As the feared waves of the COVID-19 pandemic loom large, the development of effective containment measures is becoming more critical. A recent study by researchers at Virginia Tech and Central China Normal University published on the preprint server medRxiv* in October 2020 discusses the various interventions required and the level of control required, whether to flatten the curve or reduce the case number.
Meeting the Asymptomatic Infection Challenge
The study is based on the well-known Susceptible-Exposed-Infected-Recovered (SEIR) model, which the researchers adapted to include time-dependent and spatial fluctuations. Their aim was specifically to capture the changes that occur near the epidemic threshold and the prevalence when the outbreak is above the threshold. In this model, the researchers attempt to include social interactions with short-range and widespread contacts.
One major challenge in the current pandemic is the large proportion of asymptomatic infections. Since these people are not aware of their status, they mingle freely in society, allowing much greater viral transmission. Testing scarcity, reluctancy to get tested, and testing delays exacerbate this situation.
Any model must, therefore, concede the chances of missing many infections. All contacts with confirmed cases should be quarantined for effective containment to break the chain by isolating asymptomatic and unidentified carriers.
Frequent Testing and Proportion of Identified Cases
The current study explores the impact of a regimen where testing is conducted periodically and positives isolated, along with their contacts. A timely diagnosis is critical here. The primary sources of delays are due to the lag in test results and in quarantining (potentially) infectious people once they identified.
These lags and their effects on transmission are explored in this study. The researchers modeled regular testing to capture Identified Infectious Individuals, IIDs. They simulated testing from day 10 onward, such that all are screened at some point, and the IID are registered. They are then isolated, and their network of contacts traced and quarantined, with unavoidable delays.
They found that both the proportion of identified cases and the testing period are important factors in determining the containment measures' efficacy. The infection peak and the spread of the virus were dependent primarily on the former measure.
Heat map representation of pertinent outcomes: The heat map colors in figures (a), (b), and (c) respectively represent the peak in the curve of the fraction of infected individuals, the fraction of the total number of recovered individuals at the end of the outbreak, and the time (in days) at which the infection peaks in the population. The fraction of identified infectious individuals (IID) is varied along the horizontal axis and the testing period (TP in days) is varied along the vertical axis. IID takes values from the set {0.1,0.25,0.5,0.75,0.85,0.95}; TP takes values from the set {1,2,5,7,10} in units of days. In all mitigated curves, the delay between test and isolation (DT = 2 days), quarantine duration of nearest neighbors (Q = 14 days), and delay between isolating positively tested individuals and quarantining their direct contacts (DQ = 2 days) are held constant.
Increasing the IID
If the infection peak is to be reduced, and the overall proportion of infected people in the population, the IID must be increased. This can be achieved by either increasing the testing inventory or the standard of the testing protocol to identify more cases.
With an IID of <25%, the infection is not effectively controlled. When the IID is between 25% and 75%, the most significant changes in the peak height and the case number is observed. However, even with an IID of 95%, a third of the population is still infected.
Reducing Testing Period
Secondly, they found an orderly and significant reduction in the testing period brought down both of the above parameters. Still, even daily testing could not contain the outbreak fully if the IID was 50%. The outcome in this situation is that half of the population may be expected to become infected.
Effective Containment
Therefore, low IID and high TP are ineffective at containing the outbreak, which will peak on the 100th day. With IID >70% and daily testing, the peak is reached at day 50, and is not only smaller, but the total infected proportion is markedly reduced, indicating effective containment has occurred.
Recent studies have shown that a strategy of physical distancing along with contact tracing is capable of bringing the effective reproduction number below the threshold for an epidemic. The role of testing delays and poor test coverage in enabling viral transmission is significant. With prompt testing, they reported that spread could be blocked in 80% of cases, but if the test is delayed by five days, the benefit of preventing spread is only 5%.
The earlier researchers recommended using mobile-mediated contact tracing to minimize delays and prevent spread, provided more than 60% of the population is tested. Some claim that such test-and-trace programs hold the key to averting repeated lockdowns and other restrictions on mobility.
The effectiveness of testing is thus a “crucial parameter for containing infectious spreading.” Of course, this assumes perfect quarantine, since otherwise, the small amount of transmission that is inevitable even with the former case will not be effective in reducing spread.
The current study also promotes a quarantine of only 10 days and not two weeks, as the latter does not significantly improve the proportion of cases averted. Quarantining for only one week causes only a small increase in the infection peak and total number of cases, as does a delay between case isolation and contact quarantine.
The researchers also explored the nature of the alteration in the epidemic dynamics if spatial parameters are applied. Using a small-world network architecture, they concluded that systematic testing, with swift isolation and quarantine, is to be applied to capture the maximum fraction of IID. This improved mitigation strategy will be, they say, "the most effective way of mitigating epidemic outbreaks.”
Implications
The model shows that by increasing the frequency of testing, the negative impact of testing delays, and some loss of test reliability could be overcome at least in part. Thus, this should be prioritized for the best outcome. Less important factors include delays in isolating IID and quarantining contacts, as well as a shorter quarantine period, which is still longer than the incubation period. These can be pushed down the list of factors to be accounted for in framing the most effective containment strategy for this or future pandemics of similar infectious diseases.
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