The psychological impact of quarantine and how to reduce it: rapid review of the evidence.

1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

Spreading of information, ideas or diseases can be conveniently modelled in the context of complex networks. An analysis now reveals that the most efficient spreaders are not always necessarily the most connected agents in a network. Instead, the position of an agent relative to the hierarchical topological organization of the network might be as important as its connectivity.

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Identification of influential spreaders in complex networks

A great variety of systems in nature, society and technology -- from the web of sexual contacts to the Internet, from the nervous system to power grids -- can be modeled as graphs of vertices coupled by edges The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems In many cases, however, the edges are not continuously active As an example, in networks of communication via email, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts In some cases, edges are active for non-negligible periods of time: eg, the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks

Temporal Networks

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(06)68175-0.pdf

Guillain-Barré syndrome

COVID-19: towards controlling of a pandemic.

What Is Special About Infectious Disease Epidemiology? Definitions Risk, Relative Risk and Attack Rate Descriptive Epidemiology The Case-Control Study: Odds, Odds Ratios. The Concepts of Confounding The Cohort Study: Rates. The Concept of Bias Some Statistical Procedures That Are Often Used in Epidemiology Clinical Epidemiology: Sensitivity, Specificity, Misclassification Multivariate Analysis and Interaction Survival Analysis Mathematical Models for Epidemics Detection and Analysis of Outbreaks Routine Surveillance of Infectious Diseases Measuring Infectivity Studying The Natural History of Infectious Diseases Seroepedemiology The Study of Contact Patterns Methods to Decide Whether or Not an Illness is Infectious The Epidemiology of Vaccination The Epidemiology of Aids and VCJD More To Read

Modern infectious disease epidemiology.

Evidence of recent or ongoing Campylobacter jejuni infection has been found in approximately one out of every four cases of Guillain-Barre syndrome (GBS). It is increasingly accepted that C. jejuni infection is an important causal factor for GBS. However, the likelihood of GBS' occurring following an episode of C. jejuni gastroenteritis has not been measured. The authors measured the incidence of GBS in a large cohort of persons with laboratory-confirmed C. jejuni infection. Cases of C. jejuni infection were derived from the Swedish national laboratory reporting system for the years 1987--1995. Follow-up for GBS was carried out using the Swedish national hospital inpatient register. Nine cases of GBS were detected in the cohort, which comprised 29,563 cases of C. jejuni infection--a rate of 30.4 per 100,000 (95% confidence interval: 13.9, 57.8). This compares with an expected incidence of 0.3 per 100,000 in a 2-month period in the general population. GBS is an important but rare complication of C. jejuni infection. The risk of developing GBS during the 2 months following a symptomatic episode of C. jejuni infection is approximately 100 times higher than the risk in the general population.

/pdf/incidence-of-guillain-barre-syndrome-following-infection-12nafxycyg.pdf

Incidence of Guillain-Barré Syndrome following Infection with Campylobacter jejuni

During 1997–2004, microbiologically confirmed gastrointestinal infections were reported for 101,855 patients in Sweden. Among patients who had Salmonella infection (n = 34,664), we found an increased risk for aortic aneurysm (standardized incidence ratio [SIR] 6.4, 95% confidence interval [CI] 3.1–11.8) within 3 months after infection and an elevated risk for ulcerative colitis (SIR 3.2, 95% CI 2.2–4.6) within 1 year after infection. We also found this elevated risk for ulcerative colitis among Campylobacter infections (n = 57,425; SIR 2.8, 95% CI 2.0–3.8). Within 1 year, we found an increased risk for reactive arthritis among patients with Yersinia enteritis (n = 5,133; SIR 47.0, 95% CI 21.5–89.2), Salmonella infection (SIR 18.2, 95% CI 12.0–26.5), and Campylobacter infection (SIR 6.3, 95% CI 3.5–10.4). Acute gastroenteritis is sometimes associated with disease manifestations from several organ systems that may require hospitalization of patients.

/pdf/short-and-long-term-effects-of-bacterial-gastrointestinal-5ar2pesgt4.pdf

Short- and long-term effects of bacterial gastrointestinal infections

The 2000 tularemia outbreak : A case-control study of risk factors in disease-endemic and emergent areas, Sweden.

/pdf/the-2000-tularemia-outbreak-a-case-control-study-of-risk-ynahr6as9u.pdf

Johan Giesecke

Papers

COVID-19: towards controlling of a pandemic.

Modern infectious disease epidemiology.

Incidence of Guillain-Barré Syndrome following Infection with Campylobacter jejuni

Short- and long-term effects of bacterial gastrointestinal infections

The 2000 Tularemia Outbreak: A Case-Control Study of Risk Factors in Disease-Endemic and Emergent Areas, Sweden