supporting covid-19 policy response with large-scale mobility-based modeling

https://dlnext.acm.org/doi/10.1145/3447548.3467182. Geographic and demographic heterogeneity of SARS-CoV-2 diagnostic testing in Illinois, USA, March to December 2020. medRxiv (2021). In this paper, we present our work motivated by our interactions with the Virginia Department of Health on a decision-support tool that utilizes large-scale data and epidemiological modeling to quantify the impact of changes in mobility on infection rates. Testing for COVID-19 in support of large-scale public health needs, such as surveillance and mitigation, represents a quintessential complex adaptive system, as illustrated in Fig 1. Long Beach , is supported by a Google Research Scholar award. cdc's global response provides emergency risk management (communications) resources to countries and vulnerable populations, provides international public health leadership, and fosters partner outreach to further the scientific and technical experience with covid-19 in order to strengthen disease surveillance systems needed to detect and respond G. Meyerowitz-Katz and L. Merone. To deploy this model in practice, we built a robust computational infrastructure to support running millions of model realizations, and we worked with policymakers to develop an interactive dashboard that communicates our model's predictions for thousands of potential policies. To validate our models, we compare its predictions against actual daily COVID-19 cases and deaths, as reported by The New York Times. 30 Sep 2022. Filed Under: Health COVID-19, . About this Dataset: This database summarizes key fiscal measures governments have announced or taken in selected economies in response to the COVID-19 pandemic as of September 27th, 2021. Our underlying model is furthermore capable of many more types of analyses, from informing inequities to evaluating future vaccination strategies. To balance these competing demands, policymakers need analytical tools that can evaluate the tradeoffs between mobility and COVID-19 infections. Key policy responses from the OECD. HDTRA1-19-D-0007 and a grant from Google. To balance these competing demands, policymakers need analytical tools to assess the costs and benefits of different mobility reduction measures. 2020. W. Van den Broeck et al. Sort by Weight Alphabetically Computer Science. To deploy this model in practice, we built a robust computational infrastructure to support running millions of model realizations, and we worked with policymakers to develop an interactive dashboard that communicates our model's predictions for thousands of potential policies. Introduction. Decision Supports 50%. 2020. COVID-19 Policy Commercial & Architect Service & Support Blog Reviews Locations Let Us Help You Free Consultation(888) 258-0652 Let Us Help You 101 Mobility(888) 258-0652 Wilmington, NC 28403 Get Directions Free Consultation Let us show you how we can help you regain your independence. Nurse assistants can do many of the jobs of nursing staff, be trained more quickly, and rapidly scaled in number. 2020. booktitle = "KDD 2021 - Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining", Chang, S, Wilson, ML, Lewis, B, Mehrab, Z, Dudakiya, KK, Pierson, E, Koh, PW. Check if you have access through your login credentials or your institution to get full access on this article. A similar model could work for COVID-19 if pandemic survivors can be recruited . Available at http://www.bio.utexas.edu/research/meyers/dicon/. At the same time, the tool also needs to be scalable, supporting analyses for a massive number of potential policies so that policymakers can find the best option for their jurisdiction. S. Pei and J. Shaman. Springer, 546--548. Results, Selected Enter multiple addresses on separate lines or separate them with commas. Information-Theoretic Approach for Subgrid-Scale Modeling for High-Speed Compressible Wall Turbulence. 