SARS-CoV-2 Lambda and Gamma variants competition in Peru, a country with high seroprevalence

Detection of SARS-CoV-2 variants in hospital wastewater in Peru, 2022

OBJECTIVE.

To identify the presence of the SARS-CoV-2 virus in wastewater from hospitals in Peru.

MATERIALS AND METHODS.

Water samples were collected from the effluents of nine hospitals in Peru during March and September 2022. SARS-CoV-2 was identified by using Illumina sequencing. Variant, lineage and clade assignments were carried out using the Illumina and Nextclado tools. We verified whether the SARS-CoV-2 variants obtained from wastewater were similar to those reported by the National Institute of Health of Peru from patients during the same period and region.

RESULTS.

Eighteen of the 20 hospital wastewater samples (90%) provided sequences of sufficient quality to be classified as the Omicron variant according to the WHO classification. Among them, six (30%) were assigned by Nextclade to clades 21K lineage BA.1.1 (n=1), 21L lineage BA.2 (n=2), and 22B lineages BA.5.1 (n=2) and BA .5.5 (n=1).

CONCLUSIONS.

SARS-CoV-2 variants were found in hospital wastewater samples and were similar to those reported by the surveillance system in patients during the same weeks and geographic areas. Wastewater monitoring could provide information on the environmental and temporal variation of viruses such as SARS-CoV-2.

Motivation for the study. To contribute to the surveillance of environmental samples from hospital effluents in order to achieve early warning of possible infectious disease outbreaks. Main findings. The Omicron variant of the COVID-19 virus was detected in wastewater from hospitals in Puno, Cuzco and Cajamarca; these results are similar to the reports by the Peruvian National Institute of Health based on nasopharyngeal swab samples. Implications. The presence of the Omicron variant in hospital wastewater during the third wave of the pandemic should raise awareness of the treatment system before wastewater is discharged into the public sewer system.

Dispersion of SARS-CoV-2 lineage BA.5.1.25 and its descendants in Peru during two COVID-19 waves in 2022

During the third year of the pandemic in Peru, the persistent transmission of SARS-CoV-2 led to the appearance of more transmissible and immune-evasive Omicron sublineages; in that context, the National Genomic Surveillance of SARS-CoV-2 performed by the Peruvian National Institute of Health detected spike mutations in the circulating Omicron BA.5.1.25 sublineage which was later designated as DJ.1 and increased during the fourth COVID-19 wave, this eventually branched into new sublineages. The introduction, emergence, and timing of the most recent common ancestor (tMRCA) of BA.5.1.25 and its descendants (DJ.1, DJ.1.1, DJ.1.2, and DJ.1.3) were investigated in this paper as well as the time lags between their emergence and identification by the Peruvian National Institute of Health. Our findings show that ongoing genomic surveillance of SARS-CoV-2 is critical for understanding its phylogenetic evolution and the emergence of novel variations.

Reproduction number projection for the COVID-19 pandemic

The recently derived Hybrid-Incidence Susceptible-Transmissible-Removed (HI-STR) prototype is a deterministic compartment model for epidemics and an alternative to the Susceptible-Infected-Removed (SIR) model. The HI-STR predicts that pathogen transmission depends on host population characteristics including population size, population density and social behaviour common within that population.

The HI-STR prototype is applied to the ancestral Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) to show that the original estimates of the Coronavirus Disease 2019 (COVID-19) basic reproduction number $\mathcal{R}_{0}$ R 0 for the United Kingdom (UK) could have been projected onto the individual states of the United States of America (USA) prior to being detected in the USA.

The Imperial College London (ICL) group’s estimate of $\mathcal{R}_{0}$ R 0 for the UK is projected onto each USA state. The difference between these projections and the ICL’s estimates for USA states is either not statistically significant on the paired Student t-test or not epidemiologically significant.

The SARS-CoV2 Delta variant’s $\mathcal{R}_{0}$ R 0 is also projected from the UK to the USA to prove that projection can be applied to a Variant of Concern (VOC). Projection provides both a localised baseline for evaluating the implementation of an intervention policy and a mechanism for anticipating the impact of a VOC before local manifestation.

Regional clustering and waves patterns due to COVID-19 by the index virus and the lambda/gamma, and delta/omicron SARS-CoV-2 variants in Peru

Background

Coronavirus disease 2019 (COVID-19) impact varies substantially due to various factors, so it is critical to characterize its main differences to inform decision-makers about where to focus their interventions and differentiate mitigation strategies. Up to this date, little is known about the patterns and regional clustering of COVID-19 waves worldwide.

