- May 2020
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www.thelancet.com www.thelancet.com
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Horton, R. (2020). Offline: Don’t let COVID-19 divert us completely. The Lancet, 395(10236), 1534. https://doi.org/10.1016/S0140-6736(20)31130-2
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www.pnas.org www.pnas.org
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Stadnytskyi, V., Bax, C. E., Bax, A., & Anfinrud, P. (2020). The airborne lifetime of small speech droplets and their potential importance in SARS-CoV-2 transmission. Proceedings of the National Academy of Sciences, 202006874. https://doi.org/10.1073/pnas.2006874117
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psyarxiv.com psyarxiv.com
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Michalak, N. M., Sng, O., Wang, I., & Ackerman, J. (2020, May 14). Sounds of sickness: Can people identify infectious disease using sounds of coughs and sneezes?. https://doi.org/10.1098/rspb.2020.0944
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Pichler, Anton, Marco Pangallo, R. Maria del Rio-Chanona, François Lafond, and J. Doyne Farmer. “Production Networks and Epidemic Spreading: How to Restart the UK Economy?” ArXiv:2005.10585 [Physics, q-Fin], May 21, 2020. http://arxiv.org/abs/2005.10585.
Tags
- inventory dynamics
- epidemiology
- reopening industry
- COVID-19
- industry
- epidemic spreading
- demand
- is:article
- production network
- consumption
- supply
- lang:en
- economic growth
- production
- transmission rate
- GDP
- social distincing
- unemployment
- work from home
- United Kingdom
- input-output constraints
- economics
Annotators
URL
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www.scirp.org www.scirp.org
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Makulilo, A. B. (2016). “A Person Is a Person through Other Persons”—A Critical Analysis of Privacy and Culture in Africa. Beijing Law Review, 7(3), 720–726. https://doi.org/10.4236/blr.2016.73020
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www.nature.com www.nature.com
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Andersen, K.G., Rambaut, A., Lipkin, W.I. et al. The proximal origin of SARS-CoV-2. Nat Med 26, 450–452 (2020). https://doi.org/10.1038/s41591-020-0820-9
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www.sciencedirect.com www.sciencedirect.com
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Chen, Z. (2020). COVID-19: A revelation – A reply to Ian Mitroff. Technological Forecasting and Social Change, 156, 120072. https://doi.org/10.1016/j.techfore.2020.120072
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Johnson, N.F., Velásquez, N., Restrepo, N.J. et al. The online competition between pro- and anti-vaccination views. Nature (2020). https://doi.org/10.1038/s41586-020-2281-1
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www.thelancet.com www.thelancet.com
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Jordana, J., & Triviño-Salazar, J. C. (2020). Where are the ECDC and the EU-wide responses in the COVID-19 pandemic? The Lancet, S0140673620311326. https://doi.org/10.1016/S0140-6736(20)31132-6
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Almaatouq, A., Noriega-Campero, A., Alotaibi, A., Krafft, P. M., Moussaid, M., & Pentland, A. (2020). Adaptive social networks promote the wisdom of crowds. Proceedings of the National Academy of Sciences, 201917687. https://doi.org/10.1073/pnas.1917687117
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science.sciencemag.org science.sciencemag.org
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Salje, H., Tran Kiem, C., Lefrancq, N., Courtejoie, N., Bosetti, P., Paireau, J., Andronico, A., Hozé, N., Richet, J., Dubost, C.-L., Le Strat, Y., Lessler, J., Levy-Bruhl, D., Fontanet, A., Opatowski, L., Boelle, P.-Y., & Cauchemez, S. (2020). Estimating the burden of SARS-CoV-2 in France. Science, eabc3517. https://doi.org/10.1126/science.abc3517
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Masuda, N., & Holme, P. (2020). Small inter-event times govern epidemic spreading on networks. Physical Review Research, 2(2), 023163. https://doi.org/10.1103/PhysRevResearch.2.023163
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www.annualreviews.org www.annualreviews.org
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Edelmann, A., Wolff, T., Montagne, D., & Bail, C. A. (2020). Computational Social Science and Sociology. Annual Review of Sociology, 46(1), annurev-soc-121919-054621. https://doi.org/10.1146/annurev-soc-121919-054621
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Lourenco, S. F., & Tasimi, A. (2020). No Participant Left Behind: Conducting Science During COVID-19. Trends in Cognitive Sciences, S1364661320301157. https://doi.org/10.1016/j.tics.2020.05.003
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link.aps.org link.aps.org
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Vasques Filho, D., & O’Neale, D. R. J. (2020). Transitivity and degree assortativity explained: The bipartite structure of social networks. Physical Review E, 101(5), 052305. https://doi.org/10.1103/PhysRevE.101.052305
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Riolo, M. A., & Newman, M. E. J. (2020). Consistency of community structure in complex networks. Physical Review E, 101(5), 052306. https://doi.org/10.1103/PhysRevE.101.052306
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Ruiu, M. L. (2020). Mismanagement of Covid-19: Lessons learned from Italy. Journal of Risk Research, 1–14. https://doi.org/10.1080/13669877.2020.1758755
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www.nejm.org www.nejm.org
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Arons, M. M., Hatfield, K. M., Reddy, S. C., Kimball, A., James, A., Jacobs, J. R., Taylor, J., Spicer, K., Bardossy, A. C., Oakley, L. P., Tanwar, S., Dyal, J. W., Harney, J., Chisty, Z., Bell, J. M., Methner, M., Paul, P., Carlson, C. M., McLaughlin, H. P., … Jernigan, J. A. (2020). Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility. New England Journal of Medicine, NEJMoa2008457. https://doi.org/10.1056/NEJMoa2008457
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www.thelancet.com www.thelancet.com
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Yong, S. E. F., Anderson, D. E., Wei, W. E., Pang, J., Chia, W. N., Tan, C. W., Teoh, Y. L., Rajendram, P., Toh, M. P. H. S., Poh, C., Koh, V. T. J., Lum, J., Suhaimi, N.-A. M., Chia, P. Y., Chen, M. I.-C., Vasoo, S., Ong, B., Leo, Y. S., Wang, L., & Lee, V. J. M. (2020). Connecting clusters of COVID-19: An epidemiological and serological investigation. The Lancet Infectious Diseases, S1473309920302735. https://doi.org/10.1016/S1473-3099(20)30273-5
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Gudbjartsson, D. F., Helgason, A., Jonsson, H., Magnusson, O. T., Melsted, P., Norddahl, G. L., Saemundsdottir, J., Sigurdsson, A., Sulem, P., Agustsdottir, A. B., Eiriksdottir, B., Fridriksdottir, R., Gardarsdottir, E. E., Georgsson, G., Gretarsdottir, O. S., Gudmundsson, K. R., Gunnarsdottir, T. R., Gylfason, A., Holm, H., … Stefansson, K. (2020). Spread of SARS-CoV-2 in the Icelandic Population. New England Journal of Medicine, NEJMoa2006100. https://doi.org/10.1056/NEJMoa2006100
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academic.oup.com academic.oup.com
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Danis, K., Epaulard, O., Bénet, T., Gaymard, A., Campoy, S., Bothelo-Nevers, E., Bouscambert-Duchamp, M., Spaccaferri, G., Ader, F., Mailles, A., Boudalaa, Z., Tolsma, V., Berra, J., Vaux, S., Forestier, E., Landelle, C., Fougere, E., Thabuis, A., Berthelot, P., … Bag, B. C. (2020). Cluster of coronavirus disease 2019 (Covid-19) in the French Alps, 2020. Clinical Infectious Diseases, ciaa424. https://doi.org/10.1093/cid/ciaa424
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Ghinai, I., McPherson, T. D., Hunter, J. C., Kirking, H. L., Christiansen, D., Joshi, K., Rubin, R., Morales-Estrada, S., Black, S. R., Pacilli, M., Fricchione, M. J., Chugh, R. K., Walblay, K. A., Ahmed, N. S., Stoecker, W. C., Hasan, N. F., Burdsall, D. P., Reese, H. E., Wallace, M., … Uyeki, T. M. (2020). First known person-to-person transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the USA. The Lancet, 395(10230), 1137–1144. https://doi.org/10.1016/S0140-6736(20)30607-3
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academic.oup.com academic.oup.com
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Li, W., Zhang, B., Lu, J., Liu, S., Chang, Z., Cao, P., Liu, X., Zhang, P., Ling, Y., Tao, K., & Chen, J. (2020). The characteristics of household transmission of COVID-19. Clinical Infectious Diseases, ciaa450. https://doi.org/10.1093/cid/ciaa450
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Bi, Q., Wu, Y., Mei, S., Ye, C., Zou, X., Zhang, Z., Liu, X., Wei, L., Truelove, S. A., Zhang, T., Gao, W., Cheng, C., Tang, X., Wu, X., Wu, Y., Sun, B., Huang, S., Sun, Y., Zhang, J., … Feng, T. (2020). Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: A retrospective cohort study. The Lancet Infectious Diseases, S1473309920302875. https://doi.org/10.1016/S1473-3099(20)30287-5
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pubmed.ncbi.nlm.nih.gov pubmed.ncbi.nlm.nih.gov
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Yi, C., Aihong, W., Keqin, D., Haibo, W., Jianmei, W., Hongbo, S., Sijia,W., & Guozhang, X. (2020) The epidemiological characteristics of infection in close contacts of COVID-19 in Ningbo city. Chinese Journal of Epidemiology. Vol. 41 Issue (0):0-0. http://dx.doi.org/10.3760/cma.j.cn112338-20200304-00251
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Smelter, T. J., & Calvillo, D. P. (2020). Pictures and repeated exposure increase perceived accuracy of news headlines. Applied Cognitive Psychology, acp.3684. https://doi.org/10.1002/acp.3684
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link.springer.com link.springer.com
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Zhong, S., Crang, M., & Zeng, G. (2020). Constructing freshness: The vitality of wet markets in urban China. Agriculture and Human Values, 37(1), 175–185. https://doi.org/10.1007/s10460-019-09987-2
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www.thelancet.com www.thelancet.com
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Horton, R. (2020). Offline: Independent science advice for COVID-19—at last. The Lancet, 395(10235), 1472. https://doi.org/10.1016/S0140-6736(20)31098-9
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science-sciencemag-org.ezproxy.redlands.edu science-sciencemag-org.ezproxy.redlands.edu
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Aspesi, C., & Brand, A. (2020). In pursuit of open science, open access is not enough. Science, 368(6491), 574–577. https://doi.org/10.1126/science.aba3763
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www.nature.com www.nature.com
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Vespignani, A., Tian, H., Dye, C. et al. Modelling COVID-19. Nat Rev Phys (2020). https://doi.org/10.1038/s42254-020-0178-4
Tags
- quarentine
- epidemiology
- China
- modeling
- mathematics
- challenge
- war time
- antibody testing
- COVID-19
- containment measures
- emergency
- computational modeling
- isolation
- is:article
- transmission dynamics
- open data
- infection
- lang:en
- forecast
- public health
- pharmaceutical
- superspreading
- prediction
- complex network
- intervention
- policy
- contact tracing
Annotators
URL
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dash.harvard.edu dash.harvard.edu
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Larremore, Daniel B., Kate M. Bubar, and Yonatan H. Grad. Implications of test characteristics and population seroprevalence on ‘immune passport’ strategies (May 2020).https://dash.harvard.edu/handle/1/42664007
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www.pnas.org www.pnas.org
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Bento, A. I., Nguyen, T., Wing, C., Lozano-Rojas, F., Ahn, Y.-Y., & Simon, K. (2020). Evidence from internet search data shows information-seeking responses to news of local COVID-19 cases. Proceedings of the National Academy of Sciences, 202005335. https://doi.org/10.1073/pnas.2005335117
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Sood, L., & Sood, V. (2020). Being African American and Rural: A Double Jeopardy from Covid‐19. The Journal of Rural Health, jrh.12459. https://doi.org/10.1111/jrh.12459
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Zahnd, W. E. (2020). The COVID‐19 Pandemic Illuminates Persistent and Emerging Disparities among Rural Black Populations. The Journal of Rural Health, jrh.12460. https://doi.org/10.1111/jrh.12460
Tags
- death rate
- internet
- infection rate
- inadequately prepared
- telehealth
- rural health
- COVID-19
- inequality
- is:article
- access to care
- lang:en
- healthcare
- racial disparity
- health equity
- testing
- screening
