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The emergence of Variants of Concern (VOCs) of SARS-CoV-2 with increased transmissibility, immune evasion properties, and virulence poses a great challenge to public health. Despite unprecedented efforts to increase genomic surveillance, fundamental facts about the evolutionary origins of VOCs remain largely unknown. One major uncertainty is whether the VOCs evolved during transmission chains of many acute infections or during long-term infections within single individuals. We test the consistency of these two possible paths with the observed dynamics, focusing on the clustered emergence of the first three VOCs, Alpha, Beta, and Gamma, in late 2020, following a period of relative evolutionary stasis. We consider a range of possible fitness landscapes, in which the VOC phenotypes could be the result of single mutations, multiple mutations that each contribute additively to increasing viral fitness, or epistatic interactions among multiple mutations that do not individually increase viral fitness--a "fitness plateau". Our results suggest that the timing and dynamics of the VOC emergence, together with the observed number of mutations in VOC lineages, are in best agreement with the VOC phenotype requiring multiple mutations and VOCs having evolved within single individuals with long-term infections.
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Detailed reconstruction of the SARS-CoV-2 transmission dynamics and assessment of its burden in several parts of the world has still remained largely unknown due to the scarcity of epidemiological analyses and limited testing capacities of different countries to identify cases and deaths attributable to COVID-19 [1-4]. Understanding the true burden of the Iranian COVID-19 epidemic is subject to similar challenges with limited clinical and epidemiological studies at the subnational level [5-9]. To address this, we develop a new quantitative framework that enables us to fully reconstruct the transmission dynamics across the country and assess the level of under-reporting in infections and deaths using province-level, age-stratified all-cause mortality data. We show that excess mortality aligns with seroprevalence estimates in each province and subsequently estimate that as of 2021-10-22, only 48% (95% confidence interval: 43-55%) of COVID-19 deaths in Iran have been reported. We find that in the most affected provinces such as East Azerbaijan, Qazvin, and Qom approximately 0.4% of the population have died of COVID-19 so far. We also find significant heterogeneity in the estimated attack rates across the country with 11 provinces reaching close to or higher than 100% attack rates. Despite a relatively young age structure in Iran, our analysis reveals that the infection fatality rate in most provinces is comparable to high-income countries with a larger percentage of older adults, suggesting that limited access to medical services, coupled with undercounting of COVID-19-related deaths, can have a significant impact on accurate estimation of COVID-19 fatalities. Our estimation of high attack rates in provinces with largely unmitigated epidemics whereby, on average, between 10% to 25% individuals have been infected with COVID-19 at least twice over the course of 20 months also suggests that, despite several waves of infection, herd immunity through natural infection has not been achieved in the population.
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High throughput sequencing enables rapid genome sequencing during infectious disease outbreaks and provides an opportunity to quantify the evolutionary dynamics of pathogens in near real-time. One difficulty of undertaking evolutionary analyses over short timescales is the dependency of the inferred evolutionary parameters on the timespan of observation. Here, we characterise the molecular evolutionary dynamics of SARS-CoV-2 and 2009 pandemic H1N1 (pH1N1) influenza during the first 12 months of their respective pandemics. We use Bayesian phylogenetic methods to estimate the dates of emergence, evolutionary rates, and growth rates of SARS-CoV-2 and pH1N1 over time and investigate how varying sampling window and dataset sizes affects the accuracy of parameter estimation. We further use a generalised McDonald-Kreitman test to estimate the number of segregating non-neutral sites over time. We find that the inferred evolutionary parameters for both pandemics are time-dependent, and that the inferred rates of SARS-CoV-2 and pH1N1 decline by [~]50% and [~]100%, respectively, over the course of one year. After at least 4 months since the start of sequence sampling, inferred growth rates and emergence dates remain relatively stable and can be inferred reliably using a logistic growth coalescent model. We show that the time-dependency of the mean substitution rate is due to elevated substitution rates at terminal branches which are 2-4 times higher than those of internal branches for both viruses. The elevated rate at terminal branches is strongly correlated with an increasing number of segregating non-neutral sites, demonstrating the role of purifying selection in generating the time-dependency of evolutionary parameters during pandemics.
