Assessment of performance for a key indicator of One Health: evidence based on One Health index for zoonoses in Sub-Saharan Africa

Nomenclature for human and animal fungal pathogens and diseases: a proposal for standardized terminology

Medically important pathogenic fungi invade vertebrate tissue and are considered primary when part of their nature life cycle is associated with an animal host and are usually able to infect immunocompetent hosts. Opportunistic fungal pathogens complete their life cycle in environmental habitats or occur as commensals within or on the vertebrate body, but under certain conditions can thrive upon infecting humans. The extent of host damage in opportunistic infections largely depends on the portal and modality of entry as well as on the host's immune and metabolic status. Diseases caused by primary pathogens and common opportunists, causing the top approximately 80% of fungal diseases [D. W. Denning, Lancet Infect Dis, 24:e428-e438, 2024, https://doi.org/10.1016/S1473-3099(23)00692-8], tend to follow a predictive pattern, while those by occasional opportunists are more variable. For this reason, it is recommended that diseases caused by primary pathogens and the common opportunists are named after the etiologic agent, for example, histoplasmosis and aspergillosis, while this should not be done for occasional opportunists that should be named as [causative fungus] [clinical syndrome], for example, Alternaria alternata cutaneous infection. The addition of a descriptor that identifies the location or clinical type of infection is required, as the general name alone may cover widely different clinical syndromes, for example, "rhinocerebral mucormycosis." A list of major recommended human and animal disease entities (nomenclature) is provided in alignment with their causative agents. Fungal disease names may encompass several genera of etiologic agents, consequently being less susceptible to taxonomic changes of the causative species, for example, mucormycosis covers numerous mucormycetous molds.

One Health Priorities: Advancing Veterinary Public Health in Latin America and the Caribbean

One Health (OH) is an integrative approach to human, animal, and environmental health and can be used as a comprehensive indicator for comparative purposes. Although an OH index has been proposed for comparing cities, states, and countries, to date, no practical study has compared countries using this approach. Accordingly, this study aimed to assess OH initiatives using a survey with a veterinary public health focus. The questionnaire contained 104 quantitative questions and was sent to representatives of governmental institutions of 32 countries in the Americas. After exclusion criteria were considered, a total of 35 questionnaires from 17 countries were analyzed, with country names remaining undisclosed during the statistical analyses to protect potentially sensitive information. Principal component analysis (PCA) of health parameters in Latin America and the Caribbean (LAC) as a function of country perception (self-vector) showed that food safety was ranked higher than public policies (p = 0.009), and that both (p = 0.003) were ranked higher than institutional routines related to zoonosis programs. National policies in accordance with international standards, regulations, recommendations, and guidelines was considered the standout topic for public policy, with higher-ranking topics including standard. Meanwhile, challenging topics included tools, preparedness, governance, and research. Food safety showed both strengths and challenges in the coordination of its activities with other sectors. Food safety communication was scored as a strength, while foodborne diseases prevention was ranked as a challenge. Institutional routines for zoonosis maintained both strong and challenging topics in the execution and implementation of attributions and daily routine. Thus, the survey showed that topics such as access to and compliance with international guidelines and intercountry integration were ranked higher than in-country articulation, particularly among food safety, zoonoses, and environmental institutions.

Bridging Food Systems and One Health: A key to preventing future pandemics?

Food Systems and One Health are two approaches increasingly known for the holistic perspective they bring when addressing the issues that concern them: food and health. This systematic literature review aims to explore the evidence for using these approaches in a concerted manner to better manage zoonoses. By zoonoses management, we refer to improving the ability to address current zoonoses as well as preventing future ones. A total of 98 scientific articles were screened, of which 29 were considered eligible due to their focus on operationalizing each approach to help address zoonoses, as well as a combination of the two. Most articles implement One Health to prevent zoonoses by guiding stakeholders in concerted and participatory decision-making processes. However, the One Health approach can also be adopted via data modelling. Several articles refer to the monitoring and evaluation process of One Health initiatives to prevent zoonoses and discuss best practices to successfully implement the approach. Contrastingly, only three studies adopt a Food System approach to manage zoonoses, despite the profound connections existing between our food systems and the emergence of zoonotic risks. We conclude that there is a lack of integration between the One Health and Food System approaches to manage zoonoses. We also show that experts call for integration, so that not only human, animal, plant, and environmental health are considered, but also the socio-economic trade-offs when monitoring and developing strategies to manage zoonoses. This can be reversed, enabling zoonotic risks to be addressed when planning for our food systems of tomorrow.

