Amoeba-bacteria interactions are prevalent in both natural ecosystems and engineered environments. Amoebae, as essential consumers, hold significant ecological importance within ecosystems. Besides, they can establish stable symbiotic associations with bacteria. Copper plays a critical role in amoeba predation by either killing or restricting the growth of ingested bacteria in phagosomes. However, certain symbiotic bacteria have evolved mechanisms to persist within the phagosomal vacuole, evading antimicrobial defenses. Despite these insights, the impact of copper on the symbiotic relationships between amoebae and bacteria remains poorly understood. In this study, we investigated the effects of copper stress on amoebae and their symbiotic relationships with bacteria. Our findings revealed that elevated copper concentration adversely affected amoeba growth and altered cellular fate. Symbiont type significantly influenced the responses of the symbiotic relationships to copper stress. Beneficial symbionts maintained stability under copper stress, but parasitic symbionts exhibited enhanced colonization of amoebae. Furthermore, copper stress favored the transition of symbiotic relationships between amoebae and beneficial symbionts toward the host\'s benefit. Conversely, the pathogenic effects of parasitic symbionts on hosts were exacerbated under copper stress. This study sheds light on the intricate response mechanisms of soil amoebae and amoeba-bacteria symbiotic systems to copper stress, providing new insights into symbiotic dynamics under abiotic factors. Additionally, the results underscore the potential risks of copper accumulation in the environment for pathogen transmission and biosafety.

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

Mosquito-borne diseases present a significant threat to human health, with the possibility of outbreaks of new mosquito-borne diseases always looming. Unfortunately, current measures to combat these diseases such as vaccines and drugs are often either unavailable or ineffective. However, recent studies on microbiomes may reveal promising strategies to fight these diseases. In this review, we examine recent advances in our understanding of the effects of both the mosquito and vertebrate microbiomes on mosquito-borne diseases. We argue that the mosquito microbiome can have direct and indirect impacts on the transmission of these diseases, with mosquito symbiotic microorganisms, particularly Wolbachia bacteria, showing potential for controlling mosquito-borne diseases. Moreover, the skin microbiome of vertebrates plays a significant role in mosquito preferences, while the gut microbiome has an impact on the progression of mosquito-borne diseases in humans. As researchers continue to explore the role of microbiomes in mosquito-borne diseases, we highlight some promising future directions for this field. Ultimately, a better understanding of the interplay between mosquitoes, their hosts, pathogens, and the microbiomes of mosquitoes and hosts may hold the key to preventing and controlling mosquito-borne diseases.

Micrografting, which was developed almost 50 years ago, has long been used for virus eradication, micropropagation, regeneration, rejuvenation, and graft compatibility. Recently, micrografting has been used for studies of long-distance trafficking and signaling of molecules between scions and rootstocks. The graft transmissiveness of obligate plant pathogens, such as viruses, viroids, and phytoplasmas, facilitated the use of micrografting to study biological indexing and pathogen transmission, pathogen-induced graft incompatibility, and screening for the pathogen resistance during the past 20 years. The present study provides comprehensive information on the latter subjects. Finally, prospects are proposed to direct further studies.

Transmission of respiratory pathogens such as SARS-CoV-2 depends on patterns of contact and mixing across populations. Understanding this is crucial to predict pathogen spread and the effectiveness of control efforts. Most analyses of contact patterns to date have focused on high-income settings.
Here, we conduct a systematic review and individual-participant meta-analysis of surveys carried out in low- and middle-income countries and compare patterns of contact in these settings to surveys previously carried out in high-income countries. Using individual-level data from 28,503 participants and 413,069 contacts across 27 surveys, we explored how contact characteristics (number, location, duration, and whether physical) vary across income settings.
Contact rates declined with age in high- and upper-middle-income settings, but not in low-income settings, where adults aged 65+ made similar numbers of contacts as younger individuals and mixed with all age groups. Across all settings, increasing household size was a key determinant of contact frequency and characteristics, with low-income settings characterised by the largest, most intergenerational households. A higher proportion of contacts were made at home in low-income settings, and work/school contacts were more frequent in high-income strata. We also observed contrasting effects of gender across income strata on the frequency, duration, and type of contacts individuals made.
These differences in contact patterns between settings have material consequences for both spread of respiratory pathogens and the effectiveness of different non-pharmaceutical interventions.
This work is primarily being funded by joint Centre funding from the UK Medical Research Council and DFID (MR/R015600/1).
Infectious diseases, particularly those caused by airborne pathogens like SARS-CoV-2, spread by social contact, and understanding how people mix is critical in controlling outbreaks. To explore these patterns, researchers typically carry out large contact surveys. Participants are asked for personal information (such as gender, age and occupation), as well as details of recent social contacts, usually those that happened in the last 24 hours. This information includes, the age and gender of the contact, where the interaction happened, how long it lasted, and whether it involved physical touch. These kinds of surveys help scientists to predict how infectious diseases might spread. But there is a problem: most of the data come from high-income countries, and there is evidence to suggest that social contact patterns differ between places. Therefore, data from these countries might not be useful for predicting how infections spread in lower-income regions. Here, Mousa et al. have collected and combined data from 27 contact surveys carried out before the COVID-19 pandemic to see how baseline social interactions vary between high- and lower-income settings. The comparison revealed that, in higher-income countries, the number of daily contacts people made decreased with age. But, in lower-income countries, younger and older individuals made similar numbers of contacts and mixed with all age groups. In higher-income countries, more contacts happened at work or school, while in low-income settings, more interactions happened at home and people were also more likely to live in larger, intergenerational households. Mousa et al. also found that gender affected how long contacts lasted and whether they involved physical contact, both of which are key risk factors for transmitting airborne pathogens. These findings can help researchers to predict how infectious diseases might spread in different settings. They can also be used to assess how effective non-medical restrictions, like shielding of the elderly and workplace closures, will be at reducing transmissions in different parts of the world.

Time-variant positive air pressure in a drainage stack poses a risk of pathogenic virus transmission into a habitable space, however, the excessive risk and its significance have not yet been sufficiently addressed for drainage system designs. This study proposes a novel measure for the probable pathogenic virus transmission risk of a high-rise drainage stack with the occurrence of positive air pressure. The proposed approach is based on time-variant positive air pressures measured in a 38 m high drainage stack of a full-scale experimental tower under steady flow conditions of flow rate 1-4 Ls-1 discharging at a height between 15 m to 33 m above the stack base. The maximum pressure and probabilistic positive air pressures in the discharging stack ventilation section with no water (Zone A of the discharging drainage stack) were determined. It was demonstrated that the positive air pressures were lower in frequency as compared with those in other stack zones and could propagate along the upper 1/3 portion of the ventilation pipe (H\' ≥ 0.63) towards the ventilation opening at the rooftop. As the probabilistic positive pressures at a stack height were found to be related to the water discharging height and flow rate, a risk model of positive air pressure is proposed. Taking the 119th, 124th, 140th and 11,547th COVID-19 cases of an epidemiological investigation in Hong Kong as a baseline of concern, excessive risk of system overuse was evaluated. The results showed that for a 20-80% increase in the frequency of discharge flow rate, the number of floors identified at risk increased from 1 to 9 and 1 to 6 in the 34- and 25-storey residential buildings, respectively. The outcome can apply to facilities planning for self-quarantine arrangements in high-rise buildings where pathogenic virus transmission associated with drainage system overuse is a concern.

Transmission mechanics of infectious pathogen in various environments are of great complexity and has always been attracting many researchers\' attention. As a cost-effective and powerful method, Computational Fluid Dynamics (CFD) plays an important role in numerically solving environmental fluid mechanics. Besides, with the development of computer science, an increasing number of researchers start to analyze pathogen transmission by using CFD methods. Inspired by the impact of COVID-19, this review summarizes research works of pathogen transmission based on CFD methods with different models and algorithms. Defining the pathogen as the particle or gaseous in CFD simulation is a common method and epidemic models are used in some investigations to rise the authenticity of calculation. Although it is not so difficult to describe the physical characteristics of pathogens, how to describe the biological characteristics of it is still a big challenge in the CFD simulation. A series of investigations which analyzed pathogen transmission in different environments (hospital, teaching building, etc) demonstrated the effect of airflow on pathogen transmission and emphasized the importance of reasonable ventilation. Finally, this review presented three advanced methods: LBM method, Porous Media method, and Web-based forecasting method. Although CFD methods mentioned in this review may not alleviate the current pandemic situation, it helps researchers realize the transmission mechanisms of pathogens like viruses and bacteria and provides guidelines for reducing infection risk in epidemic or pandemic situations.

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