text:
The dengue virus has a single-stranded positive-sense RNA genome of ∼10.700 nucleotides with a single open reading frame that encodes three structural (C, prM, and E) and seven nonstructural (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) proteins. It possesses four antigenically distinct serotypes (DENV 1–4). Many phylogenetic studies address particularities of the different serotypes using convenience samples that are not conducive to a spatio-temporal analysis in a single urban setting. We describe the pattern of spread of distinct lineages of DENV-3 circulating in São José do Rio Preto, Brazil, during 2006. Blood samples from patients presenting dengue-like symptoms were collected for DENV testing. We performed M-N-PCR using primers based on NS5 for virus detection and identification. The fragments were purified from PCR mixtures and sequenced. The positive dengue cases were geo-coded. To type the sequenced samples, 52 reference sequences were aligned. The dataset generated was used for iterative phylogenetic reconstruction with the maximum likelihood criterion. The best demographic model, the rate of growth, rate of evolutionary change, and Time to Most Recent Common Ancestor (TMRCA) were estimated. The basic reproductive rate during the epidemics was estimated. We obtained sequences from 82 patients among 174 blood samples. We were able to geo-code 46 sequences. The alignment generated a 399-nucleotide-long dataset with 134 taxa. The phylogenetic analysis indicated that all samples were of DENV-3 and related to strains circulating on the isle of Martinique in 2000–2001. Sixty DENV-3 from São José do Rio Preto formed a monophyletic group (lineage 1), closely related to the remaining 22 isolates (lineage 2). We assumed that these lineages appeared before 2006 in different occasions. By transforming the inferred exponential growth rates into the basic reproductive rate, we obtained values for lineage 1 of R0 = 1.53 and values for lineage 2 of R0 = 1.13. Under the exponential model, TMRCA of lineage 1 dated 1 year and lineage 2 dated 3.4 years before the last sampling. The possibility of inferring the spatio-temporal dynamics from genetic data has been generally little explored, and it may shed light on DENV circulation. The use of both geographic and temporally structured phylogenetic data provided a detailed view on the spread of at least two dengue viral strains in a populated urban area.
Author Summary
Most of the molecular phylogeny studies of dengue fever, an important public health problem, use convenience samples for their analysis, and they do not evaluate the spatial and temporal features involved in the spread of the different serotypes (and genotypes) circulating in urban settings during an outbreak. Our study describes the patterns of spread of different lineages of dengue 3 virus circulating in a medium-sized city from Brazil, and we also analyzed the dynamics and microevolution of the disease during the 2006 outbreak. We used both geographic and temporally structured phylogenetic data, which provided a relatively detailed view on the spread of at least two dengue viral lineages circulating in an urban area. The pattern of dengue virus circulation might be similar to many other settings all over the world, and the information provided by our study can help a better understanding of dengue outbreaks, providing important information for public-health systems. We could identify at least two lineages, which were introduced in different occasions. They circulated and spread at different rates within the city, and this differential spread and the role of socioeconomic features in this phenomenon are discussed.
Citation: Mondini A, Bronzoni RVdM, Nunes SHP, Chiaravalloti Neto F, Massad E, Alonso WJ, et al. (2009) Spatio-Temporal Tracking and Phylodynamics of an Urban Dengue 3 Outbreak in São Paulo, Brazil. PLoS Negl Trop Dis 3(5): e448. https://doi.org/10.1371/journal.pntd.0000448
Editor: Duane Gubler, Duke University-National University of Singapore, Singapore
Received: September 26, 2008; Accepted: April 30, 2009; Published: May 26, 2009
Copyright: © 2009 Mondini et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by FAPESP grants to MLN (04/11098-2) and FCN (06/01070-9). MLN is supported by a FINEP grant (Genprot DENGUE). RVMB is a recipient of a FAPESP fellowship. AM is a recipient of a CAPES scholarship. This work is s supported in part by the Viral Genetic Diversity Network (FAPESP). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
The genus Flavivirus includes 53 arthropod borne viruses that can cause severe encephalitis, hemorrhagic fever and febrile illness in humans [1]. Dengue viruses (DENV), Saint Louis Encephalitis virus (SLEV), and Yellow Fever virus (YFV) belong to this genus and are important public health issues in most tropical and subtropical countries [2]. Dengue is the most common arboviral infection all over the world [3]. Like other flaviviruses, dengue virus has a single-stranded positive-sense RNA genome of ∼10,700 nucleotides that is surrounded by a nucleocapsid and covered by a lipid envelope with viral glycoproteins. The RNA genome contains a single open reading frame (ORF) flanked by two untranslated regions (UTRs 3′ and 5′). The single ORF encodes a precursor polyprotein, which is co- and post-translationally cleaved into three structural (C, prM and E) and seven nonstructural (NS1, NS2A, NS2B, NS3, NS4A, NS4B, NS5) proteins [4]. The disease is caused by four antigenically distinct virus serotypes (DENV 1–4) and each serotype harbors phylogenetically defined genotypes [5] that have been experiencing massive bursts of genetic diversity as a consequence of the exponentially increasing human population during the last 200 years [5],[6],[7].
Dengue infection may be asymptomatic and lead to undifferentiated fever, dengue fever (DF) or evolve to more serious conditions (dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS)) [3],[8]. DF is an acute febrile viral disease that is characterized by headaches, biphasic fever, skin rash, retro orbital pain, leukopenia, thrombocytopenia and lymphadenopathy [3]. DHF is characterized by high fever, hemorrhagic manifestations and signs of circulatory failure. Patients presenting such symptoms may develop hypovolemic shock, leading to DSS, which can be fatal [8]. Outside Africa, the disease is transmitted mainly by the Aedes aegypti mosquito, which is widely distributed and established in all tropical countries and subtropical countries. Nearly three billion people are at risk of infection by DENV [9]. Brazil was responsible for approximately 94.5% of the reported dengue cases in Central and South America and 60% all over the world in 2007. Moreover, until the 39th epidemiological week, which started in September 23rd 2007 and finished in 29th 2007, 481.316 cases of DF (out of a population of approximately 186 million people, www.ibge.gov.br/english/) were reported along with 1076 DHF manifestations [10]. At the same period, São Paulo State with 21% of the Brazilian population was responsible for 17% of the cases (82.684). The impact of the disease is very heterogeneous in the State: the city of São José do Rio Preto – included in our study - reported 12% (9.331) of the occurrences in the State having only 1% of its population [11]. Even before the 2006 outbreak, dengue was endemic in São José do Rio Preto [12]. Many molecular phylogeny studies addressed particularities of the dynamics of the different dengue serotypes [6],[7],[13],[14],[15],[16],[17],[18],[19],[20],[21],[22],[23],[24],[25]. However, there is still a need to study particular outbreaks in single urban settings at a fine-grained spatio-temporal scale. In the present work we describe the pattern of spread of distinct lineages of DENV-3 virus circulating in São José do Rio Preto, São Paulo, Brazil during the 2006 outbreak and analyze the dynamics and microevolution during the outbreak.
