Operational guidelines for the elimination of human fascioliasis as a public health problem in the Americas

Fascioliasis is a parasitic disease that affects both people and a wide variety of animals, primarily herbivores. In Latin America and the Caribbean, it is caused by the trematode Fasciola hepatica. Fascioliasis is classified by the World Health Organization (WHO) as one of the neglected tropical diseases. The Pan American Health Organization (PAHO), as part of its commitment to achieving the goals of the 2030 Agenda for Sustainable Development and the Sustainable Health Agenda for the Americas 2018-2030, has launched an initiative to eliminate communicable diseases in the Region of the Americas, which includes among its objectives the elimination of fascioliasis as a public health problem in the Americas by 2030. These operational guidelines have been developed to provide information and guidance to support endemic countries in advancing towards and achieving that goal. They have been prepared with the support of technicians from the countries as well as expert professionals from the Region and the WHO Collaborating Centre on fascioliasis and its vector snails, attempting to incorporate current practices and considering the challenges and particularities of endemic areas. While fasciolosis in animals is a problem in many countries of the Region, leading to economic losses, human fascioliasis is limited to environments where the ethnographic characteristics and socio-economic determinants necessary for human infection are present. These operational guidelines focus on such areas, typically associated with small-scale farmers and rural communities, and are framed within the "One Health" approach, integrating different sectors involved, working together and synergistically to make interventions more effective and sustainable.

Single domain antibodies from camelids in the treatment of microbial infections.

Infectious diseases continue to pose significant global health challenges. In addition to the enduring burdens of ailments like malaria and HIV, the emergence of nosocomial outbreaks driven by antibiotic-resistant pathogens underscores the ongoing threats. Furthermore, recent infectious disease crises, exemplified by the Ebola and SARS-CoV-2 outbreaks, have intensified the pursuit of more effective and efficient diagnostic and therapeutic solutions. Among the promising options, antibodies have garnered significant attention due to their favorable structural characteristics and versatile applications. Notably, nanobodies (Nbs), the smallest functional single-domain antibodies of heavy-chain only antibodies produced by camelids, exhibit remarkable capabilities in stable antigen binding. They offer unique advantages such as ease of expression and modification and enhanced stability, as well as improved hydrophilicity compared to conventional antibody fragments (antigen-binding fragments (Fab) or single-chain variable fragments (scFv)) that can aggregate due to their low solubility. Nanobodies directly target antigen epitopes or can be engineered into multivalent Nbs and Nb-fusion proteins, expanding their therapeutic potential. This review is dedicated to charting the progress in Nb research, particularly those derived from camelids, and highlighting their diverse applications in treating infectious diseases, spanning both human and animal contexts.

[Taking origins into account in medical reasoning in infectious and tropical diseases? A critical look]. / Tenir compte des origines dans le raisonnement médical en maladies infectieuses et tropicales ? Un regard critique.

Healthcare discriminations based on one's ethnic background is increasingly being studied in medicine. The scale of the Covid-19 pandemic has played an important role in bringing them to light. Data, although scarce, exist in France. These discriminations have an impact on the care pathway and contribute to the renunciation of care by the most affected populations. The issue of discrimination is particularly relevant in infectious diseases. Although the epidemiology of infectious diseases is unevenly distributed worldwide, erroneous social representations are prevalent and expose to a harmful prejudice against migrants with regard to infectious diseases. The transmissible nature of some infectious diseases reinforces their stigmatizing potential. In this context, it seems important to discuss the dimension to be given to social determinants, geographical origin, phenotype, and ethnicity in teaching and medical reasoning. The English-speaking world uses the concept of "race" in a structural way, whereas this "international standard" has not been applied in France until now. To improve the care of people from minority groups, it seems important to better document and teach a more nuanced clinical reasoning based on origin, without neglecting the importance of collecting and taking into account social determinants of health and environmental factors.

Integrating gated recurrent unit in graph neural network to improve infectious disease prediction: an attempt.

Objective: This study focuses on enhancing the precision of epidemic time series data prediction by integrating Gated Recurrent Unit (GRU) into a Graph Neural Network (GNN), forming the GRGNN. The accuracy of the GNN (Graph Neural Network) network with introduced GRU (Gated Recurrent Units) is validated by comparing it with seven commonly used prediction methods. Method: The GRGNN methodology involves multivariate time series prediction using a GNN (Graph Neural Network) network improved by the integration of GRU (Gated Recurrent Units). Additionally, Graphical Fourier Transform (GFT) and Discrete Fourier Transform (DFT) are introduced. GFT captures inter-sequence correlations in the spectral domain, while DFT transforms data from the time domain to the frequency domain, revealing temporal node correlations. Following GFT and DFT, outbreak data are predicted through one-dimensional convolution and gated linear regression in the frequency domain, graph convolution in the spectral domain, and GRU (Gated Recurrent Units) in the time domain. The inverse transformation of GFT and DFT is employed, and final predictions are obtained after passing through a fully connected layer. Evaluation is conducted on three datasets: the COVID-19 datasets of 38 African countries and 42 European countries from worldometers, and the chickenpox dataset of 20 Hungarian regions from Kaggle. Metrics include Average Root Mean Square Error (ARMSE) and Average Mean Absolute Error (AMAE). Result: For African COVID-19 dataset and Hungarian Chickenpox dataset, GRGNN consistently outperforms other methods in ARMSE and AMAE across various prediction step lengths. Optimal results are achieved even at extended prediction steps, highlighting the model's robustness. Conclusion: GRGNN proves effective in predicting epidemic time series data with high accuracy, demonstrating its potential in epidemic surveillance and early warning applications. However, further discussions and studies are warranted to refine its application and judgment methods, emphasizing the ongoing need for exploration and research in this domain.

Temporal shifts in 24 notifiable infectious diseases in China before and during the COVID-19 pandemic.

The coronavirus disease 2019 (COVID-19) pandemic, along with the implementation of public health and social measures (PHSMs), have markedly reshaped infectious disease transmission dynamics. We analysed the impact of PHSMs on 24 notifiable infectious diseases (NIDs) in the Chinese mainland, using time series models to forecast transmission trends without PHSMs or pandemic. Our findings revealed distinct seasonal patterns in NID incidence, with respiratory diseases showing the greatest response to PHSMs, while bloodborne and sexually transmitted diseases responded more moderately. 8 NIDs were identified as susceptible to PHSMs, including hand, foot, and mouth disease, dengue fever, rubella, scarlet fever, pertussis, mumps, malaria, and Japanese encephalitis. The termination of PHSMs did not cause NIDs resurgence immediately, except for pertussis, which experienced its highest peak in December 2023 since January 2008. Our findings highlight the varied impact of PHSMs on different NIDs and the importance of sustainable, long-term strategies, like vaccine development.

Social contacts patterns relevant to the transmission of infectious diseases in Suzhou, China following the COVID-19 epidemic.

BACKGROUND: The COVID-19 pandemic has profoundly affected human social contact patterns, but there is limited understanding regarding the post-pandemic social contact patterns. Our objective is to quantitatively assess social contact patterns in Suzhou post-COVID-19. METHODS: We employed a diary design and conducted social contact surveys from June to October 2023, utilizing paper questionnaires. A generalized linear model was utilized to analyze the relationship between individual contacts and covariates. We examined the proportions of contact type, location, duration, and frequency. Additionally, age-related mixed matrices were established. RESULTS: The participants reported an average of 11.51 (SD 5.96) contact numbers and a total of 19.78 (SD 20.94) contact numbers per day, respectively. The number of contacts was significantly associated with age, household size, and the type of week. Compared to the 0-9 age group, those in the 10-19 age group reported a higher number of contacts (IRR = 1.12, CI: 1.01-1.24), while participants aged 20 and older reported fewer (IRR range: 0.54-0.67). Larger households (5 or more) reported more contacts (IRR = 1.09, CI: 1.01-1.18) and fewer contacts were reported on weekends (IRR = 0.95, CI: 0.90-0.99). School had the highest proportion of contact durations exceeding 4 h (49.5%) and daily frequencies (90.4%), followed by home and workplace. The contact patterns exhibited clear age-assortative mixing, with Q indices of 0.27 and 0.28. CONCLUSIONS: We assessed the characteristics of social contact patterns in Suzhou, which are essential for parameterizing models of infectious disease transmission. The high frequency and intensity of contacts among school-aged children should be given special attention, making school intervention policies a crucial component in controlling infectious disease transmission.

Why We Need to Change How We Talk About Infectious Disease.

This article builds a case for raising occupational consciousness by critically questioning ahistorical and apolitical uses of battle language, especially when referring to infectious diseases. Words such as invasion, colonization, and resistance are particularly ethically troubling, and this article considers why the social practices our language brings about matter in health care. Dynamic relationships among humans and microbes, as well as metaphor, are considered here in historical context and through the lens of Derrida's portmanteau hostipitality, which invites reconsideration of an infectious disease notion of host and how conceptions of hospitality have been institutionalized and commodified. This article argues that language used in infectious disease care settings should be informed by coexistence as a guiding value of clinical and ethical relevance.

A risk-induced dispersal strategy of the infected population for a disease-free state in the SIS epidemic model.

