Symptom-Based Markers for COVID-19 Transmission : Contact Network Transmission Modeling of Healthcare Associated Infections: Symptom-Based Markers for COVID-19 Transmission
One important approach for decreasing COVID-19 transmission in healthcare settings is to prevent healthcare professionals from working while ill. Currently, facilities are asking screening questions and measuring temperatures to help identify symptomatic healthcare professionals and exclude them from providing patient care. Simulations can be used to inform the effectiveness of different screening approaches, but the results of these simulations depend upon the effectiveness of the intervention, e.g., the ability to identify healthcare professionals on their way to work, or to study the impact of healthcare professionals returning to work too early. Thus, simulations must necessarily depend upon realistic disease parameters: for example, it is suspected that a non-trivial proportion of patients with COVID-19 may be asymptomatic or have minimal symptoms, but the relative size of the asymptomatic subpopulation is unknown.The plan for this study is to develop a method for granular measurement of twice-daily symptoms from healthcare professionals and other research subjects of similar ages. After being diagnosed, the goal is to determine what symptoms participants have and how long they have had them. This will be done using a previously-developed bidirectional texting platform to query participants about symptoms at least twice a day for ten days post diagnosis. Participants will be asked about subjective symptoms, including fevers, chills, cough, shortness of breath, fatigue, gastrointestinal symptoms, etc. They will also take their temperature twice daily during the recovery period, which will help determine the effectiveness of screening based on symptoms and/or thermometer readings..
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Klinische Studie| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
ClinicalTrials.gov - (2024) vom: 26. März Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
610 |
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| Anmerkungen: |
Source: Link to the current ClinicalTrials.gov record., First posted: December 11, 2020, Last downloaded: ClinicalTrials.gov processed this data on April 03, 2024, Last updated: April 03, 2024 |
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| Study ID: |
NCT04665245 |
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| Veröffentlichungen zur Studie: |
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| PPN (Katalog-ID): |
CTG000126748 |
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| 520 | |a One important approach for decreasing COVID-19 transmission in healthcare settings is to prevent healthcare professionals from working while ill. Currently, facilities are asking screening questions and measuring temperatures to help identify symptomatic healthcare professionals and exclude them from providing patient care. Simulations can be used to inform the effectiveness of different screening approaches, but the results of these simulations depend upon the effectiveness of the intervention, e.g., the ability to identify healthcare professionals on their way to work, or to study the impact of healthcare professionals returning to work too early. Thus, simulations must necessarily depend upon realistic disease parameters: for example, it is suspected that a non-trivial proportion of patients with COVID-19 may be asymptomatic or have minimal symptoms, but the relative size of the asymptomatic subpopulation is unknown.The plan for this study is to develop a method for granular measurement of twice-daily symptoms from healthcare professionals and other research subjects of similar ages. After being diagnosed, the goal is to determine what symptoms participants have and how long they have had them. This will be done using a previously-developed bidirectional texting platform to query participants about symptoms at least twice a day for ten days post diagnosis. Participants will be asked about subjective symptoms, including fevers, chills, cough, shortness of breath, fatigue, gastrointestinal symptoms, etc. They will also take their temperature twice daily during the recovery period, which will help determine the effectiveness of screening based on symptoms and/or thermometer readings. | ||
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