A global aircraft-based wastewater genomic surveillance network for early warning of future pandemics

Optimization and performance analytics of global aircraft-based wastewater surveillance networks

Aircraft wastewater surveillance has been proposed as a novel approach to monitor the global spread of pathogens. Here we develop a computational framework to provide actionable information for designing and estimating the effectiveness of global aircraft-based wastewater surveillance networks (WWSNs). We study respiratory diseases of varying transmission potentials and find that networks of 10 to 20 strategically placed wastewater sentinel sites can provide timely situational awareness and function effectively as an early warning system. The model identifies potential blind spots and suggests optimization strategies to increase WWSNs effectiveness while minimizing resource use. Our findings highlight that increasing the number of sentinel sites beyond a critical threshold does not proportionately improve WWSNs capabilities, stressing the importance of resource optimization. We show through retrospective analyses that WWSNs can significantly shorten the detection time for emerging pathogens. The presented approach offers a realistic analytic framework for the analysis of WWSNs at airports.

Wastewater disinfection with photodynamic treatment and evaluation of its ecotoxicological effects

Research has demonstrated the presence of viruses in wastewater (WW), which can remain viable for a long period, posing potential health risks. Conventional WW treatment methods involving UV light, chlorine and ozone efficiently reduce microbial concentrations, however, they produce hazardous byproducts and microbial resistance that are detrimental to human health and the ecosystem. Hence, there is a need for novel disinfection techniques. Antimicrobial Photodynamic Inactivation (PDI) emerges as a promising strategy, utilizing photosensitizers (PS), light, and dioxygen to inactivate viruses. This study aims to assess the efficacy of PDI by testing methylene blue (MB) and the cationic porphyrin TMPyP as PSs, along a low energy consuming white light source (LED) at an irradiance of 50 mW/cm2, for the inactivation of bacteriophage Phi6. Phi6 serves as an enveloped RNA-viruses surrogate model in WW. PDI experiments were conducted in a buffer solution (PBS) and real WW matrices (filtered and non-filtered). Considering the environmental release of the treated effluents, this research also evaluated the ecotoxicity of the resulting solution (post-PDI treatment effluent) on the model organism Daphnia magna, following the Organisation for Economic Cooperation and Development (OECD) immobilization technical 202 guideline. Daphnids were exposed to WW containing the tested PS at different concentrations and dilutions (accounting for the dilution factor during WW release into receiving waters) over 48 h. The results indicate that PDI with MB efficiently inactivated the model virus in the different aqueous matrices, achieving reductions superior to 8 log10 PFU/mL, after treatments of 5 min in PBS and of ca. 90 min in WW. Daphnids survival increased when subjected to the PDI-treated WW with MB, considering the dilution factor. Overall, the effectiveness of PDI in eliminating viruses in WW, the fading of the toxic effects on daphnids after MB' irradiation and the rapid dilution effect upon WW release in the environment highlight the possibility of using MB in WW PDI-disinfection.

Infectious disease surveillance needs for the United States: lessons from Covid-19

The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform evidence-based public health guidance and policies. Here, we discuss requirements for an effective surveillance system to support decision making during a pandemic, drawing on the lessons of COVID-19 in the U.S., while looking to jurisdictions in the U.S. and beyond to learn lessons about the value of specific data types. In this report, we define the range of decisions for which surveillance data are required, the data elements needed to inform these decisions and to calibrate inputs and outputs of transmission-dynamic models, and the types of data needed to inform decisions by state, territorial, local, and tribal health authorities. We define actions needed to ensure that such data will be available and consider the contribution of such efforts to improving health equity.

RBD amplicon sequencing of wastewater reveals patterns of variant emergence and evolution

Rapid evolution of SARS-CoV-2 has resulted in the emergence of numerous variants, posing significant challenges to public health surveillance. Clinical genome sequencing, while valuable, has limitations in capturing the full epidemiological dynamics of circulating variants in the general population. This study utilized receptor-binding domain (RBD) amplicon sequencing of wastewater samples to monitor the SARS-CoV-2 community dynamics and evolution in El Paso, TX. Over 17 months, we identified 91 variants and observed waves of dominant variants transitioning from BA.2 to BA.2.12.1, BA.4&5, BQ.1, and XBB.1.5. Our findings demonstrated early detection of variants and identification of unreported outbreaks, while showing strong consistency with clinical genome sequencing data at the local, state, and national levels. Alpha diversity analyses revealed significant periodical variations, with the highest diversity observed in winter and the outbreak lag phases, likely due to lower competition among variants before the outbreak growth phase. The data underscores the importance of low transmission periods for rapid mutation and variant evolution. This study highlights the effectiveness of integrating RBD amplicon sequencing with wastewater surveillance in tracking viral evolution, understanding variant emergence, and enhancing public health preparedness.

Assessment of nucleic acid extraction protocols for antibiotic resistance genes (ARGs) quantification in aircraft wastewater

This study evaluated ten nucleic acid extraction protocols (EP1 to EP10) for measuring five endogenous antibiotic resistance genes (ARGs) in four aircraft wastewater samples (AWW1 to AWW4). The targeted ARGs, including blaCTX-M, blaNDM-1, ermB, qnrS, and tetA, encompassed highly and minimally abundant ARGs. TetA and ermB were consistently detected across four aircraft wastewater samples using the DNeasy Blood and Tissue Kit and the AllPrep PowerViral DNA/RNA kit. QnrS displayed high detection rates with specific extraction protocols and aliquot volumes. Concentrations of ARGs varied across aircraft wastewater samples, with differing extraction protocols influencing quantitative results. The concentrations of tetA, ermB, and qnrS in AWW1 were distinct, while AWW2 to AWW4 exhibited a broader range for tetA, ermB, qnrS, blaCTX-M, and blaNDM-1. EP1 consistently produced the highest concentrations for several ARGs. Collective data analysis revealed varying ARG concentrations across the ten extraction protocols, suggesting the importance of careful extraction protocol selection in ARG monitoring in aircraft wastewater samples. Based on the results, we suggest that a small sample volume (as low as 0.2 mL) may be sufficient for ARG characterization in aircraft wastewater samples. The findings also emphasize the need for considering toilet paper removal without compromising nucleic acid extraction efficiency. The study highlights promising prospects for aircraft wastewater monitoring of ARGs, calling for further investigation into the import and spread of unique ARGs through transport hubs.

Long-term wastewater monitoring of SARS-CoV-2 viral loads and variants at the major international passenger hub Amsterdam Schiphol Airport: A valuable addition to COVID-19 surveillance

Wastewater-based epidemiological surveillance at municipal wastewater treatment plants has proven to play an important role in COVID-19 surveillance. Considering international passenger hubs contribute extensively to global transmission of viruses, wastewater surveillance at this type of location may be of added value as well. The aim of this study is to explore the potential of long-term wastewater surveillance at a large passenger hub as an additional tool for public health surveillance during different stages of a pandemic. Here, we present an analysis of SARS-CoV-2 viral loads in airport wastewater by reverse-transcription quantitative polymerase chain reaction (RT-qPCR) from the beginning of the COVID-19 pandemic in Feb 2020, and an analysis of SARS-CoV-2 variants by whole-genome next-generation sequencing from Sep 2020, both until Sep 2022, in the Netherlands. Results are contextualized using (inter)national measures and data sources such as passenger numbers, clinical surveillance data and national wastewater surveillance data. Our findings show that wastewater surveillance was possible throughout the study period, irrespective of measures, as viral loads were detected and quantified in 98.6 % (273/277) of samples. Emergence of SARS-CoV-2 variants, identified in 91.0 % (161/177) of sequenced samples, coincided with increases in viral loads. Furthermore, trends in viral load and variant detection in airport wastewater closely followed, and in some cases preceded, trends in national daily average viral load in wastewater and variants detected in clinical surveillance. Wastewater-based epidemiology at a large international airport is a valuable addition to classical COVID-19 surveillance and the developed expertise can be applied in pandemic preparedness plans for other (emerging) pathogens in the future.

Leveraging wastewater surveillance for managing the spread of SARS-CoV-2 and concerned pathogens during FIFA World Cup Qatar 2022

Wastewater-based epidemiology (WBE) has been proven effective for the monitoring of infectious disease outbreaks during mass gathering events and for timely public health interventions. As part of Qatar's efforts to monitor and combat the spread of infectious diseases during the FIFA World Cup Qatar 2022™ (FWC'22), wastewater surveillance was used to monitor the spread of SARS-CoV-2, human enterovirus, and poliovirus. The screening covered five major wastewater treatment plants servicing the event locations between October 2022 and January 2023. Viruses were concentrated from the wastewater samples by PEG precipitation, followed by qRT-PCR to measure the viral load in the wastewater. As expected, SARS-CoV-2 and enterovirus RNA were detected in all samples, while poliovirus was not detected. The concentration of SARS-CoV-2 was correlated with population density, such as areas surrounding the World Cup venues, and with the number of reported clinical cases. Additionally, we observed temporal fluctuations in viral RNA concentrations, with peak levels coinciding with the group stage matches of the FWC'22. This study has been useful in providing public health authorities with an efficient and cost-effective surveillance system for potential infectious disease outbreaks during mega-events.

Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data

Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity, which can be used to identify viral lineages (including variants of concern) that are circulating in a local population. Capturing the genetic diversity by WBS sequencing is not trivial, as wastewater samples often contain a diverse mixture of viral lineages with real mutations and sequencing errors, which must be deconvoluted computationally from short sequencing reads. In this study we assess nine different computational tools that have recently been developed to address this challenge. We simulated 100 wastewater sequence samples consisting of SARS-CoV-2 BA.1, BA.2, and Delta lineages, in various mixtures, as well as a Delta-Omicron recombinant and a synthetic 'novel' lineage. Most tools performed well in identifying the true lineages present and estimating their relative abundances and were generally robust to variation in sequencing depth and read length. While many tools identified lineages present down to 1 % frequency, results were more reliable above a 5 % threshold. The presence of an unknown synthetic lineage, which represents an unclassified SARS-CoV-2 lineage, increases the error in relative abundance estimates of other lineages, but the magnitude of this effect was small for most tools. The tools also varied in how they labelled novel synthetic lineages and recombinants. While our simulated dataset represents just one of many possible use cases for these methods, we hope it helps users understand potential sources of error or bias in wastewater sequencing analysis and to appreciate the commonalities and differences across methods.

Advancing pathogen genomics in resource-limited settings

Genomic sequencing has emerged as a powerful tool to enhance early pathogen detection and characterization with implications for public health and clinical decision making. Although widely available in developed countries, the application of pathogen genomics among low-resource, high-disease burden settings remains at an early stage. In these contexts, tailored approaches for integrating pathogen genomics within infectious disease control programs will be essential to optimize cost efficiency and public health impact. We propose a framework for embedding pathogen genomics within national surveillance plans across a spectrum of surveillance and laboratory capacities. We adopt a public health approach to genomics and examine its application to high-priority diseases relevant in resource-limited settings. For each grouping, we assess the value proposition for genomics to inform public health and clinical decision-making, alongside its contribution toward research and development of novel diagnostics, therapeutics, and vaccines.

Travel vaccines-priorities determined by incidence and impact

BACKGROUND

Infectious disease epidemiology is continuously shifting. While travel has been disrupted by the COVID-19 pandemic and travel-related epidemiological research experienced a pause, further shifts in vaccine-preventable diseases (VPDs) relevant for travellers have occurred.

METHODS

We conducted a literature search on the epidemiology of travel-related VPD and synthesized data for each disease with a focus on symptomatic cases and on the impact of the respective infection among travellers, considering the hospitalization rate, disease sequela and case fatality rate. We present new data and revised best estimates on the burden of VPD relevant for decisions on priorities in travel vaccines.

RESULTS

COVID-19 has emerged to be a top travel-related risk and influenza remains high in the ranking with an estimated incidence at 1% per month of travel. Dengue is another commonly encountered infection among international travellers with estimated monthly incidence of 0.5-0.8% among non-immune exposed travellers; the hospitalized proportion was 10 and 22%, respectively, according to two recent publications. With recent yellow fever outbreaks particularly in Brazil, its estimated monthly incidence has risen to >0.1%. Meanwhile, improvements in hygiene and sanitation have led to some decrease in foodborne illnesses; however, hepatitis A monthly incidence remains substantial in most developing regions (0.001-0.01%) and typhoid remains particularly high in South Asia (>0.01%). Mpox, a newly emerged disease that demonstrated worldwide spread through mass gathering and travel, cannot be quantified regarding its travel-related risk.

CONCLUSION

The data summarized may provide a tool for travel health professionals to prioritize preventive strategies for their clients against VPD. Updated assessments on incidence and impact are ever more important since new vaccines with travel indications (e.g. dengue) have been licensed or are undergoing regulatory review.

Stability of SARS-CoV-2 on Commercial Aircraft Interior Surfaces with Implications for Effective Control Measures

BACKGROUND

The COVID-19 pandemic from 2019 to 2022 devastated many aspects of life and the economy, with the commercial aviation industry being no exception. One of the major concerns during the pandemic was the degree to which the internal aircraft environment contributed to virus transmission between humans and, in particular, the stability of SARS-CoV-2 on contact surfaces in the aircraft cabin interior.

METHOD

In this study, the stability of various major strains of SARS-CoV-2 on interior aircraft surfaces was evaluated using the TCID50 assessment.

RESULTS

In contrast to terrestrial materials, SARS-CoV-2 was naturally less stable on common contact points in the aircraft interior, and, over a 4 h time period, there was a 90% reduction in culturable virus. Antiviral and surface coatings were extremely effective at mitigating the persistence of the virus on surfaces; however, their benefit was diminished by regular cleaning and were ineffective after 56 days of regular use and cleaning. Finally, successive strains of SARS-CoV-2 have not evolved to be more resilient to survival on aircraft surfaces.

CONCLUSIONS

We conclude that the mitigation strategies for SARS-CoV-2 on interior aircraft surfaces are more than sufficient, and epidemiological evidence over the past three years has not found that surface spread is a major route of transmission.