scholarly journals Impact of misinformation in temporal network epidemiology

2019 ◽  
Vol 7 (1) ◽  
pp. 52-69 ◽  
Author(s):  
Petter Holme ◽  
Luis E. C. Rocha
Keyword(s):  
Contact Structure ◽  
Exponential Convergence ◽  
Disease Outbreaks ◽  
Structural Factors ◽  
Temporal Network ◽  
Temporal Networks ◽  
Network Epidemiology ◽  
Time To Extinction ◽  
Time Stamps ◽  
The Impact

AbstractWe investigate the impact of misinformation about the contact structure on the ability to predict disease outbreaks. We base our study on 31 empirical temporal networks and tune the frequencies in errors in the node identities or time stamps of contacts. We find that for both these spreading scenarios, the maximal misprediction of both the outbreak size and time to extinction follows an stretched exponential convergence as a function of the error frequency. We furthermore determine the temporal-network structural factors influencing the parameters of this convergence.

Online Sampling of Temporal Networks

2021 ◽  
Vol 15 (4) ◽  
pp. 1-27
Author(s):  
Nesreen K. Ahmed ◽  
Nick Duffield ◽  
Ryan A. Rossi
Keyword(s):  
Unbiased Estimation ◽  
Temporal Network ◽  
Temporal Networks ◽  
Network Sampling ◽  
Unbiased Estimators ◽  
Sampling Algorithms ◽  
Ablation Study ◽  
Network Patterns ◽  
Online Sampling ◽  
The Impact

Temporal networks representing a stream of timestamped edges are seemingly ubiquitous in the real world. However, the massive size and continuous nature of these networks make them fundamentally challenging to analyze and leverage for descriptive and predictive modeling tasks. In this work, we propose a general framework for temporal network sampling with unbiased estimation. We develop online, single-pass sampling algorithms, and unbiased estimators for temporal network sampling. The proposed algorithms enable fast, accurate, and memory-efficient statistical estimation of temporal network patterns and properties. In addition, we propose a temporally decaying sampling algorithm with unbiased estimators for studying networks that evolve in continuous time, where the strength of links is a function of time, and the motif patterns are temporally weighted. In contrast to the prior notion of a △ t -temporal motif, the proposed formulation and algorithms for counting temporally weighted motifs are useful for forecasting tasks in networks such as predicting future links, or a future time-series variable of nodes and links. Finally, extensive experiments on a variety of temporal networks from different domains demonstrate the effectiveness of the proposed algorithms. A detailed ablation study is provided to understand the impact of the various components of the proposed framework.

scholarly journals Concurrency measures in the era of temporal network epidemiology: a review

2021 ◽  
Vol 18 (179) ◽  
pp. 20210019
Author(s):  
Naoki Masuda ◽  
Joel C. Miller ◽  
Petter Holme
Keyword(s):  
Sexually Transmitted Infections ◽  
Temporal Network ◽  
Temporal Networks ◽  
Sexually Transmitted ◽  
New Approaches ◽  
Contact Patterns ◽  
Network Epidemiology ◽  
History Of ◽  
Direct Models

Diseases spread over temporal networks of interaction events between individuals. Structures of these temporal networks hold the keys to understanding epidemic propagation. One early concept of the literature to aid in discussing these structures is concurrency—quantifying individuals’ tendency to form time-overlapping ‘partnerships’. Although conflicting evaluations and an overabundance of operational definitions have marred the history of concurrency, it remains important, especially in the area of sexually transmitted infections. Today, much of theoretical epidemiology uses more direct models of contact patterns, and there is an emerging body of literature trying to connect methods to the concurrency literature. In this review, we will cover the development of the concept of concurrency and these new approaches.

