Modeling Covid-19 dynamics for real-time estimates and projections: an application to Albanian data

Mapping Intimacies ◽

10.1101/2020.03.20.20038141 ◽

2020 ◽

Cited By ~ 2

Author(s):

Erida Gjini

Keyword(s):

Real Time ◽

Control Measures ◽

Time Data ◽

Modeling Framework ◽

Adaptive Intervention ◽

Time Dynamics ◽

Time Estimates ◽

Model Predictions ◽

Travel Restrictions ◽

Transmission Reduction

AbstractThe SARS-CoV-2 epidemic is one of the biggest challenges healthcare systems worldwide have ever had to face. To curb transmission many countries have adopted social distancing measures and travel restrictions. Estimating the effect of these measures in each context is challenging and requires mathematical models of the transmission dynamics. Projections for the future course of the epidemic strongly rely on model predictions and accurate representation of real-time data as they accumulate. Here I develop an SEIR modeling framework for Covid-19, to evaluate reported cases and fatalities, and to enable forecasting using evidence-based Bayesian parameter estimation. This Bayesian framework offers a tool to parametrize real-time dynamics of Covid-19 cases, and explore the effect of control as it unfolds in any setting. I apply the model to Covid-19 data from Albania, where drastic control measures were put in place already on the day of the first confirmed case. Evaluating the dynamics of reported cases 9-31 March 2020, I estimate parameters and make preliminary projections. Three weeks into the measures, Albanian data already indicate a strong signature of more than 40% transmission reduction, and lend support to a progressively increasing effect of control measures rather than a static one. In the Albanian setting, the model and data match well, projecting the peak of the outbreak may be around 5-15 April, and be contained within 300 active confirmed cases if control continues with the same trend. This framework can be used to understand the quantitative effects of different control measures in real-time, and inform adaptive intervention for success in other settings.

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Learning In Spike Trains: Estimating Within-Session Changes In Firing Rate Using Weighted Interpolation

10.1101/041301 ◽

2016 ◽

Author(s):

Greg Jensen ◽

Fabian Muñoz ◽

Vincent P. Ferrera

Keyword(s):

Real Time ◽

Electrophysiological Study ◽

Monte Carlo Algorithm ◽

Small Samples ◽

Weighted Interpolation ◽

Time Dynamics ◽

Firing Rates ◽

The Past ◽

Time Estimates ◽

Quantitative Procedure

AbstractThe electrophysiological study of learning is hampered by modern procedures for estimating firing rates: Such procedures usually require large datasets, and also require that included trials be functionally identical. Unless a method can track the real-time dynamics of how firing rates evolve, learning can only be examined in the past tense. We propose a quantitative procedure, called ARRIS, that can uncover trial-by-trial firing dynamics. ARRIS provides reliable estimates of firing rates based on small samples using the reversible-jump Markov chain Monte Carlo algorithm. Using weighted interpolation, ARRIS can also provide estimates that evolve over time. As a result, both real-time estimates of changing activity, and of task-dependent tuning, can be obtained during the initial stages of learning.

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Real-Time Dispatching Operation Risk Assessment Based on Fault Tree Theory

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.732-733.909 ◽

2013 ◽

Vol 732-733 ◽

pp. 909-914

Author(s):

En Wang ◽

Wei Wei ◽

Bing Dong Wang ◽

Zhe Liu

Keyword(s):

Real Time ◽

Fault Tree ◽

Test System ◽

Control Measures ◽

Risk Level ◽

Time Data ◽

Risk Indices ◽

Risk Sources ◽

Line Overload ◽

Operation Risk

Reasonable dispatching strategies are important to guarantee secure and reliable operation of power system. Now the operators use real-time data and their experience to dispatch the system, but the huge data system brings much inconvenience to operators. In this paper, the risk theory is introduced into dispatching operation quantitative assessment, and a real-time dispatching operation risk analysis method is proposed. Fault tree is used to simulate dispatching operation process and comprehensively analyze the system risk in both under-successful and failure state of the operation. Risk indices are given to quantitatively reflect the risk level of each operation step based on local information, such as voltage out-of-limit risk, line overload risk, load curtailment risk, so that the operators can clearly recognize the risk and risk sources in each operation step and take corresponding pre-control measures. Finally, the effectiveness and practicability of proposed method is validated by an IEEE RTS test system.

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PubliCo. A protocol for a new risk and crisis communication platform to bridge the gap between policy makers and the public in the context of the COVID-19 crisis (Preprint)

10.2196/preprints.33653 ◽

2021 ◽

Author(s):

Giovanni Spitale ◽

Sonja Merten ◽

Kristen Jafflin ◽

Bettina Schwind ◽

Andrea Kaiser-Grolimund ◽

...

Keyword(s):

Real Time ◽

Crisis Communication ◽

Public Perception ◽

Online Survey ◽

Control Measures ◽

Time Data ◽

Flexible Tool ◽

Policy Makers ◽

Real Time Data ◽

Restrictive Measures

UNSTRUCTURED Background Since the end of 2019, COVID-19 has had a significant impact on citizens around the globe. As governments institute more restrictive measures, public adherence could decrease and discontent mount. Providing high-quality information and countering fake news is important. But we also need feedback loops so that government officials can refine preventive measures and communication strategies. Policy-makers need information – preferably based on real-time data – on the public’s cognitive, emotional and behavioural reaction to public health messages and restrictive measures. PubliCo aims to foster effective and tailored risk and crisis communication as well as an assessment of the risks and benefits of prevention and control measures, as their effectiveness depends on public trust and cooperation. Objective Our project aims to develop a tool that helps tackle the COVID-19 infodemic, with a focus on enabling a nuanced and in-depth understanding of public perception. The project adopts a trans-disciplinary multi-stakeholder approach, including participatory citizen science. Methods Methodologically, we combine literature and media review and analysis and empirical research using mixed methods, including an online survey and diary-based research, both of which are ongoing and continuously updated. Building on real-time data and continuous data collection, our research results will be highly adaptable to the evolving situation. Strengths and limitations of this study - PubliCo is a new modular and flexible tool to provide bi-directional interaction between citizens and policy-makers for risk and crisis communication - PubliCo relies on quantitative and qualitative data to provide a precise, timely and rich analysis of complex phenomena - PubliCo is open and transparent by design - Although important safeguards are put in place in the code, in a less democratic context it could be used for social control - Communicating complex notions with moral implications (e.g. about health risks, allocation strategies, and community benefits) is a challenge.

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Evaluation of Quantitative Precipitation Estimations through Hydrological Modeling in IFloodS River Basins

Journal of Hydrometeorology ◽

10.1175/jhm-d-15-0149.1 ◽

2017 ◽

Vol 18 (2) ◽

pp. 529-553 ◽

Cited By ~ 16

Author(s):

Huan Wu ◽

Robert F. Adler ◽

Yudong Tian ◽

Guojun Gu ◽

George J. Huffman

Keyword(s):

Real Time ◽

River Basin ◽

Hydrological Modeling ◽

Research Quality ◽

Quality Data ◽

Time Data ◽

Modeling Framework ◽

Precipitation Estimation ◽

Precipitation Bias

Abstract A multiple-product-driven hydrologic modeling framework (MMF) is utilized for evaluation of quantitative precipitation estimation (QPE) products, motivated by improving the utility of satellite QPE in global flood modeling. This work addresses the challenge of objectively determining the relative value of various QPEs at river basin/subbasin scales. A reference precipitation dataset is created using a long-term water-balance approach with independent data sources. The intercomparison of nine QPEs and corresponding hydrologic simulations indicates that all products with long-term (2002–13) records have similar merits as over the short-term (April–June 2013) Iowa Flood Studies period. The model performance in calculated streamflow varies approximately linearly with precipitation bias, demonstrating that the model successfully translated the level of precipitation quality to streamflow quality with better streamflow simulations from QPEs with less bias. Phase 2 of the North American Land Data Assimilation System (NLDAS-2) has the best streamflow results for the Iowa–Cedar River basin, with daily and monthly Nash–Sutcliffe coefficients and mean annual bias of 0.81, 0.88, and −2.1%, respectively, for the long-term period. The evaluation also indicates that a further adjustment of NLDAS-2 to form the best precipitation estimation should consider spatial–temporal distribution of bias. The satellite-only products have lower performance (peak and timing) than other products, while simple bias adjustment can intermediately improve the quality of simulated streamflow. The TMPA research product (TMPA-RP; research-quality data) can generate results approaching those of the ground-based products with only monthly gauge-based adjustment to the TMPA real-time product (TMPA-RT; near-real-time data). It is further noted that the streamflow bias is strongly correlated to precipitation bias at various time scales, though other factors may play a role as well, especially on the daily time scale.

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Le portail SIGLA – un système d'information géographique sur Internet pour le programme portugais de surveillance entomologique de la fièvre catarrhale ovine

Revue d’élevage et de médecine vétérinaire des pays tropicaux ◽

10.19182/remvt.10078 ◽

2009 ◽

Vol 62 (2-4) ◽

pp. 176

Author(s):

H. Martins ◽

T. Nunes ◽

Fernando Boinas

Keyword(s):

Real Time ◽

Relational Database ◽

Spatial Data ◽

Temporal Distribution ◽

Control Measures ◽

Geographical Information ◽

Time Data ◽

Gis Technology ◽

Web Mapping ◽

Système D’Information

Bluetongue (BT) is an infectious non-contagious disease, whose transmission is commonly associated with an intermediate arthropod host from the Culicoides genre. A BT entomological surveillance programme was implemented in Portugal in May 2005 to collect data on the abundance, and spatial and temporal distribution of several species potentially involved in the transmission of the disease. At that time a simple local alphanumerical relational database was built to record all data. Although it fulfilled the initial objectives of data management, there was an increasing need to share this information in real-time with national veterinary authorities. Moreover, sharing this data in a map-based approach was not possible without considerable time-consuming effort. To overcome these needs, a new web-based system with geographical information system (GIS) capabilities was designed and is currently being developed exclusively using Open Source Software (Portal SIGLA). The alphanumerical component was partially migrated from the previous system, though introducing query capabilities visually supported by the use of dynamic charts further enriched it. The geographical component is now the development core, but it already contains several tools of a standard web mapping application (zooming, panning, distance and area measurements, activation/deactivation of spatial layers, legend panel, graphical and numerical scale…). This enterprise-level relational database with geographical functions also makes spatial editing available through the web and thus enables technicians with no GIS expertise to create and handle easily spatial data. The system democratizes GIS technology and provides veterinary officers with real-time data sharing. It helps to gain further insight into disease dynamics and thus to contribute to more effective sanitary control measures. Future developments are mainly related to spatial querying of data through the form of choropleth and chart maps. This will further enrich the analysis capabilities of the system.

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Cross-Country Comparison of Public Awareness, Rumors, and Behavioral Responses to the COVID-19 Epidemic: Infodemiology Study

Journal of Medical Internet Research ◽

10.2196/21143 ◽

2020 ◽

Vol 22 (8) ◽

pp. e21143 ◽

Cited By ~ 9

Author(s):

Zhiyuan Hou ◽

Fanxing Du ◽

Xinyu Zhou ◽

Hao Jiang ◽

Sam Martin ◽

...

Keyword(s):

Real Time ◽

Public Awareness ◽

Behavioral Responses ◽

Control Measures ◽

Herbal Remedies ◽

Effective Control ◽

Time Data ◽

The Public ◽

Public Reaction ◽

And Behavior

Background Understanding public behavioral responses to the coronavirus disease (COVID-19) epidemic and the accompanying infodemic is crucial to controlling the epidemic. Objective The aim of this study was to assess real-time public awareness and behavioral responses to the COVID-19 epidemic across 12 selected countries. Methods Internet surveillance was used to collect real-time data from the general public to assess public awareness and rumors (China: Baidu; worldwide: Google Trends) and behavior responses (China: Ali Index; worldwide: Google Shopping). These indices measured the daily number of searches or purchases and were compared with the numbers of daily COVID-19 cases. The trend comparisons across selected countries were observed from December 1, 2019 (prepandemic baseline) to April 11, 2020 (at least one month after the governments of selected countries took actions for the pandemic). Results We identified missed windows of opportunity for early epidemic control in 12 countries, when public awareness was very low despite the emerging epidemic. China's epidemic and the declaration of a public health emergency of international concern did not prompt a worldwide public reaction to adopt health-protective measures; instead, most countries and regions only responded to the epidemic after their own case counts increased. Rumors and misinformation led to a surge of sales in herbal remedies in China and antimalarial drugs worldwide, and timely clarification of rumors mitigated the rush to purchase unproven remedies. Conclusions Our comparative study highlights the urgent need for international coordination to promote mutual learning about epidemic characteristics and effective control measures as well as to trigger early and timely responses in individual countries. Early release of official guidelines and timely clarification of rumors led by governments are necessary to guide the public to take rational action.

