Dynamics and Control of Fluidized Catalytic Crackers. 4. The Impact of Design on Partial Control

1997 ◽  
Vol 36 (3) ◽  
pp. 747-759 ◽  
Author(s):  
Arnon Arbel ◽  
Irven H. Rinard ◽  
Reuel Shinnar
Keyword(s):  
Partial Control ◽  
Dynamics And Control ◽  
And Control ◽  
The Impact

scholarly journals Dynamics and control of measles in Portugal: Accessing the impact of anticipating the age for the first dose of MMR from 15 to 12 months of age

Vaccine ◽  
2008 ◽  
Vol 26 (19) ◽  
pp. 2418-2427 ◽  
Author(s):  
Ana Cristina Paulo ◽  
Manuel C. Gomes ◽  
M.Gabriela M. Gomes
Keyword(s):  
Dynamics And Control ◽  
And Control ◽  
The Impact

scholarly journals Mathematical modelling and phylodynamics for the study of dog rabies dynamics and control: A scoping review

2021 ◽  
Vol 15 (5) ◽  
pp. e0009449
Author(s):  
Maylis Layan ◽  
Simon Dellicour ◽  
Guy Baele ◽  
Simon Cauchemez ◽  
Hervé Bourhy
Keyword(s):  
Mathematical Modelling ◽  
Mathematical Models ◽  
Scoping Review ◽  
Control Strategies ◽  
Domestic Dog ◽  
Interdisciplinary Approaches ◽  
Dynamics And Control ◽  
And Control ◽  
The Impact

Background Rabies is a fatal yet vaccine-preventable disease. In the last two decades, domestic dog populations have been shown to constitute the predominant reservoir of rabies in developing countries, causing 99% of human rabies cases. Despite substantial control efforts, dog rabies is still widely endemic and is spreading across previously rabies-free areas. Developing a detailed understanding of dog rabies dynamics and the impact of vaccination is essential to optimize existing control strategies and developing new ones. In this scoping review, we aimed at disentangling the respective contributions of mathematical models and phylodynamic approaches to advancing the understanding of rabies dynamics and control in domestic dog populations. We also addressed the methodological limitations of both approaches and the remaining issues related to studying rabies spread and how this could be applied to rabies control. Methodology/principal findings We reviewed how mathematical modelling of disease dynamics and phylodynamics have been developed and used to characterize dog rabies dynamics and control. Through a detailed search of the PubMed, Web of Science, and Scopus databases, we identified a total of n = 59 relevant studies using mathematical models (n = 30), phylodynamic inference (n = 22) and interdisciplinary approaches (n = 7). We found that despite often relying on scarce rabies epidemiological data, mathematical models investigated multiple aspects of rabies dynamics and control. These models confirmed the overwhelming efficacy of massive dog vaccination campaigns in all settings and unraveled the role of dog population structure and frequent introductions in dog rabies maintenance. Phylodynamic approaches successfully disentangled the evolutionary and environmental determinants of rabies dispersal and consistently reported support for the role of reintroduction events and human-mediated transportation over long distances in the maintenance of rabies in endemic areas. Potential biases in data collection still need to be properly accounted for in most of these analyses. Finally, interdisciplinary studies were determined to provide the most comprehensive assessments through hypothesis generation and testing. They also represent new avenues, especially concerning the reconstruction of local transmission chains or clusters through data integration. Conclusions/significance Despite advances in rabies knowledge, substantial uncertainty remains regarding the mechanisms of local spread, the role of wildlife in dog rabies maintenance, and the impact of community behavior on the efficacy of control strategies including vaccination of dogs. Future integrative approaches that use phylodynamic analyses and mechanistic models within a single framework could take full advantage of not only viral sequences but also additional epidemiological information as well as dog ecology data to refine our understanding of rabies spread and control. This would represent a significant improvement on past studies and a promising opportunity for canine rabies research in the frame of the One Health concept that aims to achieve better public health outcomes through cross-sector collaboration.

scholarly journals Transmission dynamics and control of multidrug-resistant Klebsiella pneumoniae in neonates in a developing country

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Thomas Crellen ◽  
Paul Turner ◽  
Sreymom Pol ◽  
Stephen Baker ◽  
To Nguyen Thi Nguyen ◽  
...  
Keyword(s):  
Klebsiella Pneumoniae ◽  
Neonatal Intensive Care ◽  
Dynamic Models ◽  
Generation Cephalosporin ◽  
Multidrug Resistant ◽  
Transmission Risk ◽  
Dynamics And Control ◽  
One Year ◽  
And Control ◽  
The Impact

Multidrug-resistant Klebsiella pneumoniae is an increasing cause of infant mortality in developing countries. We aimed to develop a quantitative understanding of the drivers of this epidemic by estimating the effects of antibiotics on nosocomial transmission risk, comparing competing hypotheses about mechanisms of spread, and quantifying the impact of potential interventions. Using a sequence of dynamic models, we analysed data from a one-year prospective carriage study in a Cambodian neonatal intensive care unit with hyperendemic third-generation cephalosporin-resistant K. pneumoniae. All widely-used antibiotics except imipenem were associated with an increased daily acquisition risk, with an odds ratio for the most common combination (ampicillin + gentamicin) of 1.96 (95% CrI 1.18, 3.36). Models incorporating genomic data found that colonisation pressure was associated with a higher transmission risk, indicated sequence type heterogeneity in transmissibility, and showed that within-ward transmission was insufficient to maintain endemicity. Simulations indicated that increasing the nurse-patient ratio could be an effective intervention.

scholarly journals State-level needs for social distancing and contact tracing to contain COVID-19 in the United States 

2020 ◽  
Author(s):  
Weihsueh A. Chiu ◽  
Rebecca Fischer ◽  
Martial L. Ndeffo-Mbah
Keyword(s):  
Large Scale ◽  
District Of Columbia ◽  
State Level ◽  
The United States ◽  
Contact Tracing ◽  
Social Distancing ◽  
Epidemic Curve ◽  
Dynamics And Control ◽  
And Control ◽  
The Impact

Abstract Starting in mid-May 2020, many US states began relaxing social distancing measures that were put in place to mitigate the spread of COVID-19. To evaluate the impact of relaxation of restrictions on COVID-19 dynamics and control, we developed a transmission dynamic model and calibrated it to US state-level COVID-19 cases and deaths. We used this model to evaluate the impact of social distancing, testing and contact tracing on the COVID-19 epidemic in each state. As of July 22, 2020, we found only three states were on track to curtail their epidemic curve. Thirty-nine states and the District of Columbia may have to double their testing and/or tracing rates and/or rolling back reopening by 25%, while eight states require an even greater measure of combined testing, tracing, and distancing. Increased testing and contact tracing capacity is paramount for mitigating the recent large-scale increases in U.S. cases and deaths.

Heterogeneities in schistosome transmission dynamics and control

Parasitology ◽  
1998 ◽  
Vol 117 (5) ◽  
pp. 475-482 ◽  
Author(s):  
M. E. J. WOOLHOUSE ◽  
J.-F. ETARD ◽  
K. DIETZ ◽  
P. D. NDHLOVU ◽  
S. K. CHANDIWANA
Keyword(s):  
Reproduction Number ◽  
Transmission Dynamics ◽  
Water Contact ◽  
Contact Rates ◽  
Control Programmes ◽  
Contact Data ◽  
Dynamics And Control ◽  
And Control ◽  
The Impact ◽  
The Basic Reproduction Number

We review the theoretical framework for exploring the impact of individual and spatial heterogeneities in patterns of exposure and contamination and on the basic reproduction number, R0, for human schistosomes. Analysis of water contact data for 5 communities in Zimbabwe and Mali suggests that the impact is substantial, increasing R0 by factors of up to 6·5, mostly due to highly overdispersed distributions of contact rates among individuals. Several practical conclusions emerge: concentration of contacts at a single site should be avoided; the impact of control targeted at certain sites cannot be predicted without knowledge of how individuals' contacts are distributed among sites; control programmes targeted at individuals or sites contributing most to transmission can be very efficient but, conversely, will be ineffective if any of these individuals or sites are missed.

scholarly journals The impact of long-term non-pharmaceutical interventions on COVID-19 epidemic dynamics and control: the value and limitations of early models

2021 ◽  
Vol 288 (1957) ◽  
pp. 20210811
Author(s):  
Marissa L. Childs ◽  
Morgan P. Kain ◽  
Mallory J. Harris ◽  
Devin Kirk ◽  
Lisa Couper ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Compartment Model ◽  
Limited Information ◽  
Epidemic Dynamics ◽  
Transmission Parameters ◽  
Santa Clara County ◽  
Dynamics And Control ◽  
Intervention Policy ◽  
And Control ◽  
The Impact

Mathematical models of epidemics are important tools for predicting epidemic dynamics and evaluating interventions. Yet, because early models are built on limited information, it is unclear how long they will accurately capture epidemic dynamics. Using a stochastic SEIR model of COVID-19 fitted to reported deaths, we estimated transmission parameters at different time points during the first wave of the epidemic (March–June, 2020) in Santa Clara County, California. Although our estimated basic reproduction number ( R 0 ) remained stable from early April to late June (with an overall median of 3.76), our estimated effective reproduction number ( R E ) varied from 0.18 to 1.02 in April before stabilizing at 0.64 on 27 May. Between 22 April and 27 May, our model accurately predicted dynamics through June; however, the model did not predict rising summer cases after shelter-in-place orders were relaxed in June, which, in early July, was reflected in cases but not yet in deaths. While models are critical for informing intervention policy early in an epidemic, their performance will be limited as epidemic dynamics evolve. This paper is one of the first to evaluate the accuracy of an early epidemiological compartment model over time to understand the value and limitations of models during unfolding epidemics.

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