A combination of differential equations and convolution in understanding the spread of an epidemic

Arni S.R. Srinivasa Rao; Masayuki Kakehashi

doi:10.1007/bf02703780

A combination of differential equations and convolution in understanding the spread of an epidemic

Arni S.R. Srinivasa Rao, Masayuki Kakehashi

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

Nonlinear dynamical method of projecting the transmission of an epidemic is accurate if the input parameters and initial value variables are reliable. Here, such a model is proposed for predicting an epidemic. A method to supplement two variables and two parameters for this proposed model is demonstrated through a robust statistical approach. The method described here worked well in case of three continuous distributions. Model predictions could be lower estimates due to under-reporting of disease cases. An ad hoc procedure with a technical note is provided in the appendix.

Original language	English (US)
Pages (from-to)	305-313
Number of pages	9
Journal	Sadhana - Academy Proceedings in Engineering Sciences
Volume	29
Issue number	3
DOIs	https://doi.org/10.1007/bf02703780
State	Published - 2004
Externally published	Yes

Keywords

Convolution
Dynamical model
HIV
Likelihood

ASJC Scopus subject areas

General

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/bf02703780

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abstract = "Nonlinear dynamical method of projecting the transmission of an epidemic is accurate if the input parameters and initial value variables are reliable. Here, such a model is proposed for predicting an epidemic. A method to supplement two variables and two parameters for this proposed model is demonstrated through a robust statistical approach. The method described here worked well in case of three continuous distributions. Model predictions could be lower estimates due to under-reporting of disease cases. An ad hoc procedure with a technical note is provided in the appendix.",

keywords = "Convolution, Dynamical model, HIV, Likelihood",

author = "{Srinivasa Rao}, {Arni S.R.} and Masayuki Kakehashi",

note = "Funding Information: We thank the anonymous referees for their comments which helped us in bringing out this final version. ASRSR thanks the Department of Science and Technology, New Delhi for financial support.",

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T1 - A combination of differential equations and convolution in understanding the spread of an epidemic

AU - Srinivasa Rao, Arni S.R.

AU - Kakehashi, Masayuki

N1 - Funding Information: We thank the anonymous referees for their comments which helped us in bringing out this final version. ASRSR thanks the Department of Science and Technology, New Delhi for financial support.

PY - 2004

Y1 - 2004

N2 - Nonlinear dynamical method of projecting the transmission of an epidemic is accurate if the input parameters and initial value variables are reliable. Here, such a model is proposed for predicting an epidemic. A method to supplement two variables and two parameters for this proposed model is demonstrated through a robust statistical approach. The method described here worked well in case of three continuous distributions. Model predictions could be lower estimates due to under-reporting of disease cases. An ad hoc procedure with a technical note is provided in the appendix.

AB - Nonlinear dynamical method of projecting the transmission of an epidemic is accurate if the input parameters and initial value variables are reliable. Here, such a model is proposed for predicting an epidemic. A method to supplement two variables and two parameters for this proposed model is demonstrated through a robust statistical approach. The method described here worked well in case of three continuous distributions. Model predictions could be lower estimates due to under-reporting of disease cases. An ad hoc procedure with a technical note is provided in the appendix.

KW - Convolution

KW - Dynamical model

KW - HIV

KW - Likelihood

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JF - Sadhana - Academy Proceedings in Engineering Sciences

IS - 3

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A combination of differential equations and convolution in understanding the spread of an epidemic

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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