Estimating the number of deaths due to COVID-19 in Lima and Peru during March and April 2020 using ARIMA time series and modeling

Abstract

Background: The SARS-CoV-2 virus which causes the COVID-19 disease is a large family of viruses that cause respiratory diseases and complications in human beings. Nowadays, the pandemic is studied by the rate of infection and mortality in different countries. Since there are discrepancies regarding the number of deaths due to the pandemic, our main goal is to estimate the number of deaths in Lima and Peru due to COVID-19. Methods: By using inference modeling techniques and statistical analysis in time series together with ARIMA-type predictions, it is possible to estimate the number of deaths caused by COVID-19. Our study took place in the city of Lima and Peru and our detailed analysis was carried out during March and April of 2020. Results: By comparing the death toll provided by the Ministry of Health (MINSA), we have obtained approximately a difference of 325.9% regarding the number of deaths due to COVID-19 in the city of Lima and a difference of 185.9% regarding the number of deaths in Peru. Conclusions: ARIMA time series modeling are a powerful statistical tool that predict and forecast data that are widely used in various fields of science, health, and economics. In this study, we have shown the discrepancy between the data reported by MINSA and the projection obtained in our ARIMA time series modeling. Therefore, we have a confidence level of 95% about the study that was carried out in March and April of 2020.

Physicians’ Perceptions as Predictors of the Future Use of the National Death Information System in Peru: Cross-sectional Study

“…The usefulness that SINADEF has shown for mortality surveillance during the COVID-19 pandemic is another aspect that highlights the importance of contributing to its institutionalization. During the COVID-19 pandemic, SINADEF was used in several studies [10][11][12]27] as an important source of information to document excess mortality from all causes in Peru and was recognized as the most reliable way to measure the severity and the impact of COVID-19 on the population. With the support of SINADEF, an excess mortality of 371.9 per 100,000 inhabitants in 2020 was documented in Peru [28], and in general, all the researchers agreed in highlighting the importance of strengthening the mortality documentation system in Peru.…”

“…Furthermore, SINADEF has played a fundamental role in documenting the excess mortality that occurred during the COVID-19 pandemic in Peru. Several studies [10][11][12] used SINADEF to warn, from the beginning of the first wave of transmission of COVID-19 in Peru, a significant difference in deaths that the physicians who used SINADEF attributed to COVID-19 and that were not reported by the system of epidemiological surveillance. In addition, they coincide in pointing out the importance of the quality of the data provided by SINADEF and the need to strengthen the entire death registration process so that it is useful for containing the health emergency.…”