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Background: Global estimates for cholera annually approximate 4 million cases worldwide with 95,000 deaths. Recent outbreaks, including Haiti and Yemen, are reminders that cholera is still a global health concern. Cholera outbreaks can rapidly induce high death tolls by overwhelming the capacity of health facilities, especially in remote areas or areas of civil unrest. Recent studies demonstrated that stool specimens preserved on filter paper facilitate molecular analysis of Vibrio cholerae in resource limited settings. Specimens preserved in a rapid, low-cost, safe and sustainable manner for sequencing provides previously unavailable data about circulating cholera strains. This may ultimately provide new information to shape public policy response on cholera control and elimination. Methodology/Principal findings: Whole genome sequencing (WGS) recovered close to a complete sequence of the V. cholerae O1 genome with satisfactory genome coverage from stool specimens enriched in alkaline peptone water (APW) and V. cholerae culture isolates, both spotted on filter paper. The minimum concentration of V. cholerae DNA sufficient to produce quality genomic information was 0.02 ng/μL. The genomic data confirmed the presence or absence of genes of epidemiological interest, including cholera toxin and pilus loci. WGS identified a variety of diarrheal pathogens from APW-enriched specimen spotted filter paper, highlighting the potential for this technique to explore the gut microbiome, potentially identifying co-infections, which may impact the severity of disease. WGS demonstrated that these specimens fit within the current global cholera phylogenetic tree, identifying the strains as the 7th pandemic El Tor. Conclusions: WGS results allowed for mapping of short reads from APW-enriched specimen and culture isolate spotted filter papers this provided valuable molecular epidemiological sequence information on V. cholerae strains from remote, low-resource settings. These results identified the presence of co-infecting pathogens while providing rare insight into the specific V. cholerae strains causing outbreaks in cholera-endemic areas. [ABSTRACT FROM AUTHOR]

Recommended Revisions to the National SEP-1 Sepsis Quality Measure: A commentary by the Society of Infectious Diseases Pharmacists on the Infectious Diseases Society of America Position Paper Keywords: sepsis; infectious diseases; septic shock EN sepsis infectious diseases septic shock 368 371 4 04/14/20 20200401 NES 200401 Following recent revisions to the U.S. Centers for Medicare & Medicaid Services Sepsis and Septic Shock Early Management Bundle (SEP-1) reporting requirement, the Infectious Diseases Society of America (IDSA) led a group of invested stakeholder organizations to develop a position paper of recommended revisions to further improve SEP-1. In addition to these specific comments on the recommendations from IDSA, SIDP also recommends general improvements in broad-spectrum antibiotic administration in patients with septic shock. [Extracted from the article]

Africa's dual burden of rising incidence of infectious diseases and increasing prevalence of non-communicable diseases (NCDs), such as cardiovascular diseases and diabetes, demands innovative approaches to disease surveillance, response, and cross-border health management in response to growing economic integration and global connectivity. In this context, we propose a discursive framework for the development and implementation of a multi-disease digital health passport (MDDHP) in Africa. The MDDHP would serve as a secure platform for storing and sharing individual health data, offering a comprehensive solution to track and respond to infectious diseases, facilitate the management of NCDs, and improve healthcare access across borders. Empowering individuals to proactively manage their health and improve overall outcomes is a key aspect of the MDDHP. In the paper, we examine the key elements necessary to effectively implement MDDHP, focusing on minimizing risks, maintaining efficacy, and driving its adoption while also taking into consideration the unique contexts of the continent. The paper is intended to provide an understanding of the key principles involved and contribute to the discussion on the development and successful implementation of MDDHP in Africa. [ABSTRACT FROM AUTHOR]

Here we describe an ultra-low-cost origami-based approach for large-scale manufacturing of microscopes, specifically demonstrating brightfield, darkfield, and fluorescence microscopes. Merging principles of optical design with origami enables high-volume fabrication of microscopes from 2D media. Flexure mechanisms created via folding enable a flat compact design. Structural loops in folded paper provide kinematic constraints as a means for passive self-alignment. This light, rugged instrument can survive harsh field conditions while providing a diversity of imaging capabilities, thus serving wide-ranging applications for cost-effective, portable microscopes in science and education. [ABSTRACT FROM AUTHOR]

India has the highest burden of Tuberculosis (TB) and multidrug-resistant TB (MDR-TB) worldwide. Innovative technology is the need of the hour to identify these cases that remain either undiagnosed or inadequately diagnosed due to the unavailability of appropriate tools at primary healthcare settings. We developed and evaluated 3 kits, namely ‘TB Detect’ (containing BioFM-Filter device), ‘TB Concentration and Transport’ (containing Trans-Filter device) and ‘TB DNA Extraction’ kits. These kits enable bio-safe equipment-free concentration of sputum on filters and improved fluorescence microscopy at primary healthcare centres, ambient temperature transport of dried inactivated sputum filters to central laboratories and molecular detection of drug resistance by PCR and DNA sequencing (Mol-DST). In a 2-site evaluation (n = 1190 sputum specimens) on presumptive TB patients, BioFM-Filter smear exhibited a significant increase in positivity of 7% and 4% over ZN smear and LED-FM smear (p<0.05), respectively and an increment in smear grade status (1+ or 2+ to 3+) of 16% over ZN smear and 20% over LED-FM smear. The sensitivity of Mol-DST in presumptive MDR-TB and XDR-TB cases (n = 148) was 90% for Rifampicin (95% confidence interval [CI], 78–96%), 84% for Isoniazid (95% CI, 72–92%), 83% for Fluoroquinolones (95% CI, 66–93%) and 75% for Aminoglycosides (95% CI, 35–97%), using phenotypic DST as the reference standard. Test specificity was 88–93% and concordance was ~89–92% (κ value 0.8–0.9). The patient-friendly kits described here address several of the existing challenges and are designed to provide ‘Universal Access’ to rapid TB diagnosis, including drug-resistant disease. Their utility was demonstrated by application to sputum at 2 sites in India. Our findings pave the way for larger studies in different point-of-care settings, including high-density urban areas and remote geographical locations. [ABSTRACT FROM AUTHOR]

