Public health

Lessons From the Mpox Response

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During the summer of 2022, mpox (then known as monkeypox) was spreading rapidly across the US, largely affecting gay and bisexual men who have sex with men (GBMSM).1 Fifteen months later, the outbreak looks very different. Cases are down to an average of approximately 1 to 2 per day (from a peak of 600 per day),2 the summer 2023 wave that was widely predicted did not materialize, and the clusters that occur now are quickly controlled (Figure). How did we get here? And what did the lessons of the mpox response teach us about managing future outbreaks? Even though the biomedical tools (tests, vaccines, and therapeutics) were available at the start of the outbreak, how they were deployed provides important lessons. There are 3 key lessons from the response that can help better manage infectious disease outbreaks in the future.

Mpox Epidemic by Week for 2022-2023

Based on data from the US Centers for Disease Control and Prevention.

The primary strategy for mpox containment was to take an approach that deeply engaged the community most affected. Rather than the community as the object of a public health intervention, they became the vehicle. The views (often criticisms) of those most affected by the virus were used to inform policy and create shared accountability. One example was creating the equity mpox workshop composed of GBMSM and transgender racial and ethnic minority individuals. This monthly workshop, suggested by a prominent member of the GBMSM community, provided feedback to the White House that helped calibrate the community-driven response. The White House Mpox Response Team (WHMRT) built trust among the community by engaging, listening, and acting on their suggestions. In return, the community became the trusted messengers.

A variety of strategies were used to distribute information from accessible webinars to infographics circulated on social media. These communications allowed local and state public health leaders to transparently answer questions on the minds of community members. One key lesson from the COVID-19 response was that outbreaks create information needs and filling those needs with high-quality, easily comprehensible information is critical to prevent misinformation from propagating. Letting the community identify the information needs and then transparently filling those needs, including acknowledging scientific uncertainty, was critical to managing the mpox outbreak.

A second lesson from the mpox response was that public health responses must be flexible and responsive. Even though vaccines were available in traditional places for administration (such as physician offices and retail pharmacies), the community partners emphasized the importance of also making vaccinations available where those who would most benefit were likely to be present and comfortable. Applying lessons learned in HIV-related outreach, vaccines were offered in safe spaces outside night clubs, pop-up events, social venues, sex parties, and other community-focused events such as Atlanta Black Pride and Southern Decadence.3–5 This level of community engagement enhanced equity in mpox vaccination and better aligned vaccine providers with the community they served, both of which were essential to curbing the outbreak.

Risk assessment is another example of a key change made due to feedback from community partners. After initially using the traditional public health approach of conducting risk assessments before administering vaccines, we quickly heard from community partners that risk assessments are often stigmatizing and could dissuade many of the highest-risk individuals from even engaging. Therefore, the need for extensive risk assessment was removed and trusted partners were leveraged to help identify the people most likely to benefit from vaccines, education, and prevention messaging. We also heard clear concerns that the temporary mark left at the mpox injection site might disclose information on sexuality or gender identity. More flexible clinical guidance was adopted that allowed the vaccine to be administered on less visible parts of the body, and encouraged people to express a preference for the injection site. This seemingly small change may have had a large effect on both creating greater vaccine acceptance and generally building community trust.

The third lesson was the importance of flexible resources and investments in public health infrastructure for preparedness and rapid response during public health emergencies. When the Secretary of the US Department of Health and Human Services determined that mpox had the potential to become an infectious disease emergency, public health officials were able to use the US Centers for Disease Control and Prevention infectious diseases rapid response reserve fund to deploy resources quickly. Public health officials working on HIV and sexually transmitted infections prevention activities were able to conduct mpox prevention work in conjunction with these ongoing activities. Given that the communities most vulnerable to mpox overlap significantly with those most affected by HIV (between 35%-47% of those diagnosed with mpox also had HIV),6 drawing on the capabilities and infrastructure that already existed for HIV proved extremely useful in containing the mpox outbreak. The WHMRT also coordinated activities across the US Department of Health and Human Services and the US Department of Housing and Urban Development to provide additional resources for the response.

Beyond those 3 key elements of the response, there is one more critical issue to consider. As the number of new cases declined during the fall of 2022, there was intense pressure to bring the mpox response to an end and fold it into ongoing public health work around sexually transmitted infections. It is tempting to see declining case numbers as an invitation to declare the effort a success.

Despite what is often a short attention span of policymakers, the White House recognized that declining case numbers or even an end to the declared public health emergency should not end the mpox response. The WHMRT was concerned with the disproportionate effect mpox had on Black and Latino communities and people living with HIV and recognized that mpox required ongoing attention and critical work to prevent resurgence.7 Instead of pulling back, the WHMRT redoubled its efforts in the spring of 2023 to build trust and vaccinate those who were vulnerable. As we neared the summer and seasonal festivities that could increase opportunities for the virus to spread, the team made additional efforts to partner with event organizers and the communities they serve to provide people with a holistic toolkit to inform their decisions about how to keep their summer healthy.8,9 The lack of a second wave of mpox this past summer was due in large part to the ongoing work with the communities most affected and the decision to continue driving awareness. Persistence is the key lesson. Even after the infection numbers decline, it is paramount to prevent outbreak resurgence.

