Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Methodological choices in brucellosis burden of disease assessments: A systematic review

Background Foodborne and zoonotic diseases such as brucellosis present many challenges to public health and economic welfare. Increasingly, researchers and public health institutes use disability-adjusted life years (DALYs) to generate a comprehensive comparison of the population health impact of these conditions. DALYs calculations, however, entail a number of methodological choices and assumptions, with data gaps and uncertainties to accommodate. Thisreview identifies existing brucellosis burden of disease studies and analyzes their methodological choices, assumptions, and uncertainties. It supports the Global Burden of Animal Diseases programme in the development of a systematic methodology to describe the impact of animal diseases on society, including human health. Methods/Principal findings A systematic search for brucellosis burden of disease calculations was conducted in pre-selected international and grey literature databases. Using a standardized reporting framework, we evaluated each estimate on a variety of key methodological assumptions necessary to compute a DALY. Fourteen studies satisfied the inclusion criteria (human brucellosis and quantification of DALYs). One study reported estimates at the global level, the rest were national or subnational assessments. Data regarding different methodological choices were extracted, including detailed assessments of the adopted disease models. Most studies retrieved brucellosis epidemiological data from administrative registries. Incidence data were often estimated on the basis of laboratory-confirmed tests. Not all studies included mortality estimates (Years of Life Lost) in their assessments due to lack of data or the assumption that brucellosis is not a fatal disease. Only two studies used a model with variable health states and corresponding disability weights. The rest used a simplified singular health state approach. Wide variation was seen in the duration chosen for brucellosis, ranging from 2 weeks to 4.5 years, irrespective of the whether a chronic state was included. Conclusion Available brucellosis burden of disease assessments vary widely in their methodology and assumptions. Further research is needed to better characterize the clinical course of brucellosis and to estimate case-fatality rates. Additionally, reporting of methodological choices should be improved to enhance transparency and comparability of estimates. These steps will increase the value of these estimates for policy makers

Methodological framework for World Health Organization estimates of the global burden of foodborne disease

Background: The Foodborne Disease Burden Epidemiology Reference Group (FERG) was established in 2007 by the World Health Organization to estimate the global burden of foodborne diseases (FBDs). This paper describes the methodological framework developed by FERG's Computational Task Force to transform epidemiological information into FBD burden estimates. Methods and Findings: The global and regional burden of 31 FBDs was quantified, along with limited estimates for 5 other FBDs, using Disability-Adjusted Life Years in a hazard- and incidence-based approach. To accomplish this task, the following workflow was defined: outline of disease models and collection of epidemiological data; design and completion of a database template; development of an imputation model; identification of disability weights; probabilistic burden assessment; and estimating the proportion of the disease burden by each hazard that is attributable to exposure by food (i.e., source attribution). All computations were performed in R and the different functions were compiled in the R package 'FERG'. Traceability and transparency were ensured by sharing results and methods in an interactive way with all FERG members throughout the process. Conclusions: We developed a comprehensive framework for estimating the global burden of FBDs, in which methodological simplicity and transparency were key elements. All the tools developed have been made available and can be translated into a user-friendly national toolkit for studying and monitoring food safety at the local level

Ethical Issues in AI-Enabled Disease Surveillance: Perspectives from Global Health

Infectious diseases, as COVID-19 is proving, pose a global health threat in an interconnected world. In the last 20 years, resistant infectious diseases such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), H1N1 influenza (swine flu), Ebola virus, Zika virus, and now COVID-19 have been impacting global health defences, and aggressively flourishing with the rise of global travel, urbanization, climate change, and ecological degradation. In parallel, this extraordinary episode in global human health highlights the potential for artificial intelligence (AI)-enabled disease surveillance to collect and analyse vast amounts of unstructured and real-time data to inform epidemiological and public health emergency responses. The uses of AI in these dynamic environments are increasingly complex, challenging the potential for human autonomous decisions. In this context, our study of qualitative perspectives will consider a responsible AI framework to explore its potential application to disease surveillance in a global health context. Thus far, there is a gap in the literature in considering these multiple and interconnected levels of disease surveillance and emergency health management through the lens of a responsible AI framework

On The Application Of Computational Modeling To Complex Food Systems Issues

Transdisciplinary food systems research aims to merge insights from multiple fields, often revealing confounding, complex interactions. Computational modeling offers a means to discover patterns and formulate novel solutions to such systems-level problems. The best models serve as hubs—or boundary objects—which ground and unify a collaborative, iterative, and transdisciplinary process of stakeholder engagement. This dissertation demonstrates the application of agent-based modeling, network analytics, and evolutionary computational optimization to the pressing food systems problem areas of livestock epidemiology and global food security. It is comprised of a methodological introduction, an executive summary, three journal-article formatted chapters, and an overarching discussion section. Chapter One employs an agent-based computer model (RUSH-PNBM v.1.1) developed to study the potential impact of the trend toward increased producer specialization on resilience to catastrophic epidemics within livestock production chains. In each run, an infection is introduced and may spread according to probabilities associated with the various modes of contact between hog producer, feed mill, and slaughter plant agents. Experimental data reveal that more-specialized systems are vulnerable to outbreaks at lower spatial densities, have more abrupt percolation transitions, and are characterized by less-predictable outcomes; suggesting that reworking network structures may represent a viable means to increase biosecurity. Chapter Two uses a calibrated, spatially-explicit version of RUSH-PNBM (v.1.2) to model the hog production chains within three U.S. states. Key metrics are calculated after each run, some of which pertain to overall network structures, while others describe each actor’s positionality within the network. A genetic programming algorithm is then employed to search for mathematical relationships between multiple individual indicators that effectively predict each node’s vulnerability. This “meta-metric” approach could be applied to aid livestock epidemiologists in the targeting of biosecurity interventions and may also be useful to study a wide range of complex network phenomena. Chapter Three focuses on food insecurity resulting from the projected gap between global food supply and demand over the coming decades. While no single solution has been identified, scholars suggest that investments into multiple interventions may stack together to solve the problem. However, formulating an effective plan of action requires knowledge about the level of change resulting from a given investment into each wedge, the time before that effect unfolds, the expected baseline change, and the maximum possible level of change. This chapter details an evolutionary-computational algorithm to optimize investment schedules according to the twin goals of maximizing global food security and minimizing cost. Future work will involve parameterizing the model through an expert informant advisory process to develop the existing framework into a practicable food policy decision-support tool

Comparison of community-wide, integrated mass drug administration strategies for schistosomiasis and soil-transmitted helminthiasis: a cost-eff ectiveness modelling study

Background More than 1·5 billion people are aff ected by schistosomiasis or soil-transmitted helminthiasis. WHO’s recommendations for mass drug administration (MDA) against these parasitic infections emphasise treatment of school-aged children, using separate treatment guidelines for these two helminthiases groups. We aimed to evaluate the cost-eff ectiveness of expanding integrated MDA to the entire community in four settings in Côte d’Ivoire. Methods We extended previously published, dynamic, age-structured models of helminthiases transmission to simulate costs and disability averted with integrated MDA (of praziquantel and albendazole) for schistosomiasis and soil-transmitted helminthiasis. We calibrated the model to data for prevalence and intensity of species-specifi c helminth infection from surveys undertaken in four communities in Côte d’Ivoire between March, 1997, and September, 2010. We simulated a 15-year treatment programme with 75% coverage in only school-aged children; school-aged children and preschool-aged children; adults; and the entire community. Treatment costs were estimated at US$0·74 for school-aged children and$1·74 for preschool-aged children and adults. The incremental costeff ectiveness ratio (ICER) was calculated in 2014 US dollars per disability-adjusted life-year (DALY) averted. Findings Expanded community-wide treatment was highly cost eff ective compared with treatment of only school-aged children (ICER $167 per DALY averted) and WHO guidelines (ICER$127 per DALY averted), and remained highly cost eff ective even if treatment costs for preschool-aged children and adults were ten times greater than those for school-aged children. Community-wide treatment remained highly cost eff ective even when elimination of helminth infections was not achieved. These fi ndings were robust across the four diverse communities in Côte d’Ivoire, only one of which would have received annual MDA for both schistosomiasis and soil-transmitted helminthiasis under the latest WHO guidelines. Treatment every 6 months was also highly cost eff ective in three out of four communities. Interpretation Integrated, community-wide MDA programmes for schistosomiasis and soil-transmitted helminthiasis can be highly cost eff ective, even in communities with low disease burden in any helminth group. These results support an urgent need to re-evaluate current global guidelines for helminthiases control programmes to include community-wide treatment, increased treatment frequency, and consideration for lowered prevalence thresholds for integrated treatment

What would framework for policy responses to pandemic diseases look like?

