scholarly journals Estimating SARS-CoV-2 infections from deaths, confirmed cases, tests, and random surveys

2021 ◽  
Vol 118 (31) ◽  
pp. e2103272118
Author(s):  
Nicholas J. Irons ◽  
Adrian E. Raftery
Keyword(s):  
Herd Immunity ◽  
The United States ◽  
Sir Model ◽  
Mitigation Strategies ◽  
Time Varying ◽  
Fatality Rate ◽  
Multiple Sources ◽  
Population Prevalence ◽  
Sample Testing ◽  
True Infection

There are multiple sources of data giving information about the number of SARS-CoV-2 infections in the population, but all have major drawbacks, including biases and delayed reporting. For example, the number of confirmed cases largely underestimates the number of infections, and deaths lag infections substantially, while test positivity rates tend to greatly overestimate prevalence. Representative random prevalence surveys, the only putatively unbiased source, are sparse in time and space, and the results can come with big delays. Reliable estimates of population prevalence are necessary for understanding the spread of the virus and the effectiveness of mitigation strategies. We develop a simple Bayesian framework to estimate viral prevalence by combining several of the main available data sources. It is based on a discrete-time Susceptible–Infected–Removed (SIR) model with time-varying reproductive parameter. Our model includes likelihood components that incorporate data on deaths due to the virus, confirmed cases, and the number of tests administered on each day. We anchor our inference with data from random-sample testing surveys in Indiana and Ohio. We use the results from these two states to calibrate the model on positive test counts and proceed to estimate the infection fatality rate and the number of new infections on each day in each state in the United States. We estimate the extent to which reported COVID cases have underestimated true infection counts, which was large, especially in the first months of the pandemic. We explore the implications of our results for progress toward herd immunity.

scholarly journals Cost Benefit Analysis of Limited Reopening Relative to a Herd Immunity Strategy or Shelter in Place for SARS-CoV-2 in the United States

2020 ◽  
Author(s):  
Robert B. Schonberger ◽  
Yair J. Listokin ◽  
Ian Ayres ◽  
Reza Yaesoubi ◽  
Zachary R. Shelley
Keyword(s):  
United States ◽  
Cost Effectiveness ◽  
Herd Immunity ◽  
The United States ◽  
Mitigation Strategies ◽  
United States Government ◽  
Effective Vaccine ◽  
Social Distancing ◽  
Mortality Effect ◽  
Life Years

ABSTRACTBackgroundFierce debate about the health and financial tradeoffs presented by different COVID-19 pandemic mitigation strategies highlights the need for rigorous quantitative evaluation of policy options.ObjectiveTo quantify the economic value of the costs and benefits of a policy of continued limited reopening with social distancing relative to alternative COVID-19 response strategies in the United States.DesignWe estimate the number and value of quality-adjusted life-years (QALY) gained from mortality averted, with a value of $125,000 per QALY, and compare these benefits to the associated costs in terms of plausible effects on US GDP under a policy of continued limited reopening with social distancing relative to a policy of full reopening toward herd immunity. Using the same QALY value assumptions, we further evaluate cost-effectiveness of a return to Shelter-in-Place relative to a policy of limited reopening.SettingUnited StatesMeasurementsQALY and cost as percent of GDP of limited reopening with continued social distancing relative to a strategy of full reopening aimed at achieving herd immunity; a limited reopening “budget” measured in the number of months before this strategy fails to demonstrate cost-effectiveness relative to a full reopening; a shelter-in-place “threshold” measured in the number of lives saved at which a month of sheltering in place demonstrates cost effectiveness relative to the limited reopening strategy.ResultsQALY benefits from mortality averted by continued social distancing and limited reopening relative to a policy of full reopening exceed projected GDP costs if an effective vaccine or therapeutic can be developed within 11.1 months from late May 2020. White House vaccine projections fall within this date, supporting a partial reopening strategy. One month of shelter-in-place restrictions provides QALY benefits from averted mortality that exceed the associated GDP costs relative to limited reopening if the restrictions prevent at least 154,586 additional COVID-19 deaths over the course of the pandemic. Current models of disease progression suggest that limited reopening will not cause this many additional deaths, again supporting a limited reopening strategy.LimitationLimited horizon of COVID-19 mortality projections; infection fatality ratio stable across strategies, ignoring both the potential for ICU overload to increase mortality and the deployment of partially effective therapeutics to decrease mortality; effect on GDP modeled as constant within a given phase of the pandemic; accounts for age and sex distribution of QALYs, but not effect of comorbidities; only considers impact from QALY lost due to mortality and from changes in GDP, excluding numerous other considerations, such as non-fatal COVID-19 morbidity, reduced quality of life caused by prolonged social distancing, or educational regression associated with prolonged school closures and restrictions.ConclusionsA limited reopening to achieve partial mitigation of COVID-19 is cost effective relative to a full reopening if an effective therapeutic or vaccine can be deployed within 11.1 months of late May 2020. One additional month of shelter-in-place restrictions should only be imposed if it saves at least 154,586 lives per month before the development of an effective therapeutic or vaccine relative to limited reopening.FundingThis work was supported in part by grant K01AI119603 from the National Institute of Allergy and Infectious Diseases (NIAID). This work does not necessarily represent the opinions of the NIAID, the NIH, or the United States Government.

scholarly journals National interest may require distributing COVID-19 vaccines to other countries

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tiziano Rotesi ◽  
Paolo Pin ◽  
Maria Cucciniello ◽  
Amyn A. Malik ◽  
Elliott E. Paintsil ◽  
...  
Keyword(s):  
United States ◽  
Quantitative Analysis ◽  
Vaccination Coverage ◽  
Herd Immunity ◽  
The United States ◽  
Sir Model ◽  
Sharp Reduction ◽  
Trade Offs ◽  
Self Interest ◽  
The Us

AbstractAs immunization campaigns are accelerating, understanding how to distribute the scarce doses of vaccines is of paramount importance and a quantitative analysis of the trade-offs involved in domestic-only versus cooperative distribution is still missing. In this study we use a network Susceptible-Infected-Removed (SIR) model to show circumstances under which it is in a country’s self-interest to ensure other countries can obtain COVID-19 vaccines rather than focusing only on vaccination of their own residents. In particular, we focus our analysis on the United States and estimate the internal burden of COVID-19 disease under different scenarios about vaccine cooperation. We show that in scenarios in which the US has reached the threshold for domestic herd immunity, the US may find it optimal to donate doses to other countries with lower vaccination coverage, as this would allow for a sharp reduction in the inflow of infected individuals from abroad.

scholarly journals Age Adaptive Social Distancing: A Nonlinear Engineering Strategy to Contrast COVID-19 via Precision and Personalized Mitigation

2020 ◽  
Author(s):  
Carlo Vittorio Cannistraci
Keyword(s):  
Active Surveillance ◽  
Scientific Evidence ◽  
Herd Immunity ◽  
Mitigation Strategies ◽  
Contact Tracing ◽  
Fatality Rate ◽  
Social Distancing ◽  
Contagious Diseases ◽  
Engineering Strategy

COVID-19 severity is heterogeneously distributed over age strata, but current mitigation strategies are homogeneously applied to all population. Social-distancing and stay-home are effective conservative approaches but lack economical sustainability on long term. Conversely, herd-immunity is a nonrestrictive strategy which can cost remarkable number of human lives and can melt the healthcare system down.Here I propose an Age Adaptive Social Distancing (AASD) engineering strategy to mitigate COVID-19 outbreak. AASD is based on the scientific evidence that the fatality rate grows nonlinearly with age, hence also the containing strategy should adapt nonlinearly. Essentially, AASD suggests that ‘silent spreaders’ (age 0-39) should avoid/minimize direct and indirect contacts with individuals in ‘dangerous zone’ (age 40+). The rationale is: 0-19 should follow parents strategy, healthy 20-39 (low fatality rate) might conduct screened life under active surveillance, to sustain economy and acquire rational immunity; 40-59 should respect social distancing (waiting a therapy); 60+ should stay at home (waiting a vaccine). This might save human lives, reduce healthcare demand and improve economical sustainability. The final take-home message is that future studies should design precision and personalized strategies for specific contagious diseases that integrate different social constrains, active surveillance and contact tracing.

Estimating Unreported COVID-19 Cases in the United States Based on Time-Varying SIR Model

2020 ◽  
Author(s):  
Lingbo Liu ◽  
Shuming Bao ◽  
Tao Hu ◽  
Hao Wu ◽  
Zhenghong Peng ◽  
...  
Keyword(s):  
United States ◽  
The United States ◽  
Sir Model ◽  
Time Varying

scholarly journals Modelling infectious diseases with herd immunity in a randomly mixed population

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kian Boon Law ◽  
Kalaiarasu M. Peariasamy ◽  
Hishamshah Mohd Ibrahim ◽  
Noor Hisham Abdullah
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Transmission Rate ◽  
Herd Immunity ◽  
The United States ◽  
Sir Model ◽  
Mixed Population ◽  
Transmission Dynamics ◽  
Vaccination Rates ◽  
Reduced Risk

AbstractThe conventional susceptible-infectious-recovered (SIR) model tends to magnify the transmission dynamics of infectious diseases, and thus the estimated total infections and immunized population may be higher than the threshold required for infection control and eradication. The study developed a new SIR framework that allows the transmission rate of infectious diseases to decline along with the reduced risk of contact infection to overcome the limitations of the conventional SIR model. Two new SIR models were formulated to mimic the declining transmission rate of infectious diseases at different stages of transmission. Model A utilized the declining transmission rate along with the reduced risk of contact infection following infection, while Model B incorporated the declining transmission rate following recovery. Both new models and the conventional SIR model were then used to simulate an infectious disease with a basic reproduction number (r0) of 3.0 and a herd immunity threshold (HIT) of 0.667 with and without vaccination. Outcomes of simulations were assessed at the time when the total immunized population reached the level predicted by the HIT, and at the end of simulations. Further, all three models were used to simulate the transmission dynamics of seasonal influenza in the United States and disease burdens were projected and compared with estimates from the Centers for Disease Control and Prevention. For the simulated infectious disease, in the initial phase of the outbreak, all three models performed expectedly when the sizes of infectious and recovered populations were relatively small. As the infectious population increased, the conventional SIR model appeared to overestimate the infections even when the HIT was achieved in all scenarios with and without vaccination. For the same scenario, Model A appeared to attain the level predicted by the HIT and in comparison, Model B projected the infectious disease to be controlled at the level predicted by the HIT only at high vaccination rates. For infectious diseases with high r0, and at low vaccination rates, the level at which the infectious disease was controlled cannot be accurately predicted by the current theorem. Transmission dynamics of infectious diseases with herd immunity can be accurately modelled by allowing the transmission rate of infectious diseases to decline along with the reduction of contact infection risk after recovery or vaccination. Model B provides a credible framework for modelling infectious diseases with herd immunity in a randomly mixed population.

scholarly journals Time fused coefficient SIR model with application to COVID-19 epidemic in the United States

2021 ◽  
pp. 1-15
Author(s):  
Hou-Cheng Yang ◽  
Yishu Xue ◽  
Yuqing Pan ◽  
Qingyang Liu ◽  
Guanyu Hu
Keyword(s):  
United States ◽  
The United States ◽  
Sir Model

scholarly journals 307 A systems approach to understanding biosecurity decision-making

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 43-43
Author(s):  
Scott C Merrill ◽  
Christopher Koliba ◽  
Gabriela Bucini ◽  
Eric Clark ◽  
Luke Trinity ◽  
...  
Keyword(s):  
Decision Making ◽  
Negative Impact ◽  
Risk Mitigation ◽  
African Swine Fever Virus ◽  
The United States ◽  
Mitigation Strategies ◽  
Communication Strategy ◽  
Livestock Industry ◽  
Diarrhea Virus ◽  
Operational Level

Abstract Disease and its consequences result in social and economic impacts to the US animal livestock industry, ranging from losses in human capital to economic costs in excess of a billion dollars annually. Impacts would dramatically escalate if a devastating disease like Foot and Mouth Disease or African Swine Fever virus were to emerge in the United States. Investing in preventative biosecurity can reduce the likelihood of disease incursions and their negative impact on our livestock industry, yet uncertainty persists with regards to developing an effective biosecurity structure and culture. Here we show the implications of human behavior and decision making for biosecurity effectiveness, from the operational level to the owner/managerial level and finally to the systems level. For example, adjustments to risk messaging strategies could double worker compliance with biosecurity practices at the operational level. The improvement of our risk communication strategy may increase willingness to invest in biosecurity. Furthermore, the adaptation of policies could nudge behavior so that we observe a short disease outbreak followed by a quick eradication instead of a pandemic. Our research shows how the emergence of now-endemic diseases, such as Porcine Epidemic Diarrhea virus, cannot be adequately modeled without the use of a human behavioral component. Focusing solely on any one sector or level of the livestock system is not sufficient to predict emergent disease patterns and their social and economic impact on livestock industries. These results provide insight toward developing more effective risk mitigation strategies and ways to nudge behavior toward more disease resilient systems.

scholarly journals Time-varying evidence of predictability of financial stress in the United States over a century: The role of inequality

2021 ◽  
Vol 57 ◽  
pp. 87-92
Author(s):  
Mehmet Balcilar ◽  
Edmond Berisha ◽  
Rangan Gupta ◽  
Christian Pierdzioch
Keyword(s):  
United States ◽  
Financial Stress ◽  
The United States ◽  
Time Varying

scholarly journals U.S. Economic Uncertainty Shocks and China’s Economic Activities: A Time-Varying Perspective

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110326
Author(s):  
Lin Liu
Keyword(s):  
Global Financial Crisis ◽  
The United States ◽  
Time Varying ◽  
Economic Uncertainty ◽  
Transient Effects ◽  
Economic Activities ◽  
Common Shocks ◽  
Uncertainty Shocks ◽  
Intensive Intervention ◽  
The Global Financial Crisis

This paper presents new empirical evidence concerning the time-varying responses of China’s macroeconomy to U.S. economic uncertainty shocks through a novel TVP-VAR model. The results robustly reveal that a rise in U.S. economic uncertainty would exert sizable, persistent, and significant detrimental effects on China’s gross domestic product (GDP), price level, and short-term interest rate during the period when common shocks take place, such as the global financial crisis around 2008, whereas small and transient effects in the tranquil times. Therefore, China should diversify its international linkages and gradually reduce the dependence on the United States into a certain range to shield the domestic economy, as well as improve the independence of monetary policy. Furthermore, to withstand unfavorable external shocks, China should be prudent on greater opening-up and carry out more intensive intervention when common shocks hit the world economy. Finally, investors should be alert to the potential detrimental impact of U.S. economic uncertainty on Chinese assets’ fundamentals.

scholarly journals The Effect of Vaccination Rates on the Infection of COVID-19 under the Vaccination Rate below the Herd Immunity Threshold

2021 ◽  
Vol 18 (14) ◽  
pp. 7491
Author(s):  
Yi-Tui Chen
Keyword(s):  
Infection Rate ◽  
Herd Immunity ◽  
The United States ◽  
Vaccination Rate ◽  
Infection Rates ◽  
Vaccination Rates ◽  
The United Kingdom ◽  
The World ◽  
Almost All ◽  
The Impact

Although vaccination is carried out worldwide, the vaccination rate varies greatly. As of 24 May 2021, in some countries, the proportion of the population fully vaccinated against COVID-19 has exceeded 50%, but in many countries, this proportion is still very low, less than 1%. This article aims to explore the impact of vaccination on the spread of the COVID-19 pandemic. As the herd immunity of almost all countries in the world has not been reached, several countries were selected as sample cases by employing the following criteria: more than 60 vaccine doses per 100 people and a population of more than one million people. In the end, a total of eight countries/regions were selected, including Israel, the UAE, Chile, the United Kingdom, the United States, Hungary, and Qatar. The results find that vaccination has a major impact on reducing infection rates in all countries. However, the infection rate after vaccination showed two trends. One is an inverted U-shaped trend, and the other is an L-shaped trend. For those countries with an inverted U-shaped trend, the infection rate begins to decline when the vaccination rate reaches 1.46–50.91 doses per 100 people.

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