Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments. Schultz and Pilz Understanding how the human brain processes information in complex everyday situations presents one of the ultimate challenges in cognitive neuroscience. The vast majority of previous neuroimaging experiments have strived to increase our understanding of the neural basis of perception using carefully controlled stimuli and tasks. However, there are reports showing that results obtained under such settings do not always generalize to real life conditions. For instance, a recent study by David and co-workers In recent studies, hemodynamic brain responses during naturalistic stimulation, such as feature films or normal connected speech, have been shown to be amenable to study using a relatively simple model-free voxel-wise inter-subject correlation (ISC) analysis Here, we hypothesized that by annotating quantitatively the movie stimulus, it is possible to disclose the specificity of IC-based networks to various stimulus features in the movie. In fact, in recent pioneering studies, stimulus-modeling approaches such as quantification of local and global movement over time in a movie In the current study, our aim was to critically test whether annotating several robust visual and auditory features that are known to activate multiple brain networks makes it possible to detect such networks during a naturalistic free viewing condition and to compare the results of the model-free ICA approach to those obtained using a conventional voxel-wise GLM analysis. A feature film “Match Factory Girl”  was re-edited in order to shorten the story to allow larger part of the main story line to be shown to healthy volunteers during fMRI scanning. From the movie, we extracted eight auditory features  energy, speech, music, lead singing, and background singing), both automatically and manually. We also extracted seven visual features . The motion categories were manually scored according to the perceived strength of motion. The spatial location of the main characters of the movie and their heads and hands and non-biological moving objects were also annotated using in-house developed semi-automated motion recognition software. Temporal dynamics of the extracted features were then compared with activation time courses of ICs and with single voxels.We hypothesized that to successfully reveal brain areas participating in coding of a complex natural stimulus we would need a complex stimulus model with a rich collection of features. We expected that such models could be used to explore brain areas and networks of areas involved in processing complex stimulus feature combinations, while any single feature alone would not be sufficient to explain the activity of the network. We selected six ICs of interest using temporal inter-subject correlation of IC time courses and employed GLM approach to fit the collections of stimulus annotations. Permutation testing was utilized to correct the increased risk of over fitting. The weights of each feature in the IC and voxel-wise models were used to inspect the extent to which annotated features are encoded at each network, and were further compared with voxel-wise analysis using isolated stimulus features.Twelve healthy native speakers of Finnish were studied. Two of the subjects were excluded from the study due to technical problems leaving ten subjects  included in the final analysis. Permission for the study was acquired from the ethical committee of Hospital district of Helsinki and Uusimaa. The study was carried out in accordance with the guidelines of the declaration of Helsinki, and written informed consent was obtained from each subject prior to participation.via a mirror located above their eyes. Projected image width was 19.7 cm. The audio track of the movie was played to the subjects with an UNIDES ADU2a audio system  via plastic tubes through porous EAR-tip  earplugs. The intensity of the auditory stimulation was selected to be loud enough to be heard over the scanner noise and was kept constant for all participants.The subjects watched 22 minutes and 58 seconds of a Finnish language film in the fMRI scanner. The feature film “Match Factory Girl”  was re-edited  in order to adapt the story to be imaged within the constraint of 20000 slice acquisitions allowed by the MRI scanner. The shorter version retained the main storyline and smooth flow of scenes. Subjects were instructed to avoid any movements and watch the movie during fMRI scanning. The beginning of the movie was synchronized to the beginning of the scanning using Presentation software . The movie was back-projected on a semitransparent screen using a 3-micromirror data projector . The subjects viewed the screen at 34 cm viewing distance Functional brain imaging was carried out with a 3.0 T GE Signa Excite MRI scanner  using a quadrature 8-channel head coil. The imaging area consisted of 29 functional gradient-echo planar (EPI) oblique slices . Images were acquired continuously during the experiment. In addition, a T1-weighted spoiled gradient echo volume was acquired for anatomical alignment . The T1 image in-plane resolution was 1 mm × 1 mm, matrix 256 × 256 and slice thickness 1 mm with no gap. Each dataset consisted of 689 functional volumes.All the preprocessing steps were performed using FSL Two approaches were used for analysis of the functional data: model free ICA and model driven GLM analysis. ICA searches for unknown latent signals in the data through the general assumption of statistical independence by minimizing or maximizing an objective function such as mutual information, negentropy http://icatb.sourceforge.net/). Infomax was chosen as the ICA algorithm with default parameters. ICA was performed 100 times with random initialization and bootstrapping enabled using ICASSO package included in GIFT. The IC clustering is based on the absolute value of the spatial correlation coefficient, and is described in detail in ICASSO publications post hoc by repeating the bootstrap calculation with several dimensionalities. The most stable results were found when the data dimensionality was 40, which was selected for the final analysis. ICs that were found in all 100 repetitions and the average intra-cluster similarity of which was >0.9 were sorted according to the mean pair-wise temporal correlation coefficient across subjects. Fisher’s Z transform was applied to correlation coefficients before calculating the mean. ICs for which the mean pair-wise correlation was significant at p < 0.001, uncorrected, were selected for subsequent analysis, and are presented in the results.Group ICA was performed using GIFT  were fitted to IC time courses using GLM fitting in MATLAB . Finally, similar GLM fitting was performed also for each voxel’s time course separately. Voxel-wise analysis was done separately on single subject data and mean activity across subjects. The mean time courses were calculated by standardizing the subjects’ voxel time courses to zero mean and normalizing the variance to unity prior to calculating the mean across subjects for each voxel. The correlation coefficients for IC and voxel-wise time courses were calculated with the fitted sum of annotations for that IC or voxel.Sensitivity of ICs to auditory features was compared by calculating the weights in GLM for single auditory features in isolation for each subjects IC time course. We performed paired t-tests to compare for which features the weights differed between ICs. T-tests were used to test which weights differed significantly from zero across subjects.Significance threshold level for correlation coefficients of the GLM fitted annotation time courses was estimated using permutation testing. The algorithm applied a circular shift to the fMRI time courses and GLM fitting of the annotations was performed on the shifted time courses. The correlation coefficients for the fitted sums of annotations and the shifted time courses were calculated. All permutations (679 different shifts) were calculated for all IC time courses  and all mean brain voxels . Separate thresholds were calculated for the visual and auditory models to account for over-fitting for each model individually. The probability distribution was estimated by creating a lookup table through dividing the observed correlation coefficients into 100 bins. The probability for each bin was estimated as the observed frequency of realizations and assigned to the center of the bin. More precise estimate was obtained through linear interpolation between the bins. The thresholds of significant  correlation in the permutation test for IC time courses were r > 0.4772 for auditory model and r > 0.4230 for visual model. For voxel-wise data threshold was r > 0.4706 for auditory and r > 0.4144 for visual model. Similar permutation testing was done for the single annotations except without GLM fitting, but because of computational expense only half of the permutation distribution was sampled . For visualization a single threshold was calculated for all auditory and visual annotations as the mean