Anderson Fernandes Brito

Motivation: Genome sequencing provides an exceptional window into the evolutionary and epidemiological dynamics of endemic and emerging pathogens, and thus allows for better, more targeted, public health interventions. Online genomic surveillance platforms can provide near real-time insight into these dynamics. Results: Nextstrain provides continually updated real-time genomic surveillance for 21 viruses and the bacterial pathogen Mycobacterium tuberculosis, with most analyses relying solely on open sequence data. Each pathogen includes steps to fetch and curate open data, classify sequences using established nomenclature systems, perform phylogenetic analyses, and share the results publicly. These analyses are automated, with most running daily to provide continually updated snapshots of pathogen evolution. Availability and Implementation: All source code is available at https://github.com/nextstrain and a snapshot is archived at Zenodo (https://doi.org/10.5281/zenodo.22697730). Phylogenetic results can be visualized and downloaded at https://nextstrain.org/pathogens, and open sequence data and curated metadata are available at https://nextstrain.org/pathogens/files.

Motivation: Genome sequencing provides an exceptional window into the evolutionary and epidemiological dynamics of endemic and emerging pathogens, and thus allows for better, more targeted, public health interventions. Online genomic surveillance platforms can provide near real-time insight into these dynamics. Results: Nextstrain provides continually updated real-time genomic surveillance for 21 viruses and the bacterial pathogen Mycobacterium tuberculosis, with most analyses relying solely on open sequence data. Each pathogen includes steps to fetch and curate open data, classify sequences using established nomenclature systems, perform phylodynamic analyses, and share the results publicly. These analyses are automated, with most running daily to provide continually updated snapshots of pathogen evolution. Availability and Implementation: All source code is available at https://github.com/nextstrain. Phylodynamic results can be visualized and downloaded at https://nextstrain.org/pathogens, and open sequence data and curated metadata are available at https://nextstrain.org/pathogens/files.

Early detection of disease outbreaks is critical for effective public health response, yet traditional surveillance systems often suffer from delayed reporting. Here, we investigate whether real-time occupancy data from healthcare facilities can act as an early warning indicator of possible outbreak activity. We analyzed occupancy trends from 17 emergency care units in the São Paulo metropolitan area and compared them with national surveillance data for infectious diseases, including SARS-CoV-2 and dengue virus. Dynamic time warping and Granger causality tests demonstrated that occupancy patterns anticipate infection dynamics with a mean lead time of three weeks. Early warning signals of three epidemiological events were identified as deviations from average occupancy. Local indicators of spatial association revealed persistent overcrowding hotspots in later outbreak stages, highlighting regions where sustained healthcare monitoring and surveillance remain necessary. These findings demonstrate the potential of privacy-safe passive occupancy data to support timely epidemic surveillance.

Bats are natural reservoirs for diverse viruses, including coronaviruses, filoviruses, and paramyxoviruses, many leading to zoonotic spillover events and demanding an integrated surveillance. Here, we present a framework that leverages Brazil’s rabies passive surveillance program to detect bat-borne viruses. Using an algorithm to select representative specimens from 2,422 bats collected across São Paulo state, we submitted 150 paired lung and intestine samples to nanopore metagenomic sequencing. We detected 98 viral contigs from 12 families of public health relevance, including Arenaviridae, Coronaviridae , and Paramyxoviridae . Notably, the approach identified a previously unknown filovirus in bats in the Americas, validating the framework’s capacity for epidemic preparedness. These findings reveal an undetected viral diversity and demonstrate how existing animal surveillance can monitor pathogen threats. Crucially, in a workshop involving multisectoral One Health experts in Brazil, this framework was validated as a scalable model for national expansion, adapted for low- and middle-income countries (LMICs). One-sentence summary line: The study introduces a viral surveillance method using metagenomics in bats, offering a scalable, cost-effective model for operationalizing One Health surveillance, especially relevant to low- and middle-income countries.

Powassan virus is an emerging tick-borne virus of concern for public health, but very little is known about its transmission patterns and ecology. Here, we expanded the genomic dataset by sequencing 279 Powassan viruses isolated from Ixodes scapularis ticks from the northeastern United States. Our phylogeographic reconstructions revealed that Powassan virus lineage II was likely introduced or emerged from a relict population in the Northeast between 1940 and 1975. Sequences strongly clustered by sampling location, suggesting a highly focal geographical distribution. Our analyses further indicated that Powassan virus lineage II emerged in the northeastern United States mostly following a south-to-north pattern, with a weighted lineage dispersal velocity of ~3 km/y. Since the emergence in the Northeast, we found an overall increase in the effective population size of Powassan virus lineage II, but with growth stagnating during recent years. The cascading effect of population expansion of white-tailed deer and I. scapularis populations likely facilitated the emergence of Powassan virus in the northeastern United States.

Genomic sequencing is essential to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments, vaccines, and guide public health responses. To investigate the global SARS-CoV-2 genomic surveillance, we used sequences shared via GISAID to estimate the impact of sequencing intensity and turnaround times on variant detection in 189 countries. In the first two years of the pandemic, 78% of high-income countries sequenced >0.5% of their COVID-19 cases, while 42% of low- and middle-income countries reached that mark. Around 25% of the genomes from high income countries were submitted within 21 days, a pattern observed in 5% of the genomes from low- and middle-income countries. We found that sequencing around 0.5% of the cases, with a turnaround time <21 days, could provide a benchmark for SARS-CoV-2 genomic surveillance. Socioeconomic inequalities undermine the global pandemic preparedness, and efforts must be made to support low- and middle-income countries improve their local sequencing capacity.

The COVID-19 pandemic has revealed the importance of virus genome sequencing to guide public health interventions to control virus transmission and understand SARS-CoV-2 evolution. As of July 20th, 2021, >2 million SARS-CoV-2 genomes have been submitted to GISAID, 94% from high income and 6% from low and middle income countries. Here, we analyse the spatial and temporal heterogeneity in SARS-CoV-2 global genomic surveillance efforts. We report a comprehensive analysis of virus lineage diversity and genomic surveillance strategies adopted globally, and investigate their impact on the detection of known SARS-CoV-2 virus lineages and variants of concern. Our study provides a perspective on the global disparities surrounding SARS-CoV-2 genomic surveillance, their causes and consequences, and possible solutions to maximize the impact of pathogen genome sequencing for efforts on public health. One-Sentence Summary The causes, consequences and possible solutions for disparities in genomic surveillance observed in the COVID-19 pandemic.

After the Zika virus (ZIKV) epidemic in the Americas in 2016, both Zika and dengue incidence declined to record lows in many countries in 2017–2018, but in 2019 dengue resurged in Brazil, causing ~2.1 million cases. In this study we use epidemiological, climatological and genomic data to investigate dengue dynamics in recent years in Brazil. First, we estimate dengue virus force of infection (FOI) and model mosquito-borne transmission suitability since the early 2000s. Our estimates reveal that DENV transmission was low in 2017–2018, despite conditions being suitable for viral spread. Our study also shows a marked decline in dengue susceptibility between 2002 and 2019, which could explain the synchronous decline of dengue in the country, partially as a result of protective immunity from prior ZIKV and/or DENV infections. Furthermore, we performed phylogeographic analyses using 69 newly sequenced genomes of dengue virus serotype 1 and 2 from Brazil, and found that the outbreaks in 2018–2019 were caused by local DENV lineages that persisted for 5–10 years, circulating cryptically before and after the Zika epidemic. We hypothesize that DENV lineages may circulate at low transmission levels for many years, until local conditions are suitable for higher transmission, when they cause major outbreaks.

Summary: Prior to the emergence of antigenically distinct SARS-CoV-2 variants, reinfections were reported infrequently - presumably due to the generation of durable and protective immune responses. However, case reports also suggested that rare, repeated infections may occur as soon as 48 days following initial disease onset. The underlying immunologic deficiencies enabling SARS-CoV-2 reinfections are currently unknown. Here we describe a renal transplant recipient who developed recurrent, symptomatic SARS-CoV-2 infection - confirmed by whole virus genome sequencing - 7 months after primary infection. To elucidate the immunological mechanisms responsible for SARS-CoV-2 reinfection, we performed longitudinal profiling of cellular and humoral responses during both primary and recurrent SARS-CoV-2 infection. We found that the patient responded to the primary infection with transient, poor-quality adaptive immune responses. The patient’s immune system was further compromised by intervening treatment for acute rejection of the renal allograft prior to reinfection. Importantly, we also identified the development of neutralizing antibodies and the formation of humoral memory responses prior to SARS-CoV-2 reinfection. However, these neutralizing antibodies failed to confer protection against reinfection, suggesting that additional factors are required for efficient prevention of SARS-CoV-2 reinfection. Further, we found no evidence supporting viral evasion of primary adaptive immune responses, suggesting that susceptibility to reinfection may be determined by host factors rather than pathogen adaptation in this patient. In summary, our study suggests that a low neutralizing antibody presence alone is not sufficient to confer resistance against reinfection. Thus, patients with solid organ transplantation, or patients who are otherwise immunosuppressed, who recover from infection with SARS-CoV-2 may not develop sufficient protective immunity and are at risk of reinfection.

In times when herpesvirus genomic data were scarce, the cospeciation between these viruses and their hosts was considered to be common knowledge. However, as more herpesviral sequences were made available, tree reconciliation analyses started to reveal topological incongruences between host and viral phylogenies, indicating that other cophylogenetic events, such as intrahost speciation and host switching, likely played important roles along more than 200 million years of evolutionary history of these viruses. Tree reconciliations performed with undated phylogenies can identify topological differences, but offer insufficient information to reveal temporal incongruences between the divergence timing of host and viral species. In this study, we performed cophylogenetic analyses using time-resolved trees of herpesviruses and their hosts, based on careful molecular clock modelling. This approach enabled us to infer cophylogenetic events over time and also integrate information on host biogeography to better understand host–virus evolutionary history. Given the increasing amount of sequence data now available, mismatches between host and viral phylogenies have become more evident, and to account for such phylogenetic differences, host switches, intrahost speciations and losses were frequently found in all tree reconciliations. For all subfamilies in Herpesviridae, under all scenarios we explored, intrahost speciation and host switching were more frequent than cospeciation, which was shown to be a rare event, restricted to contexts where topological and temporal patterns of viral and host evolution were in strict agreement.