An alternative model to explain the vectorial capacity using as example Aedes aegypti case in dengue transmission
Fecha
2019-01-01
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Elsevier BV
Resumen
Vectorial capacity (VC), as a concept that describes the potential of a vector to transmit a pathogen, has had historical problems related to lacks in dimensional significance and high error propagation from parameters that take part in the model to output. Hence, values estimated with those equations are not sufficiently reliable to consider in control strategies or vector population study. In this paper, we propose a new VC model consistent at dimensional level, i.e., the definition and the equation of VC have same and consistent units, with a parameter estimation method and mathematical structure that reduces the uncertainty in model output, using as a case of study an Aedes aegypti population of the municipality of Bello, Colombia. After a literature review, we selected one VC equation following biological, measurability and dimensional criteria, then we rendered a local and global sensitivity analysis, identifying the mortality rate of mosquitoes as a target component of the equation. Thus, we studied the Weibull and Exponential distributions as probabilistic models that represent the expectation of mosquitoes infective life, intending to include the best distribution in a selected VC structure. The proposed mortality rate estimation method includes a new parameter that represents an increase or decrease in vector mortality, as it may apply. We noticed that its estimation reduces the uncertainty associated with the expectation of mosquitoes' infective life expression, which also reduces the output range and variance in almost a half. Virology; Applied mathematics; Health sciences; Epidemiology; Infectious disease; Mortality; Uncertainty analysis; Vectorial capacity; Sensitivity analysis; Dengue © 2019 The Authors
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Applied mathematics, Dengue, Epidemiology, Health sciences, Infectious disease, Mortality, Sensitivity analysis, Uncertainty analysis, Vectorial capacity, Virology