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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
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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
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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
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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
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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

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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. 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)

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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
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Article ; Online: Mathematical analysis of a power-law form time dependent vector-borne disease transmission model.

Sardar, Tridip / Saha, Bapi

Mathematical biosciences

2017 Volume 288, Page(s) 109–123

Abstract: In the last few years, fractional order derivatives have been used in epidemiology to capture the memory phenomena. However, these models do not have proper biological justification in most of the cases and lack a derivation from a stochastic process. In ...

Abstract	In the last few years, fractional order derivatives have been used in epidemiology to capture the memory phenomena. However, these models do not have proper biological justification in most of the cases and lack a derivation from a stochastic process. In this present manuscript, using theory of a stochastic process, we derived a general time dependent single strain vector borne disease model. It is shown that under certain choice of time dependent transmission kernel this model can be converted into the classical integer order system. When the time-dependent transmission follows a power law form, we showed that the model converted into a vector borne disease model with fractional order transmission. We explicitly derived the disease-free and endemic equilibrium of this new fractional order vector borne disease model. Using mathematical properties of nonlinear Volterra type integral equation it is shown that the unique disease-free state is globally asymptotically stable under certain condition. We define a threshold quantity which is epidemiologically known as the basic reproduction number (R
MeSH term(s)	Aedes/virology ; Animals ; Basic Reproduction Number ; Dengue/epidemiology ; Dengue/transmission ; Dengue/virology ; Epidemics ; Humans ; Incidence ; Insect Vectors/virology ; Models, Biological ; Puerto Rico/epidemiology ; Stochastic Processes ; Time Factors
Language	English
Publishing date	2017
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1126-5
ISSN	1879-3134 ; 0025-5564
ISSN (online)	1879-3134
ISSN	0025-5564
DOI	10.1016/j.mbs.2017.03.004
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Article: Estimation of growth regulation in natural populations by extended family of growth curve models with fractional order derivative: Case studies from the global population dynamics database

Bhowmick, Amiya Ranjan / Sardar, Tridip / Bhattacharya, Sabyasachi

Ecological informatics. 2019 Sept., v. 53

2019

Abstract: Estimating the trend in population time series data using growth curve models is a central idea in population ecology. Several models, mainly governed by differential or difference equations, have been applied to real data sets to identify general growth ...

Abstract	Estimating the trend in population time series data using growth curve models is a central idea in population ecology. Several models, mainly governed by differential or difference equations, have been applied to real data sets to identify general growth pattern and make predictions. In this article, we analyze ecological time series data by fitting mathematical models governed by fractional differential equations (FDE). The order of the FDE (α) is used to quantify the evidence of memory in the population processes. The application of FDE is exemplified by analyzing time series data on two bird species Phalacrocorax carbo (Great cormorant) and Parus bicolor (Tufted titmouse) and two mammal species Castor canadensis (Beaver) and Ursus americanus (American black bear) extracted from the global population dynamics database. Five different population growth models were fitted to these data; density-independent exponential, negative density-dependent logistic and θ-logistic model, positive density-dependent exponential Allee and strong Allee model. Both ordinary and fractional derivative representations of these models were fitted to the time series data. Markov chain Monte Carlo (MCMC) method was used to estimate the model parameters and Akaike information criterion was used to select the best model. By estimating the return rate for each of the time series, we have shown that populations governed by FDE with a small value of α (high level of memory) return to the stable equilibrium faster. This demonstrates a synergistic interplay between memory and stability in natural populations.
Keywords	Baeolophus bicolor ; Castor canadensis ; Markov chain ; Phalacrocorax carbo ; Ursus americanus ; birds ; case studies ; data collection ; databases ; differential equation ; extended families ; growth curves ; growth models ; mammals ; mathematical models ; population growth ; prediction ; time series analysis
Language	English
Dates of publication	2019-09
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	2212016-6
ISSN	1878-0512 ; 1574-9541
ISSN (online)	1878-0512
ISSN	1574-9541
DOI	10.1016/j.ecoinf.2019.100980
Database	NAL-Catalogue (AGRICOLA)

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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
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