Making. 2023 Oct-Nov;43(7-8):914-929. [link]
Cipriano LE, Haddara WMR, Zaric GS, Enns EA. Impact of university re-opening on total community COVID-19 burden. Plos One. 2021; 16(8):e0255782 [link]
Fairley M, Cipriano LE, Goldhaber-Fiebert JD. Optimal allocation of research funds under a budget constraint. Medical Decision Making. 2020; 40(6):797–814 [link]
Chehrazi N, Cipriano LE, Enns EA. Dynamics of drug resistance: optimal control of an infectious disease. Operations Research. 2019; 67(3):619–650. [link]
Cipriano LE, Weber TA. Population-level intervention and information-collection in dynamic healthcare policy. Health Care Management Science. 2018; 21(4):604–631. [link]
Cipriano LE, Goldhaber-Fiebert JD, Liu S, Weber TA. Optimal information collection policies in a Markov decision process framework. Medical Decision Making. 2018; 38(7):797–809. [link]
Cipriano LE, Liu S, Shahzada KS, Holodniy M, Goldhaber-Fiebert JD. Economically efficient hepatitis C virus treatment prioritization improves health outcomes. Medical Decision Making. 2018; 38(7): 849–865. [link]
Cipriano LE, Zaric GS. Cost-effectiveness of naloxone kits in secondary schools. Drug and Alcohol Dependence. 2018; 192:352–361. [link]
For a full list of publications, please see Google Scholar
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Ghamat, S.; Araghi, M.; Cipriano, L. E.; Silverman, M., 2024, "Influencing Primary Care Antibiotic Prescription Behavior Using Financial Incentives", Production and Operations Management, October 33(10): 2051 - 2072.
Abstract: Antibiotic resistance is an ongoing public health crisis fueled by overuse and misuse of antibiotics. The goal of this article is to examine the impact of action-based incentive payments on reducing inappropriate antibiotic prescriptions in primary care, where 30%–50% of antibiotic prescriptions are inappropriate. Various financial incentive programs to reduce the rate of inappropriate antibiotic prescriptions have been implemented and studied empirically. However, there have not been analytical studies to evaluate payment model contract design features and the potential for payment models to impact diagnosis decision making. We develop a stylized physician compensation model to study the interaction between a payer and a provider. The payer offers a payment contract, with a bonus tied to the prescription, to maximize social welfare, considering total costs of providing care and social harm from antibiotic resistance. Given the contract offered and their own opportunity cost associated with factors such as fear of misdiagnosis and time spent explaining to patients why antibiotics are not indicated, the provider chooses whether or not to prescribe antibiotics to patients for whom antibiotics are not clinically indicated. We consider four cases: when diagnostic accuracy relies on symptom presentation versus additional diagnostic testing and when the opportunity cost of not prescribing antibiotics is public versus private information of the provider. When there is no information asymmetry, an action-based incentive payment can co-ordinate care and achieve the first-best policy, decreasing the rate of inappropriate prescribing, even when incentive payments can affect the diagnosis behavior. However, when the diagnosis depends on additional testing, the first-best policy results in fewer inappropriate antibiotic prescriptions, when the test has high specificity. Therefore, when an accurate technical diagnostic is available, a simple to implement action-based incentive payment can be effective in reducing inappropriate antibiotic prescribing. In the realistic setting where the provider’s opportunity cost is private information, an action-based incentive payment cannot eliminate inappropriate antibiotic prescribing. In these settings, the introduction of point of care diagnostics to aid in objective diagnostic criteria will reduce the unintended consequences of the contract.
Link(s) to publication:
http://dx.doi.org/10.1177/10591478241264022
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Xia, Y.; Flores Anato, J. L.; Colijn, C.; Janjua, N.; Irvine, M.; Williamson, T.; Varughese, M. B.; Li, M.; Osgood, N.; Earn, D. J. D., et al., 2024, "Canada’s provincial COVID-19 pandemic modelling efforts: A review of mathematical models and their impacts on the responses", Canadian Journal of Public Health, August 115(4): 541 - 557.
Abstract: Setting: Mathematical modelling played an important role in the public health response to COVID-19 in Canada. Variability in epidemic trajectories, modelling approaches, and data infrastructure across provinces provides a unique opportunity to understand the factors that shaped modelling strategies. Intervention: Provinces implemented stringent pandemic interventions to mitigate SARS-CoV-2 transmission, considering evidence from epidemic models. This study aimed to summarize provincial COVID-19 modelling efforts. We identified modelling teams working with provincial decision-makers, through referrals and membership in Canadian modelling networks. Information on models, data sources, and knowledge translation were abstracted using standardized instruments. Outcomes: We obtained information from six provinces. For provinces with sustained community transmission, initial modelling efforts focused on projecting epidemic trajectories and healthcare demands, and evaluating impacts of proposed interventions. In provinces with low community transmission, models emphasized quantifying importation risks. Most of the models were compartmental and deterministic, with projection horizons of a few weeks. Models were updated regularly or replaced by new ones, adapting to changing local epidemic dynamics, pathogen characteristics, vaccines, and requests from public health. Surveillance datasets for cases, hospitalizations and deaths, and serological studies were the main data sources for model calibration. Access to data for modelling and the structure for knowledge translation differed markedly between provinces. Implication: Provincial modelling efforts during the COVID-19 pandemic were tailored to local contexts and modulated by available resources. Strengthening Canadian modelling capacity, developing and sustaining collaborations between modellers and governments, and ensuring earlier access to linked and timely surveillance data could help improve pandemic preparedness.
Link(s) to publication:
http://dx.doi.org/10.17269/s41997-024-00910-9
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Rahman, S.; Cipriano, L. E.; McDonald, C.; Cocco, S.; Hindi, Z.; Chakraborty, D.; French, K.; Siddiqi, O.; Brahmania, M.; Wilson, A., et al., 2024, "Propofol sedation does not improve measures of colonoscopy quality but increase cost – findings from a large population-based cohort study", eClinicalMedicine, April 70: 102503 - 102503.
Abstract: Background
Propofol is often used for sedation during colonoscopy. We assessed the impact of propofol sedation on colonoscopy related quality metrics and cost in a population-based cohort study.
Methods
All colonoscopies performed at 21 hospitals in the province of Ontario, Canada, during an 18-month period, from April 1, 2017 to October 31, 2018, using either propofol or conscious sedation were evaluated. The primary outcome was adenoma detection rate (ADR) and secondary outcomes were sessile serrated polyp detection rate (ssPDR), polyp detection rate (PDR), cecal intubation rate (CIR), and perforation rate. Binary outcomes were assessed using a modified Poisson regression model adjusted for clustering and potential confounders based on patient, procedure, and physician characteristics.
Findings
A total of 46,634 colonoscopies were performed, of which 16,408 (35.2%) received propofol and 30,226 (64.8%) received conscious sedation. Compared to conscious sedation, the use of propofol was associated with a lower ADR (24.6% vs. 27.0%, p < 0.0001) but not ssPDR (5.0% vs. 4.7%, p = 0.26), PDR (40.5% vs 40.4%, p = 0.79), CIR (97.1% vs. 96.8%, p = 0.15) or perforation rate (0.04% vs. 0.06%, p = 0.45). On multi-variable analysis, propofol sedation was not associated with any differences in ADR (RR = 0.90, 95% CI 0.74–1.10, p = 0.30), ssPDR (RR = 1.20, 95% CI 0.90–1.60, p = 0.22), PDR (RR = 1.00, 95% CI 0.90–1.11, p = 0.99), or CIR (RR = 1.00, 95% CI 0.80–1.26, p = 0.99). The additional cost associated with propofol sedation was $12,730,496 for every 100,000 cases.
Interpretation
The use of propofol sedation was not associated with improved colonoscopy related quality metrics but increased costs. The routine use of propofol for colonoscopy should be reevaluated.
Link(s) to publication:
http://dx.doi.org/10.1016/j.eclinm.2024.102503
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Hafeez, A.; Cipriano, L. E.; Kim, R. B.; Zaric, G. S.; Schwarz, U. I.; Sarma, S., 2024, "Cost-Effectiveness Analysis of Pharmacogenomics (PGx)-Based Warfarin, Apixaban, and Rivaroxaban Versus Standard Warfarin for the Management of Atrial Fibrillation in Ontario, Canada", PharmacoEconomics, January 42(1): 69 - 90.
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Ologundudu, O. M.; Palaniyappan, L.; Cipriano, L. E.; Wijnen, B. F. M.; Anderson, K. K.; Ali, S., 2023, "Risk stratification for treating people at ultra-high risk for psychosis: A cost-effectiveness analysis", Schizophrenia Research, November 261: 225 - 233.
Abstract: People who are at ultra-high risk (UHR) for psychosis receive clinical care with the aim to prevent first-episode psychosis (FEP), regardless of the risk of conversion to psychosis. An economic model from the Canadian health system perspective was developed to evaluate the cost-effectiveness of treating all with UHR compared to risk stratification over a 15-year time horizon, based on conversion probability, expected quality-of-life and costs. The analysis used a decision tree followed by a Markov model. Health states included: Not UHR, UHR with <20 % risk of conversion to FEP (based on the North American Prodrome Longitudinal Study risk calculator), UHR with ≥20 % risk, FEP, Remission, Post-FEP, and Death. The analysis found that: risk stratification (i.e., only treating those with ≥20 % risk) had lower costs ($1398) and quality-adjusted life-years (0.055 QALYs) per person compared to treating all. The incremental cost-effectiveness ratio for ‘treat all’ was $25,448/QALY, and suggests treating all may be cost-effective. The model was sensitive to changes to the probability of conversion.
Link(s) to publication:
http://dx.doi.org/10.1016/j.schres.2023.09.015
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Goldhaber-Fiebert, J.; Cipriano, L. E., 2023, "Pricing Treatments Cost-Effectively when They Have Multiple Indications: Not Just a Simple Threshold Analysis", Medical Decision Making, October 43(7-8): 914 - 929.
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Tran, C.; Cipriano, L. E.; Driman, D. K., 2023, "Impact of COVID-19-related health care disruptions on pathologic cancer staging during the first pandemic year: a retrospective cohort study from March 2018 to March 2021", CMAJ Open, May 11(3): E475 - E484.
Abstract: Background: The COVID-19 pandemic has created major disruptions in cancer care, with reductions in diagnostic tests and treatments. We evaluated the impact of these health care–related changes on cancer staging by comparing cancers staged before and during the pandemic.
Methods: We performed a retrospective cohort study at London Health Sciences Centre and St. Joseph’s Health Care London, London, Ontario, Canada. We evaluated all pathologically staged breast, colorectal, prostate, endometrial and lung cancers (the 5 most common cancers by site, excluding nonmelanoma skin cancer) over a 3-year period (Mar. 15, 2018–Mar. 14, 2021). The pre-COVID-19 group included procedures performed between Mar. 15, 2018, and Mar. 14, 2020, and the COVID-19 group included procedures performed between Mar. 15, 2020, and Mar. 14, 2021. The primary outcome was cancer stage group, based on the pathologic tumour, lymph node, metastasis system. We performed univariate analyses to compare demographic characteristics, pathologic features and cancer stage between the 2 groups. We performed multivariable ordinal regression analyses using the proportional odds model to evaluate the association between stage and timing of staging (before v. during the pandemic).
Results: There were 4055 cases across the 5 cancer sites. The average number of breast cancer staging procedures per 30 days increased during the pandemic compared to the yearly average in the pre-COVID-19 period (41.3 v. 39.6), whereas decreases were observed for endometrial cancer (15.9 v. 16.4), colorectal cancer (21.8 v. 24.3), prostate cancer (13.6 v. 18.5) and lung cancer (11.5 v. 15.9). For all cancer sites, there were no statistically significant differences in demographic characteristics, pathologic features or cancer stage between the 2 groups (p > 0.05). In multivariable regression analysis, for all cancer sites, cases staged during the pandemic were not associated with higher stage (breast: odds ratio [OR] 1.071, 95% confidence interval [CI] 0.826–1.388; colorectal: OR 1.201, 95% CI 0.869–1.661; endometrium: OR 0.792, 95% CI 0.495–1.252; prostate: OR 1.171, 95% CI 0.765–1.794; and lung: OR 0.826, 95% CI 0.535–1.262).
Interpretation: Cancer cases staged during the first year of the COVID-19 pandemic were not associated with higher stage; this likely reflects the prioritization of cancer procedures during times of reduced capacity. The impact of the pandemic period on staging procedures varied between cancer sites, which may reflect differences in clinical presentation, detection and treatment.
Link(s) to publication:
http://dx.doi.org/10.9778/cmajo.20220092
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Cipriano, L. E., 2023, "Evaluating the Impact and Potential Impact of Machine Learning on Medical Decision Making", Medical Decision Making, February 43(2): 147 - 149.
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Roseborough, A. D.; Saad, L.; Goodman, M.; Cipriano, L. E.; Hachinski, V. C.; Whitehead, S. N., 2023, "White matter hyperintensities and longitudinal cognitive decline in cognitively normal populations and across diagnostic categories: A meta‐analysis, systematic review, and recommendations for future study harmonization", Alzheimers & Dementia, January 19(1): 194 - 207.
Abstract: Introduction: The primary aim of this paper is to improve the clinical interpretation of white matter hyperintensities (WMHs) and provide an overarching summary of methodological approaches, allowing researchers to design future studies targeting current knowledge gaps. Methods:
A meta-analysis and systematic review was performed investigating associations between baseline WMHs and longitudinal cognitive outcomes in cognitively normal populations, and populations with mild cognitive impairment (MCI), Alzheimer's disease (AD), and stroke. Results: Baseline WMHs increase the risk of cognitive impairment and dementia across diagnostic categories and most consistently in MCI and post-stroke populations. Apolipoprotein E (APOE) genotype and domain-specific cognitive changes relating to strategic anatomical locations, such as frontal WMH and executive decline, represent important considerations. Meta-analysis reliability was assessed using multiple methods of estimation, and results suggest that heterogeneity in study design and reporting remains a significant barrier. Discussion: Recommendations and future directions for study of WMHs are provided to improve cross-study comparison and translation of research into consistent clinical interpretation.
Link(s) to publication:
http://dx.doi.org/10.1002/alz.12642
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Vilches, T. N.; Abdollahi, E.; Cipriano, L. E.; Haworth-Brockman, M.; Keynan, Y.; Sheffield, H.; Langley, J. M.; Moghadas, S. M., 2022, "Impact of non-pharmaceutical interventions and vaccination on COVID-19 outbreaks in Nunavut, Canada: a Canadian Immunization Research Network (CIRN) study", Bmc Public Health, December 22(1): 1042 - 1042.
Abstract: Background: Nunavut, the northernmost Arctic territory of Canada, experienced three community outbreaks of the coronavirus disease 2019 (COVID-19) from early November 2020 to mid-June 2021. We sought to investigate how non-pharmaceutical interventions (NPIs) and vaccination affected the course of these outbreaks.
Methods: We used an agent-based model of disease transmission to simulate COVID-19 outbreaks in Nunavut. The model encapsulated demographics and household structure of the population, the effect of NPIs, and daily number of vaccine doses administered. We fitted the model to inferred, back-calculated infections from incidence data reported from October 2020 to June 2021. We then compared the fit of the scenario based on case count data with several counterfactual scenarios without the effect of NPIs, without vaccination, and with a hypothetical accelerated vaccination program whereby 98% of the vaccine supply was administered to eligible individuals. Results: We found that, without a territory-wide lockdown during the first COVID-19 outbreak in November 2020, the peak of infections would have been 4.7 times higher with a total of 5,404 (95% CrI: 5,015—5,798) infections before the start of vaccination on January 6, 2021. Without effective NPIs, we estimated a total of 4,290 (95% CrI: 3,880—4,708) infections during the second outbreak under the pace of vaccination administered in Nunavut. In a hypothetical accelerated vaccine rollout, the total infections during the second Nunavut outbreak would have been 58% lower, to 1,812 (95% CrI: 1,593—2,039) infections. Vaccination was estimated to have the largest impact during the outbreak in April 2021, averting 15,196 (95% CrI: 14,798—15,591) infections if the disease had spread through Nunavut communities. Accelerated vaccination would have further reduced the total infections to 243 (95% CrI: 222—265) even in the absence of NPIs. Conclusions:
NPIs have been essential in mitigating pandemic outbreaks in this large, geographically distanced and remote territory. While vaccination has the greatest impact to prevent infection and severe outcomes, public health implementation of NPIs play an essential role in the short term before attaining high levels of immunity in the population.
Link(s) to publication:
http://dx.doi.org/10.1186/s12889-022-13432-1
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Tarride, J-E.; Cheung, M.; Hanna, T. P.; Cipriano, L. E.; Regier, D. A.; Hey, S. P.; Chan, K. K. W.; Mittmann, N., 2022, "Platform, Basket, and Umbrella Trial Designs: Issues Around Health Technology Assessment of Novel Therapeutics", Canadian Journal of Health Technologies, July 2(7)
Abstract: Advancements in genomic and precision medicine have changed the way oncology clinical trials are designed. Compared to the traditional single tumour-based trial, master protocols, which are often classified as basket, umbrella, or platform trials, conduct studies on multiple subgroups under a single overarching protocol.
This paper summarizes the discussion held during CADTH’s second webinar, which examined issues around health technology assessment of evidence generated using these trial designs.
In this workshop, several experts were invited to present on the clinical, health economic, patient value, and ethical aspects associated with these new study designs. The discussion section of this paper summarizes the major points raised by the presenters, as well as questions from the audience and answers from the presenters.
Link(s) to publication:
https://canjhealthtechnol.ca/index.php/cjht/article/view/nm0002
http://dx.doi.org/10.51731/cjht.2022.385
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Avan, A.; Hachinski, V.; Aamodt, A. H.; Alessi, C.; Ali, S.; Alladi, S.; Andersen, R.; Anderson, K. K.; Azarpazhooh, M. R.; Bassetti, C. L. A., et al., 2022, "Brain health: Key to health, productivity, and well-being", Alzheimer's and Dementia, July 18(7): 1396 - 1407.
Abstract: Brain health is essential for physical and mental health, social well-being, productivity, and creativity. Current neurological research focuses mainly on treating a diseased brain and preventing further deterioration rather than on developing and maintaining brain health. The pandemic has forced a shift toward virtual working environments that accelerated opportunities for transdisciplinary collaboration for fostering brain health among neurologists, psychiatrists, psychologists, neuro and socio-behavioral scientists, scholars in arts and humanities, policymakers, and citizens. This could shed light on the interconnectedness of physical, mental, environmental, and socioeconomic determinants of brain disease and health. We advocate making brain health the top priority worldwide, developing common measures and definitions to enhance research and policy, and finding the cause of the decline of incidence of stroke and dementia in some countries and then applying comprehensive customized cost-effective prevention solutions in actionable implementation units. Life cycle brain health offers the best single individual, communal, and global investment.
Link(s) to publication:
http://dx.doi.org/10.1002/alz.12478
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Fairley, M.; Cipriano, L. E.; Goldhaber-Fiebert, J. D., 2022, "Author Response to “Optimal Sample Size Calculation for Clinical Research under a Budget Constraint”", Medical Decision Making, May 42(4): 419 - 420.
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Cerasuolo, J. O.; Mandzia, J.; Cipriano, L. E.; Kapral, M. K.; Fang, J.; Hachinski, V.; Sposato, L. A., 2022, "Intravenous Thrombolysis After First-Ever Ischemic Stroke and Reduced Incident Dementia Rate", Stroke, April 53(4): 1170 - 1177.
Abstract: Background:
The use of intravenous thrombolysis is associated with improved clinical outcomes. Whether thrombolysis is associated with reduced incidence of poststroke dementia remains uncertain. We sought to estimate if the use of thrombolysis following first-ever ischemic stroke was associated with a reduced rate of incident dementia using a pragmatic observational design.
Methods:
We included first-ever ischemic stroke patients from the Ontario Stroke Registry who had not previously been diagnosed with dementia. The primary outcome was incident dementia ascertained by a validated diagnostic algorithm. We employed inverse probability of treatment-weighted Cox proportional hazard models to estimate the cause-specific hazard ratio for the association of thrombolysis and incident dementia at 1 and 5 years following stroke.
Results:
From July 2003 to March 2013, 7072 patients with ischemic stroke were included, 3276 (46.3%) were female and mean age was 71.0 (SD, 12.8) years. Overall, 38.2% of the cohort (n=2705) received thrombolysis, 77.2% (n=2087) of which was administered within 3 hours of stroke onset. In the first year following stroke, thrombolysis administration was associated with a 24% relative reduction in the rate of developing dementia (cause-specific hazard ratio, 0.76 [95% CI, 0.58–0.97]). This association remained significant at 5 years (cause-specific hazard ratio, 0.79 [95% CI, 0.66–0.91]) and at the end of follow-up (median 6.3 years; cause-specific hazard ratio, 0.79 [95% CI, 0.68–0.89]).
Conclusions:
Thrombolysis administration following first-ever ischemic stroke was independently associated with a reduced rate of dementia. Incident dementia should be considered as a relevant outcome when evaluating risk/benefit of thrombolysis in ischemic stroke patients.
Link(s) to publication:
https://doi.org/10.1161/STROKEAHA.121.034969
http://dx.doi.org/10.1161/STROKEAHA.121.034969
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Cipriano, L. E.; Haddara, W. M. R.; Zaric, G. S.; Enns, E. A., 2021, "Impact of University Re-opening on Total Community COVID-19 Burden", PLOS ONE, August 16(8): e0255782 - e0255782.
Abstract: Background: University students have higher average number of contacts than the general population. Students returning to university campuses may exacerbate COVID-19 dynamics in the surrounding community.
Methods: We developed a dynamic transmission model of COVID-19 in a mid-sized city currently experiencing a low infection rate. We evaluated the impact of 20,000 university students arriving on September 1 in terms of cumulative COVID-19 infections, time to peak infections, and the timing and peak level of critical care occupancy. We also considered how these impacts might be mitigated through screening interventions targeted to students.
Results: If arriving students reduce their contacts by 40% compared to pre-COVID levels, the total number of infections in the community increases by 115% (from 3,515 to 7,551), with 70% of the incremental infections occurring in the general population, and an incremental 19 COVID-19 deaths. Screening students every 5 days reduces the number of infections attributable to the student population by 42% and the total COVID-19 deaths by 8. One-time mass screening of students prevents fewer infections than 5-day screening, but is more efficient, requiring 196 tests needed to avert one infection instead of 237.
Interpretation: University students are highly inter-connected with the surrounding off-campus community. Screening targeted at this population provides significant public health benefits to the community through averted infections, critical care admissions, and COVID-19 deaths.
Link(s) to publication:
http://dx.doi.org/10.1371/journal.pone.0255782
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