Materials and Methods
Study site
The city of São José do Rio Preto (SJRP) is on the northwestern region of São Paulo State, Brazil (20°49′11″ S e 49°22′46″ W), with a total area of 434,10 Km2 and an urban area of 96,81 Km2. The estimated population in 2007 was 424,114. SJRP has a tropical climate with a mean annual temperature of 25°C and mean rainfall of 1410 mm concentrated in the summer months. The city has development indexes comparable to those of developed countries and its economy encompasses industry, services, commerce and agro-business. The urban area of the municipality is divided in 432 census tracts. The census tracts comprise 300 homes in areas defined by the Instituto Brasileiro de Geografia e Estatística — IBGE (Brazilian Institute of Geography and Statistics) to optimize the collection of data sets during census. Although SJRP was infested by the Aedes aegypti in 1985, only imported dengue cases where reported until 1989. Human to human DENV-1 transmission was first observed in 1990. From that date, dengue cases have been reported every year, with the exception of 1992 [12] and DENV-2 and DENV-3 were introduced in 1998 and 2006.
Geo-coding of autochthonous dengue cases was done using ArcGIS 9.0 (Environmental Systems Research Institute, Inc.). The geographic position of each patient was assumed to be the latitude and longitude of their postal code (zip code) obtained from sampled patient address records provided by the municipality of São José do Rio Preto.
Sample collection
Blood samples from patients presenting acute febrile illness, with or without hemorrhagic manifestations, infection with sudden start, nausea, vomit, diarrhea, symptoms of DF and DHF were collected for Flavivirus testing in the municipal health units and hospitals, upon informed consent. This study was approved by the Ethical Review Board of the Faculdade de Medicina de São José do Rio Preto and blood collection was performed upon Written Informed Consent.
cDNA synthesis and sequencing
The blood samples were centrifuged and the viral RNA was extracted from the serum with the QIAmp viral RNA mini kit (Qiagen) according to the manufacturer's instructions. The first RT-PCR was performed using Flavivirus generic primers based on the non-structural protein 5 (NS5), which is a conserved region in dengue viruses and would detect most of the circulating dengue virus in Brazil in a single PCR reaction. In the second PCR, nested assays based on multiplex or conventional systems were used with species-specific primers for virus identification [26]. The forward FG1 (5′TCAAGGAACTCCACACATGAGATGTACT3′) and reverse FG2 (5′GTGTCCCATCCTGCTGTGTCATCAGCATACA3′) primer set anneals to the NS5 gene, producing amplicons of approximately 958 bp [27]. A specific inner primer for DENV-3 (5′TTCCTCGTCCTCAACAGCAGCTCTCGCACT3′) produced amplicons with 659 bp [26]. The fragments were purified from PCR mixtures and sequenced with the BigDye v3.1 Terminator (Applied Biosystens, Foster City, CA, USA) using the forward FG1 primer and the reverse DENV-3 primer in an ABI377 automated sequencer (Applied Biosystenss, Foster City, CA, USA). The products were aligned with Accelrys Gene 2.0 (Accelrys Software Inc. 2006).
Phylogenetic reconstruction
In order to type the sequenced samples, 52 reference sequences including representatives of the 4 serotypes were hand-aligned in Se-Al version 2.0a11 program (data available from authors upon request). The dataset generated was used for phylogenetic reconstruction with the maximum likelihood criterion using a genetic algorithm method implemented in the program GARLI version 0.95 [28] that estimates simultaneously the best topology, branch lengths and the best values for the parameters for the General Time Reversible (GTR) model of nucleotide evolution with Gamma-distributed variable rates and invariant sites (GTR+Γ+I). One hundred independent random runs were conducted with GARLI and the tree with highest likelihood was subsequently used as input for further topological optimization with PAUP v.4.0b10 [29], since both GARLI and PAUP calculate the same likelihood score for a tree under the same model. Support for the topology was sought after 100 bootstrap replicates with GARLI.
Phylodynamics of dengue 3
The best demographic model among: (i) constant population size, (ii) exponential population growth and, (iii) logistic population growth for the data, the rate of growth (r = Ne.g) (i.e., the effective number of transmission events times the generation time of the pathogen), rate of evolutionary change (μ) (subs/site/year) and, the Time to Most Recent Common Ancestor (TMRCA) were estimated from the Coalescent using Bayesian inference with a Markov Chain Monte Carlo (MCMC) search method available in BEAST v1.6 [30]. Sequences were dated according to the day of sampling and the MCMC were run until the effective sampling size (ESS) for each parameter converged at values above 100. The confidence intervals for each parameter were given by the 95% highest probability density (HPD). The data was analyzed using a relaxed molecular clock (uncorrelated lognormal) under the constant, exponential and logistic demographic models. Because the priors were not necessarily the same, demographic models were compared by calculating the Log 10 of the Bayes factor using the harmonic mean without smoothing of the sum of the likelihoods for the coalescent and tree obtained during each MCMC for each model with TRACER v1.6 program [30].
