Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil
Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i) which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii) how vector density spatial heterogeneity influences control efforts; (iii) with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4) in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0) that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases.
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Instituto Oswaldo Cruz, Ministério da Saúde
2003
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oai:scielo:S0074-027620030007000022004-01-07Uncertainties regarding dengue modeling in Rio de Janeiro, BrazilLuz,Paula MendesCodeço,Cláudia TorresMassad,EduardoStruchiner,Claudio José dengue modeling uncertainties vector density spatial heterogeneity control measures of arthropod-borne diseases Rio de Janeiro Brazil Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i) which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii) how vector density spatial heterogeneity influences control efforts; (iii) with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4) in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0) that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases.info:eu-repo/semantics/openAccessInstituto Oswaldo Cruz, Ministério da SaúdeMemórias do Instituto Oswaldo Cruz v.98 n.7 20032003-10-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762003000700002en10.1590/S0074-02762003000700002 |
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Luz,Paula Mendes Codeço,Cláudia Torres Massad,Eduardo Struchiner,Claudio José |
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Luz,Paula Mendes Codeço,Cláudia Torres Massad,Eduardo Struchiner,Claudio José Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil |
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Luz,Paula Mendes Codeço,Cláudia Torres Massad,Eduardo Struchiner,Claudio José |
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Luz,Paula Mendes |
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Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil |
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Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil |
title_full |
Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil |
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Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil |
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Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil |
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uncertainties regarding dengue modeling in rio de janeiro, brazil |
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Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i) which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii) how vector density spatial heterogeneity influences control efforts; (iii) with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4) in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0) that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases. |
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Instituto Oswaldo Cruz, Ministério da Saúde |
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2003 |
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http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762003000700002 |
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