Household visitation during the COVID-19 pandemic

The COVID-19 pandemic has posed novel risks related to the indoor mixing of individuals from different households and challenged policymakers to adequately regulate this behaviour. While in many cases household visits are necessary for the purpose of social care, they have been linked to broadening community transmission of the virus. In this study we propose a novel, privacy-preserving framework for the measurement of household visitation at national and regional scales, making use of passively collected mobility data. We implement this approach in England from January 2020 to May 2021. The measures expose significant spatial and temporal variation in household visitation patterns, impacted by both national and regional lockdown policies, and the rollout of the vaccination programme. The findings point to complex social processes unfolding differently over space and time, likely informed by variations in policy adherence, vaccine relaxation, and regional interventions

Estimating the impact of COVID-19 vaccine inequities: a modeling study.

Access to COVID-19 vaccines on the global scale has been drastically hindered by structural socio-economic disparities. Here, we develop a data-driven, age-stratified epidemic model to evaluate the effects of COVID-19 vaccine inequities in twenty lower middle and low income countries (LMIC) selected from all WHO regions. We investigate and quantify the potential effects of higher or earlier doses availability. In doing so, we focus on the crucial initial months of vaccine distribution and administration, exploring counterfactual scenarios where we assume the same per capita daily vaccination rate reported in selected high income countries. We estimate that more than 50% of deaths (min-max range: [54-94%]) that occurred in the analyzed countries could have been averted. We further consider scenarios where LMIC had similarly early access to vaccine doses as high income countries. Even without increasing the number of doses, we estimate an important fraction of deaths (min-max range: [6-50%]) could have been averted. In the absence of the availability of high-income countries, the model suggests that additional non-pharmaceutical interventions inducing a considerable relative decrease of transmissibility (min-max range: [15-70%]) would have been required to offset the lack of vaccines. Overall, our results quantify the negative impacts of vaccine inequities and underscore the need for intensified global efforts devoted to provide faster access to vaccine programs in low and lower-middle-income countries

Tracking the State and Behavior of People in Response to COVID-1 19 Through the Fusion of Multiple Longitudinal Data Streams

The changing nature of the COVID-19 pandemic has highlighted the importance of comprehensively considering its impacts and considering changes over time. Most COVID-19 related research addresses narrowly focused research questions and is therefore limited in addressing the complexities created by the interrelated impacts of the pandemic. Such research generally makes use of only one of either 1) actively collected data such as surveys, or 2) passively collected data. While a few studies make use of both actively and passively collected data, only one other study collects it longitudinally. Here we describe a rich panel dataset of active and passive data from U.S. residents collected between August 2020 and July 2021. Active data includes a repeated survey measuring travel behavior, compliance with COVID-19 mandates, physical health, economic well-being, vaccination status, and other factors. Passively collected data consists of all locations visited by study participants, taken from smartphone GPS data. We also closely tracked COVID-19 policies across counties of residence throughout the study period. Such a dataset allows important research questions to be answered; for example, to determine the factors underlying the heterogeneous behavioral responses to COVID-19 restrictions imposed by local governments. Better information about such responses is critical to our ability to understand the societal and economic impacts of this and future pandemics. The development of this data infrastructure can also help researchers explore new frontiers in behavioral science. The article explains how this approach fills gaps in COVID-19 related data collection; describes the study design and data collection procedures; presents key demographic characteristics of study participants; and shows how fusing different data streams helps uncover behavioral insights

COVID-19 policy analysis: labour structure dictates lockdown mobility behaviour

Countries and cities around the world have resorted to unprecedented mobility restrictions to combat COVID-19 transmission. Here we exploit a natural experiment whereby Colombian cities implemented varied lockdown policies based on ID number and gender to analyse the impact of these policies on urban mobility. Using mobile phone data, we find that the restrictiveness of cities' mobility quotas (the share of residents allowed out daily according to policy advice) does not correlate with mobility reduction. Instead, we find that larger, wealthier cities with more formalized and complex industrial structure experienced greater reductions in mobility. Within cities, wealthier residents are more likely to reduce mobility, and commuters are especially more likely to stay at home when their work is located in wealthy or commercially/industrially formalized neighbourhoods. Hence, our results indicate that cities' employment characteristics and work-from-home capabilities are the primary determinants of mobility reduction. This finding underscores the need for mitigations aimed at lower income/informal workers, and sheds light on critical dependencies between socio-economic classes in Latin American cities

Weaving Equity into Infrastructure Resilience Research and Practice: A Decadal Review and Future Directions

