Ecological and evolutionary dynamics of cell-virus-virophage systems.

Microbial eukaryotes, giant viruses and virophages form a unique hyperparasitic system. Virophages are parasites of the virus transcription machinery and can interfere with virus replication, resulting in a benefit to the eukaryotic host population. Surprisingly, virophages can integrate into the genomes of their cell or virus hosts, and have been shown to reactivate during coinfection. This raises questions about the role of integration in the dynamics of cell-virus-virophage systems. We use mathematical models and computational simulations to understand the effect of virophage integration on populations of cells and viruses. We also investigate multicellularity and programmed cell-death (PCD) as potential antiviral defence strategies used by cells. We found that virophages which enter the cell independently of the host virus, such as Mavirus, are expected to integrate commonly into the genomes of their cell hosts. Our models suggest that integrations from virophages without an independent mode of entry like Sputnik, are less likely to become fixed in the cell host population. Alternatively, we found that Sputnik virophages can stably persist integrated in the virus population, as long as they do not completely inhibit virus replication. We also show that increasing virophage inhibition can stabilise oscillatory dynamics, which may explain the long-term persistence of viruses and virophages in the environment. Our results demonstrate that inhibition by virophages and multicellularity are effective antiviral strategies that may act in synergy against viral infection in microbial species.

Revisiting the origins of the Sobemovirus genus: A case for ancient origins of plant viruses.

The discrepancy between short- and long-term rate estimates, known as the time-dependent rate phenomenon (TDRP), poses a challenge to extrapolating evolutionary rates over time and reconstructing evolutionary history of viruses. The TDRP reveals a decline in evolutionary rate estimates with the measurement timescale, explained empirically by a power-law rate decay, notably observed in animal and human viruses. A mechanistic evolutionary model, the Prisoner of War (PoW) model, has been proposed to address TDRP in viruses. Although TDRP has been studied in animal viruses, its impact on plant virus evolutionary history remains largely unexplored. Here, we investigated the consequences of TDRP in plant viruses by applying the PoW model to reconstruct the evolutionary history of sobemoviruses, plant pathogens with significant importance due to their impact on agriculture and plant health. Our analysis showed that the Sobemovirus genus dates back over four million years, indicating an ancient origin. We found evidence that supports deep host jumps to Poaceae, Fabaceae, and Solanaceae occurring between tens to hundreds of thousand years ago, followed by specialization. Remarkably, the TDRP-corrected evolutionary history of sobemoviruses was extended far beyond previous estimates that had suggested their emergence nearly 9,000 years ago, a time coinciding with the Neolithic period in the Near East. By incorporating sequences collected through metagenomic analyses, the resulting phylogenetic tree showcases increased genetic diversity, reflecting a deep history of sobemovirus species. We identified major radiation events beginning between 4,600 to 2,000 years ago, which aligns with the Neolithic period in various regions, suggesting a period of rapid diversification from then to the present. Our findings make a case for the possibility of deep evolutionary origins of plant viruses.

Insights into SARS-CoV-2 in Angola during the COVID-19 peak: Molecular epidemiology and genome surveillance.

Background: In Angola, COVID-19 cases have been reported in all provinces, resulting in >105,000 cases and >1900 deaths. However, no detailed genomic surveillance into the introduction and spread of the SARS-CoV-2 virus has been conducted in Angola. We aimed to investigate the emergence and epidemic progression during the peak of the COVID-19 pandemic in Angola. Methods: We generated 1210 whole-genome SARS-CoV-2 sequences, contributing West African data to the global context, that were phylogenetically compared against global strains. Virus movement events were inferred using ancestral state reconstruction. Results: The epidemic in Angola was marked by four distinct waves of infection, dominated by 12 virus lineages, including VOCs, VOIs, and the VUM C.16, which was unique to South-Western Africa and circulated for an extended period within the region. Virus exchanges occurred between Angola and its neighboring countries, and strong links with Brazil and Portugal reflected the historical and cultural ties shared between these countries. The first case likely originated from southern Africa. Conclusion: A lack of a robust genome surveillance network and strong dependence on out-of-country sequencing limit real-time data generation to achieve timely disease outbreak responses, which remains of the utmost importance to mitigate future disease outbreaks in Angola.

