A Quantitative Approach to the Prioritization of Zoonotic Diseases in North America: A Health Professionals’ Perspective

Background

Currently, zoonoses account for 58% to 61% of all communicable diseases causing illness in humans globally and up to 75% of emerging human pathogens. Although the impact of zoonoses on animal health and public health in North America is significant, there has been no published research involving health professionals on the prioritization of zoonoses in this region.

Methodology/Principal Findings

We used conjoint analysis (CA), a well-established quantitative method in market research, to identify the relative importance of 21 key characteristics of zoonotic diseases for their prioritization in Canada and the US. Relative importance weights from the CA were used to develop a point-scoring system to derive a recommended list of zoonoses for prioritization in Canada and the US. Study participants with a background in epidemiology, public health, medical sciences, veterinary sciences and infectious disease research were recruited to complete the online survey (707 from Canada and 764 from the US). Hierarchical Bayes models were fitted to the survey data to derive CA-weighted scores for disease criteria. Scores were applied to 62 zoonotic diseases to rank diseases in order of priority.

Conclusions/Significance

We present the first zoonoses prioritization exercise involving health professionals in North America. Our previous study indicated individuals with no prior knowledge in infectious diseases were capable of producing meaningful results with acceptable model fits (79.4%). This study suggests health professionals with some knowledge in infectious diseases were capable of producing meaningful results with better-fitted models than the general public (83.7% and 84.2%). Despite more similarities in demographics and model fit between the combined public and combined professional groups, there was more uniformity across priority lists between the Canadian public and Canadian professionals and between the US public and US professionals. Our study suggests that CA can be used as a potential tool for the prioritization of zoonoses.     

A stakeholder-informed approach to the identification of criteria for the prioritization of zoonoses in Canada

Background

Zoonotic diseases account for over 60% of all communicable diseases causing illness in humans and 75% of recently emerging infectious diseases. As limited resources are available for the control and prevention of zoonotic diseases, it is necessary to prioritize diseases in order to direct resources into those with the greatest needs. The selection of criteria for prioritization has traditionally been on the basis of expert opinion; however, details of the methods used to identify criteria from expert opinion often are not published and a full range of criteria may not be captured by expert opinion.

Methodology/Principal Findings

This study used six focus groups to identify criteria for the prioritization of zoonotic diseases in Canada. Focus groups included people from the public, animal health professionals and human health professionals. A total of 59 criteria were identified for prioritizing zoonotic diseases. Human-related criteria accounted for the highest proportion of criteria identified (55%), followed by animal-related criteria (26%) then pathogen/disease-related criteria (19%).Similarities and differences were observed in the identification and scoring of criteria for disease prioritization between groups; the public groups were strongly influenced by the individual-level of disease burden, the responsibility of the scientific community in disease prioritization and the experiences of recent events while the professional groups were influenced by the societal- and population-level of disease burden and political and public pressure.

Conclusions/Significance

This was the first study to describe a mixed semi-quantitative and qualitative approach to deriving criteria for disease prioritization. This was also the first study to involve the opinion of the general public regarding disease prioritization. The number of criteria identified highlights the difficulty in prioritizing zoonotic diseases. The method presented in this paper has formulated a comprehensive list of criteria that can be used to inform future disease prioritization studies.     

The Burden of Parasitic Zoonoses in Nepal: A Systematic Review

Background

Parasitic zoonoses (PZs) pose a significant but often neglected threat to public health, especially in developing countries. In order to obtain a better understanding of their health impact, summary measures of population health may be calculated, such as the Disability-Adjusted Life Year (DALY). However, the data required to calculate such measures are often not readily available for these diseases, which may lead to a vicious circle of under-recognition and under-funding.

Methodology

We examined the burden of PZs in Nepal through a systematic review of online and offline data sources. PZs were classified qualitatively according to endemicity, and where possible a quantitative burden assessment was conducted in terms of the annual number of incident cases, deaths and DALYs.

