Action is needed to safeguard the independence of patient organizations and charities – new study finds
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International Journal of Social Determinants of Health and Health Services
Data/statistical analysis
Not applicable
Pharmaceutical Industry Payments to Patient Organizations in Poland: Analysis of the Patterns, Evolution, and Structure of Connections
The COVID-19 pandemic highlighted how crucial testing is for disease preparedness and response, and new research from the Johns Hopkins Applied Physics Laboratory (APL) and a team of collaborators underscores that principle.
Published in the Jan. 2 edition of The Lancet Public Health, the research included simulation and analysis that suggests public-private partnerships to develop, produce and distribute COVID-19 diagnostic tests saved an estimated 1.4 million lives and prevented about 7 million patient hospitalizations in the United States during the pandemic.
APL, based in Laurel, Maryland, teamed with the Administration for Strategic Preparedness and Response (ASPR), the U.S. Centers for Disease Control and Prevention, and consultants from MITRE Corporation on the study.
“The analysis found that the early development, manufacturing and distribution of tests significantly reduced severe COVID-19 outcomes,” said Gary Lin, a computational epidemiologist at APL and a study co-author. “Through modeling and simulation, we’ve shown how national coordination can effectively leverage resources and capabilities.”
APL researchers developed a digital twin prototype — a virtual simulation environment — to model the testing and diagnostic supply chain. The tool was used to simulate baseline scenarios and assess the effects of potential pandemic interventions.
“The digital twin helps us quantitatively understand the impact and consequences of disruptions and changing infection levels on test availability,” said Elizabeth Currier, the APL digital twin project manager. “It can also evaluate the impact of policies and investments and be used in planning and evaluating supply needs, aiding in response and ensuring a secure supply chain for future medical crises.”
The prototype model integrated diverse data sources, including manufacturing, retail and government stockpile information as well as wastewater and inpatient data, which enabled the team to assess complex scenarios. It simulated forecasting for infectious disease cases to reflect demand for tests, production of tests, and supply and distribution logistics.
Between January 2020 and December 2022, government efforts produced more than 6.7 billion COVID-19 tests in the United States. These included laboratory tests, point-of-care tests and over-the-counter tests, with more than 2.7 billion tests performed in U.S. laboratories, in health care facilities or at home.
“The findings underscore the importance of robust and rapid test development, production and distribution to address future public health threats,” Currier said. “The insights gained from integrating data go beyond responding to COVID-19: They prepare us for future pandemics with a scalable framework to allocate resources effectively.”
APL’s digital twin modeling has since expanded to monitor nationwide testing for COVID-19, influenza, respiratory syncytial virus (RSV) and other public health threats under an all-hazards approach.
The Lancet Public Health
Computational simulation/modeling
Not applicable
The SARS-CoV-2 test scale-up in the USA: an analysis of the number of tests produced and used over time and their modelled impact on the COVID-19 pandemic
3-Jan-2025
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A visual representation of Artificial Intelligence applications in pandemic response, highlighting key areas like epidemiological modelling, vaccine development, healthcare optimization and challenges & considerations.
view moreCredit: Praveen Kumar
A recent article published in Molecular Biomedicine by researchers at Datta Meghe Institute of Higher Education and Research explores the multifaceted role of Artificial Intelligence (AI) in pandemic preparedness and response. The team, comprising Dr. Praveen Kumar, undergraduate contributors Mayur Gawande, Nikita Zade and Induni Nayodhara Weerarathna, and faculty members Dr. Swapnil Gundewar and Dr. Prateek Verma, delves deeply into the applications, benefits, and challenges of AI technologies in global health crises.
The review provides a comprehensive assessment of AI's transformative potential, starting with its use in epidemiological modelling. AI-driven models, such as SIR (Susceptible-Infectious-Recovered) and SIS (Susceptible-Infectious-Susceptible), are highlighted as key tools for understanding and predicting disease transmission. These models have significantly improved outbreak forecasting, allowing policymakers to implement timely and effective interventions. By integrating large datasets from varied sources, AI optimizes resource allocation and enhances the efficiency of public health responses.
The article also investigates AI’s role in vaccine development, one of the most critical aspects of pandemic management. The authors detail how AI expedites the identification of vaccine candidates through molecular simulations and accelerates the design of clinical trials, reducing the time to market for life-saving vaccines. For instance, AI was instrumental in rapidly developing mRNA vaccines during the COVID-19 pandemic, showcasing its ability to tackle unprecedented challenges.
A significant strength of the review is its balanced analysis of the ethical, practical, and societal challenges accompanying AI applications in healthcare. Data privacy, algorithmic biases, and equitable access to AI-driven healthcare innovations are thoroughly discussed. The authors emphasize the need for responsible governance and robust ethical frameworks to ensure AI technologies are applied fairly and inclusively, particularly in resource-constrained settings.
In addition to its technical applications, the review explores AI's impact on real-time disease surveillance and monitoring. AI algorithms process data from diverse sources, including electronic health records, mobile applications, and social media platforms, to detect and track outbreaks early. These insights enable health authorities to act swiftly, potentially preventing the escalation of localized outbreaks into global pandemics.
The article also highlights the collaborative potential of AI. Researchers and public health officials can create integrated systems that enhance pandemic preparedness and response by combining expertise from multiple disciplines. The review underscores the importance of international cooperation, shared data infrastructures, and interdisciplinary research in realizing AI’s full potential for global health security.
Finally, the authors call for continued research to address the gaps and challenges in implementing AI technologies. The review stresses the importance of ethical AI deployment and its alignment with public health goals, advocating for its use to anticipate, mitigate, and ultimately overcome global health crises.
This comprehensive review is an essential resource for healthcare, technology, and policymaking stakeholders, providing a roadmap for leveraging AI to create resilient and adaptive health systems in the face of future pandemics.
See the article:
The Role of Artificial Intelligence in Pandemic Responses: From Epidemiological Modeling to Vaccine Development.
https://doi.org/10.1186/s43556-024-00238-3
Molecular Biomedicine
The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development
3-Jan-2025
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| 1 MILLION DEAD FROM COVID UNDER TRUMP |
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A solar farm in the desert.
view moreCredit: Coimbra Research Group, 2018
Rooftop solar panels are popular in many parts of the world, but power is generated much more cheaply and efficiently in utility-scale solar farms. Often, though, these large-scale solar farms are deployed in desert habitats, which contain native flora and fauna that are highly sensitive to changes in temperature and humidity.
In a study recently published in Advances in Atmospheric Sciences, Professor Carlos Coimbra of the University of California San Diego outlines in detail the thermal balances between solar farm panels and the surrounding environment, which can then be used to examine the thermal effects of solar plants on desert habitats and vice versa.
The work falls under the umbrella of the emerging field of “energy meteorology”, which in its broadest sense covers any effect that weather has on power generation, transmission and distribution systems. In Professor Coimbra’s study, whilst the use of energy meteorology is restricted to solar power generation, its usual scope is also expanded to include not only the effects of weather on solar power plants, but also the reverse, i.e., the effect of solar power plants on the local environment.
The ability to calculate in detail the thermal balances of solar panels, which are characterized according to their main material components, allows relationships to be derived between difficult-to-measure flow-dependent variables such as the mean convective heat transfer coefficients and radiative fluxes to and from the panels. These relationships can then be exploited through measurements or model estimates to develop a more complete and consistent picture of solar farm thermal effects on the local environment.
In addition, the study puts forward a method that can classify regional microclimates in terms of the effective optical depth of the cloudy atmosphere. Such a classification can provide resourcing information that complements the monthly, daily, or hourly averaged values of cloudiness or clearness indices for shortwave radiation used in the design, siting and management of solar power plants.
“It behooves us in the solar energy research community to answer concerns and criticisms that the solar power industry encounters with the best possible science. It could very well be that the net thermal impact of large-scale power plants is minimal, or even benign, but the conflicting results reported in the research literature point toward the need to study the problem from the standpoint of fundamental thermal balances,” explains Professor Coimbra.
In this respect, the work reported in this paper stands as an attempt to motivate solar engineers and energy meteorologists alike to push forward with studying and assessing the environmental impacts of large-scale solar farms. Essentially, the analysis is intended to serve as a research primer for those interested in exploring new research opportunities in energy meteorology applied to solar farms.
The study is included in a recently published special collection on solar energy meteorology.
Advances in Atmospheric Sciences
Energy Meteorology for the Evaluation of Solar Farm Thermal Impacts on Desert Habitats
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Virunga National Park
view moreCredit: INRAE - S. Desbureaux
Sub-Saharan Africa is home to 13% of biodiversity and represents approximately 20% of the world’s forests. Protected areas play an essential role in protecting biodiversity and ecosystems. Since the first protected area was set up in 1925 in the Democratic Republic of the Congo, the Virunga National Park, several thousand parks have been established. But the structural lack of funding, limited management capacities, weak institutions and governance complicate the missions of these areas to protect wildlife and their habitats effectively. To alleviate these difficulties, innovative management models have been set up over the last 20 years: states and NGOs co-manage these parks through public-private partnerships. These collaborative management partnerships (CMPs) can also go as far as delegating the full management of thousands of square kilometres of a territory in one or several states to national or international NGOs. Another specificity of these CMPs is their duration: the collaborations are set up for several decades (around 25-30 years, even 40 years in certain cases), while NGOs usually support projects over 2 to 5 years. CMPs facilitate substantial, long-term funding (P. Lindsey et al. 2021 Biological Conservation), making it possible, for example, to recruit and train staff and park rangers, as well as to build infrastructure to help local populations to reduce their dependence on park resources and improve their living conditions (power stations around the Garamba and Virunga Parks, roads, tourism infrastructure, etc).
The researchers examined this change in approach to see whether these investments have made protected areas more effective. Their study identified 127 partnerships across 16 countries in Sub-Saharan Africa in 2023, involving 48 NGOs, 21 of which are national and 27 international. These areas cover almost 1 million square kilometres, nearly twice the size of France. The researchers assessed the impact of CMPs by comparing the rate of tree cover loss before and after they were established. Their results show that CMPs have reduced deforestation by an average of 55% in protected areas. They are particularly effective in protected areas under a high level of anthropogenic pressure, where the reduction in deforestation reaches 66%.
These results illustrate that long-term CMPs between governments and non-governmental organizations can be part of the solution to improving biodiversity protection. However, the duration of CMPs requires states to implement monitoring mechanisms to assess their impact. In addition, future research will need to determine whether the improvement in environmental conditions benefits the populations living near these parks.
Proceedings of the National Academy of Sciences
Collaborative management partnerships strongly decreased deforestation in the most at-risk protected areas in Africa since 2000
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Copper-cluster catalysts on activated carbon.
view moreCredit: Cedric Koolen (EPFL)
Acetaldehyde is a vital chemical used in making everything from perfumes to plastics. Today, its production largely relies on ethylene, a petrochemical. But increasing environmental concerns are pushing the chemical industry to reduce its reliance on fossil fuels, so scientists have been searching for greener ways to produce acetaldehyde.
Currently, acetaldehyde is produced through the so-called “Wacker process”, a chemical synthesis method that uses ethylene from oil and natural gas with other chemicals such as strong acids, i.e. hydrochloric acid. The Wacker process not only has a large carbon footprint but is resource-heavy and is unsustainable in the long run.
A promising solution to this problem is the electrochemical reduction of carbon dioxide (CO2) into useful products. As CO2 is a waste product that contributes to global warming, this approach tackles two environmental issues at once: it reduces CO2 emissions and creates valuable chemicals.
An innovative catalyst for greater efficiency
Copper-based catalysts have shown potential for this transformation, but so far, they’ve struggled with low selectivity — which means that they produce a mixture of products rather than the desired acetaldehyde.
Now, scientists of a public-private consortium, led by Cedric David Koolen in the group of Andreas Züttel at EPFL, Jack K. Pedersen at the University of Copenhagen, and Wen Luo at Shanghai University have developed a novel copper-based catalyst that can selectively convert CO2 into acetaldehyde with an impressive efficiency of 92%.
The breakthrough, published in Nature Synthesis, provides a greener and more sustainable way to produce acetaldehyde, and could replace the Wacker process. Moreover, the catalyst is scalable and cost-effective, opening the door for industrial applications.
“The Wacker process effectively hasn’t changed in the past 60 years. It is still based on the same basic chemistry. The time was ripe for a green breakthrough,” says Koolen.
“Fascinating chemistry”
The researchers began by synthesizing tiny clusters of copper particles, each about 1.6 nanometers in size, using a method called spark ablation. This technique involves vaporizing copper electrodes in an inert gas environment, and allowed the scientists to precisely control particle sizes. The copper clusters were then immobilized on carbon supports to create a stable and reusable catalyst.
In the lab, the team tested the catalyst’s performance by running it through a series of electrochemical reactions with CO2 in a controlled environment. Using a synchrotron — a large scale facility that generates a very bright light source — the team ensured that the copper clusters were actively converting CO2 to acetaldehyde by a technique called X-ray absorption spectroscopy.
The results were remarkable. The copper clusters achieved 92% selectivity for acetaldehyde at a relatively low voltage, which is essential for energy efficiency. In a 30-hour stress test, the catalyst demonstrated high stability, maintaining its performance across multiple cycles. The researchers also found that the copper particles retained their metallic nature throughout the reaction, which contributes to the catalyst’s longevity.
“What was really surprising to us was that the copper remained metallic, even after removal of the potential and exposure to air,” says co-lead author Wen Luo. “. “Copper usually oxidizes like crazy, especially copper that small. But in our case, an oxide shell formed around the cluster protecting the core from further oxidation. And this explains the recyclability of the material. Fascinating chemistry.”
The keys to success
Why did the new catalyst work so well? Computational simulations showed that the copper clusters feature a specific configuration of atoms that promotes CO2 molecules to bond and transform in a way that favors the production of acetaldehyde over other possible products, like ethanol or methane.
“The great thing about our process is the fact that it can be applied to any other catalysts system,” says co-lead author Jack K. Pedersen. “With our computational framework, we can quickly screen clusters for promising characteristics. If it’s for CO2 reduction, or water electrolysis, with spark ablation we can produce the new material with ease and directly test it in the lab. This is so much faster than your typical test-learn-repeat cycle.”
The new copper catalyst is a significant step toward greener industrial chemistry. If scaled up, it could replace the Wacker process, reducing the need for petrochemicals and cutting down on CO2 emissions. Since acetaldehyde is a building block for many other chemicals, this research has the potential to transform multiple industries, from pharmaceuticals to agriculture.
Other contributors
Reference
Koolen, C. D., Pedersen, J. K., Zijlstra, B., Winzely, M., Zhang, J., Pfeiffer, T. V., Vrijburg, W., Li, M., Agarwal, A., Akbari, Z., Kuddusi, Y., Herranz, J., Safonova, O. V., Schmidt-Ott, A., Luo, W., Züttel, A. Scalable synthesis of Cu cluster catalysts via spark ablation for the highly selective electrochemical conversion of CO2 to acetaldehyde. Nature Synthesis 03 January 2025. DOI: 10.1038/s44160-024-00705-3
Cedric David Koolen showing an example electrochemical cell used in the Laboratory of Materials for Renewable Energy.
Cedric David Koolen, co-lead-author of the study, posing with the spark ablation device used to generate the clusters in the Laboratory of Materials for Renewable Energy.
Credit
EPFL
Nature Synthesis
Scalable synthesis of Cu cluster catalysts via spark ablation for the highly selective electrochemical conversion of CO2 to acetaldehyde.
3-Jan-2025
“In high-income countries like the U.S. or Germany, farmers receive less than a quarter of food spending, compared to over 70 percent in Sub-Saharan Africa, where farming costs make up a larger portion of food prices,” says David Meng-Chuen Chen, PIK scientist and lead author of the study published in Nature Food. “This gap underscores how differently food systems function across regions.” The researchers project that as economies develop and food systems industrialise, farmers will increasingly receive a smaller share of consumer spending, a measure known as the ‘farm share’ of the food dollar.
“In wealthy countries, we increasingly buy processed products like bread, cheese or candy where raw ingredients make up just a small fraction of the cost,” adds Benjamin Bodirsky, PIK scientist and author of the study. “The majority of the price is spent for processing, retail, marketing and transport. This also means that consumers are largely shielded from fluctuations in farm prices caused by climate policies such as taxes on pollution or restrictions on land expansion, but it also underscores how little farmers actually earn.”
Examining the full food value chain to uncover climate policy impacts
To arrive at these conclusions, the team of scientists combined statistical and process-based modelling to assess food price components across 136 countries and 11 food groups. They studied prices of food both consumed at home and away from home. "Most models stop at farm costs, but we went all the way to the grocery store and even the restaurant or canteen,” says Chen. By analysing the entire food value chain, the researchers also provide new insights into how greenhouse gas mitigation policies impact consumers: “Climate policies aimed at reducing emissions in agriculture often raise concerns about rising food prices, particularly for consumers. Our analysis shows that long supply chains of modern food systems buffer consumer prices from drastic increases, especially in wealthier countries,” explains Chen.
Climate policies impact consumers differently in wealthy and poor countries
“Even under very ambitious climate policies with strong greenhouse gas pricing on farming activities the impact on consumer prices by the year 2050 would be far smaller in wealthier countries,” Bodirsky says. Consumer food prices in richer countries would be 1.25 times higher with climate policies, even if producer prices are 2.73 times higher by 2050. In contrast, lower-income countries would see consumer food prices rise by a factor of 2.45 under ambitious climate policies by 2050, while producer prices would rise by a factor of 3.3. While even in lower-income countries consumer price rises are less pronounced than for farmers, it would still make it harder for people in lower-income countries to afford sufficient and healthy food.
Despite food price inflation, poor consumers do not necessarily need to suffer from climate mitigation policies. A previous study by PIK (Soergel et al 2021) showed that if revenues from carbon pricing were used to support low-income households, these households would be net better off despite food price inflation, due to their higher incomes.
“Climate policies might be challenging for consumers, farmers, and food producers in the short term, but they are essential for safeguarding agriculture and food systems in the long run,” says Hermann Lotze-Campen, Head of Research Department “Climate Resilience” at PIK and author of the study. “Without ambitious climate policies and emission reductions, much larger impacts of unabated climate change, such as crop harvest failures and supply chain disruptions, are likely to drive food prices even higher. Climate policies should be designed to include mechanisms that help producers and consumers to transition smoothly, such as fair carbon pricing, financial support for vulnerable regions and population groups, and investments in sustainable farming practices.”
Article
David Meng-Chuen Chen, Benjamin Bodirsky, Xiaoxi Wang, Jiaqi Xuan, Jan Philipp Dietrich, Alexander Popp, Hermann Lotze-Campen (2025): Future food prices will become less sensitive to agricultural market prices and mitigation costs. Nature Food. DOI: 10.1038/s43016-024-01099-3
Nature Food
Computational simulation/modeling
Future food prices will become less sensitive to agricultural market prices and mitigation costs.
3-Jan-2025