The recency and geographical origins of the bat viruses ancestral to SARS-CoV and SARS-CoV-2.

The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 has led to increased sampling of related sarbecoviruses circulating primarily in horseshoe bats. These viruses undergo frequent recombination and exhibit spatial structuring across Asia. Employing recombination-aware phylogenetic inference on bat sarbecoviruses, we find that the closest-inferred bat virus ancestors of SARS-CoV and SARS-CoV-2 existed just ~1-3 years prior to their emergence in humans. Phylogeographic analyses examining the movement of related sarbecoviruses demonstrate that they traveled at similar rates to their horseshoe bat hosts and have been circulating for thousands of years in Asia. The closest-inferred bat virus ancestor of SARS-CoV likely circulated in western China, and that of SARS-CoV-2 likely circulated in a region comprising southwest China and northern Laos, both a substantial distance from where they emerged. This distance and recency indicate that the direct ancestors of SARS-CoV and SARS-CoV-2 could not have reached their respective sites of emergence via the bat reservoir alone. Our recombination-aware dating and phylogeographic analyses reveal a more accurate inference of evolutionary history than performing only whole-genome or single gene analyses. These results can guide future sampling efforts and demonstrate that viral genomic fragments extremely closely related to SARS-CoV and SARS-CoV-2 were circulating in horseshoe bats, confirming their importance as the reservoir species for SARS viruses.

A billion years arms-race between viruses, virophages, and eukaryotes.

Bamfordviruses are arguably the most diverse group of viruses infecting eukaryotes. They include the Nucleocytoplasmic Large DNA viruses (NCLDVs), virophages, adenoviruses, Mavericks and Polinton-like viruses. Two main hypotheses for their origins have been proposed: the 'nuclear-escape' and 'virophage-first' hypotheses. The nuclear-escape hypothesis proposes an endogenous, Maverick-like ancestor which escaped from the nucleus and gave rise to adenoviruses and NCLDVs. In contrast, the virophage-first hypothesis proposes that NCLDVs coevolved with protovirophages; Mavericks then evolved from virophages that became endogenous, with adenoviruses escaping from the nucleus at a later stage. Here, we test the predictions made by both models and consider alternative evolutionary scenarios. We use a data set of the four core virion proteins sampled across the diversity of the lineage, together with Bayesian and maximum-likelihood hypothesis-testing methods, and estimate rooted phylogenies. We find strong evidence that adenoviruses and NCLDVs are not sister groups, and that Mavericks and Mavirus acquired the rve-integrase independently. We also found strong support for a monophyletic group of virophages (family Lavidaviridae) and a most likely root placed between virophages and the other lineages. Our observations support alternatives to the nuclear-escape scenario and a billion years evolutionary arms-race between virophages and NCLDVs.

The evolution of SARS-CoV-2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths and substantial morbidity worldwide. Intense scientific effort to understand the biology of SARS-CoV-2 has resulted in daunting numbers of genomic sequences. We witnessed evolutionary events that could mostly be inferred indirectly before, such as the emergence of variants with distinct phenotypes, for example transmissibility, severity and immune evasion. This Review explores the mechanisms that generate genetic variation in SARS-CoV-2, underlying the within-host and population-level processes that underpin these events. We examine the selective forces that likely drove the evolution of higher transmissibility and, in some cases, higher severity during the first year of the pandemic and the role of antigenic evolution during the second and third years, together with the implications of immune escape and reinfections, and the increasing evidence for and potential relevance of recombination. In order to understand how major lineages, such as variants of concern (VOCs), are generated, we contrast the evidence for the chronic infection model underlying the emergence of VOCs with the possibility of an animal reservoir playing a role in SARS-CoV-2 evolution, and conclude that the former is more likely. We evaluate uncertainties and outline scenarios for the possible future evolutionary trajectories of SARS-CoV-2.