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BackgroundThe number of publicly reported deaths from COVID-19 may underestimate the true death toll from the epidemic as they rely on provisional data that are often incomplete or omit undocumented deaths from COVID-19. In addition, these reports may be subject to significant under-reporting due to a limited testing capacity of a country to identify suspect cases. This study estimated the number of seasonal excess deaths attributable to the COVID-19 epidemic in 31 provinces of Iran. MethodsWe gathered the nationwide and provincial time series of the seasonal all-cause mortality data from spring 2015 to summer 2020 (21 March 2015 to 21 September 2020), in accordance with the Solar Hijri (SH) calendar, from the National Organization for Civil Registration (NOCR). We estimated the expected number of seasonal deaths for each province using a piecewise linear regression model which we established based on the mortality figures for the previous years and considered any significant deviations from the expectation during winter, spring, and summer of 2020 to be directly associated with COVID-19. ResultsOur analysis shows that from the start of winter to the end of summer (from 22 December 2019 to 21 September 2020), there were a total of 58.9K (95%CI: 46.9K - 69.5K) excess deaths across all 31 provinces with 27% (95%CI: 20% - 34%) estimated nationwide exposure to SARS-CoV-2. In particular, 2 provinces in the central and northern Iran, namely Qom and Golestan, had the highest level of exposure with 57% (95%CI: 44% - 69%) and 56% (95%CI: 44% - 69%), respectively, while another 27 provinces had significant levels of excess mortality in at least one season with >20% population-level exposure to the virus. We also detected unexpectedly high levels of excess mortality during fall 2019 (from 23 September to 21 December 2019) across 18 provinces. Our findings suggest that this spike cannot be a result of an early cryptic transmission of COVID-19 across the country and is also inconsistent with the molecular phylogenetics estimates for the start of the pandemic and its arrival to Iran. However, in the absence of appropriate surveillance data for detecting severe acute respiratory infections we were unable to make a determination as to what caused the spike in fall 2019. Conflict of InterestNone.
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BackgroundSevere COVID-19 pneumonia has been associated with the development of intense inflammatory responses during the course of infections with SARS-CoV-2. Given that Human Endogenous Retroviruses (HERVs) are known to be activated during and participate in inflammatory processes, we examined whether HERV dysregulation signatures are present in COVID-19 patients. ResultsBy comparing transcriptomes of Peripheral Blood Monocytes (PBMCs) and Bronchoalveolar Lavage Fluid (BALF) from patients and normal controls we have shown that HERVs are intensely dysregulated in BALF, but not in PBMCs. In particular, upregulation in the expression of multiple HERV families was detected in BALF samples of COVID-19 patients, with HERV-W being the most highly upregulated family among the families analysed. In addition, we compared the expression of HERVs in Human Bronchial Epithelial Cells (HBECs) without and after senescence induction in an oncogene-induced senescence model, in order to quantitatively measure changes in the expression of HERVs in bronchial cells during the processes of cellular senescence. ConclusionsThis apparent difference of HERV dysregulation between PBMCs and BALF warrants further studies in involvement of HERVs in inflammatory pathogenetic mechanisms as well as exploration of HERVs as potential biomarkers for disease progression. Furthermore, the increase in the expression of HERVs in senescent HBECs in comparison to non-induced HBECs provides a potential link for increased COVID-19 severity and mortality in aged populations.
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Many countries with an early outbreak of SARS-CoV-2 struggled to gauge the size and start date of the epidemic mainly due to limited testing capacities and a large proportion of undetected asymptomatic and mild infections. Iran was among the first countries with a major outbreak outside China. Using all genomic sequences collected from patients with a travel link to Iran, we estimate that the epidemic started on 21/01/2020 (95% HPD: 05/12/2019 - 14/02/2020) with a doubling time of 3 days (95% HPD: 1.68 - 16.27). We also show, using air travel data from confirmed exported cases, that from late February to early March the number of active cases across the country were more than a hundred times higher than the reported cases at the time. A detailed province-level analysis of all-cause mortality shows 20,718 (CI 95%: 18,859 - 22,576) excess deaths during winter and spring 2020 compared to previous years, almost twice the number of reported COVID-19-related deaths at the time. Correcting for under-reporting of prevalence and deaths, we use an SEIR model to reconstruct the outbreak dynamics in Iran. Our model forecasted the second epidemic peak and suggests that by 14/07/2020 a total of 9M (CI 95%: 118K - 44M) have recovered from the disease across the country. These findings have profound implications for assessing the stage of the epidemic in Iran and shed light on the dynamics of SARS-CoV-2 transmissions in Iran and central Asia despite significant levels of under-reporting. One Sentence SummaryWe use epidemiological and genetic data to investigate the origins of the SARS-CoV-2 outbreak in Iran and assess the degree of under-reporting in prevalence and deaths.
