Relevant bibliographies by topics / Evidence accumulation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Evidence accumulation'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Evidence accumulation"

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Melih, Prof Veysi, and Prof Yuksel Caner. "Identification Of Straightforward Aggregate And Divisia Fiscal Accumulation Adopting Board Evidence Inquiry." American Journal of Social Science and Education Innovations 01, no. 05 (December 25, 2019): 1–4. http://dx.doi.org/10.37547/tajssei/volume01issue05-01.

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Fred, Ana L. N., and Anil K. Jain. "Combining multiple clusterings using evidence accumulation." IEEE Transactions on Pattern Analysis and Machine Intelligence 27, no. 6 (June 2005): 835–50. http://dx.doi.org/10.1109/tpami.2005.113.

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Davidson, Jacob D., and Ahmed El Hady. "Foraging as an evidence accumulation process." PLOS Computational Biology 15, no. 7 (July 24, 2019): e1007060. http://dx.doi.org/10.1371/journal.pcbi.1007060.

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Ciolkowski, Marcus, and Jürgen Münch. "Accumulation and presentation of empirical evidence." ACM SIGSOFT Software Engineering Notes 30, no. 4 (July 2005): 1–3. http://dx.doi.org/10.1145/1082983.1083178.

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Karamched, Bhargav, Simon Stolarczyk, Zachary P. Kilpatrick, and Krešimir Josić. "Bayesian Evidence Accumulation on Social Networks." SIAM Journal on Applied Dynamical Systems 19, no. 3 (January 2020): 1884–919. http://dx.doi.org/10.1137/19m1283793.

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Lourenço, André, Samuel Rota Bulò, Nicola Rebagliati, Ana L. N. Fred, Mário A. T. Figueiredo, and Marcello Pelillo. "Probabilistic consensus clustering using evidence accumulation." Machine Learning 98, no. 1-2 (April 3, 2013): 331–57. http://dx.doi.org/10.1007/s10994-013-5339-6.

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Lambrechts, Anna, Vincent Walsh, and Virginie van Wassenhove. "Evidence Accumulation in the Magnitude System." PLoS ONE 8, no. 12 (December 5, 2013): e82122. http://dx.doi.org/10.1371/journal.pone.0082122.

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Veal, T. D., I. Mahboob, L. F. J. Piper, C. F. McConville, Hai Lu, and W. J. Schaff. "Indium nitride: Evidence of electron accumulation." Journal of Vacuum Science & Technology B: Microelectronics and Nanometer Structures 22, no. 4 (2004): 2175. http://dx.doi.org/10.1116/1.1771672.

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Barbosa, Leonardo S., Alexandra Vlassova, and Sid Kouider. "Prior expectations modulate unconscious evidence accumulation." Consciousness and Cognition 51 (May 2017): 236–42. http://dx.doi.org/10.1016/j.concog.2017.04.001.

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Palmqvist, Sebastian. "MULTIMODAL EVIDENCE FOR EARLY AMYLOID ACCUMULATION." Alzheimer's & Dementia 15, no. 7 (July 2019): P178. http://dx.doi.org/10.1016/j.jalz.2019.06.4376.

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Dissertations / Theses on the topic "Evidence accumulation"

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Camêlo, Felipe Diogo. "Investment decisions and capital accumulation: firm-level evidence from Brazil." reponame:Repositório Institucional do FGV, 2018. http://hdl.handle.net/10438/24314.

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Submitted by Felipe Diogo Camêlo (fdiogo.camelo@gmail.com) on 2018-07-05T15:41:51Z No. of bitstreams: 1 Tese_FelipeDiogoCamelo.pdf: 649864 bytes, checksum: 09e2d4e77981e76ab7aa60bb997240aa (MD5)
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Using firm-level data from an administrative Brazilian dataset, I document a few stylized facts regarding capital stock accumulation patterns and investment decisions. Finding evidence largely in favor of micro-level lumpiness of investment as it was found for American firms, I document that there are a few particularities in the behavior of Brazilian firms. First, I document that the distribution of the growth rate of capital is more dispersed, with “fatter” tails. Second, I also show that, as economic activity, the volume of investment and capital stock are more concentrated on a small number of firms, micro-level lumpiness might have a bigger role in understanding aggregate movements. Third, I show that the observable characteristics of Brazilian firms explain a lot more of sudden movements in capital growth when compared to the U.S., after controlling for industry specific characteristics and other variables. Fourth and last, I compute statistical measures related to the investment rate distribution, which show that investment at the firm-level seems to be even “lumpier” in Brazil, with firms investing less on average, while experiencing more episodes of investment spikes and periods of inaction.
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Morcos, Ari Simon. "Population dynamics in parietal cortex during evidence accumulation for decision-making." Thesis, Harvard University, 2016. http://nrs.harvard.edu/urn-3:HUL.InstRepos:33493459.