Analysis of spatio-temporal dispersion patterns
First, to examine whether the samples were overly spatially or temporally structured we generated matrices of distances between the samples and compared those matrices. The matrices of distances show how each sample is relatively close to all others, considering separately their date of collection, their place of collection and their genetics. Corrected genetic distances were obtained with PAUP using the values for the GTR+Γ+I model found for the maximum likelihood tree inferred with GARLI. Geographic distances were measured along straight lines (using geographic information system) between samples and temporal distances were the interval between sample collections. The null hypothesis of no association between the genetic and geographic and temporal distances was assessed using partial Mantel tests [31]. Statistical distributions were generated by a Monte Carlo method randomising rows (and corresponding columns) in the matrix of phylogenetic distances 1,000 times, and calculating for each one of these permutations the partial correlation coefficient between the two matrices, controlling for the third (geographic) matrix. The one-tailed probability of a type I error (i.e., rejection of a true null hypothesis) was taken as the proportion of correlation coefficients sorted in ascending order that were higher than or equal to the obtained correlation coefficient. We accepted probabilities below α = 0.05 as statistically significant. Second, to obtain the putative spatio-temporal pattern of spread of dengue in SJRP we applied a simple algorithm that checks all samples (but the first) in a temporal sequence, and would attribute the linkage of ancestry to the (temporally) previous sample with higher genetic proximity (hence, let's call it "nepotistic algorithm"). No obvious important geographic barriers for the circulation of the vector or host were identified within the area studied; hence we did not add any friction/cost to the movement of viruses into the algorithm. We did apply instead a limit of 0.00739 substitutions/site/year that we considered as the genetic distance that could have been generated by a virus replicating during 100 days at a rate of 10−4 substitutions/site/year. Therefore, if one sample was not closer in distance than this value to any of its chronologically previous samples, it was assumed that this sample resulted from another virus introduction in the locality.
Calculation of the Basic Reproduction Number (R0) for the 2006 SJRP dengue epidemics
Because each viral sequence was obtained from a distinct patient, nodes in the virus gene genealogy can be assumed as transmission events in the human population. Therefore the basic reproductive rate of a pathogen (R0) during an epidemics can be estimated as R0 = 1+D(ln2/td) [32], where D is the mean time of infectiousness (i.e., 7 days for virus shedding in humans) [33] and td is the doubling time of the epidemics and, since the growth rate (r) obtained from the viral phylodynamics equals ln2/td [30], we estimated R0 as 1+Dr. However, the monotonic-increasing population models (exponential en logistic) available in BEAST do not account properly for fluctuating dynamics, such as that observed during the studied outbreak, possibly affecting the growth rate estimates using these models. This was further substantiated by the fluctuating nature of the Bayesian skyline (BSL) plot for dengue that showed rapid increase at the onset of the epidemic phase, followed in time by a reduction of cases at the end of the outbreak. Therefore, we also used for comparison an alternative way of estimating R0, based on the growth phase of the epidemics alone, by deriving the force of infection at the increasing phase of the BSL as follows. The normalized median of the Bayesian estimates from the sequences analyzed, y(t), was fitted to a continuous logistic curve according to the following model:(1)
From equation (1) it is possible to estimate the force of infection for the data [34],[35]:(2)where,(3)
The Basic Reproduction Number, R0, was estimated from the average force of infection, calculated from equation (2) by its equality to the number of new cases per time unit per susceptibles, according to a previous study [33]:(4)where, μ is the mosquito mortality rate and γ is the recovery rate of viraemia in humans. The mosquitoes mortality rate is the rate by which moquitoes die, on average, in each unit of time and is the inverse of the average life expectancy of each specific mosquito population. It varies from place to place and in the same place it also varies with environmental conditions, like temperature, rain pattern and othe climatic variables. We used the mosquito mortality rate of to 2.23×10-2/day previously estimated for SJRP [33].
Dengue characterization and sequencing
We obtained 399 bp-long sequences of a portion of the NS5 gene from viral genomic RNA amplified directly from the blood of 82 patients from 198 samples collected in the city of São José do Rio Preto for a period of 174 days, from January 12 to June 5th of 2006, which covered the zenith of the outbreak (i.e., above 1000 cases per 100,000 inhabitants) in April 2006 (GenBank accession numbers from EU715692 to EU715773). We were able to geo-locate 46 patients based on the addresses of their residences, from the cohort of 82 patients. The reason for not geo-coding the other 36 patients was the lack of their complete home address.
Dengue typing and origin
By aligning the 82 sequences with the 52 references we generated a 399-nucleotide-long dataset (without gaps) with 134 taxa. Preliminary phylogenetic analyzes, including the 4 serotypes indicated that all samples were of serotype 3 (data not shown). Furthermore, all of our samples nested within DENV-3 and were closely related to strains circulating in the isle of Martinique in the Caribbean in 2000 and 2001 and, to the DENV-3 strain Den3_BR74886 circulating in Brazil in 2002 (Figure 1). Moreover, Figure 1 indicated that, given the reference samples included in our analyses, the South American lineages were more related to lineages circulating in South East Asia. Another important finding was that 60 DENV-3 from SJRP formed a monophyletic group (lineage 1, shown in blue) with 90% posterior probability, which were closely related to the remaining 22 isolates that did not form a clear monophyletic cluster (lineage 2 and 3, shown in orange) that had a more basal position in the tree and that intermingled with the other South American references available from Martinique and Brazil.
MCC tree for 131 Dengue 3 isolates from several places in World, indicating that the origin of the 60 lineage 1 samples (with 90% posterior probability support) from viruses from the lineage 2 (with 77% posterior probability support). The close-related BR47886 sampled in 2002 in Brazil and the H IMTSSA sampled in 2000 in Martinique had a basal position in relation to the SJRP lineages (with 100% posterior probability support).