- African American
- USA
- black people
- social determinants of health
- hospital
- demographics
- outbreak
Annotators
URL
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arxiv.org arxiv.org
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Pastor-Satorras, R., & Castellano, C. (2020). The localization of non-backtracking centrality in networks and its physical consequences. ArXiv:2005.03913 [Physics]. http://arxiv.org/abs/2005.03913
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arxiv.org arxiv.org
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Qian, Y., Expert, P., Panzarasa, P., & Barahona, M. (2020). Geometric graphs from data to aid classification tasks with graph convolutional networks. ArXiv:2005.04081 [Physics, Stat]. http://arxiv.org/abs/2005.04081
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Mehrotra, S., Rahimian, H., Barah, M., Luo, F., & Schantz, K. (2020 May 02). A model of supply-chain decisions for resource sharing with an application to ventilator allocation to combat COVID-19. Naval Research Logistics (NRL). https://doi.org/10.1002/nav.21905
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Thome, J., Coogan, A., Fischer, M., Tucha, O., & Faltraco, F. (2020). Challenges for mental health services during the 2020 Covid‐19 outbreak in Germany. Psychiatry and Clinical Neurosciences, pcn.13019. https://doi.org/10.1111/pcn.13019
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Yao, H., Chen, J., Zhao, M., Qiu, J., Koenen, K. C., Stewart, R., Mellor, D., & Xu, Y. (2020). Mitigating mental health consequences during the COVID ‐19 outbreak: Lessons from China. Psychiatry and Clinical Neurosciences, pcn.13018. https://doi.org/10.1111/pcn.13018
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Riblet, N. B., Stevens, S. P., Watts, B. V., & Shiner, B. (2020). A pandemic of Body, Mind, and Spirit: The Burden of “Social Distancing” in Rural Communities During an Era of Heightened Suicide Risk. The Journal of Rural Health, jrh.12456. https://doi.org/10.1111/jrh.12456
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Casas, R. S., Cooper, J. L., & Hempel, E. V. (2020). COVID‐19 risk triage: Engaging residents in telephonic screening. Medical Education, medu.14211. https://doi.org/10.1111/medu.14211
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Yoshioka‐Maeda, K., Motegi, R. I., & Honda, C. (2020). Preventing the dysfunction of public health centers responding to COVID‐19 by focusing on public health nurses in Japan. Journal of Advanced Nursing, jan.14409. https://doi.org/10.1111/jan.14409
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www.nature.com www.nature.com
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Li, A., Zhou, L., Su, Q., Cornelius, S. P., Liu, Y.-Y., Wang, L., & Levin, S. A. (2020). Evolution of cooperation on temporal networks. Nature Communications, 11(1), 1–9. https://doi.org/10.1038/s41467-020-16088-w
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Roland, L. T., Gurrola, J. G., Loftus, P. A., Cheung, S. W., & Chang, J. L. (2020). Smell and taste symptom‐based predictive model for COVID‐19 diagnosis. International Forum of Allergy & Rhinology, alr.22602. https://doi.org/10.1002/alr.22602
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journals.plos.org journals.plos.org
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Rivkind, A., Schreier, H., Brenner, N., & Barak, O. (2020). Scale free topology as an effective feedback system. PLOS Computational Biology, 16(5), e1007825. https://doi.org/10.1371/journal.pcbi.1007825
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psycnet.apa.org psycnet.apa.org
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Can we count on parents to help their children learn at home? (2020, May 8). Evidence for Action. https://blogs.unicef.org/evidence-for-action/can-we-count-on-parents-to-help-their-children-learn-at-home/
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Wang, C., Li, W., Drabek, D. et al. A human monoclonal antibody blocking SARS-CoV-2 infection. Nat Commun 11, 2251 (2020). https://doi.org/10.1038/s41467-020-16256-y
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jamanetwork.com jamanetwork.com
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Gostin, L. O. (2020). COVID-19 Reveals Urgent Need to Strengthen the World Health Organization. JAMA Health Forum, 1(4), e200559–e200559. https://doi.org/10.1001/jamahealthforum.2020.0559
