arXiv subjects

Sara Pasquali

Publications and source records attributed to Sara Pasquali.

3 recordsLinked to original sources

arXiv2021

A stochastic SIR model for the analysis of the COVID-19 Italian epidemic

We propose a stochastic SIR model, specified as a system of stochastic differential equations, to analyse the data of the Italian COVID-19 epidemic, taking also into account the under-detection of infected and recovered individuals in the population. We find that a correct assessment of the amount of under-detection is important to obtain reliable estimates of the critical model parameters. Moreover, a single SIR model over the whole epidemic period is unable to correctly describe the behaviour of the pandemic. Then, the adaptation of the model in every time-interval between relevant government decrees that implement contagion mitigation measures, provides short-term predictions and a continuously updated assessment of the basic reproduction number.

q-bio.PE↗

arXiv2020

Estimation of the mortality rate functions from time series field data in a stage-structured demographic model for Lobesia botrana

Simulating the population dynamics of a stage-structured population requires the knowledge of the biodemographic functions characterizing the species, namely development, mortality and fecundity. In general, development and fecundity can satisfactorily be estimated starting from literature data. Unfortunately, this is often not the case of the mortality function, because of the lack of experimental data. To overcome this problem we estimate the mortality rate function from field data on the abundance of the species. The mortality is expressed as a linear combination of cubic splines and the estimation method allows to determine its coefficients taking into account the observations measurement error. Moreover, the variability in the estimate is quantified by means of the confidence bands for both mortality and dynamics. The presented method allows to obtain a more flexible shape for the mortality rate functions compared with previous methods applied to the same pest. The method is applied to the case of Lobesia botrana, the main pest in the European vineyards, with abundance data collected in a location in the North of Italy for five consecutive years. Data collected over three years are used to estimate the mortality and to analyze the variability in the estimate and its effects on the population dynamics. Other two datasets are used to validate the model simulating the dynamics using the estimated mortality.

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arXiv2018

The effects of fecundity, mortality and distribution of the initial condition in phenological models

Pest phenological models describe the cumulative flux of the individuals into each stage of the life cycle of a stage-structured population. Phenological models are widely used tools in pest control decision making. Despite the fact that these models do not provide information on population abundance, they share some advantages with respect to the more sophisticated and complex demographic models. The main advantage is that they do not require data collection to define the initial conditions of model simulation, reducing the effort for field sampling and the high uncertainty affecting sample estimates. Phenological models are often built considering the developmental rate function only. To the aim of adding more realism to phenological models, in this paper we explore the consequences of improving these models taking into consideration three additional elements: the age distribution of individuals which exit from the overwintering phase, the age- and temperature-dependent profile of the fecundity rate function and the consideration of a temperature-dependent mortality rate function. Numerical simulations are performed to investigate the effect of these elements with respect to phenological models considering development rate functions only. To further test the implications of different models formulation, we compare results obtained from different phenological models to the case study of the codling moth (Cydia pomonella) a primary pest of the apple orchard. The results obtained from model comparison are discussed in view of their potential application in pest control decision support.

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