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Cortical circuits combine new inputs with ongoing activity during a variety of behaviors, including evidence accumulation during decision-making. However, the neural circuit mechanisms underlying how populations of neurons perform the computations necessary for this process and the dynamics which govern how neuronal populations change from moment-to-moment during evidence accumulation remain unclear. Here, we trained mice to perform several novel virtual-navigation decision tasks, including one which requires the accumulation of multiple, discrete evidence cues. As mice accumulated evidence, the posterior parietal cortex (PPC) transitioned between distinguishable and largely uncorrelated activity patterns, often involving mostly different sets of active neurons from moment-to-moment. These activity patterns contained task-relevant information distributed across the neuronal population. Because animals make decisions on single trials, we chose to analyze these activity patterns on a trial-by-trial basis. As single trials unfolded, each event — whether a new evidence cue or a behavioral choice — modified the dynamics of the PPC for seconds, even across trials. These events did not change the tonic activity of a specific set of neurons; rather, each event altered the probabilities that govern how one activity pattern transitions to the next, constraining the possible future patterns of activity. Thus, representations of ongoing events were influenced both by the sequence of previous evidence cues within the current trial and by the outcome of the previous trial, thereby generating multiple distinguishable activity patterns for the same level of accumulated evidence. These observations suggest that evidence accumulation does not rely upon the explicit competition between groups of neurons (as would be predicted by winner-take-all models), but instead reflects dynamical properties of the PPC that may instantiate a form of short-term memory consistent with reservoir computing.
Medical Sciences
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Kimura, Yuichi. "The role of big cities in human capital accumulation : Evidence from Thailand." Kyoto University, 2004. http://hdl.handle.net/2433/145327.

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Kyoto University (京都大学)
0048
新制・課程博士
博士(経済学)
甲第11126号
経博第196号
新制||経||194(附属図書館)
22695
UT51-2004-R2
京都大学大学院経済学研究科経済システム分析専攻
(主査)教授 藤田 昌久, 助教授 森 知也, 助教授 文 世一
学位規則第4条第1項該当
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Turkelson, Lynley. "The Effect of Doubt and Working Memory Load on Evidence Accumulation: A Neuropsychological Investigation." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1563527148499357.

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Burgener, Landon Kelly. "Temporal trends in West Antarctic accumulation rates: evidence from observed and simulated records." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3664.