After about a decade of research in this domain, what is missing is a systematic overview of the research agenda across different infrastructures and hazards. It is now imperative to evaluate the current progress and gaps. This paper presents a systematic review of equity literature on disrupted infrastructure during a natural hazard event. Following a systematic review protocol, we collected, screened, and evaluated almost 3,000 studies. Our analysis focuses on the intersection within the dimensions of the eight-dimensional assessment framework that distinguishes focus of the study, methodological approaches, and equity dimensions (distributional-demographic, distributional-spatial, procedural, and capacity equity). To conceptualize the intersection of the different dimensions of equity, we refer to pathways, which identify how equity is constructed, analyzed, and used. Significant findings show that (1) the interest in equity in infrastructure resilience has exponentially increased, (2) the majority of studies are in the US and by extension in the global north, (3) most data collection use descriptive and open-data and none of the international studies use location-intelligence data. The most prominent equity conceptualization is distributional equity, such as the disproportionate impacts to vulnerable populations and spaces. The most common pathways to study equity connect distributional equity to the infrastructure's power, water, and transportation in response to flooding and hurricane storms. Other equity concepts or pathways, such as connections of equity to decision-making and building household capacity, remain understudied. Future research directions include quantifying the social costs of infrastructure disruptions and better integration of equity into resilience decision-making.Comment: 37 pages, 11 figures, 2 table

Social inequality and the changing patterns of travel in the pandemic and post-pandemic era

The COVID-19 pandemic has had an unprecedented impact on mobility patterns resulting in a significant literature investigating travel behaviours over the course of the pandemic. Missing from much existing work on pandemic mobility is an explicit handling of the time-of-day of travel, which in previous literature has been shown to be an important factor in understanding mobility and, importantly, in understanding the impact on transport networks. In this article, we present a novel analysis of anonymised individual daily mobility patterns in the UK over a 30-month period covering the COVID-19 pandemic using privacy-preserving mobile phone GPS data, collected via integration of software development kits (SDKs) into mobile apps. Our analysis is based on time series clustering of mobility profiles at an hourly level of resolution and enables us to characterize five distinct daily mobility patterns. This typology appears remarkably robust over time, albeit with varying levels of each pattern during the course of the study period. We analyse the relative frequency of these patterns in relation to two dimensions of neighbourhood deprivation in England, with a particular focus on understanding mobility post-lockdown and for over a year after the final restrictions were lifted in the UK. Our results show that although overall mobility patterns have largely returned to their pre-pandemic levels, there remain persistent inequalities in relation to ‘traditional commute’, ‘highly mobile’ and ‘out in the evening’ activity patterns. This finding is expected to have important ongoing policy implications

Estimating the effect of social inequalities on the mitigation of COVID-19 across communities in Santiago de Chile

We study the spatio-temporal spread of SARS-CoV-2 in Santiago de Chile using anonymized mobile phone data from 1.4 million users, 22% of the whole population in the area, characterizing the effects of non-pharmaceutical interventions (NPIs) on the epidemic dynamics. We integrate these data into a mechanistic epidemic model calibrated on surveillance data. As of August 1, 2020, we estimate a detection rate of 102 cases per 1000 infections (90% CI: [95–112 per 1000]). We show that the introduction of a full lockdown on May 15, 2020, while causing a modest additional decrease in mobility and contacts with respect to previous NPIs, was decisive in bringing the epidemic under control, highlighting the importance of a timely governmental response to COVID-19 outbreaks. We find that the impact of NPIs on individuals’ mobility correlates with the Human Development Index of comunas in the city. Indeed, more developed and wealthier areas became more isolated after government interventions and experienced a significantly lower burden of the pandemic. The heterogeneity of COVID-19 impact raises important issues in the implementation of NPIs and highlights the challenges that communities affected by systemic health and social inequalities face adapting their behaviors during an epidemic

The adoption of non-pharmaceutical interventions and the role of digital infrastructure during the COVID-19 pandemic in Colombia, Ecuador, and El Salvador

AbstractAdherence to the non-pharmaceutical interventions (NPIs) put in place to mitigate the spreading of infectious diseases is a multifaceted problem. Several factors, including socio-demographic and socio-economic attributes, can influence the perceived susceptibility and risk which are known to affect behavior. Furthermore, the adoption of NPIs is dependent upon the barriers, real or perceived, associated with their implementation. Here, we study the determinants of NPIs adherence during the first wave of the COVID-19 Pandemic in Colombia, Ecuador, and El Salvador. Analyses are performed at the level of municipalities and include socio-economic, socio-demographic, and epidemiological indicators. Furthermore, by leveraging a unique dataset comprising tens of millions of internet Speedtest® measurements from Ookla®, we investigate the quality of the digital infrastructure as a possible barrier to adoption. We use mobility changes provided by Meta as a proxy of adherence to NPIs and find a significant correlation between mobility drops and digital infrastructure quality. The relationship remains significant after controlling for several factors. This finding suggests that municipalities with better internet connectivity were able to afford higher mobility reductions. We also find that mobility reductions were more pronounced in larger, denser, and wealthier municipalities.</jats:p