Pathogenic Nationalism: Epidemic Outbreak and Xenophobic Patriotism in Galdós's Zaragoza

2021 ◽  
Vol 56 (1) ◽  
pp. 73-92
Author(s):  
Sarah Sierra
Keyword(s):  
Epidemic Outbreak

Epidemic Outbreak Surveillance (EOS)

2006 ◽  
Author(s):  
Thomas C. Scofield ◽  
Elizabeth Walter ◽  
Samuel J. Livingstone
Keyword(s):  
Epidemic Outbreak

scholarly journals PDE limits of stochastic SIS epidemics on networks

2020 ◽  
Vol 8 (4) ◽  
Author(s):  
F Di Lauro ◽  
J-C Croix ◽  
L Berthouze ◽  
I Z Kiss
Keyword(s):  
Network Inference ◽  
Mean Field ◽  
Population Level ◽  
Death Process ◽  
Disease Dynamics ◽  
Epidemic Outbreak ◽  
Numerical Tests ◽  
Mean Field Models ◽  
Stochastic Epidemic ◽  
Fokker Planck Equations

Abstract Stochastic epidemic models on networks are inherently high-dimensional and the resulting exact models are intractable numerically even for modest network sizes. Mean-field models provide an alternative but can only capture average quantities, thus offering little or no information about variability in the outcome of the exact process. In this article, we conjecture and numerically demonstrate that it is possible to construct partial differential equation (PDE)-limits of the exact stochastic susceptible-infected-susceptible epidemics on Regular, Erdős–Rényi, Barabási–Albert networks and lattices. To do this, we first approximate the exact stochastic process at population level by a Birth-and-Death process (BD) (with a state space of $O(N)$ rather than $O(2^N)$) whose coefficients are determined numerically from Gillespie simulations of the exact epidemic on explicit networks. We numerically demonstrate that the coefficients of the resulting BD process are density-dependent, a crucial condition for the existence of a PDE limit. Extensive numerical tests for Regular, Erdős–Rényi, Barabási–Albert networks and lattices show excellent agreement between the outcome of simulations and the numerical solution of the Fokker–Planck equations. Apart from a significant reduction in dimensionality, the PDE also provides the means to derive the epidemic outbreak threshold linking network and disease dynamics parameters, albeit in an implicit way. Perhaps more importantly, it enables the formulation and numerical evaluation of likelihoods for epidemic and network inference as illustrated in a fully worked out example.

scholarly journals Clinical correlates of anti-SARS-CoV-2 antibody profiles in Spanish COVID-19 patients from a high incidence region

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Robert Markewitz ◽  
Antje Torge ◽  
Klaus-Peter Wandinger ◽  
Daniela Pauli ◽  
Andre Franke ◽  
...  
Keyword(s):  
Case Fatality ◽  
Time Frame ◽  
Epidemic Outbreak ◽  
Sample Collection ◽  
Rt Pcr ◽  
High Incidence ◽  
Duration Of Hospitalization ◽  
Reasonable Time Frame ◽  
Support Treatment ◽  
Diagnostic And Prognostic Value

AbstractLaboratory testing for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) consists of two pillars: the detection of viral RNA via rt-PCR as the diagnostic gold standard in acute cases, and the detection of antibodies against SARS-CoV-2. However, concerning the latter, questions remain about their diagnostic and prognostic value and it is not clear whether all patients develop detectable antibodies. We examined sera from 347 Spanish COVID-19 patients, collected during the peak of the epidemic outbreak in Spain, for the presence of IgA and IgG antibodies against SARS-CoV-2 and evaluated possible associations with age, sex and disease severity (as measured by duration of hospitalization, kind of respiratory support, treatment in ICU and death). The presence and to some degree the levels of anti-SARS-CoV-2 antibodies depended mainly on the amount of time between onset of symptoms and the collection of serum. A subgroup of patients did not develop antibodies at the time of sample collection. Compared to the patients that did, no differences were found. The presence and level of antibodies was not associated with age, sex, duration of hospitalization, treatment in the ICU or death. The case-fatality rate increased exponentially with older age. Neither the presence, nor the levels of anti-SARS-CoV-2 antibodies served as prognostic markers in our cohort. This is discussed as a possible consequence of the timing of the sample collection. Age is the most important risk factor for an adverse outcome in our cohort. Some patients appear not to develop antibodies within a reasonable time frame. It is unclear, however, why that is, as these patients differ in no respect examined by us from those who developed antibodies.

scholarly journals The Ongoing COVID-19 Epidemic Curves Indicate Initial Point Spread in China with Log-Normal Distribution of New Cases Per Day with a Predictable Last Date of the Outbreak Version 2: Evaluation of Previous Prediction and Testing the Method for S Korea and the Use of the Method by an Unexperienced Person

2020 ◽  
Author(s):  
Stefan Olsson ◽  
Jing Zhang
Keyword(s):  
Normal Distribution ◽  
Coming Out ◽  
Additional Data ◽  
Initial Point ◽  
Epidemic Outbreak ◽  
Spreadsheet Program ◽  
Epidemic Curve ◽  
Log Normal ◽  
Log Normal Distribution ◽  
Previous Prediction

During an epidemic outbreak it is useful for planners and responsible authorities to be able to plan ahead to estimate when an outbreak of an epidemic is likely to ease and when the last case can be predicted in their area of responsibility. Theoretically this could be done for a point source epidemic using epidemic curve forecasting. The extensive data now coming out of China makes it possible to test if this can be done using MS Excel a standard spreadsheet program available to most offices. The available data is divided up for whole China and the different provinces. This and the high number of cases makes the analysis possible. Data for new confirmed infections for Hubei, Hubei outside Wuhan, China excluding Hubei as well as Zhejiang and Fujian provinces all follow a log-normal distribution that can be used to make a rough estimate for the date of the last new confirmed cases in respective areas. In this continuation work 9 additional days were added for the Chinese data to evaluate the previous predictions. We also tested the feasibility for a non-specialist to make similar predictions using additional data from S Korea now available. The extra data now available from China follows the previous predicted trend supporting the usefulness of this simple technique.

scholarly journals Geographic Information Systems and COVID-19: The Johns Hopkins University Dashboard

2020 ◽  
Author(s):  
BELMIRO N JOAO
Keyword(s):  
Information Systems ◽  
Single Case ◽  
Single Case Study ◽  
Epidemic Outbreak ◽  
Global Epidemic ◽  
Johns Hopkins University ◽  
Successful Case ◽  
Other Information

Abstract Background: This article presents a single case study on the development of a GIS for global monitoring of coronavirus (COVID-19). For such concepts presented about GIS, its use and evolution in epidemic events and a presentation of the context of the current coronavirus outbreak and the meaningless results of consolidating a panel with reliable data.Methods: A single case study of a GIS in continuous development with data sharing and comments from the scientific community was carried out. Because it is not a post-mortem analysis, or a follow-up to a successful case, it was not possible to use more rigorous and systematic approaches such as those used by Lee (1989) and Onsrud, Pinto and Azad (1992) for case studies in GIS.Results: The case study presents the results of the development of a control dashboard, as well as the availability of consolidated data made by researchers at Johns Hopkins University and who showed a reliable platform and a world reference for health comunity.Conclusions: Efforts to develop a dashboard and provide data on the coronavirus outbreak resulted in the immediate replication of several other information systems with different approaches (Power BI, R, Tableau), becoming a reference for any new global epidemic outbreak events.

scholarly journals Compliance with NPIs and Possible Deleterious Effects on Mitigation of an Epidemic Outbreak

2021 ◽  
Author(s):  
Maria Vittoria Barbarossa ◽  
Jan Fuhrmann
Keyword(s):  
Compartmental Model ◽  
Epidemic Outbreak ◽  
Number Of Individuals ◽  
Pharmaceutical Interventions

The first attempt to control and mitigate an epidemic outbreak caused by a previously unknown virus occurs primarily via non-pharmaceutical interventions (NPIs). In case of the SARS-CoV-2 virus, which since the early days of 2020 caused the COVID-19 pandemic, NPIs aimed at reducing transmission enabling contacts between individuals. The effectiveness of contact reduction measures directly correlates with the number of individuals adhering to such measures. Here, we illustrate by means of a very simple compartmental model how partial noncompliance with NPIs can prevent these from stopping the spread of an epidemic.

scholarly journals Comparing the Clinical Characteristics and Mortality of Residential and Non-Residential Older People with COVID-19: Retrospective Observational Study

2022 ◽  
Vol 19 (1) ◽  
pp. 483
Author(s):  
Francesc X. Marin-Gomez ◽  
Jacobo Mendioroz-Peña ◽  
Miguel-Angel Mayer ◽  
Leonardo Méndez-Boo ◽  
Núria Mora ◽  
...  
Keyword(s):  
Risk Factors ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Clinical Characteristics ◽  
Fold Increase ◽  
The Elderly ◽  
Health Administration ◽  
Epidemic Outbreak ◽  
Risk Of Death ◽  
Using Data

Nursing homes have accounted for a significant part of SARS-CoV-2 mortality, causing great social alarm. Using data collected from electronic medical records of 1,319,839 institutionalised and non-institutionalised persons ≥ 65 years, the present study investigated the epidemiology and differential characteristics between these two population groups. Our results showed that the form of presentation of the epidemic outbreak, as well as some risk factors, are different among the elderly institutionalised population with respect to those who are not. In addition to a twenty-fold increase in the rate of adjusted mortality among institutionalised individuals, the peak incidence was delayed by approximately three weeks. Having dementia was shown to be a risk factor for death, and, unlike the non-institutionalised group, neither obesity nor age were shown to be significantly associated with the risk of death among the institutionalised. These differential characteristics should be able to guide the actions to be taken by the health administration in the event of a similar infectious situation among institutionalised elderly people.

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