Four principles to establish a universal virus taxonomy.

A universal taxonomy of viruses is essential for a comprehensive view of the virus world and for communicating the complicated evolutionary relationships among viruses. However, there are major differences in the conceptualisation and approaches to virus classification and nomenclature among virologists, clinicians, agronomists, and other interested parties. Here, we provide recommendations to guide the construction of a coherent and comprehensive virus taxonomy, based on expert scientific consensus. Firstly, assignments of viruses should be congruent with the best attainable reconstruction of their evolutionary histories, i.e., taxa should be monophyletic. This fundamental principle for classification of viruses is currently included in the International Committee on Taxonomy of Viruses (ICTV) code only for the rank of species. Secondly, phenotypic and ecological properties of viruses may inform, but not override, evolutionary relatedness in the placement of ranks. Thirdly, alternative classifications that consider phenotypic attributes, such as being vector-borne (e.g., "arboviruses"), infecting a certain type of host (e.g., "mycoviruses," "bacteriophages") or displaying specific pathogenicity (e.g., "human immunodeficiency viruses"), may serve important clinical and regulatory purposes but often create polyphyletic categories that do not reflect evolutionary relationships. Nevertheless, such classifications ought to be maintained if they serve the needs of specific communities or play a practical clinical or regulatory role. However, they should not be considered or called taxonomies. Finally, while an evolution-based framework enables viruses discovered by metagenomics to be incorporated into the ICTV taxonomy, there are essential requirements for quality control of the sequence data used for these assignments. Combined, these four principles will enable future development and expansion of virus taxonomy as the true evolutionary diversity of viruses becomes apparent.

Discovery of novel papillomaviruses in the critically endangered Malayan and Chinese pangolins.

Pangolins are scaly and toothless mammals which are distributed across Africa and Asia. Currently, the Malayan, Chinese and Philippine pangolins are designated as critically endangered species. Although few pangolin viruses have been described, their viromes have received more attention following the discovery that they harbour sarbecoviruses related to SARS-CoV-2. Using large-scale genome mining, we discovered novel lineages of papillomaviruses infecting the Malayan and Chinese pangolins. We were able to assemble three complete circular papillomavirus genomes with an intact coding capacity and five additional L1 genes encoding the major capsid protein. Phylogenetic analysis revealed that seven out of eight L1 sequences formed a monophyletic group which is the sister lineage to the Tupaia belangeri papillomavirus 1, isolated from Yunnan province in China. Additionally, a single L1 sequence assembled from a Chinese pangolin was placed in a clade closer to Alphapapillomavirus and Omegapapillomavirus. Examination of the SRA data from 95 re-sequenced genomes revealed that 49.3% of Malayan pangolins and 50% of Chinese pangolins were positive for papillomavirus reads. Our results indicate that pangolins in South-East Asia are the hosts of diverse and highly prevalent papillomaviruses, and highlight the value of in silico mining of host sequencing data for the discovery of novel viruses.

Evolutionary Analysis of Placental Orthologues Reveals Two Ancient DNA Virus Integrations.