The last few years have been remarkable in how infectious diseases have taken a toll. The lesson from the mpox response is clear: community engagement and flexibility of response are necessary as well as the existing public health infrastructure that can be deployed to manage outbreaks. Medical countermeasures are key, but so are community partnerships, flexibility, and persistence. That is how infectious disease outbreaks should be managed now and in the future.

Artificial intelligence cooperation to support the global response to COVID-19

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In an unprecedented effort of scientific collaboration, researchers across fields are racing to support the response to COVID-19. Making a global impact with AI tools will require scalable approaches for data, model and code sharing; adapting applications to local contexts; and cooperation across borders.

As of 24 April 2020, the SARS-CoV-2 virus had infected 823,626 people with more than 40,598 confirmed deaths, and with nearly every citizen of the planet at risk1. Given the need to interrupt disease transmission and the increasing scale of the pandemic, digital technologies are relevant to support the fight against the virus. Among these technologies, machine learning and artificial intelligence (AI) methods are being applied in many COVID-related domains, resulting in approximately 200 preprints and scientific articles from 1 January 2020 to 24 April 20202. However, for AI applications addressing COVID-19 to have a global impact, large-scale data and model sharing, operational validation, and adaptation to local contexts are needed. This requires cooperation and solidarity across borders as well as the involvement of many relevant parties, including healthcare workers.

Taxonomy and applications

In a review of the emerging literature at the intersection of AI and COVID-19 by some of us3, a framework to categorize multidisciplinary research on three scales is proposed: molecular, clinical and societal (epidemiology and infodemics).

Molecular applications include protein structure prediction4, improving viral nucleic acid testing5, drug repurposing6 and drug discovery7. These applications draw on a range of AI methods including the construction and mining of biomedical knowledge graphs, deep learning architectures designed to predict characteristics of protein structures or protein–ligand binding affinities, text modelling approaches applied to genetic sequences, and the use of reinforcement learning for drug design.

Clinical applications to improve patient care range from diagnosis to patient follow-up, treatment and outcome prediction. Deep learning techniques can help image-based diagnosis of COVID-19 from patterns in X-ray images and computed tomography (CT) scans8. Operational human-in-the-loop AI systems have been developed to help radiologists reduce the time needed to review scans. Smart watches, mobile phones and other wearables can potentially be used for disease tracking9, along with other remote monitoring applications that allow doctors to follow patients remotely, saving time and personal protective equipment. Combining different data sources like health records and medical imagery can help predict patient outcomes10 and could be used to project the needs of hospitals and healthcare systems such as surges in demand for intensive care unit beds. The use of robotics in telemedicine and in other tasks like cleaning and sterilizing medical facilities could also prove valuable.

For epidemiology, AI can improve early warning systems and the modelling of empirical data11. In particular, AI can be applied to understand and simulate public policy interventions such as quarantining, social distancing and de-escalation strategies, and augment classical epidemiological techniques by approximating functions for which analytic transmission equations are not known12,13. Additionally, unsupervised clustering techniques and risk-scoring algorithms, which are able to combine disparate data sources, may help identify similarities between regions, and forecast which areas will require more resources.

For infodemics, AI can be used to fight misinformation and disinformation by managing the current overabundance of information, which creates confusion and makes it difficult to identify trusted sources14,15. AI methods can support audience analysis (for example, social media, TV, radio) and accelerate fact checking16. Social media analysis, for example, is providing insights into global trends and sentiment around the pandemic and its socioeconomic impacts17. Research is being conducted to identify the emergence and escalation of hate speech and verbal attacks against minorities and communities suffering from discrimination that may result in violent action or their exclusion from access to healthcare18. Virtual assistants and chatbots are being used to disseminate trusted content at scale19, requiring mechanisms for propagation of updates to information as new evidence becomes available in the COVID-19 response.

Data and model sharing

AI applications require data. There are currently dozens of data-sharing initiatives around COVID-19 at the three application scales, spanning the international, national and local levels. These datasets include: genetic sequences20, genome analysis21, protein structures, patient clinical data, medical imagery, case statistics, epidemiological data22, mobility data, social media posts, news articles and scientific literature23. The hyper-fragmentation of data-sharing efforts is a challenge, as it might result in advances that are restricted to particular projects and local communities. Establishing scalable approaches for data, model and code sharing could accelerate the development and dissemination of new applications. At this stage, global, open, comprehensive, comparable and verified data-sharing initiatives will be beneficial to connect and promote cooperation between disparate communities and geographies24.

Open science can accelerate knowledge dissemination and capacity building of national health systems, supported by multi-stakeholder AI partnerships operating across international borders. For example, the data platform of the Epidemic Intelligence from Open Sources (EIOS)25 network enables early detection, verification and assessment of public health risks and threats using open source information. Under the philosophy of collaboration and not competition in early detection, the community of practice for public health intelligence includes governments, international organizations and research institutes that collaboratively assess and share information about outbreak events in real time. The EIOS network picked up the first article reporting an unknown pneumonia cluster in Wuhan at 3:14 UTC on 31 December 2019. From the epidemiological perspective, global standards and interoperability between databases could enable coordinated response and decision-making at global, national and local levels. Understanding the epidemiologic features and risk characteristics of different demographics as we move into different phases of the pandemic will require accounting for health system resource capacities, public health interventions, environmental factors and the social implications of COVID-19.

Beyond data sharing, few initiatives currently share trained AI models related to any of the proposed applications. Barriers to be overcome include constraints due to specific computational, architecture and infrastructure requirements; a lack of documentation; validation and explainability aspects; and legal concerns regarding privacy and intellectual property. Sharing pre-trained and validated AI models could accelerate the adaptation of solutions to local contexts. Examples of models that could be widely applicable include those used to diagnose illness from imagery, predict patient outcomes, filter misinformation and disinformation based on spreading patterns through social networks, or distil knowledge graphs from large collections of scientific articles. Getting to a future of open AI models will require AI governance frameworks that take into account ethical, social, clinical, legal and commercial considerations.

From research to impact

One of the challenges of making a greater impact with AI applications is not knowing where to start and how efforts can be most effective. There is a need for greater cooperation between practitioners and the AI community. The AI community already is, and should continue to seek advice and guidance from domain experts, including government officials, healthcare professionals and first responders, among others. They can help flag processes that are good candidates for automation. These include repetitive or time-consuming tasks that involve finding patterns in rich image, video, audio or biomedical data — for example, CT scans — or tasks that involve synthesizing massive datasets from sources such as symptom tracking systems or social media channels.

To date, few of the research projects and systems presented are as yet sufficiently mature to be operationalized at scale, with different applications having different timescales of development, validation and deployment. As a result, it is important for the founders, users and AI community to map which technologies could assist with the short-term response, mid-term recovery efforts, and the longer-term preparedness for future pandemics.

Developing solutions for the current pandemic requires coordination and prioritization26, focused on key unmet needs that account for operational realities. When possible, solutions should be based on adapting already validated systems27 and should avoid overburdening an already stretched healthcare workforce with new tools that may not always help to improve outcomes. Furthermore, it is important that new and existing solutions are adapted to fill the specific needs and contexts of low- and middle-income countries. Applications dealing with clinical and patient data should not ignore the existing regulatory frameworks designed to ensure quality, security and safety, and minimize potential risks and harms. Despite the urgency of the fight against COVID-19, rigorous assessment of potential solutions is required, which in some opportunities can be fast-tracked without increasing risks.

Collaborations among global health actors, private sector partners and other stakeholders are already forming to accelerate the development, production and equitable global access to new health technologies essential to COVID-1928. Coordination and cooperation between regulatory bodies and international and regional organizations would aid in channelling research on the ground, and would assist in implementing systems in countries with weaker frameworks and governance structures. Compliance with reporting guidelines29,30 would enable more systematic and efficient reviews of evidence, and comparisons of healthcare-related AI applications along the dimensions of safety, clinical validity and performance accuracy.

The global fight against the COVID-19 infodemic should be treated as a scientific challenge on a par with the spread of the disease itself, since behavioural change is critical to the pandemic response. Media and information literacy remain critical, and there is a need to quantify individual rates of exposure to misinformation and disinformation. Infodemic management frameworks can be used to support timely translation of evidence into knowledge and advocacy adapted to local cultures, languages and contexts. AI methods and tools should be used to fill the health information gaps for individuals and policymakers alike for a whole-of-society response based on evidence and science. To effectively combat the infodemic while ensuring the fundamental right to access to information, the international community must share and amplify good practices, identify priorities, facilitate partnerships, and provide advice and technical assistance to governments and relevant national stakeholders to foster international cooperation. The pandemic is stoking xenophobia, hate and exclusion, posing a far-reaching — and potentially long-lasting — threat to human rights31. Understanding the dynamics and spread of hateful speech will help design more effective interventions and change the narrative.

Global challenges and digital cooperation

We now have the ability to create new AI tools to address age-old problems. But having the means to create such applications doesn’t necessarily mean we should. Any AI application that could be used in the fight against COVID-19 ought to undergo an assessment to ensure that it complies with ethical principles and, above all, respects human rights. Even when following privacy-by-design and ethics-by-design guidelines in the development and deployment of AI-based solutions, practitioners will be confronted with questions on how to protect fundamental rights, including the right to privacy. When rolling out any of the above proposed AI solutions at scale, we must ensure they do not breach global commitments to protect rights and freedoms, including commitments to non-discrimination, preventing mass surveillance, and protecting journalistic sources. In order to do so, stakeholders should ensure that principles, including those of openness and accessibility, are at the heart of AI-enabled solutions. AI applications in health should also promote fair and equitable global access, supporting member states’ commitments to achieve universal health coverage.

The global nature of the pandemic requires global solutions, but there is also a need for local adaptation to account for biases and contextual factors. For instance, a system to diagnose COVID-19 pneumonia in chest X-rays will need to be trained differently in countries with different levels of prevalence of diseases or conditions with related image patterns, such as tuberculosis and HIV. Similarly, epidemiological models tailored to pastoral areas, island states, refugee camps or conflict zones should take into account different socioeconomic, cultural and structural variables than the ones described in scientific literature — which have been developed mostly in China or in Western countries. Likewise, chatbots to inform citizens about public health measures require specific natural language processing models, and often vast amounts of training data, which today are available for just a few hundred of the more than 7,000 living languages. The participation of researchers and local data science collaboratives from underrepresented regions including Africa and Latin America, for example the Data Science Africa network, will be critical to ensure that any AI system has a positive impact at global scale. With this in mind, solutions may need to be designed with low-bandwidth requirements up front — for example, medical diagnosis apps without need for connectivity and that do not compromise privacy or data security. Such applications represent an opportunity to promote edge computing for AI and other energy-efficient approaches for the responsible use of computational resources.

The role of AI in providing meaningful solutions to the current pandemic has yet to be defined. However, there is a clear need for a globally inclusive research agenda to direct action against this pandemic — and future ones — without leaving anyone behind. It is reasonable to believe that the world will be more digital than ever in the post-coronavirus era, and that AI will increasingly become one of the driving forces shaping our society32. This pandemic underscores the urgency for stakeholders to effectively translate ethical principles for AI into practice33. ‘Solidarity’ is the name of the international clinical trial launched by the World Health Organization to help find an effective treatment for COVID-1934. It is the sense of solidarity with our neighbours that encourages physical distancing, which is vital to suppressing transmission of the virus within communities. Similarly, solidarity should be a core principle guiding the development of innovative and ethical AI applications to fight the COVID-19 pandemic, and help advance the global Sustainable Development Agenda

Science, Competing Values, and Trade-offs in Public Health — The Example of Covid-19 and Masking

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Public health institutions have long walked the difficult line between respecting individual freedoms and protecting society from disease threats — which has sometimes involved restricting those freedoms. This balancing act has often been met with contentious public debate and legal challenges. In perhaps the most famous example, the state’s police power to protect public health was affirmed by the U.S. Supreme Court in its 1905 decision in Jacobson v. Massachusetts. The Court determined that a state may compel vaccination, as a result compromising people’s right to bodily autonomy, for the purpose of promoting public health — thereby upholding the community’s competing right to protect itself from deadly disease.

During the Covid-19 pandemic, negotiating such trade-offs became substantially more complex, given a rapidly changing environment and an evolving body of knowledge about SARS-CoV-2. Particularly early in the pandemic, decisions affecting personal freedoms had to be made quickly, with little opportunity for public deliberation. Public health authorities understandably made decisions by relying on prepandemic planning that was based on previous experience with respiratory viruses. As the pandemic dragged on, however, the continued absence of publicized debate about these trade-offs within public health institutions and among public health experts turned masking into a flash point for the clash between competing rights: the right to bodily autonomy (including the freedom to decide whether to mask) and the right to be protected from the threat of Covid-19. Far too often, discussions about the implications of various masking policies were drowned out by absolutist language on both sides of the debate, suggesting, on the one hand, that mask mandates were an unacceptable infringement on freedoms or, on the other, that choosing not to mask was tantamount to choosing to harm others.

The reality is far more complex, and the all-or-nothing disputes that have predominated during the past 2 years have obscured the difficult choices that public health authorities must make and the range of factors that should be weighed when considering mask mandates. Such factors include, but aren’t limited to, the evidence for the efficacy of masking in communities with a range of Covid-19 transmission rates, the potential downsides of wearing a mask in various social contexts, and which groups of people bear the highest risk of infection. Early in the pandemic, when Covid-19 vaccines weren’t available, when there was limited epidemiologic evidence to inform mitigation policy, and when the risk of infection was high, it was perhaps easier for authorities to reach decisions to implement mask mandates. Matters became more complicated, however, as the pandemic evolved. We believe the decisions that have been made during this later stage of the pandemic — after the introduction of highly effective vaccines, and when the trade-off between the efficacy and the perceived harms of masking in public spaces was more nuanced — warrant reexamination by public health institutions.

One example of public spaces affected by mask mandates are grocery stores. For the average, healthy customer, a mask mandate may serve little purpose if community levels of Covid-19 are low. But the risk calculation is different for cashiers and other essential workers in these spaces. These workers are more likely than members of the general working public to be Black or Latinx, to have incomes below 200% of the federal poverty level, or to live with someone who is 65 years of age or older.1 Such lower-income and marginalized racial and ethnic groups have had disproportionately poor outcomes during the pandemic, as have older adults. In these spaces, the benefits of mask mandates to essential workers may outweigh the inconvenience that masks pose to customers, even if community transmission levels are relatively low. At the same time, such benefits may not outweigh the costs associated with engaging in frequent confrontations with customers over masking. The ability to make these calculations, which are specific to local contexts, might obviate the need for a blanket masking policy; such nuances also suggest that the most useful role for public health institutions may be to provide data to support risk assessments and frameworks that could guide decision making by relevant local leaders.

Another example of public spaces affected by mask requirements and other Covid-related policies are local courthouses. The state has the power to compel people to be present in courthouses as defendants, lawyers, witnesses, and jury members. Given this power to compel, the state has a duty to protect people in these spaces. Criminal defendants are often residing in congregate-living settings (i.e., jails), where Covid-19 outbreaks have spread quickly and with deadly consequences, and many are poor and are members of marginalized racial groups. The state also has a responsibility to citizens who expect their health and safety to be protected while they serve as jurors for their peers.

To fulfill these responsibilities while carrying out essential functions of the legal system during Covid-19 surges in 2020 and 2021, many courts adopted risk-mitigation measures, including virtual court hearings, social distancing in courtrooms, lightened trial schedules and delayed trial dates, mask mandates, and jury-service exemptions for people at high risk for complications of Covid-19 (or people who were particularly fearful of Covid-19).2 But some of these measures may have compromised the rights of people interacting with the legal system. Lightened trial schedules hinder the constitutional right to a public trial without delay. Holding trials virtually or spreading jurors throughout the courtroom to facilitate social distancing may make it too easy for jurors to become distracted and may thus influence judgments.3 Masks may affect jurors’ perception of testimony, thereby potentially compromising the right to a fair trial.4 There is no simple way to balance the right to health and safety with the right to equal access to justice for people compelled to participate in the court system. The role of public health institutions is to advance recommendations based on science, but decisions must ultimately take into account a breadth of concerns, many of which may be beyond the remit of public health authorities. Public health entities shouldn’t make these judgment calls in isolation, particularly without including local stakeholders in the process.

Public health decision making related to Covid-19 has required complicated balancing; some decisions, such as whether to close schools, can have substantial consequences for an entire generation. A confluence of factors that coincided with the beginning of the Covid-19 pandemic — including an impending U.S. federal election and the ascendance of social media as a dominant platform for public conversation — limited the ability of public health practitioners to seriously discuss the trade-offs involved in Covid-related decisions.

As the pandemic evolves, we believe it’s time to shift away from this dynamic and to recognize that pandemic-era decision making requires the transparent balancing of multiple rights. Complex decisions should be widely and publicly debated by public health institutions. Similarly, it would behoove public health practitioners to stop suggesting in social media posts that nuanced questions have universally correct answers. We believe the primary objective of public health institutions during a pandemic — after the early crisis stage has passed — should be to provide data and decision-making frameworks that local partners can use in diverse contexts to weigh various trade-offs. These local partners may include community government leaders, private-sector executives, and stakeholders from civic organizations, school boards, and health care facilities. Public health practitioners can look to previous approaches to pandemic preparedness for rich examples of deliberate public engagement to inform decision making.5 Consideration of multiple perspectives, especially those of the groups most affected by public health policies, will permit more robust decision making and foster increased public trust when decisions that restrict freedoms must be made.

Source: NEJM

CDC Researchers Blame JUUL for Rise in Teen Vaping

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“JUUL’s high nicotine concentration, discreet shape, and flavors could be particularly appealing to, and problematic for, youths.”

Science says vaping is cool. Okay, maybe science doesn’t directly say that, but evidence shows that more and more teens are using e-cigarettes, and teens are cool, so vaping must be cool, right? Unfortunately, public health officials at the US Centers for Disease Control and Prevention disagree. And they’re placing much of the blame for the rise in teen vaping on one company: the Silicon Valley e-cigarette startup JUUL Laboratories.

In a research letter published Tuesday in the Journal of the American Medical Association, researchers at the CDC and nonprofit RTI International’s Centers for Health Policy Science and Tobacco Research analyzed data from retailers across the country and outlined how JUUL’s meteoric rise in popularity may be accredited — at least in part — to its appeal among teenagers. While all e-cigarette brands increased in popularity between 2013 and 2017 because of marketing suggesting that they help people quit smoking, JUUL has become the most in-demand manufacturer of all.

“JUUL’s high nicotine concentration, discreet shape, and flavors could be particularly appealing to, and problematic for, youths,” wrote the study’s authors, led by Brian King, Ph.D., M.P.H., deputy director for research translation in the CDC’s Office on Smoking and Health.

Many teens may initially try e-cigarettes, like those manufactured by JUUL, because they’re seen as safer alternatives to traditional tobacco cigarettes. And JUUL’s sleek, compact design makes the device look like a USB drive, meaning it can easily be slipped into a pocket or concealed in the palm of the hand. Several reports suggest teens easily sneak it into classrooms. Its modular “pod” design also makes it easy for users to refill the nicotine-containing liquid by simply switching out a coin-sized cartridge. Compared to disposable devices with integrated batteries, JUUL’s rechargeable device offers several attractive qualities to many consumers, and the numbers bear this out.

According to the study’s authors, JUUL Laboratories sales increased by a whopping 641 percent from 2016 to 2017. This growth translated to a 515 percent increase in JUUL Laboratories’ share of the e-cigarette market, jumping from just 2 percent of the vape market when the company started to 13 percent in early 2017. The company’s hold on the vape market exploded after that, and as of December 2017, the company controlled 29 percent of e-cigarette sales. This means that almost one out of every three e-cigarettes purchased in the US is a JUUL.

Notably, the study only used purchasing data from retailers, so it was not possible for researchers to determine how old buyers were. The study’s authors did note, though, that previous research has suggested many of these purchases may have been made by consumers under the legal smoking age.

“These sales could reflect products purchased by adults to attempt smoking cessation or products obtained directly or indirectly by youths; a recent analysis found retail stores were the primary location where youths reported obtaining the JUUL device and refill pods,” they wrote.

JUUL podmod starter kit
A JUUL starter pack includes the device, a USB charger, and four pods of different flavored nicotine-containing e-liquid, all for less than $50.

In response to Inverse’s request for comment on the new paper, JUUL spokesperson Victoria Davis did not address the assertion that JUUL products are popular among young people. Davis did emphasize targeting “adult smokers” three times, though:

JUUL Labs is focused on its mission to improve the lives of the world’s one billion adult smokers. Like many Silicon Valley technology startups, our growth is the result of a superior product disrupting an archaic industry — in this case, one whose products are the number one cause of preventable death. When adult smokers find a satisfying alternative to cigarettes, they tell other adult smokers. JUUL Labs has helped more than 1 million Americans switch from cigarettes, and we’re excited about our continued expansion into markets outside of the United States such as the United Kingdom, Canada, and Israel.

This public relations tactic is becoming familiar territory for JUUL, whose official Instagram page is dominated by images of full-on adult adults, including testimonials from people like 68-year-old Kathy, a gray-haired woman named Barbara, and the rapper/actress Awkwafina, who, at 29 years old is young but no teen. The explicit focus on adults may be coming a little too late for the company, though, as it’s already in federal regulators’ crosshairs.

On September 13, Inverse reported that US Food and Drug Administration Commissioner Scott Gottlieb, M.D., announced that vaping had become an “epidemic.” Gottlieb noted that the FDA had issued 56 warning letters to retailers who illegally sold the devices to kids under 18 years old, and JUUL was specifically mentioned in his announcement. This week, the FDA also announced it had raided JUUL’s headquarters on Friday, seizing thousands of pages of documents. The operation was part of an investigation into whether JUUL has been marketing its products to children.

Brain Scans Reveal How Drinking Turns People Into Raging Assholes

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We all have that friend who gets a little out of hand when they start drinking alcohol. Maybe he gets loud, or maybe she starts fights with strangers for looking at her funny. Alcohol seems to induce aggression, changing the brain in a way that makes a drunk person more likely to see minor social cues as threats, but how it does so has always been a bit of biological mystery.

Scientists found that alcohol-induced aggression was correlated to decreased activity in the prefrontal cortex.

But in a paper published in the journal Cognitive, Affective, & Behavioral Neuroscience, a team of researchers led by Thomas Denson, Ph.D., of the University of New South Wales School of Psychology use brain scans to show that alcohol changes activity in certain key parts of the brain related to aggression and emotion.

Using functional magnetic resonance imaging (fMRI), a technique that tracks changes in blood flow in the brain, the team looked at the brains of 50 young men after they consumed either two alcoholic drinks or two non-alcoholic placebo drinks. These volunteers engaged in a task that gauged their level of aggression in the face of provocation, which revealed the parts of the brain that become more active in such situations.

These scans show how alcohol-induced aggression was related to decreased activity in the prefrontal cortex, caudate, and ventral striatum, but increased activity in the hippocampus.
These scans show how alcohol-induced aggression was related to decreased activity in the prefrontal cortex, caudate, and ventral striatum, but increased activity in the hippocampus.

The researchers found that alcohol-induced aggression was correlated with decreased activity in prefrontal cortex, caudate, and ventral striatum, but increased activity in the hippocampus. These parts of the brain all control key factors in aggression: The prefrontal cortex is associated with thoughtful action and social behavior, the caudate is linked to the brain’s reward system and inhibitory control, and the ventral striatum is a part of the reward system that makes you feel good when you do something good. The hippocampus, meanwhile, is associated with emotion and memory.

These results support previous hypotheses that prefrontal cortex dysfunction is associated with alcohol-induced aggression. Taking all these brain areas together, the researchers say their findings suggest that intoxicated people have trouble processing information through their working memory. In short, they suspect that alcohol focuses a person’s attention on the cues that could instigate aggression while taking attention away from their knowledge of social norms that say violence is not acceptable.

Along similar lines, they also suspect that alcohol could make relatively minor cues seem aggressive or violent, which can cause a drunk person to overreact to a minor incident, like someone looking at them funny or accidentally bumping into them at the bar. Denson’s previous research on the angry brain found a lot of overlap in the way the prefrontal cortex behaves when someone is drunk and angry versus when they’re simply ruminating on their anger while sober.

This research proposes some possible brain biomarkers for alcohol-induced aggression, which is a significant public health issue. According to the Centers for Disease Control and Prevention, in the United States, alcohol-related violence — including homicide, child abuse, suicide, and firearm injuries — was responsible for more than 16,000 deaths between 2006 and 2010, the most recent years the agency reported figures.

While the new study doesn’t propose a solution per se, it does build on our body of knowledge around an age-old question: Why do some people become assholes when they get drunk?

Abstract: Alcohol intoxication is implicated in approximately half of all violent crimes. Over the past several decades, numerous theories have been proposed to account for the influence of alcohol on aggression. Nearly all of these theories imply that altered functioning in the prefrontal cortex is a proximal cause. In the present functional magnetic resonance imaging (fMRI) experiment, 50 healthy young men consumed either a low dose of alcohol or a placebo and completed an aggression paradigm against provocative and nonprovocative opponents. Provocation did not affect neural responses. However, relative to sober participants, during acts of aggression, intoxicated participants showed decreased activity in the prefrontal cortex, caudate, and ventral striatum, but heightened activation in the hippocampus. Among intoxicated participants, but not among sober participants, aggressive behavior was positively correlated with activation in the medial and dorsolateral prefrontal cortex. These results support theories that posit a role for prefrontal cortical dysfunction as an important factor in intoxicated aggression.

Latent HIV Reservoir May Be Larger Than Previous Estimates

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The sleeping giant of HIV infection—a reservoir of viral DNA that lies dormant in human immune cells—could be far larger than previously believed.

A study published today in the journal Cell shows that the reservoir, consisting of proviruses integrated into resting CD4 immune cells, may be 60 times larger than scientists had estimated. Antiretroviral therapy (ART) kills replicating HIV but not the latent proviruses, which pose a major barrier to eradicating the virus from the body and curing infection.

The latent HIV reservoir in people who are infected could be 60 times larger than previously estimated, according to a new study. Image: JAMA, ©AMA

Recent research had indicated that fewer than 1% of proviruses become infectious when resting CD4 cells are activated in a test tube. Without activation, proviruses can’t replicate. The proviruses that don’t cause infection have been considered defective, but investigators hadn’t described specifics about the deficiencies.

In the new study, a team of investigators used a more detailed method to study proviruses that didn’t switch on and become infectious when the resting CD4 cells they inhabited were activated in the laboratory. They cloned the genomes of 213 inactive proviruses from 8 HIV-infected patients treated with ART for more than 6 months. Their genetic analyses showed that about 88% of proviruses that didn’t turn on had obvious defects that prevented them from replicating. But nearly 12%—a far greater percentage than previously estimated—were capable of replicating and causing infection.

The investigators said their study suggests that there are enough proviruses that don’t turn on but are capable of replicating to boost the size of the latent reservoir by 60-fold. “These results indicate an increased barrier to cure, as all intact noninduced proviruses need to be eradicated,” senior author Robert Siliciano, MD, PhD, of Johns Hopkins University School of Medicine in Baltimore, said in a statement.

“We would like to use these findings by developing better ways to measure the size of the latent reservoir in patients who are participating in future trials of potentially curative strategies,” Siliciano added. “In this way, we think our analysis will contribute to HIV eradication efforts.”

Rare Q fever outbreak reported in American medical tourists

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Five Americans came down with an unusual illness after traveling to Germany for a controversial treatment involving injections with sheep cells, health officials reported Wednesday.

The treatment is not permitted in the U.S. The New York residents received the “live cell therapy” in May last year. About a week later, they developed fever, fatigue and other symptoms of a dangerous bacterial illness called Q fever.

Two told investigators that they were part of a group that, for the last five years, had traveled to Germany twice a year for the injections. They said they get them to improve their health and vitality. There is no published clinical proof the treatments work, health officials say.

The Centers for Disease Control and Prevention on Wednesday released a report on the outbreak, which included a Canadian case — another medical tourist who got the treatment in Germany at about the same time. The four women and two men ranged in age from 59 to 83.

Live or fresh cell therapy involves injecting people with fetal cells from sheep. It’s sometimes offered as an anti-aging therapy, but also has been touted as a treatment for conditions ranging from impotence to migraines to liver disease.

Q fever is caused by a hardy germ found in cattle, sheep and goats. People usually get it from inhaling barnyard dust — it’s an occupational hazard for farmers.

But cases in the U.S. are unusual — each year fewer than 200 are reported. It is treated with antibiotics and U.S. residents rarely die from Q fever; three or four deaths are reported in the worst years.

Wayne C. Koff describes a scientific project that promises to accelerate the development of next-generation weapons in the fight against deadly infectious diseases.

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Vaccines are one of the great success stories in the history of individual and public health. They have helped rid the planet of the scourge of smallpox, are poised to eliminate polio, and each year prevent millions of deaths, reducing the suffering and costs caused by infectious diseases.

But there are still many diseases for which vaccines do not yet exist. Moreover, strategies that have previously led to the successful development of vaccines are unlikely to work against more complex bacteria or viruses, such as HIV, which have evolved multiple mechanisms to evade the immune system.

The history of vaccinology is one in which biomedical and technological advances usher in the “next generation” of vaccines. In the 1950’s, a breakthrough that enabled viruses to grow in tissue cultures led to the development of both live attenuated vaccines and inactivated vaccines for measles, polio, and other diseases. In the 1980’s, recombinant DNA technology led to the development of vaccines against hepatitis B and human papillomavirus.

Around the turn of the century, the first sequencing of the human genome led to “reverse vaccinology.” This approach, whereby computational analysis of a pathogen’s genome enables identification and screening of a great many more potential vaccine targets than was previously possible, was used in the successful development of a vaccine against meningitis B.

The past decade has already yielded major advances in structure-assisted vaccine discovery, synthetic biology, systems biology, and immune monitoring. However, successfully translating these advances into the development of next-generation vaccines continues to be impeded by gaps in our understanding of the human immune response that protects against specific bacteria, viruses, or parasites.

That is why I, along with eight fellow scientists, have proposed the establishment of a new human-immunology-based clinical-research initiative, the Human Vaccines Project. In February 2014, leading scientists and public-health specialists will gather in La Jolla, California, to craft a scientific plan to identify, prioritize, and, most important, solve the major problems currently hindering development of vaccines against diseases such as AIDS, tuberculosis, and malaria.

Such a project would represent a paradigm shift in vaccine development. The current process is long (often spanning decades from concept to licensure), has a low probability of success (because of the limitations of animal models in predicting immune response and efficacy in humans), and is costly (often requiring hundreds of millions of dollars to develop a single vaccine).

Consider this: In just the past few years, many candidate vaccines against HIV, dengue, herpes, tuberculosis, and staphylococcus aureus have failed, at a cost of more than $1 billion. Investing that amount over the next decade in a coordinated effort to address the major questions facing vaccine development would rapidly accelerate our search for effective solutions, implying a transformative impact on individual and public health.

HIV presents perhaps the greatest challenge, because the virus leverages its extensive genetic variability to hide from the immune system. Using recent advances, however, scientists have now identified highly conserved regions of this variable virus, determined their molecular structure, and begun designing next-generation vaccine candidates to elicit antibodies that target these regions to prevent HIV infection. But HIV vaccine development, like that for several other diseases, is still impeded by the limitations of what animal models can tell us about how to elicit the necessary immune responses in humans.

Two recent advances could accelerate vaccine development and reduce its costs dramatically. In synthetic biology, the rapid engineering of nucleic acid-based vaccines means more candidates move more quickly from concept to trial. In systems biology, high-throughput technologies have increased the number of genetic and immunologic parameters assessed in trials. This approach has helped predict the efficacy of potential new-generation vaccines against yellow fever and influenza within days of immunization, compared with the usual timeframe of months or years.

Vaccines already prevent the deaths of 2-3 million people every year, preempt human suffering, lighten the burden placed on health-care systems, and enable more rapid economic and social development. Models show that adding even a partly effective AIDS vaccine to the current range of prevention and treatment procedures could dramatically lower the rate of HIV infection.

As the Nobel Peace Prize laureate Desmond Tutu, one of the world’s great campaigners against HIV/AIDS, wrote recently: “We must make the most of scientific advances over the last half-century, which have made vaccines for other preventable diseases the most powerful and cost-effective health-care investment that currently exists.”

That is the idea behind the Human Vaccines Project – a concept that would have been unimaginable even a decade ago. Today, technological advances in vaccine discovery and immune monitoring allow us realistically to explore this potentially game-changing approach to disease prevention. February’s gathering in California may take us a giant step closer to a world without deadly and debilitating infectious diseases.

Antibiotics are ‘not for snot’

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Running noses and green phlegm do not mean patients need antibiotics, say doctors and public health experts.

It was described as a “prevailing myth” that the drugs were needed to treat such infections.

Snotty child

Public Health England and the Royal College of General Practitioners said the symptoms were often caused by viruses.

And the use of antibiotics was leading to resistance, they said.

Public Health England said its own research showed that 40% of people thought antibiotics would help a cough if the phlegm was green, while very few thought it would make a difference to clear-coloured phlegm.

Dr Cliodna McNulty, from the organisation, said: “It’s a prevailing myth that anyone with green phlegm or snot needs a course of antibiotics to get better.

“Most of the infections that generate lots of phlegm and snot are viral illnesses and will get better on their own although you can expect to feel pretty poorly for a few weeks.

“The problems of antibiotic resistance are growing. Everyone can help by not using antibiotics for the treatment of uncomplicated infections.”

Taking antibiotics affects the trillions of bacteria that naturally live in the human body and can lead to resistance.

Dr Maureen Baker, chairwoman of the Royal College of GPs, said: “Overuse of antibiotics is a serious public health concern.

“Infections adapt to antibiotics used to kill them and can ultimately make treatment ineffective so it’s crucial that antibiotics are used appropriately.”

The green colour in phlegm and snot is the result of a protein made by the immune system to fight infection.

The latest advice comes on European Antibiotics Awareness Day.

Tylenol Just Once A Month Raises A Child’s Asthma Risk 540%.

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The vast majority of babies are given Tylenol (acetaminophen) within the first six months of life. It is the go to medicine for modern parents whenever discomfort or fever strikes even very young children and its use is frequently encouraged by many pediatricians.

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Now, a major study of over 20,000 children suggests that giving this popular medicine even as infrequently as once per year could have a permanent, life-threatening health effect.

Researchers at the University of A Coruna in Spain asked the parents of 10,371 children ages 6-7 and 10,372 adolescents aged 13-14 whether their children had asthma and how often they had been given acetaminophen within the previous year and when they were babies.
The children in the younger age group who had received the medicine only once per year were at 70% greater risk for asthma while those receiving Tylenol once a month or more were shockingly 540% more likely to have asthma.

The study, published in the European Journal of Public Health, also found that children who had even a single dose of Tylenol before their first birthday had a 60% risk of developing asthma.

In the older age group of 13 and 14 year-olds, asthma was 40 percent more likely if they had taken acetaminophen within the previous 12 months. The young teenagers were 250% more at risk if they took it once a month.

The researchers speculated that Tylenol, called paracetamol in the UK, may reduce a potent antioxidant called glutathione in the lungs and blood, which results in damage to the lung tissue. Glutathione is produced by the body (it is a combination of three amino acids:  cysteine, glycine and glutamine) and is referred to as the “mother” of all antioxidants by Dr. Mark Hyman MD.
While Tylenol use is strongly associated with a significant increase in asthma and the effect is greater the more often the drug is taken, no causal link is yet established via randomized-controlled trials. Does this mean the results of this large study should be dismissed and parents should continue favoring use of the popular over the counter medication for fever and pain?
Not so fast.

It would certainly be the wise and cautious approach for parents to investigate alternatives to Tylenol while additional follow-up research is performed.

Asthma rates have been on the increase for decades at the same time Tylenol use became more widespread. The potential link cannot and should not be ignored.

Examination of 20,000 children establishing such a strong associative risk must be taken seriously and the dismissal of the research by some doctors is irresponsible given the seriousness and life altering outcome of an asthma diagnosis.