Methods

We assessed the patterns and regional clustering of COVID-19 waves in Peru by using the weekly mortality rates for each of the 25 regions as an outcome of interest. We obtained the death counts from the National Informatics System of Deaths and population estimates from the National Registry of Identification and Civil Status. In addition, we characterized each wave according to its duration, peak, and mortality rates by age group and gender. Additionally, we used polynomial regression models to compare them graphically and performed a cluster analysis to identify regional patterns.

Results

We estimated the average mortality rate at the first, second, and third waves at 13.01, 14.12, and 9.82 per 100,000 inhabitants, respectively, with higher mortality rates among elders and men. The patterns of each wave varied substantially in terms of duration, peak, impact, and wave shapes. Based on our clustering analysis, during the first wave caused by the index virus, the 25 regions of Peru presented six different wave patterns. However, the regions were clustered in two different wave patterns during the second and third, caused by alpha/lambda/delta and omicron.

Conclusions

The propagation of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) variants behaved in Peru with varying wave patterns and regional clustering. During the COVID-19 pandemic, the weekly mortality rates followed different spatiotemporal patterns with solid clustering, which might help project the impact of future waves of COVID-19.

Prevalence of SARS-CoV-2 Variants and Disease Outcome of COVID-19 Patients in the Amazonas Region of Peru

Peru was severely affected by COVID-19 with a fatality rate that reached up to 6%. In this study, the relationship between SARS-CoV-2 variants and COVID-19 disease outcome in Amazonas, a region of northeastern Peru, was evaluated. The variants were determined by genomic sequencing, and clinical-epidemiological data were collected from 590 patients between April 2021 and February 2022. There was no association between mortality and hospitalization with any of the variants, but we did find that Omicron is more likely to infect vaccinated and nonvaccinated people. A significant association was also found between unvaccinated patients and hospitalization. Interestingly, in the indigenous population, there were fewer hospitalizations than in the general population. In conclusion, SARS-CoV-2 variants were not associated with the disease outcome in the Amazonas region, and indigenous population were found to be less vulnerable to severe COVID-19 illness.

Phylodynamic of SARS-CoV-2 during the second wave of COVID-19 in Peru

At over 0.6% of the population, Peru has one of the highest SARS-CoV-2 mortality rate in the world. Much effort to sequence genomes has been done in this country since mid-2020. However, an adequate analysis of the dynamics of the variants of concern and interest (VOCIs) is missing. We investigated the dynamics of the COVID-19 pandemic in Peru with a focus on the second wave, which had the greatest case fatality rate. The second wave in Peru was dominated by Lambda and Gamma. Analysis of the origin of Lambda shows that it most likely emerged in Peru before the second wave (June-November, 2020). After its emergence it reached Argentina and Chile from Peru where it was locally transmitted. During the second wave in Peru, we identify the coexistence of two Lambda and three Gamma sublineages. Lambda sublineages emerged in the center of Peru whereas the Gamma sublineages more likely originated in the north-east and mid-east. Importantly, it is observed that the center of Peru played a prominent role in transmitting SARS-CoV-2 to other regions within Peru.

Resolving the enigma of Iquitos and Manaus: A modeling analysis of multiple COVID-19 epidemic waves in two Amazonian cities

The two nearby Amazonian cities of Iquitos and Manaus endured explosive COVID-19 epidemics and may well have suffered the world's highest infection and death rates over 2020, the first year of the pandemic. State-of-the-art epidemiological and modeling studies estimated that the populations of both cities came close to attaining herd immunity (>70% infected) at the termination of the first wave and were thus protected. This makes it difficult to explain the more deadly second wave of COVID-19 that struck again in Manaus just months later, simultaneous with the appearance of a new P.1 variant of concern, creating a catastrophe for the unprepared population. It was suggested that the second wave was driven by reinfections, but the episode has become controversial and an enigma in the history of the pandemic. We present a data-driven model of epidemic dynamics in Iquitos, which we also use to explain and model events in Manaus. By reverse engineering the multiple epidemic waves over 2 y in these two cities, the partially observed Markov process model inferred that the first wave left Manaus with a highly susceptible and vulnerable population (≈40% infected) open to invasion by P.1, in contrast to Iquitos (≈72% infected). The model reconstructed the full epidemic outbreak dynamics from mortality data by fitting a flexible time-varying reproductive number [Formula: see text] while estimating reinfection and impulsive immune evasion. The approach is currently highly relevant given the lack of tools available to assess these factors as new SARS-CoV-2 virus variants appear with different degrees of immune evasion.

