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  1. Article: From the index case to global spread: the global mobility based modelling of the COVID-19 pandemic implies higher infection rate and lower detection ratio than current estimates.

    Siwiak, Marian / Szczesny, Pawel / Siwiak, Marlena

    PeerJ

    2020  Volume 8, Page(s) e9548

    Abstract: Background: Since the outbreak of the COVID-19 pandemic, multiple efforts of modelling of the geo-temporal transmissibility of the virus have been undertaken, but none describes the pandemic spread at the global level. The aim of this research is to ... ...

    Abstract Background: Since the outbreak of the COVID-19 pandemic, multiple efforts of modelling of the geo-temporal transmissibility of the virus have been undertaken, but none describes the pandemic spread at the global level. The aim of this research is to provide a high-resolution global model of the pandemic that overcomes the problem of biased country-level data on the number of infected cases. To achieve this we propose a novel SIR-type metapopulation transmission model and a set of analytically derived model parameters. We used them to perform a simulation of the disease spread with help of the Global Epidemic and Mobility (GLEAM) framework embedding actual population densities, commute patterns and long-range travel networks. The simulation starts on 17 November 2019 with the index case (presymptomatic, yet infectious) in Wuhan, China, and results in an accurate prediction of the number of diagnosed cases after 154 days in multiple countries across five continents. In addition, the model outcome shows high compliance with the results of a random screening test conducted on pregnant women in the New York area.
    Methods: We have built a modified SIR metapopulation transmission model and parameterized it analytically either by setting the values of the parameters based on the literature, or by assuming their plausible values. We compared our results with the number of diagnosed cases in twenty selected countries, ones which provide reliable statistics but differ substantially in terms of strength and speed of undertaken Non-Drug Interventions. The obtained 95% confidence intervals for the predictions are in agreement with the empirical data.
    Results: The parameters that successfully model the pandemic are: the basic reproduction number
    Discussion: Parameters that successfully reproduce the observed number of cases indicate that both
    Keywords covid19
    Language English
    Publishing date 2020-07-10
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2703241-3
    ISSN 2167-8359
    ISSN 2167-8359
    DOI 10.7717/peerj.9548
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: From the index case to global spread

    Marian Siwiak / Pawel Szczesny / Marlena Siwiak

    PeerJ, Vol 8, p e

    the global mobility based modelling of the COVID-19 pandemic implies higher infection rate and lower detection ratio than current estimates

    2020  Volume 9548

    Abstract: Background Since the outbreak of the COVID-19 pandemic, multiple efforts of modelling of the geo-temporal transmissibility of the virus have been undertaken, but none describes the pandemic spread at the global level. The aim of this research is to ... ...

    Abstract Background Since the outbreak of the COVID-19 pandemic, multiple efforts of modelling of the geo-temporal transmissibility of the virus have been undertaken, but none describes the pandemic spread at the global level. The aim of this research is to provide a high-resolution global model of the pandemic that overcomes the problem of biased country-level data on the number of infected cases. To achieve this we propose a novel SIR-type metapopulation transmission model and a set of analytically derived model parameters. We used them to perform a simulation of the disease spread with help of the Global Epidemic and Mobility (GLEAM) framework embedding actual population densities, commute patterns and long-range travel networks. The simulation starts on 17 November 2019 with the index case (presymptomatic, yet infectious) in Wuhan, China, and results in an accurate prediction of the number of diagnosed cases after 154 days in multiple countries across five continents. In addition, the model outcome shows high compliance with the results of a random screening test conducted on pregnant women in the New York area. Methods We have built a modified SIR metapopulation transmission model and parameterized it analytically either by setting the values of the parameters based on the literature, or by assuming their plausible values. We compared our results with the number of diagnosed cases in twenty selected countries, ones which provide reliable statistics but differ substantially in terms of strength and speed of undertaken Non-Drug Interventions. The obtained 95% confidence intervals for the predictions are in agreement with the empirical data. Results The parameters that successfully model the pandemic are: the basic reproduction number R0, 4.4; a latent non-infectious period of 1.1. days followed by 4.6 days of the presymptomatic infectious period; the probability of developing severe symptoms, 0.01; the probability of being diagnosed when presenting severe symptoms of 0.6; the probability of diagnosis for cases with ...
    Keywords COVID19 ; SARS-CoV-2 ; Pandemic modelling ; Outbreak modelling ; Global COVID19 model ; Analytic parametrization ; Medicine ; R ; Biology (General) ; QH301-705.5 ; covid19
    Subject code 310
    Language English
    Publishing date 2020-07-01T00:00:00Z
    Publisher PeerJ Inc.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: From a single host to global spread. The global mobility based modelling of the COVID-19 pandemic implies higher infection and lower detection rates than current estimates.

    Siwiak, Marlena M / Szczesny, Pawel / Siwiak, Marian P

    medRxiv

    Keywords covid19
    Language English
    Publishing date 2020-03-23
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2020.03.21.20040444
    Database COVID19

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  4. Article ; Online: From a Single Host to Global Spread. The Global Mobility Based Modelling of the COVID-19 Pandemic Implies Higher Infection and Lower Detection Rates than Current Estimates

    Siwiak, Marlena M. / Szczesny, Pawel / Siwiak, Marian P.

    SSRN Electronic Journal ; ISSN 1556-5068

    2020  

    Keywords covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    DOI 10.2139/ssrn.3562477
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: From a single host to global spread. The global mobility based modelling of the COVID-19 pandemic implies higher infection and lower detection rates than current estimates.

    Siwiak, Marlena M / Szczesny, Pawel / Siwiak, Marian P

    Abstract: Background: Since the outbreak of the COVID-19 pandemic, multiple efforts of modelling of the geo-temporal transmissibility of the virus have been undertaken, but none succeeded in describing the pandemic at the global level. We propose a set of ... ...

    Abstract Background: Since the outbreak of the COVID-19 pandemic, multiple efforts of modelling of the geo-temporal transmissibility of the virus have been undertaken, but none succeeded in describing the pandemic at the global level. We propose a set of parameters for the first COVID-19 Global Epidemic and Mobility Model (GLEaM). The simulation starting with just a single pre-symptomatic, yet infectious, case in Wuhan, China, results in an accurate prediction of the number of diagnosed cases after 125 days in multiple countries across three continents. Methods: We have built a modified SIR model and parameterized it analytically, according to the literature and by fitting the missing parameters to the observed dynamics of the virus spread. We compared our results with the number of diagnosed cases in sixeight selected countries which provide reliable statistics but differ substantially in terms of strength and speed of undertaken precautions. The obtained 95% confidence intervals for the predictions fit well to the empirical data. Findings: The parameters that successfully model the pandemic are: the basic reproduction number R0, ~4.4; a latent non-infectious period of 1.1. days followed by 4.6 days of the presymptomatic infectious period; the probability of developing severe symptoms, 0.01; the probability of being diagnosed when presenting severe symptoms of 0.6; the probability of diagnosis for cases with mild symptoms or asymptomatic, 0.001. Also, the higher the testing rate per country, the lower the discrepancy between data (diagnosed cases) and model. Interpretation: Parameters that successfully reproduce the observed number of cases indicate that both R0 and the prevalence of the virus might be underestimated. This is in concordance with the newest research on undocumented COVID-19 cases. Consequently, the actual mortality rate is putatively lower than estimated. Confirmation of the pandemic characteristic by further refinement of the model and screening tests is crucial for developing an effective strategy for the global epidemiological crisis.
    Keywords covid19
    Publisher MedRxiv; WHO
    Document type Article ; Online
    DOI 10.1101/2020.03.21.20040444
    Database COVID19

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  6. Article ; Online: From the index case to global spread

    Siwiak, Marian / Szczesny, Pawel / Siwiak, Marlena

    PeerJ

    the global mobility based modelling of the COVID-19 pandemic implies higher infection rate and lower detection ratio than current estimates

    2020  Volume 8, Page(s) e9548

    Abstract: Background Since the outbreak of the COVID-19 pandemic, multiple efforts of modelling of the geo-temporal transmissibility of the virus have been undertaken, but none describes the pandemic spread at the global level. The aim of this research is to ... ...

    Abstract Background Since the outbreak of the COVID-19 pandemic, multiple efforts of modelling of the geo-temporal transmissibility of the virus have been undertaken, but none describes the pandemic spread at the global level. The aim of this research is to provide a high-resolution global model of the pandemic that overcomes the problem of biased country-level data on the number of infected cases. To achieve this we propose a novel SIR-type metapopulation transmission model and a set of analytically derived model parameters. We used them to perform a simulation of the disease spread with help of the Global Epidemic and Mobility (GLEAM) framework embedding actual population densities, commute patterns and long-range travel networks. The simulation starts on 17 November 2019 with the index case (presymptomatic, yet infectious) in Wuhan, China, and results in an accurate prediction of the number of diagnosed cases after 154 days in multiple countries across five continents. In addition, the model outcome shows high compliance with the results of a random screening test conducted on pregnant women in the New York area. Methods We have built a modified SIR metapopulation transmission model and parameterized it analytically either by setting the values of the parameters based on the literature, or by assuming their plausible values. We compared our results with the number of diagnosed cases in twenty selected countries, ones which provide reliable statistics but differ substantially in terms of strength and speed of undertaken Non-Drug Interventions. The obtained 95% confidence intervals for the predictions are in agreement with the empirical data. Results The parameters that successfully model the pandemic are: the basic reproduction number R 0 , 4.4; a latent non-infectious period of 1.1. days followed by 4.6 days of the presymptomatic infectious period; the probability of developing severe symptoms, 0.01; the probability of being diagnosed when presenting severe symptoms of 0.6; the probability of diagnosis for cases with mild symptoms or asymptomatic, 0.001. Discussion Parameters that successfully reproduce the observed number of cases indicate that both R 0 and the prevalence of the virus might be underestimated. This is in concordance with the newest research on undocumented COVID-19 cases. Consequently, the actual mortality rate is putatively lower than estimated. Confirmation of the pandemic characteristic by further refinement of the model and screening tests is crucial for developing an effective strategy for the global epidemiological crisis.
    Keywords General Biochemistry, Genetics and Molecular Biology ; General Neuroscience ; General Agricultural and Biological Sciences ; General Medicine ; covid19
    Language English
    Publisher PeerJ
    Publishing country us
    Document type Article ; Online
    ZDB-ID 2703241-3
    ISSN 2167-8359
    ISSN 2167-8359
    DOI 10.7717/peerj.9548
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  7. Article: From the index case to global spread: The global mobility based modelling of the COVID-19 pandemic implies higher infection rate and lower detection ratio than current estimates

    Siwiak, Marian / Szczesny, Pawel / Siwiak, Marlena

    PeerJ

    Abstract: Background: Since the outbreak of the COVID-19 pandemic, multiple efforts of modelling of the geo-temporal transmissibility of the virus have been undertaken, but none describes the pandemic spread at the global level. The aim of this research is to ... ...

    Abstract Background: Since the outbreak of the COVID-19 pandemic, multiple efforts of modelling of the geo-temporal transmissibility of the virus have been undertaken, but none describes the pandemic spread at the global level. The aim of this research is to provide a high-resolution global model of the pandemic that overcomes the problem of biased country-level data on the number of infected cases. To achieve this we propose a novel SIR-type metapopulation transmission model and a set of analytically derived model parameters. We used them to perform a simulation of the disease spread with help of the Global Epidemic and Mobility (GLEAM) framework embedding actual population densities, commute patterns and long-range travel networks. The simulation starts on 17 November 2019 with the index case (presymptomatic, yet infectious) in Wuhan, China, and results in an accurate prediction of the number of diagnosed cases after 154 days in multiple countries across five continents. In addition, the model outcome shows high compliance with the results of a random screening test conducted on pregnant women in the New York area. Methods: We have built a modified SIR metapopulation transmission model and parameterized it analytically either by setting the values of the parameters based on the literature, or by assuming their plausible values. We compared our results with the number of diagnosed cases in twenty selected countries, ones which provide reliable statistics but differ substantially in terms of strength and speed of undertaken Non-Drug Interventions. The obtained 95% confidence intervals for the predictions are in agreement with the empirical data. Results: The parameters that successfully model the pandemic are: the basic reproduction number R0, 4.4; a latent non-infectious period of 1.1. days followed by 4.6 days of the presymptomatic infectious period; the probability of developing severe symptoms, 0.01; the probability of being diagnosed when presenting severe symptoms of 0.6; the probability of diagnosis for cases with mild symptoms or asymptomatic, 0.001. Discussion: Parameters that successfully reproduce the observed number of cases indicate that both R0and the prevalence of the virus might be underestimated. This is in concordance with the newest research on undocumented COVID-19 cases. Consequently, the actual mortality rate is putatively lower than estimated. Confirmation of the pandemic characteristic by further refinement of the model and screening tests is crucial for developing an effective strategy for the global epidemiological crisis.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #680620
    Database COVID19

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  8. Article ; Online: A modified SEIR meta-population transmission based Modeling and Forecasting of the COVID-19 pandemic in Pakistan

    Yasin, Zafar / Hassan, Muhammad Sohaib / Mughal, Bilal Javed / Siwiak, Marian

    medRxiv

    Abstract: The coronavirus disease 2019 (COVID−19) started from China at the end of 2019, has now spread across the globe. Modeling and simulation of the − outspread is significant for timely and effective measures to be taken. Scientists around the world are using ...

    Abstract The coronavirus disease 2019 (COVID−19) started from China at the end of 2019, has now spread across the globe. Modeling and simulation of the − outspread is significant for timely and effective measures to be taken. Scientists around the world are using various epidemiological models to help policymakers to plan and determine what interventions and resources will be needed in case of a surge and to estimate the potential future burden on health care system. Pakistan is also among the affected countries with 18th highest number of total detected number of cases, as of 3rd of June, 2020. A modified time-dependent Susceptible-Exposed-Infected-Recovered (SEIR) metapopulation transmission model is used in the Global Epidemic and Mobility Model (GLEaM) for this simulation. The simulation assumes the index case in Wuhan, China and models the global spread of SARS− COV−2 with reasonable results for several countries within the 95% confidence interval. This model was then tuned with parameters for Pakistan to predict the outspread of COVID−19 in Pakistan. The impact of Non-Drug Interventions on flattening the curve are also incorporated in the simulation and the results are further extended to find the peak of the pandemic and future predictions. It has been observed that in the current scenario, the epidemic trend of COVID−19 spread in Pakistan would attain a peak in the second decade of month of June with approximately (3600−4200) daily cases. The current wave of SARS−COV−2 in Pakistan with is estimated to cause some (210,000 − 226,000) cumulative cases and (4400 − 4750) cumulative lost lives by the end of August when the epidemic is reduced by 99%. However, the disease is controllable in the likely future if inclusive and strict control measures are taken.
    Keywords covid19
    Language English
    Publishing date 2020-06-05
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2020.06.03.20121517
    Database COVID19

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  9. Article ; Online: Structural models of CFTR-AMPK and CFTR-PKA interactions: R-domain flexibility is a key factor in CFTR regulation.

    Siwiak, Marian / Edelman, Aleksander / Zielenkiewicz, Piotr

    Journal of molecular modeling

    2011  Volume 18, Issue 1, Page(s) 83–90

    Abstract: Cystic fibrosis (CF), the most common lethal genetic disease among Caucasians, is caused by mutations in cystic fibrosis transmembrane conductance regulator (CFTR). CFTR's main role is to transport chloride ions across epithelial cell membranes. It also ... ...

    Abstract Cystic fibrosis (CF), the most common lethal genetic disease among Caucasians, is caused by mutations in cystic fibrosis transmembrane conductance regulator (CFTR). CFTR's main role is to transport chloride ions across epithelial cell membranes. It also regulates many cell functions. However, the exact role of CFTR in cellular processes is not yet fully understood. It is recognized that a key factor in CFTR-related regulation is its phosphorylation state. The important kinases regulating CFTR are cAMP-dependent protein kinase A (PKA) and 5'-AMP-activated protein kinase (AMPK). PKA and AMPK have opposite effects on CFTR activity despite their highly similar structures and recognition motifs. Utilizing homology modeling, in silico mutagenesis and literature mining, we supplement available information regarding the atomic-resolution structures of PKA, AMPK and CFTR, and the complexes CFTR-PKA and CFTR-AMPK. The atomic-resolution structural predictions reveal an unexpected availability of CFTR Ser813 for phosphorylation by both PKA and AMPK. These results indicate the key role of the structural flexibility of the serine-rich R-domain in CFTR regulation by phosphorylation.
    MeSH term(s) AMP-Activated Protein Kinases/metabolism ; Amino Acid Sequence ; Cyclic AMP-Dependent Protein Kinases/metabolism ; Cystic Fibrosis Transmembrane Conductance Regulator/metabolism ; Humans ; Models, Molecular ; Phosphorylation ; Protein Interaction Domains and Motifs ; Protein Structure, Tertiary ; Sequence Analysis, Protein
    Chemical Substances CFTR protein, human ; Cystic Fibrosis Transmembrane Conductance Regulator (126880-72-6) ; Cyclic AMP-Dependent Protein Kinases (EC 2.7.11.11) ; AMP-Activated Protein Kinases (EC 2.7.11.31)
    Language English
    Publishing date 2011-04-01
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 1284729-X
    ISSN 0948-5023 ; 1610-2940
    ISSN (online) 0948-5023
    ISSN 1610-2940
    DOI 10.1007/s00894-011-1029-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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