Forecast of the occupancy of standard and intensive care unit beds by COVID-19 inpatients

This paper proposes a methodology to forecast the number of hospital beds required by COVID-19 inpatients in mild and in critical conditions. To that end, a compartmental model is extended to include the number of critical inpatients, which require hospitalization in intensive care units (ICUs). The model parameters are tailored by using a data-driven approach and a computational methodology for numerical optimization. A multi-objective cost function is adopted, representing the match between the model output and the observed data for four variables, namely the total number of cases, demises, hospitalizations and ICU beds. Results for different regions of the Brazilian state of Sao Paulo are presented. The results show that the model represents well the training data and is able to predict the required health system resources.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)2020/14357-

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. Results for four states and four cities, selected among the most populated in Mexico, are presented. The model was able to suitably fit the local data for the selected regions under evaluation. Moreover, the trend analysis enabled one to assess the accuracy of the forecasts.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)2020/14357-

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. The results discussed here are illustrative for six cities in Israel, including Jerusalem and Tel Aviv. They show that the model employed fits well with the observed data and is able to suitably describe the COVID-19 dynamics in a country strongly impacted by the disease that holds one of the most successful vaccination programs in the world.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)2020/14357-12019/18294-

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

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. Trend analyses are run, allowing to assess the effects of public policies. Easy to interpret metrics over the quality of the fitted curves are provided. Country-wise data from the European Centre for Disease Prevention and Control (ECDC) concerning the daily number of cases and demises around the world are used, as well as detailed data from Johns Hopkins University and from the Brasil.io project describing individually the occurrences in United States counties and in Brazilian states and cities, respectively. U. S. and Brazil were chosen for a more detailed analysis because they are the current focus of the pandemic. Results: Illustrative results for different countries, U. S. counties and Brazilian states and cities are presented and discussed. Conclusion: The main contributions of this work lie in (i) a straightforward model of the curves to represent the data, which allows automation of the process without requiring interventions from experts; (ii) an innovative approach for trend analysis, whose results provide important information to support authorities in their decision-making process; and (iii) the developed computational tool, which is freely available and allows the user to quickly update the COVID-19 analyses and forecasts for any country, United States county or Brazilian state or city present in the periodic reports from the authorities.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)2020/14357-

Information System for Epidemic Control: a computational solution addressing successful experiences and main challenges

Purpose: The SARS-CoV-2 pandemic has caused a major impact on worldwide public health and economics. The lessons learned from the successful attempts to contain the pandemic escalation revealed that the wise usage of contact tracing and information systems can widely help the containment work of any contagious disease. In this context, this paper investigates other researches on this domain, as well as the main issues related to the practical implementation of such systems, and specifies a technical solution. Methodology: The solution is based on the automatic identification of relevant contacts between infected or suspected cases with susceptible people; inference of contamination risk based on symptoms history, user navigation records, and contact information; real-time georeferenced information of population density of infected or suspect people; and automatic individual social distancing recommendation calculated through the individual contamination risk and the worsening of clinical condition risk. Findings: The solution was specified, prototyped, and evaluated by potential users and health authorities. The proposed solution has the potential of becoming a reference on how to coordinate the efforts of health authorities and the population on epidemic control. Originality: This paper proposed an original information system for epidemic control, which was applied for the SARS-CoV-2 pandemic and could be easily extended to other epidemics.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)2020/14357-