scholarly journals Does better identification of the Legionella pneumophila serogroup 1 strains by Sequence-Based Typing (SBT) allow for the implementation of more effective contamination control strategies and more targeted intervention measures?

2014 ◽  
Vol 115 ◽  
pp. 126-129 ◽  
Author(s):  
Savina Ditommaso ◽  
Monica Giacomuzzi ◽  
Susan R. Arauco Rivera ◽  
Carla M. Zotti
Keyword(s):  
Legionella Pneumophila ◽  
Control Strategies ◽  
Targeted Intervention ◽  
Contamination Control ◽  
Intervention Measures

A Contamination Control Strategy Gone Wrong

2021 ◽  
Vol 25 (5) ◽  
Author(s):  
Jeanne Moldenhauer
Keyword(s):  
Control Strategy ◽  
Control Strategies ◽  
Pharmaceutical Manufacturing ◽  
Production Facility ◽  
Vaccine Production ◽  
Contamination Control

Warning letters and regulatory inspection observation reports (e.g., FDA 483) often provide useful information for assessing risks in your facility and preparing for upcoming inspections. Starting with the updates to the European Union’s Annex 1 for the Manufacture of Sterile Drugs there has been an increased focus on contamination control strategies in facilities. A contamination control strategy is an integral part of pharmaceutical manufacturing, whether sterile or non-sterile. For this article we are going to look at a series of observations for a vaccine production facility and how we might learn from these observations. Highlighted are some of the contamination control issues. The FDA 483 Report was published in redacted form.

scholarly journals SARS-CoV-2 transmission across age groups in France and implications for control

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Cécile Tran Kiem ◽  
Paolo Bosetti ◽  
Juliette Paireau ◽  
Pascal Crépey ◽  
Henrik Salje ◽  
...  
Keyword(s):  
Young Adults ◽  
Age Groups ◽  
Deep Understanding ◽  
Transmission Dynamics ◽  
Age Group ◽  
Older Individuals ◽  
Targeted Intervention ◽  
Social Distancing ◽  
Intervention Measures ◽  
Better Than

AbstractThe shielding of older individuals has been proposed to limit COVID-19 hospitalizations while relaxing general social distancing in the absence of vaccines. Evaluating such approaches requires a deep understanding of transmission dynamics across ages. Here, we use detailed age-specific case and hospitalization data to model the rebound in the French epidemic in summer 2020, characterize age-specific transmission dynamics and critically evaluate different age-targeted intervention measures in the absence of vaccines. We find that while the rebound started in young adults, it reached individuals aged ≥80 y.o. after 4 weeks, despite substantial contact reductions, indicating substantial transmission flows across ages. We derive the contribution of each age group to transmission. While shielding older individuals reduces mortality, it is insufficient to allow major relaxations of social distancing. When the epidemic remains manageable (R close to 1), targeting those most contributing to transmission is better than shielding at-risk individuals. Pandemic control requires an effort from all age groups.

Hopf bifurcation of a delay SIRS epidemic model with novel nonlinear incidence: Application to scarlet fever

2018 ◽  
Vol 11 (07) ◽  
pp. 1850091 ◽  
Author(s):  
Yong Li ◽  
Xianning Liu ◽  
Lianwen Wang ◽  
Xingan Zhang
Keyword(s):  
Hopf Bifurcation ◽  
Time Delay ◽  
Epidemic Model ◽  
Scarlet Fever ◽  
Reproduction Number ◽  
Control Strategies ◽  
Nonlinear Incidence ◽  
Sirs Epidemic Model ◽  
Intervention Measures ◽  
Theoretical Results

An [Formula: see text] epidemic model incorporating incubation time delay and novel nonlinear incidence is proposed and analyzed to seek for the control strategies of scarlet fever, where the contact rate which can reflect the regular behavior and habit changes of children is non-monotonic with respect to the number of susceptible. The model without delay may exhibit backward bifurcation and bistable states even though the basic reproduction number is less than unit. Furthermore, we derive the conditions for occurrence of Hopf bifurcation when the time delay is considered as a bifurcation parameter. The data of scarlet fever of China are simulated to verify our theoretical results. In the end, several effective preventive and intervention measures of scarlet fever are found out.