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jamanetwork.com jamanetwork.com
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Nundy, S., & Patel, K. K. (2020). Hospital-at-Home to Support COVID-19 Surge—Time to Bring Down the Walls? JAMA Health Forum, 1(5), e200504–e200504. https://doi.org/10.1001/jamahealthforum.2020.0504
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jamanetwork.com jamanetwork.com
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Steinbrook, R. (2020). Contact Tracing, Testing, and Control of COVID-19—Learning From Taiwan. JAMA Internal Medicine. https://doi.org/10.1001/jamainternmed.2020.2072
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Inglesby, T. V. (2020). Public Health Measures and the Reproduction Number of SARS-CoV-2. JAMA. https://doi.org/10.1001/jama.2020.7878
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jamanetwork.com jamanetwork.com
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Khullar, D., Bond, A. M., & Schpero, W. L. (2020). COVID-19 and the Financial Health of US Hospitals. JAMA. https://doi.org/10.1001/jama.2020.6269
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www.nejm.org www.nejm.org
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Zagury-Orly, I., & Schwartzstein, R. M. (2020). Covid-19—A Reminder to Reason. New England Journal of Medicine, NEJMp2009405. https://doi.org/10.1056/NEJMp2009405
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catalyst.nejm.org catalyst.nejm.org
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Guney S., Daniels C., & Childers Z.. (2020 April 30). Using AI to Understand the Patient Voice During the Covid-19 Pandemic. Catalyst Non-Issue Content, 1(2). https://doi.org/10.1056/CAT.20.0103
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Dunn, C. G., Kenney, E., Fleischhacker, S. E., & Bleich, S. N. (2020). Feeding Low-Income Children during the Covid-19 Pandemic. New England Journal of Medicine, 382(18), e40. https://doi.org/10.1056/NEJMp2005638
Tags
- federal nutrition
- social distancing
- School Breakfast Program
- food insecurity
- food
- government
- COVID-19
- psychological distress
- risk of infection
- is:article
- access
- funding
- lang:en
- federal aid
- National School Lunch Program
- children
- transmission reduction
- USA
- adaptation
- financial assistance
- low-income
- solution
- health effect
Annotators
URL
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www.nejm.org www.nejm.org
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Chu, H. Y., Englund, J. A., Starita, L. M., Famulare, M., Brandstetter, E., Nickerson, D. A., Rieder, M. J., Adler, A., Lacombe, K., Kim, A. E., Graham, C., Logue, J., Wolf, C. R., Heimonen, J., McCulloch, D. J., Han, P. D., Sibley, T. R., Lee, J., Ilcisin, M., … Bedford, T. (2020). Early Detection of Covid-19 through a Citywide Pandemic Surveillance Platform. New England Journal of Medicine, NEJMc2008646. https://doi.org/10.1056/NEJMc2008646
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www.nature.com www.nature.com
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West, R., Michie, S., Rubin, G. J., & Amlôt, R. (2020). Applying principles of behaviour change to reduce SARS-CoV-2 transmission. Nature Human Behaviour, 1–9. https://doi.org/10.1038/s41562-020-0887-9
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arxiv.org arxiv.org
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Nguyen, C. T., Saputra, Y. M., Van Huynh, N., Nguyen, N.-T., Khoa, T. V., Tuan, B. M., Nguyen, D. N., Hoang, D. T., Vu, T. X., Dutkiewicz, E., Chatzinotas, S., & Ottersten, B. (2020). Enabling and Emerging Technologies for Social Distancing: A Comprehensive Survey. ArXiv:2005.02816 [Physics]. http://arxiv.org/abs/2005.02816
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Robson, D. (n.d.). The fear of coronavirus is changing our psychology. Retrieved May 7, 2020, from https://www.bbc.com/future/article/20200401-covid-19-how-fear-of-coronavirus-is-changing-our-psychology
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science.sciencemag.org science.sciencemag.org
