Antiepileptic Drugs as Potential Dementia Prophylactics Following Traumatic Brain Injury.

Seizures and other forms of neurovolatility are emerging as druggable prodromal mechanisms that link traumatic brain injury (TBI) to the progression of later dementias. TBI neurotrauma has both acute and long-term impacts on health, and TBI is a leading risk factor for dementias, including chronic traumatic encephalopathy and Alzheimer's disease. Treatment of TBI already considers acute management of posttraumatic seizures and epilepsy, and impressive efforts have optimized regimens of antiepileptic drugs (AEDs) toward that goal. Here we consider that expanding these management strategies could determine which AED regimens best prevent dementia progression in TBI patients. Challenges with this prophylactic strategy include the potential consequences of prolonged AED treatment and that a large subset of patients are refractory to available AEDs. Addressing these challenges is warranted because the management of seizure activity following TBI offers a rare opportunity to prevent the onset or progression of devastating dementias.

Stable diverse food webs become more common when interactions are more biologically constrained.

Ecologists have long sought to understand how diversity and structure mediate the stability of whole ecosystems. For high-diversity food webs, the interactions between species are typically represented using matrices with randomly chosen interaction strengths. Unfortunately, this procedure tends to produce ecological systems with no underlying equilibrium solution, and so ecological inferences from this approach may be biased by nonbiological outcomes. Using recent computationally efficient methodological advances from metabolic networks, we employ for the first time an inverse approach to diversity-stability research. We compare classical random interaction matrices of realistic food web topology (hereafter the classical model) to feasible, biologically constrained, webs produced using the inverse approach. We show that an energetically constrained feasible model yields a far higher proportion of stable high-diversity webs than the classical random matrix approach. When we examine the energetically constrained interaction strength distributions of these matrix models, we find that although these diverse webs have consistent negative self-regulation, they do not require strong self-regulation to persist. These energetically constrained diverse webs instead show an increasing preponderance of weak interactions that are known to increase local stability. Further examination shows that some of these weak interactions naturally appear to arise in the model food webs from a constraint-generated realistic generalist-specialist trade-off, whereby generalist predators have weaker interactions than more specialized species. Additionally, the inverse technique we present here has enormous promise for understanding the role of the biological structure behind stable high-diversity webs and for linking empirical data to the theory.

Algorithms for seeding social networks can enhance the adoption of a public health intervention in urban India.

Targeting structurally influential individuals within social networks can enhance adoption of health interventions within populations. We tested the effectiveness of two algorithms to improve social contagion that do not require knowledge of the whole network structure. We mapped the social interactions of 2,491 women in 50 residential buildings (chawls) in Mumbai, India. The buildings, which are social units, were randomized to (1) targeting 20% of the women at random, (2) targeting friends of such randomly chosen women, (3) targeting pairs of people composed of randomly chosen women and a friend, or (4) no targeting. Both targeting algorithms, friendship nomination and pair targeting, enhanced adoption of a public health intervention related to the use of iron-fortified salt for anemia. In particular, the targeting of pairs of friends, which is relatively easily implementable in field settings, enhanced adoption of novel practices through both social influence and social reinforcement.

Simulating respiratory disease transmission within and between classrooms to assess pandemic management strategies at schools.

The global spread of coronavirus disease 2019 (COVID-19) has emphasized the need for evidence-based strategies for the safe operation of schools during pandemics that balance infection risk with the society's responsibility of allowing children to attend school. Due to limited empirical data, existing analyses assessing school-based interventions in pandemic situations often impose strong assumptions, for example, on the relationship between class size and transmission risk, which could bias the estimated effect of interventions, such as split classes and staggered attendance. To fill this gap in school outbreak studies, we parameterized an individual-based model that accounts for heterogeneous contact rates within and between classes and grades to a multischool outbreak data of influenza. We then simulated school outbreaks of respiratory infectious diseases of ongoing threat (i.e., COVID-19) and potential threat (i.e., pandemic influenza) under a variety of interventions (changing class structures, symptom screening, regular testing, cohorting, and responsive class closures). Our results suggest that interventions changing class structures (e.g., reduced class sizes) may not be effective in reducing the risk of major school outbreaks upon introduction of a case and that other precautionary measures (e.g., screening and isolation) need to be employed. Class-level closures in response to detection of a case were also suggested to be effective in reducing the size of an outbreak.

HIV pre-exposure prophylaxis services, provision, and delivery in the European treatment network of HIV, hepatitis and global emerging infectious diseases (NEAT ID).

OBJECTIVES: We conducted a survey to evaluate HIV pre-exposure prophylaxis (PrEP) practices in a European clinical research network on HIV, hepatitis, and global infectious diseases (NEAT ID). METHODS: An online survey comprising 22 questions was sent via a secure electronic tool to the investigating physician of each of the 342 NEAT ID study centres across 15 European countries in November 2020. RESULTS: In total, 50 sites from 12 countries responded (15% response rate). Most sites were in Western Europe, two were in Poland, and one was in Hungary. Of the responding sites, 45 provided PrEP services for a total of 27 416 PrEP users, with 1361 new PrEP initiators each month. These centres supplied PrEP for men who have sex with men (100%), people who inject drugs (84%), sex workers (84%), women (62%), and transgender women (31%). PrEP persistence after 1 year was >90%, 75%-90%, and 40%-75% in 17, 24, and 4 centres, respectively. In total, 32/45 (71%) centres reported strong community-based organization commitment at their site, and 15/45 (33%) centres developed task-shifting processes to deliver PrEP through nurses (11/15), pharmacists (5/15), and key-population peers (2/15). The biggest barriers to implementation of PrEP were low awareness of and knowledge about PrEP (47%), unwillingness to disclose sexual identity or at-risk behaviour (36%), and lack of administrative support (29%). Of the 45 centres, 32 (71%) have already been involved in PrEP research and 43 (96%) were interested in participating in such studies. CONCLUSIONS: The few NEAT ID centres that responded to the survey showed disparities in PrEP deployment and practices despite a common interest in participating in research in this field.

Intercropping enhances maize growth and nutrient uptake by driving the link between rhizosphere metabolites and microbiomes.

Intercropping leads to different plant roots directly influencing belowground processes and has gained interest for its promotion of increased crop yields and resource utilization. However, the precise mechanisms through which the interactions between rhizosphere metabolites and the microbiome contribute to plant production remain ambiguous, thus impeding the understanding of the yield-enhancing advantages of intercropping. This study conducted field experiments (initiated in 2013) and pot experiments, coupled with multi-omics analysis, to investigate plant-metabolite-microbiome interactions in the rhizosphere of maize. Field-based data revealed significant differences in metabolite and microbiome profiles between the rhizosphere soils of maize monoculture and intercropping. In particular, intercropping soils exhibited higher microbial diversity and metabolite chemodiversity. The chemodiversity and composition of rhizosphere metabolites were significantly related to the diversity, community composition, and network complexity of soil microbiomes, and this relationship further impacted plant nutrient uptake. Pot-based findings demonstrated that the exogenous application of a metabolic mixture comprising key components enriched by intercropping (soyasapogenol B, 6-hydroxynicotinic acid, lycorine, shikimic acid, and phosphocreatine) significantly enhanced root activity, nutrient content, and biomass of maize in natural soil, but not in sterilized soil. Overall, this study emphasized the significance of rhizosphere metabolite-microbe interactions in enhancing yields in intercropping systems. It can provide new insights into rhizosphere controls within intensive agroecosystems, aiming to enhance crop production and ecosystem services.

Preoperative structural-functional coupling at the default mode network predicts surgical outcomes of temporal lobe epilepsy.

OBJECTIVE: Structural-functional coupling (SFC) has shown great promise in predicting postsurgical seizure recurrence in patients with temporal lobe epilepsy (TLE). In this study, we aimed to clarify the global alterations in SFC in TLE patients and predict their surgical outcomes using SFC features. METHODS: This study analyzed presurgical diffusion and functional magnetic resonance imaging data from 71 TLE patients and 48 healthy controls (HCs). TLE patients were categorized into seizure-free (SF) and non-seizure-free (nSF) groups based on postsurgical recurrence. Individual functional connectivity (FC), structural connectivity (SC), and SFC were quantified at the regional and modular levels. The data were compared between the TLE and HC groups as well as among the TLE, SF, and nSF groups. The features of SFC, SC, and FC were categorized into three datasets: the modular SFC dataset, regional SFC dataset, and SC/FC dataset. Each dataset was independently integrated into a cross-validated machine learning model to classify surgical outcomes. RESULTS: Compared with HCs, the visual and subcortical modules exhibited decoupling in TLE patients (p < .05). Multiple default mode network (DMN)-related SFCs were significantly higher in the nSF group than in the SF group (p < .05). Models trained using the modular SFC dataset demonstrated the highest predictive performance. The final prediction model achieved an area under the receiver operating characteristic curve of .893 with an overall accuracy of .887. SIGNIFICANCE: Presurgical hyper-SFC in the DMN was strongly associated with postoperative seizure recurrence. Furthermore, our results introduce a novel SFC-based machine learning model to precisely classify the surgical outcomes of TLE.

Indirect structural changes and reduced controllability after temporal lobe epilepsy resection.

OBJECTIVE: To understand the potential behavioral and cognitive effects of mesial temporal resection for temporal lobe epilepsy (TLE) a method is required to characterize network-wide functional alterations caused by a discrete structural disconnection. The objective of this study was to investigate network-wide alterations in brain dynamics of patients with TLE before and after surgical resection of the seizure focus using average regional controllability (ARC), a measure of the ability of a node to influence network dynamics. METHODS: Diffusion-weighted imaging (DWI) data were acquired in 27 patients with drug-resistant unilateral mesial TLE who underwent selective amygdalohippocampectomy. Imaging data were acquired before and after surgery and a presurgical and postsurgical structural connectome was generated from whole-brain tractography. Edge-wise strength, node strength, and node ARC were compared before and after surgery. Direct and indirect edge-wise strength changes were identified using patient-specific simulated resections. Direct edges were defined as primary edges disconnected by the resection zone itself. Indirect edges were secondary measured edge strength changes. Changes in node strength and ARC were then related to both direct and indirect edge changes. RESULTS: We found nodes with significant postsurgical changes in both node strength and ARC surrounding the resection zone (paired t tests, p < .05, Bonferroni corrected). ARC identified additional postsurgical changes in nodes outside of the resection zone within the ipsilateral occipital lobe, which were associated with indirect edge-wise strength changes of the postsurgical network (Fisher's exact test, p < .001). These indirect edge-wise changes were facilitated through the "hub" nodes including the thalamus, putamen, insula, and precuneus. SIGNIFICANCE: Discrete network disconnection from TLE resection results in widespread structural and functional changes not predicted by disconnection alone. These can be well characterized by dynamic controllability measures such as ARC and may be useful for investigating changes in brain function that may contribute to seizure recurrence and behavioral or cognitive changes after surgery.

The Underlying Structure of Preventive Behaviors and Related Factors During the COVID-19 Pandemic: A Comprehensive Network Analysis.

BACKGROUND: Various strategies against COVID-19 have been adopted in different countries, with vaccination and mask-wearing being widely used as self-preventive interventions. However, the underlying structure of these behaviors and related factors remain unclear. PURPOSE: In this study, we aimed to explore the network structure of preventive behaviors during the COVID-19 pandemic and their underlying factors, incorporating age and sex in the network. METHODS: We used a multi-center sample of 20,863 adults who were vaccinated against COVID-19 in China between April 1, 2021, and June 1, 2021. Networks were estimated using unregularized partial correlation models. We also estimated the accuracy and stability of the network. RESULTS: The preventive behaviors related to network factors revealed that self-initiated vaccination was more connected with cognition factors, and mask-wearing was more connected with personal profiles. The two clusters were linked through information-seeking and political beliefs. Moreover, self-initiated vaccination was negatively connected with vaccine hesitancy and concerns about COVID-19 vaccines and positively connected with trust in the vaccines, pandemic-related altruism, political beliefs, and being married. Mask-wearing was negatively connected with being a professional/white collar worker and higher education level and positively connected with regular physical examination, self-rated health, migration, being married, and better family relationships. Incorporation of age and sex into the network revealed relevant associations between age and mask-wearing and age and self-initiated vaccination. The network was highly accurately estimated. The subset bootstrap showed that the order of node strength centrality, betweenness, and closeness were all stable. The correlation stability coefficient (CS-coefficient) also showed the stability of this estimate, with 0.75 for node strength, 0.75 for betweenness, and 0.67 for closeness. CONCLUSIONS: The internal structures of vaccination and mask-wearing behaviors were quite different, the latter of which were mainly affected by socioeconomic status and health-related behaviors and the former by knowledge about vaccines and political beliefs. Information-seeking and family relationships were the bridge factors connecting these two self-preventive behavior clusters, suggesting the direction of future efforts.

A novel in-bed body posture monitoring for decubitus ulcer prevention using body pressure distribution mapping.

BACKGROUND: Decubitus ulcers are prevalent among the aging population due to a gradual decline in their overall health, such as nutrition, mental health, and mobility, resulting in injury to the skin and tissue. The most common technique to prevent these ulcers is through frequent repositioning to redistribute body pressures. Therefore, the main goal of this study is to facilitate the timely repositioning of patients through the use of a pressure mat to identify in-bed postures in various sleep environments. Pressure data were collected from 10 healthy participants lying down on a pressure mat in 19 various in-bed postures, correlating to the supine, prone, right-side, and left-side classes. In addition, pressure data were collected from participants sitting at the edge of the bed as well as an empty bed. Each participant was asked to lie in these 19 postures in three distinct testing environments: a hospital bed, a home bed, and a home bed with a foam mattress topper. To categorize each posture into its respective class, the pre-trained 2D ResNet-18 CNN and the pre-trained Inflated 3D CNN algorithms were trained and validated using image and video pressure mapped data, respectively. RESULTS: The ResNet-18 and Inflated 3D CNN algorithms were validated using leave-one-subject-out (LOSO) and leave-one-environment-out (LOEO) cross-validation techniques. LOSO provided an average accuracy of 92.07% ± 5.72% and 82.22% ± 8.50%, for the ResNet-18 and Inflated 3D CNN algorithms, respectively. Contrastingly, LOEO provided a reduced average accuracy of 85.37% ± 14.38% and 77.79% ± 9.76%, for the ResNet-18 and Inflated 3D CNN algorithms, respectively. CONCLUSION: These pilot results indicate that the proposed algorithms can accurately distinguish between in-bed postures, on unseen participant data as well as unseen mattress environment data. The proposed algorithms can establish the basis of a decubitus ulcer prevention platform that can be applied to various sleeping environments. To the best of our knowledge, the impact of mattress stiffness has not been considered in previous studies regarding in-bed posture monitoring.

Discovering different acupoint combinations of manual or electro-acupuncture to treat chemotherapy-induced nausea and vomiting based on the complex networks analysis.

OBJECTIVES: The aim of this research was to find the acupoint combinations of manual and electro-acupuncture to treat chemotherapy-induced nausea and vomiting via the complex networks analysis. METHODS: We conducted searches using PubMed, ScienceDirect, MEDLINE, Ovid, spring, Wiley, EMBASE, the Chinese biomedicine database, VIP information network, and China National Knowledge Infrastructure from the establishment of the databases to the August, 2023. Information about titles, journals, interventions, and main acupoints was extracted using the self-established "acupoint for prevention CINV data base" powered by EpiData. According to the level of literature evidence and sample size, the clinical trials and weights of the outcome indicators including nausea/vomiting efficiency were combined. After identifying articles, literature processing and complex network analysis were conducted. The degree distribution of each node, the probability distribution of node degree, the node clustering coefficient, and the distance matrix are calculated by software. RESULTS: Of the 4001 screened publications, 489 were eligible after careful selection. Our result showed the acupoints ST36 and PC6 were the most common combination acupoints in both electro and manual acupuncture. In terms of efficiency, ST36, PC6, and CV12 are significantly effective acupoints for manual acupuncture, and the PC6 and ST36 are effective acupoint for electro-acupuncture. CONCLUSIONS: We found that the near-far collocation method has been commonly used for different types of acupuncture treatment in CINV. Zhongwan, Shangwan, and Liangmen have been mainly used as local acupoints, while Neiguan, Hegu, Quchi, Zusanli, Gongsun, TaiChong, and Neiguan have been mainly used as distal acupoints. From the effect analysis, acupuncture treatment of nausea manual acupuncture effect is better; acupuncture treatment of vomiting or electro-acupuncture effect is better.

Pantoprazole and Vonoprazan Performed Well in Preventing Peptic Ulcer Recurrence in Low-Dose Aspirin Users.

BACKGROUND: Low-dose aspirin (LDA) administration is associated with an elevated risk of recurring peptic ulcer (PU) and gastrointestinal (GI) hemorrhage. AIMS: This systematic review and Bayesian network meta-analysis aimed to comprehensively assess the effectiveness of diverse medications in preventing the recurrence of PU and GI hemorrhage in patients with a history of PU receiving long-term LDA therapy. METHODS: This systematic review and network meta-analysis followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and was registered on PROSPERO (CRD42023406550). We searched relevant studies in main databases from inception to March 2023. All statistical analyses were performed using R (version 4.1.3), with the "Gemtc" (version 1.0-1) package. The pooled risk ratio (RR), corresponding 95% credible interval (95% CrI), and the surface under the cumulative ranking curve (SUCRA) were calculated. RESULTS: 11 Randomized clinical trials (RCTs) were included. The analysis underscored pantoprazole was the most efficacious for reducing the risk of PU recurrence (RR [95% CrI] = 0.02 [0, 0.28]; SUCRA: 90.76%), followed by vonoprazan (RR [95% CrI] = 0.03 [0, 0.19]; SUCRA: 86.47%), comparing with the placebo group. Pantoprazole also performed well in preventing GI hemorrhage (RR [95% CrI] = 0.01[0, 0.42]; SUCRA: 87.12%) compared with Teprenone. CONCLUSIONS: For patients with a history of PU receiving LDA, pantoprazole and vonoprazan might be the optimal choices to prevent PU recurrence and GI hemorrhage.

A network analysis of exhaustion disorder symptoms throughout treatment.

BACKGROUND: Stress-induced Exhaustion Disorder (ED) is associated with work absenteeism and adverse health outcomes. Currently, little is known regarding how the symptoms of ED are interrelated and whether the patterns of symptoms influence treatment outcomes. To this end, the current study applied network analyses on ED patients participating in a multimodal intervention. METHODS: The first aim of the study was to explore the internal relationships between exhaustion symptoms and identify symptoms that were more closely related than others. A second aim was to examine whether the baseline symptom network of non-responders to treatment was more closely connected than the baseline symptom networks of responders, by comparing the sum of all absolute partial correlations in the respective groups' symptom network. This comparison was made based on the hypothesis that a more closely connected symptom network before treatment could indicate poorer treatment outcomes. Network models were constructed based on self-rated ED symptoms in a large sample of patients (n = 915) participating in a 24-week multimodal treatment program with a 12-month follow-up. RESULTS: The internal relations between self-rated exhaustion symptoms were stable over time despite markedly decreased symptom levels throughout participation in treatment. Symptoms of limited mental stamina and negative emotional reactions to demands were consistently found to be the most closely related to other ED symptoms. Meanwhile, sleep quality and irritability were weakly related to other exhaustion symptoms. The symptom network for the full sample became significantly more closely connected from baseline to the end of treatment and 12-month follow-up. The symptom network of non-responders to treatment was not found to be more closely connected than the symptom network of responders at baseline. CONCLUSIONS: The results of the current study suggest symptoms of limited mental stamina and negative emotional reactions to demands are central ED symptoms throughout treatment, while symptoms of irritability and sleep quality seem to have a weak relation to other symptoms of ED. The implications of these findings are discussed in relation to the conceptualization, assessment, and treatment of ED. TRIAL REGISTRATION: The clinical trial was registered on Clinicaltrials.gov 2017-12-02 (Identifier: NCT03360136).

Efficacy and acceptability of different probiotic products plus laxatives for pediatric functional constipation: a network meta-analysis of randomized controlled trials.

The prevalence of pediatric constipation ranges from 0.7 to 29.6% across different countries. Functional constipation accounts for 95% of pediatric constipation, and the efficacy of pharmacotherapy is limited, with a success rate of 60%. Several randomized controlled trials (RCTs) have shown the benefits of probiotic supplements in treating this condition. However, the reported strains of probiotics varied among the RCTs. We aimed to compare the efficacy and acceptability of different probiotic supplements for pediatric functional constipation. The current frequentist model-based network meta-analysis (NMA) included RCTs of probiotic supplements for functional constipation in children. The primary outcome was changes in bowel movement or stool frequency; acceptability outcome was all-cause discontinuation. Nine RCTs were included (N = 710; mean age = 5.5 years; 49.4% girls). Most probiotic products, used either alone or combined with laxatives, were associated with significantly better improvement in bowel movement or stool frequency than placebo/control. Protexin plus laxatives (standardized mean difference (SMD) = 1.87, 95% confidence interval (95% CI) = 0.85 to 2.90) were associated with the greatest improvement in bowel movement or stool frequency among all the investigated probiotic products. For the single probiotic interventions, only Lactobacillus casei rhamnosus Lcr35 was associated with significant efficacy compared to placebo/control treatments (SMD = 1.37, 95% CI: 0.32 to 2.43). All the investigated probiotic products had fecal incontinence and patient drop-out rates similar to those of placebo/control treatments.  Conclusion: The results of our NMA support the application of an advanced combination of probiotics and laxatives for pediatric functional constipation if there is no concurrent contraindication.  Registration: PROSPERO (CRD42022298724). What is Known: • Despite of the high prevalence of pediatric constipation, which ranges from 0.7% to 29.6%, the efficacy of pharmacotherapy is limited, with a success rate of 60%. Several randomized controlled trials (RCTs) have shown the benefits of probiotic supplements in treating this condition. However, the reported strains of probiotics varied among the RCTs. The widely heterogeneous strains of probiotics let the traditional meta-analysis, which pooled all different strains into one group, be nonsense and insignificant. What is New: • By conducting a comprehensive network meta-analysis, we aimed to compare the efficacy and acceptability of different strains of probiotic supplements for pediatric functional constipation. Network meta-analysis of nine randomized controlled trials revealed that the most probiotic products, used either alone or combined with laxatives, were associated with significantly better improvement in bowel movement or stool frequency than placebo/control. Protexin plus laxatives was associated with the greatest improvement in bowel movement or stool frequency among all the investigated probiotic products. For the single probiotic interventions, only Lactobacillus casei rhamnosus Lcr35 was associated with significant efficacy compared to placebo/control treatments. All the investigated probiotic products had fecal incontinence and patient drop-out rates similar to those of placebo/control treatments.

Cost-effectiveness of severe acute malnutrition treatment delivered by community health workers in the district of Mayahi, Niger.

BACKGROUND: A non-randomized controlled trial, conducted from June 2018 to March 2019 in two rural communes in the health district of Mayahi in Niger, showed that including community health workers (CHWs) in the treatment of severe acute malnutrition (SAM) resulted in a better recovery rate (77.2% vs. 72.1%) compared with the standard treatment provided solely at the health centers. The present study aims to assess the cost and cost-effectiveness of the CHWs led treatment of uncomplicated SAM in children 6-59 months compared to the standard national protocol. METHODS: To account for all relevant costs, the cost analysis included activity-based costing and bottom-up approaches from a societal perspective and on a within-trial time horizon. The cost-effectiveness analysis was conducted through a decision analysis network built with OpenMarkov and evaluated under two approaches: (1) with recovery rate and cost per child admitted for treatment as measures of effectiveness and cost, respectively; and (2) assessing the total number of children recovered and the total cost incurred. In addition, a multivariate probabilistic sensitivity analysis was carried out to evaluate the effect of uncertainty around the base case input data. RESULTS: For the base case data, the average cost per child recovered was 116.52 USD in the standard treatment and 107.22 USD in the CHWs-led treatment. Based on the first approach, the CHWs-led treatment was more cost-effective than the standard treatment with an average cost per child admitted for treatment of 82.81 USD vs. 84.01 USD. Based on the second approach, the incremental cost-effectiveness ratio of the transition from the standard to the CHWs-led treatment amounted to 98.01 USD per additional SAM case recovered. CONCLUSIONS: In the district of Mayahi in Niger, the CHWs-led SAM treatment was found to be cost-effective when compared to the standard protocol and provided additional advantages such as the reduction of costs for households. TRIAL REGISTRATION: ISRCTN with ID 31143316. https://doi.org/10.1186/ISRCTN31143316.

Governance of the wildlife trade and the prevention of emerging zoonoses: a mixed methods network analysis of transnational organisations, silos, and power dynamics.

INTRODUCTION: The wildlife trade is an important arena for intervention in the prevention of emerging zoonoses, and leading organisations have advocated for more collaborative, multi-sectoral approaches to governance in this area. The aim of this study is to characterise the structure and function of the network of transnational organisations that interact around the governance of wildlife trade for the prevention of emerging zoonoses, and to assess these network characteristics in terms of how they might support or undermine progress on these issues. METHODS: This study used a mixed methods social network analysis of transnational organisations. Data were collected between May 2021 and September 2022. Participants were representatives of transnational organisations involved in the governance of wildlife trade and the prevention of emerging zoonoses. An initial seed sample of participants was purposively recruited through professional networks, and snowball sampling was used to identify additional participants. Quantitative data were collected through an online network survey. Measures of centrality (degree, closeness, and betweenness) were calculated and the network's largest clique was identified and characterised. To understand the extent to which organisations were connected across sectors, homophily by sector was assessed using exponential random graph modelling. Qualitative data were collected through semi-structured interviews. The findings from the quantitative analysis informed the focus of the qualitative analysis. Qualitative data were explored using thematic analysis. RESULTS: Thirty-seven participants completed the network survey and 17 key informants participated in semi-structured interviews. A total of 69 organisations were identified as belonging to this network. Organisations spanned the animal, human, and environmental health sectors, among others including trade, food and agriculture, and crime. Organisation types included inter-governmental organisations, non-governmental organisations, treaty secretariats, research institutions, and network organisations. Participants emphasised the highly inter-sectoral nature of this topic and the importance of inter-sectoral work, and connections were present across existing sectors. However, there were many barriers to effective interaction, particularly conflicting goals and agendas. Power dynamics also shaped relationships between actors, with the human health sector seen as better resourced and more influential, despite having historically lower engagement than the environmental and animal health sectors around the wildlife trade and its role in emerging zoonoses. CONCLUSION: The network of transnational organisations focused on the governance of wildlife trade and the prevention of emerging zoonoses is highly multi-sectoral, but despite progress catalysed by the COVID-19 pandemic, barriers still exist for inter-sectoral interaction and coordination. A One Health approach to governance at this level, which has gained traction throughout the COVID-19 pandemic, was shared as a promising mechanism to support a balancing of roles and agendas in this space. However, this must involve agreement around equity, priorities, and clear goal setting to support effective action.

Quantifying relational change in community organisations participating in a Veteran suicide prevention learning collaborative: a social network analysis.

BACKGROUND: Veteran suicide remains a significant issue, as 17.5 Veterans die by suicide each day. The US Department of Veteran Affairs (VA) has implemented a robust suicide prevention program within its integrated behavioural health system. Further, the VA has increasingly contributed to suicide prevention in community settings, where a large proportion of Veterans receive health care and social services. One component integral to preventing suicide among Veterans receiving community services is ensuring that organisations are equipped with the latest evidence-based Veteran-specific suicide prevention strategies. METHODS: The Patient Safety Center of Inquiry-Suicide Prevention Collaborative piloted a Veteran suicide prevention learning collaborative in the Denver/Colorado Springs, CO region, spanning 16 months as a multimodal initiative to integrate community organisations and assist them in implementing Veteran suicide prevention strategies used within VA. Agencies completed social network analysis surveys at baseline (T1), year 1 (T2) and 16 months (T3) to examine social networks, partnerships and collaborations among community organisations and the VA over time. RESULTS: The quantity of learning collaborative relationships increased from 30 at T1 to 41 at T3 while the quality of relationships deepened over time from awareness and cooperative to more coordinated and integrated. CONCLUSION: Improvement in relationship quantity and quality facilitates community organisation engagement in collaborating to strengthen their Veteran suicide prevention programming. Learning collaboratives work with the individual organisation for intraorganisational facilitation of implementing suicide prevention strategies and engage and enhance interorganisational partnerships. This multimodal intervention can engage community organisations and provide a stronger safety net for Veterans at risk for suicide.

The common drivers of children and young people's health and wellbeing across 13 local government areas: a systems view.

BACKGROUND: System dynamics approaches, including group model building (GMB) and causal loop diagrams (CLDs), can be used to document complex public health problems from a community perspective. This paper aims to apply Social Network Analysis (SNA) methods to combine multiple CLDs created by local communities into a summary CLD, to identify common drivers of the health and wellbeing of children and young people. METHODS: Thirteen community CLDs regarding children and young people health and wellbeing were merged into one diagram involving three steps: (1) combining variable names; (2) CLD merging, where multiple CLDs were combined into one CLD with a set of unique variables and connections; (3) paring, where the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was used to generate a cut-point to reduce the number of variables and connections and to rank the overall importance of each variable in the merged CLD. RESULTS: Combining variable names resulted in 290 variables across the 13 CLDS. A total of 1,042 causal links were identified in the merged CLD. The DEMATEL analysis of the merged CLD identified 23 common variables with a net importance between 1.0 and 4.5 R + C values and 57 causal links. The variables with the highest net importance were 'mental health' and 'social connection & support' classified as high net receivers of influence within the system. CONCLUSIONS: Combining large CLDs into a simple diagram represents a generalisable model of the drivers of complex health problems.

An integrated FoodNet in North East India: fostering one health approach to fortify public health.

BACKGROUND: Food safety is a critical factor in promoting public health and nutrition, especially in developing countries like India, which experience several foodborne disease outbreaks, often with multidrug-resistant pathogens. Therefore, implementing regular surveillance of enteric pathogens in the human-animal-environment interface is necessary to reduce the disease burden in the country. OBJECTIVE: To establish a network of laboratories for the identification of major food and waterborne pathogens prevailing in the northeast region of India through integrated surveillance of animal, food, human, and environment and investigate the antimicrobial susceptibility pattern of the pathogens of public health significance. METHODS: The Indian Council of Medical Research (ICMR) has identified FoodNet laboratories; based on their geographical location, inclination to undertake the study, preparedness, proficiency, and adherence to quality assurance procedures, through an 8-step process to systematically expand to cover the Northeastern Region (NER) with comprehensive diagnostic capacities for foodborne pathogens and diarrhea outbreak investigations. Network initiated in the NER given the unique food habits of the ethnic population. FINDINGS: This surveillance network for foodborne enteric pathogens was established in Assam, Arunachal Pradesh, Tripura, and Sikkim, and expanded to other four states, i.e., Manipur, Mizoram, Meghalaya, and Nagaland, thereby covering the entire NER by including nine medical and three veterinary centers. All these centers are strengthened with periodic training, technical support, funding, capacity building, quality assurance, monitoring, centralized digital data management, and website development. RESULTS: The ICMR-FoodNet will generate NER-specific data with close to real-time reporting of foodborne disease and outbreaks, and facilitate the updating of food safety management protocols, policy reforms, and public health outbreak response. During 2020-2023, 13,981 food samples were tested and the detection of enteric pathogens ranged from 3 to 4%. In clinical samples, the detection rate of the pathogens was high in the diarrheal stools (8.9%) when 3,107 samples were tested. Thirteen outbreaks were investigated during the study period. CONCLUSION: Foodborne diseases and outbreaks are a neglected subject. Given the frequent outbreaks leading to the deaths of children, it is crucial to generate robust data through well-established surveillance networks so that a strong food safety policy can be developed for better public health.

Implementation processes of social network interventions for physical activity and sedentary behavior among children and adolescents: a scoping review.

BACKGROUND: The characteristics of the implementation process of interventions are essential for bridging the gap between research and practice. This scoping review aims to identify the implementation process of social network interventions (SNI) to address physical activity and sedentary behaviors in children and adolescents. METHODS: The scoping review was conducted adhering to the established guidelines. The search was carried out in the ERIC, EBSCO, EMBASE, SCOPUS, and Lilacs databases in April 2023. Social network intervention studies in children and adolescents were included, addressing physical activity or sedentary behaviors. Replicability (TIDieR), applicability (PRECIS-2), and generalizability (RE-AIM) were the explored components of the implementation process. Each component was quantitatively and separately analyzed. Then, a qualitative integration was carried out using a narrative method. RESULTS: Most SNI were theoretically framed on the self-determination theory, used social influence as a social mechanism, and used the individual typology of network intervention. Overall, SNI had strong replicability, tended to be pragmatic, and three RE-AIM domains (reach, adoption (staff), and implementation) showed an acceptable level of the generalizability of findings. CONCLUSIONS: The analyzed SNI for physical activity and sedentary behaviors in adolescents tended to be reported with high replicability and were conducted pragmatically, i.e., with very similar conditions to real settings. The RE-AIM domains of reach, adoption (staff), and implementation support the generalizability of SNI. Some domains of the principles of implementation strategies of SNI had acceptable external validity (actor, action targets, temporality, dose, and theoretical justification).