Containing pandemics through targeted testing of households

Voigt, A.; Martyushenko, N.; Karlsen, E.; Hall, M.; Nyhamar, K.; Omholt, S. W.; Almaas, E.

While invasive social distancing measures have proven efficient to control the spread of pandemics in the absence of a vaccine, they carry vast societal costs. Guided by the finding that large households function as hubs for the propagation of COVID-19, we developed a data-driven individual-based epidemiological network-model to assess the intervention efficiency of targeted testing of large households. For an outbreak with reproductive numbers R between 1.1 and 2, our results suggest that the intervention effect of weekly pooled testing of the 10% largest households in an urban area is on par with the effect of imposing strict lockdown measures. By testing no more than 20% of households every 4 days, the model predicts that one can reduce R from 1.6 to below unity over a few weeks, lowering the prevalence by 75%. Pooled household testing appears to be a powerful alternative to more invasive measures as a localized early response to contain epidemic outbreaks.