The genomes of eukaryotes preserve a vast diversity of ancient viruses in the form of endogenous viral elements (EVEs). Study of this genomic fossil record provides insights into the diversity, origin, and evolution of viruses across geological timescales. In particular, Mavericks have emerged as one of the oldest groups of endogenous viruses infecting vertebrates (≥419 million years [My]). They have been found in the genomes of fish, amphibians, birds, and nonavian reptiles but had been overlooked in mammals. Thus, their evolutionary history and the causes of their demise in mammals remain puzzling questions. Here, we conducted a detailed evolutionary study of two Maverick integrations found on human chromosomes 7 and 8. We performed a comparative analysis of the integrations and determined their orthology across placental mammals (Eutheria) via the syntenic arrangement of neighboring genes. The integrations were absent at the orthologous sites in the genomes of marsupials and monotremes. These observations allowed us to reconstruct a time-calibrated phylogeny and infer the age of their most recent common ancestor at 127 to 262 My. In addition, we estimate the age of the individual integrations at ~102 My, which represents the oldest nonretroviral EVEs found in the human genome. Our findings suggest that active Mavericks still existed in the ancestors of modern mammals ~172 My ago (Jurassic Period) and potentially to the end of the Early Cretaceous. We hypothesize that Mavericks could have gone extinct in mammals from the evolution of an antiviral defense system or from reduced opportunities for transmission in terrestrial hosts. IMPORTANCE The genomes of vertebrates preserve a large diversity of endogenous viral elements (remnants of ancient viruses that accumulate in host genomes over evolutionary time). Although retroviruses account for the vast majority of these elements, diverse DNA viruses have also been found and novel lineages are being described. Here, we analyzed two elements found in the human genome belonging to an ancient group of DNA viruses called Mavericks. We studied their evolutionary history, finding that the elements are shared between humans and many different species of placental mammals. These observations suggest that the elements inserted at least ~102 million years ago (Mya) in the most recent common ancestor of placentals. We further estimated the age of the viral ancestor at around 127 to 262 My. Our results provide evidence for some of the oldest viral integrations in the human genome and insights into the ancient interactions of viruses with the ancestors of modern-day mammals.

A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data.

The transmission dynamics and burden of SARS-CoV-2 in many regions of the world is still largely unknown due to the scarcity of epidemiological analyses and lack of testing to assess the prevalence of disease. In this work, we develop a quantitative framework based on excess mortality data to reconstruct SARS-CoV-2 transmission dynamics and assess the level of underreporting in infections and deaths. Using weekly all-cause mortality data from Iran, we are able to show a strong agreement between our attack rate estimates and seroprevalence measurements in each province and find significant heterogeneity in the level of exposure across the country with 11 provinces reaching near 100% attack rates. Despite having a young population, our analysis reveals that incorporating limited access to medical services in our model, coupled with undercounting of COVID-19-related deaths, leads to estimates of infection fatality rate in most provinces of Iran that are comparable to high-income countries.

Purifying Selection Determines the Short-Term Time Dependency of Evolutionary Rates in SARS-CoV-2 and pH1N1 Influenza.

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. Crucially, there are an increasing number of molecular clock analyses using external evolutionary rate priors to infer evolutionary parameters. However, it is not clear which rate prior is appropriate for a given time window of observation due to the time-dependent nature of evolutionary rate estimates. Here, we characterize 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 data set sizes affect the accuracy of parameter estimation. We further use a generalized McDonald-Kreitman test to estimate the number of segregating nonneutral 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 1 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 nonneutral sites, demonstrating the role of purifying selection in generating the time dependency of evolutionary parameters during pandemics.

Paleovirology of the DNA viruses of eukaryotes.

Paleovirology is the study of ancient viruses and how they have coevolved with their hosts. An increasingly detailed understanding of the diversity, origins, and evolution of the DNA viruses of eukaryotes has been obtained through the lens of paleovirology in recent years. Members of multiple viral families have been found integrated in the genomes of eukaryotes, providing a rich fossil record to study. These elements have extended our knowledge of exogenous viral diversity, host ranges, and the timing of viral evolution, and are revealing the existence of entire new families of eukaryotic integrating dsDNA viruses and transposons. Future work in paleovirology will continue to provide insights into antiviral immunity, viral diversity, and potential applications, and reveal other secrets of the viral world.

Vaccinating adolescents against SARS-CoV-2 in England: a risk-benefit analysis.

