Optimal COVID-19 quarantine and testing strategies

Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases

BACKGROUND

In settings with zero community transmission, any new SARS-CoV-2 outbreaks are likely to be the result of random incursions. The level of restrictions in place at the time of the incursion is likely to considerably affect possible outbreak trajectories, but the probability that a large outbreak eventuates is not known.

METHODS

We used an agent-based model to investigate the relationship between ongoing restrictions and behavioural factors, and the probability of an incursion causing an outbreak and the resulting growth rate. We applied our model to the state of Victoria, Australia, which has reached zero community transmission as of November 2020.

RESULTS

We found that a future incursion has a 45% probability of causing an outbreak (defined as a 7-day average of > 5 new cases per day within 60 days) if no restrictions were in place, decreasing to 23% with a mandatory masks policy, density restrictions on venues such as restaurants, and if employees worked from home where possible. A drop in community symptomatic testing rates was associated with up to a 10-percentage point increase in outbreak probability, highlighting the importance of maintaining high testing rates as part of a suppression strategy.

CONCLUSIONS

Because the chance of an incursion occurring is closely related to border controls, outbreak risk management strategies require an integrated approaching spanning border controls, ongoing restrictions, and plans for response. Each individual restriction or control strategy reduces the risk of an outbreak. They can be traded off against each other, but if too many are removed there is a danger of accumulating an unsafe level of risk. The outbreak probabilities estimated in this study are of particular relevance in assessing the downstream risks associated with increased international travel.

The economic value of quarantine is higher at lower case prevalence, with quarantine justified at lower risk of infection

Some infectious diseases, such as COVID-19 or the influenza pandemic of 1918, are so harmful that they justify broad-scale social distancing. Targeted quarantine can reduce the amount of indiscriminate social distancing needed to control transmission. Finding the optimal balance between targeted versus broad-scale policies can be operationalized by minimizing the total amount of social isolation needed to achieve a target reproductive number. Optimality is achieved by quarantining on the basis of a risk threshold that depends strongly on current disease prevalence, suggesting that very different disease control policies should be used at different times or places. Aggressive quarantine is warranted given low disease prevalence, while populations with a higher base rate of infection should rely more on social distancing by all. The total value of a quarantine policy rises as case counts fall, is relatively insensitive to vaccination unless the vaccinated are exempt from distancing policies, and is substantially increased by the availability of modestly more information about individual risk of infectiousness.

A literature review of the economics of COVID-19

The goal of this piece is to survey the developing and rapidly growing literature on the economic consequences of COVID-19 and the governmental responses, and to synthetize the insights emerging from a very large number of studies. This survey: (i) provides an overview of the data sets and the techniques employed to measure social distancing and COVID-19 cases and deaths; (ii) reviews the literature on the determinants of compliance with and the effectiveness of social distancing; (iii) mentions the macroeconomic and financial impacts including the modelling of plausible mechanisms; (iv) summarizes the literature on the socioeconomic consequences of COVID-19, focusing on those aspects related to labor, health, gender, discrimination, and the environment; and (v) summarizes the literature on public policy responses.

Reducing COVID-19 quarantine with SARS-CoV-2 testing: a simulation study

OBJECTIVE

To evaluate the effectiveness of SARS-CoV-2 testing on shortening the duration of quarantines for COVID-19 and to identify the most effective choices of testing schedules.

DESIGN

We performed extensive simulations to evaluate the performance of quarantine strategies when one or more SARS-CoV-2 tests were administered during the quarantine. Simulations were based on statistical models for the transmissibility and viral loads of SARS-CoV-2 infections and the sensitivities of available testing methods. Sensitivity analyses were performed to evaluate the impact of perturbations in model assumptions on the outcomes of optimal strategies.

RESULTS

We found that SARS-CoV-2 testing can effectively reduce the length of a quarantine without compromising safety. A single reverse transcription-PCR (RT-PCR) test performed before the end of quarantine can reduce quarantine duration to 10 days. Two tests can reduce the duration to 8 days, and three highly sensitive RT-PCR tests can justify a 6-day quarantine. More strategic testing schedules and longer quarantines are needed if tests are administered with less-sensitive RT-PCR tests or antigen tests. Shorter quarantines can be used for applications that tolerate a residual postquarantine transmission risk comparable to a 10-day quarantine.

CONCLUSIONS

Testing could substantially reduce the length of isolation, reducing the physical and mental stress caused by lengthy quarantines. With increasing capacity and lowered costs of SARS-CoV-2 tests, test-assisted quarantines could be safer and more cost-effective than 14-day quarantines and warrant more widespread use.

Reducing travel-related SARS-CoV-2 transmission with layered mitigation measures: symptom monitoring, quarantine, and testing

BACKGROUND

Balancing the control of SARS-CoV-2 transmission with the resumption of travel is a global priority. Current recommendations include mitigation measures before, during, and after travel. Pre- and post-travel strategies including symptom monitoring, antigen or nucleic acid amplification testing, and quarantine can be combined in multiple ways considering different trade-offs in feasibility, adherence, effectiveness, cost, and adverse consequences.

METHODS

We used a mathematical model to analyze the expected effectiveness of symptom monitoring, testing, and quarantine under different estimates of the infectious period, test-positivity relative to time of infection, and test sensitivity to reduce the risk of transmission from infected travelers during and after travel.

RESULTS

If infection occurs 0-7 days prior to travel, immediate isolation following symptom onset prior to or during travel reduces risk of transmission while traveling by 30-35%. Pre-departure testing can further reduce risk, with testing closer to the time of travel being optimal even if test sensitivity is lower than an earlier test. For example, testing on the day of departure can reduce risk while traveling by 44-72%. For transmission risk after travel with infection time up to 7 days prior to arrival at the destination, isolation based on symptom monitoring reduced introduction risk at the destination by 42-56%. A 14-day quarantine after arrival, without symptom monitoring or testing, can reduce post-travel risk by 96-100% on its own. However, a shorter quarantine of 7 days combined with symptom monitoring and a test on day 5-6 after arrival is also effective (97--100%) at reducing introduction risk and is less burdensome, which may improve adherence.

CONCLUSIONS

Quarantine is an effective measure to reduce SARS-CoV-2 transmission risk from travelers and can be enhanced by the addition of symptom monitoring and testing. Optimal test timing depends on the effectiveness of quarantine: with low adherence or no quarantine, optimal test timing is close to the time of arrival; with effective quarantine, testing a few days later optimizes sensitivity to detect those infected immediately before or while traveling. These measures can complement recommendations such as social distancing, using masks, and hand hygiene, to further reduce risk during and after travel.

Optimal test-assisted quarantine strategies for COVID-19

Objective

To evaluate the effectiveness of SARS-CoV-2 testing on shortening the duration of quarantines for COVID-19 and to identify the most effective choices of testing schedules.

Design

We performed extensive simulations to evaluate the performance of quarantine strategies when one or more SARS-CoV-2 tests were administered during the quarantine. Simulations were based on statistical models for the transmissibility and viral loads of SARS-CoV-2 infections and the sensitivities of available testing methods. Sensitivity analyses were performed to evaluate the impact of perturbations in model assumptions on the outcomes of optimal strategies.

Results

We found that SARS-CoV-2 testing can effectively reduce the length of a quarantine without compromising safety. A single RT-PCR test performed before the end of quarantine can reduce quarantine duration to 10 days. Two tests can reduce the duration to 8 days, and three highly sensitive RT-PCR tests can justify a 6-day quarantine. More strategic testing schedules and longer quarantines are needed if tests are administered with less sensitive RT-PCR tests or antigen tests. Shorter quarantines can be utilized for applications that tolerate a residual post-quarantine transmission risk comparable to a 10-day quarantine.

Conclusions

Testing could substantially reduce the length of isolation, reducing the physical and mental stress caused by lengthy quarantines. With increasing capacity and lowered costs of SARS-CoV-2 tests, test-assisted quarantines could be safer and more cost-effective than 14-day quarantines and warrant more widespread use.

