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  1. Book ; Online: Estimating the efficiency turn-on curve for a constant-threshold trigger without a calibration dataset

    Pollmann, Tina R.

    2019  

    Abstract: Many particle physics experiments use constant threshold triggers, where the trigger threshold is in an online estimator that can be calculated quickly by the trigger module. Offline data analysis then calculates a more precise offline estimator for the ... ...

    Abstract Many particle physics experiments use constant threshold triggers, where the trigger threshold is in an online estimator that can be calculated quickly by the trigger module. Offline data analysis then calculates a more precise offline estimator for the same quantity, for example the event energy. The efficiency curve is a step function in the online estimator, but not in the offline estimator. One typically obtains the shape of the efficiency curve in the offline estimator by way of a calibration dataset, where the true rate of events at each value of the offline estimator is measured once and compared to the rate observed in the physics dataset. For triggers with a fixed threshold condition, it is sometimes possible to bootstrap the trigger efficiency curve without use of a calibration dataset. This is useful to verify stability of a calibration over time when calibration data cannot be taken often enough. It also makes it possible to use datasets for which no calibration is available. This paper describes the method and the conditions that must be met for it to be applicable.
    Keywords High Energy Physics - Experiment ; Physics - Data Analysis ; Statistics and Probability
    Subject code 612
    Publishing date 2019-01-30
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article: The impact of digital contact tracing on the SARS-CoV-2 pandemic-a comprehensive modelling study.

    Pollmann, Tina R / Schönert, Stefan / Müller, Johannes / Pollmann, Julia / Resconi, Elisa / Wiesinger, Christoph / Haack, Christian / Shtembari, Lolian / Turcati, Andrea / Neumair, Birgit / Meighen-Berger, Stephan / Zattera, Giovanni / Neumair, Matthias / Apel, Uljana / Okolie, Augustine

    EPJ data science

    2021  Volume 10, Issue 1, Page(s) 37

    Abstract: Contact tracing is one of several strategies employed in many countries to curb the spread of SARS-CoV-2. Digital contact tracing (DCT) uses tools such as cell-phone applications to improve tracing speed and reach. We model the impact of DCT on the ... ...

    Abstract Contact tracing is one of several strategies employed in many countries to curb the spread of SARS-CoV-2. Digital contact tracing (DCT) uses tools such as cell-phone applications to improve tracing speed and reach. We model the impact of DCT on the spread of the virus for a large epidemiological parameter space consistent with current literature on SARS-CoV-2. We also model DCT in combination with random testing (RT) and social distancing (SD). Modelling is done with two independently developed individual-based (stochastic) models that use the Monte Carlo technique, benchmarked against each other and against two types of deterministic models. For current best estimates of the number of asymptomatic SARS-CoV-2 carriers (approximately 40%), their contagiousness (similar to that of symptomatic carriers), the reproductive number before interventions (
    Language English
    Publishing date 2021-07-20
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 2705691-0
    ISSN 2193-1127
    ISSN 2193-1127
    DOI 10.1140/epjds/s13688-021-00290-x
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: The impact of digital contact tracing on the SARS-CoV-2 pandemic - a comprehensive modelling study

    Pollmann, Tina R / Pollmann, Julia / Wiesinger, Christoph / Haack, Christian / Shtembari, Lolian / Turcati, Andrea / Neumair, Birgit / Meighen-Berger, Stephan / Zattera, Giovanni / Neumair, Matthias / Apel, Uljana / Okolie, Augustine / Mueller, Johannes / Schoenert, Stefan / Resconi, Elisa

    medRxiv

    Abstract: Contact tracing is one of several strategies employed in many countries to curb the spread of SARS-CoV-2. Digital contact tracing (DCT) uses tools such as cell-phone applications to improve tracing speed and reach. We model the impact of DCT on the ... ...

    Abstract Contact tracing is one of several strategies employed in many countries to curb the spread of SARS-CoV-2. Digital contact tracing (DCT) uses tools such as cell-phone applications to improve tracing speed and reach. We model the impact of DCT on the spread of the virus for a large epidemiological parameter space consistent with current literature on SARS-CoV-2. We also model DCT in combination with random testing (RT) and social distancing (SD). Modelling is done with two independently developed individual-based (stochastic) models that use the Monte Carlo technique, benchmarked against each other and against two types of deterministic models. For current best estimates of the number of asymptomatic SARS-CoV-2 carriers (approximately 40\%), their contagiousness (similar to that of symptomatic carriers), the reproductive number before interventions (R0 at least 3) we find that DCT must be combined with other interventions such as SD and/or RT to push the reproductive number below one. At least 60\% of the population would have to use the DCT system for its effect to become significant. On its own, DCT cannot bring the reproductive number below 1 unless nearly the entire population uses the DCT system and follows quarantining and testing protocols strictly. For lower uptake of the DCT system, DCT still reduces the number of people that become infected. When DCT is deployed in a population with an ongoing outbreak where O(0.1\%) of the population have already been infected, the gains of the DCT intervention come at the cost of requiring up to 15% of the population to be quarantined (in response to being traced) on average each day for the duration of the epidemic, even when there is sufficient testing capability to test every traced person.
    Keywords covid19
    Language English
    Publishing date 2020-09-14
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2020.09.13.20192682
    Database COVID19

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  4. Article ; Online: The impact of digital contact tracing on the SARS-CoV-2 pandemic - a comprehensive modelling study

    Pollmann, Tina R / Pollmann, Julia / Wiesinger, Christoph / Haack, Christian / Shtembari, Lolian / Turcati, Andrea / Neumair, Birgit / Meighen-Berger, Stephan / Zattera, Giovanni / Neumair, Matthias / Apel, Uljana / Okolie, Augustine / Mueller, Johannes / Schoenert, Stefan / Resconi, Elisa

    Abstract: Contact tracing is one of several strategies employed in many countries to curb the spread of SARS-CoV-2. Digital contact tracing (DCT) uses tools such as cell-phone applications to improve tracing speed and reach. We model the impact of DCT on the ... ...

    Abstract Contact tracing is one of several strategies employed in many countries to curb the spread of SARS-CoV-2. Digital contact tracing (DCT) uses tools such as cell-phone applications to improve tracing speed and reach. We model the impact of DCT on the spread of the virus for a large epidemiological parameter space consistent with current literature on SARS-CoV-2. We also model DCT in combination with random testing (RT) and social distancing (SD). Modelling is done with two independently developed individual-based (stochastic) models that use the Monte Carlo technique, benchmarked against each other and against two types of deterministic models. For current best estimates of the number of asymptomatic SARS-CoV-2 carriers (approximately 40%), their contagiousness (similar to that of symptomatic carriers), the reproductive number before interventions (R0 at least 3) we find that DCT must be combined with other interventions such as SD and/or RT to push the reproductive number below one. At least 60% of the population would have to use the DCT system for its effect to become significant. On its own, DCT cannot bring the reproductive number below 1 unless nearly the entire population uses the DCT system and follows quarantining and testing protocols strictly. For lower uptake of the DCT system, DCT still reduces the number of people that become infected. When DCT is deployed in a population with an ongoing outbreak where O(0.1%) of the population have already been infected, the gains of the DCT intervention come at the cost of requiring up to 15% of the population to be quarantined (in response to being traced) on average each day for the duration of the epidemic, even when there is sufficient testing capability to test every traced person.
    Keywords covid19
    Publisher MedRxiv; WHO
    Document type Article ; Online
    Note WHO #Covidence: #20192682
    DOI 10.1101/2020.09.13.20192682
    Database COVID19

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