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Drew, D. A., Nguyen, L. H., Steves, C. J., Menni, C., Freydin, M., Varsavsky, T., Sudre, C. H., Cardoso, M. J., Ourselin, S., Wolf, J., Spector, T. D., Chan, A. T., & Consortium§, C. (2020). Rapid implementation of mobile technology for real-time epidemiology of COVID-19. Science. https://doi.org/10.1126/science.abc0473
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www.thelancet.com www.thelancet.com
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Lipsitch, M., Perlman, S., & Waldor, M. K. (2020). Testing COVID-19 therapies to prevent progression of mild disease. The Lancet Infectious Diseases, 0(0). https://doi.org/10.1016/S1473-3099(20)30372-8
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www.thelancet.com www.thelancet.com
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Psychiatry, T. L. (2020). Mental health and COVID-19: Change the conversation. The Lancet Psychiatry, 0(0). https://doi.org/10.1016/S2215-0366(20)30194-2
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www.thelancet.com www.thelancet.com
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Wells, C. R., Stearns, J. K., Lutumba, P., & Galvani, A. P. (2020). COVID-19 on the African continent. The Lancet Infectious Diseases, 0(0). https://doi.org/10.1016/S1473-3099(20)30374-1
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blogs.lse.ac.uk blogs.lse.ac.uk
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The Coronavirus (COVID-19) outbreak highlights serious deficiencies in scholarly communication. (2020, March 5). Impact of Social Sciences. https://blogs.lse.ac.uk/impactofsocialsciences/2020/03/05/the-coronavirus-covid-19-outbreak-highlights-serious-deficiencies-in-scholarly-communication/
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journals.plos.org journals.plos.org
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Ross-Hellauer, T., Tennant, J. P., Banelytė, V., Gorogh, E., Luzi, D., Kraker, P., Pisacane, L., Ruggieri, R., Sifacaki, E., & Vignoli, M. (2020). Ten simple rules for innovative dissemination of research. PLOS Computational Biology, 16(4), e1007704. https://doi.org/10.1371/journal.pcbi.1007704
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www.thelancet.com www.thelancet.com
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Graeden, E., Carlson, C., & Katz, R. (2020). Answering the right questions for policymakers on COVID-19. The Lancet Global Health, 0(0). https://doi.org/10.1016/S2214-109X(20)30191-1
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www.nature.com www.nature.com
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Desai, A., Warner, J., Kuderer, N., Thompson, M., Painter, C., Lyman, G., & Lopes, G. (2020). Crowdsourcing a crisis response for COVID-19 in oncology. Nature Cancer, 1–4. https://doi.org/10.1038/s43018-020-0065-z
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www.cmu.edu www.cmu.edu
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Bruine De Bruin, W., Fischhoff, B., Brilliant, L., & Caruso, D. (2006). Expert judgments of pandemic influenza risks. Global Public Health, 1(2), 179–194. https://doi.org/10.1080/17441690600673940
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Orcutt, M., Patel, P., Burns, R., Hiam, L., Aldridge, R., Devakumar, D., Kumar, B., Spiegel, P., & Abubakar, I. (2020). Global call to action for inclusion of migrants and refugees in the COVID-19 response. The Lancet, 0(0). https://doi.org/10.1016/S0140-6736(20)30971-5
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jamanetwork.com jamanetwork.com
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Butler, S. M. (2020). After COVID-19—Thinking Differently About Running the Health Care System. JAMA Health Forum, 1(4), e200478–e200478. https://doi.org/10.1001/jamahealthforum.2020.0478
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www.medrxiv.org www.medrxiv.org
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Shental, N., Levy, S., Skorniakov, S., Wuvshet, V., Shemer-Avni, Y., Porgador, A., & Hertz, T. (2020). Efficient high throughput SARS-CoV-2 testing to detect asymptomatic carriers. MedRxiv, 2020.04.14.20064618. https://doi.org/10.1101/2020.04.14.20064618
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- China
- international
- supply chain
- shift
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- public health
- transmission
- spread
- misinformation
- COVID-19
- vaccination
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