Study finds landfill point source emissions have an outsized impact and opportunity to tackle U.S. waste methane

Largest measurement-based landfill methane assessment to date identifies major emission sources missing from traditional accounting that can be prioritized for mitigation

CARBON MAPPER

 

IMAGE: 

METHANE PLUMES OBSERVED BY CARBON MAPPER DURING AERIAL SURVEYS AT A LANDFILL IN GEORGIA.

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CREDIT: CARBON MAPPER

Thursday, 28 March, 2024

Study finds landfill point source emissions have an outsized impact and opportunity to tackle U.S. waste methane 

Largest measurement-based landfill methane assessment to date identifies major emission sources missing from traditional accounting that can be prioritized for mitigation

March 28, 2024—Pasadena, CA—A new study, led by Carbon Mapper scientists alongside researchers from NASA Jet Propulsion Laboratory, Arizona State University, University of Arizona, Scientific Aviation, and the U.S. Environmental Protection Agency, provides the largest comprehensive assessment of hundreds of U.S. landfills using direct observations through airborne surveys. The study reveals the outsized impact of landfill point source emissions, which are responsible for a disproportionately large share of pollution from this important sector. It also sheds light on potential gaps in traditional model-based emission accounting methods that may benefit from sustained direct measurement using emerging surface-, air-, and space-based monitoring technologies. 

“Addressing these high methane sources and mitigating persistent landfill emissions offers a strong potential for climate benefit,” said Dr. Dan Cusworth, Carbon Mapper Program Scientist and lead author on the paper. “The ability to precisely identify leaks is an efficient way to make quick progress on methane reduction at landfills, which could be critical for slowing global warming.”

Landfills are considered the third largest source of human-caused methane emissions in the U.S., responsible for 14.3% of methane in 2021 and emitting the equivalent to the greenhouse gas (GHG) emissions from nearly 23.1 million gasoline-powered passenger vehicles driven for one year, according to the EPA. Despite the climate impact of landfills, societal understanding of these emissions is largely limited to model-based estimates, and the sector remains under-addressed compared to other big methane sources like oil and gas. Traditional surface-based surveys with handheld methane sensors provide an incomplete picture of emissions. This is due to factors like limited access to many sections of active landfills as well as logistical and personnel safety reasons.

To help fill these gaps, Carbon Mapper and research partners used advanced aircraft to conduct the largest direct measurement-based survey of active municipal solid waste landfills to date from 2018 through 2022. This included aerial surveys, led by Carbon Mapper and Scientific Aviation, of over 200 active U.S. landfills that participate in the U.S. Greenhouse Gas Reporting Program (20% of approximately 1,200 reported open landfills). Surveys led by Carbon Mapper utilized partner aircraft—including NASA JPL’s AVIRIS-NG and Arizona State University’s Global Airborne Observatory with the Center for Global Discovery and Conservation Science.

Key findings
Evaluating this large data set yielded insights that site owners and operators, policymakers, regulators, and civil society can use to better assess and act on landfill emissions. 

(1) Landfill point source emissions have an outsized methane impact. Fifty-two percent (52%) of surveyed landfills had observable point source emissions. This far exceeds the 0.2% to 1% detection rate observed for super-emitters from surveyed oil and gas infrastructure in California and the Permian Basin. 

(2) Landfill point source emissions are generally more persistent compared to their counterparts in oil and gas production. For those landfills with observed emissions, 60% had emissions that persisted over months or years. These persistent emissions totaled 87% of all quantified emissions in the study. Comparatively, the majority of methane super-emitters in the oil and gas sector are related to irregular, short-duration events.

(3) There are significant gaps in landfill leak detection and quantification protocols. Current walking surveys with hand-held sensors are ineffective in completely sampling the landfill surface and may miss high point source activity that can dominate the facility’s emissions while remaining undetected for extended periods. Advanced monitoring strategies, such as remote sensing from satellites, aircraft and drones, can provide a more accurate picture of landfill methane emissions. When combined with improved ground-based measurements, remote sensing can provide consistent, comprehensive measurements to better inform models, guide mitigation efforts and verify emission reductions.

(4) A robust dataset of quantified emissions at U.S. landfills finds little agreement with national reporting frameworks. A misalignment between observed and reported emissions indicates that current methods used to report facility emissions, such as the EPA’s Greenhouse Gas Reporting Program (GHGRP), are missing or misrepresenting large sources of methane. On average, aerial emission rates were 1.4 times higher than GHGRP. This presents a significant difference between observed and reported emissions, supported by the largest airborne or ground-based survey of U.S. landfills to date.

