Underdetected dispersal and extensive local transmission drove the 2022 mpox epidemic.

The World Health Organization declared mpox a public health emergency of international concern in July 2022. To investigate global mpox transmission and population-level changes associated with controlling spread, we built phylogeographic and phylodynamic models to analyze MPXV genomes from five global regions together with air traffic and epidemiological data. Our models reveal community transmission prior to detection, changes in case reporting throughout the epidemic, and a large degree of transmission heterogeneity. We find that viral introductions played a limited role in prolonging spread after initial dissemination, suggesting that travel bans would have had only a minor impact. We find that mpox transmission in North America began declining before more than 10% of high-risk individuals in the USA had vaccine-induced immunity. Our findings highlight the importance of broader routine specimen screening surveillance for emerging infectious diseases and of joint integration of genomic and epidemiological information for early outbreak control.

Health Digital Twins in Life Science and Health Care Innovation.

Health digital twins (HDTs) are virtual representations of real individuals that can be used to simulate human physiology, disease, and drug effects. HDTs can be used to improve drug discovery and development by providing a data-driven approach to inform target selection, drug delivery, and design of clinical trials. HDTs also offer new applications into precision therapies and clinical decision making. The deployment of HDTs at scale could bring a precision approach to public health monitoring and intervention. Next steps include challenges such as addressing socioeconomic barriers and ensuring the representativeness of the technology based on the training and validation data sets. Governance and regulation of HDT technology are still in the early stages.

Development of prediction models to identify hotspots of schistosomiasis in endemic regions to guide mass drug administration.

Schistosomiasis is a neglected tropical disease affecting over 150 million people. Hotspots of Schistosoma transmission-communities where infection prevalence does not decline adequately with mass drug administration-present a key challenge in eliminating schistosomiasis. Current approaches to identify hotspots require evaluation 2-5 y after a baseline survey and subsequent mass drug administration. Here, we develop statistical models to predict hotspots at baseline prior to treatment comparing three common hotspot definitions, using epidemiologic, survey-based, and remote sensing data. In a reanalysis of randomized trials in 589 communities in five endemic countries, a regression model predicts whether Schistosoma mansoni infection prevalence will exceed the WHO threshold of 10% in year 5 ("prevalence hotspot") with 86% sensitivity, 74% specificity, and 93% negative predictive value (NPV; assuming 30% hotspot prevalence), and a regression model for Schistosoma haematobium achieves 90% sensitivity, 90% specificity, and 96% NPV. A random forest model predicts whether S. mansoni moderate and heavy infection prevalence will exceed a public health goal of 1% in year 5 ("intensity hotspot") with 92% sensitivity, 79% specificity, and 96% NPV, and a boosted trees model for S. haematobium achieves 77% sensitivity, 95% specificity, and 91% NPV. Baseline prevalence is a top predictor in all models. Prediction is less accurate in countries not represented in training data and for a third hotspot definition based on relative prevalence reduction over time ("persistent hotspot"). These models may be a tool to prioritize high-risk communities for more frequent surveillance or intervention against schistosomiasis, but prediction of hotspots remains a challenge.

Reassessing the role of urban green space in air pollution control.

The assumption that vegetation improves air quality is prevalent in scientific, popular, and political discourse. However, experimental and modeling studies show the effect of green space on air pollutant concentrations in urban settings is highly variable and context specific. We revisited the link between vegetation and air quality using satellite-derived changes of urban green space and air pollutant concentrations from 2,615 established monitoring stations over Europe and the United States. Between 2010 and 2019, stations recorded declines in ambient NO2, (particulate matter) PM10, and PM2.5 (average of -3.14% y-1), but not O3 (+0.5% y-1), pointing to the general success of recent policy interventions to restrict anthropogenic emissions. The effect size of total green space on air pollution was weak and highly variable, particularly at the street scale (15 to 60 m radius) where vegetation can restrict ventilation. However, when isolating changes in tree cover, we found a negative association with air pollution at borough to city scales (120 to 16,000 m) particularly for O3 and PM. The effect of green space was smaller than the pollutant deposition and dispersion effects of meteorological drivers including precipitation, humidity, and wind speed. When averaged across spatial scales, a one SD increase in green space resulted in a 0.8% (95% CI: -3.5 to 2%) decline in air pollution. Our findings suggest that while urban greening may improve air quality at the borough-to-city scale, the impact is moderate and may have detrimental street-level effects depending on aerodynamic factors like vegetation type and urban form.

The role of positive emotion in harmful health behavior: Implications for theory and public health campaigns.

Meta-analyses have concluded that positive emotions do not reduce appetitive risk behaviors (risky behaviors that fulfill appetitive or craving states, such as smoking and excessive alcohol use). We propose that this conclusion is premature. Drawing on the Appraisal Tendency Framework and related theories of emotion and decision-making, we hypothesized that gratitude (a positive emotion) can decrease cigarette smoking, a leading cause of premature death globally. A series of multimethod studies provided evidence supporting our hypothesis (collective N = 34,222). Using nationally representative US samples and an international sample drawn from 87 countries, Studies 1 and 2 revealed that gratitude was inversely associated with likelihood of smoking, even after accounting for numerous covariates. Other positive emotions (e.g., compassion) lacked such consistent associations, as expected. Study 3, and its replication, provided further support for emotion specificity: Experimental induction of gratitude, unlike compassion or sadness, reduced cigarette craving compared to a neutral state. Study 4, and its replication, showed that inducing gratitude causally increased smoking cessation behavior, as evidenced by enrollment in a web-based cessation intervention. Self-reported gratitude mediated the effects in both experimental studies. Finally, Study 5 found that current antismoking messaging campaigns by the US Centers for Disease Control and Prevention primarily evoked sadness and compassion, but seldom gratitude. Together, our studies advance understanding of positive emotion effects on appetitive risk behaviors; they also offer practical implications for the design of public health campaigns.

Identifying outbreaks in sewer networks: An adaptive sampling scheme under network's uncertainty.

Motivated by the implementation of a SARS-Cov-2 sewer surveillance system in Chile during the COVID-19 pandemic, we propose a set of mathematical and algorithmic tools that aim to identify the location of an outbreak under uncertainty in the network structure. Given an upper bound on the number of samples we can take on any given day, our framework allows us to detect an unknown infected node by adaptively sampling different network nodes on different days. Crucially, despite the uncertainty of the network, the method allows univocal detection of the infected node, albeit at an extra cost in time. This framework relies on a specific and well-chosen strategy that defines new nodes to test sequentially, with a heuristic that balances the granularity of the information obtained from the samples. We extensively tested our model in real and synthetic networks, showing that the uncertainty of the underlying graph only incurs a limited increase in the number of iterations, indicating that the methodology is applicable in practice.

Social competition drives collective action to reduce informal waste burning in Uganda.

Improving urban air quality is a pressing challenge in the Global South. A key source of air pollution is the informal burning of household waste. Reducing informal burning requires governments to develop formal systems for waste disposal and for residents to adopt new disposal behaviors. Using a randomized experiment, we show that social competitions between pairs of neighborhoods in Nansana municipality, Uganda, galvanized leadership and inspired collective action to reduce informal burning. All 44 neighborhoods in the study received a public health campaign, while 22 treated neighborhoods were paired and competed to reduce waste burning over an 8-mo period. Treated neighborhoods showed a 24 percent reduction (95% CI: 11 to 35 percent) in waste burning relative to control neighborhoods at the end of the competition period. There is no evidence that treated neighborhoods experienced a rebound in waste burning several months after the competitions. Community leaders reported greater effort in coordinating residents and more pride in their neighborhood when assigned to the competition treatment. These results suggest that creating focal points for leadership and collective action can be an effective and low-cost strategy to address policy problems that require broad participation and costly behavior change.

The European Union Emissions Trading System might yield large co-benefits from pollution reduction.

Mitigating greenhouse gas emissions and reducing air pollution represent two pressing and interwoven environmental challenges. While international carbon markets, such as the European Union emissions trading system (EU ETS), have demonstrated their effectiveness in curbing carbon emissions (CO[Formula: see text]), their indirect impact on hazardous co-pollutants remains understudied. This study investigates how key toxic air pollutants-sulfur dioxide (SO[Formula: see text]), fine particulate matter (PM[Formula: see text]), and nitrogen oxides (NO[Formula: see text])-evolved after the introduction of the EU ETS with a comparative analysis of regulated and unregulated sectors. Leveraging the generalized synthetic control method, we offer an ex post analysis of how the EU ETS and concurrent emission standards may have jointly generated sizable pollution reductions in regulated sectors between 2005 and 2021. We provide an aggregate assessment that these pollution reductions could translate into large health co-benefits, potentially in the hundreds of billions of Euros, even when bounding the effect of emission standards. These order-of-magnitude estimates underscore key implications for policy appraisal and motivate further microlevel research around the health co-benefits of carbon abatement.

Health Effects of Wildfire Smoke Exposure.

We review current knowledge on the trends and drivers of global wildfire activity, advances in the measurement of wildfire smoke exposure, and evidence on the health effects of this exposure. We describe methodological issues in estimating the causal effects of wildfire smoke exposures on health and quantify their importance, emphasizing the role of nonlinear and lagged effects. We conduct a systematic review and meta-analysis of the health effects of wildfire smoke exposure, finding positive impacts on all-cause mortality and respiratory hospitalizations but less consistent evidence on cardiovascular morbidity. We conclude by highlighting priority areas for future research, including leveraging recently developed spatially and temporally resolved wildfire-specific ambient air pollution data to improve estimates of the health effects of wildfire smoke exposure.

Impact of Wildfires on Cardiovascular Health.

Wildfire smoke (WFS) is a mixture of respirable particulate matter, environmental gases, and other hazardous pollutants that originate from the unplanned burning of arid vegetation during wildfires. The increasing size and frequency of recent wildfires has escalated public and occupational health concerns regarding WFS inhalation, by either individuals living nearby and downstream an active fire or wildland firefighters and other workers that face unavoidable exposure because of their profession. In this review, we first synthesize current evidence from environmental, controlled, and interventional human exposure studies, to highlight positive associations between WFS inhalation and cardiovascular morbidity and mortality. Motivated by these findings, we discuss preventative measures and suggest interventions to mitigate the cardiovascular impact of wildfires. We then review animal and cell exposure studies to call attention on the pathophysiological processes that support the deterioration of cardiovascular tissues and organs in response to WFS inhalation. Acknowledging the challenges of integrating evidence across independent sources, we contextualize laboratory-scale exposure approaches according to the biological processes that they model and offer suggestions for ensuring relevance to the human condition. Noting that wildfires are significant contributors to ambient air pollution, we compare the biological responses triggered by WFS to those of other harmful pollutants. We also review evidence for how WFS inhalation may trigger mechanisms that have been proposed as mediators of adverse cardiovascular effects upon exposure to air pollution. We finally conclude by highlighting research areas that demand further consideration. Overall, we aspire for this work to serve as a catalyst for regulatory initiatives to mitigate the adverse cardiovascular effects of WFS inhalation in the community and alleviate the occupational risk in wildland firefighters.

Agricultural intensification and childhood cancer in Brazil.

Over the last several decades, Brazil has become both the world's leading soy producer and the world's leading consumer of hazardous pesticides. Despite identified links between pesticide exposure and carcinogenesis, there has been little population-level research on the effects of pesticide intensification on broader human health in Brazil. We estimate the relationship between expanded soy production-and related community exposure to pesticides-on childhood cancer incidence using 15 y of data on disease mortality. We find a statistically significant increase in pediatric leukemia following expanded local soy production, but timely access to treatment mitigates this relationship. We show that pesticide exposure likely occurs via water supply penetration. Our findings represent only the tip of the iceberg for substantial health externalities of high-input crop production and land use change. Our results are of particular interest in developing contexts with demand for intensified food production systems and underscore the need for stronger regulation of pesticides and increased public health attention to exposure in the broader community.

The impact of threshold decision mechanisms of collective behavior on disease spread.

Humans are a hyper-social species, which greatly impacts the spread of infectious diseases. How do social dynamics impact epidemiology and what are the implications for public health policy? Here, we develop a model of disease transmission that incorporates social dynamics and a behavior that reduces the spread of disease, a voluntary nonpharmaceutical intervention (NPI). We use a "tipping-point" dynamic, previously used in the sociological literature, where individuals adopt a behavior given a sufficient prevalence of the behavior in the population. The thresholds at which individuals adopt the NPI behavior are modulated by the perceived risk of infection, i.e., the disease prevalence and transmission rate, costs to adopt the NPI behavior, and the behavior of others. Social conformity creates a type of "stickiness" whereby individuals are resistant to changing their behavior due to the population's inertia. In this model, we observe a nonmonotonicity in the attack rate as a function of various biological and social parameters such as the transmission rate, efficacy of the NPI, costs of the NPI, weight of social consequences of shirking the social norm, and the degree of heterogeneity in the population. We also observe that the attack rate can be highly sensitive to these parameters due to abrupt shifts in the collective behavior of the population. These results highlight the complex interplay between the dynamics of epidemics and norm-driven collective behaviors.

Association of vaccination, international travel, public health and social measures with lineage dynamics of SARS-CoV-2.

Continually emerging SARS-CoV-2 variants of concern that can evade immune defenses are driving recurrent epidemic waves of COVID-19 globally. However, the impact of measures to contain the virus and their effect on lineage diversity dynamics are poorly understood. Here, we jointly analyzed international travel, public health and social measures (PHSM), COVID-19 vaccine rollout, SARS-CoV-2 lineage diversity, and the case growth rate (GR) from March 2020 to September 2022 across 63 countries. We showed that despite worldwide vaccine rollout, PHSM are effective in mitigating epidemic waves and lineage diversity. An increase of 10,000 monthly travelers in a single country-to-country route between endemic countries corresponds to a 5.5% (95% CI: 2.9 to 8.2%) rise in local lineage diversity. After accounting for PHSM, natural immunity from previous infections, and waning immunity, we discovered a negative association between the GR of cases and adjusted vaccine coverage (AVC). We also observed a complex relationship between lineage diversity and vaccine rollout. Specifically, we found a significant negative association between lineage diversity and AVC at both low and high levels but not significant at the medium level. Our study deepens the understanding of population immunity and lineage dynamics for future pandemic preparedness and responsiveness.

Digital public health interventions at scale: The impact of social media advertising on beliefs and outcomes related to COVID vaccines.

Public health organizations increasingly use social media advertising campaigns in pursuit of public health goals. In this paper, we evaluate the impact of about $40 million of social media advertisements that were run and experimentally tested on Facebook and Instagram, aimed at increasing COVID-19 vaccination rates in the first year of the vaccine roll-out. The 819 randomized experiments in our sample were run by 174 different public health organizations and collectively reached 2.1 billion individuals in 15 languages. We find that these campaigns are, on average, effective at influencing self-reported beliefs-shifting opinions close to 1% at baseline with a cost per influenced person of about $3.41. Combining this result with an estimate of the relationship between survey outcomes and vaccination rates derived from observational data yields an estimated cost per additional vaccination of about $5.68. There is further evidence that campaigns are especially effective at influencing users' knowledge of how to get vaccines. Our results represent, to the best of our knowledge, the largest set of online public health interventions analyzed to date.

Neisseria gonorrhoeae vaccines: a contemporary overview.

Neisseria gonorrhoeae infection is an important public health issue, with an annual global incidence of 87 million. N. gonorrhoeae infection causes significant morbidity and can have serious long-term impacts on reproductive and neonatal health and may rarely cause life-threatening disease. Global rates of N. gonorrhoeae infection have increased over the past 20 years. Importantly, rates of antimicrobial resistance to key antimicrobials also continue to increase, with the United States Centers for Disease Control and Prevention identifying drug-resistant N. gonorrhoeae as an urgent threat to public health. This review summarizes the current evidence for N. gonorrhoeae vaccines, including historical clinical trials, key N. gonorrhoeae vaccine preclinical studies, and studies of the impact of Neisseria meningitidis vaccines on N. gonorrhoeae infection. A comprehensive survey of potential vaccine antigens, including those identified through traditional vaccine immunogenicity approaches, as well as those identified using more contemporary reverse vaccinology approaches, are also described. Finally, the potential epidemiological impacts of a N. gonorrhoeae vaccine and research priorities for further vaccine development are described.

Digital Footprints of Obesity Treatment: GLP-1 Receptor Agonists and the Health Equity Divide.

Our research investigates the societal implications of access to glucagon-like peptide-1 (GLP-1) agonists, particularly in light of recent clinical trials demonstrating the efficacy of semaglutide in reducing cardiovascular mortality. A decade-long analysis of Google Trends indicates a significant increase in searches for GLP-1 agonists, primarily in North America. This trend contrasts with the global prevalence of obesity. Given the high cost of GLP-1 agonists, a critical question arises: Will this disparity in medication accessibility exacerbate the global health equity gap in obesity treatment? This viewpoint explores strategies to address the health equity gap exacerbated by this emerging medication. Because GLP-1 agonists hold the potential to become a cornerstone in obesity treatment, ensuring equitable access is a pressing public health concern.

The American Heart Association at 100: A Century of Scientific Progress and the Future of Cardiovascular Science: A Presidential Advisory From the American Heart Association.

In 1924, the founders of the American Heart Association (AHA) envisioned an international society focused on the heart and aimed at facilitating research, disseminating information, increasing public awareness, and developing public health policy related to heart disease. This presidential advisory provides a comprehensive review of the past century of cardiovascular and stroke science, with a focus on the AHA's contributions, as well as informed speculation about the future of cardiovascular science into the next century of the organization's history. The AHA is a leader in fundamental, translational, clinical, and population science, and it promotes the concept of the "learning health system," in which a continuous cycle of evidence-based practice leads to practice-based evidence, permitting an iterative refinement in clinical evidence and care. This advisory presents the AHA's journey over the past century from instituting professional membership to establishing extraordinary research funding programs; translating evidence to practice through clinical practice guidelines; affecting systems of care through quality programs, certification, and implementation; leading important advocacy efforts at the federal, state and local levels; and building global coalitions around cardiovascular and stroke science and public health. Recognizing an exciting potential future for science and medicine, the advisory offers a vision for even greater impact for the AHA's second century in its continued mission to be a relentless force for longer, healthier lives.

Bloodmeals fuel dengue virus replication in the female mosquito Aedes aegypti.

Vector competence defines the ability of a vector to acquire, host, and transmit a pathogen. Understanding the molecular determinants of the mosquitos' competence to host dengue virus (DENV) holds promise to prevent its transmission. To this end, we employed RNA-seq to profile mRNA transcripts of the female Aedes aegypti mosquitos feeding on naïve vs viremic mouse. While most transcripts (12,634) did not change their abundances, 360 transcripts showed decreases. Biological pathway analysis revealed representatives of the decreased transcripts involved in the wnt signaling pathway and hippo signaling pathway. One thousand three hundred fourteen transcripts showed increases in abundance and participate in 21 biological pathways including amino acid metabolism, carbon metabolism, fatty acid metabolism, and oxidative phosphorylation. Inhibition of oxidative phosphorylation with antimycin A reduced oxidative phosphorylation activity and ATP concentration associated with reduced DENV replication in the Aedes aegypti cells. Antimycin A did not affect the amounts of the non-structural proteins 3 and 5, two major components of the replication complex. Ribavirin, an agent that reduces GTP concentration, recapitulated the effects of reduced ATP concentration on DENV replication. Knocking down one of the oxidative phosphorylation components, ATP synthase subunit ß, reduced DENV replication in the mosquitos. In summary, our results suggest that DENV enhances metabolic pathways in the female Aedes aegypti mosquitos to supply nutrients and energy for virus replication. ATP synthase subunit ß knockdown might be exploited to reduce the mosquitos' competence to host and transmit DENV. IMPORTANCE: Through evolution, the mosquito-borne viruses have adapted to the blood-feeding behaviors of their opportunist hosts to fulfill a complete lifecycle in humans and mosquitos. Disruption in the mosquitos' ability to host these viruses offers strategies to prevent diseases caused by them. With the advent of genomic tools, we discovered that dengue virus (DENV) benefited from the female mosquitos' bloodmeals for metabolic and energetic supplies for replication. Chemical or genetic disruption in these supplies reduced DENV replication in the female mosquitos. Our discovery can be exploited to produce genetically modified mosquitos, in which DENV infection leads to disruption in the supplies and thereby reduces replication and transmission. Our discovery might be extrapolated to prevent mosquito-borne virus transmission and the diseases they cause.

A community science approach to public health and public trust in science.

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the importance of health literacy and trust in pandemic management. Collaborating with the community to prepare for pandemics is incredibly effective in fostering understanding and building trust in public health and scientific research.

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

BACKGROUND: Periodic bioinformatics-based screening of wastewater for assessing the diversity of potential human viral pathogens circulating in a given community may help to identify novel or potentially emerging infectious diseases. Any identified contigs related to novel or emerging viruses should be confirmed with targeted wastewater and clinical testing. RESULTS: During the COVID-19 pandemic, untreated wastewater samples were collected for a 1-year period from the Great Lakes Water Authority Wastewater Treatment Facility in Detroit, MI, USA, and viral population diversity from both centralized interceptor sites and localized neighborhood sewersheds was investigated. Clinical cases of the diseases caused by human viruses were tabulated and compared with data from viral wastewater monitoring. In addition to Betacoronavirus, comparison using assembled contigs against a custom Swiss-Prot human virus database indicated the potential prevalence of other pathogenic virus genera, including: Orthopoxvirus, Rhadinovirus, Parapoxvirus, Varicellovirus, Hepatovirus, Simplexvirus, Bocaparvovirus, Molluscipoxvirus, Parechovirus, Roseolovirus, Lymphocryptovirus, Alphavirus, Spumavirus, Lentivirus, Deltaretrovirus, Enterovirus, Kobuvirus, Gammaretrovirus, Cardiovirus, Erythroparvovirus, Salivirus, Rubivirus, Orthohepevirus, Cytomegalovirus, Norovirus, and Mamastrovirus. Four nearly complete genomes were recovered from the Astrovirus, Enterovirus, Norovirus and Betapolyomavirus genera and viral species were identified. CONCLUSIONS: The presented findings in wastewater samples are primarily at the genus level and can serve as a preliminary "screening" tool that may serve as indication to initiate further testing for the confirmation of the presence of species that may be associated with human disease. Integrating innovative environmental microbiology technologies like metagenomic sequencing with viral epidemiology offers a significant opportunity to improve the monitoring of, and predictive intelligence for, pathogenic viruses, using wastewater.