LIVIVO - Search results -

Search results

Result 1 - 10 of total 13

Search options

Article ; Online: Mathematical Modelling to Assess the Impact of Lockdown on COVID-19 Transmission in India: Model Development and Validation.

Ambikapathy, Bakiya / Krishnamurthy, Kamalanand

JMIR public health and surveillance

2020 Volume 6, Issue 2, Page(s) e19368

Abstract: Background: The World Health Organization has declared the novel coronavirus disease (COVID-19) to be a public health emergency; at present, India is facing a major threat of community spread. We developed a mathematical model for investigating and ... ...

Abstract	Background: The World Health Organization has declared the novel coronavirus disease (COVID-19) to be a public health emergency; at present, India is facing a major threat of community spread. We developed a mathematical model for investigating and predicting the effects of lockdown on future COVID-19 cases with a specific focus on India. Objective: The objective of this work was to develop and validate a mathematical model and to assess the impact of various lockdown scenarios on COVID-19 transmission in India. Methods: A model consisting of a framework of ordinary differential equations was developed by incorporating the actual reported cases in 14 countries. After validation, the model was applied to predict COVID-19 transmission in India for different intervention scenarios in terms of lockdown for 4, 14, 21, 42, and 60 days. We also assessed the situations of enhanced exposure due to aggregation of individuals in transit stations and shopping malls before the lockdown. Results: The developed model is efficient in predicting the number of COVID-19 cases compared to the actual reported cases in 14 countries. For India, the model predicted marked reductions in cases for the intervention periods of 14 and 21 days of lockdown and significant reduction for 42 days of lockdown. Such intervention exceeding 42 days does not result in measurable improvement. Finally, for the scenario of "panic shopping" or situations where there is a sudden increase in the factors leading to higher exposure to infection, the model predicted an exponential transmission, resulting in failure of the considered intervention strategy. Conclusions: Implementation of a strict lockdown for a period of at least 21 days is expected to reduce the transmission of COVID-19. However, a further extension of up to 42 days is required to significantly reduce the transmission of COVID-19 in India. Any relaxation in the lockdown may lead to exponential transmission, resulting in a heavy burden on the health care system in the country.
MeSH term(s)	COVID-19 ; Coronavirus Infections/epidemiology ; Coronavirus Infections/prevention & control ; Coronavirus Infections/transmission ; Humans ; India/epidemiology ; Models, Theoretical ; Pandemics/prevention & control ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/prevention & control ; Pneumonia, Viral/transmission ; Reproducibility of Results
Keywords	covid19
Language	English
Publishing date	2020-05-07
Publishing country	Canada
Document type	Journal Article
ISSN	2369-2960
ISSN (online)	2369-2960
DOI	10.2196/19368
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: An algorithm to estimate the real time secondary infections in sub-urban bus travel: COVID-19 epidemic experience at Chennai Metropolitan city India.

Arumugam, Ganesh Ram / Ambikapathy, Bakiya / Krishnamurthy, Kamalanand / Kumar, Ashwani / De Britto, Lourduraj

Virusdisease

2023 Volume 34, Issue 1, Page(s) 39–49

Abstract: Globalization, global climatic changes, and human behavior pose threats to highly pathogenic avian influenza (HPAI) virus spillover from animals to human. Current SARS-CoV2 transmission continues in several countries despite drastic reduction in COVID-19 ...

