SARS-CoV-2 lineage-specific disease symptoms and disease severity in Sao Caetano do Sul city, Brazil (preprint)

Background: The city of Sao Caetano do Sul, Brazil, established a web-based platform to provide primary care to suspected COVID-19 patients, integrating clinical and demographic data and sample metadata. Here we describe lineage-specific spatiotemporal dynamics of infections, clinical symptoms, and disease severity during the first year of the epidemic. Methods: We selected and sequenced 879 PCR+ swab samples (8% of all reported cases), obtaining a spatially and temporally representative set of sequences. Daily lineage-specific prevalence was estimating using a moving-window approach, allowing inference of cumulative cases and symptom probability stratified by lineage using integrated data from the platform. Results: Most infections were caused by B.1.1.28 (41.3%), followed by Gamma (31.7%), Zeta (9.6%) and B1.1.33 (9.0%). Gamma and Zeta were associated with larger prevalence of dyspnoea (respectively 81.3% and 78.5%) and persistent fever (84.7% and 61.1%) compared to B.1.1.28 and B.1.1.33. Ageusia, anosmia, and coryza were respectively 18.9%, 20.3% and 17.8% less commonly caused by Gamma, while altered mental status was 108.9% more common in Zeta. Case incidence was spatially heterogeneous and larger in poorer and younger districts. Discussion: Our study demonstrates that Gamma was associated with more severe disease, emphasising the role of its increased disease severity in the heightened mortality levels in Brazil.

Global Expansion of SARS-CoV-2 Variants of Concern: Dispersal Patterns and Influence of Air Travel (preprint)

In many regions of the world, the Alpha, Beta and Gamma SARS-CoV-2 Variants of Concern (VOCs) co-circulated during 2020-21 and fueled waves of infections. During 2021, these variants were almost completely displaced by the Delta variant, causing a third wave of infections worldwide. This phenomenon of global viral lineage displacement was observed again in late 2021, when the Omicron variant disseminated globally. In this study, we use phylogenetic and phylogeographic methods to reconstruct the dispersal patterns of SARS-CoV-2 VOCs worldwide. We find that the source-sink dynamics of SARS-CoV-2 varied substantially by VOC, and identify countries that acted as global hubs of variant dissemination, while other countries became regional contributors to the export of specific variants. We demonstrate a declining role of presumed origin countries of VOCs to their global dispersal: we estimate that India contributed <15% of all global exports of Delta to other countries and South Africa <1-2% of all global Omicron exports globally. We further estimate that >80 countries had received introductions of Omicron BA.1 100 days after its inferred date of emergence, compared to just over 25 countries for the Alpha variant. This increased speed of global dissemination was associated with a rebound in air travel volume prior to Omicron emergence in addition to the higher transmissibility of Omicron relative to Alpha. Our study highlights the importance of global and regional hubs in VOC dispersal, and the speed at which highly transmissible variants disseminate through these hubs, even before their detection and characterization through genomic surveillance.

Using multiple sampling strategies to estimate SARS-CoV-2 epidemiological parameters from genomic sequencing data (preprint)

SARS-CoV-2 virus genomes are currently being sequenced at an unprecedented pace. The choice of sequences used in genetic and epidemiological analysis is important as it can induce biases that detract from the value of these rich datasets. This raises questions about how a set of sequences should be chosen for analysis, and which epidemiological parameters derived from genomic data are sensitive or robust to changes in sampling. We provide initial insights on these largely understudied problems using SARS-CoV-2 genomic sequences from Hong Kong and the Amazonas State, Brazil. We consider sampling schemes that select sequences uniformly, in proportion or reciprocally with case incidence and which simply use all available sequences (unsampled). We apply Birth-Death Skyline and Skygrowth methods to estimate the time-varying reproduction number (Rt) and growth rate (rt) under these strategies as well as related R0 and date of origin parameters. We compare these to estimates from case data derived from EpiFilter, which we use as a reference for assessing bias. We find that both Rt and rt are sensitive to changes in sampling whilst R0 and date of origin are relatively robust. Moreover, we find that the unsampled datasets (opportunistic sampling) provided, overall, the worst Rt and rt estimates for both Hong Kong and the Amazonas case studies. We highlight that sampling strategy may be an influential yet neglected component of sequencing analysis pipelines. More targeted attempts at genomic surveillance and epidemic analyses, particularly in resource-poor settings which have a limited genomic capability, are necessary to maximise the informativeness of virus genomic datasets.

Context-specific emergence and growth of the SARS-CoV-2 Delta variant (preprint)

The Delta variant of concern of SARS-CoV-2 has spread globally causing large outbreaks and resurgences of COVID-19 cases. The emergence of Delta in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. Here we analyse 52,992 Delta genomes from England in combination with 93,649 global genomes to reconstruct the emergence of Delta, and quantify its introduction to and regional dissemination across England, in the context of changing travel and social restrictions. Through analysis of human movement, contact tracing, and virus genomic data, we find that the focus of geographic expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced >1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers from India reduced onward transmission from importations; however the transmission chains that later dominated the Delta wave in England had been already seeded before restrictions were introduced. In England, increasing inter- regional travel drove Delta's nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from other regions. Subsequently, increased levels of local population mixing, not the number of importations, was associated with faster relative growth of Delta. Among US states, we find that regions that previously experienced large waves also had faster Delta growth rates, and a model including interactions between immunity and human behaviour could accurately predict the rise of Delta there. Delta's invasion dynamics depended on fine scale spatial heterogeneity in immunity and contact patterns and our findings will inform optimal spatial interventions to reduce transmission of current and future VOCs such as Omicron.

Scale-free dynamics of Covid-19 in a Brazilian city (preprint)

Mathematical models can provide insights into the control of pandemic COVID-19, which remains a global priority. The dynamics of directly-transmitted infectious diseases, such as COVID-19, are usually described by compartmental models where individuals are classified as susceptible, infected and removed. These SIR models typically assume homogenous transmission of infection, even in large populations, a simplification that is convenient but inconsistent with observations. Here we use original data on the dynamics of COVID-19 spread in a Brazilian city to investigate the structure of the transmission network. We find that transmission can be described by a network in which each infectious individual has a small number of susceptible contacts, of the order of 2-5, which is independent of total population size. Compared with standard models of homogenous mixing, this scale-free, fractal infection process gives a better description of COVID-19 dynamics through time. In addition, the contact process explains the geographically localized clusters of disease seen in this Brazilian city. Our scale-free model can help refine criteria for physical and social distancing in order to more effectively mitigate the spread of COVID-19. We propose that scale-free COVID-19 dynamics could be a widespread phenomenon, a topic for further investigation.

Global disparities in SARS-CoV-2 genomic surveillance (preprint)

Genomic sequencing provides critical information to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments and vaccines, and guide public health responses. To investigate the spatiotemporal heterogeneity in the global SARS-CoV-2 genomic surveillance, we estimated the impact of sequencing intensity and turnaround times (TAT) on variant detection in 167 countries. Most countries submit genomes >21 days after sample collection, and 77% of low and middle income countries sequenced <0.5% of their cases. We found that sequencing at least 0.5% of the cases, with a TAT <21 days, could be a benchmark for SARS-CoV-2 genomic surveillance efforts. Socioeconomic inequalities substantially impact our ability to quickly detect SARS-CoV-2 variants, and undermine the global pandemic preparedness. One-Sentence SummarySocioeconomic inequalities impacted the SARS-CoV-2 genomic surveillance, and undermined the global pandemic preparedness.

Reinfection by the SARS-CoV-2 P.1 variant in blood donors in Manaus, Brazil (preprint)

The city of Manaus, north Brazil, was stricken by a severe epidemic of SARS-Cov-2 in March 2020, reaching a seroprevalence of 76% by October 2020. Nevertheless, in late November an abrupt increase in hospitalizations and deaths hit Manaus, causing higher number of deaths compared to the first epidemic wave. It has been hypothesized that virus lineages circulating in the second wave, namely the P.1 variant of concern first detected in early December in Manaus, could be better at evading immunity generated in response to previous infection with other lineages. In order to estimate the reinfection rate during the resurgence of SARS-CoV-2 in Manaus, we tested serial samples from 238 unvaccinated repeat blood donors using a SARS-CoV-2 anti-N IgG chemiluminescence microparticle assay. Blood donors were divided into six groups that reflected the inferred sequence of infection and reinfection with non-P.1 and P.1 variants. We assumed that reinfections induce a recrudescence (or boosting) of plasma anti-N IgG antibody levels, yielding a V-shaped time series of antibody reactivity levels. We infer that 16.9% (95% CI [9.48%, 28.5%]) of all presumed P.1 infections that were observed in 2021 were reinfections. If we also include cases of probable or possible reinfections (defined by considering the time period when the antibody levels are expected to grow after recovery and the range of half-lives for antibody waning after seroconversion), these percentages increase respectively to 25.8% (95% CI [16.7%, 37.4%]), and 31.0% (95% CI [21.4%, 42.5%]). Our data suggest that reinfection due to P.1 is common and more frequent than what has been detected by traditional epidemiologic, molecular and genomic surveillance of clinical cases.

Tracking the emergence of disparities in the subnational spread of COVID-19 in Brazil using an online application for real-time data visualisation. (preprint)

Brazil is one of the countries worst affected by the COVID-19 pandemic. We have developed CLIC-Brazil an online application for the real-time visualisation of COVID-19 data in Brazil at the municipality level. In the app, case and death data are standardised to allow comparisons to be made between places and over time. Estimates of Rt , a measure of the rate of propagation of the epidemic, over time are also made. Using data from the app, regression analyses identified factors associated with; the rate of initial spread, early epidemic intensity and predictions of the likelihood of occurrence of new incidence maxima. Municipalities with higher metrics of social development experienced earlier onset and faster growing epidemics, although space and time were the predominant predictive factors. Differences in the initial epidemic intensity (mean Rt ) were largely driven by geographic location and the date of local onset. This study demonstrates that by monitoring, standardising and analysing the development of an epidemic at a local level, insights can be gained into spatial and temporal heterogeneities.

Genomic epidemiology of SARS-CoV-2 transmission lineages in Ecuador (preprint)

Characterisation of SARS-CoV-2 genetic diversity through space and time can reveal trends in virus importation and domestic circulation, and permit the exploration of questions regarding the early transmission dynamics. Here we present a detailed description of SARS-CoV-2 genomic epidemiology in Ecuador, one of the hardest hit countries during the early stages of the COVID-19 pandemic. We generate and analyse 160 whole genome sequences sampled from all provinces of Ecuador in 2020. Molecular clock and phylgeographic analysis of these sequences in the context of global SARS-CoV-2 diversity enable us to identify and characterise individual transmission lineages within Ecuador, explore their spatiotemporal distributions, and consider their introduction and domestic circulation. Our results reveal a pattern of multiple international importations across the country, with apparent differences between key provinces. Transmission lineages were mostly introduced before the implementation of non-pharmaceutical interventions (NPIs), with differential degrees of persistence and national dissemination.

Social and racial inequalities in COVID-19 risk of hospitalisation and death across Sao Paulo state, Brazil (preprint)

BackgroundLittle evidence exists on the differential health effects of COVID-19 on disadvantaged population groups. Here we characterise the differential risk of hospitalisation and death in Sao Paulo state, Brazil and show how vulnerability to COVID-19 is shaped by socioeconomic inequalities. MethodsWe conducted a cross-sectional study using hospitalised severe acute respiratory infections (SARI) notified from March to August 2020, in the Sistema de Monitoramento Inteligente de Sao Paulo (SIMI-SP) database. We examined the risk of hospitalisation and death by race and socioeconomic status using multiple datasets for individual-level and spatio-temporal analyses. We explained these inequalities according to differences in daily mobility from mobile phone data, teleworking behaviour, and comorbidities. FindingsThroughout the study period, patients living in the 40% poorest areas were more likely to die when compared to patients living in the 5% wealthiest areas (OR: 1{middle dot}60, 95% CI: 1{middle dot}48 - 1{middle dot}74) and were more likely to be hospitalised between April and July, 2020 (OR: 1{middle dot}08, 95% CI: 1{middle dot}04 - 1{middle dot}12). Black and Pardo individuals were more likely to be hospitalised when compared to White individuals (OR: 1{middle dot}37, 95% CI: 1{middle dot}32 - 1{middle dot}41; OR: 1{middle dot}23, 95% CI: 1{middle dot}21 - 1{middle dot}25, respectively), and were more likely to die (OR: 1{middle dot}14, 95% CI: 1{middle dot}07 - 1{middle dot}21; 1{middle dot}09, 95% CI: 1{middle dot}05 - 1{middle dot}13, respectively). InterpretationLow-income and Black and Pardo communities are more likely to die with COVID-19. This is associated with differential access to healthcare, adherence to social distancing, and the higher prevalence of comorbidities. FundingThis project was supported by a Medical Research Council-Sao Paulo Research Foundation (FAPESP) CADDE partnership award (MR/S0195/1 and FAPESP 18/14389-0) (http://caddecentre.org/). This work received funding from the U.K. Medical Research Council under a concordat with the U.K. Department for International Development.

Establishment & lineage dynamics of the SARS-CoV-2 epidemic in the UK (preprint)

The UK's COVID-19 epidemic during early 2020 was one of world's largest and unusually well represented by virus genomic sampling. Here we reveal the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 SARS-CoV-2 genomes, including 26,181 from the UK sampled throughout the country's first wave of infection. Using large-scale phylogenetic analyses, combined with epidemiological and travel data, we quantify the size, spatio-temporal origins and persistence of genetically-distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown were larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, whilst lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.

COVID-19 herd immunity in the Brazilian Amazon (preprint)

The herd immunity threshold is the proportion of a population that must be immune to an infectious disease, either by natural infection or vaccination such that, in the absence of additional preventative measures, new cases decline and the effective reproduction number falls below unity. This fundamental epidemiological parameter is still unknown for the recently-emerged COVID-19, and mathematical models have predicted very divergent results. Population studies using antibody testing to infer total cumulative infections can provide empirical evidence of the level of population immunity in severely affected areas. Here we show that the transmission of SARS-CoV-2 in Manaus, located in the Brazilian Amazon, increased quickly during March and April and declined more slowly from May to September. In June, one month following the epidemic peak, 44% of the population was seropositive for SARS-CoV-2, equating to a cumulative incidence of 52%, after correcting for the false-negative rate of the antibody test. The seroprevalence fell in July and August due to antibody waning. After correcting for this, we estimate a final epidemic size of 66%. Although non-pharmaceutical interventions, plus a change in population behavior, may have helped to limit SARS-CoV-2 transmission in Manaus, the unusually high infection rate suggests that herd immunity played a significant role in determining the size of the epidemic.

Baseline T cell immune phenotypes predict virologic and disease control upon SARS-CoV infection (preprint)

The COVID-19 pandemic has revealed that infection with SARS-CoV-2 can result in a wide range of clinical outcomes in humans, from asymptomatic or mild disease to severe disease that can require mechanical ventilation. An incomplete understanding of immune correlates of protection represents a major barrier to the design of vaccines and therapeutic approaches to prevent infection or limit disease. This deficit is largely due to the lack of prospectively collected, pre-infection samples from indiviuals that go on to become infected with SARS-CoV-2. Here, we utilized data from a screen of genetically diverse mice from the Collaborative Cross (CC) infected with SARS-CoV to determine whether circulating baseline T cell signatures are associated with a lack of viral control and severe disease upon infection. SARS-CoV infection of CC mice results in a variety of viral load trajectories and disease outcomes. Further, early control of virus in the lung correlates with an increased abundance of activated CD4 and CD8 T cells and regulatory T cells prior to infections across strains. A basal propensity of T cells to express IFNg and IL17 over TNFa also correlated with early viral control. Overall, a dysregulated, pro-inflammatory signature of circulating T cells at baseline was associated with severe disease upon infection. While future studies of human samples prior to infection with SARS-CoV-2 are required, our studies in mice with SARS-CoV serve as proof of concept that circulating T cell signatures at baseline can predict clinical and virologic outcomes upon SARS-CoV infection. Identification of basal immune predictors in humans could allow for identification of individuals at highest risk of severe clinical and virologic outcomes upon infection, who may thus most benefit from available clinical interventions to restrict infection and disease.

Comparative analysis reveals the species-specific genetic determinants of ACE2 required for SARS-CoV-2 entry (preprint)

Coronavirus interaction with viral receptor is a primary genetic determinant of host range and tissue tropism. SARS-CoV-2 utilizes ACE2 as the receptor to enter the host cell in a species-specific manner. We and others have previously shown that ACE2 orthologs from New World monkeys, koala and mouse cannot interact with SARS-CoV-2 to mediate viral entry, and this defect can be restored by humanization of the restrictive residues in New World monkey ACE2. To better understand the genetic determinants of susceptibility of ACE2 orthologs to viral entry, we compared koala and mouse ACE2 sequences with human ortholog, and identified the key residues in koala or mouse ACE2 that restrict its viral receptor activity. Humanization of these critical residues could render the capabilities of koala and mouse ACE2 to bind viral spike protein and facilitate the viral entry. Our work identifies the genetic determinant of ACE2 for SARS-CoV-2 susceptibility, and a single mutation could restore the mouse ACE2 receptor activity, providing a potential avenue for the development of mouse model of SARS-CoV-2.

Cryo-EM structure of S-Trimer, a subunit vaccine candidate for COVID-19 (preprint)

Less than a year after its emergence, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over 22 million people worldwide with a death toll approaching 1 million. Vaccination remains the best hope to ultimately put this pandemic to an end. Here, using Trimer-Tag technology, we produced both wild-type (WT) and furin site mutant (MT) S-Trimers for COVID-19 vaccine studies. Cryo-EM structures of the WT and MT S-Trimers, determined at 3.2 Angstrom and 2.6 Angstrom respectively, revealed that both antigens adopt a tightly closed conformation and their structures are essentially identical to that of the previously solved full-length WT S protein in detergent. These results validate Trimer-Tag as a platform technology in production of metastable WT S-Trimer as a candidate for COVID-19 subunit vaccine.

SARS-CoV-2 Nsp1 suppresses host but not viral translation through a bipartite mechanism (preprint)

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a highly contagious virus that underlies the current COVID-19 pandemic. SARS-CoV-2 is thought to disable various features of host immunity and cellular defense. The SARS-CoV-2 nonstructural protein 1 (Nsp1) is known to inhibit host protein translation and could be a target for antiviral therapy against COVID-19. However, how SARS-CoV-2 circumvents this translational blockage for the production of its own proteins is an open question. Here, we report a bipartite mechanism of SARS-CoV-2 Nsp1 which operates by: (1) hijacking the host ribosome via direct interaction of its C-terminal domain (CT) with the 40S ribosomal subunit and (2) specifically lifting this inhibition for SARS-CoV-2 via a direct interaction of its N-terminal domain (NT) with the 5 untranslated region (5 UTR) of SARS-CoV-2 mRNA. We show that while Nsp1-CT is sufficient for binding to 40S and inhibition of host protein translation, the 5 UTR of SARS-CoV-2 mRNA removes this inhibition by binding to Nsp1-NT, suggesting that the Nsp1-NT-UTR interaction is incompatible with the Nsp1-CT-40S interaction. Indeed, lengthening the linker between Nsp1-NT and Nsp1-CT of Nsp1 progressively reduced the ability of SARS-CoV-2 5 UTR to escape the translational inhibition, supporting that the incompatibility is likely steric in nature. The short SL1 region of the 5 UTR is required for viral mRNA translation in the presence of Nsp1. Thus, our data provide a comprehensive view on how Nsp1 switches infected cells from host mRNA translation to SARS-CoV-2 mRNA translation, and that Nsp1 and 5 UTR may be targeted for anti-COVID-19 therapeutics.

An immunodominance hierarchy exists in CD8+ T cell responses to HLA-A*02:01-restricted epitopes identified from the non-structural polyprotein 1a of SARS-CoV-2. (preprint)

COVID-19 vaccines are being rapidly developed and human trials are underway. Almost all of these vaccines have been designed to induce antibodies targeting spike protein of SARS-CoV-2 in expectation of neutralizing activities. However, non-neutralizing antibodies are at risk of causing antibody-dependent enhancement. Further, the longevity of SARS-CoV-2-specific antibodies is very short. Therefore, in addition to antibody-induced vaccines, novel vaccines on the basis of SARS-CoV-2-specific cytotoxic T lymphocytes (CTLs) should be considered in the vaccine development. Here, we attempted to identify HLA-A*02:01-restricted CTL epitopes derived from the non-structural polyprotein 1a of SARS-CoV-2. Eighty-two peptides were firstly predicted as epitope candidates on bioinformatics. Fifty-four in 82 peptides showed high or medium binding affinities to HLA-A*02:01. HLA-A*02:01 transgenic mice were then immunized with each of the 54 peptides encapsulated into liposomes. The intracellular cytokine staining assay revealed that 18 out of 54 peptides were CTL epitopes because of the induction of IFN-{gamma}-producing CD8+ T cells. In the 18 peptides, 10 peptides were chosen for the following analyses because of their high responses. To identify dominant CTL epitopes, mice were immunized with liposomes containing the mixture of the 10 peptides. Some peptides were shown to be statistically predominant over the other peptides. Surprisingly, all mice immunized with the liposomal 10 peptide mixture did not show the same reaction pattern to the 10 peptides. There were three pattern types that varied sequentially, suggesting the existence of an immunodominance hierarchy, which may provide us more variations in the epitope selection for designing CTL-based COVID-19 vaccines. ImportanceFor the development of vaccines based on SARS-CoV-2-specific cytotoxic T lymphocytes (CTLs), we attempted to identify HLA-A*02:01-restricted CTL epitopes derived from the non-structural polyprotein 1a of SARS-CoV-2. Out of 82 peptides predicted on bioinformatics, 54 peptides showed good binding affinities to HLA-A*02:01. Using HLA-A*02:01 transgenic mice, 18 in 54 peptides were found to be CTL epitopes in the intracellular cytokine staining assay. Out of 18 peptides, 10 peptides were chosen for the following analyses because of their high responses. To identify dominant epitopes, mice were immunized with liposomes containing the mixture of the 10 peptides. Some peptides were shown to be statistically predominant. Surprisingly, all immunized mice did not show the same reaction pattern to the 10 peptides. There were three pattern types that varied sequentially, suggesting the existence of an immunodominance hierarchy, which may provide us more variations in the epitope selection for designing CTL-based COVID-19 vaccines.

Early transmission dynamics, spread, and genomic characterization of SARS-CoV-2 in Panama. (preprint)

BackgroundWith more than 50000 accumulated cases, Panama has one of the highest incidences of SARS-CoV-2 in Central America, despite the fast implementation of disease control strategies. We investigated the early transmission patterns of the virus and the outcomes of mitigation measures in the country. MethodsWe collected information from epidemiological surveillance, including contact tracing, and genetic data from SARS-CoV-2 whole genomes, of the first five weeks of the outbreak. These data were used to estimate the exponential growth rate, doubling time and the time-varying effective reproductive number (Rt) using date of symptom onset in a Bayesian framework. The time of most recent ancestor for the introduced and circulating lineages was estimated by Bayesian analysis. FindingsA total of 4210 subjects were SARS-CoV-2 positive during the period evaluated, of them we sequenced 313 cases, detecting the circulation of 10 SARS-CoV-2 lineages. Whole genomes analysis identified the local transmission of one cryptic lineage as early as 2 weeks before it was detected by surveillance systems. Analysis of transmission dynamics showed that lockdown reduced Rt and increased the doubling time, however, these measures did not stop the circulation of this lineage in the country. InterpretationThese results demonstrate the value of epidemiological modeling and genome surveillance to assess mitigation strategies. At the same time, an active search for cryptic transmission clusters is crucial to interrupt local transmission of SARS-CoV-2 in a region. FundingMinistry of Health, Contribution from private donors and Secretaria Nacional de Ciencia y Tecnologia. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSIn May 2020, we searched for published studies in PubMed and web of Science related to genetic variability and dynamics of SARS-CoV-2 transmission in Latin America, and there was none. On July 2020, there was one study of this type on SARS-CoV-2 transmission in Brazil and none in Central America. We were particularly interested in SARS-CoV-2 cryptic transmission that could allow the virus spread through locals without being detected by respiratory health system surveillance, and no publication was reported. On July 2020, seven papers (five in preprint) were about SARS-CoV-2 cryptic transmission, one in China, another in UK and five in the US. None in Central America. All of them showed the importance of genomic surveillance to detect different lineage introductions, cryptic transmission and its role in early spread in a region or in health-care setting. Added value of this studyWe integrate data collected from tested individual during national surveillance of COVID19 suspected cases or contact of cases, as part of the National COVID19 Laboratory network. This data was used to estimate epidemiological parameters of the outbreak as well as the effect of mitigation measures on the epidemic dynamic. We sequence the whole genome of SARS-COV-2 of 7.4% of RT-PCR confirmed cases at the national level, and with phylogenetic analysis we identified SARS-CoV-2 lineages introduced in the country and estimate date of their introductions. Epidemiological and genetic data was compared and we observed the cryptic transmission of one introduced lineage and the rise of a local lineage that was not detected by the active contact tracing implemented by the health system surveillance. This cryptic lineage could explain the fact that early implementation measures decreased the transmission rate and the increased the doubling time, however they were not able to eliminate totally the virus spread. Implications of all the available evidenceThis is the first study that analyzed the epidemiology and transmission dynamics of the early COVID19 epidemic in a Central American country using both epidemiological and genomic surveillance. Our findings suggest that strict containment measures and movement restrictions in Panama might have contributed to decrease the early spread of the virus, but that cryptic local transmission allowed a continual basal virus diffusion that could explain, in part, the high incidence of cases in the country. More broadly, our findings are crucial to inform intervention policy in real-time, for countries in similar situations and the importance of constant monitoring of SARS-CoV-2 lineages to understand its transmission in a region.