Containing pandemics through targeted testing of households

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 larger households. For an outbreak with reproductive number R = 1.5, we find that weekly testing of just the 15% largest households is capable of forcing R below unity. For the case of R = 1.2, our results suggest that the same testing regime with the largest 20% of households in an urban area is as effective as imposing strict lockdown measures and will curb the outbreak in a few weeks. Pooled household testing appears to be a powerful alternative to more invasive measures as a localized early response to contain epidemic outbreaks.