Looking forward, this study reveals the need for a comprehensive monitoring strategy to measure, quantify and act on methane emissions at landfills more effectively. Resources like the Carbon Mapper Coalition satellite program can offer efficient solutions for measurement challenges. The coalition’s first Tanager satellite, which is launching in 2024 as part of a public-private partnership between Carbon Mapper, Planet Labs PBC, NASA JPL and others, is uniquely designed and optimized to detect methane at landfills. Carbon Mapper is also conducting a multi-year initiative to assess thousands of high-emitting solid waste sites globally, using remote sensing technologies to establish a methane emissions baseline for managed landfills and unmanaged dumps. This includes U.S. landfill aerial campaigns planned for 2024. 

Carbon Mapper’s methane data is publicly available on its portal to maximize the availability of emissions data for a wide range of operators across many jurisdictions, including major waste management companies and local city and county governments. This helps empower them to mitigate emissions and make informed decisions that maximize methane capture. The data is also made available for policymakers, regulators, community groups and others to support science-based decision making.

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About Carbon Mapper

Carbon Mapper is a nonprofit based in Pasadena, CA with the mission to drive greenhouse gas emissions reductions by making methane and carbon dioxide data accessible and actionable. They focus on filling gaps in the emerging ecosystem of methane and CO2 monitoring systems by delivering data at facility scale that is precise, timely, and accessible to empower decision making and direct mitigation action. The organization leads a public-private coalition that is developing and deploying a constellation of satellites capable of detecting, quantifying, and verifying methane emissions worldwide. Data from these satellites will offer the next major step in scaling up the organization’s robust data portal featuring thousands of direct observations of global methane and CO2 super-emitters. Learn more at carbonmapper.org, view data at data.carbonmapper.org, and follow us on Twitter @carbonmapper.

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JOURNAL

Science

DOI

10.1126/science.adi7735 

ARTICLE TITLE

Quantifying Methane Emissions from United States Landfills

ARTICLE PUBLICATION DATE

28-Mar-2024

U.S. landfills emit significant amounts of methane

AMERICAN ASSOCIATION FOR THE ADVANCEMENT OF SCIENCE (AAAS)

A new survey finds that United States open landfills are emitting significant amounts of methane, one of the most important greenhouse gases causing global climate change. The study by Daniel Cusworth and colleagues was conducted using airborne imaging spectrometers that observe methane emissions and is the largest airborne or ground-based survey of U.S. landfills to date, representing 20% of the nation’s landfills. Among the 250 sites across 18 states surveyed between 2018 and 2022, the researchers were able to detect significant point-source methane emissions at 52% of sites. This percentage “far exceed[s] the point-source detection rate from other methane emission sectors,” Cusworth et al. conclude, suggesting that solid waste is an important contributor to greenhouse gas emission in the U.S. The findings also uncover a large discrepancy in the emission estimates calculated by airborne detection and more traditional estimates made by walking over landfill sites. On average, aerial emission rates were a factor 2.7 higher than those reported to the U.S. Greenhouse Gas Reporting Program, the researchers note. Point-source emissions are emission “hotspots” confined to a local area, as compared to emissions spread over a broad area of the landfill. Point-source emissions are important to regulate because they often represent a significant emission source and are more likely to be linked to the dynamic operations of a landfill. The point-source emissions observed in the study sometimes persisted for months or even years. The researchers even found a distinct population of landfills where point-source activity continued almost throughout the entire study period. “This long-duration population represents more than 60% of all landfills, and 87% of all quantified emissions,” the researchers write.

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JOURNAL

Science

DOI

10.1126/science.adi7735 

ARTICLE TITLE

Quantifying methane emissions from United States landfills

ARTICLE PUBLICATION DATE

29-Mar-2024

 

Reviving Europe’s orchard meadows: researchers call for action

PENSOFT PUBLISHERS

 

IMAGE: 

AN ORCHARD IN RUTESHEIM-PEROUSE, SOUTHERN GERMANY.

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CREDIT: KLAUS HENLE.

A study spearheaded by researchers at the Helmholtz Centre for Environmental Research and Macquarie University has highlighted the important ecological role of traditional orchard meadows, calling for political and public support and incentives for farmers to protect these landscapes.

The paper, published in the open-access journal Nature Conservation, reviews the effects of management, habitat and landscape characteristics on the biodiversity of orchard meadows in Central Europe.

Orchard meadows, characterised by the combination of cultivated grasslands and scattered fruit trees, exhibit high flora and fauna biodiversity. Despite their ecological value, these habitats have been in decline since the mid-19th century due their decreasing economic worth. They now face threats from land abandonment and intensification of agriculture.

The study emphasises the importance of moderate management intensity, connectivity to neighbouring habitats, and the preservation of structural diversity to maintain and enhance the conservation value of orchard meadows. The findings also advocate for a nuanced understanding of management impacts across taxonomic groups and points out the limitation of available studies on orchard meadows in Central Europe.

