The limits of human mobility traces to predict the spread of COVID-19 (preprint)

Mobile phone data have been widely used to model the spread of COVID-19, however, quantifying and comparing their predictive value across different settings is challenging. Their quality is affected by various factors and their relationship with epidemiological indicators varies over time. Here we adopt a model-free approach based on transfer entropy to quantify the relationship between mobile phone-derived mobility metrics and COVID-19 cases and deaths in more than 200 European subnational regions. We found that past knowledge of mobility does not provide statistically significant information on COVID-19 cases or deaths in most of the regions. In the remaining ones, measures of contact rates were often more informative than movements in predicting the spread of the disease, while the most predictive metrics between mid-range and short-range movements depended on the region considered. We finally identify geographic and demographic factors, such as users' coverage and commuting patterns, that can help determine the best metric for predicting disease incidence in a particular location. Our approach provides epidemiologists and public health officials with a general framework to evaluate the usefulness of human mobility data in responding to epidemics.

Association of close-range contact patterns with SARS-CoV-2: a household transmission study (preprint)

Background Households are an important location for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, especially during periods where travel and work was restricted to essential services. We aimed to assess the association of close-range contact patterns with SARS-CoV-2 transmission. Methods We deployed proximity sensors for two weeks to measure face-to-face interactions between household members after SARS-CoV-2 was identified in the household, in South Africa, 2020 - 2021. We calculated duration, frequency and average duration of close range proximity events with SARS-CoV-2 index cases. We assessed the association of contact parameters with SARS-CoV-2 transmission using mixed effects logistic regression accounting for index and household member characteristics. Results We included 340 individuals (88 SARS-CoV-2 index cases and 252 household members). On multivariable analysis, factors associated with SARS-CoV-2 acquisition were index cases with minimum Ct value <30 (aOR 10.2 95%CI 1.4-77.4) vs >35, contacts aged 13-17 years (aOR 7.7 95%CI 1.0-58.2) vs <5 years and female contacts (aOR 2.3 95%CI 1.1-4.8). No contact parameters were associated with acquisition (aOR 1.0 95%CI 1.0-1.0) for all three of duration, frequency and average duration. Conclusion We did not find an association between close-range proximity events and SARS-CoV-2 household transmission. It may be that droplet-mediated transmission during close-proximity contacts play a smaller role than airborne transmission of SARS-CoV-2 in the household, due to high contact rates in households or study limitations. Funding Wellcome Trust (Grant number 221003/Z/20/Z) in collaboration with the Foreign, Commonwealth and Development Office, United Kingdom.

Socioeconomic determinants of mobility responses during the first wave of COVID-19 in Italy: from provinces to neighbourhoods (preprint)

As the second wave of SARS-CoV-2 infections is surging across Europe, it is crucial to identify the drivers of mobility responses to mitigation efforts during different restriction regimes, for planning interventions that are both economically and socially sustainable while effective in controlling the outbreak. Here, using anonymous and privacy enhanced cell phone data from Italy, we investigate the determinants of spatial variations of reductions in mobility and co-location in response to the adoption and the lift of restrictions, considering both provinces and city neighbourhoods. In large urban areas, our analysis uncovers the desertification of historic city centers, which persisted after the end of the lockdown. At the province level, the local structure of the labour market mainly explained the variations in mobility responses, together with other demographic factors, such as populations age and sex composition. In the future, targeted interventions should take into account how the ability to comply with restrictions varies across geographic areas and socio-demographic groups.

COVID-19 outbreak response: a first assessment of mobility changes in Italy following national lockdown (preprint)

Italy is currently experiencing the largest COVID-19 outbreak in Europe so far, with more than 100,000 confirmed cases. Following the identification of the first infections, on February 21, 2020, national authorities have put in place an increasing number of restrictions aimed at containing the outbreak and delaying the epidemic peak. Since March 12, the whole country is under lockdown. Here we provide the first quantitative assessment of the impact of such measures on the mobility and the spatial proximity of Italians, through the analysis of a large-scale dataset on de-identified, geo-located smartphone users. With respect to pre-outbreak averages, we estimate a reduction of 50% of the total trips between Italian provinces, following the lockdown. In the same week, the average users' radius of gyration has declined by about 50% and the average degree of the users' proximity network has dropped by 47% at national level.