Pyocyanin is a toxin produced by Pseudomonas aeruginosa. Here we describe a novel paper-based electrochemical sensor for pyocyanin detection, manufactured with a simple and inexpensive approach based on electrode printing on paper. The resulting sensors constitute an effective electrochemical method to quantify pyocyanin in bacterial cultures without the conventional time consuming pretreatment of the samples. The electrochemical properties of the paper-based sensors were evaluated by ferri/ferrocyanide as a redox mediator, and showed reliable sensing performance. The paper-based sensors readily allow for the determination of pyocyanin in bacterial cultures with high reproducibility, achieving a limit of detection of 95 nM and a sensitivity of 4.30 μA/μM in standard culture media. Compared to the similar commercial ceramic based sensors, it is a 2.3-fold enhanced performance. The simple in-house fabrication of sensors for pyocyanin quantification allows researchers to understand in vitro adaptation of P. aeruginosa infections via rapid screenings of bacterial cultures that otherwise are expensive and time-consuming. [ABSTRACT FROM AUTHOR]

Background: Identification of the source of mosquito blood meals is an important component for disease control and surveillance. Recently, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling has emerged as an effective tool for mosquito blood meal identification, using the abdomens of freshly engorged mosquitoes. In the field, mosquito abdomens are crushed on Whatman filter papers to determine the host feeding patterns by identifying the origin of their blood meals. The aim of this study was to test whether crushing engorged mosquito abdomens on Whatman filter papers was compatible with MALDI-TOF MS for mosquito blood meal identification. Both laboratory reared and field collected mosquitoes were tested. Material and methods: Sixty Anopheles gambiae Giles were experimentally engorged on the blood of six distinct vertebrate hosts (human, sheep, rabbit, dog, chicken and rat). The engorged mosquito abdomens were crushed on Whatman filter papers for MALDI-TOF MS analysis. 150 Whatman filter papers, with mosquitoes engorged on cow and goat blood, were preserved. A total of 77 engorged mosquito abdomens collected in the Comoros Islands and crushed on Whatman filter papers were tested with MALDI-TOF MS. Results: The MS profiles generated from mosquito engorged abdomens crushed on Whatman filter papers exhibited high reproducibility according to the original host blood. The blood meal host was correctly identified from mosquito abdomens crushed on Whatman filter papers by MALDI-TOF MS. The MS spectra obtained after storage were stable regardless of the room temperature and whether or not they were frozen. The MS profiles were reproducible for up to three months. For the Comoros samples, 70/77 quality MS spectra were obtained and matched with human blood spectra. This was confirmed by molecular tools. Conclusion: The results demonstrated that MALDI-TOF MS could identify mosquito blood meals from Whatman filter papers collected in the field during entomological surveys. The application of MALDI-TOF MS has proved to be rapid and successful, making it a new and efficient tool for mosquito-borne disease surveillance. [ABSTRACT FROM AUTHOR]

Today, because infectious diseases have a large impact on people, control methods for all infectious diseases are crucial. In this paper, we propose a SIQR model with Crowley-Martin type incidence rate and saturated treatment. We have incorporated precautionary measures taken by the population through the saturated incidence rate. Screening of individuals who have come into contact with infected individuals is modelled. Thus, we explore a four-dimensional mathematical model to study the dynamics of the infectious diseases and their management. Stability and bifurcation analysis ofthe system is done. The Mensitivity analysis of all parameters in relation to the basic reproduction number has been performed and the theoretical results have been validated using numerical simulation. Mathematical results in this paper suggest that both government interventions and individual efforts must be incorporated to achieve better control of emerging infectious diseases in the population. [ABSTRACT FROM AUTHOR]

The article offers information on catalyzing Neglected Tropical Diseases (NTD) gender and equity research. Topics discussed include significance of the NTD program predicated opportunity to treat disease, prevent morbidity and disability, and interrupt infection transmission among large populations; addresses the issue of gender equity, organizational, policy, and practice activities; and sex and gender roles can profound effect on healthcare access and health outcomes.

The purpose of this paper is to explore the ethical foundation for resolving ethical issues arising from the biomedical big data analytics on emerging infectious diseases. To this end, this paper first compares the moral issues arising from the analysis of healthcare big data for emerging infectious diseases with the existing problem areas of biomedical ethics. We will discuss how existing bioethical debates, especially those dealing with the issue of individual autonomy, are inadequate to address the ethical issues of biomedical big data analytics for emerging infectious diseases, even though they have some relevance. Based on these discussions, I will present one approach to addressing the ethical issues of biomedical big data analytics for emerging infectious diseases, centered on L. Floridi’s notion of agents. This will provide an opportunity to expand the existing discussion of bioethics to include information ethics. [ABSTRACT FROM AUTHOR]

As more HIV-infected people gain access to antiretroviral therapy (ART), monitoring HIV drug resistance (HIVDR) becomes essential to combat both acquired and transmitted HIVDR. Studies have demonstrated dried blood spots (DBS) are a suitable alternative in HIVDR monitoring using DBS collected on Whatman 903 (W-903). In this study, we sought to evaluate two other commercially available filter papers, Ahlstrom 226 (A-226) and Munktell TFN (M-TFN), for HIVDR genotyping following ambient temperature storage. DBS were prepared from remnant blood specimens collected from 334 ART patients and stored at ambient temperature for a median time of 30 days. HIV-1 viral load was determined using NucliSENS EasyQ® HIV-1 v2.0 RUO test kits prior to genotyping of the protease and reverse transcriptase regions of the HIV-1 pol gene using an in-house assay. Among the DBS tested, 26 specimens had a viral load ≥1000 copies/mL in all three types of filter paper and were included in the genotyping analysis. Genotyping efficiencies were similar between DBS collected on W-903 (92.3%), A-226 (88.5%), and M-TFN (92.3%) filter papers (P = 1.00). We identified 50 DR-associated mutations in DBS collected on W-903, 33 in DBS collected on A-226, and 48 in DBS collected on M-TFN, resulting in mutation detection sensitivities of 66.0% for A-226 and 88.0% for M-TFN when compared to W-903. Our data indicate that differences among filter papers may exist at this storage condition and warrant further studies evaluating filter paper type for HIVDR monitoring. [ABSTRACT FROM AUTHOR]

Background: Loop mediated isothermal amplification (LAMP) provides an opportunity for improved, field-friendly detection of malaria infections in endemic areas. However data on the diagnostic accuracy of LAMP for active case detection, particularly low-density parasitaemias, are lacking. We therefore evaluated the performance of a new LAMP kit compared with PCR using DNA from filter paper blood spots. Methods and Findings: Samples from 865 fever patients and 465 asymptomatic individuals collected in Zanzibar were analysed for Pan (all species) and Pf (P. falciparum) DNA with the Loopamp MALARIA Pan/Pf kit. Samples were amplified at 65°C for 40 minutes in a real-time turbidimeter and results were compared with nested PCR. Samples with discordant results between LAMP and nested PCR were analysed with real-time PCR. The real-time PCR corrected nested PCR result was defined as gold standard. Among the 117 (13.5%) PCR detected P. falciparum infections from fever patients (mean parasite density 7491/µL, range 6–782,400) 115, 115 and 111 were positive by Pan-LAMP, Pf-LAMP and nested PCR, respectively. The sensitivities were 98.3% (95%CI 94–99.8) for both Pan and Pf-LAMP. Among the 54 (11.6%) PCR positive samples from asymptomatic individuals (mean parasite density 10/µL, range 0–4972) Pf-LAMP had a sensitivity of 92.7% (95%CI 80.1–98.5) for detection of the 41 P. falciparum infections. Pan-LAMP had sensitivities of 97% (95%CI 84.2–99.9) and 76.9% (95%CI 46.2–95) for detection of P. falciparum and P. malariae, respectively. The specificities for both Pan and Pf-LAMP were 100% (95%CI 99.1–100) in both study groups. Conclusion: Both components of the Loopamp MALARIA Pan/Pf detection kit revealed high diagnostic accuracy for parasite detection among fever patients and importantly also among asymptomatic individuals of low parasite densities from minute blood volumes preserved on filter paper. These data support LAMPs potential role for improved detection of low-density malaria infections in pre-elimination settings. [ABSTRACT FROM AUTHOR]

Spreading quickly throughout populations, whether animal or human-borne, infectious illnesses provide serious risks and difficulties. Controlling their spread and averting disinformation requires effective risk assessment and epidemic identification. Technology-enabled data analysis on diseases allows for quick solutions to these problems. A Combinational Data Assessment Scheme intended to accelerate disease detection is presented in this paper. The suggested strategy avoids duplicate data replication by sharing data among edge devices. It uses indexed data gathering to improve early detection by using tree classifiers to discern between various kinds of information. Both data similarity and index measurements are considered throughout the data analysis stage to minimize assessment errors. Accurate risk detection and assessment based on information kind and sharing frequency are ensured by comparing non-linear accumulations with accurate shared edge data. The suggested system exhibits high accuracy, low mistakes, and decreased data repetition to improve overall effectiveness in illness detection and risk reduction. [ABSTRACT FROM AUTHOR]

On July 19th, 2023, the National Institute of Allergy and Infectious Diseases co-organized a workshop with the Society of Mathematical Biology, with the authors of this paper as the organizing committee. The workshop, "Bridging multiscale modeling and practical clinical applications in infectious diseases" sought to create an environment for mathematical modelers, statisticians, and infectious disease researchers and clinicians to exchange ideas and perspectives. [ABSTRACT FROM AUTHOR]

The importance of user-friendly, inexpensive, sensitive, and selective detection of viruses has been highlighted again due to the recent Coronavirus disease 2019 (COVID-19) pandemic. Among the analytical tools, paper-based devices (PADs) have become a leading alternative for point-of-care (POC) testing. In this review, we discuss the recent development strategies and applications in nucleic acid-based, antibody/antigen-based and other affinity-based PADs using optical and electrochemical detection methods for sensing viruses. In addition, advantages and drawbacks of presented PADs are identified. Current state and insights towards future perspectives are presented regarding developing POC diagnosis platform for COVID-19. This review considers state-of-the-art technologies for further development and improvement in PADs performance for virus detection. [Display omitted] • Reviewed developments in PADs for optical and electrochemical detection of viruses. • Highlighted recent applications in antibody/antigen-, nucleic acid-, aptamer- and CRISPR-based PADs for viral detection. • Emphasized low-cost POC diagnostic tools to control the global COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

One of the major bottlenecks affecting the expansion of the freshwater aquaculture sector in developing countries is the outbreak of diseases. Fish farmers have traditionally relied on antibiotics and synthetic chemicals to control diseases. However, antibiotics and synthetic chemicals are associated with negative effects on the environment and consumers and their excessive use has resulted in antibiotic-resistant pathogens. In addition, the majority of freshwater fish farmers, especially small-scale farmers, have limited access to antibiotics and synthetic chemicals due to lack of resources. Medicinal plants have been reported to be suitable replacements in aquaculture, but their usage in aquaculture is still limited. The aim of this paper is to undertake a meta-analysis on the effect of medicinal plants on innate immune response and disease resistance in commonly farmed freshwater aquaculture fish species, namely Mozambique tilapia (Oreochromis mossambicus), African catfish (Clarias gariepinus), trout (Oncorhynchus mykiss), and cyprinids (Labeo rohita and Cyprinus carpio). The analysis showed that the mean effect size for respiratory burst (− 1.90 (95% CI − 2.40; − 1.40), I2 = 100%, P = 0); lysozyme activity (0.05 (95% CI − 0.38; 0.48), I2 = 97%, P < 0.01); white blood cells (− 0.69 (95% CI − 1.16; − 0.23), I2 = 89%, P < 0.01); and phagocytic activity (− 1.21 (95% CI − 2.08; − 0.35), I2 = 91%, P < 0.01) was significantly different. Mean effect size for survival rates was not significantly different (2.56 (95% CI 0.10; 5.01), I2 = 0%, P = 1). The funnel plots for all parameters were asymmetrical, which indicates possible publication bias or the presence of systematic differences or inconsistencies among studies. Overall, the meta-analysis showed that medicinal plants could enhance immunity and disease resistance in tilapia, African catfish, carp, and trout. These findings reinforce the observation that plant supplements can be used to prevent disease outbreaks in aquaculture. It is therefore recommended that freshwater fish farmers in African regions such as Southern Africa learn to produce their own diets supplemented with plants at their farms in order to prevent diseases in cultured fish. [ABSTRACT FROM AUTHOR]

Background: Previously, many methods have been used to predict the incidence trends of infectious diseases. There are numerous methods for predicting the incidence trends of infectious diseases, and they have exhibited varying degrees of success. However, there are a lack of prediction benchmarks that integrate linear and nonlinear methods and effectively use internet data. The aim of this paper is to develop a prediction model of the incidence rate of infectious diseases that integrates multiple methods and multisource data, realizing ground-breaking research. Results: The infectious disease dataset is from an official release and includes four national and three regional datasets. The Baidu index platform provides internet data. We choose a single model (seasonal autoregressive integrated moving average (SARIMA), nonlinear autoregressive neural network (NAR), and long short-term memory (LSTM)) and a deep evolutionary fusion neural network (DEFNN). The DEFNN is built using the idea of neural evolution and fusion, and the DEFNN + is built using multisource data. We compare the model accuracy on reference group data and validate the model generalizability on external data. (1) The loss of SA-LSTM in the reference group dataset is 0.4919, which is significantly better than that of other single models. (2) The loss values of SA-LSTM on the national and regional external datasets are 0.9666, 1.2437, 0.2472, 0.7239, 1.4026, and 0.6868. (3) When multisource indices are added to the national dataset, the loss of the DEFNN + increases to 0.4212, 0.8218, 1.0331, and 0.8575. Conclusions: We propose an SA-LSTM optimization model with good accuracy and generalizability based on the concept of multiple methods and multiple data fusion. DEFNN enriches and supplements infectious disease prediction methodologies, can serve as a new benchmark for future infectious disease predictions and provides a reference for the prediction of the incidence rates of various infectious diseases. [ABSTRACT FROM AUTHOR]

In 2023, Katalin Karikó and Drew Weissman were awarded the Nobel Prize in Physiology or Medicine for their nucleoside base modifications research that later enabled mRNA vaccine development against COVID-19. This paper briefly reviews these achievements in the context of the development of mRNA technology and its enormous potential for medicine in the prevention of various infectious diseases and cancer treatment, including personalised therapies. It is beyond any doubt that discoveries made by Karikó and Weissman were pivotal in overcoming one of the major hurdles in the practical application of mRNA molecules, i.e., the recognition of exogenous mRNAs by endosomal Toll-like receptors and downstream innate immune response, ultimately leading to the decreased translational activity of delivered mRNA and its degradation. Although the Nobel Prize for Karikó and Weissman is fully justified, it must be stressed that mRNA technology would never unfold its potential for public health without a collective scientific effort encompassing over 40 years of research. [ABSTRACT FROM AUTHOR]

Microfluidic paper-based analytical devices (µPADs) have become promising tools offering various analytical applications for chemical and biological assays at the point-of-care (POC). Compared to traditional microfluidic devices, µPADs offer notable advantages; they are cost-effective, easily fabricated, disposable, and portable. Because of our better understanding and advanced engineering of µPADs, multistep assays, high detection sensitivity, and rapid result readout have become possible, and recently developed µPADs have gained extensive interest in parallel analyses to detect biomarkers of interest. In this review, we focus on recent developments in order to achieve µPADs with high-throughput capability. We discuss existing fabrication techniques and designs, and we introduce and discuss current detection methods and their applications to multiplexed detection assays in relation to clinical diagnosis, drug analysis and screening, environmental monitoring, and food and beverage quality control. A summary with future perspectives for µPADs is also presented. [ABSTRACT FROM AUTHOR]

Infectious diseases are a cause of humanitarian and economic crises across the world. In developing regions, a severe epidemic can result in the collapse of healthcare infrastructure or even the failure of an affected state. The most recent 2013–2015 outbreak of Ebola virus disease in West Africa is an example of such an epidemic. The economic, infrastructural, and human costs of this outbreak provide strong motivation for the examination of adaptive treatment strategies that allocate resources in response to and anticipation of the evolution of an epidemic. We formalize adaptive management of an emerging infectious disease spreading across a set of locations as a treatment regime that maps up-to-date information on the epidemic to a subset of locations identified as high-priority for treatment. An optimal treatment regime in this context is defined as maximizing the expectation of a pre-specified cumulative utility measure, e.g., the number of disease-free individuals or the estimated reduction in morbidity or mortality relative to a baseline intervention strategy. Because the disease dynamics are not known at the beginning of an outbreak, an optimal treatment regime must be estimated online, i.e., as data accumulate; thus, an effective estimation algorithm must balance choosing interventions that lead to information gain and thereby model improvement with interventions that appear to be optimal under the current estimated model. We develop a novel model-free algorithm for the online management of an infectious disease spreading over a finite set of locations and an indefinite or infinite time horizon. The proposed algorithm balances exploration and exploitation using a semi-parametric variant of Thompson sampling. We also introduce a graph neural network-based estimator in order to improve the performance of this class of algorithms. Simulations, including those mimicking the spread of the 2013–2015 Ebola outbreak, suggest that an adaptive treatment strategy has the potential to significantly reduce mortality relative to ad hoc management strategies. Supplementary materials accompanying this paper appear online. [ABSTRACT FROM AUTHOR]

