The basic reproduction number $R_0$ and effectiveness of reactive interventions during dengue epidemics: The 2002 dengue outbreak in Easter Island, Chile
We use a stochastic simulation model to explore the effect of reactive intervention strategies during the 2002 dengue outbreak in the small population of Easter Island, Chile. We quantified the effect of interventions on the transmission dynamics and epidemic size as a function of the simulated con...
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| Language: | English |
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AIMS Press
2013-07-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2013.10.1455 |
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| author | Gerardo Chowell R. Fuentes A. Olea X. Aguilera H. Nesse J. M. Hyman |
| author_facet | Gerardo Chowell R. Fuentes A. Olea X. Aguilera H. Nesse J. M. Hyman |
| author_sort | Gerardo Chowell |
| collection | DOAJ |
| description | We use a stochastic simulation model to explore the effect of reactive intervention strategies during the 2002 dengue outbreak in the small population of Easter Island, Chile. We quantified the effect of interventions on the transmission dynamics and epidemic size as a function of the simulated control intensity levels and the timing of initiation of control interventions. Because no dengue outbreaks had been reported prior to 2002 in Easter Island, the 2002 epidemic provided a unique opportunity to estimate the basic reproduction number $R_0$ during the initial epidemic phase, prior to the start of control interventions. We estimated $R_0$ at $27.2$ ($95 \%$CI: $14.8$, $49.3$). We found that the final epidemic size is highly sensitive to the timing of start of interventions. However, even when the control interventions start several weeks after the epidemic onset, reactive intervention efforts can have a significant impact on the final epidemic size. Our results indicate that the rapid implementation of control interventions can have a significant effect in reducing the epidemic size of dengue epidemics. |
| format | Article |
| id | doaj-art-97c737ad57bf4c46a6a36f78eeafc45f |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2013-07-01 |
| publisher | AIMS Press |
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| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-97c737ad57bf4c46a6a36f78eeafc45f2025-01-24T02:26:34ZengAIMS PressMathematical Biosciences and Engineering1551-00182013-07-01105&61455147410.3934/mbe.2013.10.1455The basic reproduction number $R_0$ and effectiveness of reactive interventions during dengue epidemics: The 2002 dengue outbreak in Easter Island, ChileGerardo Chowell0R. Fuentes1A. Olea2X. Aguilera3H. Nesse4J. M. Hyman5Mathematical, Computational & Modeling Sciences Center, School of Human Evolution and Social Change, Arizona State University, Box 872402, Tempe, AZ 85287Department of Epidemiology, Ministerio de Salud, SantiagoUniversidad del Desarrollo, SantiagoUniversidad del Desarrollo, SantiagoSchool of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287Tulane University, New Orleans, LA, 70118We use a stochastic simulation model to explore the effect of reactive intervention strategies during the 2002 dengue outbreak in the small population of Easter Island, Chile. We quantified the effect of interventions on the transmission dynamics and epidemic size as a function of the simulated control intensity levels and the timing of initiation of control interventions. Because no dengue outbreaks had been reported prior to 2002 in Easter Island, the 2002 epidemic provided a unique opportunity to estimate the basic reproduction number $R_0$ during the initial epidemic phase, prior to the start of control interventions. We estimated $R_0$ at $27.2$ ($95 \%$CI: $14.8$, $49.3$). We found that the final epidemic size is highly sensitive to the timing of start of interventions. However, even when the control interventions start several weeks after the epidemic onset, reactive intervention efforts can have a significant impact on the final epidemic size. Our results indicate that the rapid implementation of control interventions can have a significant effect in reducing the epidemic size of dengue epidemics.https://www.aimspress.com/article/doi/10.3934/mbe.2013.10.1455chiledengueepidemiceaster island2002 outbreakreproduction number.dengue hemorrhagic fevermathematical model |
| spellingShingle | Gerardo Chowell R. Fuentes A. Olea X. Aguilera H. Nesse J. M. Hyman The basic reproduction number $R_0$ and effectiveness of reactive interventions during dengue epidemics: The 2002 dengue outbreak in Easter Island, Chile Mathematical Biosciences and Engineering chile dengue epidemic easter island 2002 outbreak reproduction number. dengue hemorrhagic fever mathematical model |
| title | The basic reproduction number $R_0$ and effectiveness of reactive interventions during dengue epidemics: The 2002 dengue outbreak in Easter Island, Chile |
| title_full | The basic reproduction number $R_0$ and effectiveness of reactive interventions during dengue epidemics: The 2002 dengue outbreak in Easter Island, Chile |
| title_fullStr | The basic reproduction number $R_0$ and effectiveness of reactive interventions during dengue epidemics: The 2002 dengue outbreak in Easter Island, Chile |
| title_full_unstemmed | The basic reproduction number $R_0$ and effectiveness of reactive interventions during dengue epidemics: The 2002 dengue outbreak in Easter Island, Chile |
| title_short | The basic reproduction number $R_0$ and effectiveness of reactive interventions during dengue epidemics: The 2002 dengue outbreak in Easter Island, Chile |
| title_sort | basic reproduction number r 0 and effectiveness of reactive interventions during dengue epidemics the 2002 dengue outbreak in easter island chile |
| topic | chile dengue epidemic easter island 2002 outbreak reproduction number. dengue hemorrhagic fever mathematical model |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2013.10.1455 |
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