To stop COVID-19, test everyone, repeatedly
This is a preprint, and has not been peer-reviewed.
Prof. Jussi Taipale*† and prof. Sten Linnarsson†
† Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden. *Applied Tumor Genomics Research Program, Faculty of Medicine, University of Helsinki, Finland and Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom
Correspondence to S.L. (linnarssonsten@gmail.com)
March 19, 2020
We propose an additional intervention that would contribute to the control of the COVID-19 pandemic and facilitate reopening of society, based on: (1) testing every individual (2) repeatedly, and (3) self-quarantine of infected individuals. By identification and isolation of the majority of infectious individuals, including the estimated 86% who are asymptomatic or undocumented, the reproduction number R0 of SARS-CoV-2 would be reduced well below 1.0, and the epidemic would collapse. This testing regime would be additive to other interventions, and allow individuals who have respiratory symptoms due to other causes to return to work, but would have to be maintained until a vaccine becomes available. Unlike sampling-based tests, population-scale testing does not need to be very accurate: false negative rates up to 15% could be tolerated if 80% comply with testing, and false positives can be almost arbitrarily high when a high fraction of the population is already effectively quarantined. Current qPCR-based methods could be scaled up and multiplexed, or a field or home test kit could be used that can be mass-produced, distributed and used without professional support. Current reagent costs for tests are in the range of a dollar or less, but low cost is not necessary given the very high cost of alternative mitigation strategies. Ideally, both viral RNA and antibodies would be tested, to identify both active and past infections. All technologies to build such kits, and to produce them in the scale required to test the entire worlds’ population exist already, but separately. Integrating them, scaling up production, and implementing the testing regime all present considerable challenges, which are however not insurmountable given the exceptionally high societal costs of the present and future epidemics.
The ongoing pandemic spread of SARS-CoV-2 is the cause of widespread and accelerating outbreaks of the respiratory syndrome COVID-19. As of March 19, 2020, a total of 209,839 persons have been confirmed to be infected, and 8,778 have died[1]. Currently, the virus is present on all continents, growing rapidly in Europe and the USA, and is a major threat to world order. Detailed models of the epidemic dynamics of SARS-CoV-2 are available that take into account population structure, and can provide estimates of the magnitude and duration of the peak of infection[2]. However, very broadly speaking, an outbreak of a novel virus in a naïve population can have only two outcomes. As long as the reproduction number R0 remains greater than 1, the virus spreads rapidly until most people have been infected (Fig. 1A), creating a temporary surge of infected individuals. If, using pharmacological or social interventions, R0 can be reduced below 1, then the epidemic collapses (Fig. 1B), and most people remain uninfected (but still susceptible). Because of the exponential nature of epidemics, the outcomes are nearly binary, since even when R0 exceeds 1 by only a small amount the disease spreads at an accelerating pace, whereas as soon as R0 falls just below 1 it rapidly collapses. These two outcomes correspond to two distinct strategies for epidemic control, suppression and mitigation, close variants of which are currently attempted by several Asian countries (with different political systems) and Western democracies, respectively.
In the mitigation model, the goal is to reduce R as much as possible but not below 1.0, hoping to end up with a population that is largely immune, without overwhelming the healthcare system in the process (as in Fig. 1A, but attempting to flatten the temporary surge of infected individuals). This could (but is not guaranteed to) lead to “herd immunity”, which would limit spread in future epidemics caused by variants of the same virus. However, exponential processes are notoriously difficult to control, particularly if their current state and the effect of policy changes are uncertain. The choice is stark: allowing the disease to spread to a large fraction of a population, however slowly, may protect the economy, but greatly increases the total number of infected people. This causes, in our opinion, unacceptable loss of life. Furthermore, given the difficulties in controlling exponential processes using limited information, even strongly enforced mitigation strategy runs the risk of overwhelming the health care system and significantly increasing the mortality rate due to the failure to treat every patient optimally (primarily due to the lack of intensive care capacity and sufficient numbers of ventilators). If the healthcare system is overwhelmed, patients must be triaged as in wartime, potentially for extended periods of time.
Notably, both strategies are unstable: the mitigation model might first wreck the health-care system and then (as the public demands harsher controls when mortality rises) also wreck the economy. The suppression model might first wreck the economy and then (as controls are eased and the virus re-emerges) also wreck the healthcare system. Both approaches are likely to result in a large fraction of the population being effectively quarantined as if they carried the virus for extended periods of time.
The fact that a large fraction of the global economy hangs in the balance, may provide an opportunity for unorthodox solutions. COVID-19 is likely to cause a contraction in the global economy by several percentage points, and may even trigger a major global depression. A 5% contraction corresponds to a loss of $4 trillion in global economic activity, and hence any intervention that costs less than a trillion dollars is likely to be cost effective in the first year. Applying the same reasoning to a small country like Sweden, any intervention that costs less than 100 billion SEK ($10 bn, i.e. $1,000 per person) is likely to be cost effective. By comparison, the Swedish government has already announced measures to shore up the economy at a potential cost of more than 300 billion SEK.
We start with the observation that suppressing the disease is far preferable to allowing it to spread, as long as suppression can be achieved at a reasonable societal cost. We further observe that in an isolated outbreak, not yet pandemic, testing, contact tracing and quarantine (TTQ) is a very effective means of suppression. Diligently breaking the chains of transmission effectively reduces the reproduction number close to zero, and the contagion collapses. The same strategy can also be successfully applied regionally, e.g. in a city, given enough resources to test broadly, trace contacts, and isolate infected individuals. This is also the strategy recommended by the WHO, and anecdotally has been reported to be effective in the Italian city of Vó in the middle of the larger pandemic[3]. However, it is slow and labor-intensive and therefore does not easily scale to whole populations. Trained staff and specialized equipment are needed for sampling, testing and contact tracing. And you have to be quick: once the epidemic runs away, the exponential dynamics ensure that it is near-impossible to catch up with it. It has been proposed that modern surveillance technology could help (e.g. tracking cell phones), but the tests still require visiting a nurse, and the tracked contacts must still be located and tested. The TTQ approach also requires very high quality clinical-grade tests, as false positives consume resources of the healthcare system, and false negatives allow the disease to spread.
Here, we propose a radically simpler strategy: just test everyone, repeatedly. If everyone is tested there is no need to trace contacts, because they will also have been tested. All that is needed is for all infected individuals to self-quarantine. If everyone is tested, and everyone who is infected self-quarantines, then the epidemic will collapse no matter how many people are already infected. It is a strategy that can be applied at any point during the epidemic, using mass distribution (e.g. regular mail), and even without the need to collect the results of the testing. In fact, the tests required do not even have to be properly “diagnostic”: in the simplest case, they do not lead to any medical decision, but simply the decision to self-quarantine. This requirement is not materially different to the present condition of many uninfected people in Western countries (including the authors). This is an important feature, as it relaxes the demands on the quality of the test. The test can tolerate many false positives, because the worst that can happen is that someone self-quarantines for two weeks when they didn’t have to. False negatives are also acceptable, however the product of compliance (c, the fraction of all people who take the test and act on it) and the true positive rate p must be large enough to catch most infected individuals. Specifically, to suppress transmission, the weighted average of the natural reproduction number R0 and the reproduction number Rq in self-quarantine must be less than one:
i.e.
For coronavirus, it has been estimated[4] that R0 = 2.4 and uncertain data from quarantine in Wuhan[5] suggests that Rq = 0.3. Therefore, our proposed test must satisfy:
This means that, in the case that no other interventions are taken, at least two thirds of all COVID-19 cases must be correctly identified with a test. This can be achieved, for example, with 80% compliance and 85% true positive rate, which is not an unreasonable goal in such exceptional circumstances. It is important to note also that the false negative rate can be reduced by self-contact tracing and considering contacts’ test results using simple rules that are easily understood. Furthermore, as other interventions, including social distancing, are additive, the demands for the test decrease further when these interventions are combined (Fig. 1C, showing the required compliance rate as a function of the strength of other interventions, assuming a fixed true positive rate of 85%). Furthermore, everyone does not need to be tested at the same time, provided that enough separation exist between the populations screened. For example, it is possible to run the screen as a sweep across a country, optimally with measures to prevent individuals from moving in the opposite direction across the screening frontline.
In a country that successfully exits an outbreak with the virus suppressed and a with a small fraction of individuals immune, new outbreaks will inevitably happen and must be suppressed by renewed TTQ and/or lockdowns. Our proposed population-scale testing would be a far cheaper and less intrusive means to prevent reemergence, and a rapid test would also allow maintaining regional quarantines. In a different situation, where a country exits an outbreak with the majority of the population having been infected and possibly immune, population-scale testing would be an inexpensive insurance against reemergence of the virus once herd immunity is lost or the virus mutates.
Building a field-deployable test is clearly feasible, using current technology. It could be based on detection of antibodies to the virus. However, as it takes time for antibodies to build, the antibody-test cannot detect cases early. A single test also does not discriminate between current and past infection. This requires that the test is combined with an RNA test, or performed twice over a period of time. Despite these drawbacks, an antibody test will clearly be part of the solution, as it can detect immune individuals that can return to work. However, deploying it at a population scale will be difficult, as the current approach requires blood samples, which decreases compliance and makes self-testing more difficult.
A test can also be based on viral proteins (technically more difficult but possible), or viral RNA, like the current state-of-the-art diagnostic tests. However, detecting viral RNA in the field at population-scale is difficult to achieve using the same design that is used for the diagnostic tests. Current diagnostic tests for SARS-CoV-2 are qRT-PCR assays that require (1) nasopharyngeal swab collected by a trained nurse, (2) sample collection in viral transport media, (3) RNA purification, (4) reverse transcription and quantitative PCR. The test is highly accurate, and the total cost is around $200. Such highly accurate testing is critical for accurate diagnosis of cases in a hospital setting. However, due to the specialized staff and equipment involved, and centralized testing facilities, such tests are difficult to scale above thousands of assays in each location. A distributed system of sample collection and testing could, however, conceivably be used to scale qRT-PCR to population levels, particularly when using a regional sweeping approach to limit the number of simultaneous tests needed.
Alternatively, we envisage supplementing the current testing regime with a mass-produced home test kit that could be used by anyone, result in a simple easily-understood readout, and be performed without specialized equipment. The test should be as easy to use as a pregnancy test, to ensure maximal compliance. Boxes of e.g. 50 tests would be mass-mailed to all citizens, and a national information campaign would encourage everyone to test themselves weekly. Compliance could be increased by both rewards and penalties, and potentially enforced by adding a serial number to each test that needs to be reported together with the test result to collect the rewards. The test result can be open in such a way that the result is clear to everyone. It can also be designed so that it maintains privacy. Here, the result (e.g. resulting color, number of bars that are visible) needs to be reported together with the serial number to a central facility to get the answer and/or the cash reward. The open and private approaches can also be combined, to design a test that is open and contains an encoded part that needs to be reported to collect a reward. Such designs may complicate the approach, but would allow the healthcare system to obtain data that would facilitate monitoring of the outbreak and large-scale contact tracing. The cash rewards could also be contingent on being regularly tested. Anyone found positive would be compelled to self-quarantine, possibly under monetary or criminal sanctions, or using additional rewards for compliance. Provided that the test is sufficiently quick, testing could be performed in workplaces, or even in checkpoints exiting areas with high infection rate that are currently under lockdown.
In an infected individual, viral RNA is present at reasonably high levels in nasopharyngeal swabs, throat swabs, sputum, and stool for up to two weeks[6], with the greatest amounts in sputum and stool. Sputum might be the ideal source for a home test kit, given the ease of sampling. Several technologies exist for highly sensitive, isothermal detection of RNA in 10–30 minutes. For example, an isothermal and colorimetric test has been described[7], based on RT-LAMP technology, which could serve as a baseline. The test consists of a reaction master mix with a pH indicator and a thermostable strand-displacing polymerase with reverse transcriptase activity (e.g. Bst polymerase). A specially designed set of primers amplifies viral RNA to high concentrations, releasing H+ as a by-product. A positive test is indicated when the pH-sensitive dye changes color from pink to yellow. This test has several desirable properties: it is isothermal; the readout is binary and can be achieved by simple observation; and it can start from crude samples[8]. However, there are also several drawbacks: the test is liquid and contains enzymes, which complicates distribution; it requires incubation at 65°C (ideally, but >50°C should work and could possibly be achieved using running hot tap water); and it requires adding a controlled amount of sputum. Many other technologies also have the potential to detect viral RNA rapidly and isothermally; these include rolling circle replication, and in vitro viral replication assays. Furthermore, in the future, a test based on sequencing that covers many acute infections could also be used to eliminate a large number of infectious diseases simultaneously. This would have significant benefits to humanity.
A challenge to the scientific community
Our proposed strategy stands a good chance of working, provided that several challenges can be overcome quickly:
- A test must be developed that can be manufactured at population scale (billions of tests) and distributed. The test need not be very cheap ($10 would be acceptable initially, or even possibly $100), but needs to be simple enough to be used by anyone. Ideally, a piece of paper that you spit on, with a control stripe and a stripe that changes color in minutes if you have the virus.
- The costs and benefits of the strategy must be modelled in sufficient detail to convince key stakeholders of its value. This includes particularly epidemiologists and political leaders in decision-making positions.
- The proposed strategy must be rolled out with an information campaign that explains the importance of taking the test and acting on the result.
We believe that a population-scale strategy has the potential to allow most individuals to return to work, and to buy precious time for a vaccine or an effective drug to be developed. A field test would also synergize with drug treatment, as many antivirals act more effectively when they are given at an early stage of the infection. Furthermore, development of field-applicable tests needed for rapid population-level screening will have great benefits in combating epidemics in countries with less developed healthcare systems, and would also help in responding to future epidemics, or variants of the current one. The costs of mobilization of scientific and industrial resources for rapid development of such a test are considerable; however, in our opinion, they are still orders of magnitude lower than the costs of the current suppression and mitigation strategies. As there is little overlap with other industrial mobilization efforts, such as scaling up current testing regime, building of ventilators or developing drugs or a vaccine, the increased effort for the development of tests would also have very limited opportunity cost.
Our proposed strategy rests on two key observations that have not been widely appreciated. First, there is a direct relationship between the reproduction number of a virus, and the required accuracy for a population-scale test to achieve epidemic control. Second, that population-scale self-testing and self-quarantine can be an effective (and additive) epidemic intervention in itself.
[2] https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf and https://neherlab.org/covid19/
[4] https://science.sciencemag.org/content/sci/early/2020/03/13/science.abb3221.full.pdf
[5] https://doi.org/10.1101/2020.03.03.20030593
[6] https://doi.org/10.1101/2020.03.05.20030502
[7] https://www.medrxiv.org/content/10.1101/2020.02.20.20025874v1 and https://www.medrxiv.org/content/10.1101/2020.02.26.20028373v1
[8] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6418238/pdf/41598_2019_Article_40960.pdf