Legionella in sugar factory process waters – Analysis and control in Nordic Sugar

2011 ◽  
pp. 597-600
Author(s):  
Christer Bergwall
Keyword(s):  
Real Time ◽  
Legionella Pneumophila ◽  
Dna Analysis ◽  
Control Strategies ◽  
Cooling Water ◽  
Treatment Method ◽  
Sugar Factory ◽  
Dispersing Agent ◽  
Assay Time ◽  
And Control

This presentation will summarise the experiences gained from a Legionella project within Nordic Sugar which emphasises risk evaluation, modern DNA analysis methods, control strategies and water treatment methods. The project started in 2002 with yearly campaign screenings for Legionella spp and Legionella pneumophila. Initially an ISO Legionella method for quantification was used, but this was replaced with a modern, rapid DNA-based Real Time Polymerase Chain Reaction assay in 2005. The assay time for quantitative results using the Real Time PCR is approximately 3 hours compared to between 10 and 14 days for the ISO-method. All Nordic Sugar factories equipped with cooling towers are screened on a weekly or bi-weekly basis during every sugar campaign. Only one sugar factory has shown consistently positive results for Legionella pneumophila on a moderate level. A multiple biocide approach combined with a dispersing agent was successfully used to control the Legionella. In 2010 a non-chemical treatment method, Wallenius AOT-system was installed to eliminate an annual high cost for biocides. The system successfully controlled the L. pneumophila even when the cooling water was partially exchanged with fresh lake water.

scholarly journals Analysis of COVID-19 Prevention and Control Effects Based on the SEITRD Dynamic Model and Wuhan Epidemic Statistics

2020 ◽  
Vol 17 (24) ◽  
pp. 9309
Author(s):  
Yusheng Zhang ◽  
Liang Li ◽  
Yuewen Jiang ◽  
Biqing Huang
Keyword(s):  
Dynamic Model ◽  
Control Method ◽  
Control Strategies ◽  
Dynamical Behavior ◽  
Model Parameters ◽  
Time Control ◽  
Intervention Measures ◽  
Travel Restrictions ◽  
And Control ◽  
The Impact

Since December 2019, millions of people worldwide have been diagnosed with COVID-19, which has caused enormous losses. Given that there are currently no effective treatment or prevention drugs, most countries and regions mainly rely on quarantine and travel restrictions to prevent the spread of the epidemic. How to find proper prevention and treatment methods has been a hot topic of discussion. The key to the problem is to understand when these intervention measures are the best strategies for disease control and how they might affect disease dynamics. In this paper, we build a transmission dynamic model in combination with the transmission characteristics of COVID-19. We thoroughly study the dynamical behavior of the model and analyze how to determine the relevant parameters, and how the parameters influence the transmission process. Furthermore, we subsequently compare the impact of different control strategies on the epidemic, the variables include intervention time, control duration, control intensity, and other model parameters. Finally, we can find a better control method by comparing the results under different schemes and choose the proper preventive control strategy according to the actual epidemic stage and control objectives.

scholarly journals Identification of two aptamers binding to Legionella pneumophila with high affinity and specificity

2019 ◽  
Author(s):  
Mariam Saad ◽  
Deanna Chinerman ◽  
Maryam Tabrizian ◽  
Sebastien P. Faucher
Keyword(s):  
Legionella Pneumophila ◽  
Control Strategies ◽  
Water System ◽  
Short Oligonucleotide ◽  
Counter Selection ◽  
Legionnaires Disease ◽  
In Situ Detection ◽  
Exponential Enrichment ◽  
Oligonucleotide Sequence

ABSTRACTLegionella pneumophila (Lp) is a water borne bacterium causing Legionnaires’ Disease (LD) in humans. Rapid detection of Lp in water system is essential to reduce the risk of LD outbreaks. The methods currently available require expert skills and are time intensive, thus delaying intervention. In situ detection of Lp by biosensor would allow rapid implementation of control strategies. To this end, a biorecognition element is required. Aptamers are considered promising biorecognition molecules for biosensing. Aptamers are short oligonucleotide sequence folding into a specific structure and are able to bind to specific molecules. Currently no aptamer and thus no aptamer-based technology exists for the detection of Lp. In this study, Systemic Evolution of Ligands through EXponential enrichment (SELEX) was used to identify aptamers binding specifically to Lp. Ten rounds of positive selection and two rounds of counter-selection against two Pseudomonas species were performed. Two aptamers binding strongly to Lp were identified with KD of 116 and 135 nM. Binding specificity of these two aptamers to Lp was confirmed by flow cytometry and fluorescence microscopy. Therefore, these two aptamers are promising biorecognition molecules for the detection of Lp in water systems.