Women's rural-urban migration in Lebanon

2019 ◽  
Author(s):  
◽  
Sally N. Youssef
Keyword(s):  
Internal Migration ◽  
Low Income ◽  
Lived Experiences ◽  
Urban Migration ◽  
Structural Factors ◽  
Migrant Women ◽  
Migration Studies ◽  
Rural Urban Migration ◽  
Low Income Women ◽  
The Impact

Women’s sole internal migration has been mostly ignored in migration studies, and the concentration on migrant women has been almost exclusively on low-income women within the household framework. This study focuses on middleclass women’s contemporary rural-urban migration in Lebanon. It probes into the determinants and outcomes of women’s sole internal migration within the empowerment framework. The study delves into the interplay of the personal, social, and structural factors that determine the women’s rural-urban migration as well as its outcomes. It draws together the lived experiences of migrant women to explore the determinants of women’s internal migration as well as the impact of migration on their expanded empowerment.

scholarly journals Evaluating polymer interplay after hot water pretreatment to investigate maize stem internode recalcitrance

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Amandine Leroy ◽  
Xavier Falourd ◽  
Loïc Foucat ◽  
Valérie Méchin ◽  
Fabienne Guillon ◽  
...  
Keyword(s):  
Cell Wall ◽  
Negative Impact ◽  
Lignin Content ◽  
Structural Features ◽  
Hot Water ◽  
Condensed State ◽  
Structural Factors ◽  
Water Pretreatment ◽  
Hot Water Pretreatment ◽  
The Impact

Abstract Background Biomass recalcitrance is governed by various molecular and structural factors but the interplay between these multiscale factors remains unclear. In this study, hot water pretreatment (HWP) was applied to maize stem internodes to highlight the impact of the ultrastructure of the polymers and their interactions on the accessibility and recalcitrance of the lignocellulosic biomass. The impact of HWP was analysed at different scales, from the polymer ultrastructure or water mobility to the cell wall organisation by combining complementary compositional, spectral and NMR analyses. Results HWP increased the kinetics and yield of saccharification. Chemical characterisation showed that HWP altered cell wall composition with a loss of hemicelluloses (up to 45% in the 40-min HWP) and of ferulic acid cross-linking associated with lignin enrichment. The lignin structure was also altered (up to 35% reduction in β–O–4 bonds), associated with slight depolymerisation/repolymerisation depending on the length of treatment. The increase in $${T}_{1\rho }^{H}$$ T 1 ρ H , $${T}_{HH}$$ T HH and specific surface area (SSA) showed that the cellulose environment was looser after pretreatment. These changes were linked to the increased accessibility of more constrained water to the cellulose in the 5–15 nm pore size range. Conclusion The loss of hemicelluloses and changes in polymer structural features caused by HWP led to reorganisation of the lignocellulose matrix. These modifications increased the SSA and redistributed the water thereby increasing the accessibility of cellulases and enhancing hydrolysis. Interestingly, lignin content did not have a negative impact on enzymatic hydrolysis but a higher lignin condensed state appeared to promote saccharification. The environment and organisation of lignin is thus more important than its concentration in explaining cellulose accessibility. Elucidating the interactions between polymers is the key to understanding LB recalcitrance and to identifying the best severity conditions to optimise HWP in sustainable biorefineries.

scholarly journals Digital proximity tracing on empirical contact networks for pandemic control

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
G. Cencetti ◽  
G. Santin ◽  
A. Longa ◽  
E. Pigani ◽  
A. Barrat ◽  
...  
Keyword(s):  
Large Scale ◽  
Disease Outbreaks ◽  
Physical Distance ◽  
Contact Tracing ◽  
Reproductive Number ◽  
Modeling Framework ◽  
Infectious Disease Outbreaks ◽  
Contact Patterns ◽  
Contact Data ◽  
The Impact

AbstractDigital contact tracing is a relevant tool to control infectious disease outbreaks, including the COVID-19 epidemic. Early work evaluating digital contact tracing omitted important features and heterogeneities of real-world contact patterns influencing contagion dynamics. We fill this gap with a modeling framework informed by empirical high-resolution contact data to analyze the impact of digital contact tracing in the COVID-19 pandemic. We investigate how well contact tracing apps, coupled with the quarantine of identified contacts, can mitigate the spread in real environments. We find that restrictive policies are more effective in containing the epidemic but come at the cost of unnecessary large-scale quarantines. Policy evaluation through their efficiency and cost results in optimized solutions which only consider contacts longer than 15–20 minutes and closer than 2–3 meters to be at risk. Our results show that isolation and tracing can help control re-emerging outbreaks when some conditions are met: (i) a reduction of the reproductive number through masks and physical distance; (ii) a low-delay isolation of infected individuals; (iii) a high compliance. Finally, we observe the inefficacy of a less privacy-preserving tracing involving second order contacts. Our results may inform digital contact tracing efforts currently being implemented across several countries worldwide.

scholarly journals Threshold Effects of Infectious Disease Outbreaks on Livestock Prices: Cases of African Swine Fever and Avian Influenza in South Korea

2021 ◽  
Vol 11 (11) ◽  
pp. 5114
Author(s):  
Hyung-Chul Rah ◽  
Hyeon-Woong Kim ◽  
Aziz Nasridinov ◽  
Wan-Sup Cho ◽  
Seo-Hwa Choi ◽  
...  
Keyword(s):  
Avian Influenza ◽  
Infectious Diseases ◽  
Disease Outbreaks ◽  
African Swine Fever ◽  
Threshold Effect ◽  
Impact Response ◽  
Threshold Effects ◽  
Infectious Disease Outbreaks ◽  
Retail Prices ◽  
The Impact

In this paper we demonstrate the threshold effects of infectious diseases on livestock prices. Daily retail prices of pork and chicken were used as structured data; news and SNS mentions of African Swine Fever (ASF) and Avian Influenza (AI) were used as unstructured data. Models were tested for the threshold effects of disease-related news and SNS frequencies, specifically those related to ASF and AI, on the retail prices of pork and chicken, respectively. The effects were found to exist, and the values of ASF-related news on pork prices were estimated to be −9 and 8, indicating that the threshold autoregressive (TAR) model can be divided into three regimes. The coefficients of the ASF-related SNS frequencies on pork prices were 1.1666, 0.2663 and −0.1035 for regimes 1, 2 and 3, respectively, suggesting that pork prices increased by 1.1666 Korean won in regime 1 when ASF-related SNS frequencies increased. To promote pork consumption by SNS posts, the required SNS frequencies were estimated to have impacts as great as one standard deviation in the pork price. These values were 247.057, 1309.158 and 2817.266 for regimes 1, 2 and 3, respectively. The impact response periods for pork prices were estimated to last 48, 6, and 8 days for regimes 1, 2 and 3, respectively. When the prediction accuracies of the TAR and autoregressive (AR) models with regard to pork prices were compared for the root mean square error, the prediction accuracy of the TAR model was found to be slightly better than that of the AR. When the threshold effect of AI-related news on chicken prices was tested, a linear relationship appeared without a threshold effect. These findings suggest that when infectious diseases such as ASF occur for the first time, the impact on livestock prices is significant, as indicated by the threshold effect and the long impact response period. Our findings also suggest that the impact on livestock prices is not remarkable when infectious diseases occur multiple times, as in the case of AI. To date, this study is the first to suggest the use of SNS to promote meat consumption.

scholarly journals The impact of structural factors on diagnostic delay in diffuse large B‐cell lymphoma

2019 ◽  
Vol 8 (4) ◽  
pp. 1416-1422
Author(s):  
Joanna C. Zurko ◽  
Raymond C. Wade ◽  
Amitkumar Mehta
Keyword(s):  
B Cell ◽  
Cell Lymphoma ◽  
Diagnostic Delay ◽  
B Cell Lymphoma ◽  
Structural Factors ◽  
Large B Cell Lymphoma ◽  
The Impact ◽  
Large B Cell

scholarly journals The risk of clinical complications and death among pregnant women with COVID-19 in the Cerner COVID-19 cohort: a retrospective analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fares Qeadan ◽  
Nana A. Mensah ◽  
Benjamin Tingey ◽  
Joseph B. Stanford
Keyword(s):  
Pregnant Women ◽  
Disease Outbreaks ◽  
Hospital Length ◽  
Morbidity And Mortality ◽  
Hospital Length Of Stay ◽  
High Risk Population ◽  
Invasive Ventilation ◽  
Female Patients ◽  
Race Ethnicity ◽  
The Impact

Abstract Background Pregnant women are potentially a high-risk population during infectious disease outbreaks such as COVID-19, because of physiologic immune suppression in pregnancy. However, data on the morbidity and mortality of COVID-19 among pregnant women, compared to nonpregnant women, are sparse and inconclusive. We sought to assess the impact of pregnancy on COVID-19 associated morbidity and mortality, with particular attention to the impact of pre-existing comorbidity. Methods We used retrospective data from January through June 2020 on female patients aged 18–44 years old utilizing the Cerner COVID-19 de-identified cohort. We used mixed-effects logistic and exponential regression models to evaluate the risk of hospitalization, maximum hospital length of stay (LOS), moderate ventilation, invasive ventilation, and death for pregnant women while adjusting for age, race/ethnicity, insurance, Elixhauser AHRQ weighted Comorbidity Index, diabetes history, medication, and accounting for clustering of results in similar zip-code regions. Results Out of 22,493 female patients with associated COVID-19, 7.2% (n = 1609) were pregnant. Crude results indicate that pregnant women, compared to non-pregnant women, had higher rates of hospitalization (60.5% vs. 17.0%, P < 0.001), higher mean maximum LOS (0.15 day vs. 0.08 day, P < 0.001) among those who stayed < 1 day, lower mean maximum LOS (2.55 days vs. 3.32 days, P < 0.001) among those who stayed ≥1 day, and higher moderate ventilation use (1.7% vs. 0.7%, P < 0.001) but showed no significant differences in rates of invasive ventilation or death. After adjusting for potentially confounding variables, pregnant women, compared to non-pregnant women, saw higher odds in hospitalization (aOR: 12.26; 95% CI (10.69, 14.06)), moderate ventilation (aOR: 2.35; 95% CI (1.48, 3.74)), higher maximum LOS among those who stayed < 1 day, and lower maximum LOS among those who stayed ≥1 day. No significant associations were found with invasive ventilation or death. For moderate ventilation, differences were seen among age and race/ethnicity groups. Conclusions Among women with COVID-19 disease, pregnancy confers substantial additional risk of morbidity, but no difference in mortality. Knowing these variabilities in the risk is essential to inform decision-makers and guide clinical recommendations for the management of COVID-19 in pregnant women.

scholarly journals Social origin and educational attainment in China: a historical analysis of 70 birth cohorts

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Changchun Fang ◽  
Xiaotian Feng
Keyword(s):  
Social Context ◽  
Educational Attainment ◽  
Educational Inequality ◽  
Historical Analysis ◽  
Chinese Society ◽  
Structural Factors ◽  
Social Origin ◽  
Birth Cohorts ◽  
The Social ◽  
The Impact

Abstract The impact of social origin on educational attainment is conditioned on the social context in which people live. In recent decades, with changes in the Chinese society, how has the impact of social origin on educational inequality changed? Based on an analysis of 70 birth cohorts, this study details the effect of social origin on educational inequality and its trends over the past 70 years. The results of this study also indicate that the historical stages hypothesis (HSH) and model-shift hypothesis (MSH) emphasized in previous studies cannot fully describe the historical changes in educational inequality. In addition to macrosocial processes, there may exist other structural factors that also affect educational inequality but are neglected. The social context and its transformation, which shaped the relationship between social origin and educational inequality, need to be examined in more detail.

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