Abstract	Globalization, global climatic changes, and human behavior pose threats to highly pathogenic avian influenza (HPAI) virus spillover from animals to human. Current SARS-CoV2 transmission continues in several countries despite drastic reduction in COVID-19 cases following world-wide containment measures including RNA vaccines. China reimposed lockdown in November 2022 following the surge in commercial hubs. Urban population density and intracity travel in over-crowded public transport play crucial roles in early transition to an exponential phase of the epidemic in metro-cities. Based on the SARS-CoV2 transmission during the lockdown period in Chennai metro-city, we developed an algorithm that mimics a real-time scenario of passengers boarding and deboarding at each bus-stop on a trip of 36.1 km in 21G bus service in Chennai city to understand the pattern of secondary infections on a daily basis. The algorithm was simulated to estimate R0, and the COVID-19 secondary infections was estimated for each bus trip. Results showed that the R0 depended on the boarding and deboarding of the infected individuals at various bus stops. R0 varied from 0 to 1.04, each trip generated 5-9 secondary infections and four bus stops as potential locations for a higher transmission level. More than 80% of the working population in metro-cities depends on unorganized sectors, and separate mitigation strategies must be in place for successful epidemic containment. The developed algorithm has significant public health relevance and can be utilized to draw necessary containment plans in near future in the event of new COVID-19 wave or any other similar epidemic. Supplementary information: The online version contains supplementary material available at 10.1007/s13337-022-00804-9.
Language	English
Publishing date	2023-02-02
Publishing country	India
Document type	Journal Article
ZDB-ID	2846993-8
ISSN	2347-3517 ; 2347-3584
ISSN (online)	2347-3517
ISSN	2347-3584
DOI	10.1007/s13337-022-00804-9
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

Order via subito

Details ▾
- Full text online
- Order with fees

Article ; Online: Comparison of Preprocessing Techniques for Dental Image Analysis.

Sukanya, Arockia / Krishnamurthy, Kamalanand / Balakrishnan, Thayumanavan

Current medical imaging

2020 Volume 16, Issue 7, Page(s) 776–780

Abstract: Various dental disorders, such as lesions, masses, carries, etc. may affect the human dental structure. Dental radiography is a technique, which passes X-rays through dental structures and records the radiographic images. These radiographic images are ... ...

Abstract	Various dental disorders, such as lesions, masses, carries, etc. may affect the human dental structure. Dental radiography is a technique, which passes X-rays through dental structures and records the radiographic images. These radiographic images are used to analyze the disorders present in the human teeth. Preprocessing is a primary step to enhance the radiographic images for further segmentation and classification of images. In this work, the preprocessing techniques such as unsharp masking using high pass filter, bi-level histogram equalization and hybrid metaheuristic have been utilized for dental radiographs. The performance measures of the preprocessing techniques were analyzed. Results demonstrate that a hybrid metaheuristic algorithm for dental radiographs achieves higher performance measures when compared to other enhancement methods. An average Peak Signal-to-Noise Ratio (PSNR) value of 21.6 was observed in the case of a hybrid metaheuristic technique for dental image enhancement.
Language	English
Publishing date	2020-10-27
Publishing country	United Arab Emirates
Document type	Journal Article
ISSN	1573-4056
ISSN (online)	1573-4056
DOI	10.2174/1573405615666191115101536
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Mathematical Modelling to Assess the Impact of Lockdown on COVID-19 Transmission in India: Model Development and Validation

Ambikapathy, Bakiya / Krishnamurthy, Kamalanand

JMIR Public Health Surveill

Abstract: BACKGROUND: The World Health Organization has declared the novel coronavirus disease (COVID-19) to be a public health emergency; at present, India is facing a major threat of community spread. We developed a mathematical model for investigating and ... ...

Abstract	BACKGROUND: The World Health Organization has declared the novel coronavirus disease (COVID-19) to be a public health emergency; at present, India is facing a major threat of community spread. We developed a mathematical model for investigating and predicting the effects of lockdown on future COVID-19 cases with a specific focus on India. OBJECTIVE: The objective of this work was to develop and validate a mathematical model and to assess the impact of various lockdown scenarios on COVID-19 transmission in India. METHODS: A model consisting of a framework of ordinary differential equations was developed by incorporating the actual reported cases in 14 countries. After validation, the model was applied to predict COVID-19 transmission in India for different intervention scenarios in terms of lockdown for 4, 14, 21, 42, and 60 days. We also assessed the situations of enhanced exposure due to aggregation of individuals in transit stations and shopping malls before the lockdown. RESULTS: The developed model is efficient in predicting the number of COVID-19 cases compared to the actual reported cases in 14 countries. For India, the model predicted marked reductions in cases for the intervention periods of 14 and 21 days of lockdown and significant reduction for 42 days of lockdown. Such intervention exceeding 42 days does not result in measurable improvement. Finally, for the scenario of "panic shopping" or situations where there is a sudden increase in the factors leading to higher exposure to infection, the model predicted an exponential transmission, resulting in failure of the considered intervention strategy. CONCLUSIONS: Implementation of a strict lockdown for a period of at least 21 days is expected to reduce the transmission of COVID-19. However, a further extension of up to 42 days is required to significantly reduce the transmission of COVID-19 in India. Any relaxation in the lockdown may lead to exponential transmission, resulting in a heavy burden on the health care system in the country.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #32365045
Database	COVID19

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾

Article ; Online: Mathematical Modelling to Assess the Impact of Lockdown on COVID-19 Transmission in India

Ambikapathy, Bakiya / Krishnamurthy, Kamalanand

JMIR Public Health and Surveillance, Vol 6, Iss 2, p e

Model Development and Validation

2020 Volume 19368

Abstract: BackgroundThe World Health Organization has declared the novel coronavirus disease (COVID-19) to be a public health emergency; at present, India is facing a major threat of community spread. We developed a mathematical model for investigating and ... ...

Abstract	BackgroundThe World Health Organization has declared the novel coronavirus disease (COVID-19) to be a public health emergency; at present, India is facing a major threat of community spread. We developed a mathematical model for investigating and predicting the effects of lockdown on future COVID-19 cases with a specific focus on India. ObjectiveThe objective of this work was to develop and validate a mathematical model and to assess the impact of various lockdown scenarios on COVID-19 transmission in India. MethodsA model consisting of a framework of ordinary differential equations was developed by incorporating the actual reported cases in 14 countries. After validation, the model was applied to predict COVID-19 transmission in India for different intervention scenarios in terms of lockdown for 4, 14, 21, 42, and 60 days. We also assessed the situations of enhanced exposure due to aggregation of individuals in transit stations and shopping malls before the lockdown. ResultsThe developed model is efficient in predicting the number of COVID-19 cases compared to the actual reported cases in 14 countries. For India, the model predicted marked reductions in cases for the intervention periods of 14 and 21 days of lockdown and significant reduction for 42 days of lockdown. Such intervention exceeding 42 days does not result in measurable improvement. Finally, for the scenario of “panic shopping” or situations where there is a sudden increase in the factors leading to higher exposure to infection, the model predicted an exponential transmission, resulting in failure of the considered intervention strategy. ConclusionsImplementation of a strict lockdown for a period of at least 21 days is expected to reduce the transmission of COVID-19. However, a further extension of up to 42 days is required to significantly reduce the transmission of COVID-19 in India. Any relaxation in the lockdown may lead to exponential transmission, resulting in a heavy burden on the health care system in the country.
Keywords	Public aspects of medicine ; RA1-1270
Subject code	306
Language	English
Publishing date	2020-05-01T00:00:00Z
Publisher	JMIR Publications
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Mathematical modelling of parental influence on human romantic relationships

Kamalanand, Krishnamurthy / Jawahar, Ponnuswamy Mannar

International journal of happiness and development Vol. 1, No. 3 , p. 294-301

2013 Volume 1, Issue 3, Page(s) 294–301

Author's details	Krishnamurthy Kamalanand; Ponnuswamy Mannar Jawahar
Keywords	human romantic relationships ; mathematical model ; ordinary differential equations
Language	English
Size	graph. Darst.
Publisher	Inderscience
Publishing place	[Olney]
Document type	Article
ZDB-ID	2711593-8
ISSN	2049-2790
Database	ECONomics Information System

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Prediction of the Transition From Subexponential to the Exponential Transmission of SARS-CoV-2 in Chennai, India: Epidemic Nowcasting.