Evidence of natural selection and dominance of SARS-CoV-2 variant Lambda (C.37) over variants of concern in Cusco, Peru

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage C.37 (Lambda) has spread rapidly in Peru and other Latin American countries. However, most studies in Peru have focused on Lima, the capital city, without knowing the dynamics of the spread of the variant in other departments. Cusco, Peru, is one of the most popular departments in the country for tourists, so the introduction of new variants of SARS-CoV-2 might occur despite closure of the borders. Therefore, in this work, we analyzed the variants circulating in Cusco. The aim of this work was to better understand the distribution of SARS-CoV-2 lineages circulating in Cusco and to characterize the genomes of these strains. To this end, 46 SARS-CoV-2 genomes from vaccinated and unvaccinated patients were sequenced in the first half of 2021. The genomes were analyzed using phylogenetic and natural selection methods. Phylogenetic trees from Cusco showed dominance of the Lambda lineage over the variants of concern (VOCs), and there was no clustering of variants by district. Natural selection analysis revealed mutations, mainly in the spike protein, at positions 75, 246, 247, 707, 769, and 1020. In addition, we found that unvaccinated patients accumulated more new mutations than did vaccinated patients, and these included the F101Y mutation in ORF7a, E419A in NSP3, a deletion in S (21,618-22,501), and a deletion in ORF3a (25,437-26,122).

Risk of death, hospitalization and intensive care unit admission by SARS-CoV-2 variants in Peru: a retrospective study

OBJECTIVES

Peru has had the highest death toll from the pandemic worldwide; however, it is not clear what the effects of the different variants on these outcomes are. The study aimed to evaluate the risk of death, hospitalization, and intensive care unit (ICU) admission rates of COVID-19 according to the SARS-CoV-2 variants detected in Peru from March 2020-February 2022.

METHODS

Retrospective study using open-access databases were published by the Peruvian Ministry of Health. Databases of genomic sequencing, death, COVID-19 cases, hospitalization and ICU, and vaccination were used. Crude and adjusted Cox proportional hazards regressions with clustered variances were modeled to calculate the hazard ratio (HR) of outcomes by variant.

RESULTS

Lambda variant had the highest risk of death (HR 1.92, 95% CI 1.37-2.68), whereas the Delta variant had the lowest risk (HR 0.50, 95% CI 0.31-0.82). Mu variant had the highest risk of hospitalization (HR: 2.39, 95% CI 1.56-3.67), Omicron the lowest (HR 0.45, 95%CI 0.23-0.90), and Gamma had the highest ICU admission rate (HR 1.95, 95%CI 1.40-2.71).

CONCLUSION

SARS-CoV-2 variants showed distinctive risks of clinical outcomes, which could have implications for the management of infected persons during the pandemic.

Overview of the SARS-CoV-2 genotypes circulating in Latin America during 2021

Latin America is one of the regions in which the COVID-19 pandemic has a stronger impact, with more than 72 million reported infections and 1.6 million deaths until June 2022. Since this region is ecologically diverse and is affected by enormous social inequalities, efforts to identify genomic patterns of the circulating SARS-CoV-2 genotypes are necessary for the suitable management of the pandemic. To contribute to the genomic surveillance of the SARS-CoV-2 in Latin America, we extended the number of SARS-CoV-2 genomes available from the region by sequencing and analyzing the viral genome from COVID-19 patients from seven countries (Argentina, Brazil, Costa Rica, Colombia, Mexico, Bolivia, and Peru). Subsequently, we analyzed the genomes circulating mainly during 2021 including records from GISAID database from Latin America. A total of 1,534 genome sequences were generated from seven countries, demonstrating the laboratory and bioinformatics capabilities for genomic surveillance of pathogens that have been developed locally. For Latin America, patterns regarding several variants associated with multiple re-introductions, a relatively low percentage of sequenced samples, as well as an increment in the mutation frequency since the beginning of the pandemic, are in line with worldwide data. Besides, some variants of concern (VOC) and variants of interest (VOI) such as Gamma, Mu and Lambda, and at least 83 other lineages have predominated locally with a country-specific enrichments. This work has contributed to the understanding of the dynamics of the pandemic in Latin America as part of the local and international efforts to achieve timely genomic surveillance of SARS-CoV-2.

Spatiotemporal Surveillance of SARS-CoV-2 in the Sewage of Three Major Urban Areas in Peru: Generating Valuable Data Where Clinical Testing Is Extremely Limited

Peru has been severely affected by the COVID-19 pandemic. By January 2022, Peru had surpassed 200 000 COVID-19 deaths, constituting the highest death rate per capita worldwide. Peru has had several limitations during the pandemic: insufficient testing access, limited contact tracing, a strained medical infrastructure, and many economic hurdles. These limitations hindered the gathering of accurate information about infected individuals with spatial resolution in real time, a critical aspect of effectively controlling the pandemic. Wastewater monitoring for SARS-CoV-2 RNA offered a promising alternative for providing needed population-wide information to complement health care indicators. In this study, we demonstrate the feasibility and value of implementing a decentralized SARS-CoV-2 RNA wastewater monitoring system to assess the spatiotemporal distribution of COVID-19 in three major cities in Peru: Lima, Callao, and Arequipa. Our data on viral loads showed the same trends as health indicators such as incidence and mortality. Furthermore, we were able to identify hot spots of contagion within the surveyed urban areas to guide the efforts of health authorities. Viral decay in the sewage network of the cities studied was found to be negligible (<2%). Overall, our results support wastewater monitoring for SARS-CoV-2 as a valuable and cost-effective tool for monitoring the COVID-19 pandemic in the Peruvian context.

SARS-CoV-2 variants: Impact on biological and clinical outcome

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that was first identified in December 2019, in Wuhan, China was found to be the etiological agent for a novel respiratory infection that led to a Coronavirus Induced Disease named COVID-19. The disease spread to pandemic magnitudes within a few weeks and since then we have been dealing with several waves across the world, due to the emergence of variants and novel mutations in this RNA virus. A direct outcome of these variants apart from the spike of cases is the diverse disease presentation and difficulty in employing effective diagnostic tools apart from confusing disease outcomes. Transmissibility rates of the variants, host response, and virus evolution are some of the features found to impact COVID-19 disease management. In this review, we will discuss the emerging variants of SARS-CoV-2, notable mutations in the viral genome, the possible impact of these mutations on detection, disease presentation, and management as well as the recent findings in the mechanisms that underlie virus-host interaction. Our aim is to invigorate a scientific debate on how pathogenic potential of the new pandemic viral strains contributes toward development in the field of virology in general and COVID-19 disease in particular.

Dissecting Naturally Arising Amino Acid Substitutions at Position L452 of SARS-CoV-2 Spike

Mutations at spike protein L452 are recurrently observed in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC), including omicron lineages. It remains elusive how amino acid substitutions at L452 are selected in VOC. Here, we characterized all 19 possible mutations at this site and revealed that five mutants expressing the amino acids Q, K, H, M, and R gained greater fusogenicity and pseudovirus infectivity, whereas other mutants failed to maintain steady-state expression levels and/or pseudovirus infectivity. Moreover, the five mutants showed decreased sensitivity toward neutralization by vaccine-induced antisera and conferred escape from T cell recognition. Contrary to expectations, sequence data retrieved from the Global Initiative on Sharing All Influenza Data (GISAID) revealed that the naturally occurring L452 mutations were limited to Q, M, and R, all of which can arise from a single nucleotide change. Collectively, these findings highlight that the codon base change mutational barrier is a prerequisite for amino acid substitutions at L452, in addition to the phenotypic advantages of viral fitness and decreased sensitivity to host immunity. IMPORTANCE In a span of less than 3 years since the declaration of the coronavirus pandemic, numerous SARS-CoV-2 variants of concern have emerged all around the globe, fueling a surge in the number of cases and deaths that caused severe strain on the health care system. A major concern is whether viral evolution eventually promotes greater fitness advantages, transmissibility, and immune escape. In this study, we addressed the differential effect of amino acid substitutions at a frequent mutation site, L452 of SARS-CoV-2 spike, on viral antigenic and immunological profiles and demonstrated how the virus evolves to select one amino acid over the others to ensure better viral infectivity and immune evasion. Identifying such virus mutation signatures could be crucial for the preparedness of future interventions to control COVID-19.

Regional clustering and waves patterns due to COVID-19 by the index virus and the lambda/gamma, and delta/omicron SARS-CoV-2 variants in Peru

Background: Coronavirus disease 2019 (COVID-19) impact varies substantially due to various factors, so it is critical to characterize its main differences to inform decision-makers about where to focus their interventions and differentiate mitigation strategies. Up to this date, little is known about the patterns and regional clustering of COVID-19 waves worldwide.  Methods: We assessed the patterns and regional clustering of COVID-19 waves in Peru by using the weekly mortality rates for each of the 25 regions as an outcome of interest. We obtained the death counts from the National Informatics System of Deaths and population estimates from the National Registry of Identification and Civil Status. In addition, we characterized each wave according to its duration, peak, and mortality rates by age group and gender. Additionally, we used polynomial regression models to compare them graphically and performed a cluster analysis to identify regional patterns.  Results: We estimated the average mortality rate at the first, second, and third wave at 13.01, 14.12, and 9.82 per 100,000 inhabitants, respectively, with higher mortality rates among elders and men. The patterns of each wave varied substantially in terms of duration, peak, impact, and wave shapes. Based on our clustering analysis, during the first wave caused by the index virus, the 25 regions of Peru presented six different wave patterns. However, the regions were clustered in two different wave patterns during the second and third, caused by alpha/lambda/delta and omicron.  Conclusions: The propagation of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) variants behaved in Peru with varying wave patterns and regional clustering. During the COVID-19 pandemic, the weekly mortality rates followed different spatiotemporal patterns with solid clustering, which might help project the impact of future waves of COVID-19.

The Influence of SARS-CoV-2 Variants on National Case-Fatality Rates: Correlation and Validation Study

Background

In 2021, new variants of the SARS-CoV-2 virus appeared with increased transmissibility and virulence as compared with the original wild variant. The first variants of concern (VoCs), Alpha (B1.1.7) and Gamma (P.1), first appeared in the United Kingdom and Brazil, respectively. The Delta (B.1.617.2) variant, seen in India in October 2020, dominated COVID-19 infections across all regions through the second half of 2021.

Objective

This research explores the degree to which SARS-CoV-2 VoCs generate waves of fluctuations in case-fatality rates (CFRs) across countries in several regions, increase the risk of mortality to persons with certain comorbidities, and decrease the risk of mortality as the percentage of fully vaccinated populations increases.

Methods

This analysis introduces a measure of the temporal dynamics of COVID-19 infections in the form of a proxy CFR (pCFR), which can be compared among countries. It uses economic and demographic data reported by the World Bank and International Monetary Fund, plus publicly available epidemiological and medical statistics reported to the relevant national and international public health authorities. From these ecological data, pandemic average and daily COVID-19 CFRs and their correlations with potential cofactors were computed for 2021, a year dominated by the spread of World Health Organization-designated VoCs. The study does not investigate disease pathology; rather, it compares the daily case rates and pCFRs to reveal underlying contributing factors that vary from country to country and region to region.

Results

The in-depth global regression analysis of cofactors found that the strongest single correlation with COVID-19 fatality was 0.36 (SD 0.02) with P<.001 for chronic kidney disease. No other single physiological cofactors display positive correlations exceeding 0.26 (SD 0.26), with P=.008 (asthma) and P=.01 (coronary disease). The study confirms that the pCFR is a valuable metric for tracking waves of infection due to different VoCs within countries.

Conclusions

The influence of social, economic, and medical cofactors on the CFR due to VoCs remains qualitatively similar, albeit strengthened, to the levels found for the wild strain. The strong regional variations of the influence of all cofactors observed for the wild strain persists in infections for all VoCs with very strong correlation coefficients seen in the Middle East for asthma (0.76), coronary heart disease (0.60), lung disease (0.70), and chronic kidney disease (0.52). Strong regional variations emphasize the influence on COVID-19 mortality due to regional differences in national economics, patterns of health care policies, and variations in cultural practices and environment. The pCFR-based analysis reveals clear patterns of the spread of VoCs across regions, but there is little evidence for the spread of the Lambda and Mu (B.1.621) variants of interest outside of South America.

Safety & effectiveness of COVID-19 vaccines: A narrative review

There are currently eight vaccines against SARS-CoV-2 that have received Emergency Use Authorization by the WHO that can offer some protection to the world's population during the COVID-19 pandemic. Though research is being published all over the world, public health officials, policymakers and governments are collecting evidence-based information to establish the public health policies. Unfortunately, continued international travel, violations of lockdowns and social distancing, the lack of mask use, the emergence of mutant strains of the virus and lower adherence by a sector of the global population that remains sceptical of the protection offered by vaccines, or about any risks associated with vaccines, hamper these efforts. Here we examine the literature on the efficacy, effectiveness and safety of COVID-19 vaccines, with an emphasis on select categories of individuals and against new SARS-CoV-2 strains. The literature shows that these eight vaccines are highly effective in protecting the population from severe disease and death, but there are some issues concerning safety and adverse effects. Further, booster shots and variant-specific vaccines would also be required.