  During the early months of the current COVID-19 pandemic, social-distancing
measures effectively slowed disease transmission in many countries in Europe
and Asia, but the same benefits have not been observed in some developing
countries such as Brazil. In part, this is due to a failure to organise
systematic testing campaigns at nationwide or even regional levels. To gain
effective control of the pandemic, decision-makers in developing countries,
particularly those with large populations, must overcome difficulties posed by
an unequal distribution of wealth combined with low daily testing capacities.
The economic infrastructure of the country, often concentrated in a few cities,
forces workers to travel from commuter cities and rural areas, which induces
strong nonlinear effects on disease transmission. In the present study, we
develop a smart testing strategy to identify geographic regions where COVID-19
testing could most effectively be deployed to limit further disease
transmission. The strategy uses readily available anonymised mobility and
demographic data integrated with intensive care unit (ICU) occupancy data and
city-specific social-distancing measures. Taking into account the heterogeneity
of ICU bed occupancy in differing regions and the stages of disease evolution,
we use a data-driven study of the Brazilian state of Sao Paulo as an example to
show that smart testing strategies can rapidly limit transmission while
reducing the need for social-distancing measures, thus returning life to a
so-called new normal, even when testing capacity is limited.
