Effective public health decision-making relies on rigorous evidence synthesis and transparent processes to facilitate its use. However, existing methods guidance has primarily been developed within clinical medicine and may not sufficiently address the complexities of public health, such as population-level considerations, multiple evidence streams, and time-sensitive decision-making. This work contributes to the European Centre for Disease Prevention and Control initiative on methods guidance development for evidence synthesis and evidence-based public health advice by systematically identifying and mapping guidance from health and health-related disciplines.

Structured searches were conducted across multiple scientific databases and websites of key institutions, followed by screening and data coding. Of the 17,386 records identified, 247 documents were classified as ‘guidance products’ providing a set of principles or recommendations on the overall process of developing evidence synthesis and evidence-based advice. While many were classified as ‘generic’ in scope, a majority originated from clinical medicine and focused on systematic reviews of intervention effects. Only 41 documents explicitly addressed public health. Key gaps included approaches for rapid evidence synthesis and decision-making and methods for synthesising evidence from laboratory research, disease burden, and prevalence studies.

The findings highlight a need for methodological development that aligns with the realities of public health practice, particularly in emergency contexts. This review provides a key repository for methodologists, researchers, and decision-makers in public health, as well as clinical medicine and health care in Europe and worldwide, supporting the evolution of more inclusive and adaptable approaches to public health evidence synthesis and decision-making.

Creatine is a vital bioenergetic compound that remains largely overlooked within food systems despite its well-established role in human health and performance. Unlike creatinine – a downstream breakdown product of creatine metabolism commonly measured as a biomarker of kidney function – creatine functions as an energy buffer, facilitating the rapid regeneration of ATP in tissues with high metabolic demands such as skeletal muscle, brain and heart. Although a portion of daily creatine requirements is met through endogenous synthesis, dietary intake – primarily from animal-source foods – remains essential to maintain optimal physiological levels. Emerging evidence indicates that suboptimal creatine status, or creatine insufficiency, may be widespread, particularly among vegetarians, vegans, older adults, individuals with chronic illness and those with increased energy needs. This paper examines the evolving role of creatine across four domains: its natural occurrence in foods, incorporation into fortified food products, use as a dietary supplement and potential future classification as a pharmaceutical agent. Special emphasis is placed on differences in regulatory status, intended use, dosage, labelling and public health implications. In light of mounting evidence that creatine insufficiency may contribute to adverse outcomes – including impaired cognition, reduced muscular performance and vulnerability to stressors – integrating creatine into food policy and nutrition strategies represents a promising, scalable and preventive approach to improve population health.

Almost a decade has passed since a DEFRA consultation concluded that existing legislation governing the UK puppy trade was “outdated, inflexible, incompatible with current welfare legislation and cumbersome for both enforcers and businesses”. The rapid outgrowth of the trade’s governing legislature, fuelled by contemporary consumer culture and the high degree of trader anonymity provided by the internet, has enabled a high-volume, untraceable and profit-driven market to evolve. Increased demand for puppies, exacerbated by social media trends and the COVID-19 pandemic, is sustained by an online medium that both encourages and capitalises upon modern-day ‘click-and-collect’ purchase behaviour. Moreover, the internet has only intensified the demand for pedigree and designer crossbreeds, many of which are shown to suffer lifelong physiological disorders caused by the positive phenotyping selection necessary to achieve breed standards. These factors have made puppies an attractively lucrative, low-risk commodity. Evidence of multi-level fraud and organised crime involvement has been revealed along the supply chain, resulting in systemic canine health and welfare issues. Whilst large-scale breeding operations reportedly smuggle unvaccinated puppies onto the British market from endemic (rabies, Leishmania) countries, high densities of pet dogs in urban areas is reportedly leaving high faecal-saturation levels, spreading anthelmic- and antibiotic-resistant pathogens. Meanwhile, unsafe concentrations of ectoparasiticides are detected in rivers and lakes. This review collates evidence from available sources that illustrate the current nature and impact of inadequate regulation in the UK puppy trade, aiming to support stakeholders in their efforts for essential and comprehensive regulatory reform.

Introduction: The COVID-19 pandemic highlighted the critical need for robust crisis standards of care (CSC) protocols to handle extreme strain when scarce resources require rationing. Evaluating how such policies might perform in the real world remains paramount; however, to date, study of their performance has been limited to retrospective cohort designs using virtual simulations.1,2 The Sequential Organ Failure Assessment score (SOFA)—a composite 0-24 score of organ dysfunction incorporating neurologic, pulmonary, cardiovascular, hematologic, hepatobiliary, and renal subscores—remains ubiquitous in nearly all crisis standards of care protocols3,4,5 despite concerns regarding the utilization and potentially exacerbating existing racial inequities.5 Existing simulation studies have handled missing SOFA values by either imputing zero or assuming data are missing at random, followed by complex computational statistical modeling.6,7 This approach may introduce significant bias, with larger outcome implications than missing data in other forms of medical research, as these values directly affect decisions on who receives life-sustaining therapies. Our study aims to better understand the frequency, structure, and consequence of missing data in CSC simulation studies.

This article examines the evolution of breastfeeding practices in twentieth-century China, focusing on the complex interplay between medical knowledge, state policies and social transformation. This study demonstrates how medical recommendations concerning lactation timing, intervals and weaning were shaped by factors beyond purely scientific developments. Mid-twentieth-century biochemical studies validated traditional practices while revolutionising attitudes towards colostrum, marking a critical juncture in Chinese infant nutrition science. Following the establishment of the People’s Republic in 1949, maternal and child health initiatives underwent fundamental changes. Drawing on new understanding of breast milk’s nutritional value, health benefits, and economic advantages, healthcare professionals and state authorities actively promoted scientific breastfeeding methods. Their multifaceted approach reflected both the dissemination of medical knowledge and the state’s strategic consideration of female labour force participation. This study analyses how women’s liberation from feudal constraints, changing employment patterns, Soviet medical influence, and advances in artificial feeding technologies shaped breastfeeding practices. Through examining the intersection of medical advice, health policies, and women’s labour liberation, it provides fresh insights into the evolution of breastfeeding discourse within Chinese medical circles. Situating these developments within broader medical, social and cultural contexts, this research not only illuminates the multiple factors that shaped modern Chinese infant feeding practices but also contributes to our understanding of the complex relationships between medical practice, state policy, and social change in twentieth-century China.

This study investigates the prevalence of coliform contamination in fresh milk and the occurrence of multidrug-resistant (MDR) bacteria within poultry environments on an integrated farm in Minna, Niger State. Bacterial isolates obtained from raw milk, poultry cloacal swabs, and intestinal swabs from commensal rats included Salmonella, Escherichia coli, and Klebsiella species. These isolates were screened for extended-spectrum beta-lactamase (ESBL) production and antimicrobial resistance profiles. The results revealed a high level of bacterial contamination in milk samples, with significant associations between contamination levels and poor hygiene practices during milking and handling. Moreover, ESBL-producing bacteria displaying resistance to critically important antibiotics such as third-generation cephalosporins and fluoroquinolones were identified across both dairy and poultry sources. These findings highlight a pressing public health concern and emphasize the need for improved biosecurity, hygiene interventions and integrated antimicrobial resistance surveillance to safeguard food safety and reduce the spread of MDR pathogens in animal-source foods.

Numerous symposia and conferences have been held to discuss the promise of Artificial Intelligence (AI). Many center on its potential to transform fields like health and medicine, law, education, business, and more. Further, while many AI-focused events include those data scientists involved in developing foundational models, to our knowledge, there has been little attention on AI’s role for data science and the data scientist. In a new symposium series with its inaugural debut in December 2024 titled AI for Data Science, thought leaders convened to discuss both the promises and challenges of integrating AI into the workflows of data scientists. A keynote address by Michael Pencina from Duke University together with contributions from three panels covered a wide range of topics including rigor, reproducibility, the training of current and future data scientists, and the potential of AI’s integration in public health.