The challenge of emerging and re-emerging infectious diseases

Evolution and regulation of microbial secondary metabolism

Microbes have disproportionate impacts on the macroscopic world. This is in part due to their ability to grow to large populations that collectively secrete massive amounts of secondary metabolites and alter their environment. Yet, the conditions favoring secondary metabolism despite the potential costs for primary metabolism remain unclear. Here we investigated the biosurfactants that the bacterium Pseudomonas aeruginosa makes and secretes to decrease the surface tension of surrounding liquid. Using a combination of genomics, metabolomics, transcriptomics, and mathematical modeling we show that the ability to make surfactants from glycerol varies inconsistently across the phylogenetic tree; instead, lineages that lost this ability are also worse at reducing the oxidative stress of primary metabolism on glycerol. Experiments with different carbon sources support a link with oxidative stress that explains the inconsistent distribution across the P. aeruginosa phylogeny and suggests a general principle: P. aeruginosa lineages produce surfactants if they can reduce the oxidative stress produced by primary metabolism and have excess resources, beyond their primary needs, to afford secondary metabolism. These results add a new layer to the regulation of a secondary metabolite unessential for primary metabolism but important to change physical properties of the environments surrounding bacterial populations.

Spatial effects of air pollution on the economic burden of disease: implications of health and environment crisis in a post-COVID-19 world

Background

Air pollution has been identified as related to the diseases of susceptible population, but the spatial heterogeneity of its economic burden and its determinants are rarely investigated. The issue is of great policy significance, especially after the epidemic of COVID-19, when human are facing the joint crisis of health and environment, and some areas is prone to falling into poverty.

Methods

The geographical detector was adopted to study the spatial distribution characteristics of the incidence of catastrophic health expenditure (ICHE) for older adults in 100 rural areas in China at the prefecture-city level. The health factors, sociological factors, policy factors and environmental factors and their interactions are identified.

Results

First, most health service factors had strong explanatory power for ICHE whether it interacts with air pollution. Second, 50 single-factor high-risk areas of ICHE were found in the study, but at the same time, there were 21 areas dominated by multiple factors.

Conclusion

The different contributions and synergy among the factors constitute the complex mechanism of factors and catastrophic health expenditure. Moreover, during this process, air pollution aggravates the contribution of health service factors toward ICHE. In addition, the leading factors of ICHE are different among regions. At the end, this paper also puts forward some policy suggestions from the perspective of health and environment crisis in the post-COVID-19 world: environmental protection policies should be combined with the prevention of infectious diseases; advanced health investment is the most cost-effective policy for the inverse health sequences of air pollution and infectious diseases such as coronavirus disease 2019 (COVID-19); integrating environmental protection policy into healthy development policy, different regions take targeted measures to cope with the intertwined crisis.

Compact Camera Fluorescence Detector for Parallel-Light Lens-Based Real-Time PCR System

The polymerase chain reaction is an important technique in biological research. However, it is time consuming and has a number of disadvantages. Therefore, real-time PCR technology that can be used in real-time monitoring has emerged, and many studies are being conducted regarding its use. Real-time PCR requires many optical components and imaging devices such as expensive, high-performance cameras. Therefore, its cost and assembly process are limitations to its use. Currently, due to the development of smart camera devices, small, inexpensive cameras and various lenses are being developed. In this paper, we present a Compact Camera Fluorescence Detector for use in parallel-light lens-based real-time PCR devices. The proposed system has a simple optical structure, the system cost can be reduced, and the size can be miniaturized. This system only incorporates Fresnel lenses without additional optics in order for the same field of view to be achieved for 25 tubes. In the center of the Fresnel lens, one LED and a complementary metal-oxide semiconductor camera were placed in directions that were as similar as possible. In addition, to achieve the accurate analysis of the results, image processing was used to correct them. As a result of an experiment using a reference fluorescent substance and double-distilled water, it was confirmed that stable fluorescence detection was possible.

Loop-Mediated Isothermal Amplification-Based Microfluidic Platforms for the Detection of Viral Infections

Purpose of Review

Easy-to-use, fast, and accurate virus detection method is essential for patient management and epidemic surveillance, especially during severe pandemics. Loop-mediated isothermal amplification (LAMP) on a microfluidic platform is suitable for detecting infectious viruses, regardless of the availability of medical resources. The purpose of this review is to introduce LAMP-based microfluidic devices for virus detection, including their detection principles, methods, and application.

Recent Findings

Facing the uncontrolled spread of viruses, the large-scale deployment of LAMP-based microfluidic platforms at the grassroots level can help expand the coverage of nucleic acid testing and shorten the time to obtain test reports. Microfluidic chip technology is highly integrated and miniaturized, enabling precise fluid control for effective virus detection. Performing LAMP on miniaturized systems can reduce analysis time, reagent consumption and risk of sample contamination, and improve analytical performance.

Summary

Compared to traditional benchtop protocols, LAMP-based microfluidic devices reduce the testing time, reagent consumption, and the risk of sample contamination. In addition to simultaneous detection of multiple target genes by special channel design, microfluidic chips can also integrate digital LAMP to achieve absolute quantification of target genes.

Potential Application of Exosomes in Vaccine Development and Delivery

Exosomes are cell-derived components composed of proteins, lipid, genetic information, cytokines, and growth factors. They play a vital role in immune modulation, cell-cell communication, and response to inflammation. Immune modulation has downstream effects on the regeneration of damaged tissue, promoting survival and repair of damaged resident cells, and promoting the tumor microenvironment via growth factors, antigens, and signaling molecules. On top of carrying biological messengers like mRNAs, miRNAs, fragmented DNA, disease antigens, and proteins, exosomes modulate internal cell environments that promote downstream cell signaling pathways to facilitate different disease progression and induce anti-tumoral effects. In this review, we have summarized how vaccines modulate our immune response in the context of cancer and infectious diseases and the potential of exosomes as vaccine delivery vehicles. Both pre-clinical and clinical studies show that exosomes play a decisive role in processes like angiogenesis, prognosis, tumor growth metastasis, stromal cell activation, intercellular communication, maintaining cellular and systematic homeostasis, and antigen-specific T- and B cell responses. This critical review summarizes the advancement of exosome based vaccine development and delivery, and this comprehensive review can be used as a valuable reference for the broader delivery science community.

The impact of positive and negative information on SIR-like epidemics in delayed multiplex networks

In order to better study the interaction between epidemic propagation and information diffusion, a new coupling model on multiplex networks with time delay is put forward in this paper. One layer represents the information diffusion about epidemics. There is not only information about the positive prevention of infectious diseases but also negative preventive information. Meanwhile, the dissemination of information at this layer will be influenced by the mass media, which can convey positive and reliable preventive measures to help the public avoid exposure to contagion. The other layer represents the transmission of infectious diseases, and the public in this layer no longer only exchange information related to infectious diseases in the virtual social network like the information layer but spread infectious diseases through contact among people. The classical SIR model is used to model for epidemic propagation. Since each infected individual needs to spend enough time to recover, the infected one at one time does not necessarily change to the recovered one at the next time, so time delay is an essential factor to be considered in the model. Based on the microscopic Markov chain approach, this paper obtains an explicit expression for epidemic threshold in the two-layered multiplex networks with time delay, which reveals some main factors affecting epidemic threshold. In particular, the time delay has a noticeable effect on the epidemic threshold to some extent. Finally, the influence of these main factors on the epidemic threshold and their interaction are proved through numerical simulations.

Copper-thiosemicarbazone complexes conjugated-cellulose fibers: Biodegradable materials with antibacterial capacity

Personal protective equipment (PPE) is vital in battling bacteria crisis, but conventional PPE materials lack antimicrobial activities and environmental friendliness. Our work focused on developing biodegradable and antibacterial fibers as promising bioprotective materials. Here, we grafted highly effective antibacterial copper-thiosemicarbazone complexes (CT1-4) on cellulose fibers via covalent linkages. Multiple methods were used to characterize the chemical composition or morphology of CT1-4 conjugated-fibers. Conjugation of CT1-4 maintains the mechanical properties (Breaking strength: 2.35-2.45 cN/dtex, Breaking elongation: 7.19 %-7.42 %) and thermal stability of fibers. CT1 can endow cellulose fibers with the excellent growth inhibition towards Escherichia coli (E. coli) (GIR: 61.5 % ± 1.28 %), Staphylococcus aureus (S. aureus) (GIR: 85.7 % ± 1.93 %), and Bacillus subtilis (B. subtilis) (GIR: 87.6 % ± 1.44 %). We believe that the application of CT1 conjugated-cellulose fibers is not limited to the high-performance PPE, and also can be extended to various types of protective equipment for food and medicine safety.

Association between antibiotics and dementia risk: A retrospective cohort study

Background: The possible relation between antibiotic exposure and the alteration of gut microbiota, which may affect dementia risk, has been revealed. However, the association between antibiotics and dementia incidence has rarely been studied. We aimed to determine the association between antibiotic exposure and the risk of dementia.

Methods: This population-based retrospective cohort study used data from the National Health Insurance Service-Health Screening Cohort (NHIS-HEALS) in South Korea. Exposure was the cumulative days of antibiotic prescription from 2002 to 2005. Newly diagnosed overall dementia, Alzheimer’s disease (AD), and vascular dementia (VD) were identified based on diagnostic codes and prescriptions for dementia-related drugs. The follow-up investigation was carried out from 1 January 2006 to 31 December 2013. The Cox proportional hazards regression was used to assess the association between cumulative antibiotic prescription days and dementia incidence.

Results: A total of 313,161 participants were analyzed in this study. Compared to antibiotic non-users, the participants who used antibiotics for 91 or more days had an increased risk of overall dementia [adjusted hazard ratio (aHR), 1.44; 95% confidence interval (CI), 1.19–1.74], AD (aHR, 1.46; 95% CI, 1.17–1.81), and VD (aHR, 1.38; 95% CI, 0.83–2.30). Those who used five or more antibiotic classes had higher risks of overall dementia (aHR, 1.28; 95% CI, 1.00–1.66) and AD (aHR, 1.34; 95% CI, 1.00–1.78) than antibiotic non-users.

Conclusion: Antibiotic exposure may increase the risk of dementia in a cumulative duration-dependent manner among adult participants. Future studies are needed to assess the causality between the long-term prescription of antibiotics and dementia risk.

Passive epidemiological surveillance in wildlife in Costa Rica identifies pathogens of zoonotic and conservation importance

Epidemiological surveillance systems for pathogens in wild species have been proposed as a preventive measure for epidemic events. These systems can minimize the detrimental effects of an outbreak, but most importantly, passive surveillance systems are the best adapted to countries with limited resources. Therefore, this research aimed to evaluate the technical and infrastructural feasibility of establishing this type of scheme in Costa Rica by implementing a pilot program targeting the detection of pathogens of zoonotic and conservation importance in wildlife. Between 2018 and 2020, 85 carcasses of free-ranging vertebrates were admitted for post-mortem and microbiology analysis. However, we encountered obstacles mainly related to the initial identification of cases and limited local logistics capacity. Nevertheless, this epidemiological surveillance scheme allowed us to estimate the general state of health of the country’s wildlife by establishing the causes of death according to pathological findings. For instance, 60% (51/85) of the deaths were not directly associated with an infectious agent. Though in 37.6% (32/85) of these cases an infectious agent associated or not with disease was detected. In 27.1% (23/85) of the cases, death was directly related to infectious agents. Furthermore, 12.9% (11/85), the cause of death was not determined. Likewise, this wildlife health monitoring program allowed the detection of relevant pathogens such as Canine Distemper Virus, Klebsiella pneumoniae, Angiostrongylus spp., Baylisascaris spp., among others. Our research demonstrated that this passive surveillance scheme is cost-effective and feasible in countries with limited resources. This passive surveillance can be adapted to the infrastructure dedicated to monitoring diseases in productive animals according to the scope and objectives of monitoring wildlife specific to each region. The information generated from the experience of the initial establishment of a WHMP is critical to meeting the challenges involved in developing this type of scheme in regions with limited resources and established as hotspots for emerging infectious diseases.

Lectins from plant and algae act as anti-viral against HIV, influenza and coronaviruses

BACKGROUND

Carbohydrate-lectin interactions are extremely specific as the lectin is capable of recognising monomeric and oligomeric sugars in a reversible manner. It has been known for a long time that lectins have antibacterial, antifungal, and insecticidal activities. Recently, it has been reported that many lectins can prevent the virus growth by interacting with the viral envelop surface glycoprotein. Spike protein, which is found on the surface of some enveloped viruses, is heavily mannosylated and will have strong affinity for mannose specific lectins. According to the findings, lectins have a high binding affinity for the glycans of the SARS-CoV-2 spike glycoprotein, which contains N-glycosylation sites. As a result, various lectins are being researched and developed as anti-viral agents.

RESULTS

According to our in silico studies, the amino acid residues Asn487, Tyr489, Gln493, Lys417, and Tyr505 of the receptor binding domain (RBD) of SARS-CoV-2 formed an interaction with the model lectin Lablab purpureus lectin. Similar interaction for SARS-CoV-2 spike protein was observed with Griffithsin lectin (algal source) as well. These observations demonstrate that lectins could be one of the potential molecules for neutralising coronavirus infection.

CONCLUSION

This review focuses on anti-viral lectins isolated and characterized from plants and algae (last 5 years) and showed anti-viral properties against HIV, Influenza, and coronaviruses.

Human Respiratory Infections in Nigeria: Influenza and the Emergence of SARS-CoV-2 Pandemic

The increasing outbreak of zoonotic diseases presents challenging times for nations and calls for a renewed effort to disrupt the chain of events that precede it. Nigeria's response to the 2006 bird flu provided a platform for outbreak response, yet it was not its first experience with Influenza. This study describes the impact of SARS-CoV-2 on Influenza surveillance and, conversely, while the 1918 Influenza pandemic remains the most devastating (500,000 deaths in 18 million population) in Nigeria, the emergence of SARS CoV-2 presented renewed opportunities for the development of vaccines with novel technology, co-infection studies outcome, and challenges globally. Although the public health Intervention and strategies left some positive outcomes for other viruses, Nigeria and Africa's preparation against the next pandemic may involve prioritizing a combination of technology, socioeconomic growth, and active surveillance in the spirit of One Health.

Reservoir population ecology, viral evolution and the risk of emerging infectious disease

The ecology and life history of wild animals influences their potential to harbour infectious disease. This observation has motivated studies identifying empirical relationships between traits of wild animals and historical patterns of spillover and emergence into humans. Although these studies have identified compelling broad-scale patterns, they are generally agnostic with respect to underlying mechanisms. Here, we develop mathematical models that couple reservoir population ecology with viral epidemiology and evolution to clarify existing verbal arguments and pinpoint the conditions that favour spillover and emergence. Our results support the idea that average lifespan influences the likelihood of an animal serving as a reservoir for human infectious disease. At the same time, however, our results show that the magnitude of this effect is sensitive to the rate of viral mutation. Our results also demonstrate that viral pathogens causing persistent infections or a transient immune response within the reservoir are more likely to fuel emergence. Genetically explicit stochastic simulations enrich these mathematical results by identifying relationships between the genetic basis of transmission and the risk of spillover and emergence. Together, our results clarify the scope of applicability for existing hypotheses and refine our understanding of emergence risk.

Generation and application of a novel high-throughput detection based on RPA-CRISPR technique to sensitively monitor pathogenic microorganisms in the environment

Staphylococcus aureus (S. aureus) is an important opportunistic human and animal pathogen that can cause a wide diversity of infections. Due to its environmental health risks, it is crucial to establish a time-saving, high-throughput, and highly sensitive technique for water quality surveillance. In this study, we developed a novel method to detect S. aureus in the water environment based on recombinase polymerase amplification (RPA) and CRISPR/Cas12a. This method utilizes isothermal amplification of nucleic acids and the trans-cleavage activity of the CRISPR/Cas12a system to generate fluorescence signals with a single-stranded DNA-fluorophore-quencher (ssDNA-FQ) reporter and a naked-eye detected lateral flow assay (LFA). Our RPA-CRISPR/Cas12a detection system can reduce the detection time to 35 min and enhance the high-throughput detection threshold to ≥5 copies of pathogen DNA, which is more sensitive than that of reported. Moreover, in the lower reaches of the Jialing River in Chongqing, China, 10 water samples from the mainstream and 7 ones from tributaries were successfully monitored S. aureus for less than 35 min using RPA-CRISPR/Cas12a detection system. Taken together, a novel high-throughput RPA-CRISPR detection was established and firstly applied for sensitively monitoring S. aureus in the natural water environment.

Wild Animal Migration As a Potential Threat of Introduction of New Viruses into Russia

The SARS-CoV-2 pandemic has shown how serious the problem of re-emerging zoonotic infections is for our existence. Migrations of animals, which are natural reservoirs of a particular virus, play a colossal role in the spread of pathogens to new territories. Examples are the migrations of both land animals (carnivores, rodents, and ungulates) and many marine mammals (pinnipeds and cetaceans). Yet the most interesting from the point of view of the speed and range of the spread of viral infections are migrations associated with flights. In nature, these can be migrations of insects, bats, and, of course, birds. Unfortunately, there are very few studies on the migration of these animals in Russia. Considering the problems related to climate change and other environmental factors, it is important to obtain up-to-date data on the changing animal migration routes and, as a consequence, to develop domestic equipment, particularly transmitters, to fix them.

Ecological super-spreaders drive host-range oscillations: Omicron and risk space for emerging infectious disease

The unusual genetic diversity of the Omicron strain has led to speculation about its origin. The mathematical modelling platform developed for the Stockholm Paradigm (SP) indicates strongly that it has retro-colonized humans from an unidentified nonhuman mammal, likely originally infected by humans. The relationship between Omicron and all other SARS-CoV-2 variants indicates oscillations among hosts, a core part of the SP. Such oscillations result from the emergence of novel variants following colonization of new hosts, replenishing and expanding the risk space for disease emergence. The SP predicts that pathogens colonize new hosts using pre-existing capacities. Those events are thus predictable to a certain extent. Novel variants emerge after a colonization and are not predictable. This makes it imperative to take proactive measures for anticipating emerging infectious diseases (EID) and mitigating their impact. The SP suggests a policy protocol, DAMA, to accomplish this goal. DAMA comprises: DOCUMENT to detect pathogens before they emerge in new places or colonize new hosts; ASSESS to determine risk; MONITOR to detect changes in pathogen populations that increase the risk of outbreaks and ACT to prevent outbreaks when possible and minimize their impact when they occur.

The effectiveness of COVID-19 vaccines in reducing the incidence, hospitalization, and mortality from COVID-19: A systematic review and meta-analysis

Background

Vaccination, one of the most important and effective ways of preventing infectious diseases, has recently been used to control the COVID-19 pandemic. The present meta-analysis study aimed to evaluate the effectiveness of COVID-19 vaccines in reducing the incidence, hospitalization, and mortality from COVID-19.

Methods

A systematic search was performed independently in Scopus, PubMed via Medline, ProQuest, and Google Scholar electronic databases as well as preprint servers using the keywords under study. We used random-effect models and the heterogeneity of the studies was assessed using I ² and χ² statistics. In addition, the Pooled Vaccine Effectiveness (PVE) obtained from the studies was calculated by converting based on the type of outcome.

Results

A total of 54 studies were included in this meta-analysis. The PVE against SARS-COV 2 infection were 71% [odds ratio (OR) = 0.29, 95% confidence intervals (CI): 0.23-0.36] in the first dose and 87% (OR = 0.13, 95% CI: 0.08-0.21) in the second dose. The PVE for preventing hospitalization due to COVID-19 infection was 73% (OR = 0.27, 95% CI: 0.18-0.41) in the first dose and 89% (OR = 0.11, 95% CI: 0.07-0.17) in the second dose. With regard to the type of vaccine, mRNA-1273 and combined studies in the first dose and ChAdOx1 and mRNA-1273 in the second dose had the highest effectiveness in preventing infection. Regarding the COVID-19-related mortality, PVE was 68% (HR = 0.32, 95% CI: 0.23-0.45) in the first dose and 92% (HR = 0.08, 95% CI: 0.02-0.29) in the second dose.

Conclusion

The results of this meta-analysis indicated that vaccination against COVID-19 with BNT162b2 mRNA, mRNA-1273, and ChAdOx1, and also their combination, was associated with a favorable effectiveness against SARS-CoV2 incidence rate, hospitalization, and mortality rate in the first and second doses in different populations. We suggest that to prevent the severe form of the disease in the future, and, in particular, in the coming epidemic picks, vaccination could be the best strategy to prevent the severe form of the disease.

Systematic review registration

PROSPERO International Prospective Register of Systematic Reviews: http://www.crd.york.ac.uk/PROSPERO/, identifier [CRD42021289937].

From magic bullets to modern therapeutics: Paul Ehrlich, the German immunobiologist and physician coined the term 'complement'

Paul Ehrlich was a pioneering Immunobiologist and physician who coined the term 'complement' in the year 1899. He was a leading visionary scientist who worked in the late 19th and early 20th centuries in Berlin and Frankfurt. He received numerous awards and honors for his substantial contributions to immunobiology and medicine, including the identification of complement, and he received the Nobel Prize in Physiology or Medicine in 1908 in recognition of his work on immunity. During his clinical work, Paul Ehrlich treated a patient with paroxysmal hemoglobinuria and reported his diagnostic approaches, including those related to erythrocyte lysis and microscopic cell analysis, to the Verein für Innere Medicine/Society of Internal Medicine, Berlin. Paroxysmal nocturnal hemoglobinuria was shown to be a complement-mediated disease; treatment of this disease with the complement inhibitor Eculzimab/Soliris was approved by the European Medicines Agency in 2003 and by the United States Food and Drug Administration in 2007.

Aedes aegypti and Ae. albopictus microbiome/virome: new strategies for controlling arboviral transmission?

Aedes aegypti and Aedes albopictus are the main vectors of highly pathogenic viruses for humans, such as dengue (DENV), chikungunya (CHIKV), and Zika (ZIKV), which cause febrile, hemorrhagic, and neurological diseases and remain a major threat to global public health. The high ecological plasticity, opportunistic feeding patterns, and versatility in the use of urban and natural breeding sites of these vectors have favored their dispersal and adaptation in tropical, subtropical, and even temperate zones. Due to the lack of available treatments and vaccines, mosquito population control is the most effective way to prevent arboviral diseases. Resident microorganisms play a crucial role in host fitness by preventing or enhancing its vectorial ability to transmit viral pathogens. High-throughput sequencing and metagenomic analyses have advanced our understanding of the composition and functionality of the microbiota of Aedes spp. Interestingly, shotgun metagenomics studies have established that mosquito vectors harbor a highly conserved virome composed of insect-specific viruses (ISV). Although ISVs are not infectious to vertebrates, they can alter different phases of the arboviral cycle, interfering with transmission to the human host. Therefore, this review focuses on the description of Ae. aegypti and Ae. albopictus as vectors susceptible to infection by viral pathogens, highlighting the role of the microbiota-virome in vectorial competence and its potential in control strategies for new emerging and re-emerging arboviruses.

The effect of information-driven resource allocation on the propagation of epidemic with incubation period

In the pandemic of COVID-19, there are exposed individuals who are infected but lack distinct clinical symptoms. In addition, the diffusion of related information drives aware individuals to spontaneously seek resources for protection. The special spreading characteristic and coevolution of different processes may induce unexpected spreading phenomena. Thus we construct a three-layered network framework to explore how information-driven resource allocation affects SEIS (susceptible-exposed-infected-susceptible) epidemic spreading. The analyses utilizing microscopic Markov chain approach reveal that the epidemic threshold depends on the topology structure of epidemic network and the processes of information diffusion and resource allocation. Conducting extensive Monte Carlo simulations, we find some crucial phenomena in the coevolution of information diffusion, resource allocation and epidemic spreading. Firstly, when E-state (exposed state, without symptoms) individuals are infectious, long incubation period results in more E-state individuals than I-state (infected state, with obvious symptoms) individuals. Besides, when E-state individuals have strong or weak infectious capacity, increasing incubation period has an opposite effect on epidemic propagation. Secondly, the short incubation period induces the first-order phase transition. But enhancing the efficacy of resources would convert the phase transition to a second-order type. Finally, comparing the coevolution in networks with different topologies, we find setting the epidemic layer as scale-free network can inhibit the spreading of the epidemic.

Effect of local and global information on the dynamical interplay between awareness and epidemic transmission in multiplex networks

Recent few years have witnessed a growing interest in exploring the dynamical interplay between awareness and epidemic transmission within the framework of multiplex networks. However, both local and global information have significant impacts on individual awareness and behavior, which have not been adequately characterized in the existing works. To this end, we propose a local and global information controlled spreading model to explore the dynamics of two spreading processes. In the upper layer, we construct a threshold model to describe the awareness diffusion process and introduce local and global awareness information as variables into an individual awareness ratio. In the lower layer, we adopt the classical susceptible-infected-susceptible model to represent the epidemic propagation process and introduce local and global epidemic information into individual precaution degree to reflect individual heterogeneity. Using the microscopic Markov chain approach, we theoretically derive the threshold for epidemic outbreaks. Our findings suggest that the local and global information can motivate individuals to increase self-protection awareness and take more precaution measures, thereby reducing disease infection probability and suppressing the spread of epidemics.

Zoonoses and gold mining: A cross-sectional study to assess yellow fever immunization, Q fever, leptospirosis and leishmaniasis among the population working on illegal mining camps in French Guiana

BACKGROUND

Most emerging pathogens are zoonoses and have a wildlife origin. Anthropization and disruption of ecosystems favor the crossing of inter-species barriers. We hypothesize that the marginalized population of undocumented goldminers in the Amazon is at risk of acquiring zoonoses.

METHOD

A multicentric cross-sectional study included consenting gold-mining adult workers in 2019. A clinical examination recorded dermatological signs of leishmaniosis and past history of yellow fever vaccination. Biological tests were performed for yellow fever, Q fever and leptospirosis serologies. Additional blood samples from a previous study in 2015 were also tested for leptospirosis.

RESULTS

In 2019, 380 individuals were included in the study, along with 407 samples from the 2015 biological collection. The seroprevalence of leptospirosis was 31.0% [95%CI = 26.4-35.5] in 2015 and 28.1% [23.5-32.7] in 2019. The seroprevalence of Q fever was 2.9% [1.2-4.6]. The majority of participants reported being vaccinated against yellow fever (93.6%) and 97.9% had seroneutralizing antibodies. The prevalence of suspected active mucocutaneous leishmaniasis was 2.4% [0.8-3.9].

DISCUSSION

These unique data shed new light on the transmission cycles of zoonoses still poorly understood in the region. They support the existence of a wild cycle of leptospirosis but not of Q fever. Leishmaniasis prevalence was high because of life conditions and tree felling. High yellow fever vaccine coverage was reassuring in this endemic area. In the era of global health, special attention must be paid to these vulnerable populations in direct contact with the tropical ecosystem and away from the health care system.

Spatial effects in parasite-induced marine diseases of immobile hosts

Emerging marine infectious diseases pose a substantial threat to marine ecosystems and the conservation of their biodiversity. Compartmental models of epidemic transmission in marine sessile organisms, available only recently, are based on non-spatial descriptions in which space is homogenized and parasite mobility is not explicitly accounted for. However, in realistic scenarios epidemic transmission is conditioned by the spatial distribution of hosts and the parasites' mobility patterns, calling for an explicit description of space. In this work, we develop a spatially explicit individual-based model to study disease transmission by waterborne parasites in sessile marine populations. We investigate the impact of spatial disease transmission through extensive numerical simulations and theoretical analysis. Specifically, the effects of parasite mobility into the epidemic threshold and the temporal progression of the epidemic are assessed. We show that larger values of pathogen mobility imply more severe epidemics, as the number of infections increases, and shorter timescales to extinction. An analytical expression for the basic reproduction number of the spatial model, R ~ 0 , is derived as a function of the non-spatial counterpart, R ₀, which characterizes a transition between a disease-free and a propagation phase, in which the disease propagates over a large fraction of the system.

Emerging and Re-emerging Infectious Diseases in the WHO Eastern Mediterranean Region, 2001-2018

BACKGROUND

Countries in the World Health Organization (WHO) Eastern Mediterranean Region (EMR) are predisposed to highly contagious, severe and fatal, emerging infectious diseases (EIDs), and re-emerging infectious diseases (RIDs). This paper reviews the epidemiological situation of EIDs and RIDs of global concern in the EMR between 2001 and 2018.

METHODS

To do a narrative review, a complete list of studies in the field was we prepared following a systematic search approach. Studies that were purposively reviewed were identified to summarize the epidemiological situation of each targeted disease. A comprehensive search of all published studies on EIDs and RIDs between 2001 and 2018 was carried out through search engines including Medline, Web of Science, Scopus, Google Scholar, and ScienceDirect.

RESULTS

Leishmaniasis, hepatitis A virus (HAV) and hepatitis E virus (HEV) are reported from all countries in the region. Chikungunya, Crimean Congo hemorrhagic fever (CCHF), dengue fever, and H5N1 have been increasing in number, frequency, and expanding in their geographic distribution. Middle East respiratory syndrome (MERS), which was reported in this region in 2012 is still a public health concern. There are challenges to control cholera, diphtheria, leishmaniasis, measles, and poliomyelitis in some of the countries. Moreover, Alkhurma hemorrhagic fever (AHF), and Rift Valley fever (RVF) are limited to some countries in the region. Also, there is little information about the real situation of the plague, Q fever, and tularemia.

CONCLUSION

EIDs and RIDs are prevalent in most countries in the region and could further spread within the region. It is crucial to improve regional capacities and capabilities in preventing and responding to disease outbreaks with adequate resources and expertise.

Emerging Infectious Diseases and One Health: Implication for Public Health

Emerging infectious diseases (EIDs) are defined as diseases that are newly identified, newly introduced, or newly evolved; or diseases that have recently and rapidly changed in incidence or expanded geographic, host, or vector range agents; or previous infections that acquire new virulence factors; or infections that spread to unaffected regions [...].

Dynamics analysis and optimal control of SIVR epidemic model with incomplete immunity

In this paper, we establish an SIVR model with diffusion, spatially heterogeneous, latent infection, and incomplete immunity in the Neumann boundary condition. Firstly, the threshold dynamic behavior of the model is proved by using the operator semigroup method, the well-posedness of the solution and the basic reproduction number ℜ 0 are given. When ℜ 0 < 1 , the disease-free equilibrium is globally asymptotically stable, the disease will be extinct; when ℜ 0 > 1 , the epidemic equilibrium is globally asymptotically stable, the disease will persist with probability one. Then, we introduce the patient's treatment into the system as the control parameter, and the optimal control of the system is discussed by applying the Hamiltonian function and the adjoint equation. Finally, the theoretical results are verified by numerical simulation.

Age-Associated Changes to Lymph Node Fibroblastic Reticular Cells

The decreased proportion of antigen-inexperienced, naïve T cells is a hallmark of aging in both humans and mice, and contributes to reduced immune responses, particularly against novel and re-emerging pathogens. Naïve T cells depend on survival signals received during their circulation among the lymph nodes by direct contacts with stroma, in particular fibroblastic reticular cells. Macroscopic changes to the architecture of the lymph nodes have been described, but it is unclear how lymph node stroma are altered with age, and whether these changes contribute to reduced naïve T cell maintenance. Here, using 2-photon microscopy, we determined that the aged lymph node displayed increased fibrosis and correspondingly, that naïve T-cell motility was impaired in the aged lymph node, especially in proximity to fibrotic deposition. Functionally, adoptively transferred young naïve T-cells exhibited reduced homeostatic turnover in aged hosts, supporting the role of T cell-extrinsic mechanisms that regulate their survival. Further, we determined that early development of resident fibroblastic reticular cells was impaired, which may correlate to the declining levels of naïve T-cell homeostatic factors observed in aged lymph nodes. Thus, our study addresses the controversy as to whether aging impacts the composition lymph node stroma and supports a model in which impaired differentiation of lymph node fibroblasts and increased fibrosis inhibits the interactions necessary for naïve T cell homeostasis.

Ethnobotanical Uses, Phytochemistry, Toxicology, and Pharmacological Properties of Euphorbia neriifolia Linn. against Infectious Diseases: A Comprehensive Review

Medicinal plants have considerable potential as antimicrobial agents due to the presence of secondary metabolites. This comprehensive overview aims to summarize the classification, morphology, and ethnobotanical uses of Euphorbia neriifolia L. and its derived phytochemicals with the recent updates on the pharmacological properties against emerging infectious diseases, mainly focusing on bacterial, viral, fungal, and parasitic infections. The data were collected from electronic databases, including Google Scholar, PubMed, Semantic Scholar, ScienceDirect, and SpringerLink by utilizing several keywords like 'Euphorbia neriifolia', 'phytoconstituents', 'traditional uses', 'ethnopharmacological uses', 'infectious diseases', 'molecular mechanisms', 'COVID-19', 'bacterial infection', 'viral infection', etc. The results related to the antimicrobial actions of these plant extracts and their derived phytochemicals were carefully reviewed and summarized. Euphol, monohydroxy triterpene, nerifoliol, taraxerol, β-amyrin, glut-5-(10)-en-1-one, neriifolione, and cycloartenol are the leading secondary metabolites reported in phytochemical investigations. These chemicals have been shown to possess a wide spectrum of biological functions. Different extracts of E. neriifolia exerted antimicrobial activities against various pathogens to different extents. Moreover, major phytoconstituents present in this plant, such as quercetin, rutin, friedelin, taraxerol, epitaraxerol, taraxeryl acetate, 3β-friedelanol, 3β-acetoxy friedelane, 3β-simiarenol, afzelin, 24-methylene cycloarenol, ingenol triacetate, and β-amyrin, showed significant antimicrobial activities against various pathogens that are responsible for emerging infectious diseases. This plant and the phytoconstituents, such as flavonoids, monoterpenoids, diterpenoids, triterpenoids, and alkaloids, have been found to have significant antimicrobial properties. The current evidence suggests that they might be used as leads in the development of more effective drugs to treat emerging infectious diseases, including the 2019 coronavirus disease (COVID-19).

Evaluation and comparison of three virucidal agents on inactivation of Nipah virus

Modern human activity is profoundly changing our relationship with microorganisms with the startling rise in the rate of emerging infectious diseases. Nipah virus together with Ebola virus and SARS-CoV-2 are prominent examples. Since COVID-19 and the West African Ebola virus disease outbreak, different chemical disinfectants have been developed for preventing the direct spread of viruses and their efficacy has also been evaluated. However, there are currently no published efficacy studies for the chemical disinfection of Nipah virus. In this study, the virucidal efficacy of three disinfectants (Micro-Chem Plus detergent disinfectant cleaner, FWD and Medical EtOH) against Nipah virus was evaluated in quantitative suspension tests including. Our results showed that the > 4 log reduction achieved for all products in inactivating Nipah virus in 15 s. Even, 19% ethanol was able to inactivate Nipah virus when applied for at least 8 min contact time. Comparative analysis displayed virucidal efficacy of each of the evaluated disinfectants against SARS-CoV-2, Ebola virus and Nipah virus, with only minor differences in working concentrations and contact times required for complete inactivation. We expect that our study can assist in decontamination in healthcare settings and high level biosafety laboratories and can be beneficial to control for emerging enveloped viruses.

Melatonin inhibits Gram-negative pathogens by targeting citrate synthase

Bacterial infections caused by Gram-negative pathogens represent a growing burden for public health worldwide. Despite the urgent need for new antibiotics that effectively fight against pathogenic bacteria, very few compounds are currently under development or approved in the clinical setting. Repurposing compounds for other uses offers a productive strategy for the development of new antibiotics. Here we report that the multifaceted melatonin effectively improves survival rates of mice and decreases bacterial loads in the lung during infection. Mechanistically, melatonin specifically inhibits the activity of citrate synthase of Gram-negative pathogens through directly binding to the R300, D363, and H265 sites, particularly for the notorious Pasteurella multocida. These findings highlight that usage of melatonin is a feasible and alternative therapy to tackle the increasing threat of Gram-negative pathogen infections via disrupting metabolic flux of bacteria.

Effect of Agroecosystems on Seroprevalence of St. Louis Encephalitis and West Nile Viruses in Birds, La Pampa, Argentina, 2017-2019

In Argentina, the Pampa ecoregion has been almost completely transformed into agroecosystems. To evaluate the environmental (agricultural area, tree coverage, distance to the nearest water body and urban site) and biological (dove, cowbird, and sparrow abundance) effects on free-ranging bird exposure to St. Louis encephalitis virus (SLEV) and West Nile virus (WNV), we used generalized linear mixed models. For 1,019 birds sampled during 2017–2019, neutralizing antibodies were found against SLEV in samples from 60 (5.8%) birds and against WNV for 21 (2.1%). The best variable for explaining SLEV seroprevalence was agricultural area, which had a positive effect; however, for WNV, no model was conclusive. Our results suggest that agroecosystems in the La Pampa ecoregion increase the exposure of avian hosts to SLEV, thus potentially increasing virus activity.

Epidemiology and Economic Burden of Continuing Challenge of Infectious Diseases in India: Analysis of Socio-Demographic Differentials

Unlike other low- and middle-income countries, infectious diseases are still predominant, and non-communicable diseases (NCDs) are emerging without replacing the burden of infectious diseases in India, where it is imposing a double burden of diseases on households in the country. This study aimed to analyse the socio-economic and demographic differentials in the magnitude of economic burden and coping strategies associated with health expenditure on infectious diseases in India. National Sample Survey Organization (NSSO) data on “Key Indicators of Social Consumption in India: Health, (2017–18)” have been employed in this study. The findings of the study revealed that more than 33% of the individuals are still suffering from infectious diseases out of the total ailing population in India. Based on the various socio-economic and demographic covariates, infectious diseases are highly prevalent among individuals with marginalized characteristics, such as individuals residing in rural areas, females, 0–14 age groups, Muslims, illiterates, scheduled tribes (STs), and scheduled castes (SCs), large family households, and economically poor people in the country. The per capita out-of-pocket (OOP) expenditure on infectious diseases is INR 7.28 and INR 29.38 in inpatient and outpatient care, respectively. Whereas, monthly per patient OOP expenditure on infectious diseases by infection-affected populations is INR 881.56 and INR 1,156.34 in inpatient and outpatient care in India. The study found that people residing in rural areas, SCs followed by other backward classes (OBCs), illiterates, poor, and very poor are more dependent on borrowings, sale of assets, and other distressed sources of financing. However, under National Health Policy 2017, many initiatives, such as “Ayushman Bharat,” PM-JAY, and National Digital Health Mission (NDHM) in 2021, have been launched by the government of India in the recent years. These initiatives are holistically launched for ensuring better health facilities, but it is early to make any prediction regarding its outcomes; hopefully, the time will define it over the passing of a few more years. Finally, the study proposed the need for proper implementations of policy initiatives, awareness against unhygienic conditions and contamination of illnesses, immunisations/vaccination campaigns, subsidized medical facilities, and the country's expansion of quality primary health-care facilities.

Rapid detection of an Ebola biomarker with optical microring resonators

Ebola virus (EBOV) is a highly infectious pathogen, with a case mortality rate as high as 89%. Rapid therapeutic treatments and supportive measures can drastically improve patient outcome; however, the symptoms of EBOV disease (EVD) lack specificity from other endemic diseases. Given the high mortality and significant symptom overlap, there is a critical need for sensitive, rapid diagnostics for EVD. Facile diagnosis of EVD remains a challenge. Here, we describe a rapid and sensitive diagnostic for EVD through microring resonator sensors in conjunction with a unique biomarker of EBOV infection, soluble glycoprotein (sGP). Microring resonator sensors detected sGP in under 40 min with a limit of detection (LOD) as low as 1.00 ng/mL in serum. Furthermore, we validated our assay with the detection of sGP in serum from EBOV-infected non-human primates. Our results demonstrate the utility of a high-sensitivity diagnostic platform for detection of sGP for diagnosis of EVD.

Managing Viral Emerging Infectious Diseases via current Molecular Diagnostics in the Emergency Department: the Tricky Cases

INTRODUCTION

Emerging infectious diseases' diagnosis has been a major problem in most hospitals and other senior care facilities, especially for the current Coronavirus Disease 2019 (COVID-19). The various clinical manifestations, and the several radiology and laboratory data combined with the misleading test results for identifying the virus, are responsible for certain misdiagnoses, especially for suspected cases that visit the emergency department and require urgent management and further treatment.

AREAS COVERED

The major challenges for emerging infectious diseases' molecular diagnosis are being described here on a great scale, and, finally, strategies for a precise and on-the-spot molecular diagnosis are thoroughly discussed. Related literature was searched using the PubMed, Science Direct, and EMBASE databases published until May 2022 on the general information for viral infections and relevant false test results.

EXPERT OPINION

Emerging diseases' molecular diagnosis via current common diagnostic assays seems to be extremely tricky, and front-line physicians and other senior care facilities should be able to recognize some falsely diagnosed cases or even prevent their existence. Further biotechnologic revolution concerning viral molecular diagnostics will be evident in the near future, thus new methods' limitations should be highlighted to physicians from the very beginning of their performances and wide utilization.

Correlation between Population Density and COVID-19 Cases during the Third Wave in Malaysia: Effect of the Delta Variant

In this study, we describe the incidence and distribution of COVID-19 cases in Malaysia at district level and determine their correlation with absolute population and population density, before and during the period that the Delta variant was dominant in Malaysia. Methods: Data on the number of locally transmitted COVID-19 cases in each of the 145 districts in Malaysia, between 20 September 2020 and 19 September 2021, were manually extracted from official reports. The cumulative number of COVID-19 cases, population and population density of each district were described using choropleth maps. The correlation between population and population density with the cumulative number of COVID-19 cases in each district in the pre-Delta dominant period (20 September 2020–29 June 2021) and during the Delta dominant period (30 June 2021–19 September 2021) were determined using Pearson’s correlation. Results: COVID-19 cases were strongly correlated with both absolute population and population density (Pearson’s correlation coefficient (r) = 0.87 and r = 0.78, respectively). A majority of the districts had higher numbers of COVID-19 cases during the Delta dominant period compared to the pre-Delta period. The correlation coefficient in the pre-Delta dominant period was r = 0.79 vs. r = 0.86 during the Delta dominant period, whereas the pre-Delta dominant population density was r = 0.72, and in the Delta dominant period, r = 0.76. Conclusion: More populous and densely populated districts have a higher risk of transmission of COVID-19, especially with the Delta variant as the dominant circulating strain. Therefore, extra and more stringent control measures should be instituted in highly populated areas to control the spread of COVID-19.

Rapid PCR-Based Nanopore Adaptive Sequencing Improves Sensitivity and Timeliness of Viral Clinical Detection and Genome Surveillance

Nanopore sequencing has been widely used for the real-time detection and surveillance of pathogens with portable MinION. Nanopore adaptive sequencing can enrich on-target sequences without additional pretreatment. In this study, the performance of adaptive sequencing was evaluated for viral genome enrichment of clinical respiratory samples. Ligation-based nanopore adaptive sequencing (LNAS) and rapid PCR-based nanopore adaptive sequencing (RPNAS) workflows were performed to assess the effects of enrichment on nasopharyngeal swab samples from human adenovirus (HAdV) outbreaks. RPNAS was further applied for the enrichment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from nasopharyngeal swab samples to evaluate sensitivity and timeliness. The RPNAS increased both the relative abundance (7.87-12.86-fold) and data yield (1.27-2.15-fold) of HAdV samples, whereas the LNAS increased only the relative abundance but had no obvious enrichment on the data yield. Compared with standard nanopore sequencing, RPNAS detected the SARS-CoV-2 reads from two low-abundance samples, increased the coverage of SARS-CoV-2 by 36.68-98.92%, and reduced the time to achieve the same coverage. Our study highlights the utility of RPNAS for virus enrichment directly from clinical samples, with more on-target data and a shorter sequencing time to recover viral genomes. These findings promise to improve the sensitivity and timeliness of rapid identification and genomic surveillance of infectious diseases.

Virus isolation data improve host predictions for New World rodent orthohantaviruses

Identifying reservoir host species is crucial for understanding the ecology of multi-host pathogens and predicting risks of pathogen spillover from wildlife to people. Predictive models are increasingly used for identifying ecological traits and prioritizing surveillance of likely zoonotic reservoirs, but these often employ different types of evidence for establishing host associations. Comparisons between models with different infection evidence are necessary to guide inferences about the trait profiles of likely hosts and identify which hosts and geographical regions are likely sources of spillover. Here, we use New World rodent-orthohantavirus associations to explore differences in the performance and predictions of models trained on two types of evidence for infection and onward transmission: RT-PCR and live virus isolation data, representing active infections versus host competence, respectively. Orthohantaviruses are primarily carried by muroid rodents and cause the diseases haemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS) in humans. We show that although boosted regression tree (BRT) models trained on RT-PCR and live virus isolation data both performed well and capture generally similar trait profiles, rodent phylogeny influenced previously collected RT-PCR data, and BRTs using virus isolation data displayed a narrower list of predicted reservoirs than those using RT-PCR data. BRT models trained on RT-PCR data identified 138 undiscovered hosts and virus isolation models identified 92 undiscovered hosts, with 27 undiscovered hosts identified by both models. Distributions of predicted hosts were concentrated in several different regions for each model, with large discrepancies between evidence types. As a form of validation, virus isolation models independently predicted several orthohantavirus-rodent host associations that had been previously identified through empirical research using RT-PCR. Our model predictions provide a priority list of species and locations for future orthohantavirus sampling. More broadly, these results demonstrate the value of multiple data types for predicting zoonotic pathogen hosts. These methods can be applied across a range of systems to improve our understanding of pathogen maintenance and increase efficiency of pathogen surveillance.

COVID-19 Pandemic: Identifying Key Issues Using Social Media and Natural Language Processing

The COVID-19 pandemic has affected people's lives in many ways. Social media data can reveal public perceptions and experience with respect to the pandemic, and also reveal factors that hamper or support efforts to curb global spread of the disease. In this paper, we analyzed COVID-19-related comments collected from six social media platforms using natural language processing (NLP) techniques. We identified relevant opinionated keyphrases and their respective sentiment polarity (negative or positive) from over 1 million randomly selected comments, and then categorized them into broader themes using thematic analysis. Our results uncover 34 negative themes out of which 17 are economic, socio-political, educational, and political issues. Twenty (20) positive themes were also identified. We discuss the negative issues and suggest interventions to tackle them based on the positive themes and research evidence.

Stable carbon and nitrogen isotope values in hair reveal management differences and hidden practices in wild boar populations

The analysis of stable isotopes in different tissues has been widely used to obtain information on the ecology and nutritional patterns of wildlife. The isotope ratios of the stable isotopes of carbon and nitrogen (δ¹³C and δ¹⁵N) analysed in different tissues are directly related to the animal's diet and, to some extent, to the environment where the individual has growth. Specifically, this type of analysis in hair samples has become relevant as it provides information on the quality and long-term composition of the diet that produced the isotope accumulation during the tissue growth. We took samples of wild boar (Sus scrofa) hair from 7 different populations in the south-west of Spain (Mediterranean habitats), in the 2018/2019 hunting season. The main objectives of this study were (i) to investigate the use of hair stable isotopes to reveal differences in composition and quality of the diet of wild boar within the same population or between populations, and (ii) to use hair isotopes as a tool to uncover hidden management practices that may occur in hunting areas associated with the use of supplementary feeding or even captive breeding and release. Each animal had a hair (long 10 cm) analysed in duplicate, previously cut into parts of equal size (from the oldest part of the hair to the most recent part), that were analysed separately. We found differences in δ¹³C and δ ¹⁵N between hair parts and populations, which can be related to management actions at different times during the hair growth. Moreover, the use of corn, a type of plant not occurring naturally in the study area, can be documented with the isotope analysis to prove unauthorized supplementary feeding or captive origin of wild boar in hunting areas.

Can microplastics facilitate the emergence of infectious diseases?

Plastic pollution is a major environmental problem. Small plastic particles (called microplastics) have been reported to have pernicious effects on human and wildlife health, by altering physiological functions (e.g., immunity, metabolism) and interfering with commensal microorganisms. However, in addition to these direct toxic effects, we suggest that microplastic pollution might also exert deleterious effects, modifying (i) the exposure to pathogens (e.g., multi-drug resistant bacteria) and (ii) the dynamics of vector-borne diseases. Therefore, we argue that microplastics should be considered as a ubiquitous environmental hazard, potentially promoting the (re)emergence of infectious diseases. The implementation of multi- and interdisciplinary research projects are crucial to properly evaluate if microplastic pollution should be added to the current list of global health threats.

Discovering trends and hotspots of biosafety and biosecurity research via machine learning

Coronavirus disease 2019 (COVID-19) has infected hundreds of millions of people and killed millions of them. As an RNA virus, COVID-19 is more susceptible to variation than other viruses. Many problems involved in this epidemic have made biosafety and biosecurity (hereafter collectively referred to as ‘biosafety’) a popular and timely topic globally. Biosafety research covers a broad and diverse range of topics, and it is important to quickly identify hotspots and trends in biosafety research through big data analysis. However, the data-driven literature on biosafety research discovery is quite scant. We developed a novel topic model based on latent Dirichlet allocation, affinity propagation clustering and the PageRank algorithm (LDAPR) to extract knowledge from biosafety research publications from 2011 to 2020. Then, we conducted hotspot and trend analysis with LDAPR and carried out further studies, including annual hot topic extraction, a 10-year keyword evolution trend analysis, topic map construction, hot region discovery and fine-grained correlation analysis of interdisciplinary research topic trends. These analyses revealed valuable information that can guide epidemic prevention work: (1) the research enthusiasm over a certain infectious disease not only is related to its epidemic characteristics but also is affected by the progress of research on other diseases, and (2) infectious diseases are not only strongly related to their corresponding microorganisms but also potentially related to other specific microorganisms. The detailed experimental results and our code are available at https://github.com/KEAML-JLU/Biosafety-analysis.