Assessing the feasibility and effectiveness of household-pooled universal testing to control COVID-19 epidemics

Abstract

Outbreaks of SARS-CoV-2 are threatening the health care systems of several countries around the world. The initial control of SARS-CoV-2 epidemics relied on non-pharmaceutical interventions, such as social distancing, teleworking, mouth masks and contact tracing. However, as pre-symptomatic transmission remains an important driver of the epidemic, contact tracing efforts struggle to fully control SARS-CoV-2 epidemics. Therefore, in this work, we investigate to what extent the use of universal testing, i.e., an approach in which we screen the entire population, can be utilized to mitigate this epidemic. To this end, we rely on PCR test pooling of individuals that belong to the same households, to allow for a universal testing procedure that is feasible with the limited testing capacity. We evaluate two isolation strategies: on the one hand pool isolation, where we isolate all individuals that belong to a positive PCR test pool, and on the other hand individual isolation, where we determine which of the individuals that belong to the positive PCR pool are positive, through an additional testing step. We evaluate this universal testing approach in the STRIDE individual-based epidemiological model in the context of the Belgian COVID-19 epidemic. As the organisation of universal testing will be challenging, we discuss the different aspects related to sample extraction and PCR testing, to demonstrate the feasibility of universal testing when a decentralized testing approach is used. We show through simulation, that weekly universal testing is able to control the epidemic, even when many of the contact reductions are relieved. Finally, our model shows that the use of universal testing in combination with stringent contact reductions could be considered as a strategy to eradicate the virus.

Fig 1. We consider that an individual goes through different phases of infection/disease, which is represented by a SEIR-like state machine.

A susceptible individual (S) can become infected, given a time-dependent infection probability λ(t). This probability depends on the transmission potential of the virus and the social contact behaviour, which due to contact reduction policies is time-dependent. When infected, the individual becomes exposed (E). Once exposed (E), an individual goes through an incubation time of ε days, after which the individual becomes infectious prior to symptom development (I_p). A pre-symptomatic infected individual (I_p) will either become asymptomatic (I_a), symptomatic with symptoms (I_s), after a period of ρ days. When asymptomatic (I_a) the individual will remain infectious for ζ days after which he/she recovers (R). When severely symptomatic, the individual will be hospitalized with an age-dependent probability ϕ(a) or recover without the need for hospitalisation.

Fig 2. Trends (average and standard deviations) for all combinations of parameters 〈k, T_d〉, for FNR_PCR = 0.1.

Universal testing starts at the first of May (left panels) and the first of July (right panels), as indicated by the vertical dotted line, which also marks the end of the lock-down. In the top panels, we follow the pool isolation strategy, where we isolate all individuals that are part of an infected pool. In the bottom panels, we follow the individual isolation strategy, where we identify the infected individuals in positive pool.

Fig 3. Distribution of the number of infections for the experiments when the lock-down ends on the first of July, in different scenarios of compliance for testing and isolation.

We show results for the pool isolation strategy (top panels) and individual based isolation strategy (bottom panels). We show the number of infections at three different time points. i.e., 90 days (left panels), 180 days (middle panels) and 270 days (right panels) after the start of the universal testing procedure. These results consider a weekly universal testing procedure (i.e., k = 32 and T_d = 50000) and a FNR_PCR = 0.1. Each box represents a combination of test and isolation compliance.

Fig 4. Trends for different leisure contact reductions, when performing weekly universal testing.

We assume that universal testing starts (and lock-down ends) on the first of July, as marked by the vertical dotted line, and that FNR_PCR = 0.1. We consider both isolation strategies: pool isolation (left panel) and individual isolation (right panel). The curves show a line that depicts the average over the trajectories of the result aggregations and a shaded area that depicts the standard deviation.

Fig 5. Trends for different leisure contact reductions, when performing weekly universal testing, and importing 10 cases per day.

We assume that universal testing starts (and lock-down ends) on the first of July, as marked by the vertical dotted line, and that FNR_PCR = 0.1. We consider both isolation strategies: pool isolation (left panel) and individual isolation (right panel). The curves show a line that depicts the average over the trajectories of the result aggregations and a shaded area that depicts the standard deviation.

Fig 6. Trends for different leisure contact reductions, when performing weekly universal testing, and importing 50 cases per day.

We assume that universal testing starts (and lock-down ends) on the first of July, as marked by the vertical dotted line, and that FNR_PCR = 0.1. We consider both isolation strategies: pool isolation (left panel) and individual isolation (right panel). The curves show a line that depicts the average over the trajectories of the result aggregations and a shaded area that depicts the standard deviation.

Fig 7. Distribution of the number of infections for the experiments when the lock-down restrictions are continued.

We show different scenarios of compliance for testing and isolation. We show the number of infections at three different time points. i.e., 45 days (left panel), 90 days (middle panel) and 135 days (right panel) after the start of the universal testing procedure. These results consider a weekly universal testing procedure (i.e., k = 32 and T_d = 50000) and a FNR_PCR = 0.1, where the isolation strategy is individual isolation. Each box represents a combination of test and isolation compliance. Note that 135 days after the start of the universal testing procedure (not shown in this figure), the number of cases dropped to zero, for all the compliance scenarios.

Fig 8. Population size per household size and number of households per size: Belgian 2011 census and model population.

Numbers are expressed in million (M). Figure from Willem et al. [21].