DENV-3 dynamics in SJRP
Our demographic analysis using a Bayesian skyline prior with BEAST generated a maximum clade credibility (MCC) tree with dated tips and internal nodes that indicated that both lineages split 1 to 3 years before the last sample was collected in SJRP (Figure 1). Moreover, since there was no sustained DENV- 3 epidemic transmission during this entire period in SJRP, we assumed that these lineages appeared before the 2006 season and that distinct lineages were possibly introduced into the city on different occasions. As a consequence, the major lineages were treated as distinct viral populations during subsequent demographic analyses. Since, most lineages shown in orange in Figure 1 had a common ancestor with 77% posterior probability , they were grouped into a single group (lineage 2) for the sake of demographic analyses. For both groups of samples there was significant population growth initiating 6 months before the last sampling, which matches quite well with reports increasing above 10 cases per 100,000 in December 2005 (Figure 2). Moreover, for both DENV-3 lineages, the constant population size model was rejected (for lineage 1, Log 10 Bayes factor>250; lineage 2, Log 10 Bayes factor>146). Although the signature of BSL in Figure 2 is clearly logistic until around the zenith of the outbreak, the logistic model did not out-perform the exponential growth model for both lineage 1 (Log 10 Bayes factor = 23.9) and lineage 2 (Log 10 Bayes factor = −4.436), in the latter case even if the logistic model had a higher Bayes factor (146.251) when compared to the exponential (150.686), there was no significant improvement by including additional logistic parameters to describe the data. Critically, as indicated by the HPD, the growth rate (r) for both lineages were significantly above zero for both, lineage 1, r = 0.0752 (with 95% HPD from 6.96E-5 to 0.258) with an ESS of 107.75 for 150,400,000 states, and lineage 2, r = 0.0182 (with 95% HPD from 1.627E-4 to 0.0391) with an ESS of 1239.444 for 325,600,000 states. By transforming the inferred exponential growth rates into the basic reproductive rate, we obtained values for lineage 1 of R0 = 1.53 (with 95% HPD ranging from above 1 to 2.8) and values for lineage 2 of R0 = 1.13 (with 95% HPD ranging from above 1 to 1.3). Although we rejected the logistic model, the basic reproductive rate obtained from the logistic growth rate values (data not shown) for lineage 1 was R0 = 3.765 (with 95% HPD ranging from above 1 to 9.554) and for lineage 2 was R0 = 3.093 (with 95% HPD ranging from above 1 to 8.896). These data meant that the rate of growth was almost 50% higher for lineage 1 at exponential growth but only 17% higher under the logistic model. Under the exponential model the most recent common ancestor MRCA of lineage 1 dated 2 years before the last sampling (with 95% HPD ranging from 6 months to 3 years) and lineage 2 also dated 2 years before the last sampling (with 95% HPD ranging from 6 months to 5 years). In sum both lineages appear to have similar growth patterns with a trend of increased rate of growth (and higher R0) for lineage 1 strains. One serious limitation of the former approach was that the monotonic-increasing models used in BEAST (logistic and exponential) may have not captured the true fluctuating dynamics of the epidemics, since both fail to detect the decrease in numbers of new infections after the Zenith of the outbreak. Therefore we also used other methods [33],[34],[35],[36]. The logistic fitting of the Bayesian skyline plot inferred by MCMC from viral genealogies for y(t) is shown in Figure 3A. The Basic Reproduction Number, R0, was estimated from the average force of infection (Figure 3B), calculated from equation (2) and equal to 0.17 new cases per time unit per susceptibles, according to the method previously proposed in a study [33]. From equation (4) the basic reproduction number (R0) obtained was 2.45. The data suggested that there was a good match among values obtained directly from the growth rate estimated with BEAST, the one found using the force of infection and, the epidemiological estimates of 3.36 previously estimated [37] from the cases' doubling time.
A) Bayesian skyline (BSL) plot of the virus genealogy-based estimate of the number of new infections (presented as Ne.g) indicated as the median for 82 DENV-3 isolates showing the increase from 180 to 120 days before the last sampling (from present day 0 or day of the last sample taken to the past), which matches with uncanny precision the rise in number of reported cases per 100,000 inhabitants from December of 2005. Apparent differences in overall population sizes are due to both the fact that the BSL shows accumulated number of new infections and to scaling problems or misreport. B) Number of Dengue reported cases in SJRP during the seasons of 2001–2002 (01_02), 2003 (02_03), 2004 (03_04), 2005 (04_05) and 2006 (05_06). It is noticeable that the maximum number of reported cases in 2006 happened in April, when the zenith of the epidemics, determined by the Bayesian skyline plot, was around February.
A) the normalized median of the Bayesian estimates from the sequences analyzed, y(t), fitted to a continuous logistic curve according to equation (1). Diamonds represent the data and the continuous line the fitted function. The period of time entails the epidemics during the fat growing phase during January and February of 2006. B) Force of infection calculated from the fitted model in A) using equation (2).
Spatio-temporal distribution of DENV-3 lineages in SJRP
By visually inspecting the temporally sorted distance matrices shown in Figure 4, we noticed some genetically similar 'blocks' (bright patches in the second matrix) following the temporal gradient (first matrix), but intercalated with "dark" lines representing lower genetic proximity. This intercalation of genetically distant samples seems to be responsible for preventing an overall statistical association and was due to the distinct lineages co-circulating in SJRP during the outbreak. There was also no spatial association between samples (third matrix) in any noticeable way when compared with the other matrices. These visual observations were confirmed by the statistical analyses, Spearman correlation between the other ones was very low (r = 0.06 with geographic, and r = 0.01 with temporal) and non-significant (<0.05 as obtained by Mantel method with 1,000 interactions, [31]).
Symmetrical matrices representing: A) temporal, B) genetic and C) spatial distances among the 46 samples. For easy visual comparison, numbers were substituted by a scale of colours that ranges from white (lower value) to black (higher value). The samples were organized temporally as indicated by the gradual pattern observed in matrix A), and the colours of the names of the samples are meant to facilitate the comparison with the results.
The analyses with the "nepotistic algorithm" suggested the existence of at least three possibly independent introductions of strains from lineages 1 and 2 into SJRP. The three lineages correspond well to the tree shown in Figure 1. The proposed spatial-temporal associations were represented in three dimensions in Figure 5, which explained the lack of overall statistical association between the correlation matrices. The three main virus introductions appeared as genetically-similar blocks intercalated with more distant rows in the genetic distance matrix of Figure 4. In fact, we can see that the "predominantly darker lines" coincide with the lineages names shown in red in Figures 4 and 5. A closer inspection also revealed that, similarly to what was observed for to the "blue" samples of lineage 1, the genetic distances between the "red samples" were low among themselves. The branching pattern of the spatio-temporal tree (Figure 5) generated with the "nepotistic algorithm" also explained why there was no correlation between geographic distance matrix and the other distances. This was because the spatial dispersion of the virus starts in three different points and does not appear to follow a single centrifugal pattern.
