LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 10 of total 26

Search options

  1. Article ; Online: Effective Lockdown and Role of Hospital-Based COVID-19 Transmission in Some Indian States: An Outbreak Risk Analysis.

    Sardar, Tridip / Rana, Sourav

    Risk analysis : an official publication of the Society for Risk Analysis

    2021  Volume 42, Issue 1, Page(s) 126–142

    Abstract: Several reports in India indicate hospitals and quarantined centers are COVID-19 hotspots. To study the transmission occurring from the hospitals and as well as from the community, we developed a mechanistic model with a lockdown effect. Using daily ... ...

    Abstract Several reports in India indicate hospitals and quarantined centers are COVID-19 hotspots. To study the transmission occurring from the hospitals and as well as from the community, we developed a mechanistic model with a lockdown effect. Using daily COVID-19 cases data from six states and overall India, we estimated several important parameters of our model. Moreover, we provided an estimation of the effective (R
    MeSH term(s) COVID-19/epidemiology ; COVID-19/transmission ; Communicable Disease Control/methods ; Humans ; India/epidemiology ; Pandemics ; Quarantine/organization & administration ; Risk Assessment/methods ; SARS-CoV-2
    Language English
    Publishing date 2021-07-05
    Publishing country United States
    Document type Journal Article ; Multicenter Study ; Research Support, Non-U.S. Gov't
    ZDB-ID 778660-8
    ISSN 1539-6924 ; 0272-4332
    ISSN (online) 1539-6924
    ISSN 0272-4332
    DOI 10.1111/risa.13781
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  2. Article: The impact of a power law-induced memory effect on the SARS-CoV-2 transmission.

    Sk, Tahajuddin / Biswas, Santosh / Sardar, Tridip

    Chaos, solitons, and fractals

    2022  Volume 165, Page(s) 112790

    Abstract: It is well established that COVID-19 incidence data follows some power law growth pattern. Therefore, it is natural to believe that the COVID-19 transmission process follows some power law. However, we found no existing model on COVID-19 with a power law ...

    Abstract It is well established that COVID-19 incidence data follows some power law growth pattern. Therefore, it is natural to believe that the COVID-19 transmission process follows some power law. However, we found no existing model on COVID-19 with a power law effect only in the disease transmission process. Inevitably, it is not clear how this power law effect in disease transmission can influence multiple COVID-19 waves in a location. In this context, we developed a completely new COVID-19 model where a force of infection function in disease transmission follows some power law. Furthermore, different realistic epidemiological scenarios like imperfect social distancing among home-quarantined individuals, disease awareness, vaccination, treatment, and possible reinfection of the recovered population are also considered in the model. Applying some recent techniques, we showed that the proposed system converted to a COVID-19 model with fractional order disease transmission, where order of the fractional derivative (
    Language English
    Publishing date 2022-10-25
    Publishing country England
    Document type Journal Article
    ZDB-ID 2003919-0
    ISSN 1873-2887 ; 0960-0779
    ISSN (online) 1873-2887
    ISSN 0960-0779
    DOI 10.1016/j.chaos.2022.112790
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  3. Article: Detection of multiple waves for COVID-19 and its optimal control through media awareness and vaccination: study based on some Indian states.

    Sardar, Tridip / Nadim, Sk Shahid / Rana, Sourav

    Nonlinear dynamics

    2022  , Page(s) 1–18

    Abstract: COVID-19 is a highly infectious disease, and in very recent times, it has shown a massive impact throughout the globe. Several countries faced the COVID-19 infection waves multiple times. These later waves are more aggressive than the first wave and ... ...

    Abstract COVID-19 is a highly infectious disease, and in very recent times, it has shown a massive impact throughout the globe. Several countries faced the COVID-19 infection waves multiple times. These later waves are more aggressive than the first wave and drastically impact social and economic factors. We developed a mechanistic model with imperfect lockdown effect, reinfection, transmission variability between symptomatic & asymptomatic, and media awareness to focus on the early detection of multiple waves and their control measures. Using daily COVID-19 cases data from six states of India, we estimated several important model parameters. Moreover, we estimated the home quarantine, community, and basic reproduction numbers. We developed an algorithm to carry out global sensitivity analysis (Sobol) of the parameters that influence the number of COVID-19 waves (
    Supplementary information: The online version contains supplementary material available at 10.1007/s11071-022-07887-5.
    Language English
    Publishing date 2022-10-06
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2012600-1
    ISSN 1573-269X ; 0924-090X
    ISSN (online) 1573-269X
    ISSN 0924-090X
    DOI 10.1007/s11071-022-07887-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  4. Article ; Online: Invasive dynamics for a predator-prey system with Allee effect in both populations and a special emphasis on predator mortality.

    Rana, Sourav / Bhowmick, Amiya Ranjan / Sardar, Tridip

    Chaos (Woodbury, N.Y.)

    2021  Volume 31, Issue 3, Page(s) 33150

    Abstract: We considered a non-linear predator-prey model with an Allee effect on both populations on a two spatial dimension reaction-diffusion setup. Special importance to predator mortality was given as it may be often controlled through human-made harvesting ... ...

    Abstract We considered a non-linear predator-prey model with an Allee effect on both populations on a two spatial dimension reaction-diffusion setup. Special importance to predator mortality was given as it may be often controlled through human-made harvesting processes. The local dynamics of the model was studied through boundedness, equilibrium, and stability analysis. An extensive numerical stability analysis was performed and found that bi-stability is not possible for the non-spatial model. By analyzing the spatial model, we found the condition for successful invasion and the persistence region of the species based on the predator Allee effect and its mortality parameter. Four different dynamics in this region of the parameter space are mainly explored. First, the Allee effect on both populations leads to various new types of species spread. Second, for a high value of per-capita growth rate, two completely new spreads (e.g., sun surface, colonial) have been found depending on the Allee effect parameter. Third, the Allee coefficient on the predator population leads to spatiotemporal chaos via a patchy spread for both linear and quadratic mortality rates. Finally, a more rigorous analysis is performed to study the chaotic nature of the system within the whole persistence domain. We have studied the possibility of chaos through temporal variation in different invasion regions. Furthermore, the chaotic fluctuation is studied through the sensitivity of initial conditions and by investigating the dominant Lyapunov exponent value.
    MeSH term(s) Animals ; Ecosystem ; Food Chain ; Humans ; Models, Biological ; Population Dynamics ; Predatory Behavior
    Language English
    Publishing date 2021-03-30
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1472677-4
    ISSN 1089-7682 ; 1054-1500
    ISSN (online) 1089-7682
    ISSN 1054-1500
    DOI 10.1063/5.0035566
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  5. Article ; Online: A realistic two-strain model for MERS-CoV infection uncovers the high risk for epidemic propagation.

    Sardar, Tridip / Ghosh, Indrajit / Rodó, Xavier / Chattopadhyay, Joydev

    PLoS neglected tropical diseases

    2020  Volume 14, Issue 2, Page(s) e0008065

    Abstract: Middle East Respiratory Syndrome Coronavirus (MERS-CoV) causes severe acute respiratory illness with a case fatality rate (CFR) of 35,5%. The highest number of MERS-CoV cases are from Saudi-Arabia, the major worldwide hotspot for this disease. In the ... ...

    Abstract Middle East Respiratory Syndrome Coronavirus (MERS-CoV) causes severe acute respiratory illness with a case fatality rate (CFR) of 35,5%. The highest number of MERS-CoV cases are from Saudi-Arabia, the major worldwide hotspot for this disease. In the absence of neither effective treatment nor a ready-to-use vaccine and with yet an incomplete understanding of its epidemiological cycle, prevention and containment measures can be derived from mathematical models of disease epidemiology. We constructed 2-strain models to predict past outbreaks in the interval 2012-2016 and derive key epidemiological information for Macca, Madina and Riyadh. We approached variability in infection through three different disease incidence functions capturing social behavior in response to an epidemic (e.g. Bilinear, BL; Non-monotone, NM; and Saturated, SAT models). The best model combination successfully anticipated the total number of MERS-CoV clinical cases for the 2015-2016 season and accurately predicted both the number of cases at the peak of seasonal incidence and the overall shape of the epidemic cycle. The evolution in the basic reproduction number (R0) warns that MERS-CoV may easily take an epidemic form. The best model correctly captures this feature, indicating a high epidemic risk (1≤R0≤2,5) in Riyadh and Macca and confirming the alleged co-circulation of more than one strain. Accurate predictions of the future MERS-CoV peak week, as well as the number of cases at the peak are now possible. These results indicate public health agencies should be aware that measures for strict containment are urgently needed before new epidemics take off in the region.
    MeSH term(s) Carrier State ; Computer Simulation ; Coronavirus Infections/epidemiology ; Coronavirus Infections/virology ; Epidemics ; Humans ; Middle East Respiratory Syndrome Coronavirus ; Models, Biological ; Risk Factors
    Keywords covid19
    Language English
    Publishing date 2020-02-14
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2429704-5
    ISSN 1935-2735 ; 1935-2727
    ISSN (online) 1935-2735
    ISSN 1935-2727
    DOI 10.1371/journal.pntd.0008065
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  6. Article: Assessment of 21 Days Lockdown Effect in Some States and Overall India: A Predictive Mathematical Study on COVID-19 Outbreak

    Tridip Sardar / Sk Nadim Shahid / Joydev Chattopadhyay

    Abstract: As of April, 6th, 2020, the total number of COVID-19 reported cases and deaths are 4778 and 136. This is an alarming situation as with a huge population within few days India will enter in stage-3 of COVID-19 transmission. In the absence of neither an ... ...

    Abstract As of April, 6th, 2020, the total number of COVID-19 reported cases and deaths are 4778 and 136. This is an alarming situation as with a huge population within few days India will enter in stage-3 of COVID-19 transmission. In the absence of neither an effective treatment or vaccine and with an incomplete understanding of the epidemiological cycle, predictive mathematical models can help exploring of both COVID-19 transmission and control. In this present study, we consider a new mathematical model on COVID-19 transmission that incorporate lock-down effect and variability in transmission between symptomatic and asymptomatic populations with former being a fast spreader of the disease. Using daily COVID-19 notified cases from three states (Maharashtra, Delhi, and Telangana) and overall India, we assess the effect of current 21 days lock-down in terms of reduction cases and deaths. Lock-down effect is studied with different lock-down success rate. Our result suggest that 21 days lock-down will have no impact in Maharashtra and overall India. Furthermore, the presence of a higher percentage of COVID-19 super-spreaders will further deteriorate the situation in Maharashtra. However, for Tamil Nadu and Delhi there is some ray of hope as our prediction shows that lock-down will reduce a significant number of cases and deaths. in these two locations. Further extension of lock-down may place Delhi and Tamil Nadu in a comfort zone. Comparing estimated parameter samples for the mentioned four locations, we find a correlation between effect of lockdown and percentage of symptomatic infected in a region. Our result suggests that a higher percentage of symptomatic infected in a region leads to a large number of reduction in notified cases and deaths due to different lock-down scenario. Finally, we suggest a policy for the Indian Govt to control COVID-19 outbreak.
    Keywords covid19
    Publisher arxiv
    Document type Article
    Database COVID19

    Kategorien

  7. Article ; Online: A realistic two-strain model for MERS-CoV infection uncovers the high risk for epidemic propagation.

