Beyond gigabit-per-second transmission rates

1987 ◽  
Author(s):  
RICHARD A. LINKE
Keyword(s):  
Transmission Rates

scholarly journals Transmission Potential of Zika Virus by Aedes aegypti (Diptera: Culicidae) and Ae. mediovittatus (Diptera: Culicidae) Populations From Puerto Rico

2021 ◽  
Author(s):  
Rebecca A Zimler ◽  
Donald A Yee ◽  
Barry W Alto
Keyword(s):  
Puerto Rico ◽  
Aedes Aegypti ◽  
Zika Virus ◽  
Mosquito Species ◽  
The United States ◽  
Infection Rates ◽  
Transmission Potential ◽  
Transmission Rates ◽  
Higher Doses ◽  
Local Transmission

Abstract Recurrence of local transmission of Zika virus in Puerto Rico is a major public health risk to the United States, where mosquitoes Aedes aegypti (Linnaeus) and Aedes mediovittatus (Coquillett) are abundant. To determine the extent to which Ae. mediovittatus are capable of transmitting Zika virus and the influence of viremia, we evaluated infection and transmission in Ae. mediovittatus and Ae. aegypti from Puerto Rico using serial dilutions of infectious blood. Higher doses of infectious blood resulted in greater infection rates in both mosquitoes. Aedes aegypti females were up to twice as susceptible to infection than Ae. mediovittatus, indicating a more effective midgut infection barrier in the latter mosquito species. Aedes aegypti exhibited higher disseminated infection (40–95%) than Ae. mediovittatus (<5%), suggesting a substantial midgut escape barrier in Ae. mediovittatus. For Ae. aegypti, transmission rates were low over a range of doses of Zika virus ingested, suggesting substantial salivary gland barriers.

scholarly journals Who acquires infection from whom? Estimating herpesvirus transmission rates between wild rodent host groups

Epidemics ◽  
2021 ◽  
pp. 100451
Author(s):  
Diana Erazo ◽  
Amy B. Pedersen ◽  
Kayleigh Gallagher ◽  
Andy Fenton
Keyword(s):  
Wild Rodent ◽  
Rodent Host ◽  
Transmission Rates

scholarly journals Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Setting-specific Transmission Rates: A Systematic Review and Meta-analysis

2021 ◽  
Author(s):  
Hayley A Thompson ◽  
Andria Mousa ◽  
Amy Dighe ◽  
Han Fu ◽  
Alberto Arnedo-Pena ◽  
...  
Keyword(s):  
Systematic Review ◽  
Severe Acute Respiratory Syndrome ◽  
Negative Binomial ◽  
Meta Analysis ◽  
Contact Tracing ◽  
Binomial Model ◽  
Transmission Potential ◽  
Transmission Rates ◽  
Symptom Status ◽  
Index Cases

Abstract Background Understanding the drivers of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission is crucial for control policies, but evidence of transmission rates in different settings remains limited. Methods We conducted a systematic review to estimate secondary attack rates (SARs) and observed reproduction numbers (Robs) in different settings exploring differences by age, symptom status, and duration of exposure. To account for additional study heterogeneity, we employed a beta-binomial model to pool SARs across studies and a negative-binomial model to estimate Robs. Results Households showed the highest transmission rates, with a pooled SAR of 21.1% (95% confidence interval [CI]:17.4–24.8). SARs were significantly higher where the duration of household exposure exceeded 5 days compared with exposure of ≤5 days. SARs related to contacts at social events with family and friends were higher than those for low-risk casual contacts (5.9% vs 1.2%). Estimates of SARs and Robs for asymptomatic index cases were approximately one-seventh, and for presymptomatic two-thirds of those for symptomatic index cases. We found some evidence for reduced transmission potential both from and to individuals younger than 20 years of age in the household context, which is more limited when examining all settings. Conclusions Our results suggest that exposure in settings with familiar contacts increases SARS-CoV-2 transmission potential. Additionally, the differences observed in transmissibility by index case symptom status and duration of exposure have important implications for control strategies, such as contact tracing, testing, and rapid isolation of cases. There were limited data to explore transmission patterns in workplaces, schools, and care homes, highlighting the need for further research in such settings.

scholarly journals Effect of park use and landscape structure on COVID-19 transmission rates

2021 ◽  
pp. 148123
Author(s):  
Thomas F. Johnson ◽  
Lisbeth A. Hordley ◽  
Matthew P. Greenwell ◽  
Luke C. Evans
Keyword(s):  
Landscape Structure ◽  
Transmission Rates ◽  
Park Use

scholarly journals Uncovering the structure and temporal dynamics of information propagation

2014 ◽  
Vol 2 (1) ◽  
pp. 26-65 ◽  
Author(s):  
MANUEL GOMEZ RODRIGUEZ ◽  
JURE LESKOVEC ◽  
DAVID BALDUZZI ◽  
BERNHARD SCHÖLKOPF
Keyword(s):  
News Media ◽  
Information Diffusion ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Inference Algorithm ◽  
Information Propagation ◽  
Transmission Rates ◽  
Diffusion Dynamics ◽  
Underlying Network ◽  
News Events

AbstractTime plays an essential role in the diffusion of information, influence, and disease over networks. In many cases we can only observe when a node is activated by a contagion—when a node learns about a piece of information, makes a decision, adopts a new behavior, or becomes infected with a disease. However, the underlying network connectivity and transmission rates between nodes are unknown. Inferring the underlying diffusion dynamics is important because it leads to new insights and enables forecasting, as well as influencing or containing information propagation. In this paper we model diffusion as a continuous temporal process occurring at different rates over a latent, unobserved network that may change over time. Given information diffusion data, we infer the edges and dynamics of the underlying network. Our model naturally imposes sparse solutions and requires no parameter tuning. We develop an efficient inference algorithm that uses stochastic convex optimization to compute online estimates of the edges and transmission rates. We evaluate our method by tracking information diffusion among 3.3 million mainstream media sites and blogs, and experiment with more than 179 million different instances of information spreading over the network in a one-year period. We apply our network inference algorithm to the top 5,000 media sites and blogs and report several interesting observations. First, information pathways for general recurrent topics are more stable across time than for on-going news events. Second, clusters of news media sites and blogs often emerge and vanish in a matter of days for on-going news events. Finally, major events, for example, large scale civil unrest as in the Libyan civil war or Syrian uprising, increase the number of information pathways among blogs, and also increase the network centrality of blogs and social media sites.

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