Genomic Surveillance of SARS-CoV-2: Methods and Public Health Reporting

Genomic surveillance of SARS-CoV-2 is the systematic process of sequencing viral genomes from clinical or environmental samples, determining their lineages, and using that information to inform public health decisions. This article provides a practical workflow for researchers, analysts, and public health professionals who need to establish or improve a genomic surveillance program. The content covers sample selection, sequencing platforms, bioinformatics analysis, data quality controls, reporting structures, and the integration of genomic findings into actionable public health communications.

At a Glance

Genomic surveillance programs vary in scale, cost, and complexity depending on their objectives. The table below summarizes the primary surveillance approaches documented in peer-reviewed literature.

A Belgian program compared sentinel SARI hospital surveillance with baseline genomic surveillance and found that the sentinel approach detected Omicron sublineages BA.1, BA.2, BA.4, and BA.5 with no more than a two week delay relative to their epidemic growth in the population. The same study noted that a minor variant, Omicron BA.3, was never detected through the sentinel system, indicating that sentinel surveillance may miss variants that do not cause substantial severe disease. See the full study in Influenza and Other Respiratory Viruses.

Scope and Purpose of Genomic Surveillance

Genomic surveillance serves distinct purposes that shape program design. A program focused on early detection of novel variants requires different sampling intensity than one tracking the prevalence of known lineages over time. The primary objectives include identifying emerging variants of concern, monitoring changes in viral transmission dynamics, assessing the impact of variants on vaccine effectiveness, and informing infection control measures.

The pandemic demonstrated that genomic surveillance programs must be adaptable. In Uruguay, researchers integrated 1792 viral genomes with vaccination records and epidemiological data to show that timely vaccination combined with real-time genomic surveillance helped control consecutive transmission waves. The analysis demonstrated that detection of the Delta variant in July 2021 did not trigger a major wave in a largely vaccinated population, in contrast to the earlier Gamma-driven wave that occurred before widespread vaccination. See the analysis in Scientific Reports.

Program objectives should be defined before selecting sequencing methods. A regional program in Andalusia, Spain established a coordinated surveillance circuit that organized sample collection through 27 hospitals, performed sequencing at three reference laboratories, and centralized data analysis at a bioinformatics platform. Between 2021 and 2025, this circuit sequenced over 42,500 SARS-CoV-2 genomes and tracked the transition from Alpha and Delta to successive Omicron waves. See the program description in Microorganisms.

Sample Selection and Collection Strategies

Clinical Sampling Approaches

Clinical sampling strategies determine the representativeness of genomic surveillance data. Baseline genomic surveillance typically sequences a proportion of all positive diagnostic samples, while sentinel surveillance focuses on specific populations such as hospitalized patients with severe acute respiratory infections. The Belgian comparison of these approaches found that sentinel surveillance accurately reflected variants of concern circulating in the population and provided a cost-effective solution for long-term genomic monitoring. See the comparison in Influenza and Other Respiratory Viruses.

Sample selection criteria should include cycle threshold (Ct) values from diagnostic RT-PCR testing. In the Republic of Congo, researchers screened 96 samples and selected 19 with Ct values below 30 for sequencing, successfully generating 11 complete genomes. See the methods in the International Journal of Infectious Diseases. In Rajasthan, India, a surveillance program processed 1757 samples with Ct values below 25 for the E and ORF genes, successfully determining lineages in 1624 samples. See the program details in the Indian Journal of Medical Microbiology.

Wastewater Sampling Approaches

Wastewater-based surveillance provides a complementary approach that captures community-level transmission without requiring individual clinical testing. A study in Mumbai, India collected wastewater samples from open drains and sewage treatment plants in vulnerable slum communities over an 11 month period. The study found correlations between wastewater viral concentrations and reported COVID-19 cases, with early detection occurring three weeks before clinical diagnoses. See the findings in The Indian Journal of Medical Research.

Wastewater surveillance requires careful consideration of sampling methods. A survey of Australian and New Zealand laboratories conducting government-funded wastewater pathogen surveillance found alignment on municipal wastewater treatment plant sampling and electromagnetic membrane filtration followed by RT-qPCR. However, the survey documented key differences in sample volumes, nucleic acid purification methods, validation approaches, and sequencing analysis methods. See the survey results in Environments.

A review of wastewater-based genomic surveillance approaches noted that the method enables rapid detection of known and emerging mutations and provides insights into circulating lineages. The review also identified challenges in sample processing and computational analysis, particularly in distinguishing similar lineages and identifying novel ones. See the review in Genome Biology.

Special Population Sampling

Genomic surveillance programs may target specific populations to address particular public health questions. A study in Lebanon collected 250 nasopharyngeal swabs from healthcare workers across the country between December 2021 and January 2022. The study identified Omicron BA.1.1 in 57.1% of samples, BA.1 in 18.9%, BA.2 in 12%, and Delta B.1.617.2 in 6.6%, demonstrating that Lebanon followed the global trend of Delta being rapidly replaced by Omicron. See the study in BMC Medical Genomics.

A surveillance program for migrants arriving in Europe through Mediterranean routes collected samples at entry points in Sicily from February 2021 to May 2022. The program obtained 472 full-length SARS-CoV-2 sequences and identified 12 unique clades belonging to 31 different lineages. The analysis identified 617 different amino acid substitutions, 156 amino acid deletions, 7 stop codons, and 6 amino acid insertions. See the program findings in the Journal of Global Health.

Sequencing Technologies and Platform Selection

Amplicon-Based Sequencing

Amplicon-based sequencing approaches use targeted PCR amplification of the viral genome before sequencing. The ARTIC Network amplicon tiling approach was used in the Belgian sentinel surveillance program on a MinION platform. This method amplifies overlapping tiled amplicons across the viral genome, enabling sequencing of samples with relatively high Ct values. See the methods in Influenza and Other Respiratory Viruses.

Whole Genome Sequencing Platforms

Illumina next-generation sequencing platforms have been widely used for SARS-CoV-2 genomic surveillance. The Republic of Congo study used Illumina NGS to sequence samples with Ct values below 30. See the methods in the International Journal of Infectious Diseases. The Lebanon healthcare worker study used the coronaHIT method for library preparation followed by whole genome sequencing on the Illumina NextSeq 500 platform. See the methods in BMC Medical Genomics.

Nanopore sequencing platforms offer real-time data generation and lower capital costs. A capacity development program in Guinea established a nanopore sequencing unit using the ONT MinION device. By July 2022, the laboratory had generated 238 SARS-CoV-2 consensus sequences with a median genomic recovery of 98.1% and a range of 90.5% to 99.4%. See the program description in Scientific Reports.

Platform Selection Criteria

Platform selection should consider sample throughput, turnaround time, cost per genome, bioinformatics requirements, and local technical capacity. The Guinea program demonstrated that nanopore sequencing can be successfully established in low-income countries through long-term mentorship and training programs. The program established a local hub for comprehensive sequencing training covering both wet-lab and bioinformatics components. See the capacity development model in Scientific Reports.

A rapid pathogen genomic surveillance workflow developed using Workflow Description Language processes input FASTA files and quality control files from Ion Torrent S5 sequencing, performs clade and variant assignments, integrates patient metadata, and stores results in a REDCap database. The workflow was designed so users with minimal informatics background can adapt it while creating a local data repository within their institution. See the workflow description in Genes.

Bioinformatics Analysis Pipeline

Lineage Assignment Tools

Lineage assignment is a core bioinformatics step in genomic surveillance. The Pangolin tool and Nextclade are the most commonly documented lineage assignment tools. The Republic of Congo study used both PANGOLIN and Nextclade to assign lineages, classifying sequences as lineage B.1 and Nextclade clades 20A and 20C. See the methods in the International Journal of Infectious Diseases. The Rajasthan program used Nextclade for lineage determination and phylogenetic tree construction. See the methods in the Indian Journal of Medical Microbiology.

The migrant surveillance program in Italy used both Nextclade and the Pangolin COVID-19 tools for clade and lineage assignment. See the methods in the Journal of Global Health.

Mutation Analysis

Mutation analysis identifies specific amino acid changes that may have functional significance. The Republic of Congo study used the web tool coronapp to annotate genomes and screen for mutations, identifying the spike mutation D614G in all sequenced genomes. See the methods in the International Journal of Infectious Diseases. The Dominican Republic study also used coronapp and Genome Detective Viral Tools to monitor epidemiological characteristics, finding that D614G was the most frequent non-synonymous mutation over the study period. See the methods in the International Journal of Environmental Research and Public Health.

Phylogenetic Analysis

Phylogenetic analysis places local sequences within a global context and can identify transmission chains and introduction events. The Bangladesh strategic framework used phylogenetic analyses to place local SARS-CoV-2 variants within a global context, indicating that the Delta variant likely entered from India and Omicron from Europe. See the framework description in Influenza and Other Respiratory Viruses.

The Dominican Republic study used maximum likelihood methods and Bayesian Markov chain Monte Carlo approaches to analyze phylogenetic relationships and evolution rates. The mean mutation rate was estimated at 1.5523 x 10^-3 nucleotide substitutions per site with a 95% highest posterior density interval of 1.2358 x 10^-3 to 1.8635 x 10^-3. See the methods in the International Journal of Environmental Research and Public Health.

Automated Pipeline Considerations

Automated pipelines reduce the bioinformatics burden for surveillance laboratories. The WDL-based workflow described in Genes combines multiple analysis steps with human-readable syntax, allowing users with minimal informatics background to adapt the workflow. The pipeline processes input FASTA files and quality control files, performs clade and variant assignments, integrates patient metadata, and stores results in a REDCap database. An interactive dashboard connects with the REDCap data sources to provide real-time monitoring and interactive visualization.

Data Quality Controls and Validation

Sequencing Quality Metrics

Quality control begins with sample selection and continues through sequencing and analysis. The Guinea program reported a median genomic recovery of 98.1% with a range of 90.5% to 99.4%, demonstrating that high-quality consensus genomes can be generated in resource-limited settings. See the quality metrics in Scientific Reports.

The Rajasthan program processed 1757 samples and successfully determined lineages in 1624 samples, representing a success rate of approximately 92.4%. See the quality metrics in the Indian Journal of Medical Microbiology.

Cross-Method Validation

Validation of sequencing results against independent methods strengthens confidence in surveillance data. The Chicago regional public health laboratory response playbook supplemented whole genome sequencing with variant screening by quantitative PCR. Genotyping qPCR concurred with WGS lineage assignments in 99.9% of 1541 samples with results by both methods. The qPCR approach was more sensitive, providing lineage results in 90.4% of 1833 samples compared to 85.1% for WGS, while significantly reducing the time to lineage result. See the validation results in BMC Public Health.

Data Completeness and Metadata Standards

Complete metadata is essential for interpreting genomic surveillance data. The Lebanon healthcare worker study collected data on the date of positive PCR, vaccination status, specific occupation, and hospitalization status of participants. See the data collection methods in BMC Medical Genomics.

The FAIR Guiding Principles provide a framework for data management and stewardship. The principles emphasize that data should be findable, accessible, interoperable, and reusable. See the guiding principles in Scientific Data.

Data Sharing and Repository Submission

Public Repository Submission

Submission of genomic sequences to public repositories enables global comparison and collaborative analysis. The Republic of Congo study submitted 11 successfully sequenced genomes to the GISAID database. See the submission details in the International Journal of Infectious Diseases. The Guinea program generated consensus genomes for variant typing and GISAID submission. See the submission process in Scientific Reports.

The Dominican Republic study obtained 1149 SARS-CoV-2 complete genome nucleotide sequences from the GISAID database for analysis, demonstrating the value of public repositories for retrospective epidemiological studies. See the data source in the International Journal of Environmental Research and Public Health.

Data Sharing Policies

Data sharing policies govern the deposition and use of genomic data. The National Institutes of Health Genomic Data Sharing Policy establishes expectations for the sharing of genomic data generated through NIH-funded research. See the policy at sharing.nih.gov.

The NCBI provides data resources for the deposition and retrieval of genomic sequences. See the available resources at ncbi.nlm.nih.gov. The EMBL-EBI offers training resources for bioinformatics analysis. See the training materials at ebi.ac.uk/training.

Public Health Reporting and Integration

Surveillance Report Structure

A genomic surveillance report should communicate findings to both technical and non-technical audiences. The report should include the number of samples sequenced, the lineages identified, the proportion of each lineage over time, and any novel or concerning variants detected. The report should also describe the sampling strategy, sequencing methods, and quality metrics so that readers can assess the reliability of the findings.

The Rajasthan program demonstrated the value of enhanced genomic surveillance for public health reporting. After the WHO designated XBB.1.16 as a variant under monitoring in March 2023, the program monitored all positive SARS-CoV-2 samples for genetic changes. XBB.1.16 was the predominant lineage in 1413 of 1624 sequenced samples, representing 87.0% of cases. The program reported that 84.15% of XBB.1.16 cases were first-time infections, hospitalization was required in only 2.2% of cases, and death was reported in 5 patients. See the reporting details in the Indian Journal of Medical Microbiology.

Integration with Epidemiological Data

Genomic surveillance data gains public health value when integrated with epidemiological information. The Uruguay study integrated genomic data with vaccination records, variant surveillance, and epidemiological information at regional and global scales. See the integration approach in Scientific Reports.

The Bangladesh strategic framework involved collaboration across 4 major institutes and 13 hospitals nationwide. The program sequenced over 2200 genomes and documented the prevalence of the Delta variant initially, followed by the emergence of Omicron variants BA.1, BA.2, BA.5, and XBB. The clinical manifestations of the variants differed, with some symptoms occurring more frequently in Delta cases. See the collaboration structure in Influenza and Other Respiratory Viruses.

Response Playbooks

Predefined response playbooks can streamline the transition from routine surveillance to enhanced surveillance when a new variant is detected. The Chicago regional public health laboratory developed a genomic surveillance response playbook that outlines modifications to sampling strategies, laboratory workflows, and communication processes based on the emerging variant's predicted viral characteristics, observed public health impact in other jurisdictions, and local community risk level. The playbook outlines procedures for implementing enhanced and accelerated genomic surveillance, including supplementing WGS with variant screening by qPCR. See the playbook description in BMC Public Health.

Common Failure Patterns and Mitigation Strategies

Sampling Bias

Sampling bias occurs when the samples selected for sequencing do not represent the broader population. Sentinel surveillance may miss variants that cause mild disease, as demonstrated by the failure to detect Omicron BA.3 in the Belgian SARI surveillance program. See the limitation in Influenza and Other Respiratory Viruses. Mitigation strategies include combining multiple surveillance approaches and periodically evaluating the representativeness of the sampling strategy.

Low Sequencing Success Rates

Low sequencing success rates can result from poor sample quality, high Ct values, or technical issues. The Republic of Congo study successfully sequenced 11 of 19 selected samples, representing a success rate of approximately 57.9%. See the results in the International Journal of Infectious Diseases. Mitigation strategies include establishing Ct value thresholds for sample selection and implementing quality control checks throughout the sequencing workflow.

Bioinformatics Bottlenecks

Bioinformatics analysis can become a bottleneck in surveillance programs, particularly when staff lack specialized training. The WDL-based workflow described in Genes was designed to address this challenge by using human-readable syntax that users with minimal informatics background can adapt. The Guinea program established a local hub for comprehensive sequencing training covering both wet-lab and bioinformatics components. See the training model in Scientific Reports.

Data Reporting Delays

Delays in data reporting reduce the public health utility of genomic surveillance. The Chicago playbook was designed to reduce the time to lineage result by supplementing WGS with qPCR screening. See the approach in BMC Public Health.

Limitations and Interpretation Constraints

Incomplete Case Ascertainment

Genomic surveillance programs capture only a fraction of total infections. The Guinea program sequenced 238 genomes representing 0.64% of the 37,464 confirmed cases reported in the country as of July 2022. See the coverage data in Scientific Reports. Low sampling fractions may miss rare variants or delay the detection of emerging lineages.

Wastewater Lineage Deconvolution

Wastewater surveillance presents unique analytical challenges. The review in Genome Biology noted that wastewater sequencing methods remain largely untested amid declining clinical surveillance and ongoing viral evolution. Distinguishing similar lineages and identifying novel ones in mixed wastewater samples requires specialized computational approaches.

Resource Constraints

Genomic surveillance programs face significant resource constraints, particularly in low-income settings. A review of genomic surveillance inequities noted that fragile settings are critical to global health security. See the review in New Microbes and New Infections. The Guinea program demonstrated that long-term mentorship and training can build local capacity, but sustained investment is required.

Evolving Viral Dynamics

The utility of genomic surveillance depends on ongoing viral evolution. The review of wastewater-based genomic surveillance noted that methods developed during the pandemic may need adaptation as the virus continues to evolve. See the review in Genome Biology.

Professional Escalation Criteria

Public health professionals should escalate findings when genomic surveillance data indicates a potential threat. Escalation criteria include the detection of a novel variant with concerning mutations, evidence of increased transmissibility or severity, detection of variants with potential immune escape, and unusual clustering of cases suggesting a transmission chain.

The Rajasthan program demonstrated the importance of enhanced surveillance after the WHO designation of XBB.1.16 as a variant under monitoring. The program rapidly identified the spread of the XBB variant, which helped authorities take control measures to prevent spread and estimate public health risks relative to previously circulating lineages. See the escalation example in the Indian Journal of Medical Microbiology.

The genomic surveillance circuit in Andalusia demonstrated the value of integrating genomic and epidemiological data for rapid variant detection, outbreak investigation, and public health decision making. See the integration example in Microorganisms.

Records and Measurements for Program Management

Core Metrics to Track

Surveillance programs should maintain records of key operational metrics. These include the number of samples collected, the number successfully sequenced, the median turnaround time from sample collection to lineage assignment, the proportion of sequences submitted to public repositories, and the proportion of sequences with complete metadata.

Quality Control Records

Quality control records should document sequencing success rates, genome coverage metrics, and validation results. The Guinea program reported a median genomic recovery of 98.1% with a range of 90.5% to 99.4%. See the quality metrics in Scientific Reports. The Chicago program documented that qPCR concurred with WGS lineage assignments in 99.9% of samples with results by both methods. See the validation data in BMC Public Health.

Lineage Prevalence Tracking

Programs should track lineage prevalence over time to identify shifts in circulating variants. The Dominican Republic study classified 870 of 1149 samples into 8 relevant variants according to Pangolin and Scorpio, with the first variants being monitored detected in December 2020 and variants of concern Delta and Omicron identified in 2021. See the lineage tracking in the International Journal of Environmental Research and Public Health.

Frequently Asked Questions

What is the difference between baseline genomic surveillance and sentinel surveillance?

Baseline genomic surveillance sequences a proportion of all positive diagnostic samples to capture broad population-level diversity. Sentinel surveillance focuses on specific populations, such as hospitalized patients with severe acute respiratory infections. A Belgian study found that sentinel surveillance detected major variants of concern with no more than a two week delay compared to baseline surveillance, but missed minor variants such as Omicron BA.3. See the comparison in Influenza and Other Respiratory Viruses.

How should samples be selected for genomic surveillance?

Sample selection should prioritize specimens with low Ct values from diagnostic RT-PCR testing. The Republic of Congo study selected samples with Ct values below 30 for sequencing. See the selection criteria in the International Journal of Infectious Diseases. The Rajasthan program used a Ct value threshold below 25 for the E and ORF genes. See the selection criteria in the Indian Journal of Medical Microbiology.

What bioinformatics tools are used for lineage assignment?

The Pangolin tool and Nextclade are the most commonly documented lineage assignment tools. The Republic of Congo study used both PANGOLIN and Nextclade. See the tools in the International Journal of Infectious Diseases. The migrant surveillance program in Italy also used both tools for clade and lineage assignment. See the tools in the Journal of Global Health.

How does wastewater surveillance compare to clinical surveillance?

Wastewater surveillance captures community-level transmission without requiring individual clinical testing. A study in Mumbai found that wastewater surveillance detected SARS-CoV-2 three weeks before clinical diagnoses. See the comparison in The Indian Journal of Medical Research. Wastewater surveillance requires specialized processing and computational analysis to distinguish lineages in mixed samples. See the challenges in Genome Biology.

What quality metrics should be tracked in a genomic surveillance program?

Programs should track sequencing success rates, genome coverage, and validation results. The Guinea program reported a median genomic recovery of 98.1%. See the quality metrics in Scientific Reports. The Chicago program documented that qPCR concurred with WGS lineage assignments in 99.9% of samples with results by both methods. See the validation data in BMC Public Health.

How should genomic surveillance data be shared?

Sequences should be submitted to public repositories such as GISAID to enable global comparison. The Republic of Congo study submitted genomes to GISAID. See the submission in the International Journal of Infectious Diseases. Data sharing should follow established policies such as the NIH Genomic Data Sharing Policy. See the policy at sharing.nih.gov.

What are the limitations of genomic surveillance in low-income settings?

Low-income settings face challenges including inadequate molecular and sequencing capabilities, limited vaccine storage, and workforce shortages. The migrant surveillance program in Italy noted that genomic-based surveillance in low-income countries represents a challenge for public health. See the challenges in the Journal of Global Health. The Guinea program demonstrated that long-term mentorship and training can build local capacity. See the capacity development model in Scientific Reports.

When should a public health response be escalated based on genomic surveillance data?

Escalation is appropriate when surveillance detects a novel variant with concerning mutations, evidence of increased transmissibility or severity, or potential immune escape. The Rajasthan program demonstrated enhanced surveillance after the WHO designated XBB.1.16 as a variant under monitoring. See the escalation example in the Indian Journal of Medical Microbiology. The Chicago playbook provides a structured approach to escalating surveillance when a new variant is detected. See the playbook in BMC Public Health.

Related Bioinformatics Guides

• The World Health Organization (WHO) and Global Genomic Surveillance
• Structural Dynamics of SARS-CoV-2 Spike Protein: Computational Insights into Immune Evasion
• Predicting AMR from Genomic Data
• Data Sharing and Privacy in Genomic Research
• Alternative Splicing Analysis from RNA-Seq Data

References and Further Reading

• EMBL-EBI Training. European Bioinformatics Institute.
• NCBI Data Resources. National Center for Biotechnology Information.
• Genomic Data Sharing Policy. National Institutes of Health.
• The FAIR Guiding Principles. Scientific Data.
• Genomic monitoring of SARS-CoV-2 variants using sentinel SARI hospital surveillance.. Influenza and other respiratory viruses, 2023.
• Genomic surveillance of SARS-CoV-2 in the Republic of Congo.. International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 2021.
• Genomic surveillance of SARS-CoV-2 in COVID-19 vaccinated healthcare workers in Lebanon.. BMC medical genomics, 2023.
• Wastewater-based genomic surveillance of SARS-CoV-2 in vulnerable communities in Mumbai.. The Indian journal of medical research, 2024.
• Genomic surveillance of SARS-CoV-2 and emergence of XBB.1.16 variant in Rajasthan.. Indian journal of medical microbiology, 2024.
• SARS-CoV-2 genomic surveillance of migrants arriving to Europe through the Mediterranean routes.. Journal of global health, 2024.
• A Strategic Framework of SARS-CoV-2 Genomic Surveillance in Bangladesh.. Influenza and other respiratory viruses, 2024.
• Genomic Surveillance of SARS-CoV-2 Variants in the Dominican Republic and Emergence of a Local Lineage.. International journal of environmental research and public health, 2023.
• From Bench to Insight: Rapid Pathogen Genomic Surveillance Workflow for SARS-CoV-2 and Emerging Pathogens. 2026.
• From Bench to Insight: Rapid Pathogen Genomic Surveillance Workflow for SARS-CoV-2 and Emerging Pathogens.. 2026.
• Genomic surveillance inequities in emerging infectious diseases: Why fragile settings like Somalia are critical to global health security.. 2026.
• SARS-CoV-2 wastewater genomic surveillance: approaches, challenges, and opportunities.. 2026.
• Two years of genomic surveillance capacity development in Guinea: an operational roadmap for local implementation in low-income countries and tracking of SARS-CoV-2 circulation dynamics. 2026.
• Two years of SARS-CoV-2 genomic surveillance capacity development in Guinea.. 2026.
• Wastewater genomic surveillance identifies the emergence of the SARS-CoV-2 JN.1 lineage in urban settings of Gujarat
• Impact of timely vaccination and genomic surveillance on controlling consecutive waves of SARS-CoV-2 variants.. 2026.
• Public health surveillance and outbreak preparedness for mpox. Current Opinion in HIV and AIDS, 2025.
• A Genomic Surveillance Circuit for Emerging Viral Pathogens. Microorganisms, 2025.
• Australian and New Zealand Laboratory Experience and Proposed Future Direction of Wastewater Pathogen Genomic Surveillance. Environments, 2025.
• A response playbook for early detection and population surveillance of new SARS-CoV-2 variants in a regional public health laboratory. BMC Public Health, 2023.
• Transforming Public Health Surveillance: Big Data Integration and Predictive Decision-Making in the Digital Era. IECCMEXICO, 2026.
• Challenges and innovations in real-time infectious disease surveillance: A U.S. public health infrastructure perspective. Magna Scientia Advanced Research and Reviews, 2026.
• Integrated genomic surveillance enables tracing of person-to-person SARS-CoV-2 transmission chains during community transmission and reveals extensive onward transmission of travel-imported infections, Germany, June to July 2021. Eurosurveillance, 2022.
• Overview of genomic surveillance related to Severe Acute Respiratory Syndrom Coronavirus 2 (SARS- CoV-2). E3s Web of Conferences, 2021.
• DeepSARS: simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2. BMC Genomics, 2022.
• Evaluation of sampling methods for genomic surveillance of SARS-CoV-2 variants in aircraft wastewater: advancing global early-warning systems for future pandemics. Frontiers in Microbiology, 2025.
• Passive sampling for genomic surveillance of SARS-CoV-2 in wastewater resource recovery facility: Insights for pandemic preparedness. Water Research, 2025.

This article is educational and does not replace validated analysis plans, institutional policy, clinical interpretation, or specialist review.