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Background The ongoing COVID-19 pandemic hit South America badly with multiple waves. Different COVID-19 variants have been storming across the region, leading to more severe infections and deaths even in places with high vaccination coverage. This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate (IFR), infection attack rate (IAR) and reproduction number ($${R}_{0}$$ R 0 ) for twelve most affected South American countries. Methods We fit a susceptible-exposed-infectious-recovered (SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities. Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World Health Organization, Johns Hopkins Coronavirus Resource Center and Our World in Data. We investigate the COVID-19 mortalities in these countries, which could represent the situation  for the overall South American region. We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR, IAR and $${R}_{0}$$ R 0 of COVID-19 for the South American countries. Results We simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR (varies between 0.303% and 0.723%), IAR (varies between 0.03 and 0.784) and $${R}_{0}$$ R 0 (varies between 0.7 and 2.5) for the 12 South American countries. We observe that the severity, dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous. Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America. Conclusions This study reveals possible reasons for the two waves of COVID-19 outbreaks in South America. We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human protective behavioral reaction to recent deaths. Thus, strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America. Graphical Abstract

It was reported that the Brazilian city, Manaus, likely exceeded the herd immunity threshold (presumably 60–70%) in November 2020 after the first wave of COVID-19, based on the serological data of a routine blood donor. However, a second wave started in November 2020, when an even higher magnitude of deaths hit the city. The arrival of the second wave coincided with the emergence of the Gamma (P.1) variant of SARS-CoV-2, with higher transmissibility, a younger age profile of cases, and a higher hospitalization rate. Prete et al. (2020 MedRxiv 21256644) found that 8 to 33 of 238 (3.4–13.9%) repeated blood donors likely were infected twice in Manaus between March 2020 and March 2021. It is unclear how this finding can be used to explain the second wave. We propose a simple model which allows reinfection to explain the two-wave pattern in Manaus. We find that the two waves with 30% and 40% infection attack rates, respectively, and a reinfection ratio at 3.4–13.9%, can explain the two waves well. We argue that the second wave was likely because the city had not exceeded the herd immunity level after the first wave. The reinfection likely played a weak role in causing the two waves.

Variants of Severe-Acute-Respiratory-Syndrome Coronavirus-2 (SARS-CoV-2) has caused tremendous impact globally. It has been widely reported that the Omicron (B.1.1.529) variant is less deadly than the Delta (B.1.617.2) variant, presumably due to immunity from vaccination and previous infection. When measuring the severity of a variant, Case-Fatality-Rate (CFR) is often estimated. The purpose of this work is to calculate the change in CFR of different variants over time from a large number of countries/regions since the start of the pandemic in 2020.

Background: The ongoing COVID-19 pandemic hit South America badly with two waves. Different COVID-19 variants have been storming across the region, leading to more severe infections and deaths even in places with high vaccination coverages.Methods: We use the start-of-the-art iterated filtering likelihood-based inference disease modelling framework. We modify the classical susceptible-exposed-infectious-recovered model with a time-varying transmission rate, and additional delayed class and vaccinations to reported COVID-19 deaths in 12 South American countries with the highest COVID-19 mortalities. Results: We yield biologically reasonable estimates for the infection fatality rate (IFR), the infection attack rate (IAR) and time-varying transmission rate. We observe that the severity, the dynamical patterns of the deaths and the time-varying transmission rates among the countries are highly heterogeneous. Further, our analysis of the model with vaccination highlights that increasing the vaccination rate could effectively suppress the pandemics in South America.Conclusion: This study reveals the possible mechanism behind the two waves of COVID-19 in South America. We observe reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions (NPIs) measures and human protective behavior reaction to recent deaths. Thus, strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America.