Factors affecting healthcare workers’ compliance with social and behavioural infection control measures during emerging infectious disease outbreaks: Rapid evidence review

AbstractThe 2019-2020 outbreak of novel coronavirus has raised concerns about nosocomial transmission; that is, transmission within healthcare settings. Research from previous outbreaks of emerging infectious diseases suggests a major cause of nosocomial transmission is healthcare professionals’ poor compliance with recommended personal protective behaviours. This rapid evidence review explored existing literature on emerging infectious disease outbreaks to identify factors associated with compliance with social and behavioural infection control measures among healthcare staff. 56 papers were reviewed and several positive associations were found: Staff working in emergency or intensive care settings appeared more likely to comply with recommendations than those in other settings, and there was some evidence that contact with confirmed cases could improve compliance. There was some evidence that staff with higher levels of anxiety and higher concern about the risk of infection were more likely to comply with recommended behaviour, and that monitoring from superiors could improve compliance. Several negative associations were also found. Observed non-compliance of colleagues could hinder compliance. Staff identified many barriers to compliance related to personal protective equipment, including availability; perceived difficulty and effectiveness; inconvenience; discomfort; and a negative impact on patient care. There appeared to be many issues regarding the communication and ease of understanding of infection control guidance. Based on the results of this review we recommend provision of training and education tailored for different occupational roles within the healthcare setting; managerial staff ‘leading by example’; ensuring adequate resources for infection control; and timely provision of practical evidence-based infection control guidelines.

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Factors affecting healthcare workers’ compliance with social and behavioural infection control measures during emerging infectious disease outbreaks: rapid evidence review

BMJ Open ◽

10.1136/bmjopen-2021-049857 ◽

2021 ◽

Vol 11 (8) ◽

pp. e049857

Author(s):

Samantha K Brooks ◽

N Greenberg ◽

Simon Wessely ◽

G J Rubin

Keyword(s):

Infectious Disease ◽

Infection Control ◽

Healthcare Workers ◽

Negative Impact ◽

Disease Outbreaks ◽

Emerging Infectious Disease ◽

Control Measures ◽

Infectious Disease Outbreaks ◽

Infection Control Measures ◽

Evidence Review

ObjectiveThe 2019–2020 outbreak of novel coronavirus has raised concerns about nosocomial transmission. This review’s aim was to explore the existing literature on emerging infectious disease outbreaks to identify factors associated with compliance with infection control measures among healthcare staff.MethodsA rapid evidence review for primary studies relevant to healthcare workers’ compliance with infection control measures.ResultsFifty-six papers were reviewed. Staff working in emergency or intensive care settings or with contact with confirmed cases appeared more likely to comply with recommendations. There was some evidence that anxiety and concern about the risk of infection were more associated with compliance, and that monitoring from superiors could improve compliance. Observed non-compliance of colleagues could hinder compliance. Staff identified many barriers to compliance related to personal protective equipment, including availability, perceived difficulty and effectiveness, inconvenience, discomfort and a negative impact on patient care. There were many issues regarding the communication and ease of understanding of infection control guidance.ConclusionWe recommend provision of training and education tailored for different occupational roles within the healthcare setting, managerial staff ‘leading by example’, ensuring adequate resources for infection control and timely provision of practical evidence-based infection control guidelines.

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Transmission network of the 2014–2015 Ebola epidemic in Sierra Leone

Journal of The Royal Society Interface ◽

10.1098/rsif.2015.0536 ◽

2015 ◽

Vol 12 (112) ◽

pp. 20150536 ◽

Cited By ~ 33

Author(s):

Wan Yang ◽

Wenyi Zhang ◽

David Kargbo ◽

Ruifu Yang ◽

Yong Chen ◽

...

Keyword(s):

Infectious Disease ◽

Sierra Leone ◽

Disease Outbreaks ◽

Emerging Infectious Disease ◽

Control Measures ◽

Transmission Network ◽

Spatial Expansion ◽

Critical Window ◽

Infectious Disease Outbreaks ◽

Observational Errors

Understanding the growth and spatial expansion of (re)emerging infectious disease outbreaks, such as Ebola and avian influenza, is critical for the effective planning of control measures; however, such efforts are often compromised by data insufficiencies and observational errors. Here, we develop a spatial–temporal inference methodology using a modified network model in conjunction with the ensemble adjustment Kalman filter, a Bayesian inference method equipped to handle observational errors. The combined method is capable of revealing the spatial–temporal progression of infectious disease, while requiring only limited, readily compiled data. We use this method to reconstruct the transmission network of the 2014–2015 Ebola epidemic in Sierra Leone and identify source and sink regions. Our inference suggests that, in Sierra Leone, transmission within the network introduced Ebola to neighbouring districts and initiated self-sustaining local epidemics; two of the more populous and connected districts, Kenema and Port Loko, facilitated two independent transmission pathways. Epidemic intensity differed by district, was highly correlated with population size ( r = 0.76, p = 0.0015) and a critical window of opportunity for containing local Ebola epidemics at the source ( ca one month) existed. This novel methodology can be used to help identify and contain the spatial expansion of future (re)emerging infectious disease outbreaks.