Revisiting the antigen markers of vector-borne parasitic diseases identified by immunomics: identification and application to disease control

INTRODUCTION

Protein microarray is a promising immunomic approach for identifying biomarkers. Based on our previous study that reviewed parasite antigens and recent parasitic omics research, this article expands to include information on vector-borne parasitic diseases (VBPDs), namely, malaria, schistosomiasis, leishmaniasis, babesiosis, trypanosomiasis, lymphatic filariasis, and onchocerciasis.

AREAS COVERED

We revisit and systematically summarize antigen markers of vector-borne parasites identified by the immunomic approach and discuss the latest advances in identifying antigens for the rational development of diagnostics and vaccines. The applications and challenges of this approach for VBPD control are also discussed.

EXPERT OPINION

The immunomic approach has enabled the identification and/or validation of antigen markers for vaccine development, diagnosis, disease surveillance, and treatment. However, this approach presents several challenges, including limited sample size, variability in antigen expression, false-positive results, complexity of omics data, validation and reproducibility, and heterogeneity of diseases. In addition, antigen involvement in host immune evasion and antigen sensitivity/specificity are major issues in its application. Despite these limitations, this approach remains promising for controlling VBPD. Advances in technology and data analysis methods should continue to improve candidate antigen identification, as well as the use of a multiantigen approach in diagnostic and vaccine development for VBPD control.

How far has the globe gone in achieving One Health? Current evidence and policy implications based on global One Health index

Background

In the 21st century, as globalization accelerates and global public health crises occur, the One Health approach, guided by the holistic thinking of human-animal-environment and emphasizing interdisciplinary collaboration to address global health issues, has been strongly advocated by the international community. An immediate requirement exists for the creation of an assessment tool to foster One Health initiatives on both global and national scales.

Methods

Built upon extensive expert consultations and dialogues, this follow-up study enhances the 2022 global One Health index (GOHI) indicator system. The GOHI framework is enriched by covering three indices, e.g. external drivers index (EDI), intrinsic drivers index (IDI), and core drivers index (CDI). The comprehensive indicator system incorporates 13 key indicators, 50 indicators, and 170 sub I-indicators, utilizing a fuzzy analytic hierarchy process to ascertain the weight for each indicator. Weighted and summed, the EDI, IDI, and CDI scores contribute to the computation of the overall GOHI 2022 score. By comparing the ranking and the overall scores among the seven regions and across 160 countries/territories, we have not only derived an overall profile of the GOHI 2022 scores, but also assessed the GOHI framework. We also compared rankings of indicators and sub I-indicators to provide greater clarity on the strengths and weaknesses of each region within the One Health domains.

Results

The GOHI 2022 performance reveals significant disparities between countries/territories ranged from 39.03 to 70.61. The global average score of the GOHI 2022 is 54.82. The average score for EDI, IDI, and CDI are 46.57, 58.01, and 57.25, respectively. In terms of global rankings, countries from North America, Europe and Central Asia, East Asia and Pacific present higher scores. In terms of One Health domains of CDI, the lowest scores are observed in antimicrobial resistance (median: 43.09), followed by food security (median: 53.78), governance (median: 54.77), climate change (median: 64.12) and zoonotic diseases (median: 69.23). Globally, the scores of GOHI vary spatially, with the highest score in North America while lowest in sub-Saharan Africa. In addition, evidence shows associations between the socio-demographic profile of countries/territories and their GOHI performance in certain One Health scenarios.

Conclusion

The objective of GOHI is to guide impactful strategies for enhancing capacity building in One Health. With advanced technology and an annually updated database, intensifying efforts to refine GOHI's data-mining methodologies become imperative. The goal is to offer profound insights into disparities and progressions in practical One Health implementation, particularly in anticipation of future pandemics.

China's application of the One Health approach in addressing public health threats at the human-animal-environment interface: Advances and challenges

Background

Due to emerging issues such as global climate change and zoonotic disease pandemics, the One Health approach has gained more attention since the turn of the 21st century. Although One Health thinking has deep roots and early applications in Chinese history, significant gaps exist in China's real-world implementation at the complex interface of the human-animal-environment.

Methods

We abstracted the data from the global One Health index study and analysed China's performance in selected fields based on Structure-Process-Outcome model. By comparing China to the Belt & Road and G20 countries, the advances and gaps in China's One Health performance were determined and analysed.

Findings

For the selected scientific fields, China generally performs better in ensuring food security and controlling antimicrobial resistance and worse in addressing climate change. Based on the SPO model, the "structure" indicators have the highest proportion (80.00%) of high ranking and the "outcome" indicators have the highest proportion (20.00%) of low ranking. When compared with Belt and Road countries, China scores above the median in almost all indicators (16 out of 18) under the selected scientific fields. When compared with G20 countries, China ranks highest in food security (scores 72.56 and ranks 6th), and lowest in climate change (48.74, 11th).

Conclusion

Our results indicate that while China has made significant efforts to enhance the application of the One Health approach in national policies, it still faces challenges in translating policies into practical measures. It is recommended that a holistic One Health action framework be established for China in accordance with diverse social and cultural contexts, with a particular emphasis on overcoming data barriers and mobilizing stakeholders both domestically and globally. Implementation mechanisms, with clarified stakeholder responsibilities and incentives, should be improved along with top-level design.

Assessing food security performance from the One Health concept: an evaluation tool based on the Global One Health Index

BACKGROUND

Food systems instantiate the complex interdependencies across humans, physical environments, and other organisms. Applying One Health approaches for agri-food system transformation, which adopts integrated and unifying approaches to optimize the overall health of humans, animals, plants, and environments, is crucial to enhance the sustainability of food systems. This study develops a potential assessment tool, named the global One Health index-Food Security (GOHI-FS), aiming to evaluate food security performance across countries/territories from One Health perspective and identify relevant gaps that need to be improved for sustainable food systems.

METHODS

We comprehensively reviewed existing frameworks and elements of food security. The indicator framework of GOHI-FS was conceptualized following the structure-process-outcome model and confirmed by expert advisory. Publicly available data in 2020 was collected for each indicator. The weighting strategy was determined by the Fuzzy Analytical Hierarchy Process. The data for each indicator was normalized and aggregated by weighted arithmetic mean. Linear regressions were performed to evaluate the associations of GOHI-FS with health and social-economic indicators.

RESULTS

The GOHI-FS includes 5 first-level indicators, 19 second-level indicators and 45 third-level indicators. There were 146 countries/territories enrolled for evaluation. The highest average score of first-level indicators was Nutrition (69.8) and the lowest was Government Support and Response (31.3). There was regional heterogeneity of GOHI-FS scores. Higher median scores with interquartile range (IQR) were shown in North America (median: 76.1, IQR: 75.5-76.7), followed by Europe and Central Asia (median: 66.9, IQR: 60.1-74.3), East Asia and the Pacific (median: 60.6, IQR: 55.5-68.7), Latin America and the Caribbean (median: 60.2, IQR: 57.8-65.0), Middle East and North Africa (median: 56.6, IQR: 52.0-62.8), South Asia (median: 51.1, IQR: 46.7-53.8), and sub-Saharan Africa (median: 41.4, IQR: 37.2-46.5). We also found significant associations between GOHI-FS and GDP per capita, socio-demographic index, health expenditure and life expectancy.

CONCLUSIONS

GOHI-FS is a potential assessment tool to understand the gaps in food security across countries/territories under the One Health concept. The pilot findings suggest notable gaps for sub-Saharan Africa in numerous aspects. Broad actions are needed globally to promote government support and response for food security.

Toward One Health: a spatial indicator system to model the facilitation of the spread of zoonotic diseases

Recurrent outbreaks of zoonotic infectious diseases highlight the importance of considering the interconnections between human, animal, and environmental health in disease prevention and control. This has given rise to the concept of One Health, which recognizes the interconnectedness of between human and animal health within their ecosystems. As a contribution to the One Health approach, this study aims to develop an indicator system to model the facilitation of the spread of zoonotic diseases. Initially, a literature review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement to identify relevant indicators related to One Health. The selected indicators focused on demographics, socioeconomic aspects, interactions between animal and human populations and water bodies, as well as environmental conditions related to air quality and climate. These indicators were characterized using values obtained from the literature or calculated through distance analysis, geoprocessing tasks, and other methods. Subsequently, Multi-Criteria Decision-Making (MCDM) techniques, specifically the Entropy and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods, were utilized to combine the indicators and create a composite metric for assessing the spread of zoonotic diseases. The final indicators selected were then tested against recorded zoonoses in the Valencian Community (Spain) for 2021, and a strong positive correlation was identified. Therefore, the proposed indicator system can be valuable in guiding the development of planning strategies that align with the One Health principles. Based on the results achieved, such strategies may prioritize the preservation of natural landscape features to mitigate habitat encroachment, protect land and water resources, and attenuate extreme atmospheric conditions.

Increased interleukin-6 is associated with long COVID-19: a systematic review and meta-analysis

BACKGROUND

Coronavirus disease 2019 (COVID-19) can involve persistence, sequelae, and other clinical complications that last weeks to months to evolve into long COVID-19. Exploratory studies have suggested that interleukin-6 (IL-6) is related to COVID-19; however, the correlation between IL-6 and long COVID-19 is unknown. We designed a systematic review and meta-analysis to assess the relationship between IL-6 levels and long COVID-19.

METHODS

Databases were systematically searched for articles with data on long COVID-19 and IL-6 levels published before September 2022. A total of 22 published studies were eligible for inclusion following the PRISMA guidelines. Analysis of data was undertaken by using Cochran's Q test and the Higgins I-squared (I²) statistic for heterogeneity. Random-effect meta-analyses were conducted to pool the IL-6 levels of long COVID-19 patients and to compare the differences in IL-6 levels among the long COVID-19, healthy, non-postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (non-PASC), and acute COVID-19 populations. The funnel plot and Egger's test were used to assess potential publication bias. Sensitivity analysis was used to test the stability of the results.

RESULTS

An increase in IL-6 levels was observed after SARS-CoV-2 infection. The pooled estimate of IL-6 revealed a mean value of 20.92 pg/ml (95% CI = 9.30-32.54 pg/ml, I² = 100%, P < 0.01) for long COVID-19 patients. The forest plot showed high levels of IL-6 for long COVID-19 compared with healthy controls (mean difference = 9.75 pg/ml, 95% CI = 5.75-13.75 pg/ml, I² = 100%, P < 0.00001) and PASC category (mean difference = 3.32 pg/ml, 95% CI = 0.22-6.42 pg/ml, I² = 88%, P = 0.04). The symmetry of the funnel plots was not obvious, and Egger's test showed that there was no significant small study effect in all groups.

CONCLUSIONS

This study showed that increased IL-6 correlates with long COVID-19. Such an informative revelation suggests IL-6 as a basic determinant to predict long COVID-19 or at least inform on the "early stage" of long COVID-19.

Assessment of integrated patterns of human-animal-environment health: a holistic and stratified analysis

BACKGROUND

Data-driven research is a very important component of One Health. As the core part of the global One Health index (GOHI), the global One Health Intrinsic Drivers index (IDI) is a framework for evaluating the baseline conditions of human-animal-environment health. This study aims to assess the global performance in terms of GOH-IDI, compare it across different World Bank regions, and analyze the relationships between GOH-IDI and national economic levels.

METHODS

The raw data among 146 countries were collected from authoritative databases and official reports in November 2021. Descriptive statistical analysis, data visualization and manipulation, Shapiro normality test and ridge maps were used to evaluate and identify the spatial and classificatory distribution of GOH-IDI. This paper uses the World Bank regional classification and the World Bank income groups to analyse the relationship between GOH-IDI and regional economic levels, and completes the case studies of representative countries.

RESULTS

The performance of One Health Intrinsic Driver in 146 countries was evaluated. The mean (standard deviation, SD) score of GOH-IDI is 54.05 (4.95). The values (mean SD) of different regions are North America (60.44, 2.36), Europe and Central Asia (57.73, 3.29), Middle East and North Africa (57.02, 2.56), East Asia and Pacific (53.87, 5.22), Latin America and the Caribbean (53.75, 2.20), South Asia (52.45, 2.61) and sub-Saharan Africa (48.27, 2.48). Gross national income per capita was moderately correlated with GOH-IDI (R2 = 0.651, Deviance explained = 66.6%, P < 0.005). Low income countries have the best performance in some secondary indicators, including Non-communicable Diseases and Mental Health and Health risks. Five indicators are not statistically different at each economic level, including Animal Epidemic Disease, Animal Biodiversity, Air Quality and Climate Change, Land Resources and Environmental Biodiversity.

CONCLUSIONS

The GOH-IDI is a crucial tool to evaluate the situation of One Health. There are inter-regional differences in GOH-IDI significantly at the worldwide level. The best performing region for GOH-IDI was North America and the worst was sub-Saharan Africa. There is a positive correlation between the GOH-IDI and country economic status, with high-income countries performing well in most indicators. GOH-IDI facilitates researchers' understanding of the multidimensional situation in each country and invests more attention in scientific questions that need to be addressed urgently.

Multi-modal deep learning based on multi-dimensional and multi-level temporal data can enhance the prognostic prediction for multi-drug resistant pulmonary tuberculosis patients

Despite the advent of new diagnostics, drugs and regimens, multi-drug resistant pulmonary tuberculosis (MDR-PTB) remains a global health threat. It has a long treatment cycle, low cure rate and heavy disease burden. Factors such as demographics, disease characteristics, lung imaging, biomarkers, therapeutic schedule and adherence to medications are associated with MDR-PTB prognosis. However, thus far, the majority of existing studies have focused on predicting treatment outcomes through static single-scale or low dimensional information. Hence, multi-modal deep learning based on dynamic data for multiple dimensions can provide a deeper understanding of personalized treatment plans to aid in the clinical management of patients.