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  1. Oct 2021
    1. Using The Global Relationship Graph To Examine Claims About Covid-19 Vaccination And Infertility Or Bell’s Palsy – The GDELT Project. (n.d.). Retrieved May 14, 2021, from https://blog.gdeltproject.org/using-the-global-relationship-graph-to-examine-claims-about-covid-19-vaccination-and-infertility-or-bells-palsy/

    2. Using The Global Relationship Graph To Examine Claims About Covid-19 Vaccination And Infertility Or Bell's Palsy
    3. Using the Global Relationship Graph's (GRG) Realtime Verb-Centered NGram Pilot, what can we learn about claims in English language media coverage about links between Covid-19 vaccinations and infertility or Bell's Palsy? The query below searches across the GRG, which today totals more than 850M relationships across English language news coverage dating back to October 27, 2020:
    1. Kupferschmidt, K., VogelMar. 27, G., 2021, & Am, 10:20. (2021, March 27). A rare clotting disorder may cloud the world’s hopes for AstraZeneca’s COVID-19 vaccine. Science | AAAS. https://www.sciencemag.org/news/2021/03/rare-clotting-disorder-may-cloud-worlds-hopes-astrazenecas-covid-19-vaccine

    2. A rare clotting disorder may cloud the world’s hopes for AstraZeneca’s COVID-19 vaccine
    3. Many European countries suspended use of AstraZeneca’s vaccine earlier this month following initial reports of the symptoms, which have led to at least 15 deaths. Most resumed vaccinations after the European Medicines Agency (EMA) recommended doing so on 18 March, saying the benefits of the vaccine outweigh any risks. EMA is continuing to investigate the matter and will convene a wide-ranging committee of experts on 29 March.
    1. The Conspiracy Theory Handbook | Center For Climate Change Communication. (n.d.). Retrieved March 3, 2021, from https://www.climatechangecommunication.org/conspiracy-theory-handbook/

    2. The Conspiracy Theory Handbook
    3. Conspiracy theories attempt to explain events as the secretive plots of powerful people. While conspiracy theories are not typically supported by evidence, this doesn’t stop them from blossoming. Conspiracy theories damage society in a number of ways. To help minimise these harmful effects, The Conspiracy Theory Handbook, by Stephan Lewandowsky and John Cook, explains why conspiracy theories are so popular, how to identify the traits of conspiratorial thinking, and what are effective response strategies.
    1. Serra-Garcia, M., & Gneezy, U. (2021). Nonreplicable publications are cited more than replicable ones. Science Advances, 7(21), eabd1705. https://doi.org/10.1126/sciadv.abd1705

    2. Nonreplicable publications are cited more than replicable ones
    3. We use publicly available data to show that published papers in top psychology, economics, and general interest journals that fail to replicate are cited more than those that replicate. This difference in citation does not change after the publication of the failure to replicate. Only 12% of postreplication citations of nonreplicable findings acknowledge the replication failure. Existing evidence also shows that experts predict well which papers will be replicated. Given this prediction, why are nonreplicable papers accepted for publication in the first place? A possible answer is that the review team faces a trade-off. When the results are more “interesting,” they apply lower standards regarding their reproducibility.
    1. Emary, K. R. W., Golubchik, T., Aley, P. K., Ariani, C. V., Angus, B., Bibi, S., Blane, B., Bonsall, D., Cicconi, P., Charlton, S., Clutterbuck, E. A., Collins, A. M., Cox, T., Darton, T. C., Dold, C., Douglas, A. D., Duncan, C. J. A., Ewer, K. J., Flaxman, A. L., … Pollard, A. J. (2021). Efficacy of ChAdOx1 nCoV-19 (AZD1222) vaccine against SARS-CoV-2 variant of concern 202012/01 (B.1.1.7): an exploratory analysis of a randomised controlled trial. The Lancet, 0(0). https://doi.org/10.1016/S0140-6736(21)00628-0


    2. Efficacy of ChAdOx1 nCoV-19 (AZD1222) vaccine against SARS-CoV-2 variant of concern 202012/01 (B.1.1.7): an exploratory analysis of a randomised controlled trial
    3. SummaryBackgroundA new variant of SARS-CoV-2, B.1.1.7, emerged as the dominant cause of COVID-19 disease in the UK from November, 2020. We report a post-hoc analysis of the efficacy of the adenoviral vector vaccine, ChAdOx1 nCoV-19 (AZD1222), against this variant.MethodsVolunteers (aged ≥18 years) who were enrolled in phase 2/3 vaccine efficacy studies in the UK, and who were randomly assigned (1:1) to receive ChAdOx1 nCoV-19 or a meningococcal conjugate control (MenACWY) vaccine, provided upper airway swabs on a weekly basis and also if they developed symptoms of COVID-19 disease (a cough, a fever of 37·8°C or higher, shortness of breath, anosmia, or ageusia). Swabs were tested by nucleic acid amplification test (NAAT) for SARS-CoV-2 and positive samples were sequenced through the COVID-19 Genomics UK consortium. Neutralising antibody responses were measured using a live-virus microneutralisation assay against the B.1.1.7 lineage and a canonical non-B.1.1.7 lineage (Victoria). The efficacy analysis included symptomatic COVID-19 in seronegative participants with a NAAT positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to vaccine received. Vaccine efficacy was calculated as 1 − relative risk (ChAdOx1 nCoV-19 vs MenACWY groups) derived from a robust Poisson regression model. This study is continuing and is registered with ClinicalTrials.gov, NCT04400838, and ISRCTN, 15281137.FindingsParticipants in efficacy cohorts were recruited between May 31 and Nov 13, 2020, and received booster doses between Aug 3 and Dec 30, 2020. Of 8534 participants in the primary efficacy cohort, 6636 (78%) were aged 18–55 years and 5065 (59%) were female. Between Oct 1, 2020, and Jan 14, 2021, 520 participants developed SARS-CoV-2 infection. 1466 NAAT positive nose and throat swabs were collected from these participants during the trial. Of these, 401 swabs from 311 participants were successfully sequenced. Laboratory virus neutralisation activity by vaccine-induced antibodies was lower against the B.1.1.7 variant than against the Victoria lineage (geometric mean ratio 8·9, 95% CI 7·2–11·0). Clinical vaccine efficacy against symptomatic NAAT positive infection was 70·4% (95% CI 43·6–84·5) for B.1.1.7 and 81·5% (67·9–89·4) for non-B.1.1.7 lineages.InterpretationChAdOx1 nCoV-19 showed reduced neutralisation activity against the B.1.1.7 variant compared with a non-B.1.1.7 variant in vitro, but the vaccine showed efficacy against the B.1.1.7 variant of SARS-CoV-2.
    1. Home - COVID 19 scenario model hub. (n.d.). Retrieved July 5, 2021, from https://covid19scenariomodelinghub.org/

    2. Scenario Modeling Hub
    3. Even the best models of emerging infections struggle to give accurate forecasts at time scales greater than 3-4 weeks due to unpredictable drivers such as a changing policy environment, behavior change, the development of new control measures, and stochastic events. However, policy decisions around the course of emerging infections often require projections in the time frame of months. The goal of long-term projections is to compare outbreak trajectories under different scenarios, as opposed to offering a specific, unconditional estimate of what “will” happen.
    1. replicationnetwork. (2021, May 18). DUAN & REED: How Are Meta-Analyses Different Across Disciplines? The Replication Network. https://replicationnetwork.com/2021/05/18/duan-reed-how-are-meta-analyses-different-across-disciplines/

    2. How Are Meta-Analyses Different Across Disciplines?
    3. Recently, one of us gave a workshop on how to conduct meta-analyses. The workshop was attended by participants from a number of different disciplines, including economics, finance, psychology, management, and health sciences. During the course of the workshop, it became apparent that different disciplines conduct meta-analyses differently. While there is a vague awareness that this is the case, we are unaware of any attempts to quantify those differences. That is the motivation for this blog.
    1. Shahsavari, S., Holur, P., Wang, T., Tangherlini, T. R., & Roychowdhury, V. (2020). Conspiracy in the time of corona: automatic detection of emerging COVID-19 conspiracy theories in social media and the news. Journal of Computational Social Science, 3(2), 279–317. https://doi.org/10.1007/s42001-020-00086-5

    2. Conspiracy in the time of corona: automatic detection of emerging COVID-19 conspiracy theories in social media and the news
    3. Rumors and conspiracy theories thrive in environments of low confidence and low trust. Consequently, it is not surprising that ones related to the COVID-19 pandemic are proliferating given the lack of scientific consensus on the virus’s spread and containment, or on the long-term social and economic ramifications of the pandemic. Among the stories currently circulating in US-focused social media forums are ones suggesting that the 5G telecommunication network activates the virus, that the pandemic is a hoax perpetrated by a global cabal, that the virus is a bio-weapon released deliberately by the Chinese, or that Bill Gates is using it as cover to launch a broad vaccination program to facilitate a global surveillance regime. While some may be quick to dismiss these stories as having little impact on real-world behavior, recent events including the destruction of cell phone towers, racially fueled attacks against Asian Americans, demonstrations espousing resistance to public health orders, and wide-scale defiance of scientifically sound public mandates such as those to wear masks and practice social distancing, countermand such conclusions. Inspired by narrative theory, we crawl social media sites and news reports and, through the application of automated machine-learning methods, discover the underlying narrative frameworks supporting the generation of rumors and conspiracy theories. We show how the various narrative frameworks fueling these stories rely on the alignment of otherwise disparate domains of knowledge, and consider how they attach to the broader reporting on the pandemic. These alignments and attachments, which can be monitored in near real time, may be useful for identifying areas in the news that are particularly vulnerable to reinterpretation by conspiracy theorists. Understanding the dynamics of storytelling on social media and the narrative frameworks that provide the generative basis for these stories may also be helpful for devising methods to disrupt their spread.
    1. CohenMay. 6, J., 2021, & Pm, 2:45. (2021, May 6). Further evidence supports controversial claim that SARS-CoV-2 genes can integrate with human DNA. Science | AAAS. https://www.sciencemag.org/news/2021/05/further-evidence-offered-claim-genes-pandemic-coronavirus-can-integrate-human-dna

    2. Further evidence supports controversial claim that SARS-CoV-2 genes can integrate with human DNA
    3. A team of prominent scientists has doubled down on its controversial hypothesis that genetic bits of the pandemic coronavirus can integrate into our chromosomes and stick around long after the infection is over. If they are right—skeptics have argued that their results are likely lab artifacts—the insertions could explain the rare finding that people can recover from COVID-19 but then test positive for SARS-CoV-2 again months later.
    1. Blomberg, B., Mohn, K. G.-I., Brokstad, K. A., Zhou, F., Linchausen, D. W., Hansen, B.-A., Lartey, S., Onyango, T. B., Kuwelker, K., Sævik, M., Bartsch, H., Tøndel, C., Kittang, B. R., Cox, R. J., & Langeland, N. (2021). Long COVID in a prospective cohort of home-isolated patients. Nature Medicine, 1–7. https://doi.org/10.1038/s41591-021-01433-3

    2. Long COVID in a prospective cohort of home-isolated patients
    3. Long COVID in a prospective cohort of home-isolated patients
    4. Long-term complications after coronavirus disease 2019 (COVID-19) are common in hospitalized patients, but the spectrum of symptoms in milder cases needs further investigation. We conducted a long-term follow-up in a prospective cohort study of 312 patients—247 home-isolated and 65 hospitalized—comprising 82% of total cases in Bergen during the first pandemic wave in Norway. At 6 months, 61% (189/312) of all patients had persistent symptoms, which were independently associated with severity of initial illness, increased convalescent antibody titers and pre-existing chronic lung disease. We found that 52% (32/61) of home-isolated young adults, aged 16–30 years, had symptoms at 6 months, including loss of taste and/or smell (28%, 17/61), fatigue (21%, 13/61), dyspnea (13%, 8/61), impaired concentration (13%, 8/61) and memory problems (11%, 7/61). Our findings that young, home-isolated adults with mild COVID-19 are at risk of long-lasting dyspnea and cognitive symptoms highlight the importance of infection control measures, such as vaccination.
    1. BigQuery + UDF = Identifying The Earliest Glimmers Of Covid-19 – The GDELT Project. (n.d.). Retrieved May 14, 2021, from https://blog.gdeltproject.org/bigquery-udf-identifying-the-earliest-glimmers-of-covid-19/

    2. BigQuery + UDF = Identifying The Earliest Glimmers Of Covid-19
    3. The GKG 2.0 is essentially a realtime metadata index over the world's news in 65 languages dating back to 2015. A typical use case is to filter it to identify coverage mentioning a specific topic or location or combination of both. However, a simple filter that just looks for articles containing a given topic in the V2Themes field and a given location in the V2Locations field will yield a lot of irrelevant matches, since the topic of interest might be mentioned at the start of the article and the location of interest mentioned in an unrelated context at the bottom. Thus, when BigQuery first debuted the ability to use custom JavaScript User Defined Functions (UDF's), we showcased how a simple UDF could be used to parse through the V2Locations field to identify each distinct location mention in the article, then parse the V2Themes field and assign each theme mention to the nearest location mention in the text within a given window. In other words, it takes each location mention in an article and compiles a list of the themes mentioned within a given number of characters of that location in the text under the assumption that if "quarantine" is mentioned within a few words of "California" they are potentially related.
    1. Coronavirus Pandemic Data Explorer. (n.d.). Our World in Data. Retrieved March 3, 2021, from https://ourworldindata.org/coronavirus-data-explorer

      is:webpage lang:en COVID-19 graph case death Germany Sweden UK Afghanistan Africa Albania Algeria Andorra Angola Anguilla Antigua Barbuda Argentina Armenia Asia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Colombia Comoros Congo Costa Rica Cote d'ivoire Croatia Cuba Cyprus Czechia Democratic Republic of Congo Denmark Djobouti Dominica Dominician Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Eswatini Ethiopia Europe Europian Union Faeroe Islands Falkland Islands Fiji Finland France Gabon Gambia Georgia Ghana Gibraltar Greece Greenland Grenada Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Honduras Hong Kong Hungary Iceland India Indonesia Iran Iraq Ireland Isle of Man Israel Italy Jamaica Japan Jersey Jordan Kazakhstan Kenya Kosovo Kuwait Kyrgyzstan Laos Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Macao Madagascar Malawi Malaysia Maldives Mali Malta Mashall Islands Mauritania Mauritius Mexico Micronesia Moldova Monaco Mongolia Montenegro Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria North America North Macedonia Northern Cyprus Norway Oceania Oman Pakistan Palestine Panama Papua New Guinea Paraguay Peru Philipines Poland Portugal Qatar Romania Russia Rwanda Saint Helena Saint Kitts and Nevis Saint Lucia Saint Vincent Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa South America South Korea South Sudan Spain Sri Lanka Sudan Suriname Switzerland Syria Taiwan Tajikistan Tanzania Thailand Timor Togo Trinidad Tobago Tunisia Turkey Turks and Caicos Islands Uganda Ukraine United Arab Emirates USA Uruguay Uzbekistan Vanuatu Vatican Venezuela Vietnam World Yemen Zambia Zimbabwe test vaccine chart map table data case fatality rate mortality
    2. Coronavirus PandemicData Explorer




    1. Collective Intelligence. (2020, July 18). SAGE Publications Ltd. https://uk.sagepub.com/en-gb/eur/collective-intelligence/journal203713

    2. Collective Intelligence
    3. Collective Intelligence, co-published by SAGE and the Association for Computing Machinery (ACM), with the collaboration of Nesta, is a global, peer-reviewed, open-access journal that publishes trans-disciplinary work bearing on collective intelligence across the disciplines. The journal embraces a policy of creative rigor in the study of collective intelligence to facilitate the discovery of principles that apply across scales and new ways of harnessing the collective to improve social, ecological, and economic outcomes. In that spirit, the journal encourages a broad-minded approach to collective performance. We welcome perspectives that emphasize traditional views of intelligence as well as optimality, satisficing, robustness, adaptability, and wisdom. In more technical terms, this includes issues related to collective output quality and assessment, aggregation of information and related topics (e.g., network structure and dynamics, higher-order vs. pairwise interactions, spatial and temporal synchronization, diversity, etc.), accumulation of information by individuals/components, environmental complexity, evolutionary considerations, and design of systems and platforms fostering collective intelligence.
    1. Heller, F. (2021, January 13). Spain to launch Whatsapp channel to fight vaccine disinformation. Www.Euractiv.Com. https://www.euractiv.com/section/digital/news/spain-to-launch-whatsapp-channel-to-fight-vaccine-disinformation/

    2. Spain to launch Whatsapp channel to fight vaccine disinformation
    3. Spain’s health ministry will soon launch a WhatsApp interactive channel to fight against disinformation on COVID-19 vaccines, El País reported. This should help reduce the percentage of Spaniards who still refuse to get vaccinated. EURACTIV’s partner EuroEfe reports.
    1. Announcing The Global Numeric Graph – The GDELT Project. (n.d.). Retrieved May 14, 2021, from https://blog.gdeltproject.org/announcing-the-global-numeric-graph/

    2. Announcing The Global Numeric Graph
    3. We are tremendously excited to announce today the debut of the GDELT Global Numeric Graph (GNG), which compiles appearances of numeric statements across worldwide online news coverage in 152 languages. Each article monitored by GDELT is scanned for all appearances of numbers, either in the numeric characters of the given language for all 152 languages or, for around 100 languages and growing, spelled numbers (ie "one million" or "fifty" in English). Each appearance is compiled along with a brief context of how the number was used and the articles that specific number-in-context was seen in. This inaugural release compiles nearly 3.8 billion numeric references across 152 languages dating back to January 1, 2020.
    1. Quantifying The COVID-19 Public Health Media Narrative Through TV & Radio News Analysis – The GDELT Project. (n.d.). Retrieved May 14, 2021, from https://blog.gdeltproject.org/quantifying-the-covid-19-public-health-media-narrative-through-tv-radio-news-analysis/

    2. Quantifying The COVID-19 Public Health Media Narrative Through TV & Radio News Analysis
    3. Quantifying The COVID-19 Public Health Media Narrative Through TV & Radio News Analysis
    4. How does the COVID-19 narrative differ across television, radio and online news and across outlets? Is COVID-19 being covered differently than past disease outbreaks like Ebola or Zika and what can we learn from those communication efforts that could help inform public health communication about the current pandemic? To help answer these critical questions, the M-DRC is working with GDELT to use Google’s Cloud Video and Cloud Speech To Text APIs to non-consumptively analyze selections of the Internet Archive’s Television News Archive and Radio News Archive in a secure research environment, analyzing in total more than 4.9 million minutes of television news across 1,113 days 2009-present and 2.5 million minutes of radio since the start of this year to create an open set of non-consumptive annotations to enable public health communication research on how the COVID-19 pandemic has been communicated to the public and how those communicative efforts compare with the pandemics of the past decade, including Cholera, Ebola, E. coli, Measles, MERS, Salmonella and Zika and a portion of the opioid epidemic.
    1. A Timeline Of Infection, Death And Vaccination Count Mentions In The News During Covid-19 Using The Global Numeric Graph – The GDELT Project. (n.d.). Retrieved May 14, 2021, from https://blog.gdeltproject.org/a-timeline-of-infection-death-and-vaccination-count-mentions-in-the-news-during-covid-19-using-the-global-numeric-graph/

    2. A Timeline Of Infection, Death And Vaccination Count Mentions In The News During Covid-19 Using The Global Numeric Graph
    3. Using the new Global Numeric Graph announced yesterday, which tracks global mentions of precise numeric counts in worldwide news coverage in 152 languages in realtime back to January 1, 2020, what does the Covid-19 pandemic look like in terms of how often disease-related numbers have appeared in the news? Using the simple queries below, we searched all appearances of numeric counts across English language news coverage monitored by GDELT from January 1, 2020 through May 9, 2021 and counted the total number of numeric statements per day that mentioned either "deaths/dead/died/dying" in context with the number, "infect*" or "vaccin*" to count how many numbers across the monitored English coverage each day were associated with these three topics. Note that this counts how many times per day a number was expressed in text alongside one of these three sets of keywords, not the actual death/infection/vaccination count itself. In other words, if an article states "more than 3,000 have died in the last 24 hours", we would record that the topic of death appeared alongside a number once in the article, not that 3,000 people died. In other words, we are looking at how prevalent death, infections and vaccinations were in global English language news coverage day by day over the course of the pandemic.
    1. Using The Global Quotation Graph To Examine Statements About Covid-19 Vaccination And Infertility Or Bell’s Palsy – The GDELT Project. (n.d.). Retrieved May 14, 2021, from https://blog.gdeltproject.org/using-the-global-quotation-graph-to-examine-statements-about-covid-19-vaccination-and-infertility-or-bells-palsy/

    2. Using the Global Quotation Graph (GQG), what can we learn about public statements quoted in English language online media about links between Covid-19 vaccinations and infertility or Bell's Palsy? The query below searches across the quote itself and the text immediately before and after it, searching the English portion of the full GQG, which totals 164 million quoted statements across 152 languages spanning January 1, 2020 through present: