One health outlook最新文献

Background: Nipah virus is an emerging zoonotic pathogen with pandemic potential, primarily transmitted through the consumption of raw date palm sap contaminated with bat excretions. Despite recurring outbreaks in Bangladesh since 2001, limited research has explored sap harvesting and trading practices. This study aimed to understand raw date palm sap collection, trade, and the risk of Nipah virus spillover at the community level in Bangladesh.

Methods: A qualitative ethnographic study was conducted in two districts of Bangladesh associated with recurrent outbreaks in February 2021 and March 2022. We recorded participant observations and conducted ethnographic interviews with raw date palm sap collectors to gather data on collection, trading practices, and protective measures they used. Data analysis followed a grounded theory approach, identifying themes related to raw date palm sap harvesting and trading.

Results: Sap collectors sold raw sap locally and also used social media to reach buyers in other districts, where they could earn higher profits. Our observations and participant reports revealed that large fruit bats, small frugivorous bats, and rodents visited the trees and drank and contaminated raw sap with their excreta. A few sap collectors were aware of Nipah virus and used protection to avoid infection from drinking raw sap. Sap collectors prefer to use non-conventional protective apparatuses like jute bags, plastic bags, and polythene sheets due to the time and resource constraints to protect bats' and rodents' access to date palm trees.

Conclusions: This study provides important insights into the knowledge of Nipah virus and understanding of its transmission in the sap collector communities where outbreaks have occurred. It underscores the need for educational outreach programs to raise awareness and promote protective measures among the stakeholders engaged in raw date palm sap harvesting. Future research should explore raw sap distribution and trading networks in large areas to better characterize the geographies, behavioral, and cultural practices that influence Nipah virus transmission. Culture-sensitive interventions with economic incentives, involving harvesters, local governments, and non-governmental organizations, along with testing the effectiveness of protective measures, are essential to prevent the spillover of Nipah and other bat-borne emerging viruses in Bangladesh.

In recent years, One Health (OH) has taken the lead as a systems-oriented method to foster transdisciplinary, multisectoral, and multi-actor action to promote global health security. However, operationalizing the OH approach is difficult since it requires equitable collaboration, communication and information sharing. The One Health High-Level Expert Panel's (OHHLEP) definition of OH lists key underlying principles at its core, which align with principles of diversity, equity and inclusion (DEI), and establishes that the application of the definition is incomplete without the adoption of these key principles. In this paper, we argue that, by overcoming the barriers that hamper OH adherence to DEI principles, the operationalization of the OH approach could be significantly enhanced to support global health security. We built on the key underlying principles included in the OHHLEP 2022 definition of OH to map barriers preventing its full-scale implementation and to identify inclusive avenues to promote the compliance of OH with its core principles. A scoping review of the literature and consultations with 10 OH professionals from different disciplinary backgrounds, regions of the world and levels of experience were performed. The barriers to the full adherence of OH to its underlying principles that emerged from this study were grouped into five categories: mindset, behaviors and awareness, conceptual, structural, power dynamics, and governance and implementation. Crucially, the engagement of diverse sectors and disciplines notably the environmental and social sciences; of different actors from communities and young people to donors and OH professionals, including the private sector; and of underrepresented groups, such as Indigenous peoples, farmers, fishers, representatives from low- and middle-income countries, and especially women across these groups, all intimately connected to the drivers of emerging health threats, is not only critical for realizing DEI principles in OH, but also to promote more effective prevention strategies and thus enhance global health security.

Antibiotic resistance is a significant global public health threat, rendering treating human and animal infections difficult, longer and expensive. This study was conducted to determine the antibiotic resistance profiles of Escherichia coli isolated from pig farming environments in selected pig farms around Kenya. Wastewater, the associated sludge, and ground surface boot sock samples were collected from preselected intensive pig farms. A total of 80 samples were collected from 16 intensive pig farms. The samples were cultured, and 112 E. coli isolates were identified using standard microbiological procedures and confirmed by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectroscopy (MALDI-TOF MS). Antibiotic susceptibility testing was performed using the Kirby-Bauer disc diffusion method against ampicillin, amoxicillin-clavulanic acid, gentamicin, trimethoprim-sulfamethoxazole, chloramphenicol, enrofloxacin and cefotaxime. The highest resistance was recorded against ampicillin at 27.7% and the lowest for cefotaxime at 7.1%. Multidrug-resistance was observed for 25.9% of the isolates. There was no significant difference between resistances from the sampling locations. Fisher's exact test conducted to determine the difference between resistance rates of different sample types and the antibiotics tested showed that trimethoprim-sulphamethoxazole showed a statistically significant difference (p = 0.003). The isolates had varied multidrug antibiotic resistance (MAR) indices, but the average index was 0.33. The mean MAR index was highest in boot socks samples (0.3 ± 0.3). Kruskal-Wallis test did not find a statistically significant difference between sample type and MAR index. The results suggest that there is potentially high antibiotic exposure in the intensive pig farms that may increase the selection pressure leading to the development and dissemination of antibiotic-resistant E. coli among pig populations. These findings highlight the presence of multidrug-resistant E. coli in intensive pig farm environments, posing a potential risk to humans and the wider environment, which may further compound the public health threat.

Recent outbreaks of Marburg virus disease in regions of sub-Saharan Africa without prior record such as Ghana, Tanzania, Equatorial Guinea, and Rwanda challenge the current understanding of areas at-risk for filovirus spillover. The orthomarburgvirus host Rousettus aegyptiacus exists in these regions, and has a sister species, Rousettus madagascariensis, native only to the island of Madagascar. We expand on previous surveillance of frugivorous bats in Madagascar, and detect seroreactivity against an orthoebolavirus antigenically-related to Bundibugyo virus at 1.50-5.06% seroprevalence in Rousettus madagascariensis. Notably, we identify R. madagascariensis as an orthomarburgvirus-host species of interest in Madagascar, the first record of this virus genus on the island. We document seroprevalences of 15.36-29.78% for Ravn virus and 12.55-33.33% for Marburg virus in R. madagascariensis. These findings will guide future biosurveillance efforts to assess filovirus spillover risk in Madagascar.

Background: The Gram-negative enteric bacterium Shigella dysenteriae serotype 1 (Sd1) has historically caused several dysentery epidemics but has largely disappeared from the global epidemiological landscape, with the last reported isolate dating back to 2010. In this study, we have recently identified Sd1 from lamb meat in India in 2022, the first detection since 2010 and compared its genetic characteristics with the two clinical Sd1 isolates that were identified in Kolkata in 2010 and other global genomic sequences collected between 1951 and 2011.

Methodology: As part of the National ICMR-FoodNet surveillance, this study isolated S. dysenteriae serotype 1 from lamb meat in Sikkim (2022; SKM-823) and compared it with two clinical isolates from Kolkata (2010). Characterization involved biochemical and serological tests, antimicrobial resistance (AMR) and whole genome sequencing. SNP-based phylogenetic analysis, MLST, ARGs, and toxin gene detection were conducted for the study isolates against 331 global Sd1 genomes.

Results: Comparative analysis of Sd1 (SKM-823) with two clinical isolates (IDH-3116 and IDH-3161) exhibited resistance to quinolones, fluroquinolones, tetracycline, chloramphenicol, and sulfamethoxazole/trimethoprim, but were susceptible to azithromycin and cephalosporins. The two clinical Sd1 isolates were resistant to azithromycin. Multi locus sequence typing identified that the clinical isolates belonging to ST5159 and SKM-823 as ST146. Both these STs are mostly represented by the other Asian Sd1 isolates. Several antimicrobial resistance encoding genes (ARGs) have been identified in the Shigella resistance locus-pathogenicity island. Four key toxin genes such as the Shiga toxins-stx1A, stx1B; enteroaggregative heat-stable toxin-astA; and invasion plasmid associated-antigen-ipaH were also identified in SKM-823, IDH-3116 and IDH-3161. The phylogenetic analysis showed clustering of SKM-823 Sd1 isolate and the other clinical isolates (IDH-3116 and IDH-3161) from India within lineage IV, consistent with the other Asian isolates.

Conclusion: This study finding reveals genomic changes and rising AMR in Sd1, underscoring its potential epidemic implications and the need to strengthen systematic surveillance. With the increasing reports on the incidence of Shigella spp from animals, foods of animal origin and food handlers, Sd1 is becoming a significant concern within the global one health framework. The identification of an epidemic causing S. dysenteriae Type 1 calls for timely action from health authorities to implement targeted interventions and ensure updated medical and policy responses remain updated and responsive.

Background: Europe and Africa are increasingly affected by (re-)emerging risk group 3 and 4, zoonotic viral disease epidemics, which not only require diagnostic BSL-3/4 laboratory capacity but also a One Health-based control strategy for efficient outbreak containment. In many European and African countries such laboratory capacity is often not readily available, and rapid response mobile laboratories (RRMLs) can play important, complementary roles in outbreak responses and pandemic preparedness activities on national, regional and international level.

Main body: The aim of the present review was to assess whether existing European and African RRML infrastructure is prepared for future One Health outbreak responses and to identify potential diagnostic gaps. Based on a literature review (2007-2021), we identified 291 mobile laboratories (Europe: 192, Africa: 99) and assessed them in respect to purpose (e.g. military, civilian), design (suitcase, modular, vehicle mounted), biosafety level, laboratory equipment, diagnostic portfolio, sample types analyzed (human, animal) and quality assurance measures. Following peaks in 2014 (Ebola/West Africa) and 2020 (COVID-19), mobile laboratory numbers have steadily increased. Whilst laboratories were originally designed to diagnose viral haemorrhagic fevers, there has been an increased focus on SARS-CoV-2 since 2020. Recently, there was a shift of African countries to develop an independent mobile laboratory capacity, rather than relying on external support for outbreak responses.

Conclusion: We identified key shortcomings of existing laboratories, as the majority only process samples of human origin (not compliant with One Health principles), only 5% have sufficient capacity to diagnose emerging risk group 3/4 (arbo)viruses, 1-10% have accredited quality assurance systems in place, and mobile laboratories are not interconnected to allow concerted national and international responses. Our results reveal the gaps that should be addressed to make future responses to zoonotic, high-consequence pathogens more effective.

Background: Wildlife farming and trade in Southeast Asia contribute to the growing threat of zoonotic diseases. Despite the diversity of species farmed and the varying levels of risk they may pose, biosecurity practices among wildlife farmers remain underexplored. This study aimed to assess the knowledge, attitudes, and practices (KAP) of wildlife farmers in Vietnam to inform targeted interventions for zoonotic risk reduction.

Method: A mixed-methods study was conducted among 210 wildlife farmers who raised bats, bamboo rats, civets, and wild boars in Lao Cai and Dong Nai provinces, Vietnam, between October 2023 and March 2024. Quantitative data were collected via structured questionnaires, and qualitative insights were obtained through 30 key informant interviews and two focus group discussions. Linear mixed-effects regression and thematic analysis were applied to explore KAP scores and associated factors.

Results: Wildlife farmers demonstrated relatively high knowledge (mean score: 10.1/13, 77.7%), positive attitudes (mean score: 41.3/50, 82.6%), and moderate preventive practices (mean score: 14.1/30, 47.0%). Farmers with college or above education had higher knowledge scores (Estimated marginal mean (EMM) = 11.8; 95% confidence interval (CI): 10.2-12.8) compared to those with no formal education (EMM = 7.8; 95% CI: 4.0-11.1). Farmers solely engaged in wildlife farming had lower attitude scores (EMM = 41.7; 95% CI: 37.8-45.0) than farmers who also worked as government employees (EMM = 46.1; 95% CI: 43.3-48.2). Farming bats (EMM = 8.5; 95% CI: 5.8-11.4) had lower practice scores compared to farming civets (EMM = 15.8; 95% CI: 13.0-18.6), and farmers consumed wild meat had lower practice score (EMM = 12.3; 95% CI: 9.5-15.2) than those did not (EMM = 14.5; 95% CI: 11.9-17.0). Qualitative findings revealed that many farmers normalised risky practices, prioritised convenience and personal experience over disease knowledge, and avoided reporting illnesses due to mistrust in veterinary authorities and fear of negative consequences.

Conclusion: This study highlights low risk perception and gaps between knowledge and practices among wildlife farmers, underscoring the urgent need for One Health interventions that promote low-cost preventive measures, build trust with authorities, and deliver targeted health education for reducing zoonotic risks.

Background: Antimicrobial resistance (AMR) is a global health challenge driven by the misuse of antimicrobials across humans, animals, and the environment, necessitating integrated One Health solutions.

Objective: This scoping review aims to synthesise evidence on the opportunities and challenges of leveraging artificial intelligence (AI) to tackle AMR within the One Health framework.

Methods: This review adhered to the PRISMA-ScR guideline. A comprehensive literature search was conducted in PubMed, Embase, Scopus, Web of Science, along with citation searching and Google Scholar.

Results: A total of 543 studies were identified from these databases. After removing duplicates, 343 studies remained for screening. Following the title and abstract screening, 273 publications were selected for full-text review, and 43 studies were included in the final analysis. Studies written in English that explored the application of AI tools and techniques for AMR in any One Health domain were included. The review found that AI is widely applied to combat AMR across different sectors (human, animal, and environmental health), with key opportunities including the rapid identification of resistant pathogens, AI-powered surveillance and early warning, integration of diverse datasets, and support for drug discovery and antibiotic stewardship. However, significant challenges remain, such as data standardisation issues, limited model transparency, infrastructure and resource gaps, ethical and privacy concerns, and difficulties in real-world implementation and validation.

Conclusion: Overall, while AI has great potential to improve AMR management, fully realising its benefits will require investment in explainable AI, better data infrastructure, stronger cross-sector collaboration, and clear regulatory frameworks to ensure ethical and effective use within the One Health approach.