Zoonotic spillover and viral mutations from low and middle-income countries: improving prevention strategies and bridging policy gaps.

The increasing frequency of zoonotic spillover events and viral mutations in low and middle-income countries presents a critical global health challenge. Contributing factors encompass cultural practices like bushmeat consumption, wildlife trade for traditional medicine, habitat disruption, and the encroachment of impoverished settlements onto natural habitats. The existing "vaccine gap" in many developing countries exacerbates the situation by allowing unchecked viral replication and the emergence of novel mutant viruses. Despite global health policies addressing the root causes of zoonotic disease emergence, there is a significant absence of concrete prevention-oriented initiatives, posing a potential risk to vulnerable populations. This article is targeted at policymakers, public health professionals, researchers, and global health stakeholders, particularly those engaged in zoonotic disease prevention and control in low and middle-income countries. The article underscores the importance of assessing potential zoonotic diseases at the animal-human interface and comprehending historical factors contributing to spillover events. To bridge policy gaps, comprehensive strategies are proposed that include education, collaborations, specialized task forces, environmental sampling, and the establishment of integrated diagnostic laboratories. These strategies advocate simplicity and unity, breaking down barriers, and placing humanity at the forefront of addressing global health challenges. Such a strategic and mental shift is crucial for constructing a more resilient and equitable world in the face of emerging zoonotic threats.

Bayesian inference for the onset time and epidemiological characteristics of emerging infectious diseases.

Background: Emerging infectious diseases pose a significant threat to global public health. Timely detection and response are crucial in mitigating the spread of such epidemics. Inferring the onset time and epidemiological characteristics is vital for accelerating early interventions, but accurately predicting these parameters in the early stages remains challenging. Methods: We introduce a Bayesian inference method to fit epidemic models to time series data based on state-space modeling, employing a stochastic Susceptible-Exposed-Infectious-Removed (SEIR) model for transmission dynamics analysis. Our approach uses the particle Markov chain Monte Carlo (PMCMC) method to estimate key epidemiological parameters, including the onset time, the transmission rate, and the recovery rate. The PMCMC algorithm integrates the advantageous aspects of both MCMC and particle filtering methodologies to yield a computationally feasible and effective means of approximating the likelihood function, especially when it is computationally intractable. Results: To validate the proposed method, we conduct case studies on COVID-19 outbreaks in Wuhan, Shanghai and Nanjing, China, respectively. Using early-stage case reports, the PMCMC algorithm accurately predicted the onset time, key epidemiological parameters, and the basic reproduction number. These findings are consistent with empirical studies and the literature. Conclusion: This study presents a robust Bayesian inference method for the timely investigation of emerging infectious diseases. By accurately estimating the onset time and essential epidemiological parameters, our approach is versatile and efficient, extending its utility beyond COVID-19.

Early-stage loss of ecological integrity drives the risk of zoonotic disease emergence.

Anthropogenic pressures have increasingly disrupted the integrity of ecosystems worldwide, jeopardizing their capacity to provide essential contributions to human well-being. Recently, the role of natural ecosystems in reducing disease emergence risk has gained prominence in decision-making processes, as scientific evidence indicates that human-driven pressure, such as habitat destruction and deforestation, can trigger the emergence of zoonotic infectious diseases. However, the intricate relationship between biodiversity and emerging infectious diseases (EIDs) remains only partially understood. Here, we updated the most comprehensive zoonotic EID event database with the latest reported events to analyse the relationship between EIDs of wildlife origin (zoonoses) and various facets of ecological integrity. We found EID risk was strongly predicted by structural integrity metrics such as human footprint and ecoregion intactness, in addition to environmental variables such as tropical rainforest density and mammal species richness. EID events were more likely to occur in areas with intermediate levels of compositional and structural integrity, underscoring the risk posed by human encroachment into pristine, undisturbed lands. Our study highlights the need to identify novel indicators and targets that can effectively address EID risk alongside other pressing global challenges in sustainable development, ultimately informing strategies for preserving both human and environmental health.

FDA's proposed rule and its regulatory impact on emerging and reemerging neglected tropical diseases in the United States.

Diagnosing infectious diseases significantly influences patient care, aiding in outbreak identification, response, and public health monitoring. However, the range of FDA-approved molecular tests remains notably limited, especially concerning neglected tropical diseases (NTDs). Drawing upon our experience as one of the largest healthcare networks in the greater New York metropolitan area, this viewpoint manuscript aims to spotlight the existing diagnostic landscape and unmet clinical needs for 4 emerging NTDs increasingly prevalent in the United States, additionally, it delves into the possible adverse effects of the FDA's Proposed Rule on Laboratory-Developed Tests for these clinical conditions and the broader spectrum of NTDs.

Alpine salamanders at risk? The current status of an emerging fungal pathogen.

Amphibians globally suffer from emerging infectious diseases like chytridiomycosis caused by the continuously spreading chytrid fungi. One is Batrachochytrium salamandrivorans (Bsal) and its disease ‒ the 'salamander plague' ‒ which is lethal to several caudate taxa. Recently introduced into Western Europe, long distance dispersal of Bsal, likely through human mediation, has been reported. Herein we study if Alpine salamanders (Salamandra atra and S. lanzai) are yet affected by the salamander plague in the wild. Members of the genus Salamandra are highly susceptible to Bsal leading to the lethal disease. Moreover, ecological modelling has shown that the Alps and Dinarides, where Alpine salamanders occur, are generally suitable for Bsal. We analysed skin swabs of 818 individuals of Alpine salamanders and syntopic amphibians at 40 sites between 2017 to 2022. Further, we compiled those with published data from 319 individuals from 13 sites concluding that Bsal infections were not detected. Our results suggest that the salamander plague so far is absent from the geographic ranges of Alpine salamanders. That means that there is still a chance to timely implement surveillance strategies. Among others, we recommend prevention measures, citizen science approaches, and ex situ conservation breeding of endemic salamandrid lineages.

Climate change, its impact on emerging infectious diseases and new technologies to combat the challenge.

ABSTRACTImproved sanitation, increased access to health care, and advances in preventive and clinical medicine have reduced the mortality and morbidity rates of several infectious diseases. However, recent outbreaks of several emerging infectious diseases (EIDs) have caused substantial mortality and morbidity, and the frequency of these outbreaks is likely to increase due to pathogen, environmental, and population effects driven by climate change. Extreme or persistent changes in temperature, precipitation, humidity, and air pollution associated with climate change can, for example, expand the size of EID reservoirs, increase host-pathogen and cross-species host contacts to promote transmission or spillover events, and degrade the overall health of susceptible host populations leading to new EID outbreaks. It is therefore vital to establish global strategies to track and model potential responses of candidate EIDs to project their future behaviour and guide research efforts on early detection and diagnosis technologies and vaccine development efforts for these targets. Multi-disciplinary collaborations are demanding to develop effective inter-continental surveillance and modelling platforms that employ artificial intelligence to mitigate climate change effects on EID outbreaks. In this review, we discuss how climate change has increased the risk of EIDs and describe novel approaches to improve surveillance of emerging pathogens that pose the risk for EID outbreaks, new and existing measures that could be used to contain or reduce the risk of future EID outbreaks, and new methods to improve EID tracking during further outbreaks to limit disease transmission.

Monkeypox Outbreak 2022, from a Rare Disease to Global Health Emergence: Implications for Travellers.

Monkeypox (mpox), a zoonotic disease caused by the monkeypox virus (MPXV), poses a significant public health threat with the potential for global dissemination beyond its endemic regions in Central and West Africa. This study explores the multifaceted aspects of monkeypox, covering its epidemiology, genomics, travel-related spread, mass gathering implications, and economic consequences. Epidemiologically, mpox exhibits distinct patterns, with variations in age and gender susceptibility. Severe cases can arise in immunocompromised individuals, underscoring the importance of understanding the factors contributing to its transmission. Genomic analysis of MPXV highlights its evolutionary relationship with the variola virus and vaccinia virus. Different MPXV clades exhibit varying levels of virulence and transmission potential, with Clade I associated with higher mortality rates. Moreover, the role of recombination in MPXV evolution remains a subject of interest, with implications for understanding its genetic diversity. Travel and mass gatherings play a pivotal role in the spread of monkeypox. The ease of international travel and increasing globalization have led to outbreaks beyond African borders. The economic ramifications of mpox outbreaks extend beyond public health. Direct treatment costs, productivity losses, and resource-intensive control efforts can strain healthcare systems and economies. While vaccination and mitigation strategies have proven effective, the cost-effectiveness of routine vaccination in non-endemic countries remains a subject of debate. This study emphasizes the role of travel, mass gatherings, and genomics in its spread and underscores the economic impacts on affected regions. Enhancing surveillance, vaccination strategies, and public health measures are essential in controlling this emerging infectious disease.

Applying lessons of COVID-19 and other emerging infectious diseases to future outbreaks.

Infectious diseases are emerging and re-emerging far more frequently than many appreciate. In the past two decades alone, there have been numerous outbreaks (e.g., Ebola, chikungunya, Zika, and Mpox) and pandemics (i.e., swine flu and coronavirus disease 2019) with profound effects to public health, the economy, and society at large. Rather than view these in isolation, there are important lessons pertaining to how best to contend with future outbreaks of emerging infectious diseases. Those lessons span definition (i.e., what constitutes a pandemic), through deficiencies in surveillance, data collection and reporting, the execution of research in a rapidly changing environment, the nuances of study design and hierarchy of clinical evidence, triage according to clinical need as supply chains become overwhelmed, and the challenges surrounding forecasting of outbreaks. Understanding those lessons and drawing on both the successes and failures of the past are imperative if we are to overcome the challenges of outbreak/pandemic responsiveness.

Emergence of Group B Streptococcus Disease in Pigs and Porcupines, Italy.

We describe group B Streptococcus linked to disease in farmed pigs and wild porcupines in Italy. Occurrence in pigs was attributed to transmission from nonpasteurized bovine milk whey. Antimicrobial-resistance profiles in isolates from porcupines suggest no common source of infection. Our findings expand the known host range for group B Streptococcus disease.

Human movement and environmental barriers shape the emergence of dengue.

Understanding how emerging infectious diseases spread within and between countries is essential to contain future pandemics. Spread to new areas requires connectivity between one or more sources and a suitable local environment, but how these two factors interact at different stages of disease emergence remains largely unknown. Further, no analytical framework exists to examine their roles. Here we develop a dynamic modelling approach for infectious diseases that explicitly models both connectivity via human movement and environmental suitability interactions. We apply it to better understand recently observed (1995-2019) patterns as well as predict past unobserved (1983-2000) and future (2020-2039) spread of dengue in Mexico and Brazil. We find that these models can accurately reconstruct long-term spread pathways, determine historical origins, and identify specific routes of invasion. We find early dengue invasion is more heavily influenced by environmental factors, resulting in patchy non-contiguous spread, while short and long-distance connectivity becomes more important in later stages. Our results have immediate practical applications for forecasting and containing the spread of dengue and emergence of new serotypes. Given current and future trends in human mobility, climate, and zoonotic spillover, understanding the interplay between connectivity and environmental suitability will be increasingly necessary to contain emerging and re-emerging pathogens.

Model analysis and data validation of structured prevention and control interruptions of emerging infectious diseases.

The design of optimized non-pharmaceutical interventions (NPIs) is critical to the effective control of emergent outbreaks of infectious diseases such as SARS, A/H1N1 and COVID-19 and to ensure that numbers of hospitalized cases do not exceed the carrying capacity of medical resources. To address this issue, we formulated a classic SIR model to include a close contact tracing strategy and structured prevention and control interruptions (SPCIs). The impact of the timing of SPCIs on the maximum number of non-isolated infected individuals and on the duration of an infectious disease outside quarantined areas (i.e. implementing a dynamic zero-case policy) were analyzed numerically and theoretically. These analyses revealed that to minimize the maximum number of non-isolated infected individuals, the optimal time to initiate SPCIs is when they can control the peak value of a second rebound of the epidemic to be equal to the first peak value. More individuals may be infected at the peak of the second wave with a stronger intervention during SPCIs. The longer the duration of the intervention and the stronger the contact tracing intensity during SPCIs, the more effective they are in shortening the duration of an infectious disease outside quarantined areas. The dynamic evolution of the number of isolated and non-isolated individuals, including two peaks and long tail patterns, have been confirmed by various real data sets of multiple-wave COVID-19 epidemics in China. Our results provide important theoretical support for the adjustment of NPI strategies in relation to a given carrying capacity of medical resources.

Reemergence of Bordetella parapertussis, United States, 2019-2023.

To determine changes in Bordetella pertussis and B. parapertussis detection rates, we analyzed 1.43 million respiratory multiplex PCR test results from US facilities from 2019 through mid-2023. From mid-2022 through mid-2023, Bordetella spp. detection increased 8.5-fold; 95% of detections were B. parapertussis. While B. parapertussis rates increased, B. pertussis rates decreased.

Modeling spillover dynamics: understanding emerging pathogens of public health concern.

The emergence of infectious diseases with pandemic potential is a major public health threat worldwide. The World Health Organization reports that about 60% of emerging infectious diseases are zoonoses, originating from spillover events. Although the mechanisms behind spillover events remain unclear, mathematical modeling offers a way to understand the intricate interactions among pathogens, wildlife, humans, and their shared environment. Aiming at gaining insights into the dynamics of spillover events and the outcome of an eventual disease outbreak in a population, we propose a continuous time stochastic modeling framework. This framework links the dynamics of animal reservoirs and human hosts to simulate cross-species disease transmission. We conduct a thorough analysis of the model followed by numerical experiments that explore various spillover scenarios. The results suggest that although most epidemic outbreaks caused by novel zoonotic pathogens do not persist in the human population, the rising number of spillover events can avoid long-lasting extinction and lead to unexpected large outbreaks. Hence, global efforts to reduce the impacts of emerging diseases should not only address post-emergence outbreak control but also need to prevent pandemics before they are established.

Acinetobacter junii: an emerging One Health pathogen.

Acinetobacter junii is an opportunistic human and animal pathogen severely understudied. Here, we conducted the largest genomic epidemiological study on this pathogen to date. Our data show that this bacterium has spread globally. Also, we found that some human and non-human isolates are not well differentiated from one another, implying transmission between clinical and non-clinical, non-human settings. Remarkably, human but also some non-human isolates have clinically important antibiotic resistance genes, and some of these genes are located in plasmids. Given these results, we put forward that A. junii should be considered an emerging One Health problem. In this regard, future molecular epidemiological studies about this species will go beyond human isolates and will consider animal-, plant-, and water-associated environments. IMPORTANCE: Acinetobacter baumannii is the most well-known species from the genus Acinetobacter. However, other much less studied Acinetobacter species could be important opportunistic pathogens of animals, plants and humans. Here, we conducted the largest genomic epidemiological study of A. junii, which has been described as a source not only of human but also of animal infections. Our analyses show that this bacterium has spread globally and that, in some instances, human and non-human isolates are not well differentiated. Remarkably, some non-human isolates have important antibiotic resistance genes against important antibiotics used in human medicine. Based on our results, we propose that this pathogen must be considered an issue not only for humans but also for veterinary medicine.