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Covid & society
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Political and Social Correlates of Covid-19 MortalityDo political and social features of states help explain the evolving distribution of reported Covid-19deaths?https://wzb-ipi.github.io/corona/https://wzb-ipi.github.io/corona/WD_paper.pdf
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Global Access to Handwashing: Implications for COVID-19 Control in Low-Income CountriesHandwashing is a key component of guidance to reduce transmission of the SARS-CoV-2 virus, responsible for the COVID-19 pandemic. In low-income countries, access to handwashing facilities with soap and water is limited. Disparities in handwashing access should be incorporated into COVID-19 forecasting models when applied to low-income countries.https://ehp.niehs.nih.gov/doi/pdf/10.1289/EHP7200
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Epidemic modelling: ABMs vs other models
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Mathematical and computational approaches to epidemic modeling: a comprehensive review[...] We introduce major epidemic models in three directions, including mathematical models, complex network models, and agent-based models. We discuss the principles, applications, advantages, and limitations of these models.https://pubmed.ncbi.nlm.nih.gov/32288946/
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A Comparison of Agent-Based Models and Equation Based Models for Infectious Disease Epidemiology[...] Specifically,the ability of the agent-based model to capture heterogeneous mixing andagent interactions enables it to give a better overall view of an outbreak.We compare the performance of both models by simulating a measlesoutbreak in 33 different Irish towns and measuring the outcomes of thisoutbreakhttp://ceur-ws.org/Vol-2259/aics_5.pdf
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Comparing compartment and agent-based modelsInfectious diseases threaten the well-being of society through direct infection ofindividuals and billions of dollars in collateral damage. As a consequence, statisticalmodelling of infectious disease plays a critical role in answering important questionsabout prediction and inference, and additionally, contingency planning. Compartmentmodels (CMs) and agent-based models (AMs) are two common frameworks to diseasemodelling. Despite the differences between equation-based CMs and simulation-basedAMs, researchers have noted substantial similarities between the two frameworks. Weintend to combine the two into a “hybrid” framework. We focus on reconciling thestatistical differences between CMs and AMs. Specifically, we study a well-knowndisease framework, Susceptible-Infectious-Recovered, with both a CM-based and AM-based framework. We develop and prove conditions under which these two frameworkshave identical statistical behavior. We then extend this equivalence to a large class ofCM-AM pairs, which allows for a basis of comparison. Additionally, we examine therelationship between the number of agents and the number of runs in the SIR-AM,which allows for improved computational performance via parallelization. For futurework, we propose to extend our current work to all valid compartment models. Thiswill include the development of statistical tests to compare two models to one anotherin order to measure the differences between them. We will also introduce practical,statistical methods to speed up AM computation time. Finally, we will examine thenumber of agents required to obtain adequate results to create a statistically justifiedhybrid model that will simulate a global epidemic.http://www.stat.cmu.edu/~sgallagh/papers/gallagher_8-17.pdf
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Antibody tests / immunity certificates
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Modeling Exit Strategies from COVID-19 Lockdown with a Focus on Antibody Tests[...] We investigate the potential effects of a combination of measures such as continuation of hygienic constraints after leaving lockdown, isolation of infectious persons, repeated and adaptive short-term contact reductions and also large-scale use of antibody tests in order to know who can be assumed to be immune and participate at public life without constraints. We apply two commonly used modeling approaches: extended SEIR models formulated both as System Dynamics and Agent-Based Simulation, in order to get insight into the disease dynamics of a complete country like Germany and also into more detailed behavior of smaller regions. [...]not peer reviewedhttps://www.medrxiv.org/content/10.1101/2020.04.14.20063750v1
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[newspaper article] Germany won't use antibody tests until ethics are debatedImmunity passports' risk dividing society, with some moving about freely, with others shut at home, officials worry.outlines the ethical dimension of immunity certificates & indicates the societal / political relevance of the topichttps://www.aljazeera.com/news/2020/05/germany-won-antibody-tests-ethics-debated-200504163615628.html
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ABM & economics
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Agent-based models: understanding the economy from the bottom upThis article considers the strengths of agent-based modelling, which explains the behaviour of a system by simulating the behaviour of each individual ‘agent’ in it, and the ways that it can be used to help central banks understand the economy.https://www.bankofengland.co.uk/quarterly-bulletin/2016/q4/agent-based-models-understanding-the-economy-from-the-bottom-up