The basis of the three dimensional graphic represents the geographic coordinates of the positions where the sample were collected, while the vertical axis represents the months of the sampling. Each independent lineage starts with a "star" (oldest sample of the lineage) and the connections to the other samples (names are displayed as close to point as possible) are done with lines, whose width is proportional to the genetic relatedness between the samples. The three lineages represented are: (i) green the more recent, with only one sample, the 122-145, (ii) red or "South-eastern" lineage (starting with 22-18, that turns to yellow with more recent "ancestry" samples) and (iii) blue, or North-western" lineage 1 (starting at 01-00, and that gets lighter as for the previous one).
The "North-western" component (lineage 1) shown in blue in the spatio-temporal trees in Figures 5 and 6, included the earliest samples from January 12th. It was also the most prevalent (36 samples), and was the more long-lasting, encompassing also the 5 more recent samples: '138-173', 146-153', '116-160', '133-173', '135-173', and '138-173', collected between June 14th and July 4th. The connections between lineage 1 samples averaged 3.25 kilometres (ranging from 15 meters to 7.23 kilometres). The average of speed of the propagation was around 67.3 meters per day, ranging from 18 centimeters/day (since two samples ('95-119' and '42-34') were collected only 15 meters apart) to a maximum speed of 428.8 meters/day. Moreover, some lineage 1 samples seem to be the possible source nodes of many other samples (the names of these samples and the number of generated links are: '01-00': 16; '42-34': 12; '64-67': 2; '90-116':2; '98-119':2). The "South-eastern" samples bundled into at least lineage 2 shown in red in the spatio-temporal tree (Figures 5 and 7), had lesser components (8 samples). Its recorded activity ranged from January 30th ('22-18') to June 14th ('132-153'). The average length of its connections was 4.7 kilometres (min: 0.2, max: 8.7 kilometres), at an average speed of 152 meters per day (min: 28 meters/day; max: 311 meters/day). The '122-145' (Figures 5, 6, and 7) would constitute another entry of dengue into SJRP.
Estimated route of dispersion of the "North-western", departing from the putative ancestor (blue dot and dispersing to other places where dengue cases were recorded - lines with more recent nodes tends to the lighter tones) projected on the aerial image of the city of São José do Rio Preto (SJRP). The sample of the third viral introduction is also shown in a green dot. (Background image obtained from Google Earth 4.2.0181.2634 – download date: September 16th 2007).
Estimated route of dispersion of the "South-eastern", departing from the putative ancestor (orange dot) and dispersing to other places where dengue cases were recorded - lines with more recent nodes tends to the yellow tones) projected on the aerial image of the city of São José do Rio Preto. The sample of the third viral introduction is also shown in a green dot. (Background image obtained from Google Earth 4.2.0181.2634 – download date: September 16th 2007).
Socioeconomic features
Figure 8 represents the autochthonous dengue cases confirmed by the Surveillance Service from September 2005 to February 2006. In September 2005, there were dengue cases within an irregular residential area (Santa Clara) in the northern area and outside the urban perimeter, which lacks proper basic sanitation. During the following months, there were several additional cases in the neighborhood and the disease spread into other areas of the urban perimeter. The molecular characterization of the circulating strains identified at least three different viral introductions 01-00, 22-18 and122-145. The first event was at Eldorado, a neighborhood with low socioeconomic levels. Other cases occurred in areas with different socioeconomic levels (Figures 5, 6, and 9). There was a cluster at Gonzaga de Campos (cases 42, 85, 95 and 141), a working-class neighborhood with low socioeconomic levels, flanking the main industrial zone of the municipality. A series of cases linked to case 42 spread among areas with different socioeconomic levels (Figures 5, 6, and 9). Case 22-18, which led to other cases in lineage 2, with the exception of case 122-145, that also occurred in São Deocleciano, an area with low socioeconomic level. There was a relation among the socioeconomic level of the census tracts and the incidence coefficients based on the cases reported by the Surveillance System (Table 1), despite an even distribution of the RT-PCR positive cases among different census tracts (Table 1 and Figure 9). Approximately 44% of the census tracts of the lowest socioeconomic level were in the highest quartile of incidences, but only 5.5% of the census tracts of the highest socioeconomic level were in the same situation.
São José do Rio Preto map with urban census tracts, irregular development areas and autochthonous dengue cases reported and confirmed by the Surveillance System from September to November (A), December (B), January (C) and February (D). The areas outside the urban perimeter are irregular development areas with urban characteristics, but with inadequate sanitation infrastructure and lowest socioeconomic conditions in comparison to urban census tracts. There is a cluster of cases in one of these irregular areas in the North Zone of the city (Santa Clara) in September 2005 and a spread of the transmission to the rest of the urban perimeter (A).
Urban census tracts (i.e., continuous and homogeneous areas comprising 300 buildings on average, IBGE 2002) according to socioeconomic levels (quartile) and dengue cases with molecular analysis according to strains from January 2006 to June 2006 (A); urban census tracts according to incidence coefficients of dengue cases (quartile) reported to the Surveillance System from September 2005 to August 2006 (B).
Inferences based on sequence data of spatio-temporal dynamics, including the speed and direction of virus propagation, have been little explored until recently [38]. Nevertheless, they can help to better understand dengue outbreaks, providing useful information for public-health systems. In this study we showcased the use of both geographic and temporally structured phylogenetic data providing a relatively detailed view on the spread of at least two dengue viral lineages in the urban area of SJRP. These two groups suggested a pattern of dispersion that was consistent with the dispersal rate of Aedes aegypti, but in some instances, seemed to entail human accidental transport. It also showed that most of the cases until July traced directly to two viral sequences, sampled in January and February, respectively.