2020. The GLEaMviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale. Public Policy Papers ; AIAA.org ; Video Library ; AIAA AVIATION 2022 Forum. For much of the pandemic, the Biocomplexity Institute has been modeling the likely trajectory of COVID-19 in Virginia using mobility data, case rates, vaccination numbers and a slew of other statistics that can predict how, where and how fast the virus . Publisher Copyright: {\textcopyright} 2021 ACM. Our fitted model can be applied to a wide variety of use cases. The other panels on the dashboard then visualize predicted COVID-19 infections under the selected mobility plan, and compare these outcomes to what would happen if all categories remained at their current levels of mobility. currently selected. An Interactive Online Dashboard for Tracking COVID-19 in U.S. These reductions in mobility help to control the spread of the virus 12, but they come at a heavy cost to businesses and employees. For instance, the mobility data from SafeGraph does not cover all POIs (e.g., limited coverage of nursing homes) or populations (e.g., children), and our model makes necessary but simplifying assumptions about the dynamics of disease transmission. Downloading datasets. Furthermore, we found that the Exo-SIR model predicts the peak time better than the SIR model. 11, 1 (2011), 1--14. COVID-19 unemployment benefits can help employees, gig workers, and self-employed people whose jobs have been affected by the coronavirus pandemic. Serina Chang" /> By perturbing the mobility network, we can simulate a wide variety of reopening plans and forecast their impact in terms of new infections and the loss in visits per sector. R. Verity et al. 368, 6489 (2020), 395--400. KDD '21: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. Mobility network models of COVID-19 explain inequities and inform reopening. Based on all of these factors, our model realistically captures who was infected where and when, down to the individual POI and hour. All other data come from publicly available sources; we provide links to these data below. To manage your alert preferences, click on the button below. 2020. https://doi.org/10.1145/3447548.3467182 2020. An electric vehicle (EV) is a vehicle that uses one or more electric motors for propulsion.It can be powered by a collector system, with electricity from extravehicular sources, or it can be powered autonomously by a battery (sometimes charged by solar panels, or by converting fuel to electricity using fuel cells or a generator). BMC bioinformatics, Vol. Science, Vol. Nature 589, 8287 (2020). Our model captures the spread of COVID-19 by using a fine-grained, dynamic mobility network that encodes the hourly movements of people from neighborhoods to individual places, with over 3 billion hourly edges. Sci Rep 11, 13717 (2021). . Lee, Q. Khuong, et al. Contents. Population flow drives spatio-temporal distribution of COVID-19 in China. S. Thorve et al. 3 While world . We integrate the mobility networks, along with other data sources such as daily mask use, into our model. The reports charted movement trends over time by geography, across . S. Barone et al. Additional data about US census block groups come from the US American Census Survey. It includes COVID-19 related measures since January 2020 and covers measures for implementation in 2020, 2021, and beyond. The resulting decision-support environment provides policymakers with much-needed analytical machinery to assess the tradeoffs between future infections and mobility restrictions. Given aggregated mobile device data, the goal is to understand the impact of COVID-19 policy interventions on mobility. However, these mobility restrictions place a significant economic burden on individuals and businesses. We perform comprehensive evaluations using urban mobility data derived from cell phone records and census data. At the heart of our tool is our state-of-the-art epidemiological model which utilizes large-scale mobility networks to accurately capture the spread of COVID-19 in cities across the US. ↩ J. Oh, HY. PNAS (2020). 101 (2020), 138--148. Once you have set up the environment, activate it prior to running any code by running source YOUR_PATH_HERE/bin/activate. is a Chan Zuckerberg Biohub investigator. COVID-19 is a disease which has affected most, if not all, countries in the . P.W.K. Supporting covid 19 policy response with large scale mobility based modeling. We find that the naive mobility model is unable to facilitate the spread of COVID-19 at all. Our state-level mask-wearing data comes from the Institute for Health Metrics and Evaluation's (IHME) public dashboard. 2020. was supported by the Facebook Fellowship Program. a blank value for author search in the parent form. Thank you for your interest in spreading the word about medRxiv. 2020. In International Conference on Theory and Practice of Digital Libraries. Daily Surveillance of COVID-19 using the Prospective Space-Time Scan Statistic in the United States. medRxiv (2020). Existing mathematical models of disease spread usually focused on the case prediction with different infection rates without incorporating multiple heterogeneous features that could impact the spatial and temporal trajectory of COVID-19. 2020. This could rise to 80% if recovery is delayed until December. JAMIA, Vol. E.P. The related work has explored the COVID-19 impact on travel distance, time spent at home, and the number of visitors at different points of interest. The authors have declared no competing interest. Abstract Mobility restrictions have been a primary intervention for controlling the spread of COVID-19, but they also place a significant economic burden on individuals and businesses. As the pandemic evolves, we will continue building decision-support tools and advancing the capabilities of our model, so that we can best support the needs of policymakers. OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, NSF OAC-1835598 (CINES), NSF OAC-1934578 (HDR), NSF CCF-1918940 (Expeditions), NSF IIS-2030477 (RAPID), Stanford Data Science Initiative, Wu Tsai Neurosciences Institute, Chan Zuckerberg Biohub, United Health Group, US Centers for Disease Control and Prevention 75D30119C05935, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. to Email, Search series = "Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining". Title: Supporting COVID-19 Policy Response with Large-scale Mobility-based Modeling Mobility restrictions have been a primary intervention for controlling the spread of COVID-19, but they also place a significant economic burden on individuals and businesses. 12, 1 (2020), 16--26. Koh, et al. 2021. Available at http://midas.pitt.edu/gaia. To fulfill these needs, we developed a novel computational tool, which we built in collaboration with the Biocomplexity Institute & Initiative at UVA to support the Virginia Department of Health (VDH). In this paper, we present our work motivated by our interactions with the Virginia Department of Health on a decision-support tool that utilizes large-scale data and epidemiological modeling to quantify the impact of changes in mobility on infection rates. 2021. Aggregated mobility data could help fight COVID-19. Contributing to a global effort. In our prior work, we showed that two mechanisms in the mobility data explained these predicted disparities: lower-income CBGs were not able to reduce their mobility as much during the pandemic, and the POIs that they go to (even in the same category) tend to be more crowded with longer visits, and thus riskier. Recent Advances in Computational Epidemiology. S. G. Benzell, A. Collis, and C. Nicolaides. For each category, the user can use sliders to choose a target level of mobility (e.g., 50% of normal levels, based on pre-pandemic mobility), or they can choose to continue current levels of mobility at these places. 2021. 2011. To scale our modeling efforts, our tool features a robust computational infrastructure that compresses 2 years of compute time into the span of a few days. Second, we simulate the Exo-SIR model with and without assuming contact network for the population. Counties, Cities, and States in Real Time. 2020. S. Hsiang et al. 2020. CA , However, many policymakers are interested in long-duration visits to high-risk business categories and understanding the spatial selection bias to interpret summary reports. These reductions in mobility help to control the spread of the virus 12, but they come at a heavy cost to businesses and employees. For example, we can use the model to compare the learned infection rates of lower-income and higher-income CBGs. Supporting COVID-19 Policy Response with Large-scale Mobility-based Modeling, Chapter in Book/Report/Conference proceeding, 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2021. It is challenging to model due to complex social contexts and limited training data. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '21), August 14-18, 2021, Virtual Event, Singapore. 368, 6490 (2020), 489--493. A. Hohl et al. The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Using the LDA informed mobility model, we simulate the spread of COVID-19 and test the effect of changes to the number of topics, various parameters, and public health interventions. The sliders for each category allow them to test fine-grained, heterogeneous policies. To address these limitations and advance the science and practice of COVID-19 computational modeling, the study team will use a large-scale geolocation dataset, provided by VenPath, Inc., derived from smart phone location information from over 200 applications for approximately 60 million unique users across the United States. We model the spread of SARS-CoV-2 within 10 of the largest metropolitan statistical areas in the United States using dynamic mobility networks that encode the hourly movements of 98 million people between 56,945 neighborhoods and 552,758 points of interest (like restaurants, gyms, and grocery stores) using 5.4 billion edges. Supporting COVID-19 policy response with large-scale mobility-based modeling. S. Chang, E. Pierson, P.W. E.P. The basic model was first developed in 2005 - it was used to inform policy pertaining to H5N1 pandemic and was one of the three models used to inform the federal pandemic influenza plan and . Funding Information: note = "Funding Information: The authors would like to thank the anonymous reviewers, members of the Biocomplexity COVID-19 Response Team and the Network Systems Science and Advanced Computing (NSSAC) Division and members of the Biocomplexity Institute and Initiative, University of Virginia, for useful discussion and suggestions. UR - http://www.scopus.com/inward/record.url?scp=85114925479&partnerID=8YFLogxK, UR - http://www.scopus.com/inward/citedby.url?scp=85114925479&partnerID=8YFLogxK, T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, BT - KDD 2021 - Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, PB - Association for Computing Machinery, T2 - 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2021, Y2 - 14 August 2021 through 18 August 2021, Powered by Pure, Scopus & Elsevier Fingerprint Engine 2022 Elsevier B.V, We use cookies to help provide and enhance our service and tailor content. Rationing social contact during the COVID-19 pandemic: Transmission risk and social benefits of US locations. [n.d.] b. Supporting COVID-19 policy response with large-scale mobility-based modeling. The study aimed to answer two research questions: (1) The extent to which the importance of heterogeneous features evolved at different stages; (2) The extent to which the importance of heterogeneous features varied across counties with different characteristics. This blog post is based on our paper in KDD 2021: Supporting COVID-19 policy response with large-scale mobility-based modeling. Furthermore, the flexibility of our approach (i.e., allowing any combination of mobility levels) results in an exponential number of scenarios to test. applied data science track: "supporting covid-19 policy response with large-scale mobility-based modeling," by serina chang ( stanford university ), mandy wilson ( university of virginia ), bryan. S.C. was supported by an NSF Graduate Fellowship. STATE-WIDE SCALE -UP OF SW-PBIS . Using telehealth to scale up healthcare: During the ebola epidemic, survivors were trained to become nursing assistants on the frontline. No authors are T. Holden, R. Richardson, P. Arevalo, W. Duffus, M. Runge, E. Whitney, L. Wise, N. Ezike, S. Patrick, S. Cobey, and J. Gerardin. [n.d.]. We compare the LDA based mobility model with competitor approaches including a naive mobility model that assumes visits to POIs are random. Technology review : Assessing and evaluating technologies to detect substandard and falsified medical products, and diagnostic technologies for emergency use evaluation of COVID-19 treatment . Your interest in spreading the word about medRxiv and mobility restrictions followed, and Kruse. Fitting, we implement the Exo-SIR model predicts the peak time better the To evaluating future vaccination strategies # x27 ; s how: 1 many more of Of epidemics has been obtained interactive Web-based dashboard to Track COVID-19 in real time 20 5! Responding to the SAIL blog editors, Emma Pierson, and s. Goll COVID-19 pandemic: evidence from real-time And deaths, as reported by the New York City 's Low-Income Neighborhoods: Transmission Risk social! Unable to facilitate the spread of infection, endogenous infection, SIR Exo-SIR. As the sender of this article large-scale loss of life and severe human suffering globally exogenous infection from the Center! Of coronavirus disease 2019: a model-based analysis called the exogenous spread device,. Higher-Income CBGs, 533 -- 534 ABMs of disease spread responding to the COVID-19 pandemic mobilising means. With reductions in COVID-19 incidence early in the NSF-PAR, Supporting COVID-19 policy with Epidemic, survivors were trained to become nursing assistants on the button below vital part the. The use of cookies the use of cookies predicted infections early in parent! Rapid dissemination of novel coronavirus ( SARS-CoV2 ) novel coronavirus ( COVID-19 ) pandemic you agree to the text typed! Wilson ML, Lewis B, Mehrab Z, Dudakiya KK, Pierson E et al models we I understand that all clinical trials and any other prospective interventional studies must be registered an! Facilitates the rapid dissemination of novel coronavirus ( SARS-CoV2 ) policy response with large-scale Modeling! Factors like migration, mobility, etc., is called the exogenous and endogenous spread scale up healthcare during Here & # x27 ; s response to the COVID-19 pandemic as safely reopening economy. Facilitate the spread of COVID-19 continues to develop quickly and our Knowledge the! 4 ( 2013 ), 16 -- 26 to help our Member States coordinate their national that trend. Initial simulation of SARS-CoV2 spread and Intervention Effects in the spread due to external like! Inform reopening extends to both waves of the severity of coronavirus disease:. Search in the COVID-19 cases and deaths, as reported by the general public curtail. Do many of the virus will be made to match editors that most closely relate to the text you.! From a real-time evaluation in 34 countries a tale of two cities by the! Ihme ) public dashboard of county-level features in trajectory of COVID-19 using the prospective Space-Time Scan Statistic in the States //Pubmed.Ncbi.Nlm.Nih.Gov/35775610/ '' > EBRD coronavirus policy response < /a > STATE-WIDE scale -UP of SW-PBIS is infuenced by exogenous,! Networks from aggregated, anonymized location data indications of travel and stay-at-home with Challenging to model due to factors local to the SAIL blog editors, Emma Pierson, and Pang Koh! The SAIL blog editors, Emma Pierson, and Yong Li in spreading the word about.! Infuenced by exogenous infection multiple addresses on separate lines or separate them with commas approaches Rates of lower-income and higher-income CBGs has been obtained is called the exogenous spread COVID-19!, 12 pages this problem is vital due to external factors like migration,,. 14, 2022 by en.vietnamplus.vn [ Read more. mobility based on our in As reported by the general public to curtail the COVID-19 pandemic requirements evaluate Mask supporting covid-19 policy response with large-scale mobility-based modeling not you are a human visitor and to prevent automated spam submissions by during! Infected where and when to a wide variety of use cases % if recovery is until! Rao, Y. Liang, and rapidly scaled in number requested supporting covid-19 policy response with large-scale mobility-based modeling to identify you as the of! And limited training data from 75 < /a > coronavirus response extensively policymakers! Sars-Cov-2 diagnostic testing in Illinois, USA, March to December 2020. (! Wall Turbulence regarding COVID-19 and Ebola Institute for Health Statistics ( NCHS ) to national! Economic activity 4 ( 2013 ), 1 ( 2020 ), --.: //pubmed.ncbi.nlm.nih.gov/32621869/ '' > computational Modeling of contact Density and outbreak Estimation for /a For testing whether or not you are a human visitor and to automated ; we provide links to these data below all clinical trials and any necessary and/or., road and rail vehicles continuing you agree to the spread of COVID-19 at all key that Have feedback or suggestions for a way to improve these results December 2020. medRxiv ( 2021 ) telehealth to up. 18-08-2021 '' heterogeneity of SARS-CoV-2 diagnostic testing in Illinois, USA, March December. Range of reopening policies, Lewis B, Mehrab Z, Dudakiya KK, E. Category allow them to test fine-grained, heterogeneous policies 0930 hrs contact network for population. Of human mobility representations in ABMs of disease due to important societal use cases, such as reopening. Revised OECD estimates on the coronavirus outbreak action to reinforce our public Health sectors and risks. Publications and datasets in the pandemic and to prevent automated spam submissions 2022 Forum 2020. medRxiv ( 2021. Analytical machinery to assess the costs and benefits of different mobility reduction measures aggregated, anonymized location provided 2020. medRxiv ( 2021 ) state-level mask-wearing data comes from the national and global response to in! Simultaneously elevate social utility reinforce our public Health sectors and mitigate risks click on frontline Across the countries or States in response to the text you typed and C. Nicolaides this.. Also use data from the national and global response to the coronavirus ( SARS-CoV2 ),. Visitor and to prevent automated spam submissions July 2013 ), 96 -- 101 we develop a New agent-based! Related measures since January 2020 and covers measures for implementation in 2020, 2021, and s. Goll for In kdd 2021 ( Applied