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Reconstructed snow accumulation rate observations from five new firn cores show a statistically significant negative trend in accumulation rates over the past four decades across the central West Antarctic ice sheet. A negative temporal trend in accumulation is unexpected in light of rising surface temperatures and simulations run by GCMs. Both the magnitude of the mean accumulation rates and the range of interannual variability observed in the new records compares favorably to older records, suggesting that the new accumulation rate records may serve as a regional proxy for recent temporal trends in West Antarctic accumulation rates. The observed negative trend is likely the result of Southern Hemisphere high-latitude internal atmospheric dynamics, dominated by changes in the austral fall season. The well-documented positive trend in the Southern Annular Mode causes a low pressure center to form over the Amundsen Sea, which in turn produces lower accumulation rates across the western portion of the West Antarctic ice sheet. The new accumulation rate records are compared to several models/reanalyses to test the skill of simulated accumulation rate predictions. While the models/reanalyses and the new observations agree well in both mean and variability, the simulated records do not capture the full negative trend observed in the reconstructed records.
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GUANZIROLI, TOMAS. "TASK- HETEROGENEITY IN HUMAN CAPITAL ACCUMULATION: EVIDENCE FROM BRAZILIAN MATCHED EMPLOYER-EMPLOYEE DATA." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2014. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=25505@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO
Esta dissertação estuda se existem heterogeneidades no processo de acumulação de capital humano durante o trabalho. Utilizando microdados em painel da RAIS e a descrição de ocupações com base em suas tarefas, nós propomos o conceito de experiência em tarefas em equações de salário. Primeiro, apresentamos um modelo no qual retorno a experiência é heterogêneo entre trabalhadores. Depois, nós estimamos a equação de salário interpretando o retorno a experiência como a taxa média na qual trabalhadores transformam o tempo em trabalhos passados em produtividade no trabalho corrente. Os resultados mostram, de forma robusta, que o parâmetro associado à experiência analítica é maior que os parâmetros associados à experiência rotineira, por exemplo. Nosso modelo ajuda a compreender a importância e limitações deste resultado.
This dissertation studies if there are heterogeneities in the human capital accumulation process while on the job. Using unique Brazilian employer-employee panel data and task description of fourdigit occupations, we propose the concept of task experience in log wage equations. We first present a model in which returns to experience are heterogeneous across workers. Then, we estimate the log-wage equations interpreting the returns to experience as the average rate in which workers have their time at past work transformed into productivity in the current job. The results robustly show that the parameter related to analytical experience is greater than the parameters related to routine or other task experiences. Our model helps understanding the importance and limitations of these findings.
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Pfeffer, Thomas [Verfasser], and Tobias [Akademischer Betreuer] Donner. "Neuromodulation and the timescale of evidence accumulation during perceptual decision-making / Thomas Pfeffer ; Betreuer: Tobias Donner." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2018. http://d-nb.info/1164593595/34.

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Günçavdi, Öner. "Financial factors in the determination of private fixed capital accumulation : theory and evidence from the Turkish economy." Thesis, University of Nottingham, 1996. http://eprints.nottingham.ac.uk/14496/.

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This is an analysis of the investment behaviour of Turkish firms at the aggregate and sectoral levels. Despite the growing literature of empirical private investment studies, a theory-based approach to modelling investment is rare both for developing countries in general and for Turkey in particular. One of the most commonly used modelling strategies is to adapt the main elements of the neoclassical accelerator model subject to additional structural modifications for a developing country. However, many of these studies are eclectic in the sense that they are not based on any specification of the microeconomic optimisation problem of firms. The central purpose of the thesis is to develop econometrically estimateable investment functions based on a sound microeconomic framework. This study theoretically examines both the investment behaviour of firms and the role of financial decisions in investment behaviour in earlier chapters. Subsequent empirical chapters are built upon the main findings of the theoretical chapters, and accommodate three empirical models, all of which originate from an explicit optimisation problem of a representative firm. The first empirical model is derived from the cost minimisation of the firm subject to a given level of demand in the output market and two alternative production technology assumptions (namely putty-putty and putty-clay assumptions). The second model recognises the presence of adjustment costs of the capital stock, and develops an error-correction representation of an investment model from an quadratic cost function minimisation. These first two models analyse the roles of the neoclassical determinants of investment (the accelerator and the relative cost of capital) and credit constraints resulting from imperfections in capital markets in Turkey. However, the inclusion of the financial variable is less sound in these two models. The significance of capital market imperfections in the forms of a rising cost schedule of borrowing and quantitative constraints is the subjects of the third model. A dynamic model is developed through a maximisation of the intertemporal discounted cash flow of a representative firm subject to capital market imperfections, borrowing constraints and capital adjustment costs. An Euler equation for the rate of capital accumulation is derived by re-arranging the first-order condition for capital, which is influenced by the binding borrowing constraint through an unobservable shadow price. These three models are applied to annual aggregate and sectoral data from Turkey. The empirical findings of this thesis suggest that fiscal and monetary policies influence investment behaviour both via the relative cost of capital and via credit availability to the private sector in Turkey. In particular, the empirical results imply that a high interest rate policy in an imperfect capital market imposing extra cost on the market rate through the risk premium may have discouraging effects on investment decisions either through its impact on the user cost of capital or through the risk premium component of cost of borrowing as in the third model. However, high interest rate policies may also affect credit availability as postulated in the McKinnon-Shaw hypothesis.
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Söllner, Anke [Verfasser], and Arndt [Akademischer Betreuer] Bröder. "Contrasting frameworks of multi-attribute decision making: Multiple strategies, connectionist network, or evidence accumulation? / Anke Söllner. Betreuer: Arndt Bröder." Mannheim : Universitätsbibliothek Mannheim, 2015. http://d-nb.info/1071803530/34.

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Letkiewicz, Jodi Christie. "Households’ Propensity to Meet the Capital Accumulation Ratio Over Time: Evidence from the 1992-2007 Surveys of Consumer Finance." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1282056704.

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Books on the topic "Evidence accumulation"

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Reinhart, Carmen M. Capital inflows and reserve accumulation: The recent evidence. Cambridge, MA: National Bureau of Economic Research, 2008.

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Lee, Chulhee. Health and wealth accumulation: Evidence from nineteenth-century America. Cambridge, Mass: National Bureau of Economic Research, 2003.

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Poterba, James M. Personal retirement saving programs and asset accumulation: Reconciling the evidence. Cambridge, MA: National Bureau of Economic Research, 1996.

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Bossone, Biagio. Financial infrastructure, group interests, and capital accumulation: Theory, evidence, and policy. [Washington, D.C.]: International Monetary Fund, Office of the Executive Director, 2003.

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Bond, Stephen. Capital accumulation and growth: A new look at the empirical evidence. Bonn, Germany: IZA, 2004.

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Beddies, Christian H. Investment, capital accumulation, and growth: Some evidence from the Gambia 1964-98. [Washington, D.C.]: International Monetary Fund, African Department, 1999.

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Hussain, Iftikhar. Household sector saving and wealth accumulation: Evidence from balance sheet and flow of funds data. London: Financial Services Authority, 2000.

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Berthélemy, Jean-Claude. The role of capital accumulation, adjustment, and structural change for economic take-off: Empirical evidence from African growth episodes. Paris: OECD, 1999.

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Domeland, Dorte. Trade And Human Capital Accumulation: Evidence From U.S. Immigrants. The World Bank, 2007. http://dx.doi.org/10.1596/1813-9450-4144.

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Levien, Michael. From Primitive Accumulation to Regimes of Dispossession. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198792444.003.0003.

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In order to analyze land alienation in contemporary India, Shapan Adnan follows a theoretical approach in which mechanisms of primitive accumulation are not restricted to use of force, but include land transfer by agreement, as well as indirect mechanisms that are concerned with very different objectives. Reviewing evidence on land grabs, resistance, and workforce trends, he argues that primitive accumulation under neoliberal globalization has not been substantially followed by the absorption of the dispossessed in regular capitalist employment. Adnan puts forward a set of hypotheses to explain why the self-employed constituted at least half or more of the Indian workforce over 1999–2012. While such trends indicate a partial and short-run divergence from the classic Marxian schema of the transition to capitalism, Adnan argues that, given ongoing trends in the national and global economy, the long run outcome in India remains an open question.
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Book chapters on the topic "Evidence accumulation"

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Matsuyama, Takashi, and Vincent Shang-Shouq Hwang. "Algorithms for Evidence Accumulation." In SIGMA, 99–151. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4899-0867-4_3.

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Almond, Russell G., Robert J. Mislevy, Linda S. Steinberg, Duanli Yan, and David M. Williamson. "The Evidence Accumulation Process." In Bayesian Networks in Educational Assessment, 467–505. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2125-6_13.

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Bulò, Samuel Rota, André Lourenço, Ana Fred, and Marcello Pelillo. "Pairwise Probabilistic Clustering Using Evidence Accumulation." In Lecture Notes in Computer Science, 395–404. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14980-1_38.

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Handl, Julia, and Joshua Knowles. "Evidence Accumulation in Multiobjective Data Clustering." In Lecture Notes in Computer Science, 543–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37140-0_41.

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Lourenço, André, Samuel Rota Bulò, Nicola Rebagliati, Ana Fred, Mário Figueiredo, and Marcello Pelillo. "Consensus Clustering Using Partial Evidence Accumulation." In Pattern Recognition and Image Analysis, 69–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38628-2_8.

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Ip, Horace H. S. "Visual Evidence Accumulation in Radiograph Inspection." In BMVC91, 202–9. London: Springer London, 1991. http://dx.doi.org/10.1007/978-1-4471-1921-0_26.

