COVID-19 Trend Analysis in Mexican States and Cities.

This paper presents a trend analysis of the COVID-19 pandemics in Mexico. The studies were run in a subnational basis because they are more useful that way, providing important information about the pandemic to local authorities. Unlike classic approaches in the literature, the trend analysis presented here is not based on the variations in the number of infections along time, but rather on the predicted value of the final number of infections, which is updated every day employing new data.

A computational tool for trend analysis and forecast of the COVID-19 pandemic.

Purpose: This paper proposes a methodology and a computational tool to study the COVID-19 pandemic throughout the world and to perform a trend analysis to assess its local dynamics.

Methods: Mathematical functions are employed to describe the number of cases and demises in each region and to predict their final numbers, as well as the dates of maximum daily occurrences and the local stabilization date. The model parameters are calibrated using a computational methodology for numerical optimization.

Study of the COVID-19 pandemic trending behavior in Israeli cities.

This paper studies the trending behavior of the COVID-19 dynamics in Israeli cities. The model employed is used to describe, for each city, the accumulated number of cases, the number of cases per day, and the predicted final number of cases. The innovative analysis adopted here is based on the daily evolution of the predicted final number of infections, estimated with data available until a given date.

A data-driven model to describe and forecast the dynamics of COVID-19 transmission.

This paper proposes a dynamic model to describe and forecast the dynamics of the coronavirus disease COVID-19 transmission. The model is based on an approach previously used to describe the Middle East Respiratory Syndrome (MERS) epidemic. This methodology is used to describe the COVID-19 dynamics in six countries where the pandemic is widely spread, namely China, Italy, Spain, France, Germany, and the USA.

Computational load reduction of the agent guidance problem using Mixed Integer Programming.

This paper employs a solution to the agent-guidance problem in an environment with obstacles, whose avoidance techniques have been extensively used in the last years. There is still a gap between the solution times required to obtain a trajectory and those demanded by real world applications. These usually face a tradeoff between the limited on-board processing performance and the high volume of computing operations demanded by those real-time applications.