Modeling and Statistical Analysis of the Spatio-Temporal Patterns of Seasonal Influenza in Israel

Background

Seasonal influenza outbreaks are a serious burden for public health worldwide and cause morbidity to millions of people each year. In the temperate zone influenza is predominantly seasonal, with epidemics occurring every winter, but the severity of the outbreaks vary substantially between years. In this study we used a highly detailed database, which gave us both temporal and spatial information of influenza dynamics in Israel in the years 1998–2009. We use a discrete-time stochastic epidemic SIR model to find estimates and credible confidence intervals of key epidemiological parameters.

Findings

Despite the biological complexity of the disease we found that a simple SIR-type model can be fitted successfully to the seasonal influenza data. This was true at both the national levels and at the scale of single cities.The effective reproductive number R_e varies between the different years both nationally and among Israeli cities. However, we did not find differences in R_e between different Israeli cities within a year. R _e was positively correlated to the strength of the spatial synchronization in Israel. For those years in which the disease was more “infectious”, then outbreaks in different cities tended to occur with smaller time lags. Our spatial analysis demonstrates that both the timing and the strength of the outbreak within a year are highly synchronized between the Israeli cities. We extend the spatial analysis to demonstrate the existence of high synchrony between Israeli and French influenza outbreaks.

Conclusions

The data analysis combined with mathematical modeling provided a better understanding of the spatio-temporal and synchronization dynamics of influenza in Israel and between Israel and France. Altogether, we show that despite major differences in demography and weather conditions intra-annual influenza epidemics are tightly synchronized in both their timing and magnitude, while they may vary greatly between years. The predominance of a similar main strain of influenza, combined with population mixing serve to enhance local and global influenza synchronization within an influenza season.     

Phenotypes of SLC26A4 gene mutations: Pendred syndrome and hypoacusis with enlarged vestibular aqueduct

This paper presents the current views, regarding the pathomechanisms, which lead to the development of pathological symptoms in the enlargement of the vestibular aqueduct syndrome (EVAS) and the Pendred syndrome (PS). Associated phenotypes have been discussed and an attempt has been undertaken to correlate them with a corresponding genotype. Mutations of SLC26A4 gene are one of the factors, which are at the base of congenital hearing losses. Inherited hearing loss occurs in these cases either as an isolated phenomenon with anatomical anomalies of the labyrinth in the background (EVAS) or with endocrine disorders (PS). The official name of SLC26A4 gene is "solute carrier family 26, member 4". Pendrin, the product of its expression, transports iodine beyond thyroid follicular cells, where it is linked with thyroglobulin and, then, used in hormone synthesis. Abnormal expression of SLC26A4 gene results in disturbance of iodine organification. In the internal ear, pendrin transports bicarbonates to the endolymph, taking in this way an active part in pH control of the endolymph and providing proper functioning of KCNJ10 potassium channels and TRP5 calcium channels. Disorders of homeostasis in labyrinth fluids are responsible for abnormalities of its structure, such as enlargement of the vestibular aqueduct and of the endolymph sac. At present, the Human Gene Mutations database provides 124 recessive mutations of SLC26A4 gene. In EVAS and PS, two missense mutations are most frequently observed: L236P and T416P, as well as the mutation, regarding abnormal splicing process, i.e., IVS8+1G-A, in a total of 55% of the patients with recognised mutation of SLC26A4 gene; the remaining 45% of changes of this gene are unique mutations.     

Ultrasound enhanced prehospital thrombolysis using microbubbles infusion in patients with acute ST elevation myocardial infarction: Rationale and design of the Sonolysis study

Background

The CONSORT Statement provides recommendations for reporting randomized controlled trials. We assessed the extent to which leading medical journals that publish reports of randomized trials incorporate the CONSORT recommendations into their journal and editorial processes.

Methods

This article reports on two observational studies. Study 1: We examined the online version of 'Instructions to Authors' for 165 high impact factor medical journals and extracted all text mentioning the CONSORT Statement or CONSORT extension papers. Any mention of the International Committee of Medical Journal Editors (ICMJE) or clinical trial registration were also sought and extracted. Study 2: We surveyed the editor-in-chief, or editorial office, for each of the 165 journals about their journal's endorsement of CONSORT recommendations and its incorporation into their editorial and peer-review processes.

Results

Study 1: Thirty-eight percent (62/165) of journals mentioned the CONSORT Statement in their online 'Instructions to Authors'; of these 37% (23/62) stated this was a requirement, 63% (39/62) were less clear in their recommendations. Very few journals mentioned the CONSORT extension papers. Journals that referred to CONSORT were more likely to refer to ICMJE guidelines (RR 2.16; 95% CI 1.51 to 3.08) and clinical trial registration (RR 3.67; 95% CI 2.36 to 5.71) than those journals which did not. Study 2: Thirty-nine percent (64/165) of journals responded to the on-line survey, the majority were journal editors. Eighty-eight percent (50/57) of journals recommended authors comply with the CONSORT Statement; 62% (35/56) said they would require this. Forty-one percent (22/53) reported incorporating CONSORT into their peer-review process and 47% (25/53) into their editorial process. Eighty-one percent (47/58) reported including CONSORT in their 'Instructions to Authors' although there was some inconsistency when cross checking information on the journal's website. Sixty-nine percent (31/45) of journals recommended authors comply with the CONSORT extension for cluster trials, 60% (27/45) for harms and 42% (19/45) for non-inferiority and equivalence trials. Few journals mentioned these extensions in their 'Instructions to Authors'.

Conclusion

Journals should be more explicit in their recommendations and expectations of authors regarding the CONSORT Statement and related CONSORT extensions papers.     

The Dynamics, Prevalence and Impact of Nematode Infections in Organically Raised Sheep in Sweden

A three-year survey (1997–99) was carried out on organically reared sheep flocks throughout Sweden. The aim was to determine the prevalence and intensity of nematode infections and to establish relationships between sheep management practices and parasite infections. Faecal samples from ewes and lambs were collected from 152 organic flocks around lambing-time and during the grazing-period for analysis. Results were compared with the different management practices that farmers use to prevent parasitism in their flocks. A high proportion of the flocks was infected with nematodes. The most prevalent species were Haemonchus contortus, Teladorsagia circumeincta, Trichostrongylus axei, T. colubriformis and Chabertia ovina and infections progressively increased during summer in lambs grazing on permanent pastures. Severity of parasitic infection in lambs was highly dependent on egg output from the ewes. H. contortus was found in 37% of the flocks, even at latitudes approximating the Polar Circle. Nematodirus battus was recorded for the first time in Sweden during the course of this study. Lambs turned out onto permanent pasture showed higher nematode faecal egg counts (epg) than lambs that had grazed on pastures, which had not carried sheep the previous year. This beneficial effect of lambs grazing non-infected pastures persisted if the ewes were treated with an anthelmintic before turn-out and if the lambs were kept on pastures of low infectivity after weaning. In lambs, the prevalence and the magnitude of their egg counts were higher during autumn in flocks where lambs were slaughtered after 8 months of age, compared with flocks where all lambs were slaughtered before this age. These results will be used in providing advice to farmers of ways to modify their flock management in order to minimise the use of anthelmintics, but at the same time efficiently produce prime lambs.     

The potential for using red claw crayfish and hybrid African catfish as biological control agents for Schistosoma host snails

The potential of red claw crayfish and hybrid African catfish (Clarias gariepinus and Clarias ngamensis) as predators for Schistosoma host snails was evaluated in 2014 by monitoring the consumption of snails by crayfish and catfish in experimental tanks over time under laboratory conditions. After 15 days, both crayfish and catfish had significantly reduced the populations of Bulinus globosus. Crayfish consumed 6.9 snails d^?1, whereas catfish consumed 5.9 snails d^?1. However, when supplied with an alternative prey, Melanoides tuberculata (100 individuals per tank), crayfish clearly preferred M. tuberculata (100% consumed over seven days) to B. globosus (100 individuals per tank) (54% consumed over the same period). Catfish, conversely, did not have a clear preference for either prey species, consuming 77% and 88% of M. tuberculata and B. globosus, respectively. It was also observed that young catfish were more efficient predators than older ones, because of ontogenetic shifts in their diet with age. Hybrid catfish retain the molluscivorous characteristics of their parent stock and red claw crayfish also preys on Schistosoma host snails. However, the effectiveness of both predators is affected by the presence of an alternative prey. Therefore, under suitable conditions, these species can be considered for biological control of schistosomiasis transmission.     

Definition of common carotid wall thickness affects risk classification in relation to degree of internal carotid artery stenosis: the Plaque At RISK (PARISK) study

Background

Mean or maximal intima-media thickness (IMT) is commonly used as surrogate endpoint in intervention studies. However, the effect of normalization by surrounding or median IMT or by diameter is unknown. In addition, it is unclear whether IMT inhomogeneity is a useful predictor beyond common wall parameters like maximal wall thickness, either absolute or normalized to IMT or lumen size. We investigated the interrelationship of common carotid artery (CCA) thickness parameters and their association with the ipsilateral internal carotid artery (ICA) stenosis degree.

Methods

CCA thickness parameters were extracted by edge detection applied to ultrasound B-mode recordings of 240 patients. Degree of ICA stenosis was determined from CT angiography.

Results

Normalization of maximal CCA wall thickness to median IMT leads to large variations. Higher CCA thickness parameter values are associated with a higher degree of ipsilateral ICA stenosis (p?<?0.001), though IMT inhomogeneity does not provide extra information. When the ratio of wall thickness and diameter instead of absolute maximal wall thickness is used as risk marker for having moderate ipsilateral ICA stenosis (>50%), 55 arteries (15%) are reclassified to another risk category.

Conclusions

It is more reasonable to normalize maximal wall thickness to end-diastolic diameter rather than to IMT, affecting risk classification and suggesting modification of the Mannheim criteria.

Trial registration

Clinical trials.gov NCT01208025.

     

Pathway analysis in metabolomics: Recommendations for the use of over-representation analysis

Over-representation analysis (ORA) is one of the commonest pathway analysis approaches used for the functional interpretation of metabolomics datasets. Despite the widespread use of ORA in metabolomics, the community lacks guidelines detailing its best-practice use. Many factors have a pronounced impact on the results, but to date their effects have received little systematic attention. Using five publicly available datasets, we demonstrated that changes in parameters such as the background set, differential metabolite selection methods, and pathway database used can result in profoundly different ORA results. The use of a non-assay-specific background set, for example, resulted in large numbers of false-positive pathways. Pathway database choice, evaluated using three of the most popular metabolic pathway databases (KEGG, Reactome, and BioCyc), led to vastly different results in both the number and function of significantly enriched pathways. Factors that are specific to metabolomics data, such as the reliability of compound identification and the chemical bias of different analytical platforms also impacted ORA results. Simulated metabolite misidentification rates as low as 4% resulted in both gain of false-positive pathways and loss of truly significant pathways across all datasets. Our results have several practical implications for ORA users, as well as those using alternative pathway analysis methods. We offer a set of recommendations for the use of ORA in metabolomics, alongside a set of minimal reporting guidelines, as a first step towards the standardisation of pathway analysis in metabolomics.     

Biological indicators in marine and coastal waters: a statistical and modelling analysis of the MARS campaign

We perform a statistical analysis of ecological data collected in the MARS project from marine environments of the Red and Mediterranean Seas in Israel, and the North Sea in Germany. In the study of fish parasite data, we examine the basic premise that the complex host lifecycles of heteroxenous (h) parasites make them more sensitive to pollution than monoxenous (m) parasites which have only one host. Unlike results from analyses of earlier survey data, we find that the pooled h/m index for a community is not a clear indicator of environmental stress as originally hypothesized. This is due to the relatively large seasonal variability at the sampling sites over the course of the 3-year survey. Other possible indicators for water pollution gradients are checked, including species richness, diversity and prevalence of parasite populations. A theoretical model of host-parasite population dynamics that makes the presence of ecological thresholds transparent is offered to help explain the abrupt transitions prominent in the distributions of parasites at different sites under different pollution loadings. Heavy metal and chlorinated hydrocarbon data collected from fish tissue samples and molluscs of the three seas are assessed as bioindicators for pollution monitoring. The xenobiotic loads and indices of defence system activity and tissue damage are shown to have great potential as monitoring bioindicators.     

A machine learning method for estimating the probability of presence using presence‐background data

Estimating the prevalence or the absolute probability of the presence of a species from presence‐background data has become a controversial topic in species distribution modelling. In this paper, we propose a new method by combining both statistics and machine learning algorithms that helps overcome some of the known existing problems. We have also revisited the popular but highly controversial Lele and Keim (LK) method by evaluating its performance and assessing the RSPF condition it relies on. Simulations show that the LK method with the RSPF assumptions would render fragile estimation/prediction of the desired probabilities. Rather, we propose the local knowledge condition, which relaxes the predetermined population prevalence condition that has so often been used in much of the existing literature. Simulations demonstrate the performance of the new method utilizing the local knowledge assumption to successfully estimate the probability of presence. The local knowledge extends the local certainty or the prototypical presence location assumption, and has significant implications for demonstrating the necessary condition for identifying absolute (rather than relative) probability of presence from presence background without absence data in species distribution modelling.     

Clustering of physical health multimorbidity in people with severe mental illness: An accumulated prevalence analysis of United Kingdom primary care data

BackgroundPeople with severe mental illness (SMI) have higher rates of a range of physical health conditions, yet little is known regarding the clustering of physical health conditions in this population. We aimed to investigate the prevalence and clustering of chronic physical health conditions in people with SMI, compared to people without SMI.Methods and findingsWe performed a cohort-nested accumulated prevalence study, using primary care data from the Clinical Practice Research Datalink (CPRD), which holds details of 39 million patients in the United Kingdom. We identified 68,783 adults with a primary care diagnosis of SMI (schizophrenia, bipolar disorder, or other psychoses) from 2000 to 2018, matched up to 1:4 to 274,684 patients without an SMI diagnosis, on age, sex, primary care practice, and year of registration at the practice. Patients had a median of 28.85 (IQR: 19.10 to 41.37) years of primary care observations. Patients with SMI had higher prevalence of smoking (27.65% versus 46.08%), obesity (24.91% versus 38.09%), alcohol misuse (3.66% versus 13.47%), and drug misuse (2.08% versus 12.84%) than comparators. We defined 24 physical health conditions derived from the Elixhauser and Charlson comorbidity indices and used logistic regression to investigate individual conditions and multimorbidity. We controlled for age, sex, region, and ethnicity and then additionally for health risk factors: smoking status, alcohol misuse, drug misuse, and body mass index (BMI). We defined multimorbidity clusters using multiple correspondence analysis (MCA) and K-means cluster analysis and described them based on the observed/expected ratio. Patients with SMI had higher odds of 19 of 24 conditions and a higher prevalence of multimorbidity (odds ratio (OR): 1.84; 95% confidence interval [CI]: 1.80 to 1.88, p < 0.001) compared to those without SMI, particularly in younger age groups (males aged 30 to 39: OR: 2.49; 95% CI: 2.27 to 2.73; p < 0.001; females aged 18 to 30: OR: 2.69; 95% CI: 2.36 to 3.07; p < 0.001). Adjusting for health risk factors reduced the OR of all conditions. We identified 7 multimorbidity clusters in those with SMI and 7 in those without SMI. A total of 4 clusters were common to those with and without SMI; while 1, heart disease, appeared as one cluster in those with SMI and 3 distinct clusters in comparators; and 2 small clusters were unique to the SMI cohort. Limitations to this study include missing data, which may have led to residual confounding, and an inability to investigate the temporal associations between SMI and physical health conditions.ConclusionsIn this study, we observed that physical health conditions cluster similarly in people with and without SMI, although patients with SMI had higher burden of multimorbidity, particularly in younger age groups. While interventions aimed at the general population may also be appropriate for those with SMI, there is a need for interventions aimed at better management of younger-age multimorbidity, and preventative measures focusing on diseases of younger age, and reduction of health risk factors.

In an observational analysis of primary care data from the UK, Naomi Launders and colleagues study the prevalence and clustering of physical health conditions and multimorbidity in individuals with severe mental illnesses.