RESEARCH IN CONTEXT

What is already known on this topic?: Recommendations for quarantining individuals who could have been infected with COVID-19 are based on limited evidence.Despite recent theoretical and case studies of test-assisted quarantines, there has been no substantive investigation to quantify the safety and efficacy of, nor an exhaustive search for, optimal test-assisted quarantine strategies.

What this study adds

Our simulations indicate that the 14-day quarantine approach is overly conservative and can be safely shortened if testing is performed.Our recommendations include testing schedules that could be immediately adopted and implemented as government and industry policies.

Role of the Funding Source

A major technology company asked that we perform simulations to understand the optimal strategy for managing personnel quarantining before forming cohorts of individuals who would work closely together. The funding entity did not influence the scope or output of the study but requested that we include antigen testing as a component of the quarantining process. Patrick Yu and Peter Matos are employees of Corporate Medical Advisors, and International S.O.S employs Julie McCashin. Other funding sources are research grants and did not influence the investigation.

Dynamic Public Health Surveillance to Track and Mitigate the US COVID-19 Epidemic: Longitudinal Trend Analysis Study

BACKGROUND

The emergence of SARS-CoV-2, the virus that causes COVID-19, has led to a global pandemic. The United States has been severely affected, accounting for the most COVID-19 cases and deaths worldwide. Without a coordinated national public health plan informed by surveillance with actionable metrics, the United States has been ineffective at preventing and mitigating the escalating COVID-19 pandemic. Existing surveillance has incomplete ascertainment and is limited by the use of standard surveillance metrics. Although many COVID-19 data sources track infection rates, informing prevention requires capturing the relevant dynamics of the pandemic.

OBJECTIVE

The aim of this study is to develop dynamic metrics for public health surveillance that can inform worldwide COVID-19 prevention efforts. Advanced surveillance techniques are essential to inform public health decision making and to identify where and when corrective action is required to prevent outbreaks.

METHODS

Using a longitudinal trend analysis study design, we extracted COVID-19 data from global public health registries. We used an empirical difference equation to measure daily case numbers for our use case in 50 US states and the District of Colombia as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R.

RESULTS

Examination of the United States and state data demonstrated that most US states are experiencing outbreaks as measured by these new metrics of speed, acceleration, jerk, and persistence. Larger US states have high COVID-19 caseloads as a function of population size, density, and deficits in adherence to public health guidelines early in the epidemic, and other states have alarming rates of speed, acceleration, jerk, and 7-day persistence in novel infections. North and South Dakota have had the highest rates of COVID-19 transmission combined with positive acceleration, jerk, and 7-day persistence. Wisconsin and Illinois also have alarming indicators and already lead the nation in daily new COVID-19 infections. As the United States enters its third wave of COVID-19, all 50 states and the District of Colombia have positive rates of speed between 7.58 (Hawaii) and 175.01 (North Dakota), and persistence, ranging from 4.44 (Vermont) to 195.35 (North Dakota) new infections per 100,000 people.

CONCLUSIONS

Standard surveillance techniques such as daily and cumulative infections and deaths are helpful but only provide a static view of what has already occurred in the pandemic and are less helpful in prevention. Public health policy that is informed by dynamic surveillance can shift the country from reacting to COVID-19 transmissions to being proactive and taking corrective action when indicators of speed, acceleration, jerk, and persistence remain positive week over week. Implicit within our dynamic surveillance is an early warning system that indicates when there is problematic growth in COVID-19 transmissions as well as signals when growth will become explosive without action. A public health approach that focuses on prevention can prevent major outbreaks in addition to endorsing effective public health policies. Moreover, subnational analyses on the dynamics of the pandemic allow us to zero in on where transmissions are increasing, meaning corrective action can be applied with precision in problematic areas. Dynamic public health surveillance can inform specific geographies where quarantines are necessary while preserving the economy in other US areas.