SearcharxivSearch

arXiv subjects

Marcelo Olivares

Publications and source records attributed to Marcelo Olivares.

2 recordsLinked to original sources

Replacing quarantine of COVID-19 contacts with periodic testing is also effective in mitigating the risk of transmission

The quarantine of identified close contacts has been vital to reducing transmission rates and averting secondary infection risk before symptom onset and by asymptomatic cases. The effectiveness of this contact tracing strategy to mitigate transmission is sensitive to the adherence to quarantines, which may be lower for longer quarantine periods or in vaccinated populations (where perceptions of risk are reduced). This study develops a simulation model to evaluate contact tracing strategies based on the sequential testing of identified contacts after exposure as an alternative to quarantines, in which contacts are isolated only after confirmation by a positive test. The analysis considers different number and types of tests (PCR and lateral flow antigen tests (LFA)) to identify the cost-effective testing policies that minimize the expected infecting days post-exposure considering different levels of testing capacity. This analysis suggests that even a limited number of tests can be effective at reducing secondary infection risk: two LFA tests (with optimal timing) avert infectiousness at a level that is comparable to 14-day quarantine with 80-90% adherence, or equivalently, 7-9 day quarantine with full adherence (depending on the sensitivity of the LFA test). Adding a third test (PCR or LFA) reaches the efficiency of a 14-day quarantine with 90-100% adherence. These results are robust to the exposure dates of the contact, test sensitivity of LFA and alternative models of viral load evolution, which suggests that simple testing rules can be effective for improving contact tracing in settings where strict quarantine adherence is difficult to implement.

q-bio.PE

The Social Divide of Social Distancing: Shelter-in-Place Behavior in Santiago during the Covid-19 Pandemic

Voluntary shelter-in-place directives and lockdowns are the main non-pharmaceutical interventions that governments around the globe have used to contain the Covid-19 pandemic. In this paper we study the impact of such interventions in the capital of a developing country, Santiago, Chile, that exhibits large socioeconomic inequality. A distinctive feature of our study is that we use granular geolocated mobile phone data to construct mobility measures that capture (1) shelter-in-place behavior, and (2) trips within the city to destinations with potentially different risk profiles. Using panel data linear regression models we first show that the impact of social distancing measures and lockdowns on mobility is highly heterogeneous and dependent on socioeconomic levels. More specifically, our estimates indicate that while zones of high socioeconomic levels can exhibit reductions in mobility of around 50\% to 90\% depending on the specific mobility metric used, these reductions are only 20\% to 50\% for lower-income communities. The large reductions in higher-income communities are significantly driven by voluntary shelter-in-place behavior. Second, also using panel data methods we show that our mobility measures are important predictors of infections: roughly, a 10\% increase in mobility correlates with a 5\% increase in the rate of infection. Our results suggest that mobility is an important factor explaining differences in infections rates between high and low incomes areas within the city. Further, they confirm the challenges of reducing mobility in lower-income communities, where people generate their income from their daily work. To be effective, shelter-in-place restrictions in municipalities of low socioeconomic levels may need to be complemented by other supporting measures that enable their inhabitants to increase compliance.

physics.soc-ph