This scoping paper discusses how information on government policy responses to pandemic diseases (e.g. non-pharmaceutical interventions (NPIs) and public health and social measures (PHSMs), and including behavioural rules, testing and contact tracing systems, policies to incentivise vaccination, etc.) have, can, and should be collected, analysed, and incorporated into the broader array of pandemic data (e.g. epidemiological, virological, behavioural, etc.) to build preparedness. It draws on both the academic and policy literature, as well as a series of interviews with policymakers and researchers, as well as a guided stakeholder workshop held in December 2022

Monitoring of selected health indicators in children living in a copper mine development area in northwestern Zambia

The epidemiology of malaria, anaemia and malnutrition in children is potentially altered in mining development areas. In a copper extraction project in northwestern Zambia, a health impact assessment (HIA) was commissioned to predict, manage and monitor health impacts. Two cross-sectional surveys were conducted: at baseline prior to project development (2011) and at four years into development (2015). Prevalence of Plasmodium falciparum, anaemia and stunting were assessed in under-five-year-old children, while hookworm infection was assessed in children aged 9-14 years in communities impacted and comparison communities not impacted by the project. P. falciparum prevalence was significantly higher in 2015 compared to 2011 in both impacted and comparison communities (odds ratio (OR) = 2.51 and OR = 6.97, respectively). Stunting was significantly lower in 2015 in impacted communities only (OR = 0.63). Anaemia was slightly lower in 2015 compared to baseline in both impacted and comparison communities. Resettlement due to the project and migration background (i.e., moving into the area within the past five years) were generally associated with better health outcomes in 2015. We conclude that repeated cross-sectional surveys to monitor health in communities impacted by projects should become an integral part of HIA to deepen the understanding of changing patterns of health and support implementation of setting-specific public health measures

Resource extraction projects and health: evidence from cross-national and national data sources

Implementation of resource extraction projects often triggers a series of complex environmental and social-ecological changes. These changes may include alterations in land use (i.e., from forestry and vegetation to infrastructure and mining), an increase in construction activities (new buildings such as houses, schools and hospitals), population increase (more people, more road traffic), urbanization, movement and installation of heavy machinery, increases in employment and business opportunities and household resettlements. These changes can positively or negatively affect health of the population living within mining areas and beyond. For instance, one common and most visible contribution of resource extraction projects is the impact on income generation. This has been widely studied in the economic literature, showing both positive and negative effects between natural resources activities and income generation. Positively, governments can benefit from the generated resource rents and royalties. Individually, people can earn income from employment and business opportunities. The revenue generated can help governments to re-invest in other sectors, including health, education and infrastructure. Negatively, the sharp increase in economic development in one sector can hamper growth in other sectors causing what is known as the Dutch disease. The presence of resource-income dependency can as well fuel local conflicts, political instability, weak institutions and corruption, and ultimately result in a slow development process causing the resource curse. One major aspect of resource extraction projects which is often under-represented is its implication on health. Health is influenced both directly and indirectly through activities involved in resource extraction projects. Evidence suggests that resource extraction projects can positively or negatively affect health and well-being of the population therein. This directly relates to the Sustainable Development Goal (SDG) number 3 (SDG3) of the SDGs 2030 agenda. SDG3 aims to ensure healthy lives and promote well-being for all at all ages. Health has a central place in SDG3, and it is also central to the three dimensions of sustainable development: environment, society and economy. Resource extract projects can act on determinants of health and ultimately contribute to improve lives and well-being. An increase in income can promote access to better care, construction of health care post and hospitals can contribute to improving healthcare delivery, constructions of water points can improve the availability of clean water, and lastly but not least, the provision of health education can contribute to knowledge and disease prevention. On the other hand, resource extraction projects can cause environmental disruption linked to air, water and land pollution. This can further result in disease outcomes. Combustion activities associated with the extraction process can result in the presence of small particulate matter (PM2.5) in the atmosphere and further lead to respiratory and cardiovascular diseases. Toxic substances often used in the extraction process can leak into the environment and result in cancer diseases. The presence of both positive and negative health outcomes in resource extraction areas present an opportunity to systematically study the contribution of resource extraction projects to health outcomes. This PhD thesis embarked on this particular opportunity and studied the association between resource extraction projects and population health indicators in three layered perspectives: global, national and subnational