of the individual annotation thresholds for the given modality. Since we aimed to compare the results of ICA and voxel-wise analysis, we did not perform explicit multiple comparisons correction between the models in our analyses to avoid overestimating the differences of the two methods. However, areas which were not significant in the tests for the full auditory and visual models are not reported in the single feature analyses.In the results we present only the ICs for which a) temporal correlation between subjects was significant , b) time course of the IC was significantly correlated  either with the auditory or visual stimulus model, and c) the IC was stable in the bootstrap test performed with ICASSO.vs. non-overlapping clusters of voxels indicated as significantly activated by ICs and GLM were extracted using MATLAB and SPM8 connected component labeling function that enforced 18 connectivity criterion (http://www.fil.ion.ucl.ac.uk/spm/software/spm8/). We selected only clusters larger than 125 voxels for the final analysis. Significance of functional connectivity between the mean time courses of the clusters was assessed with permutation testing. We performed ten million permutations to obtain a reliable estimate of the permutation distribution. Each permutation consisted of randomly selecting a seed region, and shifting its time course by at least five samples. We then calculated the correlation of the shifted time course with the time courses of all other clusters and saved the maximum value. The threshold of significant  functional connectivity in the permutation test was r = 0.4121.The overlapping Time intervals of the movie containing speech, instrumental music, lead singing, and background singing were annotated from the sound track manually and modeled as boxcar functions with 1-s resolution. MIRToolbox The video was high-pass filtered using discrete cosine transform and applying a two dimensional spatial mask with cutoff of 2π/16 rad/pixel. Cutoff frequency was selected by visual inspection of the high-pass filtered images so that only sharp contrast edges were retained in the image. Absolute values of the pixel intensities were calculated for each frame resulting in an image where the high-frequency content corresponded to high pixel intensity . Mean pie.g., camera or background or large part of the background moving), and 6) inferred motion of body parts not directly visible in the picture. Motion was scored on a scale 0–4 in a two-step process  mechanical motion, 2) hand movements, 3) head movements, 4) body movements, 5) global motion  and non-biological objects. Large crowds of people were annotated as a single object. The time courses of area and speed were mapped to a scale similar to the manual annotations and grouped to categories . Area whose size was less than 1/10 of the whole image area received the score 0, for areas between 1/10 and 1/6 the score was 1, and larger objects received the score 2. Speed of each object was calculated as the sum of instantaneous speeds within each 1 second window, and thresholded so that speed of less than 15 pixels/second received the score 0, speeds between 15 and 50 pixels/second  received the score 1, and speeds faster than 50 pixels/second received the score 2. Maximum value of objects within each category was used as the measure of speed and area within each temporal window and motion time course for each category was calculated as a sum of the speed and the area similar to the manual annotations.2) between the two being 0.6353 (p < 0.001). Mean inter-subject correlation (ISC) of the activation time courses of individual subjects (ISC ± variance) was 0.41 ± 0.02 (p < 0.001).2  =  0.3758 (p < 0.001). Mean ISC of the activation time courses of individual subjects was 0.31 ± 0.03 (p < 0.001).IC2 encompasses a widespread bilateral network of brain areas including the MTG, posterior regions of temporal lobe and temporoparietal junction (TPJ), pars triangularis region of inferior frontal gyrus (ptIFG), dorsomedial prefrontal cortex (dmPFC), premotor cortex (PMC) just anterior to the approximate location of the lip area of the motor strip, part of precuneus (Pcu), and a small cluster in the paracingulate gyrus (pCG). The clusters of cortical activity appear larger in the left hemisphere. The IC2 encompasses a more extensive network of brain areas than IC1 and, further, the areas included in the network of IC2 are ones that are typically associated with hierarchically higher-order auditory processing of than those of IC1, for example meanings of words and sentences vs. motor-cue based speech perception The time courses of IC1 and IC2 are very similar (i.e. they are as sensitive) when there is speech .2  =  0.3003, and mean ISC of the activation time courses of individual subjects was 0.25 ± 0.02 (p < 0.001).IC4 coincides with the motion sensitive visual area V5 and extends to surrounding areas of the posterior temporal lobe and lateral occipital lobe. It shows highest sensitivity to hand motion , but is also sensitive to other motion categories, except inferred motion. The stimulus model fit R2  =  0.4078, and mean ISC of the activation time courses of individual subjects was 0.36 ± 0.01 (p < 0.001).IC5 includes posterior region of the parietal lobe and lateral-ventral aspects of the occipital lobe, and posterior lobe of the cerebellum on the left. Similarly to IC4 and IC6, IC5 is sensitive to hand and mechanical motion. It also shares sensitivity to body motion with IC3 and IC4. The stimulus model fit R2  =  0.4636. IC6 is very sensitive to hand motion, and to a lesser extent to mechanical motion. Mean ISC of the activation time courses of individual subjects was r  =  0.38 ± 0.03 (p < 0.001).IC6 is located in superior parietal lobule including intraparietal sulcus (IPS), inferior part of the temporo-occipital junction (TOJ), ventral parts of lateral premotor cortex, and the frontal eye fields (FEF). The visual stimulus model fits the activity with RAs is revealed by the weights of the annotations, sensitivities of these four visual-processing related ICs differ in their specificity to annotated visual features. IC3 and IC4, reflecting activity in lower-order visual areas, are sensitive to different types of visual motion and contrast edges. IC5 and IC6 are quite insensitive to contrast edges, but sensitive to visual motions. IC6 is most selective to a specific type of motion, hand movements, but also to mechanical motion.2 values: IC3  =  0.3097, IC4  =  0.2543, IC5  =  0.2855, IC6  =  0.307) but the relative weights were almost identical. Therefore, we show only results for the manually annotated motion model.Similar fitting as in In addition to the analysis where the time courses of the brain networks captured by the ICs were fitted to the time courses of stimulus annotations, we performed GLM fitting of the stimulus annotation time courses with individual-voxel time courses using both the across-subjects averaged voxel time courses as well as single-subject data. The overall model fit for single-subject data was lower  than for the mean activity across subjects  presumably due to lower signal-to-noise of the single-subject BOLD data. However, the areas of best fit were highly similar with these two approaches. Therefore, we present here only the results of the group-level analysis.i.e., there is a high correlation between brain areas contained in each IC), whereas the voxel-wise GLM based analysis reflects the relation of each individual voxel and the stimulus model. Because the thresholds for significant correlation were between r = 0.41 and r = 0.48 for both region-region and region-model correlations it is possible that the significant functional connectivity may be caused by variance in the data which is not explained by the model. As seen in To assess the differences of results revealed by ICA and voxel-wise analyses in We calculated the correlations of the mean time courses of the ROIs with each other and with the stimulus model . For botOur results demonstrate the feasibility of using highly complex naturalistic stimuli such as feature films in neuroimaging studies to disclose how the human brain processes information under naturalistic conditions approaching those that one encounters in real life. Previous neuroimaging studies using movies as stimuli have demonstrated that brains of individual subjects react similarly Auditory ICs depicted in Analogously to the auditory case, our results, obtained by combining stimulus annotations with ICA and voxel-wise analysis see  functionSpatial ICA extracts independent networks of brain activity revealing functionally connected brain areas Temporal lobe and lip representation area of the motor cortex, and inferior frontal gyrus pars triangularis encompassed by IC2 were found to be sensitive to speech. These areas are very similar to a widespread network of temporal and frontal areas linked to processing of natural connected speech over long timescales, but not to processing of scrambled sentences ICA was not sensitive enough to reveal presumed