The connections among our samples averaged 3.75 kilometers, and the speed of propagation ranged from 0 to 428.8 meters per day. Aedes aegypti lays its eggs at many different sites (i.e., skip ovoposition) [39], maximizing spread potential and the chance of survival. Nevertheless, our data stressed the notion that both, mosquito and human circulation, do play an important role in the dispersal of the virus and were in good agreement with previous estimates of dispersion distances ranging from 15 to 800 meters [40],[41],[42]. The co-circulation of distinct dengue lineages in SJRP could be explained by independent introductions experiencing different dynamic outcomes or accretion of genetic diversity generated locally. Lineages can vanish from a given locality due to unfavourable conditions such as temperature, low mosquito population and changes in immunity status of the population during the outbreak. However, Aedes aegypti eggs are resistant to desiccation and this characteristic (i.e., overwintering) may have important implications for the cryptic maintenance of viral strain. Therefore, viral lineages not detected in one season can re-emerge in the next rainy season due to transovarial transmission that is believed to be the most important factor for the maintenance of the virus in the nature [43]. Therefore it is not possible at this time to determine precisely the order of introduction events and the proper time of introduction of the distinct lineages that we have detected. The region of SJRP experiences an increase in rainfall starting in December reaching a peak in January/February. Concurrently, the number of dengue cases began to increase following the infestation by Aedes aegypti. In SJRP, the two main lineages were present at the zenith of dengue transmission, which coincided with the highest values for temperature and humidity. Another lineage (represented in green in Figures 4, 5, and 6) appeared later in May, when temperature, rainfall and humidity were decreasing. However, it is not known if this lineage became established (we could not identify putative links of this sample with other samples), given that the data collection finished in July 2006. Possibly viruses included in lineage 2 did not succeed in getting established in the city or faded away, given its appearance later in scene (June 6th) when the dryer and colder weather did not favour the development of the larvae and/or the survival and activity of the mosquito [44],[45]. Alternatively, its establishment may have been hampered by the decreasing availability of susceptible hosts in the later stages of the outbreak. The matrices of distances displayed in Figure 4 show how each sample is relatively close to all other samples, considering separately their date of collection, their place of collection and their genetics. As interesting they are in their own, each one cannot suggest a hypothetical scenario for the dynamics of the dispersion of dengue in São José do Rio Preto. Only when we combine all this information (time, space and genetics) based on parsimonious assumptions (each sample should be connected - by descended or siblinghood - to the closest genetic sample of the past) we can suggest a plausible dispersion scenario and, from this, infer other very useful information - like the speed or direction of the events.
DENV-3 was first isolated in São José do Rio Preto in January 2006. According to our results, both lineages split around one to three years before the collection of the last sample. In the four-year period at Figure 2, we noticed that during the three years after the introduction of DENV-2, in 1998, the incidence started to decrease every year, possibly due to the lack of susceptible hosts, but DENV-2 was still circulating in June 2005. The introduction of DENV-3 into the naive population to this serotype in SJRP may have occurred during 2005, because in September of this year, a neighborhood in the northern part of the city presented a significant increase in dengue incidences. The outbreak continued during October and November and culminated in April of 2006. The notion of a probable start of DENV-3 transmission at the Santa Clara neighborhood in September 2005 and its subsequent spread to the rest of the municipality (Figure 8) is in accordance with the results presented in Figures 2A and 3A. The outset of DENV-3 transmission at this underdeveloped urban area was to be expected, because Aedes aegypti larval infestation studies done in January 2005 [46] indicated that areas in SJRP with lower socioeconomic levels, with deficient sanitation infrastructure, presented higher infestation levels when compared to affluent neighborhoods inside the urban perimeter. The spread of dengue transmission through the entire municipality is in accordance with the high R0 values we found, possibly because the population was susceptible to serotype 3. An interesting result was that the BSL (Figure 2A), based on viral sequences recovered with great precision the dynamics of the epidemics obtained from case reports (Figure 2B). Nevertheless, the zenith determined by the BSL took place around February, two months before the maxima determined by case report in April (Figure 2). Interestingly, these results could be explained by the fact that up until March of 2006 clinical differential diagnostics was used in conjunction with serology, which increases the accuracy of the dengue diagnostics. On the other hand, after the number of cases exceeded 300 per 100,000 inhabitants in April 2006, only clinical criteria were used, which may have caused an increase in false positives, due to the lack of further serological confirmation. These results further validate the use of viral gene genealogies to infer epidemiological parameters of DENV in particular and, of fast-evolving viruses in general.
The use of home addresses for geo-positioning our patients for spatial analysis was justified because individuals spend considerable time at home, which constitutes a highly probable site of transmission. Nevertheless, transmission might also occur at other places and this fact certainly may have had some impact on our data, which would be hard to account for. Nevertheless, our exercise was valid, since it indicated coherent patterns of transmission, which may be relevant for implementing control measures. Our molecular data indicated that the viral spread was not dependent entirely on vector dispersal. The exponential growth phase associated with linked transmission events beyond the usual flight range of the mosquito may have been caused by under-sampling and movement of viremic humans, but is certainly indicative of fast transmission among susceptible individuals. Therefore, surveillance systems need to be capable of monitor proactively the occurrence of initial low levels of transmission, identify early cryptic circulation of new serotypes and, be able to map where infected patients are circulating, preferably at the lag phase of the outbreak.
Although we have not found clear relationships between dengue cases with molecular analysis and socioeconomic levels (Table 1 and Figure 9A), the first samples associated with the beginning of the outbreak, which were possible source nodes for many other samples, were found in regions with low socioeconomic level. Moreover, a higher transmission in poor areas of SJRP has been shown, especially in the north zones of the city [47]. Therefore, it is relevant to further evaluate if the occurrence of transmission in poor areas facilitates a higher dispersion of the virus to other areas of the city. However, the association between higher dengue transmission and low socioeconomic levels is controversial. Some studies have demonstrated the association of poverty and high incidences of dengue [48],[49], others have not [50],[51],[52] and others have indicated an inverse relation [53]. A study [48] demonstrated that dengue occurred at higher levels in poorer areas of SJRP in 1995 but, from 1998 to 2002, after the introduction of DENV-2, the variable that best explained dengue cases was the proportion of one-story homes. The socioeconomic features lost its explanatory power as the years passed and the spatial characteristic of the areas was more relevant [54]. A higher transmission of dengue in poor areas of the north zone was observed again in 2005–2006 [47].
