Smart Testing with Vaccination: A Bandit Algorithm for Active Sampling for Managing COVID-19
References
- (2021) Call for papers—Special issue of information systems research—Unleashing the power of information technology for strategic management of disasters. Inform. Systems Res. 32(4):1490–1493.Link, Google Scholar
- (2020) Fairness in machine learning for healthcare. Proc. 26th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (ACM, New York), 3529–3530.Google Scholar
- (2008) Just-in-time adaptive classifiers—Part i: Detecting nonstationary changes. IEEE Trans. Neural Networks 19(7):1145–1153.Crossref, Google Scholar
- (2022) Comparative transmission of SARS-CoV-2 Omicron (B.1.1.529) and Delta (b.1.617.2) variants and the impact of vaccination: National cohort study, England. Preprint, submitted February 17, https://doi.org/10.1101/2022.02.15.22271001.Google Scholar
- (2015) Online learning with feedback graphs: Beyond bandits. Proc. 28th Conf. Learning Theory, PMLR 40:23–35.Google Scholar
- (2020) Community risk perception and compliance with preventive measures for COVID-19 pandemic in Ethiopia. Risk Management Healthcare Policy 13:2887–2897.Crossref, Google Scholar
- (2020) What will be the economic impact of COVID-19 in the US? Rough estimates of disease scenarios. NBER Working Paper No. 26867, National Bureau of Economic Research, Cambridge, MA.Google Scholar
- (2002) Finite-time analysis of the multi-armed bandit problem. Machine Learning 47(2–3):235–256.Crossref, Google Scholar
- Baxter A, Oruc BE, Asplund J, Keskinocak P, Serban N (2022) Evaluating scenarios for school reopening under COVID19. BMC Public Health 22(1):1–10.Google Scholar
- (2021) Compliance with the main preventive measures of covid-19 in spain: The role of knowledge, attitudes, practices, and risk perception. Transboundary Emerging Diseases 69(4):e871–e882.Google Scholar
- (2014) Stochastic multi-armed-bandit problem with non-stationary rewards. Adv. Neural Inform. Processing Systems 27.Google Scholar
- (2013) Efficient data stream classification via probabilistic adaptive windows. Proc. 28th Annual ACM Sympos. Appl. Comput. (ACM, New York), 801–806.Google Scholar
- (2020) Self-isolation compliance in the COVID-19 era influenced by compensation: Findings from a recent survey in Israel: Public attitudes toward the COVID-19 outbreak and self-isolation: A cross sectional study of the adult population of Israel. Health Affairs 39(6):936–941.Crossref, Google Scholar
- (2012) Regret analysis of stochastic and nonstochastic multi-armed bandit problems. Foundations Trends Machine Learn. 5(1):1–122.Google Scholar
- (2016) Revealing graph bandits for maximizing local influence. Proc. 19th Internat. Conf. Artificial Intelligence Statistics, PMLR 51:10–18.Google Scholar
- (2018) Evaluating and characterizing incremental learning from non-stationary data. Preprint, submitted June 18, https://doi.org/10.48550/arXiv.1806.06610.Google Scholar
- (2020) Modelling transmission and control of the COVID-19 pandemic in Australia. Nature Comm. 11(1):5710.Google Scholar
- (2011) An empirical evaluation of Thompson sampling. Adv. Neural Inform. Processing Systems 24:2249–2257.Google Scholar
- (2021) Understanding bandits with graph feedback. Adv. Neural Inform. Processing Systems 34:24659–24669.Google Scholar
- (2020) Allocation of COVID-19 vaccines under limited supply. Preprint, submitted August 31, https://dx.doi.org/10.2139/ssrn.3678986.Google Scholar
- (2022) Hedging the drift: Learning to optimize under non stationarity. Management Sci. 68(3):1696–1713.Link, Google Scholar
- (2020) Neural online graph exploration. Preprint, submitted December 6, https://doi.org/10.48550/arXiv.2012.03345.Google Scholar
- (2011) Contextual bandits with linear payoff functions. Proc. 14th Internat.. Conf. Artificial Intelligence Statistics, PMLR 15:208–214.Google Scholar
- (1996) Active learning with statistical models. J. Artificial Intelligence Res. 4(1):129–145.Crossref, Google Scholar
- (2020) A SIR model assumption for the spread of COVID-19 in different communities. Chaos Solitons Fractals 139:110057.Crossref, Google Scholar
- (2019) Learning transferable graph exploration. Adv. Neural Inform. Processing Systems 32.Google Scholar
- (2015) Epidemic predictions in an imperfect world: Modelling disease spread with partial data. Proc. Royal Soc. B Biol. Sci. 282:20150205.Crossref, Google Scholar