Principal Findings

Between 2000 and 2012, the highest annual burden was imposed by neurocysticercosis and congenital toxoplasmosis (14,268 DALYs [95% Credibility Interval (CrI): 5450–27,694] and 9255 DALYs [95% CrI: 6135–13,292], respectively), followed by cystic echinococcosis (251 DALYs [95% CrI: 105–458]). Nepal is probably endemic for trichinellosis, toxocarosis, diphyllobothriosis, foodborne trematodosis, taeniosis, and zoonotic intestinal helminthic and protozoal infections, but insufficient data were available to quantify their health impact. Sporadic cases of alveolar echinococcosis, angiostrongylosis, capillariosis, dirofilariosis, gnathostomosis, sparganosis and cutaneous leishmaniosis may occur.

Conclusions/Significance

In settings with limited surveillance capacity, it is possible to quantify the health impact of PZs and other neglected diseases, thereby interrupting the vicious circle of neglect. In Nepal, we found that several PZs are endemic and are imposing a significant burden to public health, higher than that of malaria, and comparable to that of HIV/AIDS. However, several critical data gaps remain. Enhanced surveillance for the endemic PZs identified in this study would enable additional burden estimates, and a more complete picture of the impact of these diseases.     

Research options for controlling zoonotic disease in India, 2010-2015

Background

Zoonotic infections pose a significant public health challenge for low- and middle-income countries and have traditionally been a neglected area of research. The Roadmap to Combat Zoonoses in India (RCZI) initiative conducted an exercise to systematically identify and prioritize research options needed to control zoonoses in India.

Methods and Findings

Priority setting methods developed by the Child Health and Nutrition Research Initiative were adapted for the diversity of sectors, disciplines, diseases and populations relevant for zoonoses in India. A multidisciplinary group of experts identified priority zoonotic diseases and knowledge gaps and proposed research options to address key knowledge gaps within the next five years. Each option was scored using predefined criteria by another group of experts. The scores were weighted using relative ranks among the criteria based upon the feedback of a larger reference group. We categorized each research option by type of research, disease targeted, factorials, and level of collaboration required. We analysed the research options by tabulating them along these categories. Seventeen experts generated four universal research themes and 103 specific research options, the majority of which required a high to medium level of collaboration across sectors. Research options designated as pertaining to ‘social, political and economic’ factorials predominated and scored higher than options focussing on ecological, genetic and biological, or environmental factors. Research options related to ‘health policy and systems’ scored highest while those related to ‘research for development of new interventions’ scored the lowest.

Conclusions

We methodically identified research themes and specific research options incorporating perspectives of a diverse group of stakeholders. These outputs reflect the diverse nature of challenges posed by zoonoses and should be acceptable across diseases, disciplines, and sectors. The identified research options capture the need for ‘actionable research’ for advancing the prevention and control of zoonoses in India.     

A random set scoring model for prioritization of disease candidate genes using protein complexes and data-mining of GeneRIF,OMIM and PubMed records

Background

Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mining exercise on the biomedical literature can establish the phenotypic profile of genes with respect to their connection to disease phenotypes. The importance of protein-protein interaction networks in the genetic heterogeneity of common diseases or complex traits is becoming increasingly recognized. Thus, the development of a network-based approach combined with phenotypic profiling would be useful for disease gene prioritization.

Results

We developed a random-set scoring model and implemented it to quantify phenotype relevance in a network-based disease gene-prioritization approach. We validated our approach based on different gene phenotypic profiles, which were generated from PubMed abstracts, OMIM, and GeneRIF records. We also investigated the validity of several vocabulary filters and different likelihood thresholds for predicted protein-protein interactions in terms of their effect on the network-based gene-prioritization approach, which relies on text-mining of the phenotype data. Our method demonstrated good precision and sensitivity compared with those of two alternative complex-based prioritization approaches. We then conducted a global ranking of all human genes according to their relevance to a range of human diseases. The resulting accurate ranking of known causal genes supported the reliability of our approach. Moreover, these data suggest many promising novel candidate genes for human disorders that have a complex mode of inheritance.

Conclusion

We have implemented and validated a network-based approach to prioritize genes for human diseases based on their phenotypic profile. We have devised a powerful and transparent tool to identify and rank candidate genes. Our global gene prioritization provides a unique resource for the biological interpretation of data from genome-wide association studies, and will help in the understanding of how the associated genetic variants influence disease or quantitative phenotypes.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-315) contains supplementary material, which is available to authorized users.     

A network control theory approach to modeling and optimal control of zoonoses: case study of brucellosis transmission in sub-Saharan Africa

Background

Developing control policies for zoonotic diseases is challenging, both because of the complex spread dynamics exhibited by these diseases, and because of the need for implementing complex multi-species surveillance and control efforts using limited resources. Mathematical models, and in particular network models, of disease spread are promising as tools for control-policy design, because they can provide comprehensive quantitative representations of disease transmission.

Methodology/Principal Findings

A layered dynamical network model for the transmission and control of zoonotic diseases is introduced as a tool for analyzing disease spread and designing cost-effective surveillance and control. The model development is achieved using brucellosis transmission among wildlife, cattle herds, and human sub-populations in an agricultural system as a case study. Precisely, a model that tracks infection counts in interacting animal herds of multiple species (e.g., cattle herds and groups of wildlife for brucellosis) and in human subpopulations is introduced. The model is then abstracted to a form that permits comprehensive targeted design of multiple control capabilities as well as model identification from data. Next, techniques are developed for such quantitative design of control policies (that are directed to both the animal and human populations), and for model identification from snapshot and time-course data, by drawing on recent results in the network control community.

Conclusions/Significance

The modeling approach is shown to provide quantitative insight into comprehensive control policies for zoonotic diseases, and in turn to permit policy design for mitigation of these diseases. For the brucellosis-transmission example in particular, numerous insights are obtained regarding the optimal distribution of resources among available control capabilities (e.g., vaccination, surveillance and culling, pasteurization of milk) and points in the spread network (e.g., transhumance vs. sedentary herds). In addition, a preliminary identification of the network model for brucellosis is achieved using historical data, and the robustness of the obtained model is demonstrated. As a whole, our results indicate that network modeling can aid in designing control policies for zoonotic diseases.     

Prioritizing emerging zoonoses in the Netherlands

Background

To support the development of early warning and surveillance systems of emerging zoonoses, we present a general method to prioritize pathogens using a quantitative, stochastic multi-criteria model, parameterized for the Netherlands.

Methodology/Principal Findings

A risk score was based on seven criteria, reflecting assessments of the epidemiology and impact of these pathogens on society. Criteria were weighed, based on the preferences of a panel of judges with a background in infectious disease control.

Conclusions/Significance

Pathogens with the highest risk for the Netherlands included pathogens in the livestock reservoir with a high actual human disease burden (e.g. Campylobacter spp., Toxoplasma gondii, Coxiella burnetii) or a low current but higher historic burden (e.g. Mycobacterium bovis), rare zoonotic pathogens in domestic animals with severe disease manifestations in humans (e.g. BSE prion, Capnocytophaga canimorsus) as well as arthropod-borne and wildlife associated pathogens which may pose a severe risk in future (e.g. Japanese encephalitis virus and West-Nile virus). These agents are key targets for development of early warning and surveillance.     

Prioritization and evaluation of depression candidate genes by combining multidimensional data resources

Background

Large scale and individual genetic studies have suggested numerous susceptible genes for depression in the past decade without conclusive results. There is a strong need to review and integrate multi-dimensional data for follow up validation. The present study aimed to apply prioritization procedures to build-up an evidence-based candidate genes dataset for depression.

Methods

Depression candidate genes were collected in human and animal studies across various data resources. Each gene was scored according to its magnitude of evidence related to depression and was multiplied by a source-specific weight to form a combined score measure. All genes were evaluated through a prioritization system to obtain an optimal weight matrix to rank their relative importance with depression using the combined scores. The resulting candidate gene list for depression (DEPgenes) was further evaluated by a genome-wide association (GWA) dataset and microarray gene expression in human tissues.

Results

A total of 5,055 candidate genes (4,850 genes from human and 387 genes from animal studies with 182 being overlapped) were included from seven data sources. Through the prioritization procedures, we identified 169 DEPgenes, which exhibited high chance to be associated with depression in GWA dataset (Wilcoxon rank-sum test, p = 0.00005). Additionally, the DEPgenes had a higher percentage to express in human brain or nerve related tissues than non-DEPgenes, supporting the neurotransmitter and neuroplasticity theories in depression.

Conclusions

With comprehensive data collection and curation and an application of integrative approach, we successfully generated DEPgenes through an effective gene prioritization system. The prioritized DEPgenes are promising for future biological experiments or replication efforts to discoverthe underlying molecular mechanisms for depression.     

Etiology of Severe Non-malaria Febrile Illness in Northern Tanzania: A Prospective Cohort Study

Introduction

The syndrome of fever is a commonly presenting complaint among persons seeking healthcare in low-resource areas, yet the public health community has not approached fever in a comprehensive manner. In many areas, malaria is over-diagnosed, and patients without malaria have poor outcomes.

Methods and Findings

We prospectively studied a cohort of 870 pediatric and adult febrile admissions to two hospitals in northern Tanzania over the period of one year using conventional standard diagnostic tests to establish fever etiology. Malaria was the clinical diagnosis for 528 (60.7%), but was the actual cause of fever in only 14 (1.6%). By contrast, bacterial, mycobacterial, and fungal bloodstream infections accounted for 85 (9.8%), 14 (1.6%), and 25 (2.9%) febrile admissions, respectively. Acute bacterial zoonoses were identified among 118 (26.2%) of febrile admissions; 16 (13.6%) had brucellosis, 40 (33.9%) leptospirosis, 24 (20.3%) had Q fever, 36 (30.5%) had spotted fever group rickettsioses, and 2 (1.8%) had typhus group rickettsioses. In addition, 55 (7.9%) participants had a confirmed acute arbovirus infection, all due to chikungunya. No patient had a bacterial zoonosis or an arbovirus infection included in the admission differential diagnosis.

Conclusions

Malaria was uncommon and over-diagnosed, whereas invasive infections were underappreciated. Bacterial zoonoses and arbovirus infections were highly prevalent yet overlooked. An integrated approach to the syndrome of fever in resource-limited areas is needed to improve patient outcomes and to rationally target disease control efforts.     

Ultrasonographic Assessment of Enthesitis in HLA-B27 Positive Patients with Rheumatoid Arthritis,a Matched Case-Only Study

Introduction

HLA-B27 has a modifier effect on the phenotype of multiple diseases, both associated and non-associated with it. Among these effects, an increased frequency of clinical enthesitis in patients with Rheumatoid Arthritis (RA) has been reported but never explored again. We aimed to replicate this study with a sensitive and quantitative assessment of enthesitis by using standardized ultrasonography (US).

Methods

The Madrid Sonography Enthesitis Index (MASEI) was applied to the US assessment of 41 HLA-B27 positive and 41 matched HLA-B27 negative patients with longstanding RA. Clinical characteristics including explorations aimed to evaluate spondyloarthrtitis and laboratory tests were also done.

Results

A significant degree of abnormalities in the entheses of the patients with RA were found, but the MASEI values, and each of its components including the Doppler signal, were similar in HLA-B27 positive and negative patients. An increase of the MASEI scores with age was identified. Differences in two clinical features were found: a lower prevalence of rheumatoid factor and a more common story of low back pain in the HLA-B27 positive patients than in the negative. The latter was accompanied by radiographic sacroiliitis in two HLA-B27 positive patients. No other differences were detected.

Conclusion

We have found that HLA-B27 positive patients with RA do not have more enthesitis as assessed with US than the patients lacking this HLA allele. However, HLA-B27 could be shaping the RA phenotype towards RF seronegativity and axial involvement.     

An Assessment of Antimicrobial Resistant Disease Threats in Canada

Background

Antimicrobial resistance (AMR) of infectious agents is a growing concern for public health organizations. Given the complexity of this issue and how widespread the problem has become, resources are often insufficient to address all concerns, thus prioritization of AMR pathogens is essential for the optimal allocation of risk management attention. Since the epidemiology of AMR pathogens differs between countries, country-specific assessments are important for the determination of national priorities.

Objective

To develop a systematic and transparent approach to AMR risk prioritization in Canada.

Methods

Relevant AMR pathogens in Canada were selected through a transparent multi-step consensus process (n=32). Each pathogen was assessed using ten criteria: incidence, mortality, case-fatality, communicability, treatability, clinical impact, public/political attention, ten-year projection of incidence, economic impact, and preventability. For each pathogen, each criterion was assigned a numerical score of 0, 1, or 2, and multiplied by criteria-specific weighting determined through researcher consensus of importance. The scores for each AMR pathogen were summed and ranked by total score, where a higher score indicated greater importance. A sensitivity analysis was conducted to determine the effects of changing the criteria-specific weights.

Results

The AMR pathogen with the highest total weighted score was extended spectrum B-lactamase-producing (ESBL) Enterobacteriaceae (score=77). When grouped by percentile, ESBL Enterobacteriaceae, Clostridium difficile, carbapenem-resistant Enterobacteriaceae, and methicillin-resistant Staphylococcus aureus were in the 80-100^th percentile.

Conclusion

This assessment provides useful information for prioritising public health strategies regarding AMR resistance at the national level in Canada. As the AMR environment and challenges change over time and space, this systematic and transparent approach can be adapted for use by other stakeholders domestically and internationally. Given the complexity of influences, resource availability and multiple stakeholders, regular consideration of AMR activities in the public health realm is essential for appropriate and responsible prioritisation of risk management that optimises the health and security of the population.     

Comparing Cutaneous Research Funded by the National Institute of Arthritis and Musculoskeletal and Skin Diseases with 2010 Global Burden of Disease Results

Importance

Disease burden data helps guide research prioritization.

Objective

To determine the extent to which grants issued by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) reflect disease burden, measured by disability-adjusted life years (DALYs) from Global Burden of Disease (GBD) 2010 project.

Design

Two investigators independently assessed 15 skin conditions studied by GBD 2010 in the NIAMS database for grants issued in 2013. The 15 skin diseases were matched to their respective DALYs from GBD 2010.

Setting

The United States NIAMS database and GBD 2010 skin condition disability data.

Main Outcome(s) and Measure(s)

Relationship of NIAMS grant database topic funding with percent total GBD 2010 DALY and DALY rank for 15 skin conditions.

Results

During fiscal year 2013, 1,443 NIAMS grants were issued at a total value of $424 million. Of these grants, 17.7% covered skin topics. Of the total skin disease funding, 82% (91 grants) were categorized as “general cutaneous research.” Psoriasis, leprosy, and “other skin and subcutaneous diseases” (ie; immunobullous disorders, vitiligo, and hidradenitis suppurativa) were over-represented when funding was compared with disability. Conversely, cellulitis, decubitus ulcer, urticaria, acne vulgaris, viral skin diseases, fungal skin diseases, scabies, and melanoma were under-represented. Conditions for which disability and funding appeared well-matched were dermatitis, squamous and basal cell carcinoma, pruritus, bacterial skin diseases, and alopecia areata.

Conclusions and Relevance

Degree of representation in NIAMS is partly correlated with DALY metrics. Grant funding was well-matched with disability metrics for five of the 15 studied skin diseases, while two skin diseases were over-represented and seven were under-represented. Global burden estimates provide increasingly transparent and important information for investigating and prioritizing national research funding allocations.     

An Algorithm for Network-Based Gene Prioritization That Encodes Knowledge Both in Nodes and in Links

Background

Candidate gene prioritization aims to identify promising new genes associated with a disease or a biological process from a larger set of candidate genes. In recent years, network-based methods – which utilize a knowledge network derived from biological knowledge – have been utilized for gene prioritization. Biological knowledge can be encoded either through the network''s links or nodes. Current network-based methods can only encode knowledge through links. This paper describes a new network-based method that can encode knowledge in links as well as in nodes.

Results

We developed a new network inference algorithm called the Knowledge Network Gene Prioritization (KNGP) algorithm which can incorporate both link and node knowledge. The performance of the KNGP algorithm was evaluated on both synthetic networks and on networks incorporating biological knowledge. The results showed that the combination of link knowledge and node knowledge provided a significant benefit across 19 experimental diseases over using link knowledge alone or node knowledge alone.

Conclusions

The KNGP algorithm provides an advance over current network-based algorithms, because the algorithm can encode both link and node knowledge. We hope the algorithm will aid researchers with gene prioritization.     

Communicable diseases prioritized for surveillance and epidemiological research: results of a standardized prioritization procedure in Germany, 2011

Introduction

To establish strategic priorities for the German national public health institute (RKI) and guide the institute''s mid-term strategic decisions, we prioritized infectious pathogens in accordance with their importance for national surveillance and epidemiological research.

Methods

We used the Delphi process with internal (RKI) and external experts and a metric-consensus approach to score pathogens according to ten three-tiered criteria. Additional experts were invited to weight each criterion, leading to the calculation of a median weight by which each score was multiplied. We ranked the pathogens according to the total weighted score and divided them into four priority groups.

Results

127 pathogens were scored. Eighty-six experts participated in the weighting; “Case fatality rate” was rated as the most important criterion. Twenty-six pathogens were ranked in the highest priority group; among those were pathogens with internationally recognised importance (e.g., Human Immunodeficiency Virus, Mycobacterium tuberculosis, Influenza virus, Hepatitis C virus, Neisseria meningitides), pathogens frequently causing large outbreaks (e.g., Campylobacter spp.), and nosocomial pathogens associated with antimicrobial resistance. Other pathogens in the highest priority group included Helicobacter pylori, Respiratory Syncytial Virus, Varicella zoster virus and Hantavirus.

Discussion

While several pathogens from the highest priority group already have a high profile in national and international health policy documents, high scores for other pathogens (e.g., Helicobacter pylori, Respiratory syncytial virus or Hantavirus) indicate a possible under-recognised importance within the current German public health framework. A process to strengthen respective surveillance systems and research has been started. The prioritization methodology has worked well; its modular structure makes it potentially useful for other settings.     

Public Hygiene Campaign in Denmark during the 2009 H1N1 Pandemic Had No Effect on Hospitalization Rate of Communicable Diseases in Children

Background

During the 2009 H1N1 pandemic the Danish National board of Health carried out massive public hygiene campaigns to limit spread of disease. We aimed to investigate whether this resulted in lower incidences of communicable diseases in the paediatric population.

Methods

The study compared annual hospitalization rates for childhood infections from 2005 to 2011.

Results

Admission rates for infections were higher during the year of the pandemic compared to the rest of the period.

Conclusion

There were no indications of a preventive effect by the hygiene campaign on incidence of severe common childhood infections.     

Buffalo, bush meat, and the zoonotic threat of brucellosis in Botswana

Background

Brucellosis is a zoonotic disease of global importance infecting humans, domestic animals, and wildlife. Little is known about the epidemiology and persistence of brucellosis in wildlife in Southern Africa, particularly in Botswana.

Methods

Archived wildlife samples from Botswana (1995–2000) were screened with the Rose Bengal Test (RBT) and fluorescence polarization assay (FPA) and included the African buffalo (247), bushbuck (1), eland (5), elephant (25), gemsbok (1), giraffe (9), hartebeest (12), impala (171), kudu (27), red lechwe (10), reedbuck (1), rhino (2), springbok (5), steenbok (2), warthog (24), waterbuck (1), wildebeest (33), honey badger (1), lion (43), and zebra (21). Human case data were extracted from government annual health reports (1974–2006).

Findings

Only buffalo (6%, 95% CI 3.04%–8.96%) and giraffe (11%, 95% CI 0–38.43%) were confirmed seropositive on both tests. Seropositive buffalo were widely distributed across the buffalo range where cattle density was low. Human infections were reported in low numbers with most infections (46%) occurring in children (<14 years old) and no cases were reported among people working in the agricultural sector.

Conclusions

Low seroprevalence of brucellosis in Botswana buffalo in a previous study in 1974 and again in this survey suggests an endemic status of the disease in this species. Buffalo, a preferred source of bush meat, is utilized both legally and illegally in Botswana. Household meat processing practices can provide widespread pathogen exposure risk to family members and the community, identifying an important source of zoonotic pathogen transmission potential. Although brucellosis may be controlled in livestock populations, public health officials need to be alert to the possibility of human infections arising from the use of bush meat. This study illustrates the need for a unified approach in infectious disease research that includes consideration of both domestic and wildlife sources of infection in determining public health risks from zoonotic disease invasions.     

The geographic synchrony of seasonal influenza: a waves across Canada and the United States

Background

As observed during the 2009 pandemic, a novel influenza virus can spread globally before the epidemic peaks locally. As consistencies in the relative timing and direction of spread could form the basis for an early alert system, the objectives of this study were to use the case-based reporting system for laboratory confirmed influenza from the Canadian FluWatch surveillance program to identify the geographic scale at which spatial synchrony exists and then to describe the geographic patterns of influenza A virus across Canada and in relationship to activity in the United States (US).

Methodology/Principal Findings

Weekly laboratory confirmations for influenza A were obtained from the Canadian FluWatch and the US FluView surveillance programs from 1997/98 to 2006/07. For the six seasons where at least 80% of the specimens were antigenically similar, we identified the epidemic midpoint of the local/regional/provincial epidemics and analyzed trends in the direction of spread. In three out of the six seasons, the epidemic appeared first in Canada. Regional epidemics were more closely synchronized across the US (3–5 weeks) compared to Canada (5–13 weeks), with a slight gradient in timing from the southwest regions in the US to northeast regions of Canada and the US. Cities, as well as rural areas within provinces, usually peaked within a couple of weeks of each other. The anticipated delay in peak activity between large cities and rural areas was not observed. In some mixed influenza A seasons, lack of synchronization sub-provincially was evident.

Conclusions/Significance

As mixing between regions appears to be too weak to force a consistency in the direction and timing of spread, local laboratory-based surveillance is needed to accurately assess the level of influenza activity in the community. In comparison, mixing between urban communities and adjacent rural areas, and between some communities, may be sufficient to force synchronization.     

Quantitative Muscle MRI as an Assessment Tool for Monitoring Disease Progression in LGMD2I: A Multicentre Longitudinal Study

Background

Outcome measures for clinical trials in neuromuscular diseases are typically based on physical assessments which are dependent on patient effort, combine the effort of different muscle groups, and may not be sensitive to progression over short trial periods in slow-progressing diseases. We hypothesised that quantitative fat imaging by MRI (Dixon technique) could provide more discriminating quantitative, patient-independent measurements of the progress of muscle fat replacement within individual muscle groups.

Objective

To determine whether quantitative fat imaging could measure disease progression in a cohort of limb-girdle muscular dystrophy 2I (LGMD2I) patients over a 12 month period.

Methods

32 adult patients (17 male;15 female) from 4 European tertiary referral centres with the homozygous c.826C>A mutation in the fukutin-related protein gene (FKRP) completed baseline and follow up measurements 12 months later. Quantitative fat imaging was performed and muscle fat fraction change was compared with (i) muscle strength and function assessed using standardized physical tests and (ii) standard T1-weighted MRI graded on a 6 point scale.

Results

There was a significant increase in muscle fat fraction in 9 of the 14 muscles analyzed using the quantitative MRI technique from baseline to 12 months follow up. Changes were not seen in the conventional longitudinal physical assessments or in qualitative scoring of the T₁w images.

Conclusions

Quantitative muscle MRI, using the Dixon technique, could be used as an important longitudinal outcome measure to assess muscle pathology and monitor therapeutic efficacy in patients with LGMD2I.     

A Meta-Analysis of the Impacts of Genetically Modified Crops

Background

Despite the rapid adoption of genetically modified (GM) crops by farmers in many countries, controversies about this technology continue. Uncertainty about GM crop impacts is one reason for widespread public suspicion.

Objective

We carry out a meta-analysis of the agronomic and economic impacts of GM crops to consolidate the evidence.

Data Sources

Original studies for inclusion were identified through keyword searches in ISI Web of Knowledge, Google Scholar, EconLit, and AgEcon Search.

Study Eligibility Criteria

Studies were included when they build on primary data from farm surveys or field trials anywhere in the world, and when they report impacts of GM soybean, maize, or cotton on crop yields, pesticide use, and/or farmer profits. In total, 147 original studies were included.

Synthesis Methods

Analysis of mean impacts and meta-regressions to examine factors that influence outcomes.

Results

On average, GM technology adoption has reduced chemical pesticide use by 37%, increased crop yields by 22%, and increased farmer profits by 68%. Yield gains and pesticide reductions are larger for insect-resistant crops than for herbicide-tolerant crops. Yield and profit gains are higher in developing countries than in developed countries.

Limitations

Several of the original studies did not report sample sizes and measures of variance.

Conclusion

The meta-analysis reveals robust evidence of GM crop benefits for farmers in developed and developing countries. Such evidence may help to gradually increase public trust in this technology.