scholarly journals Forecasting the long-term trend of COVID-19 epidemic using a dynamic model

2020 ◽  
Author(s):  
Jichao Sun ◽  
Xi Chen ◽  
Ziheng Zhang ◽  
Shengzhang Lai ◽  
Bo Zhao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Control Strategies ◽  
Integrated Approach ◽  
Cumulative Number ◽  
Learning Models ◽  
Term Trend ◽  
Intervention Measures ◽  
Long Term Trend ◽  
Machine Learning Models

Abstract Background The current outbreak of coronavirus disease 2019 (COVID-19) has recently been declared as a pandemic and spread over 200 countries and territories. Forecasting the long-term trend of the COVID-19 epidemic can help health authorities determine the transmission characteristics of the virus and take appropriate prevention and control strategies beforehand. Previous studies that applied the traditional epidemic models or machine learning models were subject to underfitting or overfitting problems.Methods We propose a new model named Dynamic-Susceptible-Exposed-Infective-Quarantined (D-SEIQ), by making appropriate modifications of the Susceptible-Exposed-Infective-Recovered (SEIR) model and integrating machine learning based parameter optimization under epidemiological rational constraints. We used the model to predict the long-term reported cumulative numbers of COVID-19 cases in China from 27 January, 2020.Results We evaluated our model on officially reported confirmed cases from three different regions in China, and the results proved the effectiveness of our model in terms of simulating and predicting the trend of COVID-19 outbreak. In China-Excluding-Hubei area within 7 days after the first public report, our model successfully and accurately predicted the 40 days long trend and the exact date of turning point. The predicted cumulative number (12,506) by 10, March 2020 was only 3·8% different with the actual number (13,005). The parameters obtained by our model proved the effectiveness of prevention and intervention strategies on epidemic control in China.Conclusions The integrated approach of epidemic and machine learning models could accurately forecast the long-term trend of COVID-19 outbreak. The learned parameters suggested the effectiveness of intervention measures taken in China.

Comparison of Chemical Filters for the Control of Airborne Molecular Contamination

2007 ◽  
Vol 50 (2) ◽  
pp. 52-72 ◽  
Author(s):  
Chris Muller
Keyword(s):  
Gas Phase ◽  
Control Strategies ◽  
Performance Evaluations ◽  
Air Filtration ◽  
Contamination Control ◽  
Factors Affecting ◽  
Filtration Equipment ◽  
Present Information ◽  
Definition Of ◽  
Control Application

Airborne molecular contamination (AMC) continues to grow as a major contamination control issue for microelectronics manufacturers. Because of this growth, chemical filter manufacturers are offering a large number of AMC control options from which the facility, process, and contamination control engineers must determine the best solution for their specific AMC control application(s). This paper will present information on the various types of chemical filters available, filter strengths and weaknesses, and the results of independent performance evaluations for a number of different chemical filter types. Several AMC control strategies employing chemical filtration will be discussed. Other topics include an introduction to gaseous contaminants and a definition of AMC; classifications of AMC; contaminants common to cleanroom applications, their sources, and effect; implementing AMC control—a three-step methodology for optimum control of AMC; gas-phase air filtration principles—adsorption, absorption, chemisorption, and factors affecting each; dry-scrubbing air filtration media—plain and chemically impregnated adsorbents; chemical filtration equipment designs—thin-bed and deep-bed systems; and AMC monitoring—passive and real-time reactivity monitors.

Shining (Invisible) Light On Viral Pathogens: Virucidal Contamination Control Strategies Using UV-C Light

2021 ◽  
Vol 27 (3) ◽  
Author(s):  
Tim Sandle
Keyword(s):  
Risk Mitigation ◽  
Control Strategies ◽  
Mitigation Strategies ◽  
Transmission Mode ◽  
Viral Pathogens ◽  
Contamination Control ◽  
Risk Mitigation Strategies ◽  
Respiratory Droplets ◽  
Uv C ◽  
Primary Transmission

Respiratory droplets are coronaviruses primary transmission mode and thus the majority of coronavirus risk mitigation strategies focus on the control of air. However, surface contact remains an alternative infection route. Hence, it remains a concern that the SARS CoV-2 virus can remain viable on surfaces for several hours.

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