- (2010) When do procedural fairness and outcome fairness interact to influence employees’ work attitudes and behaviors? The moderating effect of uncertainty. J. Appl. Psych. 95(2):291.Crossref, Google Scholar
- (2003) Contact tracing and disease control. Proc. Royal Soc. B Biol. Sci. 270(1533):2565–2571.Crossref, Google Scholar
- (2020) Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing. Science 368(6491):eabb6936.Crossref, Google Scholar
- (2021) Coronavirus risk perception and compliance with social distancing measures in a sample of young adults: Evidence from Switzerland. PLoS One. 16(2):e0247447.Crossref, Google Scholar
- (1998) Studying dynamics of the HIV epidemic: Population-based data compared with sentinel surveillance in Zambia. AIDS 12(10):1227–1242.Crossref, Google Scholar
- (2011) The KL-UCB algorithm for bounded stochastic bandits and beyond. Proc. 24th Annual Conf. Learning Theory (PMLR, New York) 19:359–376.Google Scholar
- (2011) On upper-confidence bound policies for switching bandit problems. Internat. Conf. Algorithmic Learning Theory (Springer, Berlin), 174–188.Google Scholar
- (2010) Assessing respondent-driven sampling. Proc. Natl. Acad. Sci. USA 107(15):6743–6747.Crossref, Google Scholar
- (2020) A framework for optimizing covid-19 testing policy using a multi armed bandit approach. Preprint, submitted July 28, https://doi.org/10.48550/arXiv.2007.14805.Google Scholar
- (2014) Online spectral learning on a graph with bandit feedback. Proc. 2014 IEEE Internat. Conf. Data Mining (IEEE, Piscataway, NJ), 833–838.Google Scholar
- (2020) Feasibility of controlling covid-19 outbreaks by isolation of cases and contacts. Lancet Global Health 8(4):E488–E496.Crossref, Google Scholar
- (2012) RolX: Structural role extraction & mining in large graphs. Proc. 18th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (ACM, New York), 1231–1239.Google Scholar
- (2000) The mathematics of infectious diseases. SIAM Rev. 42(4):599–653.Crossref, Google Scholar
- (2020) Facing the COVID-19 epidemic in NYC: A stochastic agent-based model of various intervention strategies. Preprint, submitted April 28, https://doi.org/10.1101/2020.04.23.20076885.Google Scholar
- (2002) Contact tracing and epidemics control in social networks. Physical Rev. E 66:056115.Crossref, Google Scholar
- (2021) Cash incentives, ethics, and COVID-19 vaccination. Science 374(6569):819–820.Crossref, Google Scholar
- (2019) Non-asymptotic uniform rates of consistency for k-NN regression. Proc. AAAI Conf. Artificial Intelligence (AAAI Press, Palo Alto, CA), 3999–4006.Google Scholar
- (2020) Influence maximization in unknown social networks: Learning policies for effective graph sampling. Proc. 19th Internat. Conf. Autonomous Agents and MultiAgent Systems, 575–583.Google Scholar
- (2018) Parallelised Bayesian optimisation via Thompson sampling. Proc. 21st Internat. Conf. Artificial Intelligence Statistics (PMLR, New York), 133–142.Google Scholar
- (2020) Interventions to mitigate early spread of SAR-CoV-2 in Singapore: A modelling study. Lancet Infectious Diseases 20(6):678–688.Crossref, Google Scholar
- (2020) Bandit Algorithms (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
- (2020) The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: Estimation and application. Ann. Internal Medicine 172(9):577–582.Crossref, Google Scholar
- (2010) Principles and Practice of Public Health Surveillance (Oxford University Press, New York).Crossref, Google Scholar
- (2010) A contextual-bandit approach to personalized news article recommendation. Proc. 19th Internat. Conf. World Wide Web (ACM, New York), 661–670.Google Scholar
- (2018) Spatial resource allocation for emerging epidemics: A comparison of greedy, myopic, and dynamic policies. Manufacturing Service Oper. Management 20(2):181–198.Link, Google Scholar
- (2015) Active search and bandits on graphs using sigma-optimality. Proc. 31st Conf. Uncertainty Artificial Intelligence (AUAI, Amsterdam), 542–551.Google Scholar
- (1998) Bandit problems and the exploration/exploitation tradeoff. IEEE Trans. Evolutionary Comput. 2(1):2–22.Crossref, Google Scholar
- (2020) Household transmission of SARS-CoV-2: A systematic review and meta-analysis. JAMA Network Open 3(12):e2031756.Crossref, Google Scholar
- (2019) A multi-armed bandit approach for exploring partially observed networks. Appl. Network Sci. 4(1):26.Crossref, Google Scholar
- (2005) Review of sampling hard-to-reach and hidden populations for HIV surveillance. AIDS 19:S67–S72.Crossref, Google Scholar
- (2022) COVID-19: How Omicron overtook Delta in three charts. Nature 10.Google Scholar
- (2020) Strong correlations between power-law growth of covid-19 in four continents and the inefficiency of soft quarantine strategies. Chaos 30(4):041102.Crossref, Google Scholar
- (2011) From bandits to experts: On the value of side-observations. Adv. Neural Inform. Processing Systems 24:684–692.Google Scholar
- (2013) Distributed representations of words and phrases and their compositionality. Adv. Neural Inform. Processing Systems 26:3111–3119.Google Scholar
- (2015) Human-level control through deep reinforcement learning. Nature 518(7540):529–533.Crossref, Google Scholar
- (2022) COVID-19 will continue but the end of the pandemic is near. Lancet 399(10323):417–419.Crossref, Google Scholar
- (1978) An analysis of approximations for maximizing submodular set functions—I. Math. Programming 14(1):265–294.Crossref, Google Scholar
- (2020) The impacts of knowledge, risk perception, emotion and information on citizens’ protective behaviors during the outbreak of COVID-19: A cross-sectional study in China. BMC Public Health 20(1):1–12.Crossref, Google Scholar
- (2009) An agent-based approach for modeling dynamics of contagious disease spread. Internat. J. Health Geographics 8(1):50.Crossref, Google Scholar
- (2014) Deepwalk: Online learning of social representations. Proc. 20th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (ACM, New York), 701–710.Google Scholar
- (2020) The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: A modelling study. Lancet Public Health 5(5):e261–e270.Crossref, Google Scholar
- (2022) The impact of batch learning in stochastic linear bandits. Preprint, submitted February 14, https://doi.org/10.48550/arXiv.2202.06657.Google Scholar
- (2017) Taming non-stationary bandits: A Bayesian approach. Preprint, submitted July 31, https://doi.org/10.48550/arXiv.1707.09727.Google Scholar
- (2020) Why is it difficult to accurately predict the COVID-19 epidemic? Infectious Disease Modelling 5:271–281.Crossref, Google Scholar
- (2007) Decision-centric active learning of binary-outcome models. Inform. Systems Res. 18(1):4–22.Link, Google Scholar
- (2020) COVID-19 epidemic in Switzerland: On the importance of testing, contact tracing and isolation. Swiss Medical Weekly 150(11–12):w20225.Google Scholar
- (2020) COVID-ABS: An agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions. Chaos Solitons Fractals 139:110088.Crossref, Google Scholar
- (2016) Mastering the game of go with deep neural networks and tree search. Nature 529(7587):484–489.Crossref, Google Scholar
- (2020) Contextual bandits with side-observations. Preprint, submitted June 6, https://doi.org/10.48550/arXiv.2006.03951.Google Scholar
- (2015) Information gathering in networks via active exploration. Proc. 24th Internat. Conf. Artificial Intelligence (AAAI Press, Palo Alto, CA), 981–988.Google Scholar
- (2017) ε-WGX: Adaptive edge probing for enhancing incomplete networks. Proc. 2017 ACM on Web Science Conf. (ACM, New York), 161–170.Google Scholar
- (2018) Reinforcement Learning: An Introduction (MIT Press, Cambridge, MA).Google Scholar
- (1933) On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika 25(3–4):285–294.Crossref, Google Scholar
- (2020) Centralized and decentralized isolation strategies and their impact on the COVID-19 pandemic dynamics. Preprint, submitted April 8, https://doi.org/10.48550/arXiv.2004.04222.Google Scholar
- (2020) Sliding-window Thompson sampling for non-stationary settings. J. Artificial Intelligence Res. 68:311–364.Crossref, Google Scholar
- (2022) Estimates of SARS-CoV-2 Omicron variant severity in Ontario, Canada. JAMA 327(13):1286–1288.Crossref, Google Scholar
- (2003) Contact tracing and population screening for tuberculosis – Who should be assessed? J. Public Health 25(1):59–61.Crossref, Google Scholar
- (2016) Dueling network architectures for deep reinforcement learning. Proc. 33rd Internat. Conf. Machine Learning, PMLR 48:1995–2003.Google Scholar
- (2004) Lessons learned from public health mass media campaigns: Marketing health in a crowded media world. Annual Rev. Public Health 25:419.Crossref, Google Scholar
- World Meter (2020) COVID-19 coronavirus pandemic. Retrieved August 31 from https://www.worldometers.info/coronavirus/.Google Scholar
- (2006) Selectively acquiring customer information: A new data acquisition problem and an active learning-based solution. Management Sci. 52(5):697–712.Link, Google Scholar