This study investigates the narratives surrounding COVID-19 in Nsukka, Enugu State, Nigeria. It assesses whether the narratives contained knowledge about the relationship between capitalist accumulation and expansion (CAnE) and the spread of COVID-19. Political ecologists argue that CAnE is associated with the spread of infectious zoonotic diseases like COVID-19. While studies on COVID-19 are growing, there has yet to be an exploration of ordinary people's knowledge of the relationship between CAnE and COVID-19 spread, especially in Africa. Thus, this paper examines the narratives of COVID-19 in Nsukka to see whether they contain information about how COVID-19 spreads through CAnE. The findings revealed a significant evolution in the narratives of COVID-19 in Nsukka over time, reflecting changing perceptions and attitudes within the community. At the pandemic's start, the dominant narratives centred around religious interpretations and scepticism about the virus's reality. However, these initial religious and sceptical narratives gradually gave way to a different perspective, termed spatial othering, as the pandemic continued, suggesting that while acknowledging the virus as real, they believed it could not thrive in Nsukka or Nigeria. This shift was accompanied by the belief that the virus did not originate in the region and thus lacked agency to thrive there. The official government narrative, as observed in public health messages, primarily focused on hygiene and sanitation measures to curb the spread of the virus. Thus, it argues that political ecology knowledge about the pandemic is not acknowledged or endorsed in the ordinary people and government narratives, highlighting the need for diversified sources of knowledge, including non-conventional forms, to reach and educate local communities effectively. Hence, the central argument in the study is that even though CAnE can contribute to the spread of infectious diseases like COVID-19 as formulated by political ecologists; this idea is absent in the narratives surrounding the pandemic in Nsukka. Whilst not discounting other sources of the pandemics and alternative perspectives, the study called for resistance against practices associated with capitalist expansion, highlighting the role of education in raising awareness, resistance and activism to address the vulnerabilities associated with capitalist expansion in the context of public health crises. [ABSTRACT FROM AUTHOR]

Introduction: Social media have become one of the leading health communication channels among the exponents of Health 2.0. Twitter has particularly noteworthy features for providing information quickly and easily. However, there is still controversy about the convenience of its use. Objectives: This paper aims to identify the main topics of health covered, the uses of Twitter in health communication and to characterize the valences (positive and negative) associated with each use. Methodology: To do that, we conducted a systematic review following PRISMA guidelines. Two databases (Web of Science and Pubmed) were searched, and 610 articles were retrieved. After removing duplicates, screening the titles and abstracts and assessing the full texts, 83 papers met the inclusion criteria. Results: The review identified five uses of Twitter: Conversation, Engagement, Information, Prevention, and Awareness, and it established the definitions of the positive and negative valences associated with each use. The most common uses found were Conversation and Engagement. Likewise, the two areas most studied were Public Health and Infectious Diseases. Conclusion: There is no consensus on the usefulness of Twitter as a tool for information or for generating debate, although the platform's effectiveness for measuring the impact of health campaigns was highlighted. [ABSTRACT FROM AUTHOR]

Nicola Low and colleagues announce a call for research papers on sexually transmitted infections, to accompany a Collection on the topic. [ABSTRACT FROM AUTHOR]

The last year saw intensive efforts to advance knowledge in pediatric medicine. This review highlights important publications that have been issued in the Italian Journal of Pediatrics in 2022. We have chosen papers in the fields of allergy, anesthesiology, cardiology, dermatology, endocrinology, gastroenterology, genetics, global health, infectious diseases, metabolism, neonatology, neurology, oncology, pulmonology. Novel valuable developments in epidemiology, pathophysiology, prevention, diagnosis and treatment that can rapidly change the approach to diseases in childhood have been included and discussed. [ABSTRACT FROM AUTHOR]

Valid and relevant models are critical for research to have biological relevance or to proceed in the right path. As well-established two-dimensional cell cultures lack niches and cues and rodent models differ in species, three-dimensional organoids emerged as a powerful platform for research. Cultured in vitro from stem cells, organoids are heterogeneous in cells and closely resemble the in vivo settings. Organoids also recapitulate the unique human features if cultured from a human source and are subjected to genetic modification. However, one type of organoid possesses only a limited selection of cells. In particular, the absence of vasculature and immune cells restricts the organoids from nutrition, cues, or critical interactions, undermining the validity of organoids as physiological or pathological models. To fill the current gap, there is an urgent need to provide organoids with vasculature and immune cells. In this paper, we review the methods to generate physiological and pathological organoid models and summarize ways to vascularize or immunize them. Our discussion continues with some advantages and disadvantages of each method and some emerging solutions to current problems. [ABSTRACT FROM AUTHOR]

In this paper, we propose a Susceptible–Infected–Removal (SIR) model with time fused coefficients. In particular, our proposed model discovers the underlying time homogeneity pattern for the SIR model's transmission rate and removal rate via Bayesian shrinkage priors. MCMC sampling for the proposed method is facilitated by the nimble package in R. Extensive simulation studies are carried out to examine the empirical performance of the proposed methods. We further apply the proposed methodology to analyze different levels of COVID-19 data in the United States. [ABSTRACT FROM AUTHOR]

Hematogenous osteomyelitis caused by Streptococcus intermedius is rare, particularly in immunocompetent adults. The aim of this paper is to provide an overview of the clinical presentation, prognosis as well as treatment of this disease, with the focus on immunocompetent adults. Six medical literature libraries were searched to identify studies reporting on Streptococcus intermedius induced hematogenous osteomyelitis in immunocompetent adults. In addition, we presented a case of a 44-year-old man from our institution that is illustrative for this disease. Four case reports describing four patients were identified by this systematic literature review. Hence, the data of five patients (including our case) were assessed. The most common presenting symptom was localised pain, followed by fever. Portal entries were found in two patients (general periodontitis and necrotic dentition). The localisations of osteomyelitis were diverse: femoral (two patients), lumbar spine (two patients), and the iliac bone (one patient). Treatment strategies varied strongly, but antibiotics (penicillins) were administered in each case, and two patients underwent surgical debridement. Follow-up ranged from 2 weeks to more than 6 months; one patient died from septic shock. Only a very limited number of immunocompetent adults with Streptococcus intermedius induced hematogenous osteomyelitis have been described. Based on the available data, we summarised the clinical presentation, prognosis as well as treatment of hematogenous osteomyelitis caused by Streptococcus intermedius in this patient population. [ABSTRACT FROM AUTHOR]

In recent decades, many infectious diseases have appeared that have negatively affected life in general and people in particular, causing many economic and human losses. Recently, many attempts have emerged to confront these diseases using computer-based technology for diagnosis, prediction, and data analysis using various techniques, the most important of which is deep learning. Previous research relied primarily on a set of images taken from the patient's body while he was in a healthcare facility, and this is the main weakness of these studies. Not all people go to a doctor or hospital when they feel the symptoms of a disease. Hence, people moving in crowded places without knowing their health status can contribute to spreading infectious diseases quickly, and this is the issue that should be confronted. Therefore, this paper presents a people-monitoring scheme, which is based on the internet of things (IoT) technology, to predict infectious disease symptoms through people's behavior as well as through a wireless body area network (WBAN). This scheme can predict the spread of disease by tracking the movements of infected persons. Additionally, a simple methodology for processing the data extracted from the monitoring process across a range of different computing centers is introduced. Moreover, to ensure the monitoring scheme operates in real-time, it was necessary to provide a powerful coverage model for its objects. Also, a simple COVID-19 case study is presented. Finally, the performance of the prediction model is measured using images, sounds and videos files. Furthermore, the performance of the data computing and coverage methodologies is measured using an intensive simulation environment for the IoT that was constructed using NS3 package. The results showed that the proposed scheme is able to predict the symptoms of disease and its spread with accepted level of accuracy. In addition, using a mixture of coverage tools and computing techniques is recommended. [ABSTRACT FROM AUTHOR]

Artificial neural networks (ANNs) ability to learn, correct errors, and transform a large amount of raw data into beneficial medical decisions for treatment and care has increased in popularity for enhanced patient safety and quality of care. Therefore, this paper reviews the critical role of ANNs in providing valuable insights for patients' healthcare decisions and efficient disease diagnosis. We study different types of ANNs in the existing literature that advance ANNs' adaptation for complex applications. Specifically, we investigate ANNs' advances for predicting viral, cancer, skin, and COVID-19 diseases. Furthermore, we propose a deep convolutional neural network (CNN) model called ConXNet, based on chest radiography images, to improve the detection accuracy of COVID-19 disease. ConXNet is trained and tested using a chest radiography image dataset obtained from Kaggle, achieving more than 97% accuracy and 98% precision, which is better than other existing state-of-the-art models, such as DeTraC, U-Net, COVID MTNet, and COVID-Net, having 93.1%, 94.10%, 84.76%, and 90% accuracy and 94%, 95%, 85%, and 92% precision, respectively. The results show that the ConXNet model performed significantly well for a relatively large dataset compared with the aforementioned models. Moreover, the ConXNet model reduces the time complexity by using dropout layers and batch normalization techniques. Finally, we highlight future research directions and challenges, such as the complexity of the algorithms, insufficient available data, privacy and security, and integration of biosensing with ANNs. These research directions require considerable attention for improving the scope of ANNs for medical diagnostic and treatment applications. [ABSTRACT FROM AUTHOR]

There is a complex inter-relationship between nutrition and morbidity in human health. Many diseases reduce nutritional status, but on the other hand, having low nutritional status is also known to make individuals more susceptible to certain diseases and to more serious illness. Modern evidence on these relationships, determined after the introduction of antibiotics and vaccines, may not be applicable to historical settings before these medical technologies were available. This paper uses a historical cohort study based on records from the London Foundling Hospital to determine the causal effect of nutritional status of children, proxied by weight- and height-for-age Z-scores, on the odds of contracting five infectious diseases of childhood (measles, mumps, rubella, chicken pox and whooping cough) and on sickness duration from these diseases. I identify a causal effect by exploiting the randomisation of environmental conditions as foundling children were removed from their original homes, then fostered with families in counties nearby London and later returned to the Foundling Hospital's main site in London. I find no effect of nutritional status on the odds of contracting the five diseases, but I do find a historically important and statistically significant effect of nutritional status on sickness duration for measles and mumps. These findings have three implications. First, historical incidence of these diseases was unrelated to nutritional status, meaning that poor nutritional status during famines or during the Colombian Exchange did not affect the spread of epidemics. However, undernutrition in these events may have exacerbated measles severity. Second, improving nutritional status in the past 150 years would have reduced the severity of measles and mumps infections but not affect the decline in whooping cough mortality. Finally, selective culling effects from measles would be larger than those from whooping cough since whooping cough severity was not correlated with underlying nutritional status. [ABSTRACT FROM AUTHOR]

Simple Summary: In a fast-changing world, it is highly important to consider the possible consequences of human-driven effects that can alter natural ecosystems. In this review, we built a framework focused on risk factors associated with new wildlife diseases, such as immune system suppression, pathogen transmission between different animal species (also called "spillover"), and disease spread. Our conceptual framework describes major potential interactions between humans and nature that might occur in coupled human and natural systems, those systems where humans and wildlife are tightly linked, conceptually and geographically. Such interactions consist of certain anthropogenic effects (such as pollution, climate change, unsustainable farming, and more) which we distributed across our conceptual framework to identify their relevance to the wildlife infectious disease risk factors that this manuscript examines. Our developed framework can be applied to many new wildlife diseases, and we provide an application example with an emerging tumoral disease of marine turtles, called Fibropapillomatosis. Our work shows how crucial it is to analyze conservation issues beyond what is immediately apparent, and for science to operate through research collaboration and synergy. Emerging infectious diseases of wildlife have markedly increased in the last few decades. Unsustainable, continuous, and rapid alterations within and between coupled human and natural systems have significantly disrupted wildlife disease dynamics. Direct and indirect anthropogenic effects, such as climate change, pollution, encroachment, urbanization, travel, and trade, can promote outbreaks of infectious diseases in wildlife. We constructed a coupled human and natural systems framework identifying three main wildlife disease risk factors behind these anthropogenic effects: (i) immune suppression, (ii) viral spillover, and (iii) disease propagation. Through complex and convoluted dynamics, each of the anthropogenic effects and activities listed in our framework can lead, to some extent, to one or more of the identified risk factors accelerating disease outbreaks in wildlife. In this review, we present a novel framework to study anthropogenic effects within coupled human and natural systems that facilitate the emergence of infectious disease involving wildlife. We demonstrate the utility of the framework by applying it to Fibropapillomatosis disease of marine turtles. We aim to articulate the intricate and complex nature of anthropogenically exacerbated wildlife infectious diseases as multifactorial. This paper supports the adoption of a One Health approach and invites the integration of multiple disciplines for the achievement of effective and long-lasting conservation and the mitigation of wildlife emerging diseases. [ABSTRACT FROM AUTHOR]

Disease outbreaks can severely disrupt the global tourism sector. New approaches for preventing infectious diseases from emerging and spreading are urgently needed to secure the prosperity of the tourism industry. This conceptual article proposes a comprehensive framework of interrelationships between tourism and emerging infectious disease. The conceptual framework highlights the pathways in which the tourism industry itself can potentially contribute to the emergence and spread of infectious diseases, including tourism-induced land changes, sourcing meat from intensive animal farms, global movement and close proximity of people, and high-risk sexual activities. Based on the interrelationships, the framework proposes tangible managerial action recommendations for tourism businesses and policy makers to contribute to the prevention of future disease outbreaks. This paper concludes with a research agenda on how scholars can support tourism practitioners and governments in reducing the likelihood of future epidemics and pandemics. [ABSTRACT FROM AUTHOR]

Most biological processes take time to occur. In infectious diseases, such as malaria or chikungunya, there is a period of time between when a susceptible individual gets bitten by the vector, and when the individual develops the disease. These times are commonly modeled by introducing delays or by adding exposed as a new population class. Given a model based on differential equations, delays can be introduced in different forms. In this paper, we study different ways of introducing the delays and, alternatively, using exposed populations. We also analyze their steady solutions and stability, and establish the conditions under which the studied models predict an epidemic. Results and conclusions are presented. [ABSTRACT FROM AUTHOR]

Background: As health systems struggle to tackle the spread of Covid-19, resilience becomes an especially relevant attribute and research topic. More than strength or preparedness, to perform resiliently to emerging shocks, health systems must develop specific abilities that aim to increase their potential to adapt to extraordinary situations while maintaining their regular functioning. Brazil has been one of the most affected countries during the pandemic. In January 2021, the Amazonas state's health system collapsed, especially in the city of Manaus, where acute Covid-19 patients died due to scarcity of medical supplies for respiratory therapy. Methods: This paper explores the case of the health system's collapse in Manaus to uncover the elements that prevented the system from performing resiliently to the pandemic, by carrying out a grounded-based systems analysis of the performance of health authorities in Brazil using the Functional Resonance Analysis Method. The major source of information for this study was the reports from the congressional investigation carried out to unveil the Brazilian response to the pandemic. Results: Poor cohesion between the different levels of government disrupted essential functions for managing the pandemic. Moreover, the political agenda interfered in the abilities of the system to monitor, respond, anticipate, and learn, essential aspects of resilient performance. Conclusions: Through a systems analysis approach, this study describes the implicit strategy of "living with Covid-19", and an in-depth view of the measures that hampered the resilience of the Brazilian health system to the spread of Covid-19. [ABSTRACT FROM AUTHOR]

Infectious disease modeling plays an important role in understanding disease spreading dynamics and can be used for prevention and control. The well-known SIR (Susceptible, Infected, and Recovered) compartment model and spatial and spatio-temporal statistical models are common choices for studying problems of this kind. This paper proposes a spatio-temporal modeling framework to characterize infectious disease dynamics by integrating the SIR compartment and log-Gaussian Cox process (LGCP) models. The method's performance is assessed via simulation using a combination of real and synthetic data for a region in São Paulo, Brazil. We also apply our modeling approach to analyze COVID-19 dynamics in Cali, Colombia. The results show that our modified LGCP model, which takes advantage of information obtained from the previous SIR modeling step, leads to a better forecasting performance than equivalent models that do not do that. Finally, the proposed method also allows the incorporation of age-stratified contact information, which provides valuable decision-making insights. [ABSTRACT FROM AUTHOR]

The quarantine strategy plays a crucial role in the prevention and control of infectious disease. In this paper, a two-layer network model coupling the transmission of infectious diseases and the dynamics of human behavior based on game theory is proposed. The basic reproduction number of the infectious disease in our proposed model is obtained by the next-generation matrix method and the stability of the disease-free equilibrium is analyzed. Theoretical results show that the spread of infectious diseases can be controlled when the voluntary quarantined individuals reach a certain proportion. The sensitivities of the parameters are analyzed by simulations, and the results show that increasing propaganda can directly accelerate quarantine, and reducing the relative cost of quarantine has a significant effect on preventing the infectious diseases. Increasing the detection rate will lead to overestimating the proportion of undiagnosed infected individuals, and can also promote individuals to quarantine. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to evaluate the response of pilgrims at Almadinah Almunawwarah Airport toward knowledge of preventive measures on respiratory infectious diseases, and to study the factors affecting the response of pilgrims to prevent infectious diseases such as SARS. Materials and Methods: This study was conducted at Almadinah Almunawwarah airport in the Kingdom of Saudi Arabia. Pilgrims who arrived at the city airport of Almadinah Almunawwarah (during the pilgrimage season in 2019) were invited to participate in this study. The tool used to collect data was a paper-based questionnaire. Results: The respondents' mean age was 39.8 years with a range of 18 to >50 years and a median age of 35-50 years. The findings indicated that 82.8% of the study participants reported overcrowding could increase the risk of infections. In addition, 67.4% of them agreed that cardiovascular and heat-related illnesses are major causes of death in travelers to the Hajj. With regards to attitudes about 70% agreed that visiting a physician before travel is essential whereas 73.7% of them agreed that personal hygiene protects them from many diseases. Conclusion: The current study shows that knowledge, attitudes, and practices toward preventive measures against respiratory infectious diseases, such as SARS, among pilgrims, are generally less acceptable if contrasted with their ways toward preventive procedures. [ABSTRACT FROM AUTHOR]