Currently loose in definition, the research team advocated for a clear definition of orchard meadows to create a common term in Europe, which would make their assessment and protection more straightforward. They suggest orchard meadows should be listed in the Habitats Directive of the Council of the European Union and farmers should get incentives for their maintenance. Finally, the research team calls for political and public support to prevent the loss and abandonment of these biodiverse landscapes.

“One way the public support the protection of these habitats is through consumer behaviour, specifically by purchasing local products from orchard meadows. However, it is crucial to subsidise these local products and prioritize them at local markets,” says lead author Cornelia Sattler.

“As long as fruits from orchard meadows are treated as 'by-products' in the market, it will be challenging to convince people to buy local products. This change is necessary to close the economic gap between intensified fruit production and extensive orchard meadows,” she concludes.

Schematic figure illustrating the effects of management intensification on species richness. The graph illustrates the potential effect of management intensity (from high over intermediate to abandonment/rewilding) on species richness in orchard meadows. 

CREDIT

Sattler et al

Research paper

Sattler C, Schrader J, Hüttner M-L, Henle K (2024) Effects of management, habitat and landscape characteristics on biodiversity of orchard meadows in Central Europe: A brief review. Nature Conservation 55: 103-134. https://doi.org/10.3897/natureconservation.55.108688

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JOURNAL

Nature Conservation

DOI

10.3897/natureconservation.55.108688 

ARTICLE TITLE

Effects of management, habitat and landscape characteristics on biodiversity of orchard meadows in Central Europe: A brief review

ARTICLE PUBLICATION DATE

28-Mar-2024

 

Q&A: How to train AI when you don't have enough data

UNIVERSITY OF WASHINGTON

Artificial intelligence excels at sorting through information and detecting patterns or trends. But these machine learning algorithms need to be trained with large amounts of data first.

As researchers explore potential applications for AI, they have found scenarios where AI could be really useful — such as analyzing X-ray image data to look for evidence of rare conditions or detecting a rare fish species caught on a commercial fishing boat — but there's not enough data to accurately train the algorithms. 

Jenq-Neng Hwang, University of Washington professor of electrical and computer and engineering, specializes in these issues. For example, Hwang and his team developed a method that teaches AI to monitor how many distinct poses a baby can achieve throughout the day. There are limited training datasets of babies, which meant the researchers had to create a unique pipeline to make their algorithm accurate and useful. The team recently published this work in the IEEE/CVF Winter Conference on Applications of Computer Vision 2024.

UW News spoke with Hwang about the project details and other similarly challenging areas the team is addressing.

Why is it important to develop an algorithm to track baby poses?

Jenq-Neng Hwang: We started a collaboration with the UW School of Medicine and the Korean Electronics and Telecommunications Research Institute's AI Lab. The goal of the project was to try to help families with a history of autism know whether their babies were also likely to have autism. Babies before 9 months don't really have language skills yet, so it's difficult to see if they’re autistic or not. Researchers developed one test, called the Alberta Infant Motor Scale, which categorizes various poses babies can do: If a baby can do this, they get two points; and if they can do that, they get three points; and so on. Then you add up all the points and if the baby is above some threshold, they likely don't have autism.

But to do this test, you need a doctor to observe all the different poses. It becomes a very tedious process because sometimes after three or four hours, we still haven't seen a baby do a specific pose. Maybe the baby could do it, but at that moment they didn't want to. One solution could be to use AI. Parents often have a baby monitor at home. The baby monitor could use AI to continuously and consistently track the various poses a baby does in a day.

Why is AI a good fit for this task?

JNH: My background is studying traditional image processing and computer vision. We were trying to teach computers to be able to figure out human poses from photos or videos, but the trouble is that there are so many variations. For example, even the same person wearing different outfits is a challenging task for traditional image processing to correctly identify that person's elbow on each photo.

But AI makes it so much easier. These models can learn. For example, you could train a machine learning model with a variety of motion captured sequences showing all different kinds of people. These sequences could be annotated with the corresponding 3D poses. Then this model could learn to output a 3D model of a person's pose on a sequence it has never seen before.

But in this case, there aren't a lot of motion captured sequences of babies that also have 3D pose annotations that you could use to train your machine learning model. What did you do instead?

JNH: We don't have a lot of 3D pose annotations of baby videos to train the machine learning model for privacy reasons. It's also difficult to create a dataset where a baby is performing all the possible potential poses that we would need. Our datasets are too small, meaning that a model trained with them would not estimate reliable poses.

But we do have a lot of annotated 3D motion sequences of people in general. So, we developed this pipeline.

First we used the large amount of 3D motion sequences of regular people to train a generic 3D pose generative AI model, which is similar to the model used in ChatGPT and other GPT-4 types of large language models.

We then finetuned our generic model with our very limited dataset of annotated baby motion sequences. The generic model can then adapt to the small dataset and produce high quality results.

Are there other tasks like this: good for AI, but there's not a lot of data to train an algorithm?

JNH: There are many types of scenarios where we don't have enough information to train the model. One example is a rare disease that is diagnosed by X-rays. The disease is so rare that we don't have enough X-ray images from patients with the disease to train a model. But we do have a lot of X-rays from healthy patients. So, we can use generative AI again to generate the corresponding synthetic X-ray image without disease, which can then be compared with the diseased image to identify disease regions for further diagnosis.

Autonomous driving is another example. There are so many real events you cannot create. For example, say you are in the middle of driving and a few leaves blow in front of the car. If you use autonomous driving, the car might think something is wrong and slam on the brakes, because the car has never seen this scenario before. This could result in an accident.

We call these "long-tail" events, which means that they are unlikely to happen. But in daily life we always see random things like this. Until we figure out how to train autonomous driving systems to handle these types of events, autonomous driving cannot be useful. Our team is working on this problem by combining data from a regular camera with radar information. The camera and radar persistently check each other’s decisions, which can help a machine learning algorithm make sense of what's happening.

Additional co-authors on the baby poses paper are Zhuoran Zhou, a UW research assistant in the electrical and computer engineering department; Zhongyu Jiang and Cheng-Yen Yang, UW doctoral students in the electrical and computer engineering department; Wenhao Chai, a UW master's student studying electrical and computer engineering; and Lei Li, a doctoral fellow at the University of Copenhagen. This research was funded by the Electronics and Telecommunications Research Institute of Korea, the National Oceanic and Atmospheric Administration and Cisco Research.

For more information, contact Hwang at hwang@uw.edu.

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ARTICLE TITLE

Efficient Domain Adaptation via Generative Prior for 3D Infant Pose Estimation

Generative AI develops potential new drugs for antibiotic-resistant bacteria

Stanford Medicine researchers devise a new artificial intelligence model, SyntheMol, which creates recipes for chemists to synthesize the drugs in the lab.

STANFORD MEDICINE

With nearly 5 million deaths linked to antibiotic resistance globally every year, new ways to combat resistant bacterial strains are urgently needed.

Researchers at Stanford Medicine and McMaster University are tackling this problem with generative artificial intelligence. A new model, dubbed SyntheMol (for synthesizing molecules), created structures and chemical recipes for six novel drugs aimed at killing resistant strains of Acinetobacter baumannii, one of the leading pathogens responsible for antibacterial resistance-related deaths.

The researchers described their model and experimental validation of these new compounds in a study published March 22 in the journal Nature Machine Intelligence.

“There’s a huge public health need to develop new antibiotics quickly,” said James Zou, PhD, an associate professor of biomedical data science and co-senior author on the study. “Our hypothesis was that there are a lot of potential molecules out there that could be effective drugs, but we haven’t made or tested them yet. That’s why we wanted to use AI to design entirely new molecules that have never been seen in nature.”

Before the advent of generative AI, the same type of artificial intelligence technology that underlies large language models like ChatGPT, researchers had taken different computational approaches to antibiotic development. They used algorithms to scroll through existing drug libraries, identifying those compounds most likely to act against a given pathogen. This technique, which sifted through 100 million known compounds, yielded results but just scratched the surface in finding all the chemical compounds that could have antibacterial properties.

“Chemical space is gigantic,” said Kyle Swanson, a Stanford computational science doctoral student and co-lead author on the study. “People have estimated that there are close to 1060 possible drug-like molecules. So, 100 million is nowhere close to covering that entire space.”

Hallucinating for drug development

Generative AI’s tendency to “hallucinate,” or make up responses out of whole cloth, could be a boon when it comes to drug discovery, but previous attempts to generate new drugs with this kind of AI resulted in compounds that would be impossible to make in the real world, Swanson said. The researchers needed to put guardrails around SyntheMol’s activity — namely, to ensure that any molecules the model dreamed up could be synthesized in a lab.

“We’ve approached this problem by trying to bridge that gap between computational work and wet lab validation,” Swanson said.

The model was trained to construct potential drugs using a library of more than 130,000 molecular building blocks and a set of validated chemical reactions. It generated not only the final compound but also the steps it took with those building blocks, giving the researchers a set of recipes to produce the drugs.

The researchers also trained the model on existing data of different chemicals’ antibacterial activity against A. baumannii. With these guidelines and its building block starting set, SyntheMol generated around 25,000 possible antibiotics and the recipes to make them in less than nine hours. To prevent the bacteria from quickly developing resistance to the new compounds, researchers then filtered the generated compounds to only those that were dissimilar from existing compounds.

“Now we have not just entirely new molecules but also explicit instructions for how to make those molecules,” Zou said.

A new chemical space

The researchers chose the 70 compounds with the highest potential to kill the bacterium and worked with the Ukrainian chemical company Enamine to synthesize them. The company was able to efficiently generate 58 of these compounds, six of which killed a resistant strain of A. baumannii when researchers tested them in the lab. These new compounds also showed antibacterial activity against other kinds of infectious bacteria prone to antibiotic resistance, including E. coli, Klebsiella pneumoniae and MRSA.

The scientists were able to further test two of the six compounds for toxicity in mice, as the other four didn’t dissolve in water. The two they tested seemed safe; the next step is to test the drugs in mice infected with A. baumannii to see if they work in a living body, Zou said.

The six compounds are vastly different from each other and from existing antibiotics. The researchers don’t know how their antibacterial properties work at the molecular level, but exploring those details could yield general principles relevant to other antibiotic development.

“This AI is really designing and teaching us about this entirely new part of the chemical space that humans just haven’t explored before,” Zou said.

Zou and Swanson are also refining SyntheMol and broadening its reach. They’re collaborating with other research groups to use the model for drug discovery for heart disease and to create new fluorescent molecules for laboratory research.

The study was funded by the Weston Family Foundation, the David Braley Centre for Antibiotic Discovery, the Canadian Institutes of Health Research, M. and M. Heersink, the Chan-Zuckerberg Biohub, and the Knight-Hennessy scholarship.

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JOURNAL

Nature Machine Intelligence

METHOD OF RESEARCH

Computational simulation/modeling

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Generative AI for designing and validating easily synthesizable and structurally novel antibiotics

 

Study underscores uncertain costs of iron fertilization

BIGELOW LABORATORY FOR OCEAN SCIENCES

 

IMAGE: 

SATELLITE DATA ON CHLOROPHYLL CONCENTRATIONS IN THE NORTHEASTERN PACIFIC OCEAN USES WARM COLORS TO SHOW AREAS OF HIGHER PHYTOPLANKTON ABUNDANCE. THE SMALL PATCH OF BRIGHT RED AND YELLOW IN THE BOTTOM CENTER OF THE IMAGE INDICATES A BLOOM CREATED BY AN IRON FERTILIZATION EXPERIMENT.

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CREDIT: NASA EARTH OBSERVATORY

As society grapples with the intensifying consequences of climate change, decision makers are increasingly looking to carbon dioxide removal as a necessary complement to emission reductions. One of the strategies that has received the most attention is the idea of fertilizing parts of the ocean with iron to stimulate phytoplankton growth. A team of researchers from Bigelow Laboratory have developed a mathematical model that estimates the potential costs of undertaking large-scale iron fertilization by either plane or ship. They focus on the oceanographic parameters that are likely to determine the effectiveness of the strategy, finding a nearly 100-fold difference in cost between the best- and worst-case scenarios.

In addition, the researchers found that iron delivery by plane, which hasn’t been widely considered, could be more cost effective than ship delivery, but also that verifying that carbon is being fixed in the deep ocean long-term and monitoring environmental impacts could add significant costs. Their findings, published recently in the journal Earth’s Future, will help researchers identify the largest uncertainties of doing ocean iron fertilization — and their cost.

“The primary reason for creating this cost model wasn’t to figure out the economics of iron fertilization exactly,” said Senior Research Scientist and lead author David Emerson. “It was to show how cost varied based on the uncertainty of all the different oceanographic aspects, including the less obvious ones, that need to be accounted for.”

Iron fertilization, like several other marine carbon dioxide removal strategies, is meant to enhance a natural process. Minimal iron availability is the primary limiting factor for phytoplankton growth in nearly one third of the ocean, including the vast Southern Ocean. When even a relatively small amount of the nutrient is added to those ecosystems — whether through natural or artificial processes — it stimulates blooms of phytoplankton. These organisms absorb carbon dioxide dissolved in the ocean from the air and, when they die, may sink it down to the ocean floor for the foreseeable future.

The cost of enhancing this process at large scales depends largely on its efficacy in terms of how much carbon makes it to the deep ocean and stays there.

“We can confidently go out and create a phytoplankton bloom with iron, but the question is how much of the carbon actually ends up getting exported into the ocean, not just over days and weeks but over years and decades,” said Senior Research Scientist Ben Twining, a co-author on the study.

The team built their economic model assuming a range of possible efficiencies at each step of the process, with different estimates of how much carbon can be taken up by phytoplankton, how much is converted back into carbon dioxide and re-released, and how much sinks to the deep ocean. They also explored the possibility that microbes that would feed on all this new plant matter could produce nitrous oxide, a far more potent greenhouse gas. On top of that, the model considers some of the logistical costs, from producing and processing the iron to operating a plane or ship to seed and monitor the resulting bloom.

The uncertainties in how the ocean would respond to iron fertilization, and how biologically efficient the process would be, resulted in a huge price range, from as little as $7 per ton of carbon removed to $1,500 per ton. When the costs of verification are included, that can increase the dollar per ton cost another three to four-fold.

The researchers caution that the exact numbers the model produces are at this point still just best estimates, but they are helpful for putting tangible values on the uncertainties in the process. To that end, the model emphasizes the need for more research particularly into how “permanent” this is as a potential solution and the risks of producing additional greenhouse gases. It also highlights the need for more information on verification methods and aerial delivery.

“The real value of this work is not the exact numbers we came up with but how it highlights where the greatest uncertainties are,” Twining said. “Models are useful, not because they give you an exact answer, but because they give you a framework for figuring out what you need to work on next.”

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JOURNAL

Earth s Future

DOI

10.1029/2023EF003732 

METHOD OF RESEARCH

Computational simulation/modeling

SUBJECT OF RESEARCH

Cells

ARTICLE TITLE

A cost model for ocean iron fertilization as a means of carbon dioxide removal that compares ship- and aerial-based delivery, and estimates verification costs

ARTICLE PUBLICATION DATE

29-Mar-2024

 

Swedish study indicates a significant decline of neutralising antibodies to monkeypox virus already during the first month after vaccination

Highlights the need for a clinical trial of a booster dose before any policy decision

EUROPEAN SOCIETY OF CLINICAL MICROBIOLOGY AND INFECTIOUS DISEASES

Previous smallpox vaccination contributes significantly to higher neutralising antibodies following first MVA-BN dose

New research to be presented at this year’s European Congress of Clinical Microbiology and Infectious Diseases (ECCMID 2024) in Barcelona, Spain (27-30 April) shows that even in men who receives two doses of mpox vaccine intradermally, their level of antibodies to the virus falls to low or zero within the first few months if they have not received a previous smallpox vaccine.

The authors, who include Dr Klara Sonden, deputy state epidemiologist of the of Public Health Agency of Sweden and affiliated to Karolinska Institute, Stockholm, Sweden, says that their study shows that booster vaccination may be needed long-term for such individuals, and that scientific evidence is needed for the background to any decisions.

Since May 2022, an mpox outbreak has emerged globally, spreading mainly among men who have sex with men (MSM). It was classified as a Public Health Emergency of International Concern (PHEIC). In Sweden, a vaccine against smallpox based on the live Modified Vaccinia Virus Ankara (MVA-BN), has been offered intradermally to risk groups. Intradermal administration means 0.1 ml in the skin, one fifth of the dose needed for subcutaneous administration. This was used as a dose-saving strategy as supplies were initially limited.

The vaccine has been shown to be efficacious in studies using real-world data from the 2022 and onward outbreak among MSM, with limited number of breakthrough infections and milder disease reported when breakthrough infections occur so far. The aim of this cohort study was to assess dynamics of, and factors affecting neutralising antibodies against mpox virus (MPXV) following MVA-BN vaccination.

A total of 100 MSM attending the sexual health clinic “Venhälsan”, Stockholm, Sweden, eligible to receive the vaccine MVA-BN were included in the study. Following the initial serum sample drawn before dose 1, serum samples were further collected before dose 2, and 28 days and three months after the second dose. These samples were tested to establish titers (levels) of MPXV-neutralising antibodies. Titers were compared in individuals with or without previous smallpox vaccination and patients with past natural infection were included as positive controls.

10 individuals were of uncertain status regarding smallpox vaccination (due to being born in many different countries in the time period 1977-1980 when vaccination was de-escalated globally) and 23 individuals were previously smallpox vaccinated. The other 67 individuals had no history of smallpox vaccination.

A total of 312 samples from four time points from the 100 individuals included in the study were analysed. In addition to the study population, anonymised age and sex matched controls from blood donors were included as negative controls (n=20) and previously MPXV-infected individuals as positive controls (n=20). The controls gave one blood sample each.

Within the study group, previous smallpox vaccination was associated with significantly higher antibody titers, and 15/23 of these individuals had pre-existing neutralising antibodies (ie, the B-cell memory was still present thanks to their previous smallpox vaccination).

Among those without prior smallpox vaccination, fewer than half of the group showed any detectable neutralizing antibodies at all 28 days after the second vaccination, with those who did exhibit responses having a median titer (standard unit of measurement of antibodies) of 20. In contrast, for previously vaccinated individuals, the median titer 28 days after a single dose of the MVA-BN vaccine was 40.

The authors say: “Our findings corroborate other studies showing that mpox vaccination results in neutralising antibodies only in a proportion of vaccinees, and that a significant decline occurs already during the first month post-vaccination Immunity after previous MPXV infection mounts a higher and more robust neutralising response. In conclusion, the findings merits the study of booster doses.”

They continue: “Our results indicate a rapid decline in neutralising antibodies after two doses and are in line with other recent studies. These results, together with the continued spread of mpox in MSM populations in Europe has prompted the consideration of a booster dose. Such a recommendation needs to be based on scientific evidence. However, as far as we know, no clinical trial has studied or is studying a 3rd MVA-BN dose (from an analysis of clinicaltrials.gov March 2024), but a booster dose is common practice for inactivated vaccines. The MVA-BN is a live, non-replicating vaccine and therefore likely equivalent to an inactivated vaccine. Studies are essential to inform public health policy, and the largest STI clinic in Sweden is planning to perform a randomised clinical trial of a booster dose with immunological parameters as the primary outcome in the comparison with those who have had the two doses of the regular full 0.5 subcutaneous dose (sc) (0.5ml), two doses of the dose-saving intradermal dose (id) (0.1ml), or one dose sc/one dose id, and those with no booster dose.”

They add that despite this, the Mpox cases in Sweden have been few and mostly imported during 2023 (12 cases) and 2024 (5 cases) and the vast majority have been among unvaccinated individuals. Data collection is ongoing regarding the occurrence of breakthrough infections in Sweden. Breakthrough cases have been reported in the scientific literature among individuals that have received different vaccination strategies (i.e. sc/sc, id/sc, id/id) (Hazra et al)*.

Dr Sonden concludes: “The results presented here indicate that long-term protective immunity might need a booster dose for its maintenance. Since the current situation regarding mpox in Sweden is stable with minimal transmission any change in policy should be backed by results from clinical trials. Currently we will focus on finding unvaccinated individuals who are at risk of getting mpox and offer them vaccination, and we believe that this as well as the previously administered vaccinations will contribute to lowering the risk for new outbreaks of mpox in Sweden in future.”

 

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ARTICLE PUBLICATION DATE

30-Mar-2024

Study shows Mpox (monkeypox) antibodies wane within a year of vaccination

However antibodies remain high in those with pre-existing immunity

EUROPEAN SOCIETY OF CLINICAL MICROBIOLOGY AND INFECTIOUS DISEASES

New research to be presented at this year’s European Congress of Clinical Microbiology and Infectious Diseases (ECCMID 2024) in Barcelona, Spain (27-30 April) shows that the antibodies produced by Modified Vaccinia virus Ankara - Bavarian Nordic (MVA-BN) vaccination against mpox wane significantly within a year of receiving the vaccination – but in people with pre-existing immunity due to childhood smallpox vaccination in childhood, antibody levels remain high in almost all cases. The study is presented by PhD student Dr. Marc Shamier, Erasmus MC, Rotterdam, Netherlands, from a research team led by Dr Rory de Vries.

During the 2022-2023 mpox outbreak, MVA-BN was rapidly deployed among at-risk populations, including gay, bisexual, and other men who have sex with men (GBMSM). This vaccine is based on a highly attenuated strain of Vaccinia virus (VACV) – a virus that belongs to the orthopoxvirus genus, as do the viruses that cause smallpox (variola virus) and Mpox (monkeypox virus).

Little is known about the longevity of immune responses induced by-MVA-BN vaccination and the impact of prior smallpox vaccination. In this study, the authors assessed the antibody levels response to MVA-BN one year after vaccination. While marketed under various names such as JYNNEOS, IMVANEX, and IMVAMUNE, all are brand names for the same Modified Vaccinia Ankara (MVA)-based vaccine. As such, the immunological effects they confer are expected to be consistent across these products.

Out of the 118 vaccine recipients, 36 (30%) returned for the 1-year follow-up visit. Among individuals without pre-existing immunity, 14/21 (67%) had undetectable levels of VACV IgG and a 10.7-fold decrease in VACV IgG GMT (geometric mean, a standard measurement for antibody levels) was observed compared to the last time point after vaccination in 2022 (4 weeks after the second dose) (Figure 1 full abstract).

In contrast, among individuals with childhood smallpox vaccination, only one participant out of 15 (7%) had undetectable VACV IgG after one year, and the GMT reduction between 4 weeks after the last vaccine dose in 2022 and the one-year follow-up visit was 2.5-fold for those vaccinated with two doses of MVA-BN, and 1.9-fold for those vaccinated with one dose of MVA-BN.

The authors say: “A rapid decline in VACV-specific IgG antibodies was observed one year after MVA-BN vaccination, leading to loss of detectable antibodies in 42% (15/36) of the participants. This reduction was most pronounced in individuals without pre-existing immunity. As the mechanism of protection for mpox remains undefined, the implications of waning antibody levels for conferring protection remain uncertain.”

The authors suggest that the decrease in antibodies over time following MVA-BN vaccination may be attributable its composition. They say: “The first and second-generation smallpox vaccines contained replication-competent vaccinia virus. MVA-BN is based on non-replicating virus, which may impact the strength and duration of the immune response; with the advantage of a low risk of side effects.”

They add: “Regarding the potential necessity for a booster, it is premature to draw such conclusions. It is unclear how waning antibody levels relate to protection. Immunity also involves other elements, such as T-cell responses. Comprehensive clinical monitoring over time, which connects infection rates with antibody levels, is required to make informed decisions about booster vaccination protocols.”

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ARTICLE PUBLICATION DATE

30-Mar-2024

Case report from Austria shows mpox breakthrough infection in man who had received both vaccine doses

A second case is currently under investigation

EUROPEAN SOCIETY OF CLINICAL MICROBIOLOGY AND INFECTIOUS DISEASES

New research to be presented at this year’s European Congress of Clinical Microbiology and Infectious Diseases (ECCMID 2024) in Barcelona, Spain (27-30 April) details the case of a man who had received two doses of the monkey pox vaccine in Autumn, 2022 yet experienced a ‘breakthrough’ mpox infection in January 2024. The authors believe breakthrough should be considered in fully vaccinated individuals engaging in high-risk behaviors. They also call for further research on the need for booster doses to protect against these breakthrough infections. The case report is by Dr Luigi Segagni-Lusignani, Public Health Authority, Vienna, Austria and colleagues. They add a second case, reported in the last few weeks (March 2024) is currently under investigation.

Following the sharp decline in notifications of new mpox infections after introducing the EMA-approved modified Vaccinia Ankara–Bavarian Nordic (MVA-BN) administration in late 2022 and early 2023, an upsurge in mpox cases occurred in the latter half of 2023 in European countries. Clusters were observed in individuals presumed immune through recent vaccination, but data on the durability of protective immunity after complete 2-dose vaccination are limited.

The authors here present a case of mpox infection in a 35-year-old, who had completed the two-dose course of intradermal third-generation Jynneos vaccine as pre-Exposure Prophylaxis (PrEP) on November 8, 2022, with a 28-day interval between the first and second dose. His medical history included well-controlled HIV infection since 2011 (CD4 count of > 700 cells/µL), hepatitis C infection in April 2017, SARS-CoV-2 infection in November 2020, and Campylobacter infections in August 2021 and January 2022.

In January 2024, five days after multiple sexual encounters during a Vienna event, the patient reported fever, chills, headache, discomfort urinating, diarrhoea with bleeding, and penile and anal itching. On day 3, a genital herpes infection was suspected, but no treatment was started. After two days, he presented to the dermatology clinic with worsening lymphadenopathy (swollen lymph nodes), where positive mpox virus PCR results were obtained. His Mpox Severity Score System (MPOX-SSS) was 10 (of a maximum score of 12).

No antiviral treatment was administered, no hospitalisation was required and the patient was home isolated. After 21 days, a control swab was still positive and the isolation had to be extended to day 25 from symptom onset, when finally all scabs fell off the lesions and PCR test on viral swab was negative.

The authors say: “This was Austria's first mpox breakthrough case. Despite no hospitalisation, the clinical course was not less severe than in unvaccinated patients, with longer disease duration and higher scores on the mpox severity scale. The 14-month interval between complete vaccination and infection suggests vaccine-induced immunity could be not durably protective. This case underscores the importance of clinical suspicion for mpox in high-risk groups, even if fully vaccinated with 2-doses. Breakthrough infections need to be explored further, as well as the possibility of vaccine boosters in vaccinated groups with epidemiological risky behaviours.”

They add: “The Austrian Vaccine Board updates its national mpox vaccine strategy annually based on new scientific evidence. Currently, there is no nationwide recommendation for booster shots after completing the currently recommend (Jynneos) vaccination regimen, even for high-risk groups. However, any potential changes to the vaccination strategy will depend on filling critical knowledge gaps in mpox immunity. These gaps include understanding the current level of immunity, the durability of immune responses, and the long-term vaccine effectiveness in high-risk groups.”

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ARTICLE PUBLICATION DATE

30-Mar-2024