OBJECTIVE: To offer a quantitative risk-benefit analysis of two doses of SARS-CoV-2 vaccination among adolescents in England. SETTING: England. DESIGN: Following the risk-benefit analysis methodology carried out by the US Centers for Disease Control, we calculated historical rates of hospital admission, Intensive Care Unit admission and death for ascertained SARS-CoV-2 cases in children aged 12-17 in England. We then used these rates alongside a range of estimates for incidence of long COVID, vaccine efficacy and vaccine-induced myocarditis, to estimate hospital and Intensive Care Unit admissions, deaths and cases of long COVID over a period of 16 weeks under assumptions of high and low case incidence. PARTICIPANTS: All 12-17 year olds with a record of confirmed SARS-CoV-2 infection in England between 1 July 2020 and 31 March 2021 using national linked electronic health records, accessed through the British Heart Foundation Data Science Centre. MAIN OUTCOME MEASURES: Hospitalisations, Intensive Care Unit admissions, deaths and cases of long COVID averted by vaccinating all 12-17 year olds in England over a 16-week period under different estimates of future case incidence. RESULTS: At high future case incidence of 1000/100,000 population/week over 16 weeks, vaccination could avert 4430 hospital admissions and 36 deaths over 16 weeks. At the low incidence of 50/100,000/week, vaccination could avert 70 hospital admissions and two deaths over 16 weeks. The benefit of vaccination in terms of hospitalisations in adolescents outweighs risks unless case rates are sustainably very low (below 30/100,000 teenagers/week). Benefit of vaccination exists at any case rate for the outcomes of death and long COVID, since neither have been associated with vaccination to date. CONCLUSIONS: Given the current (as at 15 September 2021) high case rates (680/100,000 population/week in 10-19 year olds) in England, our findings support vaccination of adolescents against SARS-CoV2.

Rapid evidence review to inform safe return to campus in the context of coronavirus disease 2019 (COVID-19).

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is transmitted predominantly through the air in crowded and unventilated indoor spaces among unvaccinated people. Universities and colleges are potential settings for its spread. Methods: An interdisciplinary team from public health, virology, and biology used narrative methods to summarise and synthesise evidence on key control measures, taking account of mode of transmission. Results: Evidence from a wide range of primary studies supports six measures.  Vaccinate (aim for > 90% coverage and make it easy to get a jab). Require masks indoors, especially in crowded settings. If everyone wears well-fitting cloth masks, source control will be high, but for maximum self-protection, respirator masks should be worn.  Masks should not be removed for speaking or singing. Space people out by physical distancing (but there is no "safe" distance because transmission risk varies with factors such as ventilation, activity levels and crowding), reducing class size (including offering blended learning), and cohorting (students remain in small groups with no cross-mixing). Clean indoor air using engineering controls-ventilation (while monitoring CO 2 levels), inbuilt filtration systems, or portable air cleaners fitted with high efficiency particulate air [HEPA] filters). Test asymptomatic staff and students using lateral flow tests, with tracing and isolating infectious cases when incidence of coronavirus disease 2019 (COVID-19) is high. Support clinically vulnerable people to work remotely. There is no direct evidence to support hand sanitising, fomite controls or temperature-taking. There is evidence that freestanding plastic screens, face visors and electronic air-cleaning systems are ineffective. Conclusions: The above six evidence-based measures should be combined into a multi-faceted strategy to maximise both student safety and the continuation of in-person and online education provision. Staff and students seeking to negotiate a safe working and learning environment should collect data (e.g. CO 2 levels, room occupancy) to inform conversations.

Upregulation of Human Endogenous Retroviruses in Bronchoalveolar Lavage Fluid of COVID-19 Patients.

Severe 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. By comparing transcriptomes of bronchoalveolar lavage fluid (BALF) of COVID-19 patients and healthy controls, and peripheral blood monocytes (PBMCs) from patients and controls, we have shown that HERVs are intensely dysregulated in BALF of COVID-19 patients compared to those in BALF of healthy control patients but not in PBMCs. In particular, upregulation in the expression of specific HERV families was detected in BALF samples of COVID-19 patients, with HERV-FRD being the most highly upregulated family among the families analyzed. 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 process of cellular senescence. This apparent difference of HERV dysregulation between PBMCs and BALF warrants further studies in the 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 that in noninduced HBECs provides a potential link for increased COVID-19 severity and mortality in aged populations. IMPORTANCE SARS-CoV-2 emerged in late 2019 in China, causing a global pandemic. Severe COVID-19 is characterized by intensive inflammatory responses, and older age is an important risk factor for unfavorable outcomes. HERVs are remnants of ancient infections whose expression is upregulated in multiple conditions, including cancer and inflammation, and their expression is increased with increasing age. The significance of this work is that we were able to recognize dysregulated expression of endogenous retroviral elements in BALF samples but not in PBMCs of COVID-19 patients. At the same time, we were able to identify upregulated expression of multiple HERV families in senescence-induced HBECs in comparison to that in noninduced HBECs, a fact that could possibly explain the differences in disease severity among age groups. These results indicate that HERV expression might play a pathophysiological role in local inflammatory pathways in lungs afflicted by SARS-CoV-2 and their expression could be a potential therapeutic target.

A mechanistic evolutionary model explains the time-dependent pattern of substitution rates in viruses.

Estimating viral timescales is fundamental in understanding the evolutionary biology of viruses. Molecular clocks are widely used to reveal the recent evolutionary histories of viruses but may severely underestimate their longer-term origins because of the inverse correlation between inferred rates of evolution and the timescale of their measurement. Here, we provide a predictive mechanistic model that readily explains the rate decay phenomenon over a wide range of timescales and recapitulates the ubiquitous power-law rate decay with a slope of -0.65. We show that standard substitution models fail to correctly estimate divergence times once the most rapidly evolving sites saturate, typically after hundreds of years in RNA viruses and thousands of years in DNA viruses. Our model successfully recreates the observed pattern of decay and explains the evolutionary processes behind the time-dependent rate phenomenon. We then apply our model to re-estimate the date of diversification of genotypes of hepatitis C virus to 423,000 (95% highest posterior density [HPD]: 394,000-454,000) years before present, a time preceding the dispersal of modern humans out of Africa, and show that the most recent common ancestor of sarbecoviruses dates back to 21,000 (95% HPD: 19,000-22,000) years ago, nearly thirty times older than previous estimates. This creates a new perspective for our understanding of the origins of these viruses and also suggests that a substantial revision of evolutionary timescales of other viruses can be similarly achieved.

Lessons for preparedness and reasons for concern from the early COVID-19 epidemic in Iran.

INTRODUCTION: 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. METHODS: We constructed a globally representative sample of 802 genomes, including 46 samples from patients inside or with a travel history to Iran. We then performed a phylogenetic analysis to identify clades related to samples from Iran and estimated the start of the epidemic and early doubling times in cases. We leveraged air travel data from 36 exported cases of COVID-19 to estimate the point-prevalence and the basic reproductive number across the country. We also analysed the province-level all-cause mortality data during winter and spring 2020 to estimate under-reporting of COVID-19-related deaths. Finally, we use this information in an SEIR model to reconstruct the early outbreak dynamics and assess the effectiveness of intervention measures in Iran. RESULTS: By identifying the most basal clade that contained genomes from Iran, our phylogenetic analysis showed that the age of the root is placed on 2019-12-21 (95 % HPD: 2019-09-07 - 2020-02-14). This date coincides with our estimated epidemic start date on 2019-12-25 (95 %CI: 2019-12-11 - 2020-02-24) based air travel data from exported cases with an early doubling time of 4.0 (95 %CI: 1.4-6.7) days in cases. Our analysis of all-cause mortality showed 21.9 (95 % CI: 16.7-27.2) thousand excess deaths by the end of summer. Our model forecasted the second epidemic peak and suggested that by 2020-08-31 a total of 15.0 (95 %CI: 4.9-25.0) million individuals recovered from the disease across the country. CONCLUSION: These findings have profound implications for assessing the stage of the epidemic in Iran despite significant levels of under-reporting. Moreover, the results shed light on the dynamics of SARS-CoV-2 transmissions in Iran and central Asia. They also suggest that in the absence of border screening, there is a high risk of introduction from travellers from areas with active outbreaks. Finally, they show both that well-informed epidemic models are able to forecast episodes of resurgence following a relaxation of interventions, and that NPIs are key to controlling ongoing epidemics.