The use of internet-based query data offers a novel approach to improve disease surveillance and provides timely disease information. This paper systematically reviewed the literature on infectious disease predictions using internet-based query data and climate factors, discussed the current research progress and challenges, and provided some recommendations for future studies. We searched the relevant articles in the PubMed, Scopus, and Web of Science databases between January 2000 and December 2019. We initially included studies that used internet-based query data to predict infectious disease epidemics, then we further filtered and appraised the studies that used both internet-based query data and climate factors. In total, 129 relevant papers were included in the review. The results showed that most studies used a simple descriptive approach (n=80; 62%) to detect epidemics of influenza (including influenza-like illness (ILI)) (n=88; 68%) and dengue (n=9; 7%). Most studies (n=61; 47%) purely used internet search metrics to predict the epidemics of infectious diseases, while only 3 out of the 129 papers included both climate variables and internet-based query data. Our research shows that including internet-based query data and climate variables could better predict climate-sensitive infectious disease epidemics; however, this method has not been widely used to date. Moreover, previous studies did not sufficiently consider the spatiotemporal uncertainty of infectious diseases. Our review suggests that further research should use both internet-based query and climate data to develop predictive models for climate-sensitive infectious diseases based on spatiotemporal models. [ABSTRACT FROM AUTHOR]

Understanding people's concepts of illness and health is key to crafting policies and communications campaigns to address a particular medical concern. This paper gathers cultural knowledge on infectious disease causation, prevention, and treatment the Philippines that are particularly relevant for the COVID-19 pandemic, and analyzes their implications for public health. This paper draws from ethnographic work (e.g. participant observation, interviews, conversations, virtual ethnography) carried out individually by each of the two authors from February to September 2020. The data was analyzed in relation to the anthropological literature on local health knowledge in the Philippines. We find that notions of hawa (contagion) and resistensiya (immunity) inform people's views of illness causation as well as their preventive practices - including the use of face masks and 'vitamins' and other pharmaceuticals, as well as the ways in which they negotiate prescriptions of face mask use and physical distancing. These perceptions and practices go beyond biomedical knowledge and are continuously being shaped by people's everyday experiences and circulations of knowledge in traditional and social media. Our study reveals that people's novel practices reflect recurrent, familiar, and long-held concepts - such as the moral undertones of hawa and experimentation inherent in resistensiya. Policies and communications efforts should acknowledge and anticipate how these notions may serve as either barriers or facilitators to participatory care and improved health outcomes. [ABSTRACT FROM AUTHOR]

World Health Organization (WHO) says since the 1970s, few new infectious diseases have almost quadrupled in developing countries. As per the WHO estimation, around 1.3 billion poor people across the globe are directly suffering from povertyrelated infectious diseases including Malaria, Diarrhoea, HIV, Tuberculosis, Dengue, etc. Deprivation, poverty, lack of quality medical care, social exclusion, etc lead to poverty-related infectious diseases. The major aim of the study is to shed light on the significance of social sciences research on infectious diseases of poverty. This paper is based on a review of various literature and other valid sources. The study indicates the connection between infectious diseases and poverty is dynamic and multifaceted. Underserved, marginalized, and socially excluded groups are mainly at greater risk due to their sub-optimal socio-economic status and unscientific health care behavior. Hence, social research on infectious diseases of poverty is needed for the hour. This paper concludes that the conversions of social research into needy health policies and a better concentration on the ground requirement in resource-poor settings are essential. Urgent ground research is required to reveal how poverty is shaped and reshaped, in different cultural settings, and structurally persistent causing different fatal diseases among the most excluded communities. [ABSTRACT FROM AUTHOR]

At the moment, the shortcomings in the system of responding to crises in the health sector lie in the imperfection of the response order and management mechanisms. The purpose of the paper is to investigate the legal regulation and reflection of public health emergencies in China, as exemplified by the case of 2019 coronavirus. The paper discusses the legal framework for the regulation of emergency situations in public health in China for the period from the end of 2019. The importance of preventing and controlling the epidemic is substantiated, and shortcomings in the work to combat the epidemic are analysed. Particular attention is paid to issues of informing the public and the rule of law in emergency situations in public health. The provisions of the legislation of the People's Republic of China in public health emergencies were also examined. The paper is of practical importance not only for China, but for the entire world in the prevention and control of coronavirus. [ABSTRACT FROM AUTHOR]

Background: Despite an abundance of information on the risk factors of SARS-CoV-2, there have been few US-wide studies of long-term effects. In this paper we analyzed a large medical claims database of US based individuals to identify common long-term effects as well as their associations with various social and medical risk factors. Methods: The medical claims database was obtained from a prominent US based claims data processing company, namely Change Healthcare. In addition to the claims data, the dataset also consisted of various social determinants of health such as race, income, education level and veteran status of the individuals. A self-controlled cohort design (SCCD) observational study was performed to identify ICD-10 codes whose proportion was significantly increased in the outcome period compared to the control period to identify significant long-term effects. A logistic regression-based association analysis was then performed between identified long-term effects and social determinants of health. Results: Among the over 1.37 million COVID patients in our datasets we found 36 out of 1724 3-digit ICD-10 codes to be statistically significantly increased in the post-COVID period (p-value < 0.05). We also found one combination of ICD-10 codes, corresponding to ‘other anemias’ and ‘hypertension’, that was statistically significantly increased in the post-COVID period (p-value < 0.05). Our logistic regression-based association analysis with social determinants of health variables, after adjusting for comorbidities and prior conditions, showed that age and gender were significantly associated with the multiple long-term effects. Race was only associated with ‘other sepsis’, income was only associated with ‘Alopecia areata’ (autoimmune disease causing hair loss), while education level was only associated with ‘Maternal infectious and parasitic diseases’ (p-value < 0.05). Conclusion: We identified several long-term effects of SARS-CoV-2 through a self-controlled study on a cohort of over one million patients. Furthermore, we found that while age and gender are commonly associated with the long-term effects, other social determinants of health such as race, income and education levels have rare or no significant associations. [ABSTRACT FROM AUTHOR]

Flavonoids are types of natural substances with phenolic structures isolated from a variety of plants. Flavonoids have antioxidant, anti-inflammatory, anticancer, and antiviral activities. Although most of the research or applications of flavonoids are focused on human diseases, flavonoids also show potential applicability against porcine virus infection. This review focuses on the recent progress in antiviral mechanisms of potential flavonoids against the most common porcine viruses. The mechanism discussed in this paper may provide a theoretical basis for drug screening and application of natural flavonoid compounds and flavonoid-containing herbs to control porcine virus infection and guide the research and development of pig feed additives. [ABSTRACT FROM AUTHOR]