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  1. Article ; Online: Using Location Intelligence to Evaluate the COVID-19 Vaccination Campaign in the United States: Spatiotemporal Big Data Analysis.

    Li, Qingfeng / Peng, James Cheng / Mohan, Diwakar / Lake, Brennan / Euler, Alex Ruiz / Weir, Brian / Kan, Lena / Yang, Cui / Labrique, Alain

    JMIR public health and surveillance

    2023  Volume 9, Page(s) e39166

    Abstract: Background: Highly effective COVID-19 vaccines are available and free of charge in the United States. With adequate coverage, their use may help return life back to normal and reduce COVID-19-related hospitalization and death. Many barriers to ... ...

    Abstract Background: Highly effective COVID-19 vaccines are available and free of charge in the United States. With adequate coverage, their use may help return life back to normal and reduce COVID-19-related hospitalization and death. Many barriers to widespread inoculation have prevented herd immunity, including vaccine hesitancy, lack of vaccine knowledge, and misinformation. The Ad Council and COVID Collaborative have been conducting one of the largest nationwide targeted campaigns ("It's Up to You") to communicate vaccine information and encourage timely vaccination across the United States. More than 300 major brands, digital and print media companies, and community-based organizations support the campaigns to reach distinct audiences.
    Objective: The goal of this study was to use aggregated mobility data to assess the effectiveness of the campaign on COVID-19 vaccine uptake.
    Methods: Campaign exposure data were collected from the Cuebiq advertising impact measurement platform consisting of about 17 million opted-in and deidentified mobile devices across the country. A Bayesian spatiotemporal hierarchical model was developed to assess campaign effectiveness through estimating the association between county-level campaign exposure and vaccination rates reported by the Centers for Disease Control and Prevention. To minimize potential bias in exposure to the campaign, the model included several control variables (eg, age, race or ethnicity, income, and political affiliation). We also incorporated conditional autoregressive residual models to account for apparent spatiotemporal autocorrelation.
    Results: The data set covers a panel of 3104 counties from 48 states and the District of Columbia during a period of 22 weeks (March 29 to August 29, 2021). Officially launched in February 2021, the campaign reached about 3% of the anonymous devices on the Cuebiq platform by the end of March, which was the start of the study period. That exposure rate gradually declined to slightly above 1% in August 2021, effectively ending the study period. Results from the Bayesian hierarchical model indicate a statistically significant positive association between campaign exposure and vaccine uptake at the county level. A campaign that reaches everyone would boost the vaccination rate by 2.2% (95% uncertainty interval: 2.0%-2.4%) on a weekly basis, compared to the baseline case of no campaign.
    Conclusions: The "It's Up to You" campaign is effective in promoting COVID-19 vaccine uptake, suggesting that a nationwide targeted mass media campaign with multisectoral collaborations could be an impactful health communication strategy to improve progress against this and future pandemics. Methodologically, the results also show that location intelligence and mobile phone-based monitoring platforms can be effective in measuring impact of large-scale digital campaigns in near real time.
    MeSH term(s) United States/epidemiology ; Humans ; COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19 Vaccines ; Bayes Theorem ; Immunization Programs ; Intelligence ; Data Analysis
    Chemical Substances COVID-19 Vaccines
    Language English
    Publishing date 2023-02-16
    Publishing country Canada
    Document type Journal Article
    ISSN 2369-2960
    ISSN (online) 2369-2960
    DOI 10.2196/39166
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Book ; Online: Multiple-level Point Embedding for Solving Human Trajectory Imputation with Prediction

    Qin, Kyle K. / Ren, Yongli / Shao, Wei / Lake, Brennan / Privitera, Filippo / Salim, Flora D.

    2023  

    Abstract: Sparsity is a common issue in many trajectory datasets, including human mobility data. This issue frequently brings more difficulty to relevant learning tasks, such as trajectory imputation and prediction. Nowadays, little existing work simultaneously ... ...

    Abstract Sparsity is a common issue in many trajectory datasets, including human mobility data. This issue frequently brings more difficulty to relevant learning tasks, such as trajectory imputation and prediction. Nowadays, little existing work simultaneously deals with imputation and prediction on human trajectories. This work plans to explore whether the learning process of imputation and prediction could benefit from each other to achieve better outcomes. And the question will be answered by studying the coexistence patterns between missing points and observed ones in incomplete trajectories. More specifically, the proposed model develops an imputation component based on the self-attention mechanism to capture the coexistence patterns between observations and missing points among encoder-decoder layers. Meanwhile, a recurrent unit is integrated to extract the sequential embeddings from newly imputed sequences for predicting the following location. Furthermore, a new implementation called Imputation Cycle is introduced to enable gradual imputation with prediction enhancement at multiple levels, which helps to accelerate the speed of convergence. The experimental results on three different real-world mobility datasets show that the proposed approach has significant advantages over the competitive baselines across both imputation and prediction tasks in terms of accuracy and stability.

    Comment: 22 pages; accepted by ACM Transactions on Spatial Algorithms and Systems
    Keywords Computer Science - Machine Learning ; 68T07 ; H.0
    Subject code 006
    Publishing date 2023-01-11
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Socio-economic determinants of mobility responses during the first wave of COVID-19 in Italy: from provinces to neighbourhoods.

    Gauvin, Laetitia / Bajardi, Paolo / Pepe, Emanuele / Lake, Brennan / Privitera, Filippo / Tizzoni, Michele

    Journal of the Royal Society, Interface

    2021  Volume 18, Issue 181, Page(s) 20210092

    Abstract: After more than 1 year into the COVID-19 pandemic, governments worldwide still face the challenge of adopting non-pharmaceutical interventions to mitigate the risks posed by the emergence of new SARS-CoV-2 variants and the lack of a worldwide equitable ... ...

    Abstract After more than 1 year into the COVID-19 pandemic, governments worldwide still face the challenge of adopting non-pharmaceutical interventions to mitigate the risks posed by the emergence of new SARS-CoV-2 variants and the lack of a worldwide equitable vaccine allocation. Thus, it becomes 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 an 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 centres, which persisted after the end of the lockdown. Such centre-periphery gradient was mainly associated with differences in educational attainment. 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 the population's age and sex composition. In the future, targeted interventions should take into account how the ability to comply with restrictions varies across geographical areas and socio-demographic groups.
    MeSH term(s) COVID-19 ; Cities ; Communicable Disease Control ; Humans ; Italy ; Pandemics ; SARS-CoV-2 ; Socioeconomic Factors
    Language English
    Publishing date 2021-08-04
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2156283-0
    ISSN 1742-5662 ; 1742-5689
    ISSN (online) 1742-5662
    ISSN 1742-5689
    DOI 10.1098/rsif.2021.0092
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Characterizing collective physical distancing in the U.S. during the first nine months of the COVID-19 pandemic.

    Klein, Brennan / LaRock, Timothy / McCabe, Stefan / Torres, Leo / Friedland, Lisa / Kos, Maciej / Privitera, Filippo / Lake, Brennan / Kraemer, Moritz U G / Brownstein, John S / Gonzalez, Richard / Lazer, David / Eliassi-Rad, Tina / Scarpino, Samuel V / Vespignani, Alessandro / Chinazzi, Matteo

    PLOS digital health

    2024  Volume 3, Issue 2, Page(s) e0000430

    Abstract: The COVID-19 pandemic offers an unprecedented natural experiment providing insights into the emergence of collective behavioral changes of both exogenous (government mandated) and endogenous (spontaneous reaction to infection risks) origin. Here, we ... ...

    Abstract The COVID-19 pandemic offers an unprecedented natural experiment providing insights into the emergence of collective behavioral changes of both exogenous (government mandated) and endogenous (spontaneous reaction to infection risks) origin. Here, we characterize collective physical distancing-mobility reductions, minimization of contacts, shortening of contact duration-in response to the COVID-19 pandemic in the pre-vaccine era by analyzing de-identified, privacy-preserving location data for a panel of over 5.5 million anonymized, opted-in U.S. devices. We define five indicators of users' mobility and proximity to investigate how the emerging collective behavior deviates from typical pre-pandemic patterns during the first nine months of the COVID-19 pandemic. We analyze both the dramatic changes due to the government mandated mitigation policies and the more spontaneous societal adaptation into a new (physically distanced) normal in the fall 2020. Using the indicators here defined we show that: a) during the COVID-19 pandemic, collective physical distancing displayed different phases and was heterogeneous across geographies, b) metropolitan areas displayed stronger reductions in mobility and contacts than rural areas; c) stronger reductions in commuting patterns are observed in geographical areas with a higher share of teleworkable jobs; d) commuting volumes during and after the lockdown period negatively correlate with unemployment rates; and e) increases in contact indicators correlate with future values of new deaths at a lag consistent with epidemiological parameters and surveillance reporting delays. In conclusion, this study demonstrates that the framework and indicators here presented can be used to analyze large-scale social distancing phenomena, paving the way for their use in future pandemics to analyze and monitor the effects of pandemic mitigation plans at the national and international levels.
    Language English
    Publishing date 2024-02-06
    Publishing country United States
    Document type Journal Article
    ISSN 2767-3170
    ISSN (online) 2767-3170
    DOI 10.1371/journal.pdig.0000430
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown.