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Cross-Country Comparison of Public Awareness, Rumors, and Behavioral Responses to the COVID-19 Epidemic: Infodemiology Study (Preprint)

10.2196/preprints.21143 ◽

2020 ◽

Cited By ~ 2

Author(s):

Zhiyuan Hou ◽

Fanxing Du ◽

Xinyu Zhou ◽

Hao Jiang ◽

Sam Martin ◽

...

Keyword(s):

Real Time ◽

Public Awareness ◽

Behavioral Responses ◽

Control Measures ◽

Herbal Remedies ◽

Effective Control ◽

Time Data ◽

The Public ◽

Public Reaction ◽

And Behavior

BACKGROUND Understanding public behavioral responses to the coronavirus disease (COVID-19) epidemic and the accompanying infodemic is crucial to controlling the epidemic. OBJECTIVE The aim of this study was to assess real-time public awareness and behavioral responses to the COVID-19 epidemic across 12 selected countries. METHODS Internet surveillance was used to collect real-time data from the general public to assess public awareness and rumors (China: Baidu; worldwide: Google Trends) and behavior responses (China: Ali Index; worldwide: Google Shopping). These indices measured the daily number of searches or purchases and were compared with the numbers of daily COVID-19 cases. The trend comparisons across selected countries were observed from December 1, 2019 (prepandemic baseline) to April 11, 2020 (at least one month after the governments of selected countries took actions for the pandemic). RESULTS We identified missed windows of opportunity for early epidemic control in 12 countries, when public awareness was very low despite the emerging epidemic. China's epidemic and the declaration of a public health emergency of international concern did not prompt a worldwide public reaction to adopt health-protective measures; instead, most countries and regions only responded to the epidemic after their own case counts increased. Rumors and misinformation led to a surge of sales in herbal remedies in China and antimalarial drugs worldwide, and timely clarification of rumors mitigated the rush to purchase unproven remedies. CONCLUSIONS Our comparative study highlights the urgent need for international coordination to promote mutual learning about epidemic characteristics and effective control measures as well as to trigger early and timely responses in individual countries. Early release of official guidelines and timely clarification of rumors led by governments are necessary to guide the public to take rational action.

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Ambulatory Assessment

European Psychologist ◽

10.1027/1016-9040.14.2.109 ◽

2009 ◽

Vol 14 (2) ◽

pp. 109-119 ◽

Cited By ~ 66

Author(s):

Ulrich W. Ebner-Priemer ◽

Timothy J. Trull

Keyword(s):

Real Time ◽

Clinical Psychology ◽

Real Life ◽

Ambulatory Assessment ◽

Computer Assisted ◽

Affective Valence ◽

Time Data ◽

Physiological Processes ◽

Context Specific ◽

Questionnaire Studies

Convergent experimental data, autobiographical studies, and investigations on daily life have all demonstrated that gathering information retrospectively is a highly dubious methodology. Retrospection is subject to multiple systematic distortions (i.e., affective valence effect, mood congruent memory effect, duration neglect; peak end rule) as it is based on (often biased) storage and recollection of memories of the original experience or the behavior that are of interest. The method of choice to circumvent these biases is the use of electronic diaries to collect self-reported symptoms, behaviors, or physiological processes in real time. Different terms have been used for this kind of methodology: ambulatory assessment, ecological momentary assessment, experience sampling method, and real-time data capture. Even though the terms differ, they have in common the use of computer-assisted methodology to assess self-reported symptoms, behaviors, or physiological processes, while the participant undergoes normal daily activities. In this review we discuss the main features and advantages of ambulatory assessment regarding clinical psychology and psychiatry: (a) the use of realtime assessment to circumvent biased recollection, (b) assessment in real life to enhance generalizability, (c) repeated assessment to investigate within person processes, (d) multimodal assessment, including psychological, physiological and behavioral data, (e) the opportunity to assess and investigate context-specific relationships, and (f) the possibility of giving feedback in real time. Using prototypic examples from the literature of clinical psychology and psychiatry, we demonstrate that ambulatory assessment can answer specific research questions better than laboratory or questionnaire studies.

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