A Risk Assessment Tool for Resumption of Research Activities During the COVID-19 Pandemic

Abstract Rationale: The spread of severe acute respiratory syndrome coronavirus-2 has suspended many non-COVID-19 related research activities. Where restarting research activities is permitted, investigators need to evaluate the risks and benefits of resuming data collection and adapt procedures to minimize risk. Objectives: In the context of the multicountry Household Air Pollution Intervention (HAPIN) trial, we developed a framework to assess the risk of each trial activity and to guide protective measures. Our goal is to maximize integrity of reseach aims while minimizing infection risk based on the latest understanding of the virus. Methods: We drew on a combination of expert consultations, risk assessment frameworks, institutional guidance and literature to develop our framework. We then systematically graded clinical, behavioral, laboratory and field environmental health research activities in four countries for both adult and child subjects using this framework. Results: Our framework assesses risk based on staff proximity to the participant, exposure time between staff and participants, and potential aerosolization while performing the activity. One of of four risk levels, from minimal to unacceptable, is assigned and guidance on protective measures is provided. Those activities which can potentially aerosolize the virus are deemed the highest risk. Conclusions: By applying a systematic, procedure-specific approach to risk assessment for each trial activity, we can compare trial activities using the same criteria. This approach allows us to protect our participants and research team and to uphold our ability to deliver on the research commitments we have made to our participants, local communities, and funders. The trial is registered with clinicaltrials.gov (NCT02944682).

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A risk assessment tool for resumption of research activities during the COVID-19 pandemic for field trials in low resource settings

BMC Medical Research Methodology ◽

10.1186/s12874-021-01232-x ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Suzanne M. Simkovich ◽

◽

Lisa M. Thompson ◽

Maggie L. Clark ◽

Kalpana Balakrishnan ◽

...

Keyword(s):

Risk Assessment ◽

Assessment Tool ◽

Field Trials ◽

Protective Measures ◽

Low Resource Settings ◽

Risk Levels ◽

Low Resource ◽

Research Activities ◽

Environmental Health Research ◽

Need To Evaluate

Abstract Rationale The spread of severe acute respiratory syndrome coronavirus-2 has suspended many non-COVID-19 related research activities. Where restarting research activities is permitted, investigators need to evaluate the risks and benefits of resuming data collection and adapt procedures to minimize risk. Objectives In the context of the multicountry Household Air Pollution Intervention (HAPIN) trial conducted in rural, low-resource settings, we developed a framework to assess the risk of each trial activity and to guide protective measures. Our goal is to maximize the integrity of reseach aims while minimizing infection risk based on the latest scientific understanding of the virus. Methods We drew on a combination of expert consultations, risk assessment frameworks, institutional guidance and literature to develop our framework. We then systematically graded clinical, behavioral, laboratory and field environmental health research activities in four countries for both adult and child subjects using this framework. National and local government recommendations provided the minimum safety guidelines for our work. Results Our framework assesses risk based on staff proximity to the participant, exposure time between staff and participants, and potential viral aerosolization while performing the activity. For each activity, one of four risk levels, from minimal to unacceptable, is assigned and guidance on protective measures is provided. Those activities that can potentially aerosolize the virus are deemed the highest risk. Conclusions By applying a systematic, procedure-specific approach to risk assessment for each trial activity, we were able to protect our participants and research team and to uphold our ability to deliver on the research commitments we have made to our staff, participants, local communities, and funders. This framework can be tailored to other research studies conducted in similar settings during the current pandemic, as well as potential future outbreaks with similar transmission dynamics. The trial is registered with clinicaltrials.gov NCT02944682 on October 26. 2016 .

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Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions

Ocean Science Discussions ◽

10.5194/osd-12-1327-2015 ◽

2015 ◽

Vol 12 (4) ◽

pp. 1327-1388 ◽

Cited By ~ 2

Author(s):

R. Fernandes ◽

F. Braunschweig ◽

F. Lourenço ◽

R. Neves

Keyword(s):

Risk Assessment ◽

Real Time ◽

Oil Spill ◽

Situational Awareness ◽

Assessment Tool ◽

Weather Conditions ◽

Traffic Monitoring ◽

Automatic Identification ◽

Decision Support Model ◽

Risk Levels

Abstract. The technological evolution in terms of computational capacity, data acquisition systems, numerical modelling and operational oceanography is supplying opportunities for designing and building holistic approaches and complex tools for newer and more efficient management (planning, prevention and response) of coastal water pollution risk events. A combined methodology to dynamically estimate time and space variable shoreline risk levels from ships has been developed, integrating numerical metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS). The risk rating combines the likelihood of an oil spill occurring from a vessel navigating in a study area – Portuguese Continental shelf – with the assessed consequences to the shoreline. The spill likelihood is based on dynamic marine weather conditions and statistical information from previous accidents. The shoreline consequences reflect the virtual spilled oil amount reaching shoreline and its environmental and socio-economic vulnerabilities. The oil reaching shoreline is quantified with an oil spill fate and behaviour model running multiple virtual spills from vessels along time. Shoreline risks can be computed in real-time or from previously obtained data. Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and to oil transport behaviour. The integration of meteo-oceanic + oil spill models with coastal vulnerability and AIS data in the quantification of risk enhances the maritime situational awareness and the decision support model, providing a more realistic approach in the assessment of shoreline impacts. The risk assessment from historical data can help finding typical risk patterns, "hot spots" or developing sensitivity analysis to specific conditions, whereas real time risk levels can be used in the prioritization of individual ships, geographical areas, strategic tug positioning and implementation of dynamic risk-based vessel traffic monitoring.

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Professional Discretion and the Predictive Validity of a Juvenile Risk Assessment Instrument

Youth Violence and Juvenile Justice ◽

10.1177/1541204015622255 ◽

2016 ◽

Vol 15 (2) ◽

pp. 103-118 ◽

Cited By ~ 7

Author(s):

James T. McCafferty

Keyword(s):

Risk Assessment ◽

Predictive Validity ◽

Assessment Tool ◽

Assessment Instrument ◽

Adjusted Risk ◽

Risk Levels ◽

Risk Assessment Instrument ◽

Actuarial Risk ◽

Using Data ◽

The Impact

The ability for professionals to override the results of an actuarial risk assessment tool is an essential part of effective correctional risk classification; however, little is known about how this important function affects the predictive validity of these tools. Using data from a statewide sample of juveniles from Ohio, this study examined the impact of professional adjustments on the predictive validity of a juvenile risk assessment instrument. This study found that the original and adjusted risk levels were significant predictors of recidivism, but the original risk levels were stronger predictors of recidivism than the adjusted risk levels that accounted for overrides.

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Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions

Ocean Science ◽

10.5194/os-12-285-2016 ◽

2016 ◽

Vol 12 (1) ◽

pp. 285-317 ◽

Cited By ~ 9

Author(s):

R. Fernandes ◽

F. Braunschweig ◽

F. Lourenço ◽

R. Neves

Keyword(s):

Risk Assessment ◽

Real Time ◽

Oil Spill ◽

Assessment Tool ◽

Weather Conditions ◽

Traffic Monitoring ◽

Automatic Identification ◽

Accident Risk ◽

Decision Support Model ◽

Risk Levels

Abstract. The technological evolution in terms of computational capacity, data acquisition systems, numerical modelling and operational oceanography is supplying opportunities for designing and building holistic approaches and complex tools for newer and more efficient management (planning, prevention and response) of coastal water pollution risk events. A combined methodology to dynamically estimate time and space variable individual vessel accident risk levels and shoreline contamination risk from ships has been developed, integrating numerical metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS). The risk rating combines the likelihood of an oil spill occurring from a vessel navigating in a study area – the Portuguese continental shelf – with the assessed consequences to the shoreline. The spill likelihood is based on dynamic marine weather conditions and statistical information from previous accidents. The shoreline consequences reflect the virtual spilled oil amount reaching shoreline and its environmental and socio-economic vulnerabilities. The oil reaching shoreline is quantified with an oil spill fate and behaviour model running multiple virtual spills from vessels along time, or as an alternative, a correction factor based on vessel distance from coast. Shoreline risks can be computed in real time or from previously obtained data. Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and to oil transport behaviour. The integration of meteo-oceanic + oil spill models with coastal vulnerability and AIS data in the quantification of risk enhances the maritime situational awareness and the decision support model, providing a more realistic approach in the assessment of shoreline impacts. The risk assessment from historical data can help finding typical risk patterns (“hot spots”) or developing sensitivity analysis to specific conditions, whereas real-time risk levels can be used in the prioritization of individual ships, geographical areas, strategic tug positioning and implementation of dynamic risk-based vessel traffic monitoring.

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