Two hypotheses might explain the controversial pattern of dengue transmission. In both 1995 and 2006 epidemic season, dengue transmission started in poor northern zones of the city in the previous years (1994 and 2005) with a subsequent spread to other areas [12],[47],[48]. Therefore, the highest initial incidence of dengue in the north and the lowest in the other areas might be related to the usual delay in adopting of control measures at the beginning of the outbreak. Another hypothesis is that dengue transmission occurred initially in poor areas and spread to the rest of the city due to the reduction of susceptible individuals in the areas that were primarily affected and, as the years passed, the distribution of the disease became similar in the whole city. This pattern was confirmed previously [55], for the period of 1994 to 1998, when only DENV-1 was circulating in the city, but not for the period of 1998 to 2002, when DENV-1 and DENV-2 were circulating simultaneously.
The introduction of new DENV serotypes and genotypes constitutes a major risk factor for severe dengue manifestations [56]. But it is still controversial whether DENV strains that cause severe disease out-compete less virulent strains, which is a cause of major concern [22]. Therefore it is paramount to address in greater detail whether differences in viral dispersion patterns are associated with viral fitness, strain competition and, ultimately, whether it has any association with increase in disease severity. We have shown that spatial analysis using Geographic Information System could provide valuable information on dengue transmission and the spread of the disease in a defined but heterogeneous urban setting, typical of the developing world. We believe that the current study helped determining with greater precision areas where the infection took place, to understand particularities of an outbreak, clarifying the mechanisms of dengue transmission in SJRP. Ultimately, the association of molecular epidemiology with spatial analysis and the understanding of some biological and reproductive characteristics of Aedes aegypti mosquitoes may shed light on the dynamics and distribution of different dengue viral strains.
Author Contributions
Conceived and designed the experiments: AM RVdMB FCN ESML MLN. Performed the experiments: AM SHPN. Analyzed the data: AM RVdMB FCN EM WJA PMdAZ MLN. Contributed reagents/materials/analysis tools: EM WJA PMdAZ. Wrote the paper: AM RVdMB FCN EM WJA PMdAZ MLN. Acquisition of data: ESML AAF.
- 1.
Monath TP, Heinz FX (1996) Flaviviruses. In: Fields BN, Knipe DM, Howley PM, editors. Virology. Philadelphia: Lippicott-Raven Publishers. pp. 961–1034.
- 2.
Zanotto PMA, Gould EA (2002) Molecular epidemiology, evolution and dispersal of the genus Flavivirus. In: Leitner T, editor. The Molecular Epidemiology of Human Viruses. Kluwer Academic Press. pp. 167–195.
- 3.
Innis B (1995) Dengue and dengue hemorrhagic fever. In: Porterfield JS, editor. Kass Handbook of Infectious Diseases: Exotic Virus Infections. 1st edition. London: Chapman and Hall Medical. pp. 103–146.
- 4. Chambers TJ, Hahn CS, Galler R, Rice CM (1990) Flavivirus genome organization, expression, and replication. Annu Rev Microbiol 44: 649–688.
- 5. Holmes EC, Twiddy SS (2003) The origin, emergence and evolutionary genetics of dengue virus. Infect Genet Evol 3: 19–28.
- 6. Twiddy SS, Holmes EC, Rambaut A (2003) Inferring the rate and time-scale of dengue virus evolution. Mol Biol Evol 20: 122–129.
- 7. Zanotto PM, Gould EA, Gao GF, Harvey PH, Holmes EC (1996) Population dynamics of flaviviruses revealed by molecular phylogenies. Proc Natl Acad Sci U S A 93: 548–553.
- 8.
WHO (1997) Dengue Haemorrhagic Fever. Diagnosis, treatment, prevention and control: WHO - World Health Organization.
- 9.
WHO (1999) Strengthening implementation of the global strategy for dengue fever/dengue haemorrhagic fever prevention and control. WHO - World Health Organization.
- 10.
PAHO (2008) 2007: Number of Reported Cases of Dengue & Dengue Hemorrhagic Fever (DHF), Region of the Americas (by Country and Subregion) Pan American Health Organization.
- 11.
CVE (2008) [Confirmed autochthonous dengue cases per municipality and per epidemiological week in 2007 in the State of São Paulo]. Centro de Vigilância Epidemiológica.
- 12. Mondini A, Chiaravalloti Neto F, Gallo y Sanches M, Lopes JC (2005) [Spatial analysis of dengue transmission in a medium-sized city in Brazil]. Rev Saude Publica 39: 444–451.
- 13. Jarman RG, Holmes EC, Rodpradit P, Klungthong C, Gibbons RV, et al. (2008) Microevolution of Dengue viruses circulating among primary school children in Kamphaeng Phet, Thailand. J Virol 82: 5494–5500.
- 14. Diaz FJ, Black WCt, Farfan-Ale JA, Lorono-Pino MA, Olson KE, et al. (2006) Dengue virus circulation and evolution in Mexico: a phylogenetic perspective. Arch Med Res 37: 760–773.
- 15. Bennett SN, Holmes EC, Chirivella M, Rodriguez DM, Beltran M, et al. (2006) Molecular evolution of dengue 2 virus in Puerto Rico: positive selection in the viral envelope accompanies clade reintroduction. J Gen Virol 87: 885–893.
- 16. Messer WB, Gubler DJ, Harris E, Sivananthan K, de Silva AM (2003) Emergence and global spread of a dengue serotype 3, subtype III virus. Emerg Infect Dis 9: 800–809.
- 17. Bennett SN, Holmes EC, Chirivella M, Rodriguez DM, Beltran M, et al. (2003) Selection-driven evolution of emergent dengue virus. Mol Biol Evol 20: 1650–1658.
- 18. Zaki A, Perera D, Jahan SS, Cardosa MJ (2008) Phylogeny of dengue viruses circulating in Jeddah, Saudi Arabia: 1994 to 2006. Trop Med Int Health 13: 584–592.
- 19. King CC, Chao DY, Chien LJ, Chang GJ, Lin TH, et al. (2008) Comparative analysis of full genomic sequences among different genotypes of dengue virus type 3. Virol J 5: 63.
- 20. Vasilakis N, Holmes EC, Fokam EB, Faye O, Diallo M, et al. (2007) Evolutionary processes among sylvatic dengue type 2 viruses. J Virol 81: 9591–9595.
- 21. Zhang C, Mammen MP Jr, Chinnawirotpisan P, Klungthong C, Rodpradit P, et al. (2006) Structure and age of genetic diversity of dengue virus type 2 in Thailand. J Gen Virol 87: 873–883.
- 22. Salda LT, Parquet MD, Matias RR, Natividad FF, Kobayashi N, et al. (2005) Molecular epidemiology of dengue 2 viruses in the Philippines: genotype shift and local evolution. Am J Trop Med Hyg 73: 796–802.
- 23. Pires Neto RJ, Lima DM, de Paula SO, Lima CM, Rocco IM, et al. (2005) Molecular epidemiology of type 1 and 2 dengue viruses in Brazil from 1988 to 2001. Braz J Med Biol Res 38: 843–852.
- 24. Klungthong C, Zhang C, Mammen MP Jr, Ubol S, Holmes EC (2004) The molecular epidemiology of dengue virus serotype 4 in Bangkok, Thailand. Virology 329: 168–179.
- 25. Uzcategui NY, Comach G, Camacho D, Salcedo M, Cabello de Quintana M, et al. (2003) Molecular epidemiology of dengue virus type 3 in Venezuela. J Gen Virol 84: 1569–1575.
- 26. de Morais Bronzoni RV, Baleotti FG, Ribeiro Nogueira RM, Nunes M, Moraes Figueiredo LT (2005) Duplex reverse transcription-PCR followed by nested PCR assays for detection and identification of Brazilian alphaviruses and flaviviruses. J Clin Microbiol 43: 696–702.
- 27. Fulop L, Barrett AD, Phillpotts R, Martin K, Leslie D, et al. (1993) Rapid identification of flaviviruses based on conserved NS5 gene sequences. J Virol Methods 44: 179–188.
- 28.
Zwickl D (2006) Genetic algorithm approaches for the phylogenetic analysis of large biological sequence datasets under the maximum likelihood criterion. Austin: The University of Texas.
- 29.
Swofford DL (2002) PAUP*. Phylogenetic Analysis Using Parsimony (*and Other Methods). Version 4.0 ed. Sunderland, Massachussets: Sinauer Associates.
- 30.
Drummond AJ, Rambaut A (2006) BEAST 1.4.
- 31. Mantel N (1967) The detection of disease clustering and a generalized regression approach. Cancer Res 27: 209–220.
- 32.
Anderson RMMR (1991) Infectious Diseases of Humans: Dynamics and Control. New York:
- 33. Massad E, Coutinho FA, Burattini MN, Lopez LF (2001) The risk of yellow fever in a dengue-infested area. Trans R Soc Trop Med Hyg 95: 370–374.
- 34. Coutinho FA, Massad E, Burattini MN, Yang HM, de Azevedo Neto RS (1993) Effects of vaccination programmes on transmission rates of infections and related threshold conditions for control. IMA J Math Appl Med Biol 10: 187–206.
- 35. De Azevedo Neto RS, Silveira AS, Nokes DJ, Yang HM, Passos SD, et al. (1994) Rubella seroepidemiology in a non-immunized population of Sao Paulo State, Brazil. Epidemiol Infect 113: 161–173.
- 36. Massad E, Burattini MN, Coutinho FA, Lopez LF (2003) Dengue and the risk of urban yellow fever reintroduction in Sao Paulo State, Brazil. Rev Saude Publica 37: 477–484.
- 37. Coelho FC, Codeco CT, Struchiner CJ (2008) Complete treatment of uncertainties in a model for dengue R0 estimation. Cad Saude Publica 24: 853–861.
- 38. Koh BK, Ng LC, Kita Y, Tang CS, Ang LW, et al. (2008) The 2005 dengue epidemic in Singapore: epidemiology, prevention and control. Ann Acad Med Singapore 37: 538–545.
- 39. Reiter P (2007) Oviposition, dispersal, and survival in Aedes aegypti: implications for the efficacy of control strategies. Vector Borne Zoonotic Dis 7: 261–273.
- 40. Harrington LC, Scott TW, Lerdthusnee K, Coleman RC, Costero A, et al. (2005) Dispersal of the dengue vector Aedes aegypti within and between rural communities. Am J Trop Med Hyg 72: 209–220.
- 41. Honorio NA, Silva Wda C, Leite PJ, Goncalves JM, Lounibos LP, et al. (2003) Dispersal of Aedes aegypti and Aedes albopictus (Diptera: Culicidae) in an urban endemic dengue area in the State of Rio de Janeiro, Brazil. Mem Inst Oswaldo Cruz 98: 191–198.
- 42. Russell RC, Webb CE, Williams CR, Ritchie SA (2005) Mark-release-recapture study to measure dispersal of the mosquito Aedes aegypti in Cairns, Queensland, Australia. Med Vet Entomol 19: 451–457.
- 43. Joshi V, Mourya DT, Sharma RC (2002) Persistence of dengue-3 virus through transovarial transmission passage in successive generations of Aedes aegypti mosquitoes. Am J Trop Med Hyg 67: 158–161.
- 44.
Christophers R (1960) Aedes aegypti (L.), the Yellow Fever Mosquito—Its Life History, Bionomics and Structure. Cambridge: Cambridge University Press.
- 45. Schultz GW (1993) Seasonal abundance of dengue vectors in Manila, Republic of the Philippines. Southeast Asian J Trop Med Public Health 24: 369–375.
- 46. Ferreira AC, Chiaravalloti Neto F (2007) [Infestation of an urban area by Aedes aegypti and relation with socioeconomic levels]. Rev Saude Publica 41: 915–922.
- 47. Galli B, Chiaravalloti Neto F (2008) [Temporal-spatial risk model to identify areas at high-risk for occurrence of dengue fever]. Rev Saude Publica 42: 656–663.
- 48. da Costa AI, Natal D (1998) [Geographical distribution of dengue and socioeconomic factors in an urban locality in southeastern Brazil]. Rev Saude Publica 32: 232–236.
- 49. Reiter P, Lathrop S, Bunning M, Biggerstaff B, Singer D, et al. (2003) Texas lifestyle limits transmission of dengue virus. Emerg Infect Dis 9: 86–89.
- 50. Bartley LM, Carabin H, