scholarly journals Threshold analyses on rates of testing, transmission, and contact for COVID-19 control in a university setting

2020 ◽  
Author(s):  
Xinmeng Zhao ◽  
Hanisha Anand Tatapudi ◽  
George Corey ◽  
Chaitra Gopalappa
Keyword(s):  
Transmission Rate ◽  
Full Range ◽  
Face Mask ◽  
Contact Rate ◽  
Contact Rates ◽  
Time Of Infection ◽  
Four Levels ◽  
The Impact ◽  
Mass Test ◽  
Rate Threshold

We simulated epidemic projections of a potential COVID-19 outbreak in a university population of 38,000 persons, under varying combinations of mass test rate (0% to 10%), contact trace and test rate (0% to 50%), transmission rate (probability of transmission per contact per day), and contact rate (number of contacts per person per day). We simulated four levels of transmission rate, 14% (average baseline), 8% (average for face mask use), 5.4% (average for 3ft distancing), and 2.5% (average for 6ft distancing and face mask use), interpolating results to the full range to understand the impact of uncertainty in effectiveness, feasibility, and adherence of face mask use and physical distancing. We evaluated contact rates between 1 and 25, to identify the threshold that, if exceeded, could lead to several deaths. When transmission rate was 8%, for trace and test at 50%, the contact rate threshold was 8. However, any time delays in trace, test, and isolation quickly raised the number of deaths. Keeping contact rate to 3 or below was more robust to testing delays, keeping deaths below 1 up to a delay of 5 days from the time of infection to diagnosis and isolation. For a contact rate of 3, the number of trace and tests peaked to about 70 per day and relaxed to 25 with the addition of 10% mass test. When transmission rate was 5.4%, for trace and test at 50%, the contact rate threshold was 10. However, keeping contact rate to 4 or below was more robust to delays in testing, keeping deaths below 1 up to a delay of 6 days from the time of infection to diagnosis and isolation. For contact rate of 4, the number of trace and tests peaked at 50 per day and relaxed to 10 per day with the addition of 10% mass test. Threshold estimates can help develop on-campus scheduling and indoor-spacing plans in conjunction with plans for asymptomatic testing for COVID-19. Combination thresholds should be selected specific to the setting based on an assessment of the feasibility and resource 48 availability for testing and quarantine.

scholarly journals Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
James D. Munday ◽  
Christopher I. Jarvis ◽  
Amy Gimma ◽  
Kerry L. M. Wong ◽  
Kevin van Zandvoort ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Transmission Rate ◽  
Transmission Risk ◽  
Individual Level ◽  
Face To Face ◽  
School Settings ◽  
Contact Rates ◽  
Contact Survey ◽  
The Uk ◽  
The Impact

Abstract Background Schools were closed in England on 4 January 2021 as part of increased national restrictions to curb transmission of SARS-CoV-2. The UK government reopened schools on 8 March. Although there was evidence of lower individual-level transmission risk amongst children compared to adults, the combined effects of this with increased contact rates in school settings and the resulting impact on the overall transmission rate in the population were not clear. Methods We measured social contacts of > 5000 participants weekly from March 2020, including periods when schools were both open and closed, amongst other restrictions. We combined these data with estimates of the susceptibility and infectiousness of children compared with adults to estimate the impact of reopening schools on the reproduction number. Results Our analysis indicates that reopening all schools under the same measures as previous periods that combined lockdown with face-to-face schooling would be likely to increase the reproduction number substantially. Assuming a baseline of 0.8, we estimated a likely increase to between 1.0 and 1.5 with the reopening of all schools or to between 0.9 and 1.2 reopening primary or secondary schools alone. Conclusion Our results suggest that reopening schools would likely halt the fall in cases observed between January and March 2021 and would risk a return to rising infections, but these estimates relied heavily on the latest estimates or reproduction number and the validity of the susceptibility and infectiousness profiles we used at the time of reopening.

scholarly journals Contact surveys reveal heterogeneities in age-group contributions to SARS-CoV-2 dynamics in the United States

2021 ◽  
Author(s):  
Taylor Chin ◽  
Dennis M. Feehan ◽  
Caroline O. Buckee ◽  
Ayesha S. Mahmud
Keyword(s):  
United States ◽  
Age Groups ◽  
The United States ◽  
Contact Rate ◽  
Age Group ◽  
Contact Rates ◽  
Contact Patterns ◽  
Age Structured ◽  
The Impact ◽  
Over Time

SARS-CoV-2 is spread primarily through person-to-person contacts. Quantifying population contact rates is important for understanding the impact of physical distancing policies and for modeling COVID-19, but contact patterns have changed substantially over time due to shifting policies and behaviors. There are surprisingly few empirical estimates of age-structured contact rates in the United States both before and throughout the COVID-19 pandemic that capture these changes. Here, we use data from six waves of the Berkeley Interpersonal Contact Survey (BICS), which collected detailed contact data between March 22, 2020 and February 15, 2021 across six metropolitan designated market areas (DMA) in the United States. Contact rates were low across all six DMAs at the start of the pandemic. We find steady increases in the mean and median number of contacts across these localities over time, as well as a greater proportion of respondents reporting a high number of contacts. We also find that young adults between ages 18 and 34 reported more contacts on average compared to other age groups. The 65 and older age group consistently reported low levels of contact throughout the study period. To understand the impact of these changing contact patterns, we simulate COVID-19 dynamics in each DMA using an age-structured mechanistic model. We compare results from models that use BICS contact rate estimates versus commonly used alternative contact rate sources. We find that simulations parameterized with BICS estimates give insight into time-varying changes in relative incidence by age group that are not captured in the absence of these frequently updated estimates. We also find that simulation results based on BICS estimates closely match observed data on the age distribution of cases, and changes in these distributions over time. Together these findings highlight the role of different age groups in driving and sustaining SARS-CoV-2 transmission in the U.S. We also show the utility of repeated contact surveys in revealing heterogeneities in the epidemiology of COVID-19 across localities in the United States.

scholarly journals Threshold analyses on combinations of testing, population size, and vaccine coverage for COVID-19 control in a university setting

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255864
Author(s):  
Xinmeng Zhao ◽  
Hanisha Tatapudi ◽  
George Corey ◽  
Chaitra Gopalappa
Keyword(s):  
Population Size ◽  
Vaccine Coverage ◽  
Disease Outbreaks ◽  
Face Mask ◽  
The United States ◽  
Contact Rate ◽  
Transmission Rates ◽  
Contact Rates ◽  
Residential University ◽  
Full Population

We simulated epidemic projections of a potential COVID-19 outbreak in a residential university population in the United States under varying combinations of asymptomatic tests (5% to 33% per day), transmission rates (2.5% to 14%), and contact rates (1 to 25), to identify the contact rate threshold that, if exceeded, would lead to exponential growth in infections. Using this, we extracted contact rate thresholds among non-essential workers, population size thresholds in the absence of vaccines, and vaccine coverage thresholds. We further stream-lined our analyses to transmission rates of 5 to 8%, to correspond to the reported levels of face-mask-use/physical-distancing during the 2020 pandemic. Our results suggest that, in the absence of vaccines, testing alone without reducing population size would not be sufficient to control an outbreak. If the population size is lowered to 34% (or 44%) of the actual population size to maintain contact rates at 4 (or 7) among non-essential workers, mass tests at 25% (or 33%) per day would help control an outbreak. With the availability of vaccines, the campus can be kept at full population provided at least 95% are vaccinated. If vaccines are partially available such that the coverage is lower than 95%, keeping at full population would require asymptomatic testing, either mass tests at 25% per day if vaccine coverage is at 63–79%, or mass tests at 33% per day if vaccine coverage is at 53–68%. If vaccine coverage is below 53%, to control an outbreak, in addition to mass tests at 33% per day, it would also require lowering the population size to 90%, 75%, and 60%, if vaccine coverage is at 38–53%, 23–38%, and below 23%, respectively. Threshold estimates from this study, interpolated over the range of transmission rates, can collectively help inform campus level preparedness plans for adoption of face mask/physical-distancing, testing, remote instructions, and personnel scheduling, during non-availability or partial-availability of vaccines, in the event of SARS-Cov2-type disease outbreaks.

scholarly journals To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic

2020 ◽  
Author(s):  
Steffen E. Eikenberry ◽  
Marina Mancuso ◽  
Enahoro Iboi ◽  
Tin Phan ◽  
Keenan Eikenberry ◽  
...  
Keyword(s):  
New York ◽  
General Public ◽  
Transmission Rate ◽  
New York State ◽  
Face Mask ◽  
Epidemic Dynamics ◽  
Highly Nonlinear ◽  
Community Transmission ◽  
Using Data ◽  
The Impact

AbstractFace mask use by the general public for limiting the spread of the COVID-19 pandemic is controversial, though increasingly recommended, and the potential of this intervention is not well understood. We develop a compartmental model for assessing the community-wide impact of mask use by the general, asymptomatic public, a portion of which may be asymptomatically infectious. Model simulations, using data relevant to COVID-19 dynamics in the US states of New York and Washington, suggest that broad adoption of even relatively ineffective face masks may meaningfully reduce community transmission of COVID-19 and decrease peak hospitalizations and deaths. Moreover, mask use decreases the effective transmission rate in nearly linear proportion to the product of mask effectiveness (as a fraction of potentially infectious contacts blocked) and coverage rate (as a fraction of the general population), while the impact on epidemiologic outcomes (death, hospitalizations) is highly nonlinear, indicating masks could synergize with other non-pharmaceutical measures. Notably, masks are found to be useful with respect to both preventing illness in healthy persons and preventing asymptomatic transmission. Hypothetical mask adoption scenarios, for Washington and New York state, suggest that immediate near universal (80%) adoption of moderately (50%) effective masks could prevent on the order of 17–45% of projected deaths over two months in New York, while decreasing the peak daily death rate by 34–58%, absent other changes in epidemic dynamics. Even very weak masks (20% effective) can still be useful if the underlying transmission rate is relatively low or decreasing: In Washington, where baseline transmission is much less intense, 80% adoption of such masks could reduce mortality by 24–65% (and peak deaths 15–69%), compared to 2–9% mortality reduction in New York (peak death reduction 9–18%). Our results suggest use of face masks by the general public is potentially of high value in curtailing community transmission and the burden of the pandemic. The community-wide benefits are likely to be greatest when face masks are used in conjunction with other non-pharmaceutical practices (such as social-distancing), and when adoption is nearly universal (nation-wide) and compliance is high.

scholarly journals Edge-based compartmental modelling for infectious disease spread

2011 ◽  
Vol 9 (70) ◽  
pp. 890-906 ◽  
Author(s):  
Joel C. Miller ◽  
Anja C. Slim ◽  
Erik M. Volz
Keyword(s):  
Infectious Disease ◽  
Mass Action ◽  
Disease Spread ◽  
Contact Rate ◽  
Compartmental Modelling ◽  
Contact Rates ◽  
Differential Equation Models ◽  
Social Heterogeneity ◽  
Edge Based ◽  
The Impact

The primary tool for predicting infectious disease spread and intervention effectiveness is the mass action susceptible–infected–recovered model of Kermack & McKendrick. Its usefulness derives largely from its conceptual and mathematical simplicity; however, it incorrectly assumes that all individuals have the same contact rate and partnerships are fleeting. In this study, we introduce edge-based compartmental modelling , a technique eliminating these assumptions. We derive simple ordinary differential equation models capturing social heterogeneity (heterogeneous contact rates) while explicitly considering the impact of partnership duration. We introduce a graphical interpretation allowing for easy derivation and communication of the model and focus on applying the technique under different assumptions about how contact rates are distributed and how long partnerships last.