Krishnamurthy, Kamalanand / Ambikapathy, Bakiya / Kumar, Ashwani / Britto, Lourduraj De

JMIR public health and surveillance

2020 Volume 6, Issue 3, Page(s) e21152

Abstract: Background: Several countries adopted lockdown to slowdown the exponential transmission of the coronavirus disease (COVID-19) epidemic. Disease transmission models and the epidemic forecasts at the national level steer the policy to implement ... ...

Abstract	Background: Several countries adopted lockdown to slowdown the exponential transmission of the coronavirus disease (COVID-19) epidemic. Disease transmission models and the epidemic forecasts at the national level steer the policy to implement appropriate intervention strategies and budgeting. However, it is critical to design a data-driven reliable model for nowcasting for smaller populations, in particular metro cities. Objective: The aim of this study is to analyze the transition of the epidemic from subexponential to exponential transmission in the Chennai metro zone and to analyze the probability of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) secondary infections while availing the public transport systems in the city. Methods: A single geographical zone "Chennai-Metro-Merge" was constructed by combining Chennai District with three bordering districts. Subexponential and exponential models were developed to analyze and predict the progression of the COVID-19 epidemic. Probabilistic models were applied to assess the probability of secondary infections while availing public transport after the release of the lockdown. Results: The model predicted that transition from subexponential to exponential transmission occurs around the eighth week after the reporting of a cluster of cases. The probability of secondary infections with a single index case in an enclosure of the city bus, the suburban train general coach, and the ladies coach was found to be 0.192, 0.074, and 0.114, respectively. Conclusions: Nowcasting at the early stage of the epidemic predicts the probable time point of the exponential transmission and alerts the public health system. After the lockdown release, public transportation will be the major source of SARS-CoV-2 transmission in metro cities, and appropriate strategies based on nowcasting are needed.
MeSH term(s)	Betacoronavirus ; COVID-19 ; Cities ; Communicable Disease Control/methods ; Coronavirus ; Coronavirus Infections/epidemiology ; Coronavirus Infections/transmission ; Coronavirus Infections/virology ; Epidemics ; Humans ; India/epidemiology ; Models, Statistical ; Motor Vehicles ; Pandemics ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/transmission ; Pneumonia, Viral/virology ; Public Health ; Railroads ; SARS-CoV-2 ; Severe Acute Respiratory Syndrome ; Transportation
Keywords	covid19
Language	English
Publishing date	2020-09-18
Publishing country	Canada
Document type	Journal Article
ISSN	2369-2960
ISSN (online)	2369-2960
DOI	10.2196/21152
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Firefly-Algorithm Supported Scheme to Detect COVID-19 Lesion in Lung CT Scan Images using Shannon Entropy and Markov-Random-Field

Venkatesan Rajinikanth / Seifedine Kadry / Krishnan Thanaraj Palani / Krishnamurthy Kamalanand / Sanghyun Seo

Abstract: The pneumonia caused by Coronavirus disease (COVID-19) is one of major global threat and a number of detection and treatment procedures are suggested by the researchers for COVID-19. The proposed work aims to suggest an automated image processing scheme ... ...

Abstract	The pneumonia caused by Coronavirus disease (COVID-19) is one of major global threat and a number of detection and treatment procedures are suggested by the researchers for COVID-19. The proposed work aims to suggest an automated image processing scheme to extract the COVID-19 lesion from the lung CT scan images (CTI) recorded from the patients. This scheme implements the following procedures; (i) Image pre-processing to enhance the COVID-19 lesions, (ii) Image post-processing to extract the lesions, and (iii) Execution of a relative analysis between the extracted lesion segment and the Ground-Truth-Image (GTI). This work implements Firefly Algorithm and Shannon Entropy (FA+SE) based multi-threshold to enhance the pneumonia lesion and implements Markov-Random-Field (MRF) segmentation to extract the lesions with better accuracy. The proposed scheme is tested and validated using a class of COVID-19 CTI obtained from the existing image datasets and the experimental outcome is appraised to authenticate the clinical significance of the proposed scheme. The proposed work helped to attain a mean accuracy of>92% during COVID-19 lesion segmentation and in future, it can be used to examine the real clinical lung CTI of COVID-19 patients.
Keywords	covid19
Publisher	arxiv
Document type	Article
Database	COVID19

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾

Article: Firefly-Algorithm Supported Scheme to Detect COVID-19 Lesion in Lung CT Scan Images using Shannon Entropy and Markov-Random-Field

Rajinikanth, Venkatesan / Kadry, Seifedine / Thanaraj, Krishnan Palani / Kamalanand, Krishnamurthy / Seo, Sanghyun

Abstract	The pneumonia caused by Coronavirus disease (COVID-19) is one of major global threat and a number of detection and treatment procedures are suggested by the researchers for COVID-19. The proposed work aims to suggest an automated image processing scheme to extract the COVID-19 lesion from the lung CT scan images (CTI) recorded from the patients. This scheme implements the following procedures; (i) Image pre-processing to enhance the COVID-19 lesions, (ii) Image post-processing to extract the lesions, and (iii) Execution of a relative analysis between the extracted lesion segment and the Ground-Truth-Image (GTI). This work implements Firefly Algorithm and Shannon Entropy (FA+SE) based multi-threshold to enhance the pneumonia lesion and implements Markov-Random-Field (MRF) segmentation to extract the lesions with better accuracy. The proposed scheme is tested and validated using a class of COVID-19 CTI obtained from the existing image datasets and the experimental outcome is appraised to authenticate the clinical significance of the proposed scheme. The proposed work helped to attain a mean accuracy of>92% during COVID-19 lesion segmentation and in future, it can be used to examine the real clinical lung CTI of COVID-19 patients.
Keywords	covid19
Publisher	ArXiv
Document type	Article
Database	COVID19

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾

Book ; Online: Firefly-Algorithm Supported Scheme to Detect COVID-19 Lesion in Lung CT Scan Images using Shannon Entropy and Markov-Random-Field

Rajinikanth, Venkatesan / Kadry, Seifedine / Thanaraj, Krishnan Palani / Kamalanand, Krishnamurthy / Seo, Sanghyun

2020

Abstract	The pneumonia caused by Coronavirus disease (COVID-19) is one of major global threat and a number of detection and treatment procedures are suggested by the researchers for COVID-19. The proposed work aims to suggest an automated image processing scheme to extract the COVID-19 lesion from the lung CT scan images (CTI) recorded from the patients. This scheme implements the following procedures; (i) Image pre-processing to enhance the COVID-19 lesions, (ii) Image post-processing to extract the lesions, and (iii) Execution of a relative analysis between the extracted lesion segment and the Ground-Truth-Image (GTI). This work implements Firefly Algorithm and Shannon Entropy (FA+SE) based multi-threshold to enhance the pneumonia lesion and implements Markov-Random-Field (MRF) segmentation to extract the lesions with better accuracy. The proposed scheme is tested and validated using a class of COVID-19 CTI obtained from the existing image datasets and the experimental outcome is appraised to authenticate the clinical significance of the proposed scheme. The proposed work helped to attain a mean accuracy of >92% during COVID-19 lesion segmentation and in future, it can be used to examine the real clinical lung CTI of COVID-19 patients. Comment: 12 pages
Keywords	Electrical Engineering and Systems Science - Image and Video Processing ; covid19
Subject code	006
Publishing date	2020-04-14
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

Kategorien

Inter-library loan at ZB MED

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED