Wastewater surveillance for public health

Statistical Relationship Between Wastewater Data and Case Notifications for COVID-19 Surveillance in the United States From 2020 to 2023: Bayesian Hierarchical Modeling Approach

Background

During the COVID-19 pandemic, several US jurisdictions began to regularly report levels of SARS-CoV-2 in wastewater as a proxy for SARS-CoV-2 incidence. Despite the promise of this approach for improving COVID-19 situational awareness, the degree to which wastewater surveillance data agree with other data has varied, and better evidence is needed to understand the situations in which wastewater surveillance data track closely with traditional surveillance data.

Objective

In this study, we quantified the statistical relationship between wastewater data and traditional case-based surveillance data for multiple jurisdictions.

Methods

We collated data on wastewater SARS-CoV-2 RNA levels and COVID-19 case reports from July 2020 to March 2023 for 107 counties representing a range in terms of geographic location, population size, and urbanicity. For these counties, we used Bayesian hierarchical regression modeling to estimate the statistical relationship between wastewater data and reported cases, allowing for variation in this relationship across counties. We compared different model structural approaches and assessed how the strength of the estimated relationships varied between settings and over time.

Results

Our analyses revealed a strong positive relationship between wastewater data and COVID-19 cases for the majority of locations, with a median correlation coefficient between observed and predicted cases of 0.904 (IQR 0.823-0.943). In total, 23/107 counties (21.5%) had correlation coefficients below 0.8, and 3/107 (2.8%) had values below 0.6. Across locations, the COVID-19 case rate associated with a given level of wastewater SARS-CoV-2 RNA concentration declined over the study period. Counties with greater population size (P<.001) and higher levels of urbanicity (P<.001) had stronger concordance between wastewater data and COVID-19 cases. Measures of model fit, and relationships with urbanicity and population size, were robust to sensitivity analyses in which we varied the time period of analysis and the sample of counties used for model fitting.

Conclusions

In a sample of 107 US counties, wastewater surveillance had a close relationship with COVID-19 cases reported for the majority of locations, with these relationships found to be stronger in counties with greater population size and urbanicity. In situations where routine COVID-19 surveillance data are less reliable, wastewater surveillance may be used to track local SARS-CoV-2 incidence trends.

Wastewater surveillance of antibiotic-resistant bacteria for public health action: potential and challenges

Antibiotic resistance is an urgent public health threat. Actions to reduce this threat include requiring prescriptions for antibiotic use, antibiotic stewardship programs, educational programs targeting patients and healthcare providers, and limiting antibiotic use in agriculture, aquaculture, and animal husbandry. Wastewater surveillance might complement clinical surveillance by tracking time/space variation essential for detecting outbreaks and evaluating efficacy of evidence-based interventions, identifying high-risk populations for targeted monitoring, providing early warning of the emergence and spread of antibiotic-resistant bacteria (ARBs), and identifying novel antibiotic-resistant threats. Wastewater surveillance was an effective early warning system for SARS-CoV-2 spread and detection of the emergence of new viral strains. In this data-driven commentary, we explore whether monitoring wastewater for antibiotic-resistant genes (ARGs) and/or bacteria resistant to antibiotics might provide useful information for public health action. Using carbapenem resistance as an example, we highlight technical challenges associated with using wastewater to quantify temporal/spatial trends in ARBs and ARGs and compare with clinical information. While ARGs and ARBs are detectable in wastewater enabling early detection of novel ARGs, quantitation of ARBs and ARGs with current methods is too variable to reliably track space/time variation.

Immunological drivers of zoonotic virus emergence, evolution, and endemicity

The disruption of natural ecosystems caused by climate change and human activity is amplifying the risk of zoonotic spillover, presenting a growing global health threat. In the past two decades, the emergence of multiple zoonotic viruses has exposed critical gaps in our ability to predict epidemic trajectories and implement effective interventions. RNA viruses, in particular, are challenging to control due to their high mutation rates and ability to adapt and evade immune defenses. To better prepare for future outbreaks, it is vital that we deepen our understanding of the factors driving viral emergence, transmission, and persistence in human populations. Specifically, deciphering the interactions between antibody-mediated immunity and viral evolution will be key. In this perspective, we explore these dynamic relationships and highlight research priorities that may guide the development of more effective strategies to mitigate the impact of emerging infectious diseases.

Characterization of bioaerosol exposures in wastewater treatment plant workers and serum levels of lung and inflammatory markers

Wastewater treatment plant (WWTP) workers are exposed to bioaerosols containing bacteria, fungi, and endotoxin, potentially posing health risks to workers. This study quantified personal exposure levels to airborne bacteria and fungi, endotoxin, and dust among 44 workers during two seasons at four WWTPs. Associations between the exposure measurements and serum levels of biomarkers CRP, SAA, and CC16 were also assessed. The potential deposition of viable microorganisms in workers' airways were explored using stationary fractionating samplers. Microbial communities were characterized using long-read nanopore amplicon sequencing and MALDI-TOF mass spectrometry to identify species, including pathogenic or allergenic microorganisms. We found that bacterial and fungal exposure levels were significantly associated with work task (p < 0.001 and p = 0.00041, respectively), with high exposure variability within and between tasks. Workshop, sewer system inspection, and sewer cleaning were associated with the highest exposure levels. A significant positive correlation was found between CRP and bacterial exposure (p = 0.013), while significant negative correlations were found between CRP and endotoxin and dust exposures (p = 0.012 and p = 0.018, respectively). No significant associations were found between SAA or CC16 and the exposure measures. Microbial community composition in bioaerosols differed significantly between some work tasks while others showed similar compositions. Viable hazardous microorganisms such as Clostridium perfringens and Aspergillus fumigatus were found in workers' exposures and in respiratory fractions of stationary air samples, indicating potential lung deposition. Further research is needed to assess possible long-term health risks from bioaerosol exposure at WWTPs.

Advances in the Management of Infectious Diseases

The landscape of infectious diseases has dramatically evolved since the 1970s and the advent of antimicrobials, which heralded a new era in medical history [...].

Pandemic monitoring with global aircraft-based wastewater surveillance networks

Aircraft wastewater surveillance has been proposed as a new approach to monitor the global spread of pathogens. Here we develop a computational framework providing actionable information for the design and estimation of the effectiveness of global aircraft-based wastewater surveillance networks (WWSNs). We study respiratory diseases of varying transmission potential and find that networks of 10-20 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 WWSN effectiveness while minimizing resource use. Our findings indicate that increasing the number of sentinel sites beyond a critical threshold does not proportionately improve WWSN capabilities, emphasizing the importance of resource optimization. We show, through retrospective analyses, that WWSNs can notably shorten detection time for emerging pathogens. The approach presented offers a realistic analytic framework for the analysis of WWSNs at airports.

Evaluating Interlaboratory Variability in Wastewater-Based COVID-19 Surveillance

Wastewater-based environmental surveillance enables the monitoring of SARS-CoV-2 dynamics within populations, offering critical epidemiological insights. Numerous workflows for tracking SARS-CoV-2 have been developed globally, underscoring the need for interlaboratory comparisons to ensure data consistency and comparability. An inter-calibration test was conducted among laboratories within the network monitoring SARS-CoV-2 in wastewater samples across the Lombardy region (Italy). The test aimed to evaluate data reliability and identify potential sources of variability using robust statistical approaches. Three wastewater samples were analyzed in parallel by four laboratories using identical pre-analytical (PEG-8000-based centrifugation) and analytical processes (qPCR targeting N1/N3 and Orf-1ab). A two-way ANOVA framework within Generalized Linear Models was applied, and multiple pairwise comparisons among laboratories were performed using the Bonferroni post hoc test. The statistical analysis revealed that the primary source of variability in the results was associated with the analytical phase. This variability was likely influenced by differences in the standard curves used by the laboratories to quantify SARS-CoV-2 concentrations, as well as the size of the wastewater treatment plants. The findings of this study highlight the importance of interlaboratory testing in verifying the consistency of analytical determinations and in identifying the key sources of variation.

Ethical Considerations for Wastewater Surveillance Conducted by the US Department of Defense

Unlabelled

The US Department of Defense (DoD) is establishing its wastewater surveillance capacities to support national security objectives and promote the public health and medical readiness of US service members. Wastewater surveillance is an emerging technology that has traditionally been leveraged for detecting infectious diseases. However, its potential future applications could yield a vast and unpredictable amount of information that could be used for a wide variety of both health- and nonhealth-related purposes. The US military also serves an inimitable role for the country and its citizens, and exercises significant levels of control over its service members compared to civilian organizations. Further, its present and potential wastewater surveillance activities may reach far beyond just military installations. These factors raise unique ethical considerations that must be accounted for by leaders and policymakers to ensure the DoD implements a wastewater surveillance network in a manner that is both impactful in supporting public health and appropriate to the scope and population under surveillance. This paper explores important ethical features in conducting wastewater surveillance that are both specific to the DoD experience and applicable to wider public health initiatives.

Interpretation of indoor air surveillance for respiratory infections: a prospective longitudinal observational study in a childcare setting

BACKGROUND

Sampling the air in indoor congregate settings, where respiratory pathogens are ubiquitous, may constitute a valuable yet underutilised data source for community-wide surveillance of respiratory infections. However, there is a lack of research comparing air sampling and individual sampling of attendees. Therefore, it remains unclear how air sampling results should be interpreted for the purpose of surveillance.

METHODS

In this prospective observational study, we compared the presence and concentration of several respiratory pathogens in the air with the number of attendees with infections and the pathogen load in their nasal mucus. Weekly for 22 consecutive weeks, we sampled the air in a single childcare setting in Belgium. Concurrently, we collected the paper tissues used to wipe the noses of 23 regular attendees: children aged zero to three and childcare workers. All samples were tested for 29 respiratory pathogens using PCR.

FINDINGS

Air sampling sensitively detected most respiratory pathogens found in nasal mucus. Some pathogens (SARS-CoV-2, Pneumocystis jirovecii) were found repeatedly in the air, but rarely in nasal mucus, whilst the opposite was true for others (Human coronavirus NL63). All three pathogens with a clear outbreak pattern (Human coronavirus HKU-1, human parainfluenza virus 3 and 4) were found in the air one week before or concurrent with the first detection in paper tissue samples. The presence and concentration of pathogens in the air was best predicted by the pathogen load of the most infectious case. However, air pathogen concentrations also correlated with the number of attendees with infections. Detection and concentration in the air were associated with CO2 concentration, a marker of ventilation and occupancy.

INTERPRETATION

Our results suggest that air sampling could provide sensitive, responsive epidemiological indicators for the surveillance of respiratory pathogens. Using air CO2 concentrations to normalise such signals emerges as a promising approach.

FUNDING

KU Leuven; DURABLE project, under the EU4Health Programme of the European Commission; Thermo Fisher Scientific.

Global wastewater surveillance for pathogens with pandemic potential: opportunities and challenges

Wastewater surveillance holds great promise as a sensitive method to detect spillover of zoonotic infections and early pandemic emergence, thereby informing risk mitigation and public health response. Known viruses with pandemic potential are shed in human stool or urine, or both, and the experiences with SARS-CoV-2, monkeypox virus, and Zika virus highlight the feasibility of community-based wastewater surveillance for pandemic viruses that have different transmission routes. We reviewed human shedding and wastewater surveillance data for prototype viruses representing viral families of concern to estimate the likely sensitivity of wastewater surveillance compared with that of clinical surveillance. We examined how data on wastewater surveillance detection, together with viral genetic sequences and animal faecal biomarkers, could be used to identify spillover infections or early human transmission and adaptation. The opportunities and challenges associated with global wastewater surveillance for the prevention of pandemics are described in this Personal View, focusing on low-income and middle-income countries, where the risk of pandemic emergence is the highest. We propose a research and public health agenda to ensure an equitable and sustainable solution to these challenges.

CRISPR: New promising biotechnological tool in wastewater treatment

The increasing demand for water resources with increase in population has sparked interest in reusing produced water, especially in water-scarce regions. The clustered regularly interspaced short palindromic repeats (CRISPR) technology is an emerging genome editing tool that has the potential to trigger significant impact with broad application scope in wastewater treatment. We provide a comprehensive overview of the scope of CRISPR-Cas based tool for treating wastewater that may bring new scope in wastewater management in future in controlling harmful contaminants and pathogens. As an advanced versatile genome engineering tool, focusing on particular genes and enzymes that are accountable for pathogen identification, regulation of antibiotic/antimicrobial resistance, and enhancing processes for wastewater bioremediation constitute the primary focal points of research associated with this technology. The technology is highly recommended for targeted mutations to incorporate desirable microalgal characteristics and the development of strains capable of withstanding various wastewater stresses. However, concerns about gene leakage from strains with modified genome and off target mutations should be considered during field application. A comprehensive interdisciplinary approach involving various fields and an intense research focus concerning delivery systems, target genes, detection, environmental conditions, and monitoring at both lab and ground level should be considered to ensure its successful application in sustainable and safe wastewater treatment.

Morbidity of SARS-CoV-2 in the evolution to endemicity and in comparison with influenza

BACKGROUND

There are three possible SARS-CoV-2 post-pandemic scenarios: (i) ongoing severity, (ii) influenza-like severity, and (iii) a transition to an endemic disease with lesser morbidity similar to that of other human coronaviruses.

METHODS

To assess a possible evolution of the pandemic under the three scenarios, we use data from the US National Covid Cohort Collaborative, CDC COVID-NET, and CDC Fluview and from the WastewaterSCAN Dashboard. We include influenza disease and treatment response as benchmark. The US National Covid Cohort Collaborative allows the quantification of viral-specific morbidity using electronic health records from 424,165 SARS-CoV-2 cases, 53,846 influenza cases, and 199,971 uninfected control subjects from 2021-2022. Evolution of hospitalization rates is estimated from the correlation between national SARS-CoV-2 and influenza hospitalization data and viral gene copies in wastewater.

RESULTS

Our findings reveal that medically attended SARS-CoV-2 infections exhibit similar morbidity to influenza [indicative of scenario (ii)], but SARS-CoV-2 hospitalization rates are one order of magnitude lower than influenza when considering virus concentration in wastewater [indicative of scenario (iii)]. Moreover, SARS-CoV-2 displays a more favorable response to antiviral therapy.

CONCLUSIONS

Our analysis confirms a rapid decline in SARS-CoV-2 morbidity as it transitions to an endemic state.

Estimating rates of change to interpret quantitative wastewater surveillance of disease trends

BACKGROUND

Wastewater monitoring data can be used to estimate disease trends to inform public health responses. One commonly estimated metric is the rate of change in pathogen quantity, which typically correlates with clinical surveillance in retrospective analyses. However, the accuracy of rate of change estimation approaches has not previously been evaluated.

OBJECTIVES

We assessed the performance of approaches for estimating rates of change in wastewater pathogen loads by generating synthetic wastewater time series data for which rates of change were known. Each approach was also evaluated on real-world data.

METHODS

Smooth trends and their first derivatives were jointly sampled from Gaussian processes (GP) and independent errors were added to generate synthetic viral load measurements; the range hyperparameter and error variance were varied to produce nine simulation scenarios representing different potential disease patterns. The directions and magnitudes of the rate of change estimates from four estimation approaches (two established and two developed in this work) were compared to the GP first derivative to evaluate classification and quantitative accuracy. Each approach was also implemented for public SARS-CoV-2 wastewater monitoring data collected January 2021-May 2023 at 25 sites in North Carolina, USA.

RESULTS

All four approaches inconsistently identified the correct direction of the trend given by the sign of the GP first derivative. Across all nine simulated disease patterns, between a quarter and a half of all estimates indicated the wrong trend direction, regardless of estimation approach. The proportion of trends classified as plateaus (statistically indistinguishable from zero) for the North Carolina SARS-CoV-2 data varied considerably by estimation method but not by site.

DISCUSSION

Our results suggest that wastewater measurements alone might not provide sufficient data to reliably track disease trends in real-time. Instead, wastewater viral loads could be combined with additional public health surveillance data to improve predictions of other outcomes.

Revealing patterns of SARS-CoV-2 variant emergence and evolution using RBD amplicon sequencing of wastewater

OBJECTIVES

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 aimed to monitor the SARS-CoV-2 variant community dynamics and evolution using receptor-binding domain (RBD) amplicon sequencing of wastewater samples.

METHODS

We sequenced wastewater from El Paso, Texas, over 17 months, compared the sequencing data with clinical genome data, and performed biodiversity analysis to reveal SARS-CoV-2 variant dynamics and evolution.

RESULTS

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. Comparison with clinical genome sequencing data revealed earlier detection of variants and identification of unreported outbreaks. Our results also showed strong consistency with clinical data for dominant variants at the local, state, and national levels. Alpha diversity analyses revealed significant seasonal variations, with the highest diversity observed in winter. By segmenting the outbreak into lag, growth, stationary, and decline phases, we found higher variant diversity during the lag phase, likely due to lower inter-variant competition preceding outbreak growth.

CONCLUSIONS

Our findings underscore the importance of low transmission periods in facilitating rapid mutation and variant evolution. Our approach, integrating RBD amplicon sequencing with wastewater surveillance, demonstrates effectiveness in tracking viral evolution and understanding variant emergence, thus enhancing public health preparedness.

Outbreak-associated Salmonella Baildon found in wastewater demonstrates how sewage monitoring can supplement traditional disease surveillance

Non-typhoidal Salmonella is a common cause of gastroenteritis worldwide, but current non-typhoidal Salmonella surveillance is suboptimal. Here, we evaluated the utility of wastewater monitoring to enhance traditional surveillance for this foodborne pathogen. In June 2022, we tested raw sewage collected twice a week from two treatment plants in central Pennsylvania for non-typhoidal Salmonella and characterized isolates using whole-genome sequencing. We recovered 43 Salmonella isolates from wastewater samples, differentiated by genomic analysis into seven serovars: 16 Panama (37.2%), 9 Senftenberg (20.9%), 8 Baildon (18.6%), and 3 or fewer of four other serovars. We assessed genetic relatedness and epidemiologic links between these wastewater isolates with those from patients with salmonellosis. All S. Baildon isolates from wastewater were genetically similar to those associated with a known contemporaneous salmonellosis outbreak. S. Baildon from wastewater and 42 outbreak-related isolates in the national outbreak detection database had the same core genome multilocus sequence typing, and outbreak code differed by zero or one single polynucleotide polymorphism. One of the 42 outbreak-related isolates was obtained from a patient residing in the wastewater sample collection catchment area, which serves approximately 17000 people. S. Baildon is a rare serovar (reported in <1% cases nationally, over five years). Our study underscores the value of monitoring sewage from a defined population to supplement traditional surveillance methods for the evidence of Salmonella infections and to determine the extent of outbreaks.IMPORTANCEDuring the COVID-19 pandemic, monitoring for SARS-CoV-2 in wastewater was highly effective in identifying the variants of concern earlier than clinical surveillance methods. Here, we show that monitoring domestic sewage can also augment traditional reporting of foodborne illnesses to public health authorities. Our study detected multiple Salmonella enterica serovars in samples from two wastewater treatment plants in central Pennsylvania. Using whole-genome sequencing, we demonstrated that the isolates of variant S. Baildon clustered with those from a foodborne salmonellosis outbreak that occurred in a similar time frame. Cases were primarily from Pennsylvania, and one individual lived within the wastewater treatment catchment area. This study highlights the effectiveness of domestic sewage testing as a proactive public health strategy to track and respond to infectious disease outbreaks.

Towards geospatially-resolved public-health surveillance via wastewater sequencing

Wastewater is a geospatially- and temporally-linked microbial fingerprint of a given population, making it a potentially valuable tool for tracking public health across locales and time. Here, we integrate targeted and bulk RNA sequencing (N = 2238 samples) to track the viral, bacterial, and functional content over geospatially distinct areas within Miami Dade County, USA, from 2020-2022. We used targeted amplicon sequencing to track diverse SARS-CoV-2 variants across space and time, and we found a tight correspondence with positive PCR tests from University students and Miami-Dade hospital patients. Additionally, in bulk metatranscriptomic data, we demonstrate that the bacterial content of different wastewater sampling locations serving small population sizes can be used to detect putative, host-derived microorganisms that themselves have known associations with human health and diet. We also detect multiple enteric pathogens (e.g., Norovirus) and characterize viral diversity across sites. Moreover, we observed an enrichment of antimicrobial resistance genes (ARGs) in hospital wastewater; antibiotic-specific ARGs correlated to total prescriptions of those same antibiotics (e.g Ampicillin, Gentamicin). Overall, this effort lays the groundwork for systematic characterization of wastewater that can potentially influence public health decision-making.

Simultaneous biomass concentration and subsequent quantitation of multiple infectious disease agents and antimicrobial resistance genes from community wastewater

Wastewater-based surveillance (WBS) of infectious disease agents is increasingly seen as a reliable source of population health data. To date, wastewater-based surveillance efforts have largely focused on individual pathogens. However, given that wastewater contains a broad range of pathogens circulating in the population, a more comprehensive approach could enhance its usability. We focused on the simultaneous detection of SARS-CoV-2, sapovirus, Campylobacter jejuni, Campylobacter coli, Salmonella spp., pathogenic Escherichia coli, Cryptosporidium spp., Giardia spp. and antimicrobial resistance genes (ARGs) of clinical relevance. To achieve this goal, biomass concentration and nucleic acid extraction methods were optimized, and samples were analyzed by using a set of (RT)-qPCR and (HT)-qPCR methods. We determined the prevalence and the spatial and temporal trends of the targeted pathogens and collected novel information on ARGs in Finnish wastewater. In addition, the use of different wastewater concentrates, namely the ultrafiltered concentrate of the supernatant and the centrifuged pellet, and the effect of freezing and thawing wastewater prior to sample processing were investigated with the indicator microbe crAssphage. Freeze-thawing of wastewater decreased the gene copy count of crAssphage in comparison to analyzing fresh samples (p < 0.001). Campylobacters were most abundant in two of the four studied summer months (30 % detection rate) and in wastewaters from regions with intensive animal farming. Salmonella, however, was detected in 40 % of the samples without any clear seasonal trends, and the highest gene copy numbers were recorded from the largest wastewater treatment plants. Beta-lactamase resistance genes that have commonly been detected in bacteria isolated from humans in Finland, namely blaCTX-M, blaOXA48, blaNDM, and blaKPC, were also frequently detected in wastewaters (100, 98, 98, and 70 % detection rates, respectively). These results confirm the reliability of using wastewater in public health surveillance and demonstrate the possibility to simultaneously perform WBS of multiple pathogens.

Removal of intracellular and extracellular antibiotic resistance genes and virulence factor genes using electricity-intensified constructed wetlands

Constructed wetland (CW) is considered a promising technology for the removal of emerging contaminants. However, its removal performance for antibiotic resistance genes (ARGs) is not efficient and influence of virulence factor genes (VFGs) have not been elucidated. Here, removal of intracellular and extracellular ARGs as well as VFGs by electricity-intensified CWs was comprehensively evaluated. The two electrolysis-intensified CWs can improve the removal of intracellular ARGs and MGEs to 0.96- and 0.85-logs, respectively. But cell-free extracellular ARGs (CF-eARGs) were significantly enriched with 1.8-logs in the electrolysis-intensified CW. Interestingly, adding Fe-C microelectrolysis to the electrolysis-intensified CW is conducive to the reduction of CF-eARGs. However, the detected number and relative abundances of intracellular and extracellular VFGs were increased in all of the three CWs. The biofilms attached onto the substrates and rhizosphere are also hotspots of both intracellular and particle-associated extracellular ARGs and VFGs. Structural equation models and correlation analysis indicated that ARGs and VFGs were significantly cooccurred, suggesting that VFGs may affect the dynamics of ARGs. The phenotypes of VFGs, such as biofilm, may act as protective matrix for ARGs, hindering the removal of resistance genes. Our results provide novel insights into the ecological remediation technologies to enhance the removal of ARGs.

Beyond water and soil: Air emerges as a major reservoir of human pathogens

Assessing the risk of human pathogens in the environment is crucial for controlling the spread of diseases and safeguarding human health. However, conducting a thorough assessment of low-abundance pathogens in highly complex environmental microbial communities remains challenging. This study compiled a comprehensive catalog of 247 human-pathogenic bacterial taxa from global biosafety agencies and identified more than 78 million genome-specific markers (GSMs) from their 17,470 sequenced genomes. Subsequently, we analyzed these pathogens' types, abundance, and diversity within 474 shotgun metagenomic sequences obtained from diverse environmental sources. The results revealed that among the four habitats studied (air, water, soil, and sediment), the detection rate, diversity, and abundance of detectable pathogens in the air all exceeded those in the other three habitats. Air, sediment, and water environments exhibited identical dominant taxa, indicating that these human pathogens may have unique environmental vectors for their transmission or survival. Furthermore, we observed the impact of human activities on the environmental risk posed by these pathogens, where greater amounts of human activities significantly increased the abundance of human pathogenic bacteria, especially in water and air. These findings have remarkable implications for the environmental risk assessment of human pathogens, providing valuable insights into their presence and distribution across different habitats.

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.

Precision public health in the era of genomics and big data

Precision public health (PPH) considers the interplay between genetics, lifestyle and the environment to improve disease prevention, diagnosis and treatment on a population level-thereby delivering the right interventions to the right populations at the right time. In this Review, we explore the concept of PPH as the next generation of public health. We discuss the historical context of using individual-level data in public health interventions and examine recent advancements in how data from human and pathogen genomics and social, behavioral and environmental research, as well as artificial intelligence, have transformed public health. Real-world examples of PPH are discussed, emphasizing how these approaches are becoming a mainstay in public health, as well as outstanding challenges in their development, implementation and sustainability. Data sciences, ethical, legal and social implications research, capacity building, equity research and implementation science will have a crucial role in realizing the potential for 'precision' to enhance traditional public health approaches.

EU surveys insights: analytical tools, future directions, and the essential requirement for reference materials in wastewater monitoring of SARS-CoV-2, antimicrobial resistance and beyond

BACKGROUND

Wastewater surveillance (WWS) acts as a vigilant sentinel system for communities, analysing sewage to protect public health by detecting outbreaks and monitoring trends in pathogens and contaminants. To achieve a thorough comprehension of present and upcoming practices and to identify challenges and opportunities for standardisation and improvement in WWS methodologies, two EU surveys were conducted targeting over 750 WWS laboratories across Europe and other regions. The first survey explored a diverse range of activities currently undertaken or planned by laboratories. The second survey specifically targeted methods and quality controls utilised for SARS-CoV-2 surveillance.

RESULTS

The findings of the two surveys provide a comprehensive insight into the procedures and methodologies applied in WWS. In Europe, WWS primarily focuses on SARS-CoV-2 with 99% of the survey participants dedicated to this virus. However, the responses highlighted a lack of standardisation in the methodologies employed for monitoring SARS-CoV-2. The surveillance of other pathogens, including antimicrobial resistance, is currently fragmented and conducted by only a limited number of laboratories. Notably, these activities are anticipated to expand in the future. Survey replies emphasise the collective recognition of the need to enhance the accuracy of results in WWS practices, reflecting a shared commitment to advancing precision and effectiveness in WWS methodologies.

CONCLUSIONS

These surveys identified a lack of standardised common procedures in WWS practices and the need for quality standards and reference materials to enhance the accuracy and reliability of WWS methods in the future. In addition, it is important to broaden surveillance efforts beyond SARS-CoV-2 to include other emerging pathogens and antimicrobial resistance to ensure a comprehensive approach to protecting public health.

High-resolution and real-time wastewater viral surveillance by Nanopore sequencing

Wastewater genomic sequencing stands as a pivotal complementary tool for viral surveillance in populations. While long-read Nanopore sequencing is a promising platform to provide real-time genomic data, concerns over the sequencing accuracy of the earlier Nanopore versions have somewhat restrained its widespread application in wastewater analysis. Here, we evaluate the latest improved version of Nanopore sequencing (R10.4.1), using SARS-CoV-2 as the model infectious virus, to demonstrate its effectiveness in wastewater viral monitoring. By comparing amplicon lengths of 400 bp and 1200 bp, we revealed that shorter PCR amplification is more suitable for wastewater samples due to viral genome fragmentation. Utilizing mock wastewater samples, we validated the reliability of Nanopore sequencing for variant identification by comparing it with Illumina sequencing results. The strength of Nanopore sequencing in generating real-time genomic data for providing early warning signals was also showcased, indicating that as little as 0.001 Gb of data can provide accurate results for variant prevalence. Our evaluation also identified optimal alteration frequency cutoffs (>50 %) for precise mutation profiling, achieving >99 % precision in detecting single nucleotide variants (SNVs) and insertions/deletions (indels). Monitoring two major wastewater treatment plants in Hong Kong from September 2022 to April 2023, covering over 4.5 million population, we observed a transition in dominant variants from BA.5 to XBB lineages, with XBB.1.5 being the most prevalent variants. Mutation detection also highlighted the potential of wastewater Nanopore sequencing in uncovering novel mutations and revealed links between signature mutations and specific variants. This study not only reveals the environmental implications of Nanopore sequencing in SARS-CoV-2 surveillance but also underscores its potential in broader applications including environmental health monitoring of other epidemic viruses, which could significantly enhance the field of wastewater-based epidemiology.

Wastewater tiling amplicon sequencing in sentinel sites reveals longitudinal dynamics of SARS-CoV-2 variants prevalence

The ongoing evolution of SARS-CoV-2 is a significant concern, especially with the decrease in clinical sequencing efforts, which impedes the ability of public health sectors to prepare for the emergence of new variants and potential COVID-19 outbreaks. Wastewater-based epidemiology (WBE) has been proposed as a surveillance program to detect and monitor the SARS-CoV-2 variants being transmitted in communities. However, research is limited in evaluating the effectiveness of wastewater collection at sentinel sites for monitoring disease prevalence and variant dynamics, especially in terms of inferring the epidemic patterns on a broader scale, such as at the state/province level. This study utilized a multiplexed tiling amplicon-based sequencing (ATOPlex) to track the longitudinal dynamics of variant of concern (VOC) in wastewater collected from municipalities in Queensland, Australia, spanning from 2020 to 2022. We demonstrated that wastewater epidemiology measured by ATOPlex exhibited a strong and consistent correlation with the number of daily confirmed cases. The VOC dynamics observed in wastewater closely aligned with the dynamic profile reported by clinical sequencing. Wastewater sequencing has the potential to provide early warning information for emerging variants. These findings suggest that WBE at sentinel sites, coupled with sensitive sequencing methods, provides a reliable and long-term disease surveillance strategy.

Detection of a Human Adenovirus Outbreak, Including Some Critical Infections, Using Multipathogen Testing at a Large University, September 2022-January 2023

Background

Human adenoviruses (HAdVs) can cause outbreaks of flu-like illness in university settings. Most infections in healthy young adults are mild; severe illnesses rarely occur. In Fall 2022, an adenovirus outbreak was identified in university students.

Methods

HAdV cases were defined as university students 17-26 years old who presented to the University Health Service or nearby emergency department with flu-like symptoms (eg, fever, cough, headache, myalgia, nausea) and had confirmed adenovirus infections by polymerase chain reaction (PCR). Demographic and clinical characteristics were abstracted from electronic medical records; clinical severity was categorized as mild, moderate, severe, or critical. We performed contact investigations among critical cases. A subset of specimens was sequenced to confirm the HAdV type.

Results

From 28 September 2022 to 30 January 2023, 90 PCR-confirmed cases were identified (51% female; mean age, 19.6 years). Most cases (88.9%) had mild illness. Seven cases required hospitalization, including 2 critical cases that required intensive care. Contact investigation identified 44 close contacts; 6 (14%) were confirmed HAdV cases and 8 (18%) reported symptoms but never sought care. All typed HAdV-positive specimens (n = 36) were type 4.

Conclusions

While most students with confirmed HAdV had mild illness, 7 otherwise healthy students had severe or critical illness. Between the relatively high number of hospitalizations and proportion of close contacts with symptoms who did not seek care, the true number of HAdV cases was likely higher. Our findings illustrate the need to consider a wide range of pathogens, even when other viruses are known to be circulating.

Evaluating and optimizing Acid-pH and Direct Lysis RNA extraction for SARS-CoV-2 RNA detection in whole saliva

COVID-19 has been a global public health and economic challenge. Screening for the SARS-CoV-2 virus has been a key part of disease mitigation while the world continues to move forward, and lessons learned will benefit disease detection beyond COVID-19. Saliva specimen collection offers a less invasive, time- and cost-effective alternative to standard nasopharyngeal swabs. We optimized two different methods of saliva sample processing for RT-qPCR testing. Two methods were optimized to provide two cost-efficient ways to do testing for a minimum of four samples by pooling in a 2.0 mL tube and decrease the need for more highly trained personnel. Acid-pH-based RNA extraction method can be done without the need for expensive kits. Direct Lysis is a quick one-step reaction that can be applied quickly. Our optimized Acid-pH and Direct Lysis protocols are reliable and reproducible, detecting the beta-2 microglobulin (B2M) mRNA in saliva as an internal control from 97 to 96.7% of samples, respectively. The cycle threshold (Ct) values for B2M were significantly higher in the Direct Lysis protocol than in the Acid-pH protocol. The limit of detection for N1 gene was higher in Direct Lysis at ≤ 5 copies/μL than Acid-pH. Saliva samples collected over the course of several days from two COVID-positive individuals demonstrated Ct values for N1 that were consistently higher from Direct Lysis compared to Acid-pH. Collectively, this work supports that each of these techniques can be used to screen for SARS-CoV-2 in saliva for a cost-effective screening platform.

Optimal environmental testing frequency for outbreak surveillance

Public health surveillance for pathogens presents an optimization problem: we require enough sampling to identify intervention-triggering shifts in pathogen epidemiology, such as new introductions or sudden increases in prevalence, but not so much that costs due to surveillance itself outweigh those from pathogen-associated illness. To determine this optimal sampling frequency, we developed a general mathematical model for the introduction of a new pathogen that, once introduced, increases in prevalence exponentially. Given the relative cost of infection vs. sampling, we derived equations for the expected combined cost per unit time of disease burden and surveillance for a specified sampling frequency, and thus the sampling frequency for which the expected total cost per unit time is lowest.

A broad wastewater screening and clinical data surveillance for virus-related diseases in the metropolitan Detroit area in Michigan

BACKGROUND

Periodic bioinformatics-based screening of wastewater for assessing the diversity of potential human viral pathogens circulating in a given community may help to identify novel or potentially emerging infectious diseases. Any identified contigs related to novel or emerging viruses should be confirmed with targeted wastewater and clinical testing.

RESULTS

During the COVID-19 pandemic, untreated wastewater samples were collected for a 1-year period from the Great Lakes Water Authority Wastewater Treatment Facility in Detroit, MI, USA, and viral population diversity from both centralized interceptor sites and localized neighborhood sewersheds was investigated. Clinical cases of the diseases caused by human viruses were tabulated and compared with data from viral wastewater monitoring. In addition to Betacoronavirus, comparison using assembled contigs against a custom Swiss-Prot human virus database indicated the potential prevalence of other pathogenic virus genera, including: Orthopoxvirus, Rhadinovirus, Parapoxvirus, Varicellovirus, Hepatovirus, Simplexvirus, Bocaparvovirus, Molluscipoxvirus, Parechovirus, Roseolovirus, Lymphocryptovirus, Alphavirus, Spumavirus, Lentivirus, Deltaretrovirus, Enterovirus, Kobuvirus, Gammaretrovirus, Cardiovirus, Erythroparvovirus, Salivirus, Rubivirus, Orthohepevirus, Cytomegalovirus, Norovirus, and Mamastrovirus. Four nearly complete genomes were recovered from the Astrovirus, Enterovirus, Norovirus and Betapolyomavirus genera and viral species were identified.

CONCLUSIONS

The presented findings in wastewater samples are primarily at the genus level and can serve as a preliminary "screening" tool that may serve as indication to initiate further testing for the confirmation of the presence of species that may be associated with human disease. Integrating innovative environmental microbiology technologies like metagenomic sequencing with viral epidemiology offers a significant opportunity to improve the monitoring of, and predictive intelligence for, pathogenic viruses, using wastewater.

In-sewer stability of 31 human health biomarkers and suitability for wastewater-based epidemiology

Monitoring urinary markers of dietary, disease, and stress by wastewater-based epidemiology (WBE) is a promising tool to better understand population health and wellbeing. However, common urinary biomarkers are subject to degradation in sewer systems and their fates have to be assessed before they can be used in WBE. This study investigated the stability of 31 urinary biomarkers (12 food biomarkers, 8 vitamins, 9 oxidative stress biomarkers, and 1 histamine biomarker) in a laboratory sewer sediment reactor and evaluated their suitability for WBE, considering their detectability in real wastewater and in-sewer stability. These biomarkers showed various transformation patterns, among which 16 compounds had half-lives <2 h while other 15 compounds presented moderate to high stability (2 to >500 h). Thirteen biomarkers showed potential for WBE because of their consistently measurable concentrations in untreated wastewater and sufficient in-sewer stability. Eighteen biomarkers were unsuitable due to their rapid in-sewer degradation and/or undetectable concentration levels in untreated wastewater using previous methods. Transformation rates of these biomarkers showed generally weak relationships with molecular properties but relatively higher correlations with biological activities in sewers. Overall, this study determined in-sewer stability of 31 health-related biomarkers through laboratory experiments, providing new findings to WBE for population health assessment.

A shadow enabled non-invasive probe for multi-feature intelligent liquid surveillance system

Liquid detection probes used to identify the features of liquids show great promise in a variety of important applications. However, some challenges, such as sample contamination by direct contact with the liquid, the requirement of additional signal emitters, and complex fabrication, hindered the development of liquid detection probes. Here, we developed a non-invasive shadow probe (SP) for a multi-feature intelligent liquid surveillance system (ILSS). The self-powered SP with the working mechanism of the shadow effect can detect the features of liquids by analyzing the variations of liquid shadows such as the area, wavelength, and brightness. The exact resolution (5 different colors, 6 different concentrations, 6 different levels, 100% accuracy) and fast response time (0.2 ms) are shown by the SP under ambient light conditions (even in 0.003 sun). The ILSS, which integrated the SPs with signal processing circuits and applied the artificial intelligence (AI) technique, successfully detects and synoptically learns about liquids simultaneously. The in-real time ILSS reaches a test accuracy of 99.3% for 10 types of liquids with multiple features. This work showcases a promising solution for non-invasive multi-feature liquid detection, displaying great potential for future applications.

Effect of wastewater collection and concentration methods on assessment of viral diversity

Monitoring of potentially pathogenic human viruses in wastewater is of crucial importance to understand disease trends in communities, predict potential outbreaks, and boost preparedness and response by public health departments. High throughput metagenomic sequencing opens an opportunity to expand the capabilities of wastewater surveillance. However, there are major bottlenecks in the metagenomic enabled wastewater surveillance, including the complexities in selecting appropriate sampling and concentration/virus enrichment methods as well as in bioinformatic analysis of complex samples with low human virus concentrations. To evaluate the abilities of two commonly used sampling and concentration methods in virus identification, virus communities concentrated with Virus Adsorption-Elution (VIRADEL) and PolyEthylene Glycol (PEG) precipitation were compared for three interceptor sites. Results indicated that more viral reads were obtained by the VIRADEL concentration method, with 2.84 ± 0.57 % viral reads in the sample. For samples concentrated with PEG, the average proportion of viral reads in the sample was 0.63 ± 0.19 %. In all wastewater samples, bacteriophage affiliated with the families Siphoviridae, Myoviridae and Podoviridae were found to be the abundant populations. Comparison against a custom Swiss-Prot human virus database indicated that the relatively abundant human viruses (average proportions in human virus community greater than 1.00 %) in samples concentrated with the VIRADEL method were Orthopoxvirus, Rhadinovirus, Parapoxvirus, Varicellovirus, Hepatovirus, Simplexvirus, Molluscipoxvirus, Parechovirus, Lymphocryptovirus, and Spumavirus. In samples concentrated with the PEG method, fewer human viruses were found to be relatively abundant. These were Orthopoxvirus, Rhadinovirus, Varicellovirus, Simplexvirus, Molluscipoxvirus, Lymphocryptovirus, and Betacoronavirus. Contigs of Betacoronavirus, which contains severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), were identified in VIRADEL and PEG samples. Our study demonstrates the feasibility of using metagenomics in wastewater surveillance as a first screening tool and the need for selecting the appropriate virus concentration methods and optimizing bioinformatic approaches in analyzing metagenomic data of wastewater samples.

Battery-free, wireless, and electricity-driven soft swimmer for water quality and virus monitoring

Miniaturized mobile electronic system is an effective candidate for in situ exploration of confined spaces. However, realizing such system still faces challenges in powering issue, untethered mobility, wireless data acquisition, sensing versatility, and integration in small scales. Here, we report a battery-free, wireless, and miniaturized soft electromagnetic swimmer (SES) electronic system that achieves multiple monitoring capability in confined water environments. Through radio frequency powering, the battery-free SES system demonstrates untethered motions in confined spaces with considerable moving speed under resonance. This system adopts soft electronic technologies to integrate thin multifunctional bio/chemical sensors and wireless data acquisition module, and performs real-time water quality and virus contamination detection with demonstrated promising limits of detection and high sensitivity. All sensing data are transmitted synchronously and displayed on a smartphone graphical user interface via near-field communication. Overall, this wireless smart system demonstrates broad potential for confined space exploration, ranging from pathogen detection to pollution investigation.

Wastewater-based epidemiology revealed in advance the increase of enterovirus circulation during the Covid-19 pandemic

Wastewater-based epidemiology (WBE) was conducted to track Enteroviruses (EVs) circulation in the Milan metropolitan area (Northern Italy) during Covid-19 pandemic (March 2020-December 2022). 202 composite 24-hour wastewater samples (WWSs) were collected weekly from March 24, 2020, to December 29, 2022 at the inlet of two wastewater treatment plants (WWTP) in Milan (1.5 million inhabitants). EV-RNA was quantified and molecular characterization of non-polio EVs (NPEV) was performed by Sanger sequence analysis. Data from WWS were matched with virological data collected in the framework of Influenza-Like Illness (ILI) surveillance in the same place and time. EV-RNA was identified in 88.2 % of WWSs. The peak in EVs circulation was observed in late August 2020 (upon conclusion of the first national lockdown), in late August 2021, and in mid-April 2022. EV-RNA concentration in WWS (normalized as copies/d/1000 people) at peak of circulation presented a yearly increase (2020: 2.47 × 1010; 2021: 6.81 × 1010; 2022: 2.14 × 1011). This trend overlapped with trend in EV-positivity rate in ILI cases, expanded from 21.7 % in 2021 to 55.6 % in 2022. EV trends in WWS preceded clinical sample detections in 2021 and 2022 by eight and five weeks, respectively, acting as an early warning of outbreak. Although sequencing of EV-positive WWSs revealed the presence of multiple EV strains, typing remained inconclusive. Molecular characterization of EVs in clinical samples revealed the co-circulation of several genotypes: EV-A accounted for 60 % of EVs, EV-B for 16.7 %, EV-D68 for 23.3 %. EVs were circulating in Milan metropolitan area between March 2020 and December 2022. The epidemiological trends unfolded the progressive accumulation of EV transmission in the population after removal of Covid-19 restrictions. The increased circulation of EVs in 2021-2022 was identified at least 35 days in advance compared to the analysis of clinical data. The inconclusive results of Sanger sequencing lookout for improvement and innovative molecular approaches to deepen track EVs.

The growing need to establish a global wastewater surveillance consortium for future pandemic preparedness

Recognizing the risk of pandemic and the importance of monitoring and data sharing, we highlight the importance of establishing a global wastewater surveillance consortium, particularly under the umbrella of an international organization such as WHO, to strengthen future pandemic preparedness.

Emerging advances in biosecurity to underpin human, animal, plant, and ecosystem health

One Biosecurity is an interdisciplinary approach to policy and research that builds on the interconnections between human, animal, plant, and ecosystem health to effectively prevent and mitigate the impacts of invasive alien species. To support this approach requires that key cross-sectoral research innovations be identified and prioritized. Following an interdisciplinary horizon scan for emerging research that underpins One Biosecurity, four major interlinked advances were identified: implementation of new surveillance technologies adopting state-of-the-art sensors connected to the Internet of Things, deployable handheld molecular and genomic tracing tools, the incorporation of wellbeing and diverse human values into biosecurity decision-making, and sophisticated socio-environmental models and data capture. The relevance and applicability of these innovations to address threats from pathogens, pests, and weeds in both terrestrial and aquatic ecosystems emphasize the opportunity to build critical mass around interdisciplinary teams at a global scale that can rapidly advance science solutions targeting biosecurity threats.

Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks

Wastewater surveillance has proved to be a valuable tool to track the COVID-19 pandemic. However, most studies using wastewater surveillance data revolve around establishing correlations and lead time relative to reported case data. In this perspective, we advocate for the integration of wastewater surveillance data with dynamic within-host and between-host models to better understand, monitor, and predict viral disease outbreaks. Dynamic models overcome emblematic difficulties of using wastewater surveillance data such as establishing the temporal viral shedding profile. Complementarily, wastewater surveillance data bypasses the issues of time lag and underreporting in clinical case report data, thus enhancing the utility and applicability of dynamic models. The integration of wastewater surveillance data with dynamic models can enhance real-time tracking and prevalence estimation, forecast viral transmission and intervention effectiveness, and most importantly, provide a mechanistic understanding of infectious disease dynamics and the driving factors. Dynamic modeling of wastewater surveillance data will advance the development of a predictive and responsive monitoring system to improve pandemic preparedness and population health.

Viral infections at the animal-human interface-Learning lessons from the SARS-CoV-2 pandemic

This Lilliput explores the current epidemiological and virological arguments for a zoonotic origin of the COVID-19 pandemic. While the role of bats, pangolins and racoon dogs as viral reservoirs has not yet been proven, a spill-over of a coronavirus infection from animals into humans at the Huanan food market in Wuhan has a much greater plausibility than alternative hypotheses such as a laboratory virus escape, deliberate genetic engineering or introduction by cold chain food products. This Lilliput highlights the dynamic nature of the animal-human interface for viral cross-infections from humans into feral white tail deer or farmed minks (reverse zoonosis). Surveillance of viral infections at the animal-human interface is an urgent task since live animal markets are not the only risks for future viral spill-overs. Climate change will induce animal migration which leads to viral exchanges between animal species that have not met in the past. Environmental change and deforestation will also increase contact between animals and humans. Developing an early warning system for emerging viral infections becomes thus a societal necessity not only for human but also for animal and environmental health (One Health concept). Microbiologists have developed tools ranging from virome analysis in key suspects such as viral reservoirs (bats, wild game animals, bushmeat) and in humans exposed to wild animals, to wastewater analysis to detect known and unknown viruses circulating in the human population and sentinel studies in animal-exposed patients with fever. Criteria need to be developed to assess the virulence and transmissibility of zoonotic viruses. An early virus warning system is costly and will need political lobbying. The accelerating number of viral infections with pandemic potential over the last decades should provide the public pressure to extend pandemic preparedness for the inclusion of early viral alert systems.

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

International airports can have a key role in screening, detecting, and mitigating cross-border transmission of SARS-CoV-2 and potentially other infectious diseases. With aircraft passengers representing a subpopulation of a country or region, aircraft-based wastewater surveillance can be a promising approach to effectively identifying emerging viruses, tracing their evolution, and mapping global spread with international flights. Therefore, we propose the development of a global aircraft-based wastewater genomic surveillance network, with the busiest international airports as central nodes and continuing air travel journeys as vectors. This surveillance programme requires routinely collecting aircraft wastewater samples for microbiological analysis and sequencing and linking the resulting data with associated international air traffic information. With the creation of a strong international alliance between the airline industry and health authorities, this surveillance network will potentially complement public health systems with a true early warning ability to inform decision making for new variants and future global health risks.

Taking on Typhoid: Eliminating Typhoid Fever as a Global Health Problem

Typhoid fever is a significant global health problem that impacts people living in areas without access to clean water and sanitation. However, collaborative international partnerships and new research have improved both knowledge of the burden in countries with endemic disease and the tools for improved surveillance, including environmental surveillance. Two typhoid conjugate vaccines (TCVs) have achieved World Health Organization prequalification, with several more in the development pipeline. Despite hurdles posed by the coronavirus disease 2019 pandemic, multiple TCV efficacy trials have been conducted in high-burden countries, and data indicate that TCVs provide a high degree of protection from typhoid fever, are safe to use in young children, provide lasting protection, and have the potential to combat typhoid antimicrobial resistance. Now is the time to double down on typhoid control and elimination by sustaining progress made through water, sanitation, and hygiene improvements and accelerating TCV introduction in high-burden locations.

Emergence of monkeypox: a worldwide public health crisis

The human monkeypox virus (MPV), a zoonotic illness that was hitherto solely prevalent in Central and West Africa, has lately been discovered to infect people all over the world and has become a major threat to global health. Humans unintentionally contract this zoonotic orthopoxvirus, which resembles smallpox, when they come into contact with infected animals. Studies show that the illness can also be transferred through frequent proximity, respiratory droplets, and household linens such as towels and bedding. However, MPV infection does not presently have a specified therapy. Smallpox vaccinations provide cross-protection against MPV because of antigenic similarities. Despite scant knowledge of the genesis, epidemiology, and ecology of the illness, the incidence and geographic distribution of monkeypox outbreaks have grown recently. Polymerase chain reaction technique on lesion specimens can be used to detect MPV. Vaccines like ACAM2000, vaccinia immune globulin intravenous (VIG-IV), and JYNNEOS (brand name: Imvamune or Imvanex) as well as FDA-approved antiviral medications such as brincidofovir (brand name: Tembexa), tecovirimat (brand name: TPOXX or ST-246), and cidofovir (brand name: Vistide) are used as therapeutic medications against MPV. In this overview, we provide an outline of the MPV's morphology, evolution, mechanism, transmission, diagnosis, preventative measures, and therapeutic approaches. This study offers the fundamental information required to prevent and manage any further spread of this emerging virus.