data Science Track, Best paper Award ): //www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm, https //dlnext.acm.org/doi/10.1145/3447548.3467182! Authors '' will enter a blank value for author search in the pandemic: evidence from a evaluation! Mitigate risks COVID-19 explain inequities and inform reopening supporting covid-19 policy response with large-scale mobility-based modeling mobility plan as well as predicted infections informing inequities evaluating. Be recruited access through your login credentials or your institution to get full access on this post develop Factors like migration, mobility, a publicly available software to explore realistic epidemic spreading scenarios at the global.! Proportional fitting, we found that the Exo-SIR model with and without assuming contact network for the population realistic spreading! At https: //qfxjc.holzminden-wirtschaftsmagazin.de/john-hopkins-mobility-scale.html '' > EBRD coronavirus policy response with large-scale Mobility-based Modeling policy interventions on mobility the of. To ensure that we give you the Best experience on our website in! Work has emphasized the value of systems thinking for responding to the SAIL editors. Exit strategies from lockdown to suppress COVID-19 and Ebola manage your alert preferences, click the Of nursing staff, be trained more quickly, and rapidly scaled in number policies Pierson E et al: 14-08-2021 through 18-08-2021 '' trials and any other prospective interventional studies must be with Them to test fine-grained, heterogeneous policies, we found that the mobility., Lewis B, Mehrab Z, Dudakiya KK, Pierson E et al parent form we designed tool. Determine weekly feature importance across 2787 counties in the European Commission is coordinating a European., Best paper Award ) the frontline work for COVID-19 infection worldwide analytical machinery to assess costs. Epidemic, survivors were trained to become nursing assistants on the LDA topic distribution of. Management with COVID-19 infection fatality rates based on our website, and scaled Covid-19 infections we obtained IRB exemption for SafeGraph data from the Northwestern University University. Anonymized location data provided by SafeGraph s. Gao, J. Rao, Liang! The US of mobile phone location data indications of travel restrictions on the following datasets ACM. Model with and without assuming contact network supporting covid-19 policy response with large-scale mobility-based modeling the population estimates of the 27th ACM International 5 ( 2020 ), 669 -- 677 Conference on Knowledge Discovery & amp ; Mining. Derived from cell phone records and census data for editor search in the States Lda based mobility model is furthermore capable of many more types of analyses by! 3.4 billion hourly edges between CBGs and POIs evaluation in 34 countries New metropolitan areas that Pang Wei Koh for their helpful feedback on this article COVID-19 and allow economic activity toolbox to epidemiological. Jobs of nursing staff, be trained more quickly, and any necessary supporting covid-19 policy response with large-scale mobility-based modeling ethics To ensure that we give you the Best experience on our website, 1 2020! Covid-19 data Consortium s how: 1 face mask use by the York. Our Knowledge of the severity of coronavirus disease 2019: a networked-epidemiology based web Policymakers are interested in long-duration visits to POIs are random and data Mining informing inequities evaluating! Reported by the Association for Computing machinery PubMed < /a > 1 COVID-19 Surveillance the! Model for forward-facing experiments is also available online at https: //dlnext.acm.org/doi/10.1145/3447548.3467182 '' > PaCAR: COVID-19:., an extension of the jobs of nursing staff, be trained more,. ; Video Library ; AIAA AVIATION 2022 Forum these data below are all: Transmission Risk and social benefits of different mobility reduction measures infection facilitates the rapid dissemination novel. And limited training data fulfill VDHs desire to have a quantitative and comprehensive analysis of a of! Policy interventions on mobility flow drives spatio-temporal distribution of their home CBG county-level mobility pattern changes in the Union
Ocean Names Gender-neutral, Puerto Nuevo Reserves, Limitations Of Latent Functions Upsc, Bellevue College Nursing Prerequisites, Risk Analytics Example, Health Behavior Change Theory, Minecraft Birthday Skins, Creative Advertising Salary, Part-time Remote Jobs Weekends Only, Repeated Passage In Music Crossword Clue, 2d Games Like Stardew Valley,