    Tridip Sardar / Indrajit Ghosh / Xavier Rodó / Joydev Chattopadhyay

    PLoS Neglected Tropical Diseases, Vol 14, Iss 2, p e

    2020  Volume 0008065

    Abstract: Middle East Respiratory Syndrome Coronavirus (MERS-CoV) causes severe acute respiratory illness with a case fatality rate (CFR) of 35,5%. The highest number of MERS-CoV cases are from Saudi-Arabia, the major worldwide hotspot for this disease. In the ... ...

    Abstract Middle East Respiratory Syndrome Coronavirus (MERS-CoV) causes severe acute respiratory illness with a case fatality rate (CFR) of 35,5%. The highest number of MERS-CoV cases are from Saudi-Arabia, the major worldwide hotspot for this disease. In the absence of neither effective treatment nor a ready-to-use vaccine and with yet an incomplete understanding of its epidemiological cycle, prevention and containment measures can be derived from mathematical models of disease epidemiology. We constructed 2-strain models to predict past outbreaks in the interval 2012-2016 and derive key epidemiological information for Macca, Madina and Riyadh. We approached variability in infection through three different disease incidence functions capturing social behavior in response to an epidemic (e.g. Bilinear, BL; Non-monotone, NM; and Saturated, SAT models). The best model combination successfully anticipated the total number of MERS-CoV clinical cases for the 2015-2016 season and accurately predicted both the number of cases at the peak of seasonal incidence and the overall shape of the epidemic cycle. The evolution in the basic reproduction number (R0) warns that MERS-CoV may easily take an epidemic form. The best model correctly captures this feature, indicating a high epidemic risk (1≤R0≤2,5) in Riyadh and Macca and confirming the alleged co-circulation of more than one strain. Accurate predictions of the future MERS-CoV peak week, as well as the number of cases at the peak are now possible. These results indicate public health agencies should be aware that measures for strict containment are urgently needed before new epidemics take off in the region.
    Keywords Arctic medicine. Tropical medicine ; RC955-962 ; Public aspects of medicine ; RA1-1270
    Subject code 612
    Language English
    Publishing date 2020-02-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

  8. Article: Assessment of lockdown effect in some states and overall India: A predictive mathematical study on COVID-19 outbreak.

    Sardar, Tridip / Nadim, Sk Shahid / Rana, Sourav / Chattopadhyay, Joydev

    Chaos, solitons, and fractals

    2020  Volume 139, Page(s) 110078

    Abstract: In the absence of neither an effective treatment or vaccine and with an incomplete understanding of the epidemiological cycle, Govt. has implemented a nationwide lockdown to reduce COVID-19 transmission in India. To study the effect of social distancing ... ...

    Abstract In the absence of neither an effective treatment or vaccine and with an incomplete understanding of the epidemiological cycle, Govt. has implemented a nationwide lockdown to reduce COVID-19 transmission in India. To study the effect of social distancing measure, we considered a new mathematical model on COVID-19 that incorporates lockdown effect. By validating our model to the data on notified cases from five different states and overall India, we estimated several epidemiologically important parameters as well as the basic reproduction number (
    Keywords covid19
    Language English
    Publishing date 2020-07-08
    Publishing country England
    Document type Journal Article
    ZDB-ID 2003919-0
    ISSN 1873-2887 ; 0960-0779
    ISSN (online) 1873-2887
    ISSN 0960-0779
    DOI 10.1016/j.chaos.2020.110078
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  9. Article: Effective lockdown and role of hospital-based COVID-19 transmission in some Indian states: An outbreak risk analysis

    Sardar, Tridip / Rana, Sourav

    Abstract: There are several reports in India that indicate hospitals and quarantined centers are COVID-19 hotspots. In the absence of efficient contact tracing tools, Govt. and the policymakers may not be paying attention to the risk of hospital-based transmission. ...