Unfunded Public Employee Health Care Benefits and GASB No. 45

2007 ◽  
Vol 21 (3) ◽  
pp. 245-263 ◽  
Author(s):  
Elizabeth K. Keating ◽  
Eric S. Berman
Keyword(s):  
Health Care ◽  
Financial Reporting ◽  
Full Range ◽  
Financial Reports ◽  
Employment Benefits ◽  
Care Plans ◽  
Advantages And Disadvantages ◽  
Government Accounting ◽  
The Government ◽  
The Impact

The Government Accounting Standards Board (GASB) recently released Statement No. 45, Accounting and Financial Reporting by Employers for Post-Employment Benefits Other Than Pensions and its companion Statement No. 43 for pooled stand-alone health care plans, which will profoundly affect American governmental finance. The goal of this article is to encourage governments to consider carefully a full range of options in funding and restructuring other post-employment benefits (OPEB). This article will review Statement No. 45's potential impact on governments and review existing disclosures in financial reports as well as bond offering statements. The article will discuss the statement's impact on budgets and governmental operations, including collective bargaining. Funding options under Statement No. 45 will be detailed, including the advantages and disadvantages of irrevocable trusts and OPEB bonds. The article will also discuss the impact of Medicare Part D subsidies received by governments, as well as the bond rating implications of policy decisions surrounding OPEB. As the largest government entities are just now implementing GASB Statement No. 45, estimates of the magnitude of unfunded OPEB liabilities are limited as are the strategies likely to be adopted to cover these obligations. This article offers a summary of the unfunded OPEB liabilities reported by states and major cities and suggests some measures for assessing the ability of these entities to address these costs.

scholarly journals Estimating asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan: a mathematical modeling study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xi Huo ◽  
Jing Chen ◽  
Shigui Ruan
Keyword(s):  
Disease Transmission ◽  
Large Scale ◽  
Transmission Rate ◽  
Control Strategies ◽  
Herd Immunity ◽  
Antibody Prevalence ◽  
Screening Process ◽  
Vaccination Programs ◽  
Prevalence Level ◽  
The Impact

Abstract Background The COVID-19 outbreak in Wuhan started in December 2019 and was under control by the end of March 2020 with a total of 50,006 confirmed cases by the implementation of a series of nonpharmaceutical interventions (NPIs) including unprecedented lockdown of the city. This study analyzes the complete outbreak data from Wuhan, assesses the impact of these public health interventions, and estimates the asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan. Methods By taking different stages of the outbreak into account, we developed a time-dependent compartmental model to describe the dynamics of disease transmission and case detection and reporting. Model coefficients were parameterized by using the reported cases and following key events and escalated control strategies. Then the model was used to calibrate the complete outbreak data by using the Monte Carlo Markov Chain (MCMC) method. Finally we used the model to estimate asymptomatic and undetected cases and approximate the overall antibody prevalence level. Results We found that the transmission rate between Jan 24 and Feb 1, 2020, was twice as large as that before the lockdown on Jan 23 and 67.6% (95% CI [0.584,0.759]) of detectable infections occurred during this period. Based on the reported estimates that around 20% of infections were asymptomatic and their transmission ability was about 70% of symptomatic ones, we estimated that there were about 14,448 asymptomatic and undetected cases (95% CI [12,364,23,254]), which yields an estimate of a total of 64,454 infected cases (95% CI [62,370,73,260]), and the overall antibody prevalence level in the population of Wuhan was 0.745% (95% CI [0.693%,0.814%]) by March 31, 2020. Conclusions We conclude that the control of the COVID-19 outbreak in Wuhan was achieved via the enforcement of a combination of multiple NPIs: the lockdown on Jan 23, the stay-at-home order on Feb 2, the massive isolation of all symptomatic individuals via newly constructed special shelter hospitals on Feb 6, and the large scale screening process on Feb 18. Our results indicate that the population in Wuhan is far away from establishing herd immunity and provide insights for other affected countries and regions in designing control strategies and planing vaccination programs.

scholarly journals Fractional SIR-Model for Estimating Transmission Dynamics of COVID-19 in India

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 86-100
Author(s):  
Nita H. Shah ◽  
Ankush H. Suthar ◽  
Ekta N. Jayswal ◽  
Ankit Sikarwar
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Sir Model ◽  
Time Dependent ◽  
Contact Rate ◽  
Distribution Maps ◽  
Fundamental Parameters ◽  
Different Order ◽  
The Basic Reproduction Number