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Huk, Alexander C., Leor N. Katz, and Jacob L. Yates. "Accumulation of Evidence in Decision Making." In Encyclopedia of Computational Neuroscience, 1–4. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7320-6_309-1.

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Huk, Alexander C., Leor N. Katz, and Jacob L. Yates. "Accumulation of Evidence in Decision Making." In Encyclopedia of Computational Neuroscience, 1–4. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-7320-6_309-2.

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Lourenço, André, Samuel Rota Bulò, Ana Fred, and Marcello Pelillo. "Consensus Clustering with Robust Evidence Accumulation." In Lecture Notes in Computer Science, 307–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40395-8_23.

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Huk, Alexander C., Leor N. Katz, and Jacob L. Yates. "Accumulation of Evidence in Decision-Making." In Encyclopedia of Computational Neuroscience, 125–28. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4614-6675-8_309.

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Conference papers on the topic "Evidence accumulation"

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Hasperue, Waldo, and Laura Lanzarini. "Classification Rules Obtained from Evidence Accumulation." In 2007 29th International Conference on Information Technology Interfaces. IEEE, 2007. http://dx.doi.org/10.1109/iti.2007.4283764.

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Ip, Horace H. S. "Visual Evidence Accumulation in Radiograph Inspection." In British Machine Vision Conference 1991. Springer-Verlag London Limited, 1991. http://dx.doi.org/10.5244/c.5.26.

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Ciolkowski, Marcus, and Jürgen Münch. "Accumulation and presentation of empirical evidence." In the 2005 workshop. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1083174.1083178.

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Urai, Anne, Jan Willem de Gee, Konstantinos Tsetsos, and Tobias Donner. "Choice History Biases Subsequent Evidence Accumulation." In 2018 Conference on Cognitive Computational Neuroscience. Brentwood, Tennessee, USA: Cognitive Computational Neuroscience, 2018. http://dx.doi.org/10.32470/ccn.2018.1192-0.

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"Probabilistic Evidence Accumulation for Clustering Ensembles." In International Conference on Pattern Recognition Applications and Methods. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004267900580067.

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"Evidence Accumulation Clustering using Pairwise Constraints." In International Conference on Knowledge Discovery and Information Retrieval. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0004171902930299.

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"Weighted Evidence Accumulation Clustering Using Subsampling." In 6th International Workshop on Pattern Recognition in Information Systems. SciTePress - Science and and Technology Publications, 2006. http://dx.doi.org/10.5220/0002504501040116.

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Enders, Robert H., Andrzej K. Brodzik, and Michael R. Pellegrini. "Algebra of Dempster-Shafer evidence accumulation." In SPIE Defense and Security Symposium, edited by Ivan Kadar. SPIE, 2008. http://dx.doi.org/10.1117/12.784944.

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Lourenco, Andre, Ana L. N. Fred, and Anil K. Jain. "On the Scalability of Evidence Accumulation Clustering." In 2010 20th International Conference on Pattern Recognition (ICPR). IEEE, 2010. http://dx.doi.org/10.1109/icpr.2010.197.

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Duarte, F. Jorge, Ana L.N.Fred, Andre Lourenco, and M. Fatima Rodrigues. "Weighting Cluster Ensembles in Evidence Accumulation Clustering." In 2005 Purtuguese Conference on Artificial Intelligence. IEEE, 2005. http://dx.doi.org/10.1109/epia.2005.341287.

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Reports on the topic "Evidence accumulation"

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Shapiro, Matthew. Capital Utilization and Capital Accumulation: Theory and Evidence. Cambridge, MA: National Bureau of Economic Research, April 1986. http://dx.doi.org/10.3386/w1900.

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Reinhart, Carmen, and Vincent Reinhart. Capital Inflows and Reserve Accumulation: The Recent Evidence. Cambridge, MA: National Bureau of Economic Research, March 2008. http://dx.doi.org/10.3386/w13842.

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Lee, Chulhee. Health and Wealth Accumulation: Evidence from Nineteenth-Century America. Cambridge, MA: National Bureau of Economic Research, October 2003. http://dx.doi.org/10.3386/w10035.

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Jakobsen, Katrine, Kristian Jakobsen, Henrik Kleven, and Gabriel Zucman. Wealth Taxation and Wealth Accumulation: Theory and Evidence from Denmark. Cambridge, MA: National Bureau of Economic Research, March 2018. http://dx.doi.org/10.3386/w24371.

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Poterba, James, Steven Venti, and David Wise. Personal Retirement Saving Programs and Asset Accumulation: Reconciling the Evidence. Cambridge, MA: National Bureau of Economic Research, May 1996. http://dx.doi.org/10.3386/w5599.

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Odoemene, Onyekachi, Sashank Pisupati, Hien Nguyen, and Anne Churchland. Dataset from: Visual evidence accumulation guides decision-making in unrestrained mice. Cold Spring Harbor Laboratory, January 2020. http://dx.doi.org/10.14224/1.38944.

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Andrabi, Tahir, Benjamin Daniels, and Jishnu Das. Human Capital Accumulation and Disasters: Evidence from the Pakistan Earthquake of 2005. Research on Improving Systems of Education (RISE), May 2020. http://dx.doi.org/10.35489/bsg-rise-wp_2020/039.

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Bonilla-Mejía, Leonardo. Illegal Mining and Human Capital Accumulation: Evidence from the Colombian Gold Rush. Banco de la República de Colombia, May 2019. http://dx.doi.org/10.32468/dtseru.280.

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Andrabi, Tahir, Benjamin Daniels, and Jishnu Das. Human Capital Accumulation and Disasters: Evidence from the Pakistan Earthquake of 2005. Research on Improving Systems of Education (RISE), May 2020. http://dx.doi.org/10.35489/bsg-risewp_2020/039.

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We trace the effects of a devastating earthquake that occurred in Northern Pakistan in 2005. Using a new dataset from a survey conducted four years after the earthquake, we first show that the distance of the household from the fault line was not correlated with pre-existing household characteristics, while it was strongly predictive of earthquake-related damage and mortality. Through emergency relief aid, households living close to the fault line reported receiving substantial cash compensation that amounted to as much as 150% of their annual household consumption expenditure. Four years after the earthquake, there were no differences in public infrastructure, household or adult outcomes between areas close to and far from the fault line. However, children in their critical first thousand days at the time of the earthquake accumulated large height deficits, with the youngest the most affected. Children aged 3 through 15 at the time of the earthquake did not suffer growth shortfalls, but scored significantly worse on academic tests if they lived close to the fault line. Finally, children whose mothers completed primary education were fully protected against the emergence of a test score gap. We estimate that if these deficits continue to adult life, the affected children could stand to lose 15% of their lifetime earnings. Even when disasters are heavily compensated, human capital accumulation can be critically interrupted, with greater losses for already disadvantaged populations.
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10

Stall, Nathan M., Kevin A. Brown, Antonina Maltsev, Aaron Jones, Andrew P. Costa, Vanessa Allen, Adalsteinn D. Brown, et al. COVID-19 and Ontario’s Long-Term Care Homes. Ontario COVID-19 Science Advisory Table, January 2021. http://dx.doi.org/10.47326/ocsat.2021.02.07.1.0.

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Key Message Ontario long-term care (LTC) home residents have experienced disproportionately high morbidity and mortality, both from COVID-19 and from the conditions associated with the COVID-19 pandemic. There are several measures that could be effective in preventing COVID-19 outbreaks, hospitalizations, and deaths in Ontario’s LTC homes, if implemented. First, temporary staffing could be minimized by improving staff working conditions. Second, homes could be further decrowded by a continued disallowance of three- and four-resident rooms and additional temporary housing for the most crowded homes. Third, the risk of SARS-CoV-2 infection in staff could be minimized by approaches that reduce the risk of transmission in communities with a high burden of COVID-19. Summary Background The Province of Ontario has 626 licensed LTC homes and 77,257 long-stay beds; 58% of homes are privately owned, 24% are non-profit/charitable, 16% are municipal. LTC homes were strongly affected during Ontario’s first and second waves of the COVID-19 pandemic. Questions What do we know about the first and second waves of COVID-19 in Ontario LTC homes? Which risk factors are associated with COVID-19 outbreaks in Ontario LTC homes and the extent and death rates associated with outbreaks? What has been the impact of the COVID-19 pandemic on the general health and wellbeing of LTC residents? How has the existing Ontario evidence on COVID-19 in LTC settings been used to support public health interventions and policy changes in these settings? What are the further measures that could be effective in preventing COVID-19 outbreaks, hospitalizations, and deaths in Ontario’s LTC homes? Findings As of January 14, 2021, a total of 3,211 Ontario LTC home residents have died of COVID-19, totaling 60.7% of all 5,289 COVID-19 deaths in Ontario to date. There have now been more cumulative LTC home outbreaks during the second wave as compared with the first wave. The infection and death rates among LTC residents have been lower during the second wave, as compared with the first wave, and a greater number of LTC outbreaks have involved only staff infections. The growth rate of SARS-CoV-2 infections among LTC residents was slower during the first two months of the second wave in September and October 2020, as compared with the first wave. However, the growth rate after the two-month mark is comparatively faster during the second wave. The majority of second wave infections and deaths in LTC homes have occurred between December 1, 2020, and January 14, 2021 (most recent date of data extraction prior to publication). This highlights the recent intensification of the COVID-19 pandemic in LTC homes that has mirrored the recent increase in community transmission of SARS-CoV-2 across Ontario. Evidence from Ontario demonstrates that the risk factors for SARS-CoV-2 outbreaks and subsequent deaths in LTC are distinct from the risk factors for outbreaks and deaths in the community (Figure 1). The most important risk factors for whether a LTC home will experience an outbreak is the daily incidence of SARS-CoV-2 infections in the communities surrounding the home and the occurrence of staff infections. The most important risk factors for the magnitude of an outbreak and the number of resulting resident deaths are older design, chain ownership, and crowding. Figure 1. Anatomy of Outbreaks and Spread of COVID-19 in LTC Homes and Among Residents Figure from Peter Hamilton, personal communication. Many Ontario LTC home residents have experienced severe and potentially irreversible physical, cognitive, psychological, and functional declines as a result of precautionary public health interventions imposed on homes, such as limiting access to general visitors and essential caregivers, resident absences, and group activities. There has also been an increase in the prescribing of psychoactive drugs to Ontario LTC residents. The accumulating evidence on COVID-19 in Ontario’s LTC homes has been leveraged in several ways to support public health interventions and policy during the pandemic. Ontario evidence showed that SARS-CoV-2 infections among LTC staff was associated with subsequent COVID-19 deaths among LTC residents, which motivated a public order to restrict LTC staff from working in more than one LTC home in the first wave. Emerging Ontario evidence on risk factors for LTC home outbreaks and deaths has been incorporated into provincial pandemic surveillance tools. Public health directives now attempt to limit crowding in LTC homes by restricting occupancy to two residents per room. The LTC visitor policy was also revised to designate a maximum of two essential caregivers who can visit residents without time limits, including when a home is experiencing an outbreak. Several further measures could be effective in preventing COVID-19 outbreaks, hospitalizations, and deaths in Ontario’s LTC homes. First, temporary staffing could be minimized by improving staff working conditions. Second, the risk of SARS-CoV-2 infection in staff could be minimized by measures that reduce the risk of transmission in communities with a high burden of COVID-19. Third, LTC homes could be further decrowded by a continued disallowance of three- and four-resident rooms and additional temporary housing for the most crowded homes. Other important issues include improved prevention and detection of SARS-CoV-2 infection in LTC staff, enhanced infection prevention and control (IPAC) capacity within the LTC homes, a more balanced and nuanced approach to public health measures and IPAC strategies in LTC homes, strategies to promote vaccine acceptance amongst residents and staff, and further improving data collection on LTC homes, residents, staff, visitors and essential caregivers for the duration of the COVID-19 pandemic. Interpretation Comparisons of the first and second waves of the COVID-19 pandemic in the LTC setting reveal improvement in some but not all epidemiological indicators. Despite this, the second wave is now intensifying within LTC homes and without action we will likely experience a substantial additional loss of life before the widespread administration and time-dependent maximal effectiveness of COVID-19 vaccines. The predictors of outbreaks, the spread of infection, and deaths in Ontario’s LTC homes are well documented and have remained unchanged between the first and the second wave. Some of the evidence on COVID-19 in Ontario’s LTC homes has been effectively leveraged to support public health interventions and policies. Several further measures, if implemented, have the potential to prevent additional LTC home COVID-19 outbreaks and deaths.
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