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Narrative synthesis of psychological and coping responses towards emerging infectious disease outbreaks in the general population: practical considerations for the COVID-19 pandemic

Singapore Medical Journal ◽

10.11622/smedj.2020046 ◽

2020 ◽

Vol 61 (7) ◽

pp. 350-356 ◽

Cited By ~ 46

Author(s):

QH Chew ◽

KC Wei ◽

S, Vasoo ◽

HC Chua ◽

K Sim

Keyword(s):

Infectious Disease ◽

General Population ◽

Disease Outbreaks ◽

Emerging Infectious Disease ◽

Narrative Synthesis ◽

Coping Responses ◽

Infectious Disease Outbreaks ◽

And Coping

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Proactive infection control measures to prevent nosocomial transmission of VRE

Journal of Microbiology Immunology and Infection ◽

10.1016/j.jmii.2015.02.192 ◽

2015 ◽

Vol 48 (2) ◽

pp. S24

Author(s):

Vincent C.C. Cheng ◽

S.C. Wong ◽

K.Y. Yuen

Keyword(s):

Infection Control ◽

Control Measures ◽

Nosocomial Transmission ◽

Infection Control Measures

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Evaluation of Infection Control Measures in Preventing the Nosocomial Transmission of Multidrug-Resistant Mycobacterium tuberculosis in a New York City Hospital

Infection Control and Hospital Epidemiology ◽

10.1086/647075 ◽

1995 ◽

Vol 16 (3) ◽

pp. 141-147 ◽

Cited By ~ 17

Author(s):

Leonardo A. Stroud ◽

Jerome I. Tokars ◽

Michael H. Grieco ◽

Jack T. Crawford ◽

David H. Culver ◽

...

Keyword(s):

New York ◽

New York City ◽

Mycobacterium Tuberculosis ◽

Infection Control ◽

York City ◽

Multidrug Resistant ◽

Control Measures ◽

Nosocomial Transmission ◽

City Hospital ◽

Infection Control Measures

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Perfect counterfactuals for epidemic simulations

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2018.0279 ◽

2019 ◽

Vol 374 (1776) ◽

pp. 20180279 ◽

Cited By ~ 4

Author(s):

Joshua Kaminsky ◽

Lindsay T. Keegan ◽

C. Jessica E. Metcalf ◽

Justin Lessler

Keyword(s):

Infectious Disease ◽

Disease Outbreaks ◽

Computation Time ◽

Control Measures ◽

Mathematical Representation ◽

Theme Issue ◽

Stochastic Variation ◽

Infectious Disease Outbreaks ◽

Negative Effect ◽

And Control

Simulation studies are often used to predict the expected impact of control measures in infectious disease outbreaks. Typically, two independent sets of simulations are conducted, one with the intervention, and one without, and epidemic sizes (or some related metric) are compared to estimate the effect of the intervention. Since it is possible that controlled epidemics are larger than uncontrolled ones if there is substantial stochastic variation between epidemics, uncertainty intervals from this approach can include a negative effect even for an effective intervention. To more precisely estimate the number of cases an intervention will prevent within a single epidemic, here we develop a ‘single-world’ approach to matching simulations of controlled epidemics to their exact uncontrolled counterfactual. Our method borrows concepts from percolation approaches, prunes out possible epidemic histories and creates potential epidemic graphs (i.e. a mathematical representation of all consistent epidemics) that can be ‘realized’ to create perfectly matched controlled and uncontrolled epidemics. We present an implementation of this method for a common class of compartmental models (e.g. SIR models), and its application in a simple SIR model. Results illustrate how, at the cost of some computation time, this method substantially narrows confidence intervals and avoids nonsensical inferences. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.

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Reducing the risk of future emerging infectious disease outbreaks by changing social norms around urban bushmeat consumption and stopping its commercial trade

10.19121/2020.report.37433 ◽

2020 ◽

Author(s):

Keyword(s):

Infectious Disease ◽

Social Norms ◽

Disease Outbreaks ◽

Emerging Infectious Disease ◽

Infectious Disease Outbreaks ◽

Commercial Trade

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Sterilization and Infection Control Measures in Dental Operatory

International Journal of Advanced and Integrated Medical Sciences ◽

10.5005/jp-journals-10050-10084 ◽

2017 ◽

Vol 2 (2) ◽

pp. 97-100

Author(s):

Santosh K Verma

Keyword(s):

Infectious Disease ◽

Health Care ◽

Infection Control ◽

Control Measures ◽

Health Care Personnel ◽

Treatment Mode ◽

Safe Environment ◽

Infection Control Measures ◽

Health Care Practitioners ◽

Control Protocols

ABSTRACT Increase in the incidence of serious transmissible diseases over the last few decades has enhanced major concern and impacted the treatment mode of all health care practitioners. Nowadays, more emphasis is made to assure the patients that they are well protected from risks of infectious disease. Infection control is the most important phase of any dental therapy that has helped to allay concerns of the health care personnel and in providing a safe environment for both patient and personnel. This study reviews different sterilization and infection control protocols in a dental operatory. How to cite this article Mohan S, Prajapati VK, Verma SK. Sterilization and Infection Control Measures in Dental Operatory. Int J Adv Integ Med Sci 2017;2(2):97-100.

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