Leptospirosis Relative Risk Estimates based on Continuous-Time, DiscreteSpace Stochastic SIR-L-SI Transmission Model
Leptospirosis is a re-emerging global disease that has become endemic in Malaysia. The transmissions usually occur between animals especially rats to rats and rats to humans. Since, it is an easily contractable disease that can be transmitted directly through contact with infected rat's urine o...
Published in: | MALAYSIAN JOURNAL OF FUNDAMENTAL AND APPLIED SCIENCES |
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Format: | Article |
Language: | English |
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PENERBIT UTM PRESS
2024
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Online Access: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001168161700019 |
author |
Ideris Sufi Hafawati; Shaadan Norshahida; Shair Syazreen Niza; Samat Nor Azah |
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Ideris Sufi Hafawati; Shaadan Norshahida; Shair Syazreen Niza; Samat Nor Azah Leptospirosis Relative Risk Estimates based on Continuous-Time, DiscreteSpace Stochastic SIR-L-SI Transmission Model Science & Technology - Other Topics |
author_facet |
Ideris Sufi Hafawati; Shaadan Norshahida; Shair Syazreen Niza; Samat Nor Azah |
author_sort |
Ideris |
spelling |
Ideris, Sufi Hafawati; Shaadan, Norshahida; Shair, Syazreen Niza; Samat, Nor Azah Leptospirosis Relative Risk Estimates based on Continuous-Time, DiscreteSpace Stochastic SIR-L-SI Transmission Model MALAYSIAN JOURNAL OF FUNDAMENTAL AND APPLIED SCIENCES English Article Leptospirosis is a re-emerging global disease that has become endemic in Malaysia. The transmissions usually occur between animals especially rats to rats and rats to humans. Since, it is an easily contractable disease that can be transmitted directly through contact with infected rat's urine or indirectly from the environment such as via water and soil, it is very challenging to curb this disease from infecting humans. Poor understanding of the disease and lack of epidemiological data also made leptospirosis is difficult to control. To cope with this problem, a leptospirosis disease transmission model is developed to study the mechanism of leptospirosis disease spread over continuoustime that may help to predict future caused of an outbreak. This study aims to construct a continuous -time and discrete -space stochastic SIR-L-SI (Susceptible, Infected, Recovered Humans-Leptospires in the Environment -Susceptible, Infectious Rats) of leptospirosis disease transmission to estimate the risk involved. A simple method of asymptotic and numerical analyses is applied as an alternative approach for solving simultaneous differential equations in the leptospirosis SIR-L-SI transmission model. The application of the proposed model is demonstrated using leptospirosis data for Malaysia. The results of asymptotic behaviour and numerical analysis provide useful information about susceptible and infective rat and human populations as well as offer relative risk estimates that can be used as one of the control measures in identifying hot -spot areas for this disease. PENERBIT UTM PRESS 2289-5981 2289-599X 2024 20 1 10.11113/mjfas.v20n1.3182 Science & Technology - Other Topics gold WOS:001168161700019 https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001168161700019 |
title |
Leptospirosis Relative Risk Estimates based on Continuous-Time, DiscreteSpace Stochastic SIR-L-SI Transmission Model |
title_short |
Leptospirosis Relative Risk Estimates based on Continuous-Time, DiscreteSpace Stochastic SIR-L-SI Transmission Model |
title_full |
Leptospirosis Relative Risk Estimates based on Continuous-Time, DiscreteSpace Stochastic SIR-L-SI Transmission Model |
title_fullStr |
Leptospirosis Relative Risk Estimates based on Continuous-Time, DiscreteSpace Stochastic SIR-L-SI Transmission Model |
title_full_unstemmed |
Leptospirosis Relative Risk Estimates based on Continuous-Time, DiscreteSpace Stochastic SIR-L-SI Transmission Model |
title_sort |
Leptospirosis Relative Risk Estimates based on Continuous-Time, DiscreteSpace Stochastic SIR-L-SI Transmission Model |
container_title |
MALAYSIAN JOURNAL OF FUNDAMENTAL AND APPLIED SCIENCES |
language |
English |
format |
Article |
description |
Leptospirosis is a re-emerging global disease that has become endemic in Malaysia. The transmissions usually occur between animals especially rats to rats and rats to humans. Since, it is an easily contractable disease that can be transmitted directly through contact with infected rat's urine or indirectly from the environment such as via water and soil, it is very challenging to curb this disease from infecting humans. Poor understanding of the disease and lack of epidemiological data also made leptospirosis is difficult to control. To cope with this problem, a leptospirosis disease transmission model is developed to study the mechanism of leptospirosis disease spread over continuoustime that may help to predict future caused of an outbreak. This study aims to construct a continuous -time and discrete -space stochastic SIR-L-SI (Susceptible, Infected, Recovered Humans-Leptospires in the Environment -Susceptible, Infectious Rats) of leptospirosis disease transmission to estimate the risk involved. A simple method of asymptotic and numerical analyses is applied as an alternative approach for solving simultaneous differential equations in the leptospirosis SIR-L-SI transmission model. The application of the proposed model is demonstrated using leptospirosis data for Malaysia. The results of asymptotic behaviour and numerical analysis provide useful information about susceptible and infective rat and human populations as well as offer relative risk estimates that can be used as one of the control measures in identifying hot -spot areas for this disease. |
publisher |
PENERBIT UTM PRESS |
issn |
2289-5981 2289-599X |
publishDate |
2024 |
container_volume |
20 |
container_issue |
1 |
doi_str_mv |
10.11113/mjfas.v20n1.3182 |
topic |
Science & Technology - Other Topics |
topic_facet |
Science & Technology - Other Topics |
accesstype |
gold |
id |
WOS:001168161700019 |
url |
https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001168161700019 |
record_format |
wos |
collection |
Web of Science (WoS) |
_version_ |
1809678907005206528 |