This article proposes a dispersal strategy for infected individuals in a spatial susceptible-infected-susceptible (SIS) epidemic model. The presence of spatial heterogeneity and the movement of individuals play crucial roles in determining the persistence and eradication of infectious diseases. To capture these dynamics, we introduce a moving strategy called risk-induced dispersal (RID) for infected individuals in a continuous-time patch model of the SIS epidemic. First, we establish a continuous-time n-patch model and verify that the RID strategy is an effective approach for attaining a disease-free state. This is substantiated through simulations conducted on 7-patch models and analytical results derived from 2-patch models. Second, we extend our analysis by adapting the patch model into a diffusive epidemic model. This extension allows us to explore further the impact of the RID movement strategy on disease transmission and control. We validate our results through simulations, which provide the effects of the RID dispersal strategy.

Contagion dynamics in time-varying metapopulation networks with node's activity and attractiveness.

The metapopulation network model is a mathematical framework used to study the spatial spread of epidemics with individuals' mobility. In this paper, we develop a time-varying network model in which the activity of a population is correlated with its attractiveness in mobility. By studying the spreading dynamics of the SIR (susceptible-infectious-recovered)-type disease in different correlated networks based on the proposed model, we theoretically derive the mobility threshold and numerically observe that increasing the correction between activity and attractiveness results in a reduced mobility threshold but suppresses the fraction of infected subpopulations. It also introduces greater heterogeneity in the spatial distribution of infected individuals. Additionally, we investigate the impact of nonpharmaceutical interventions on the spread of epidemics in different correlation networks. Our results show that the simultaneous implementation of self-isolation and self-protection is more effective in negatively correlated networks than that in positively correlated or non-correlated networks. Both self-isolation and self-protection strategies enhance the mobility threshold and, thus, slow down the spread of the epidemic. However, the effectiveness of each strategy in reducing the fraction of infected subpopulations varies in different correlated networks. Self-protection is more effective in positively correlated networks, whereas self-isolation is more effective in negatively correlated networks. Our study will provide insights into epidemic prevention and control in large-scale time-varying metapopulation networks.

The burden of infectious diseases throughout and after the COVID-19 pandemic (2020-2023) and Russo-Ukrainian war migration.

Understanding how the infectious disease burden was affected throughout the COVID-19 pandemic is pivotal to identifying potential hot spots and guiding future mitigation measures. Therefore, our study aimed to analyze the changes in the rate of new cases of Poland's most frequent infectious diseases during the entire COVID-19 pandemic and after the influx of war refugees from Ukraine. We performed a registry-based population-wide study in Poland to analyze the changes in the rate of 24 infectious disease cases from 2020 to 2023 and compared them to the prepandemic period (2016-2019). Data were collected from publicly archived datasets of the Epimeld database published by national epidemiological authority institutions. The rate of most of the studied diseases (66.6%) revealed significantly negative correlations with the rate of SARS-CoV-2 infections. For the majority of infectious diseases, it substantially decreased in 2020 (in case of 83%) and 2021 (63%), following which it mostly rebounded to the prepandemic levels and, in some cases, exceeded them in 2023 when the exceptionally high annual rates of new cases of scarlet fever, Streptococcus pneumoniae infections, HIV infections, syphilis, gonococcal infections, and tick-borne encephalitis were noted. The rate of Clostridioides difficile enterocolitis was two-fold higher than before the pandemic from 2021 onward. The rate of Legionnaires' disease in 2023 also exceeded the prepandemic threshold, although this was due to a local outbreak unrelated to lifted COVID-19 pandemic restrictions or migration of war refugees. The influx of war migrants from Ukraine could impact the epidemiology of sexually transmitted diseases. The present analysis indicates that continued efforts are needed to prevent COVID-19 from overwhelming healthcare systems again and decreasing the control over the burden of other infectious diseases. It also identifies the potential tipping points that require additional mitigation measures, which are also discussed in the paper, to avoid escalation in the future.

Obesity is a communicable disease.

Obesity has multiple causes and correlates. Usually studied as a metabolic and endocrine disease, with mechanical and musculoskeletal comorbidities, obesity also has a communicable angle to it. Obesity can be considered a communicable disease from the conventional point of view, as it is associated with viral etiology in animal and human models. It is also associated with increased prevalence and worse prognosis of infectious diseases. Not only that, obesity is a 'socially communicable' disease, as it 'spreads' amongst people living in similar environments.

Vitamin D and viral infections: Infectious diseases, autoimmune diseases, and cancers.

Viruses can cause many human diseases. Three types of human diseases caused by viruses are discussed in this chapter: infectious diseases, autoimmune diseases, and cancers. The infectious diseases included in this chapter include three respiratory tract diseases: influenza, COVID-19, and respiratory syncytial virus. In addition, the mosquito-borne dengue virus diseases are discussed. Vitamin D can reduce risk, severity, and mortality of the respiratory tract diseases and possibly for dengue virus. Many autoimmune diseases are initiated by the body's reaction to a viral infection. The protective role of vitamin D in Epstein-Barr virus-related diseases such as multiple sclerosis is discussed. There are a few cancers linked to viral infections. Such cancers include cervical cancer, head and neck cancers, Hodgkin's and non-Hodgkin's lymphoma, and liver cancer. Vitamin D plays an important role in reducing risk of cancer incidence and mortality, although not as strongly for viral-linked cancers as for other types of cancer.

Geography and health: role of human translocation and access to care.

Natural, geographical barriers have historically limited the spread of communicable diseases. This is no longer the case in today's interconnected world, paired with its unprecedented environmental and climate change, emphasising the intersection of evolutionary biology, epidemiology and geography (i.e. biogeography). A total of 14 articles of the special issue entitled "Geography and health: role of human translocation and access to care" document enhanced disease transmission of diseases, such as malaria, leishmaniasis, schistosomiasis, COVID-19 (Severe acute respiratory syndrome corona 2) and Oropouche fever in spite of spatiotemporal surveillance. High-resolution satellite images can be used to understand spatial distributions of transmission risks and disease spread and to highlight the major avenue increasing the incidence and geographic range of zoonoses represented by spill-over transmission of coronaviruses from bats to pigs or civets. Climate change and globalization have increased the spread and establishment of invasive mosquitoes in non-tropical areas leading to emerging outbreaks of infections warranting improved physical, chemical and biological vector control strategies. The translocation of pathogens and their vectors is closely connected with human mobility, migration and the global transport of goods. Other contributing factors are deforestation with urbanization encroaching into wildlife zones. The destruction of natural ecosystems, coupled with low income and socioeconomic status, increase transmission probability of neglected tropical and zoonotic diseases. The articles in this special issue document emerging or re-emerging diseases and surveillance of fever symptoms. Health equity is intricately connected to accessibility to health care and the targeting of healthcare resources, necessitating a spatial approach. Public health comprises successful disease management integrating spatial surveillance systems, including access to sanitation facilities. Antimicrobial resistance caused, e.g. by increased use of antibiotics in health, agriculture and aquaculture, or acquisition of resistance genes, can be spread by horizontal gene transfer. This editorial reviews the key findings of this 14-article special issue, identifies important gaps relevant to our interconnected world and makes a number of specific recommendations to mitigate the transmission risks of infectious diseases in the post-COVID-19 pandemic era.

Macrophage membrane-coated nanoparticles for the treatment of infectious diseases.

Infectious diseases severely threaten human health, and traditional treatment techniques face multiple limitations. As an important component of immune cells, macrophages display unique biological properties, such as biocompatibility, immunocompatibility, targeting specificity, and immunoregulatory activity, and play a critical role in protecting the body against infections. The macrophage membrane-coated nanoparticles not only maintain the functions of the inner nanoparticles but also inherit the characteristics of macrophages, making them excellent tools for improving drug delivery and therapeutic implications in infectious diseases (IDs). In this review, we describe the characteristics and functions of macrophage membrane-coated nanoparticles and their advantages and challenges in ID therapy. We first summarize the pathological features of IDs, providing insight into how to fight them. Next, we focus on the classification, characteristics, and preparation of macrophage membrane-coated nanoparticles. Finally, we comprehensively describe the progress of macrophage membrane-coated nanoparticles in combating IDs, including drug delivery, inhibition and killing of pathogens, and immune modulation. At the end of this review, a look forward to the challenges of this aspect is presented.

Nanobodies in the fight against infectious diseases: repurposing nature's tiny weapons.

Nanobodies are the smallest known antigen-binding molecules to date. Their small size, good tissue penetration, high stability and solubility, ease of expression, refolding ability, and negligible immunogenicity in the human body have granted them excellence over conventional antibodies. Those exceptional attributes of nanobodies make them promising candidates for various applications in biotechnology, medicine, protein engineering, structural biology, food, and agriculture. This review presents an overview of their structure, development methods, advantages, possible challenges, and applications with special emphasis on infectious diseases-related ones. A showcase of how nanobodies can be harnessed for applications including neutralization of viruses and combating antibiotic-resistant bacteria is detailed. Overall, the impact of nanobodies in vaccine design, rapid diagnostics, and targeted therapies, besides exploring their role in deciphering microbial structures and virulence mechanisms are highlighted. Indeed, nanobodies are reshaping the future of infectious disease prevention and treatment.