In this article, a time-dependent susceptible-infected-recovered (SIR) model is constructed to investigate the transmission rate of COVID-19 in various regions of India. The model included the fundamental parameters on which the transmission rate of the infection is dependent, like the population density, contact rate, recovery rate, and intensity of the infection in the respective region. Looking at the great diversity in different geographic locations in India, we determined to calculate the basic reproduction number for all Indian districts based on the COVID-19 data till 7 July 2020. By preparing district-wise spatial distribution maps with the help of ArcGIS 10.2, the model was employed to show the effect of complete lockdown on the transmission rate of the COVID-19 infection in Indian districts. Moreover, with the model's transformation to the fractional ordered dynamical system, we found that the nature of the proposed SIR model is different for the different order of the systems. The sensitivity analysis of the basic reproduction number is done graphically which forecasts the change in the transmission rate of COVID-19 infection with change in different parameters. In the numerical simulation section, oscillations and variations in the model compartments are shown for two different situations, with and without lockdown.

scholarly journals Impact of Face Masks on 6-Minute Walk Test in Healthy Volunteers

2021 ◽  
Vol 11 (1) ◽  
pp. 204589402098843
Author(s):  
Kevin M. Swiatek ◽  
Charnetta Lester ◽  
Nicole Ng ◽  
Saahil Golia ◽  
Janet Pinson ◽  
...  
Keyword(s):  
Healthy Volunteers ◽  
Face Mask ◽  
Walk Test ◽  
Six Minute Walk Test ◽  
Significant Difference ◽  
6 Minute Walk Test ◽  
The Impact ◽  
Minute Walk

Our objective was to establish the impact of wearing a face mask on the outcome of six-minute walk test in healthy volunteers. In a study of 20 healthy volunteers who each completed two 6MWTs, one with a mask and one without, there was no difference in distance walked. However, there was a significant difference in perception of dyspnea between the two groups.

scholarly journals Impact of public health interventions to curb SARS-CoV-2 spread assessed by an evidence-educated Delphi panel and tailored SEIR model

2021 ◽  
Author(s):  
Bernd Brüggenjürgen ◽  
Hans-Peter Stricker ◽  
Lilian Krist ◽  
Miriam Ortiz ◽  
Thomas Reinhold ◽  
...  
Keyword(s):  
Public Health ◽  
Transmission Rate ◽  
Latency Period ◽  
Policy Decision ◽  
Sensitivity Analyses ◽  
Delphi Panel ◽  
Time Step ◽  
Seir Model ◽  
Health Policy Decision ◽  
The Impact

Abstract Aim To use a Delphi-panel-based assessment of the effectiveness of different non-pharmaceutical interventions (NPI) in order to retrospectively approximate and to prospectively predict the SARS-CoV-2 pandemic progression via a SEIR model (susceptible, exposed, infectious, removed). Methods We applied an evidence-educated Delphi-panel approach to elicit the impact of NPIs on the SARS-CoV-2 transmission rate R0 in Germany. Effectiveness was defined as the product of efficacy and compliance. A discrete, deterministic SEIR model with time step of 1 day, a latency period of 1.8 days, duration of infectiousness of 5 days, and a share of the total population of 15% assumed to be protected by immunity was developed in order to estimate the impact of selected NPI measures on the course of the pandemic. The model was populated with the Delphi-panel results and varied in sensitivity analyses. Results Efficacy and compliance estimates for the three most effective NPIs were as follows: test and isolate 49% (efficacy)/78% (compliance), keeping distance 42%/74%, personal protection masks (cloth masks or other face masks) 33%/79%. Applying all NPI effectiveness estimates to the SEIR model resulted in a valid replication of reported occurrence of the German SARS-CoV-2 pandemic. A combination of four NPIs at consented compliance rates might curb the CoViD-19 pandemic. Conclusion Employing an evidence-educated Delphi-panel approach can support SARS-CoV-2 modelling. Future curbing scenarios require a combination of NPIs. A Delphi-panel-based NPI assessment and modelling might support public health policy decision making by informing sequence and number of needed public health measures.

Sign in / Sign up

Export Citation Format

Share Document