Evolution of scaling emergence in large-scale spatial epidemic spreading

Background: Zipf's law and Heaps' law are two representatives of the scaling concepts, which play a significant role in the study of complexity science. The coexistence of the Zipf's law and the Heaps' law motivates different understandings on the dependence between these two scalings, which is still hardly been clarified. Methodology/Principal Findings: In this article, we observe an evolution process of the scalings: the Zipf's law and the Heaps' law are naturally shaped to coexist at the initial time, while the crossover comes with the emergence of their inconsistency at the larger time before reaching a stable state, where the Heaps' law still exists with the disappearance of strict Zipf's law. Such findings are illustrated with a scenario of large-scale spatial epidemic spreading, and the empirical results of pandemic disease support a universal analysis of the relation between the two laws regardless of the biological details of disease. Employing the United States(U.S.) domestic air transportation and demographic data to construct a metapopulation model for simulating the pandemic spread at the U.S. country level, we uncover that the broad heterogeneity of the infrastructure plays a key role in the evolution of scaling emergence. Conclusions/Significance: The analyses of large-scale spatial epidemic spreading help understand the temporal evolution of scalings, indicating the coexistence of the Zipf's law and the Heaps' law depends on the collective dynamics of epidemic processes, and the heterogeneity of epidemic spread indicates the significance of performing targeted containment strategies at the early time of a pandemic disease.Comment: 24pages, 7figures, accepted by PLoS ON

ELISA versus PCR for diagnosis of chronic Chagas disease: systematic review and meta-analysis

<p>Abstract</p> <p>Background</p> <p>Most current guidelines recommend two serological tests to diagnose chronic Chagas disease. When serological tests are persistently inconclusive, some guidelines recommend molecular tests. The aim of this investigation was to review chronic Chagas disease diagnosis literature and to summarize results of ELISA and PCR performance.</p> <p>Methods</p> <p>A systematic review was conducted searching remote databases (MEDLINE, LILACS, EMBASE, SCOPUS and ISIWeb) and full texts bibliography for relevant abstracts. In addition, manufacturers of commercial tests were contacted. Original investigations were eligible if they estimated sensitivity and specificity, or reliability -or if their calculation was possible - of ELISA or PCR tests, for chronic Chagas disease.</p> <p>Results</p> <p>Heterogeneity was high within each test (ELISA and PCR) and threshold effect was detected only in a particular subgroup. Reference standard blinding partially explained heterogeneity in ELISA studies, and pooled sensitivity and specificity were 97.7% [96.7%-98.5%] and 96.3% [94.6%-97.6%] respectively. Commercial ELISA with recombinant antigens studied in phase three investigations partially explained heterogeneity, and pooled sensitivity and specificity were 99.3% [97.9%-99.9%] and 97.5% [88.5%-99.5%] respectively. ELISA's reliability was seldom studied but was considered acceptable. PCR heterogeneity was not explained, but a threshold effect was detected in three groups created by using guanidine and boiling the sample before DNA extraction. PCR sensitivity is likely to be between 50% and 90%, while its specificity is close to 100%. PCR reliability was never studied.</p> <p>Conclusions</p> <p>Both conventional and recombinant based ELISA give useful information, however there are commercial tests without technical reports and therefore were not included in this review. Physicians need to have access to technical reports to understand if these serological tests are similar to those included in this review and therefore correctly order and interpret test results. Currently, PCR should not be used in clinical practice for chronic Chagas disease diagnosis and there is no PCR test commercially available for this purpose. Tests limitations and directions for future research are discussed.</p

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P &lt; 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Mood and the Market: Can Press Reports of Investors’ Mood Predict Stock Prices?

We examined whether press reports on the collective mood of investors can predict changes in stock prices. We collected data on the use of emotion words in newspaper reports on traders’ affect, coded these emotion words according to their location on an affective circumplex in terms of pleasantness and activation level, and created indices of collective mood for each trading day. Then, by using time series analyses, we examined whether these mood indices, depicting investors’ emotion on a given trading day, could predict the next day’s opening price of the stock market. The strongest findings showed that activated pleasant mood predicted increases in NASDAQ prices, while activated unpleasant mood predicted decreases in NASDAQ prices. We conclude that both valence and activation levels of collective mood are important in predicting trend continuation in stock prices

Determinants of the Pace of Global Innovation in Energy Technologies

Understanding the factors driving innovation in energy technologies is of critical importance to mitigating climate change and addressing other energy-related global challenges. Low levels of innovation, measured in terms of energy patent filings, were noted in the 1980s and 90s as an issue of concern and were attributed to limited investment in public and private research and development (R&D). Here we build a comprehensive global database of energy patents covering the period 1970–2009, which is unique in its temporal and geographical scope. Analysis of the data reveals a recent, marked departure from historical trends. A sharp increase in rates of patenting has occurred over the last decade, particularly in renewable technologies, despite continued low levels of R&D funding. To solve the puzzle of fast innovation despite modest R&D increases, we develop a model that explains the nonlinear response observed in the empirical data of technological innovation to various types of investment. The model reveals a regular relationship between patents, R&D funding, and growing markets across technologies, and accurately predicts patenting rates at different stages of technological maturity and market development. We show quantitatively how growing markets have formed a vital complement to public R&D in driving innovative activity. These two forms of investment have each leveraged the effect of the other in driving patenting trends over long periods of time.National Science Foundation (U.S.) (Grant SBE-0738187)Solomon Buchsbaum AT&T Research Fun