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The economy needs agent-based modellingshows the significant research desiderata of ABM in economics, against the backdrop of flawed models like DSGEhttps://www.nature.com/articles/460685a
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Covid ABMs comparisons
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ABM as a methodology
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Agent-based modelling as scientific method:
a case study analysing primate social behaviour
[...] This article demonstrates that this methodology can be applied to the biological sciences; agent-based models, like any other scientific hypotheses, can be tested, critiqued, generalized or specified. We review the state of the art for ABM as a methodology for biology and then present a case study based on the most widely published agent-based model in the biological sciences: Hemelrijk’s DomWorld, a model of primate social behaviour. [...]demonstrates the potential structure a methodological contribution could take https://ccl.northwestern.edu/2007/Bryson-etal-PTRS07.pdf
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Agent-based Models in Empirical ResearchAgent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first discuss the motivations for using agent-based models in both basic science and policy- oriented social research. Next, we provide an overview of methods and strategies for incorporating data on behavior and populations into agent- based models, and review techniques for validating and testing the sensi- tivity of agent-based models. We close with suggested directions for future research.Nice discussion of ways in which ABMs can be usefulhttps://journals.sagepub.com/doi/10.1177/0049124113506405
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COVID-19 impact projections / forecasts
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Report 13: Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries[...] Europe is experiencing large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions including case isolation, the closure of schools and universities, banning of mass gatherings and/or public events, and most recently, widescale social distancing including local and national lockdowns. In this report, we use a semi-mechanistic Bayesian hierarchical model to attempt to infer the impact of these interventions across 11 European countries. Our methods assume that changes in the reproductive number – a measure of transmission - are an immediate response to these interventions being implemented rather than broader gradual changes in behaviour. Our model estimates these changes by calculating backwards from the deaths observed over time to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. [...]Latest report from Imperial College London.Code for the whole project on GitHub: https://github.com/ImperialCollegeLondon/covid19model

Accelerated article preprint: https://www.nature.com/articles/s41586-020-2405-7_reference.pdf
https://www.imperial.ac.uk/media/imperial-college/medicine/mrc-gida/2020-03-30-COVID19-Report-13.pdf
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Report 12: The Global Impact of COVID-19 and Strategies for Mitigation and Suppression[...] Here we combine data on age-specific contact patterns and COVID-19 severity to project the health impact of the pandemic in 202 countries. We compare predicted mortality impacts in the absence of interventions or spontaneous social distancing with what might be achieved with policies aimed at mitigating or suppressing transmission. [...]https://www.imperial.ac.uk/media/imperial-college/medicine/mrc-gida/2020-03-26-COVID19-Report-12.pdf
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Predicted COVID-19 Fatality Rates Based on Age, Sex, Comorbidities, and Health System CapacityEarly reports suggest the fatality rate from COVID-19 varies greatly across countries, but non-random testing and incomplete vital registration systems render it impossible to directly estimate the infection fatality rate (IFR) in many low- and middle-income countries. To fill this gap, we estimate the adjustments required to extrapolate estimates of the IFR from high- to lower-income regions. Accounting for differences in the distribution of age, sex, and relevant comorbidities yields substantial differences in the predicted IFR across 21 world regions, ranging from 0.11% in Western Sub-Saharan Africa to 1.07% for High Income Asia Pacific. However, these predictions must be treated as lower bounds, as they are grounded in fatality rates from countries with advanced health systems. In order to adjust for health system capacity, we incorporate regional differences in the relative odds of infection fatality from childhood influenza. This adjustment greatly diminishes, but does not entirely erase, the demography-based advantage predicted in the lowest income settings, with regional estimates of the predicted COVID-19 IFR ranging from 0.43% in Western Sub-Saharan Africa to 1.83% for Eastern Europe.Focuses on low- and middle-income countries. Interesting methodology. Their IFR numbers are higher than most early influential reports (incl. Imperial's above). https://www.cgdev.org/sites/default/files/predicted-covid-19-fatality-rates-based-age-sex-comorbidities-and-health-system-capacity.pdf
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