    Pepe, Emanuele / Bajardi, Paolo / Gauvin, Laetitia / Privitera, Filippo / Lake, Brennan / Cattuto, Ciro / Tizzoni, Michele

    Scientific data

    2020  Volume 7, Issue 1, Page(s) 230

    Abstract: Italy has been severely affected by the COVID-19 pandemic, reporting the highest death toll in Europe as of April 2020. Following the identification of the first infections, on February 21, 2020, national authorities have put in place an increasing ... ...

    Abstract Italy has been severely affected by the COVID-19 pandemic, reporting the highest death toll in Europe as of April 2020. 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. On March 12, the government imposed a national lockdown. To aid the evaluation of the impact of interventions, we present daily time-series of three different aggregated mobility metrics: the origin-destination movements between Italian provinces, the radius of gyration, and the average degree of a spatial proximity network. All metrics were computed by processing a large-scale dataset of anonymously shared positions of about 170,000 de-identified smartphone users before and during the outbreak, at the sub-national scale. This dataset can help to monitor the impact of the lockdown on the epidemic trajectory and inform future public health decision making.
    MeSH term(s) Betacoronavirus ; COVID-19 ; Communicable Disease Control/methods ; Coronavirus Infections/epidemiology ; Geographic Information Systems ; Humans ; Italy/epidemiology ; Pandemics ; Pneumonia, Viral/epidemiology ; SARS-CoV-2 ; Smartphone ; Social Isolation ; Travel/statistics & numerical data
    Keywords covid19
    Language English
    Publishing date 2020-07-08
    Publishing country England
    Document type Dataset ; Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2775191-0
    ISSN 2052-4463 ; 2052-4463
    ISSN (online) 2052-4463
    ISSN 2052-4463
    DOI 10.1038/s41597-020-00575-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: COVID-19 outbreak response: a first assessment of mobility changes in Italy following national lockdown

    Pepe, Emanuele / Bajardi, Paolo / Gauvin, Laetitia / Privitera, Filippo / Lake, Brennan / Cattuto, Ciro / Tizzoni, Michele

    Abstract: 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 ... ...

    Abstract 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.
    Keywords covid19
    Publisher MedRxiv; WHO
    Document type Article ; Online
    DOI 10.1101/2020.03.22.20039933
    Database COVID19

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  7. Article: COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown

    Pepe, Emanuele / Bajardi, Paolo / Gauvin, Laetitia / Privitera, Filippo / Lake, Brennan / Cattuto, Ciro / Tizzoni, Michele

    Sci Data

    Abstract: Italy has been severely affected by the COVID-19 pandemic, reporting the highest death toll in Europe as of April 2020. Following the identification of the first infections, on February 21, 2020, national authorities have put in place an increasing ... ...

    Abstract Italy has been severely affected by the COVID-19 pandemic, reporting the highest death toll in Europe as of April 2020. 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. On March 12, the government imposed a national lockdown. To aid the evaluation of the impact of interventions, we present daily time-series of three different aggregated mobility metrics: the origin-destination movements between Italian provinces, the radius of gyration, and the average degree of a spatial proximity network. All metrics were computed by processing a large-scale dataset of anonymously shared positions of about 170,000 de-identified smartphone users before and during the outbreak, at the sub-national scale. This dataset can help to monitor the impact of the lockdown on the epidemic trajectory and inform future public health decision making.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #635878
    Database COVID19

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  8. Article ; Online: COVID-19 outbreak response: a first assessment of mobility changes in Italy following national lockdown

    Pepe, Emanuele / Bajardi, Paolo / Gauvin, Laetitia / Privitera, Filippo / Lake, Brennan / Cattuto, Ciro / Tizzoni, Michele

    medRxiv

    Keywords covid19
    Language English
    Publishing date 2020-03-27
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2020.03.22.20039933
    Database COVID19

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  9. Article ; Online: Mobility Patterns and Income Distribution in Times of Crisis

    Ruiz-Euler, Alex / Privitera, Filippo / Giuffrida, Danilo / Lake, Brennan / Zara, Ilenia

    SSRN Electronic Journal ; ISSN 1556-5068

    U.S. Urban Centers During the COVID-19 Pandemic

    2020  

    Keywords covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    DOI 10.2139/ssrn.3572324
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Socioeconomic determinants of mobility responses during the first wave of COVID-19 in Italy: from provinces to neighbourhoods

    Gauvin, Laetitia / Bajardi, Paolo / Pepe, Emanuele / Lake, Brennan / Privitera, Filippo / Tizzoni, Michele

    medRxiv

    Abstract: 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 ... ...

    Abstract 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 population9s 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.
    Keywords covid19
    Language English
    Publishing date 2020-11-18
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2020.11.16.20232413
    Database COVID19

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