    Abstract There are several reports in India that indicate hospitals and quarantined centers are COVID-19 hotspots. In the absence of efficient contact tracing tools, Govt. and the policymakers may not be paying attention to the risk of hospital-based transmission. To explore more on this important route and its possible impact on lockdown effect, we developed a mechanistic model with hospital-based transmission. Using daily notified COVID-19 cases from six states (Maharashtra, Delhi, Madhya Pradesh, Rajasthan, Gujarat, and Uttar Pradesh) and overall India, we estimated several important parameters of the model. Moreover, we provided an estimation of the basic ($R_{0}$), the community ($R_{C}$), and the hospital ($R_{H}$) reproduction numbers for those seven locations. To obtain a reliable forecast of future COVID-19 cases, a BMA post-processing technique is used to ensemble the mechanistic model with a hybrid statistical model. Using the ensemble model, we forecast COVID-19 notified cases (daily and cumulative) from May 3, 2020, till May 20, 2020, under five different lockdown scenarios in the mentioned locations. Our analysis of the mechanistic model suggests that most of the new COVID-19 cases are currently undetected in the mentioned seven locations. Furthermore, a global sensitivity analysis of four epidemiologically measurable \&controllable parameters on $R_{0}$ and as well on the lockdown effect, indicate that if appropriate preventive measures are not taken immediately, a much larger COVID-19 outbreak may trigger from hospitals and quarantined centers. In most of the locations, our ensemble model forecast indicates a substantial percentage of increase in the COVID-19 notified cases in the coming weeks in India. Based on our results, we proposed a containment policy that may reduce the threat of a larger COVID-19 outbreak in the coming days.
    Keywords covid19
    Publisher ArXiv
    Document type Article
    Database COVID19

    Kategorien

  10. Book ; Online: Effective lockdown and role of hospital-based COVID-19 transmission in some Indian states

    Sardar, Tridip / Rana, Sourav

    An outbreak risk analysis

    2020  

    Abstract: There are several reports in India that indicate hospitals and quarantined centers are COVID-19 hotspots. In the absence of efficient contact tracing tools, Govt. and the policymakers may not be paying attention to the risk of hospital-based transmission. ...

    Abstract There are several reports in India that indicate hospitals and quarantined centers are COVID-19 hotspots. In the absence of efficient contact tracing tools, Govt. and the policymakers may not be paying attention to the risk of hospital-based transmission. To explore more on this important route and its possible impact on lockdown effect, we developed a mechanistic model with hospital-based transmission. Using daily notified COVID-19 cases from six states (Maharashtra, Delhi, Madhya Pradesh, Rajasthan, Gujarat, and Uttar Pradesh) and overall India, we estimated several important parameters of the model. Moreover, we provided an estimation of the basic ($R_{0}$), the community ($R_{C}$), and the hospital ($R_{H}$) reproduction numbers for those seven locations. To obtain a reliable forecast of future COVID-19 cases, a BMA post-processing technique is used to ensemble the mechanistic model with a hybrid statistical model. Using the ensemble model, we forecast COVID-19 notified cases (daily and cumulative) from May 3, 2020, till May 20, 2020, under five different lockdown scenarios in the mentioned locations. Our analysis of the mechanistic model suggests that most of the new COVID-19 cases are currently undetected in the mentioned seven locations. Furthermore, a global sensitivity analysis of four epidemiologically measurable \& controllable parameters on $R_{0}$ and as well on the lockdown effect, indicate that if appropriate preventive measures are not taken immediately, a much larger COVID-19 outbreak may trigger from hospitals and quarantined centers. In most of the locations, our ensemble model forecast indicates a substantial percentage of increase in the COVID-19 notified cases in the coming weeks in India. Based on our results, we proposed a containment policy that may reduce the threat of a larger COVID-19 outbreak in the coming days.

    Comment: 45 pages
    Keywords Quantitative Biology - Populations and Evolution ; Mathematics - Dynamical Systems ; 92B10 ; 92D30 ; covid19
    Publishing date 2020-05-03
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

To top