fine-grained differences in sensitivity to different acoustic features in the auditory cortical areas. Therefore, it was valuable to complement the data driven analysis with model-based methods. Evidently, there are situations where a well-defined model may be able to separate functionally distinct regions, when they are not independent enough to be segregated with blind source separation techniques. Depending on the amount and quality of data and the employed implementation ICA methods may be used to extract a higher number of components than was achievable in the current study presumably helping to capture many of the distinctions between cortical areas we have demonstrated using model-based methods. However, the stability of source estimates should be analyzed to evaluate their reliability as increasing the number of ICs may lead to over fitting and unstable IC estimates. The selection of the number of ICs to be estimated is typically rather arbitrary and the methods used for estimating the appropriate number of components often yield relatively high estimates leading to unstable ICs. While using multiple methods in the analysis of any data without appropriate corrections for multiple post-hoc comparisons does increase the risk for false positive findings, a voxel-wise analysis is a worthwhile “sanity check” for functional connectivity analyses (such as ICA) when it is possible to conduct.Reverse correlation methods have been suggested for finding the stimulus features related to the observed activity of brain areas during natural viewing of complex stimuli We have taken the exploration of data one step further by looking at the time dependent activity levels of voxels over the whole brain synchronized with the movie stimulus . To undeWhile the results of the current study demonstrate that it is possible to extract simple stimulus features and find their neural correlates in a naturalistic context, selecting and modeling the relevant features for the model is not trivial. Manual annotation is laborious, which makes it important to develop accurate algorithms to annotate both optic flow and acoustics of the complex stimuli as accurately as possible. However, at least at present, these annotations need to be checked by the experimenter. Furthermore, as suggested by our results, the brain activity is not likely to be linearly dependent on the raw stimulus properties and manual annotations of, in this case, perceptual motion strength may better fit the brain activity than automated ones. In addition, many important aspects of the movie are missed if only the sensory properties are modeled. Therefore, expert annotations, subjective ratings, and behavioral data may play a key role in finding neural basis for endogenous/higher order cognitive and emotional processes not directly related to physical qualities of the stimulus. Further work on exploring what combinations of sensory features and endogenous processes best explain the observed brain activity is of great importance in trying to form a cohesive theory of how the human brain processes the complex natural world.Our results suggest that patterns of brain activity underlying the processing of various acoustic and visual features can be effectively studied using highly complex audiovisual stimulation, such as a feature film, by combining detailed annotations of the stimulus with ICA and voxel-wise analyses, and even unguided exploration of whole brain fMRI data. We have further demonstrated important differences between the employed methods. Studying how the human brain processes information under naturalistic conditions is an important addition to the repertoire of paradigms aiming to increase our understanding of the processing of stimulus features in the human brain. Naturalistic experiments have the potential to reveal such aspects of processing of especially complex features which are difficult or even impossible to discover using very simple stimuli and tasks. Further, the approach we present here could be extended in future studies with self-reports of subjective experiences such as emotional states as well as complementary behavioral measures such as tracking of eye-movements to enable more comprehensive investigation of the neural basis of human perceptual, cognitive and emotional processes.


Background. Opioid analgesics are included in treatment guidelines for the symptomatic management of osteoarthritis (OA). Starting with a low dose of opioid and slowly titrating to a higher dose may help avoid intolerable side effects. Methods. Subjects aged ≥40 years, with moderate to severe pain induced by OA of the hip or knee not adequately controlled by previous non-steroidal anti-inflammatory drugs (NSAIDs) or paracetamol treatment, were enrolled. Subjects received OROS hydromorphone 4 mg or placebo once-daily. The dose was titrated every 3-4 days in case of unsatisfactory pain control during the 4-week titration phase. A 12 week maintenance phase followed. The primary efficacy endpoint was the change in “pain on average” measured on the Brief Pain Inventory (BPI) scale from baseline to the end of the maintenance phase. Results. 139 subjects received OROS hydromorphone and 149 subjects received placebo. All efficacy endpoints showed similar improvements from baseline to end of study in the 2 groups. The safety results were consistent with the safety profile of OROS hydromorphone. Conclusion.The study did not meet the primary endpoint; although many subjects' pain was not adequately controlled at inclusion, their pain may have improved with continued paracetamol or NSAID treatment. Providing relief from chronic pain is a major worldwide public health issue . A systeOsteoarthritis (OA) is the most common form of joint disease. The prevalence of OA increases with age; more than 75% of subjects over 70 years of age have radiologically detectable OA changes –8); OA lOpioid therapy is increasingly being used for the treatment of chronic noncancer pain although long-term opioid use remains controversial owing to concerns about long-term effectiveness and safety, particularly the risk of developing tolerance, dependence, or abuse –17). Com. Com17])The use of opioid analgesics is included in treatment guidelines for the symptomatic management of OA of the hip or knee; weak opioids may be considered for the treatment of refractory pain where other pharmacological agents have been ineffective, whilst strong opioids should only be used for managing severe chronic pain in exceptional circumstances . The effGuidelines on the use of opioids for chronic pain have recommended the use of controlled release formulations and scheduled regimens –22). Con. Con22])OROS hydromorphone  is a unique, once-daily opioid formulation that uses the patented OROS Push-Pull technology  to deliver hydromorphone with continuous, monophasic drug release over 24 hours, with the aim of providing consistent, longlasting analgesia , 29). In. In29]).Here we report the results of the hydromorphone for OA pain (HOP) trial. In this placebo-controlled trial, subjects who were randomised to treatment with OROS hydromorphone hydrochloride were started on the lowest dose of 4 mg once daily; their dose was titrated every 3-4 days in the event of unsatisfactory pain control during the 4-week titration phase. The rationale for using a lower starting dose of 4 mg is that it may induce tolerance to the adverse effects of the opioid and therefore may reduce the number of AEs and consequently the dropout rate. The primary objective was to compare the analgesic effect of flexibly titrated OROS hydromorphone hydrochloride and placebo in subjects with moderate-to-severe pain induced by OA of the hip or knee that had not been adequately controlled by previous treatment with non-steroidal anti-inflammatory drugs (NSAIDs) or paracetamol measured by “pain on average” on the brief pain inventory (BPI) scale. Secondary objectives included assessing the dropout rate due to AEs, the effect of treatment on subjects' functionality using the total score of the Western Ontario and McMaster Universities (WOMAC) OA index, the effect of treatment on pain using the pain subscales of the WOMAC OA index and the HRQoL instrument short form (SF)-36 and pain-related items measured on the BPI scale, and the overall safety and tolerability of the drug. Secondary objectives analysed on an exploratory basis included assessing the effect of treatment on subjects' HRQoL using all other subscales, except pain, of the instrument SF-36, the effect of treatment on subjects' functional impairment and stiffness using these subscales of the WOMAC OA index, the effect of treatment on subjects' quality of sleep using a medical outcome study (MOS) sleep subscale score, and the dropout rate due to inefficacy.The study protocol and amendments were reviewed by the appropriate Independent Ethics Committee (IEC) or Institutional Review Board (IRB) for each study centre.The study was conducted in accordance with the ethical principles that have their origin in the Declaration of Helsinki  and that are consistent with good clinical practices (GCP) and applicable regulatory requirements.Subjects gave written informed consent before entering the study.This phase IIIb, multicentre, randomised, parallel-group, placebo-controlled, double-blind study was carried out at 18 sites in four European countries . The study included male and female subjects aged ≥40 years, with moderate-to-severe pain induced by OA (as defined by the American College of Rheumatology) of the hip or knee. Moderate-to-severe OA pain was defined as a mean weekly score of ≥5 on a scale of 0–10 for “pain on average” on the BPI scale, which was calculated as a mean of the pain assessments collected at screening visit (week −1), telephone call (week –0.5), and baseline visit (week 0). Subjects must have suffered from chronic OA pain in the target joint for more than 3 months, and their pain must not have been adequately controlled with daily analgesic (NSAIDs or paracetamol) treatment for the month before beginning the study. Subjects were excluded from the study for any of the following reasons: regular treatment with an opioid in the 4 weeks before the screening visit—infrequent use of tramadol, codeine, tilidine, or dihydrocodeine for no more than 10 days in the 4 weeks before the screening visit was acceptable, but subjects were to stop any use of weak opioids at the screening visit, another type of continuous pain that stood out in comparison with OA pain such as fibromyalgia, cervical radiculopathy, or chronic low back pain, any of the following 6 months before entering study: major trauma to target joints, infection in target joints, radiologically apparent avascular necrosis in target joints, hyaluronan injections in the target joints, arthrodesis in the year or arthroscopy in the 2 months before entering study, planned treatment that could have altered the degree of pain within the study period, subjects who were being treated with buprenorphine, nalbuphine, or pentazocine; corticosteroid injections in the 3 months before the start of the study.At the screening visit (week –1), subjects taking weak opioids discontinued their medication; subjects taking NSAIDs or paracetamol remained on a stable dose. Subjects were randomised to receive either oral OROS hydromorphone hydrochloride 4 mg once daily or matched placebo; placebo tablets were of identical appearance to the OROS hydromorphone hydrochloride tablets, that is matched for colour and size. Treatment comprised a 4-week titration phase and a 12-week maintenance phase. In the event of unsatisfactory pain control, subjects had their dose titrated 3-4 days after randomisation until week 4 of the study with intervals of at least 3-4 days between dose increments. Possible doses were 4 mg, 8 mg, 12 mg, 16 mg, 24 mg, and a maximum daily dose of 32 mg. There followed a 12-week maintenance phase on as stable a dose as possible. If a dose of 32 mg did not provide sufficient analgesia, subjects were withdrawn owing to lack of efficacy and had their dose tapered off by reducing their dose in specified increments every 2 days. At the end of the double-blind treatment phase, subjects had their dose tapered off to allow safe discontinuation of the study drug. This tapering off phase also applied if subjects prematurely discontinued. Paracetamol was allowed as rescue medication, provided that a subject did not exceed the total permitted daily dose (4 g per day until day 8 and then 2 g per day for the remainder of the study). Subjects returned to the clinic at 1, 2, 3, 4, 8, 12, and 16 weeks for scheduled assessments and were contacted by telephone call between visits. All items of the BPI were used to assess pain at screening, visit 1 (week 0), visit 5 (week 4), visit 6 (week 8), visit 7 (week 12), and visit 8 (week 16). Bodily pain, functional impairment, and stiffness were assessed using the WOMAC OA index at visit 1 (week 0), visit 5 (week 4), visit 6 (week 8), visit 7 (week 12), and visit 8 (week 16). HRQoL was assessed at visit 1 (week 0), visit 5 (week 4), visit 6 (week 8), visit 7 (week 12), and visit 8 (week 16) using the SF-36 HRQoL questionnaire. Quality of sleep was assessed at visit 1 (week 0) and visit 8 (week 16) using a MOS sleep subscale. AEs were monitored throughout the study. Subjects were randomly assigned to receive daily doses of OROS hydromorphone hydrochloride or placebo in a 1 : 1 ratio based on a computer-generated randomisation schedule prepared by an independent statistician (AJ). The randomisation was balanced by using randomly permuted blocks of subjects, with a block size of 4 and was stratified by OA of the hip or knee; study sites received blocks of study medication. There were two separate randomisation lists; one corresponded to OA of the hip and the other to OA of the knee. Each site received treatment kits for both strata (hip and knee), and the investigators were instructed to select the next available (consecutive) number for each of the strata. If subjects had OA of both the hip and knee, they were stratified according to whichever target joint was predominantly painful. Based on these randomisation lists, the study drug was packaged and labelled for the group of subjects according to the target joint. Subject numbers were preprinted on the study drug labels (distinctive identification numbers for hip and knee) and assigned as subjects qualified for the study. The medication kits were labelled with a 2-part tear-off label bearing information that met applicable regulatory requirements. One part of the tear-off label was attached to the subject's drug-dispensing log when the drug was dispensed. The investigator and the subject were blinded to treatment allocation.A difference of 1 point in “pain on average” on the BPI scale was considered to be a clinically important difference . Based oA reassessment of the sample size was done, without breaking the blind, when 50% of subjects were randomised and approximately 40% of subjects had either completed the study or dropped out. This analysis confirmed the assumptions of the sample size calculation.The safety population included all randomised subjects who received at least one dose of study drug. The intent-to-treat (ITT) population was used for efficacy analyses. The ITT population excluded subjects who had no post-baseline efficacy data and included subjects who discontinued early owing to lack of efficacy or other reasons. The per-protocol (PP) population was a subgroup of the ITT population that excluded subjects who discontinued early and all subjects with major protocol deviations. This population was used for supportive evidence for the efficacy analyses.The primary efficacy endpoint was assessed by recording the subjects' score in “pain on average” measured on the BPI scale at each study visit. Only data for the BPI collected at clinic visits was used. The primary efficacy endpoint was analyzed using a mixed-model regression analysis (mixed model for repeated measures (MMRM)), which took into account the correlation among repeated measures within individual subjects and allowed subjects with incomplete data (as a result of early dropout) to contribute their existing data to the analysis. The main model to test for the primary efficacy variable consisted of “pain on average” measured on the BPI scale as repeated measurement variable, treatment groups, time on study represented by the visit number, study joint, and baseline “pain on average” value (the latest pre-study treatment assessment) as fixed effects. The random effect was the subject number.Secondary efficacy endpoints were the total score of the WOMAC OA index , pain as assessed using the pain subscales of the WOMAC OA index , pain as assessed using the pain subscales of the HRQoL instrument SF-36 , pain as assessed by “pain at its worst in the last 24 hours”, “pain at its least in the last 24 hours”, and “pain right now” measured on the BPI scale , all subscales except pain of the HRQoL instrument SF-36 , the functional impairment and stiffness subscales of the WOMAC OA index , the MOS sleep subscale (visits 1 and 8), the dropout rate due to AEs, and the dropout rate due to inefficacy. Safety assessment was based on reported AEs, dropouts due to AEs, vital sign measurements, and physical examinations. Secondary endpoints and safety results were summarised descriptively. AEs were coded using MedDRA dictionary version 11.0 (22 May 2008), and analyses were done using SAS Version 9.1.3.Post hoc analyses were done to try to understand why the primary endpoint was not reached in this study. These included concomitant medication analyses to investigate, in an exploratory sense, the extent to which the primary objective of the study was compromised by use of concomitant analgesic medication, specifically paracetamol or NSAIDs. Analyses were done using Stata Version 9.2.The first subject attended the first study visit on 05 October 2007, and the last subject completed the last study visit on 24 November 2008.344 subjects were screened and 288 were randomised: 139 subjects to the OROS hydromorphone group and 149 subjects to the placebo group. The maintenance phase was completed by 84 subjects in the OROS hydromorphone group and 116 subjects in the placebo group. In both groups, AE, inefficacy, and withdrawal of consent were the most common reasons for discontinuation of study treatment. Flow of subjects through the study is summarised in The mean (standard deviation [SD]) age of subjects was 65 (±10.2) years. There were more subjects with OA of the knee (74%) than OA of the hip (26%). The baseline BPI, WOMAC OA index, HRQoL, and MOS sleep subscale scores results were similar for the OROS hydromorphone and placebo groups. Demography and baseline characteristics are summarised in The median (range) daily dose of study medication during the study, calculated from total dose used and the number of days on treatment, was 12.2 (3–28) mg and 20.1 (4–29) mg in the OROS hydromorphone and placebo groups, respectively.P = .1212). The factors “time on study” and baseline “pain on average” score measured on the BPI scale had a highly significant effect (P < .001) on the BPI scale “pain on average” score, which means baseline pain severity and time treated with the study drug had an influence on pain on average at endpoint; study joint (hip or knee) had no significant impact on the BPI scale “pain on average” score. Mean change from baseline in “pain on average” measured on the BPI scale score by time is shown in The study did not meet the primary objective of showing superiority of OROS hydromorphone compared with placebo in its analgesic effect in subjects with moderate-to-severe pain induced by OA of the hip or knee, as measured by mean change from baseline in “pain on average” measured on the BPI scale. The primary efficacy analysis did not show superiority of OROS hydromorphone compared with placebo  than the placebo group ; many of the AEs leading to discontinuation in the OROS hydromorphone group were typical opioid-related side effects, most commonly nausea and constipation. Subjects in the placebo group  more often dropped out owing to inefficacy compared with subjects in the OROS hydromorphone group .The majority of TEAEs reported during the study were of mild or moderate severity: 208/232 TEAEs in the OROS hydromorphone group and 103/109 TEAEs in the placebo group. The frequency of mild TEAEs was comparable between treatment groups, 35% versus 30% of subjects in the OROS hydromorphone and placebo group, respectively. Higher proportions of subjects reported moderate and severe TEAEs in the OROS hydromorphone group (33% moderate and 14% severe) compared with placebo (12% moderate and 4% severe).TEAEs that were possibly, probably, or very likely related to study drug were reported by 78% of subjects in the OROS hydromorphone group and 37% of subjects in the placebo group. Drug-related TEAEs were most frequently reported in the gastrointestinal disorders and nervous system disorders body systems in both groups; the frequency of these drug-related TEAEs was higher in the OROS hydromorphone group compared with the placebo group. Concomitant medications for the treatment of TEAEs were given to 48 (35%) subjects in the OROS hydromorphone group and 14 (9%) subjects in the placebo group. More subjects in the OROS hydromorphone group than the placebo group required treatment for drug-related constipation, nausea, and vomiting. Laxatives were used by 19.4% of subjects in the OROS hydromorphone group compared with 2.0% of subjects in the placebo group, and antiemetics were taken by 10.8% of subjects in the OROS hydromorphone group compared with 1.3% of subjects in the placebo group. One death (not considered related to study) occurred in the placebo group, no deaths occurred in the OROS hydromorphone group. There were 19 serious TEAEs reported during the study; 10 events occurred in 4 (2.9%) subjects in the OROS hydromorphone group, and 9 events occurred in 7 (4.7%) subjects in the placebo group.Post hoc analyses were done to try to determine the extent to which the primary objective of the study was compromised by use of concomitant paracetamol or NSAIDs. During the study, almost 100% of subjects received either NSAIDs or paracetamol either as concomitant medication or as rescue medication .N = 51; N = 236). Post-baseline “pain on average” scores measured on the BPI scale were lower throughout the study for OROS hydromorphone compared with placebo in subjects not taking concomitant NSAIDs N = 51; . Scores N = 49). Scores were similar between groups in subjects who did not take concomitant paracetamol (N = 238).Post-baseline “pain on average” scores measured on the BPI scale were lower throughout the study for OROS hydromorphone compared with placebo in subjects taking paracetamol . Ho. Ho33]).Subjects were using non-opioid analgesics and NSAIDs before entering the study; based on expert scientific advice and ethical considerations, concomitant and rescue medication were permitted in the study design. Although subjects' pain was not adequately controlled with the concomitant analgesics at inclusion, subjects in the placebo group had a good response without side effects, whereas subjects in the OROS hydromorphone group got a good response with side effects. The strong placebo effect observed suggests that subjects may not have needed opioid treatment and their pain score (and other assessment results) would have improved with continued paracetamol and/or NSAID treatment . Indeed,Subject selection may also have contributed to the outcome of this study. The subject selection criteria used may not have been stringent enough to ensure that only subjects with truly chronic pain were included; the mean “pain on average” score measured on the BPI scale was calculated from three assessments made during a one-week period from the screening visit to the baseline visit. Therefore, although subjects had sufficient pain severity to meet the inclusion criteria in the week immediately before the study, they may not have been experiencing pain from OA of that severity for a long period of time. It is, therefore, possible that some patients were experiencing a temporary exacerbation of pain that would have subsided with or without treatment. Comparison of the baseline WOMAC OA scores between the HOP trial and two previous placebo-controlled opioid studies suggest that the subjects in the HOP trial may have been less affected by their underlying illness compared with subjects in the other trials. In a randomised, placebo-controlled trial that recruited patients with OA requiring joint replacement and with moderate-to-severe pain that had been adequately controlled by weak opioids, transdermal fentanyl provided significantly better pain relief compared with placebo in patients even though previously prescribed NSAIDs and simple analgesics were continued . In a stDuring the study, drug-related TEAEs were reported by almost twice as many subjects in the OROS hydromorphone group compared with the placebo group. In both groups, the most frequently reported drug-related TEAEs were gastrointestinal and nervous system disorders; these events are commonly associated with opioids. No changes were observed in the well-documented safety profile of hydromorphone.n = 71) versus ER oxycodone initiated at a dose of 10 mg twice daily (n = 67). The study consisted of a 14-day dose-titration and stabilisation period and a 28-day maintenance period. The knee was the affected joint in 79.8% of participants. Comparable levels of pain relief reductions in pain severity were observed. Some improvements were evident early in the study, when patients were receiving lower doses of analgesic. Dropouts due to AEs were similar between treatment groups; 35.2% in the hydromorphone group and 32.8% in the oxycodone group. There is some limited evidence that starting with a low dose of opioid and slowly titrating to a higher dose may be advantageous for avoiding intolerable side effects when starting treatment with oxycodone, oxymorphone, or hydromorphone –27). The. The27])In conclusion, the primary objective of showing superiority for OROS hydromorphone hydrochloride compared with placebo in its analgesic effect in subjects with moderate-to-severe pain induced by OA of the hip or knee was not met in this study. Secondary efficacy endpoints were also similar between the two treatment groups. Possible reasons for failure of the study are that subjects were not experiencing chronic moderate-to-severe pain or that their pain was adequately treated with paracetamol and/or NSAIDs. No changes were observed in the well documented safety profile of hydromorphone.Before selecting patients with chronic OA pain for treatment with opioids, we recommend that clinicians be satisfied that pain is truly chronic and does not respond to weaker analgesics. A report published by the European league against rheumatism (EULAR) OA task force notes that opioid analgesics, with or without paracetamol, are useful alternatives in patients in whom NSAIDs, including COX-2 selective inhibitors, are contraindicated, ineffective, and/or poorly tolerated .


It is well established that smoking rates in people with common mental disorders such as anxiety or depressive disorders are much higher than in people without mental disorders. It is less clear whether people with these mental disorders want to quit smoking, attempt to quit smoking or successfully quit smoking at the same rate as people without such disorders.We used data from the 2005 Cancer Control Supplement to the United States National Health Interview Survey to explore the relationship between psychological distress as measured using the K6 scale and smoking cessation, by comparing current smokers who had tried unsuccessfully to quit in the previous 12 months to people able to quit for at least 7 to 24 months prior to the survey. We also used data from the 2007 Australian National Survey of Mental Health and Wellbeing to examine the relationship between psychological distress (K6) scores and duration of mental illness.The majority of people with high K6 psychological distress scores also meet diagnostic criteria for mental disorders, and over 90% of these people had first onset of mental disorder more than 2 years prior to the survey. We found that people with high levels of non-specific psychological distress were more likely to be current smokers. They were as likely as people with low levels of psychological distress to report wanting to quit smoking, trying to quit smoking, and to have used smoking cessation aids. However, they were significantly less likely to have quit smoking.The strong association between K6 psychological distress scores and mental disorders of long duration suggests that the K6 measure is a useful proxy for ongoing mental health problems. As people with anxiety and depressive disorders make up a large proportion of adult smokers in the US, attention to the role of these disorders in smoking behaviours may be a useful area of further investigation for tobacco control. The health consequences of smoking have been long known and are well described ,2. As smThere is a strong association between smoking and mental disorders, and around one-third of adult smokers in the US and Australia have been found to have DSM-IV and ICD-10 mental disorders. In comparison only 15% of adults who are not current smokers have diagnosable mental disorders . While tPrevious studies have investigated the relationship between smoking cessation attempts and outcomes, but these have mainly focused on socio-demographic predictors of quit attempts and successful smoking cessation ,9,17-19.In consideration of the high proportion of US adult smokers who have common mental disorders, we set out to add to previous research by investigating the relationship between mental health, smoking cessation attempts and successful smoking cessation. The aims of the study were to test the following hypotheses:a) rates of smoking increase with increasing level of non-specific psychological distress after adjusting for socio-demographic factors including education, income and marital statusb) among adults who smoke, rates of wanting to quit smoking, attempting to quit smoking and using smoking cessation aids do not vary by level of non-specific psychological distressc) among adults who smoke, rates of quitting smoking decrease with increasing level of non-specific psychological distress.To test these hypotheses we used data from the 2005 US National Health Interview Survey (NHIS), a large representative sample of the US population n = 31,428). The NHIS uses the K6 scale to assess non-specific psychological distress . The NHI. HoweverWe used data from the 2005 United States National Health Interview Survey (NHIS) . The NHIAs the study consisted of analysis of publicly available confidentialised files, no institutional ethics approval was required.We used the full sample of 31,428 NHIS respondents to examine the relationship between socio-demographic characteristics, psychological distress and current smoking. We used the subset of 6,511 current smokers in the NHIS to examine the relationship between psychological distress and wanting to quit smoking, trying to quit smoking and using smoking cessation aids.current smokers with a recent unsuccessful quit attempt. Respondents who don't currently smoke were asked "How long has it been since you quit smoking cigarettes?" Those who responded by choosing the category 7-24 months were identified as the group comprising recent successful quitters. The screening process used to define these two groups is illustrated in Figure To examine the relationship between outcome of smoking cessation attempts, psychological distress and socio-demographic characteristics, we selected a cohort comprising recent successful quitters  with current smokers who had unsuccessfully attempted to quit smoking in the past 12 months. Respondents were asked "Have you smoked at least 100 cigarettes in your entire life?", and if yes, "Do you now smoke cigarettes every day, some days, or not at all?" Respondents who said they smoked every day or some days were asked "During the past 12 months, have you stopped smoking for more than 1 day because you were trying to quit smoking?" Those that said yes were identified as the group of A range of demographic characteristics collected in the NHIS was used. Age was grouped in 10 year groups up to 65 years and over (with the youngest group coded as 18-24 years). Educational status was divided into less than high school graduate, high school graduate or GED , some college or associate degree, and college graduate or higher. Family income is considered a sensitive data item, and not all respondents are willing to report their income. Where this occurs, respondents are asked to indicate if their family income is above or below $20,000 per annum. For respondents who provided their income, we grouped family income into four categories: under $20,000, $20,000-$44,999, $45,000-$74,999, $75,000 and above. Respondents who didn't provide their full income were separately classified into above or below $20,000. We also used sex, marital status, whether born in the United States, and housing tenure.Non-specific psychological distress was measured in the NHIS using the K6 non-specific psychological distress scale ,31. The Data from both the US NHIS and the Australian NSMHWB have been weighted to account for the sample design and response patterns to allow estimation for the US or Australian adult population. All analysis was conducted using SAS software, Version 9.2 . We usedBecause the K6 scale specifically refers to the 30 days prior to the survey, we first examined data from the Australian NSMHWB to test the relationship between the K6 measure of non-specific psychological distress, ICD-10 mental disorders as identified using the CIDI, and first onset of anxiety or depressive disorders. We found that the distribution of K6 scores in Australia was similar to that found in the US NHIS, particularly in the higher levels of distress categories Table .For Australian adults who were diagnosed with depressive or anxiety disorders in the NSMHWB, the survey ascertained date of first onset of symptoms. For those adults with high or very high K6 scores who were given an ICD-10 diagnosis of an anxiety or depressive disorder, the vast majority had first onset of disorder more than 10 years prior to the survey. Less than 10% reported onset within two years of the survey. Even though the K6 questions ask about the 30 days prior to the survey, the vast majority of people with disorders reporting high levels of psychological distress have had their disorder for many years. Among people with K6 scores in the range 13-24, 90.2% (95% CI: 84.5%-95.8%) had first onset of symptoms more than 5 years prior to the survey. Among individuals with K6 scores in the range 8-12, 88.9% (95% CI: 84.1%-93.7%) had first onset more than 5 years prior to the survey, and among those with K6 scores in the range 3-7, 80.9% (95% CI: 77.5%-84.4%) had first onset more than 5 years prior to the survey  would like to completely quit smoking cigarettes, b) if they had stopped smoking for more than one day in the past 12 months because they were trying to quit smoking, and c) whether they had used nicotine gum, patches, spray, inhalers, lozenges or prescription pills to try to quit smoking. The proportion of people wanting to quit smoking was lowest among people with K6 scores in the lowest range (0-2) at 61.6%. The proportion of people wanting to quit smoking was significantly higher in each other category of K6 score . The apparent drop in proportion wanting to quit smoking between people with K6 scores in the 8-12 range and people with K6 scores 13 and over was not statistically significant (p = 0.100) Table . People Figure The K6 scale is a useful short measure for assessing mental health problems in omnibus surveys. It was specifically designed for surveys such as the NHIS which seek to assess a large number of topics, and thus need effective, short screening scales. Our results showing that the K6 score was strongly associated with ICD-10 diagnosis of anxiety or depressive disorders are consistent with previous findings ,32. AlthThe K6 has an additional advantage of being a dimensional scale, with higher scores being associated with higher levels of psychological distress. It has been suggested that research based on applying ICD-10 or DSM-IV diagnostic criteria may underestimate the contribution of mental illness to smoking behaviours by ignoring the contribution of sub-threshold disorders . StudiesThe relationship between smoking and severe mental illness is well known ,40. PrevWe found that people with moderate and high levels of non-specific psychological distress were more likely than people with low levels of psychological distress to want to quit smoking and to try to quit smoking. People with moderate and high levels of psychological distress were also just as likely as those with low levels of non-specific psychological distress to use smoking cessation aids. However, they were significantly less likely to have successfully quit smoking for six months or more. Mental illness has been associated with higher levels of nicotine dependence, and higher intensity of smoking ,49. It iPeople with moderate and high levels of non-specific psychological distress may require a higher level of support, or more specifically targeted strategies to support their smoking cessation efforts. Analysis of tobacco industry marketing research and market segmentation studies has shown that historically the tobacco industry has used psychosocial and other personality traits to develop targeted promotional strategies that encourage uptake of tobacco use ,50,51. AIt is well recognised that the profile of adult smokers now is demographically and psychosocially very different from the profile of those who smoked a couple of decades ago . That suIt is known that many common mental disorders, in particular anxiety disorders, have onset during childhood and adolescence, and persist for many years . Most adOnly a small proportion of people with high levels of non-specific psychological distress, and common mental disorders such as anxiety and depression, are treated by specialist mental health services . The majChanges in the socio-demographic profile of smokers over time, and the persistence of smoking despite long-term advertising of the health dangers have led to the development of the hardening hypothesis and identification of possible hard-core smokers . This hyCross-sectional studies, such as the NHIS, describe associations but cannot inform causal pathways. It is not possible to conclude from these data whether psychological distress leads to smoking uptake or whether smoking causes psychological distress or whether both are related to some other causal factors. However, the data from the Australian NSMHWB showed that the vast majority of people who have moderate or high levels of non-specific psychological distress have mental disorders of long duration. It is reasonable to assume that a high proportion of people with moderate and high levels of non-specific psychological distress in the NHIS sample would have had long-standing elevated levels of psychological distress, predating quit attempts in the 12 months prior to the survey, in most cases by many years. A longitudinal study of Swedish male military conscripts found that lower levels of smoking cessation between ages 30 and 50 were predicted by higher levels of psychological distress measured at 18 years .While the K6 scale has been shown to be a good predictor of mental disorders, and people with high K6 scores are likely to have mental disorders of long duration, K6 scores are not the same as making formal psychiatric diagnoses. Studies that use the K6 and the CIDI are primarily designed to assess mental disorders during discrete time intervals. It has also been suggested that the strong association between anxiety, depression and smoking could be conceptualised in terms of neuroticism - the general personality trait that encompasses long-term and persistent susceptibility to anxiety and depressive symptoms ,63. TherOverall, people with moderate or high levels of non-specific psychological distress are more likely to be current smokers. People with moderate or high levels of psychological distress are at least as likely as anyone else to report wanting to quit smoking, trying to quit smoking, and using smoking cessation aids. However, people with psychological distress are less likely to have successfully quit smoking. Common mental health problems such as anxiety and depression, which are highly correlated with psychological distress, are important, yet commonly overlooked factors, in tobacco control programs. As these mental health problems have high prevalence, and many people with these mental health problems do not receive treatment, both service-based and population-based initiatives will be required to address smoking in this population. To date, targeted population-based strategies in particular, seem to be an under-developed area. Attention to developing new programs and initiatives directed at smokers with common mental health problems may be helpful in reducing the high rates of smoking-related morbidity and mortality in this group.The authors declare that they have no competing interests.DL and FM conceived the original idea for the study. All authors contributed to the development of the study methodology. DL acquired and analysed the data, and wrote the first draft of the manuscript. All authors edited the paper. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/11/256/prepub


Aedes aegyti and A. albopictus and increasing urbanization. With no effective treatment and limited success of vector control, dengue vaccines constitute the best control measure for the foreseeable future. With four interacting dengue serotypes, the development of an effective vaccine has been a challenge. Several dengue vaccine candidates are currently being tested in clinical trials. Before the widespread introduction of a new dengue vaccine, one needs to consider how best to use limited supplies of vaccine given the complex dengue transmission dynamics and the immunological interaction among the four dengue serotypes.Dengue is a mosquito-borne infectious disease that constitutes a growing global threat with the habitat expansion of its vectors We developed an individual-level (including both humans and mosquitoes), stochastic simulation model for dengue transmission and control in a semi-rural area in Thailand. We calibrated the model to dengue serotype-specific infection, illness and hospitalization data from Thailand. Our simulations show that a realistic roll-out plan, starting with young children then covering progressively older individuals in following seasons, could reduce local transmission of dengue to low levels. Simulations indicate that this strategy could avert about 7,700 uncomplicated dengue fever cases and 220 dengue hospitalizations per 100,000 people at risk over a ten-year period.Vaccination will have an important role in controlling dengue. According to our modeling results, children should be prioritized to receive vaccine, but adults will also need to be vaccinated if one wants to reduce community-wide dengue transmission to low levels. An estimated 40% of the world's population is at risk of infection with dengue, a mosquito-borne disease that can lead to hospitalization or death. Dengue vaccines are currently being tested in clinical trials and at least one product will likely be available within a couple of years. Before widespread deployment, one should plan how best to use limited supplies of vaccine. We developed a mathematical model of dengue transmission in semi-rural Thailand to help evaluate different vaccination strategies. Our modeling results indicate that children should be prioritized to receive vaccine to reduce dengue-related morbidity, but adults will also need to be vaccinated if one wants to eliminate local dengue transmission. Dengue is a challenging disease to study because of its four interacting serotypes, seasonality of its transmission, and pre-existing immunity in a population. Models such as this one are useful coherent framework for synthesizing these complex issues and evaluating potential public health interventions such as mass vaccination. Aedes aegypti and A. albopictus, because of climate change and increasing urbanization in the developing world. Severe dengue cases  and dengue hemorrhagic fever (DHF)) occur primarily among children Dengue is a mosquito-borne disease, caused by a flavivirus with four serotypes, responsible for an estimated 500,000 hospitalizations and 20,000 deaths per year, mostly in the tropics Several dengue vaccine candidates are currently in development or in clinical trials Here, we investigate the potential effectiveness of different dengue vaccination strategies using a model of dengue transmission in a Thai population. The individual-level stochastic model was developed to match the epidemiology of dengue in a population in semi-rural Thailand that has experienced hyperendemic dengue transmission for many years. We modeled both single-year campaigns, in which part of the population is vaccinated well before the dengue season, and multi-year roll-outs, in which young children are vaccinated first and progressively older individuals are vaccinated in subsequent years as part of a catch-up campaign.We developed an agent-based model of dengue transmission. The model is described in detail in Secondary cases may have severe outcomes  at an age-specific proportion . SecondaWe describe the synthetic population created for the model in detail in Thailand . We popuThailand . The synWithin each square kilometer, individual households, schools, and workplaces are assigned random locations. Children of the appropriate age are sent to the elementary school (ages 5 to 10 years), lower secondary school (ages 11 to 14 years), or upper secondary school (15 to 17 years). People of the appropriate age are assigned workplaces according to a gravity model in which people tend to commute to locations that are nearby and have a relatively high population density. Workplaces have an average of 20 workers, who occupy the same location during the workday.During the morning and evening hours, people are at home, and they may go to school or work during the rest of the day . IndividTo simulate multi-year epidemics, we make two simplifying assumptions: 1) there is no correlation of prior exposure to dengue within households and 2) household structures do not change over time. After simulating a single year of dengue transmission, we “age” the population by setting the immune status (both prior infections and vaccination) of all individuals of age In the model, individuals are assigned to have immunity from prior exposure to the four serotypes of dengue based on their age. The age-specific immune profile is based on two sources of data on the prevalence of serotypes in Thailand. Thailand's Ministry of Public Health releases an “Annual epidemiological surveillance report” that summarizes dengue serotype surveillance data. Reports from 2000–2009 are available at epid.moph.go.th, which we summarize in http://epid.moph.go.th) and Queen Sirikit National Institute of Child Health in Bangkok from 1973–1999 We estimate the age-specific immunity to the four dengue serotypes in our model. We assume that the level of exposure to dengue each year was such that 11% of nave individuals would be infected, based on studies in nearby Vietnam For each of the years for which we have serotype prevalence estimates, we randomly selected 11% of the population who was alive in that year  to be exposed to dengue, and for each individual simulated exposure to a single serotype drawn from that year's prevalence data. Individuals exposed to a serotype are considered to be permanently immune. For years before 1973, we performed the same procedure, except that we assumed that the serotype prevalence was the mean serotype prevalence from 1973–2009. The mean serotype prevalences are 9.8%, 14.6%, 7.5%, and 5.2% for DENV-1, DENV-2, DENV-3, and DENV-4, respectively. In other words, we assumed that there was a constant 11% exposure to dengue (sufficient to infect) for all individuals, regardless of age or immune status, and that exposure to a serotype at any point in an individual's past grants sterilizing immunity to that serotype. In other words, each person who is exposed to dengue each year is exposed to exactly one serotype of dengue, and he or she gains sterilizing immunity to that serotype if he or she was not already immune from prior exposure.Because the four serotypes have different symptomatic fractions, surveillance data give a skewed representation of the number of individuals infected by each serotype. We re-scaled the number of cases for each of the four serotypes in the historical data as described in We simulated a single year of dengue transmission in Ratchaburi, Thailand . Dengue The simulated dengue season produced a 5% infection attack rate with some stochastic variation among runs . BecauseWe report the total number of uncomplicated and severe (DSS/DHF) cases produced by our model assuming perfect surveillance. Estimates of reporting rates would be needed to compare our modeling results with actual surveillance data. Wichmann et al. estimated that, among children, total dengue cases in Thailand may be underreported by a factor of 8.7 and severe (inpatient) dengue cases by 2.6, with less underreporting in school-aged children than in younger children During the simulated seasonal peak of dengue transmission, a single person infected an average of 1.9 to 2.3 others, depending on the serotype . This isWe simulated vaccinating the population to protect them before a single dengue season. Recently, an observer-blind, randomized, controlled, phase 2b vaccine trial was conducted with a tetravalent dengue vaccine increased transmission of the remaining serotype, at least in the short term.Vaccinating 70% of children 2 to 14 years old would reduce the number of dengue infections by 48%, uncomplicated dengue fever cases by 41%, and severe dengue cases (DSS/DHF) by 54% in a single year . The pronot vaccinated receive indirect protection when enough of the remaining population is vaccinated. In our simulations, those who are over 46 years old are never vaccinated, but people in this age group were 44%, 61%, and 71% less likely to become infected when 30%, 50%, and 70% of those from ages 2 to 46 years were vaccinated. Unvaccinated individuals from ages 2 to 46 were 60%, 80%, and 91% less likely to become infected when 30%, 50%, and 70% of this age cohort were vaccinated.Those who are Certain age groups could be prioritized to receive vaccine. Younger people have the least prior exposure, so they would be the most likely to become infected with and transmit dengue. Simulations demonstrated that vaccinating children (2–14 years old) would reduce dengue infections in the total population more than using the same number of doses to cover both children and adults (2–46 years old) . HoweverDue to limited vaccine availability and the logistics of mass vaccination programs, dengue vaccine will probably be deployed in multi-year vaccine roll-out campaigns We also simulated a vaccine roll-out that extended the catch-up to include adults up to age 46. This roll-out targets the same age groups for the first three years as the previously described roll-out, but after this point both 2-year-olds and the youngest four unvaccinated age cohorts are vaccinated, as shown in We used a dengue simulation model to estimate that vaccination of 50% of the population of rural Thailand could be sufficient to reduce local dengue transmission to low levels. Based on our modeling study, we conclude that at least 70% efficacy against infection for all serotypes is desirable if one wants to control dengue in a hyperendemic area, and a higher efficacy vaccine would require less careful targeting of vaccine to reduce community-wide transmission of dengue. We further showed that vaccinating children is the most efficient use of vaccine to reduce cases and hospitalizations, but control of dengue transmission would also require vaccinating adults. In addition, both vaccinated and unvaccinated people would receive protection from mass vaccination because of the considerable indirect effects of dengue vaccination. A vaccine that only protects against only three serotypes could lead to a significant reduction in overall vaccine effectiveness. Further work will be needed in order to understand how to use vaccines that may not protect against all four serotypes. Using a detailed model of dengue transmission allows one to explore strategies that target vaccines most efficiently.To capture the complex interactions required to evaluate the effectiveness of mass vaccination with tetravalent dengue vaccines, the model includes vector population seasonality An estimated 40% of the world's population is at risk of dengue infection Large-scale vaccination campaigns would be both challenging and costly but could be more cost-effective than relying solely on vector control and other non-pharmaceutical interventions Figure S1Diagram of how vaccine roll-out occurs in the model. In the model, we target a set of age cohorts each year for vaccination. The numbers in the diagrams indicate the ages of the population cohorts in years. The numbers in black in each row indicate the cohorts targeted each year, while the numbers in red indicate those already protected by vaccine from previous years. The set of individuals who are protected advance in age each year, so the youngest eligible cohort (2-year-olds) needs to be vaccinated every year. (A) A roll-out that covers only children from ages 2 to 14 years. (B) A roll-out that covers both children and adults from ages 2 to 46 years.(EPS)Click here for additional data file.Table S1Serotype surveillance data from Thailand's Ministry of Public Health. Data from http://epid.moph.go.th/Annual/.(PDF)Click here for additional data file.Table S2Serotype surveillance data from Queen Sirikit National Institute of Child Health in Bangkok. Data from Nisalak et al (2003).(PDF)Click here for additional data file.Text S1Dengue transmission model description.(PDF)Click here for additional data file.Text S2Parameter selection for the model.(PDF)Click here for additional data file.Text S3Sensitivity of attack rates to maximum infection parity assumptions.(PDF)Click here for additional data file.Text S4Sensitivity of attack rates to vaccine efficacy.(PDF)Click here for additional data file.