Final validation of the forecast for the spread of the Ebola virus disease 2018-20 (EVD 2018-20) done with the Be-CoDiS mathematical model

Depto. de Análisis Matemático y Matemática AplicadaInstituto de Matemática Interdisciplinar (IMI)Fac. de Ciencias MatemáticasFALSEMinisterio de Economía y Competitividad (MINECO)unpu

Mathematical modeling of the spread of the coronavirus disease 2019 (COVID-19) taking into account the undetected infections. The case of China

In this paper we develop a mathematical model for the spread of the coronavirus disease 2019 (COVID-19). We use a compartmental model (but not a SIR, SEIR or other general purpose model) and take into account the known special characteristics of this disease, as the existence of infectious undetected cases. We study the particular case of China (including Chinese Mainland, Macao, Hong-Kong and Taiwan, as done by the World Health Organization in its reports about COVID-19), the country spreading the disease, and use its reported data to identify the modelparameters, which can be of interest for estimating the spread of COVID-19 in other countries. The model is also able to estimate the needs of beds in hospitals for intensive care units. Finally, we also study the behavior of the outputs returned by our model when considering incomplete data (by truncating them at some dates before and after the peak of daily reported cases). By comparing those results with real observation we can estimate the error produced by the model when identifying the parameters at early stages of the epidemic

Improving the performance of a preference-based multi-objective algorithm to optimize food treatment processes

This work focuses on the optimization of some high-pressure and temperature food treatments. When dealing with real--life multi-objective optimization problems, the computational cost of evaluating the considered objective functions is usually quite high. Therefore, only a reduced number of iterations is affordable for the optimization algorithm. However, using fewer iterations can lead to inaccurate solutions far from the real Pareto optimal front. In this work, we analyze and compare different mechanisms to improve the convergence of a preference-based multi-objective optimization algorithm called Weighting Achievement Scalarizing Function Genetic Algorithm. The combination of these techniques has been applied for optimizing a particular food treatment process. In particular, the proposed method based on the introduction of an advanced population achieves important improvements in the considered quality indicator measures

Modeling the impact of SARS-CoV-2 variants and vaccines on the spread of COVID-19

The continuous mutation of SARS-CoV-2 opens the possibility of the appearance of new variants of the virus with important differences in its spreading characteristics, mortality rates, etc. On 14 December 2020, the United Kingdom reported a potentially more contagious coronavirus variant, present in that country, which is referred to as VOC 202012/01. On 18 December 2020, the South African government also announced the emergence of a new variant in a scenario similar to that of the UK, which is referred to as variant 501.V2. Another important milestone regarding this pandemic was the beginning, in December 2020, of vaccination campaigns in several countries. There are several vaccines, with different characteristics, developed by various laboratories and research centers. A natural question arises: what could be the impact of these variants and vaccines on the spread of COVID-19? Many models have been proposed to simulate the spread of COVID-19 but, to the best of our knowledge, none of them incorporates the effects of potential SARS-CoV-2 variants together with the vaccines in the spread of COVID-19. We develop here a -SVEIHQRD mathematical model able to simulate the possible impact of this type of variants and of the vaccines, together with the main mechanisms influencing the disease spread. The model may be of interest for policy makers, as a tool to evaluate different possible future scenarios. We apply the model to the particular case of Italy (as an example of study case), showing different outcomes. We observe that the vaccines may reduce the infections, but they might not be enough for avoiding a new wave, with the current expected vaccination rates in that country, if the control measures are relaxed. Furthermore, a more contagious variant could increase significantly the cases, becoming the most common way of infection. We show how, even with the pandemic cases slowing down (with an effective reproduction number less than 1) and the disease seeming to be under control, the effective reproduction number of just the new variant may be greater than 1 and, eventually, the number of infections would increase towards a new disease wave. Therefore, a rigorous follow-up of the evolution of the number of infections with any potentially more dangerous new variant is of paramount importance at any stage of the pandemic

A multi-objective approach to estimate parameters of compartmental epidemiological models. Application to Ebola Virus Disease epidemics.

In this work, we propose a novel methodology to adjust parameters of compartmental epidemiological models. It is based on solving a multi-objective optimization problem that consists in fitting some of the model outputs to real observations. First, according to the available data of the considered epidemic, we define a multi-objective optimization problem where the model parameters are the optimization variables. Then, this problem is solved by considering a particular optimization algorithm called ParWASF-GA (ParallelWeighting Achievement Scalarizing Function Genetic Algorithm). Finally, the decision maker chooses, within the set of possible solutions, the values of parameters that better suit his/her preferences. In order to illustrate the benefit of using our approach, it is applied to estimate the parameters of a deterministic epidemiological model, called Be-CoDiS (Between-Countries Disease Spread), used to forecast the possible spread of human diseases within and between countries. We consider data from different Ebola outbreaks from 2014 up to 2019. In all cases, the proposed methodology helps to obtain reasonable predictions of the epidemic magnitudes with the considered model

Safety of hospital discharge before return of bowel function after elective colorectal surgery

© 2020 BJS Society Ltd Published by John Wiley & Sons LtdBackground: Ileus is common after colorectal surgery and is associated with an increased risk of postoperative complications. Identifying features of normal bowel recovery and the appropriateness for hospital discharge is challenging. This study explored the safety of hospital discharge before the return of bowel function. Methods: A prospective, multicentre cohort study was undertaken across an international collaborative network. Adult patients undergoing elective colorectal resection between January and April 2018 were included. The main outcome of interest was readmission to hospital within 30 days of surgery. The impact of discharge timing according to the return of bowel function was explored using multivariable regression analysis. Other outcomes were postoperative complications within 30 days of surgery, measured using the Clavien–Dindo classification system. Results: A total of 3288 patients were included in the analysis, of whom 301 (9·2 per cent) were discharged before the return of bowel function. The median duration of hospital stay for patients discharged before and after return of bowel function was 5 (i.q.r. 4–7) and 7 (6–8) days respectively (P < 0·001). There were no significant differences in rates of readmission between these groups (6·6 versus 8·0 per cent; P = 0·499), and this remained the case after multivariable adjustment for baseline differences (odds ratio 0·90, 95 per cent c.i. 0·55 to 1·46; P = 0·659). Rates of postoperative complications were also similar in those discharged before versus after return of bowel function (minor: 34·7 versus 39·5 per cent; major 3·3 versus 3·4 per cent; P = 0·110). Conclusion: Discharge before return of bowel function after elective colorectal surgery appears to be safe in appropriately selected patients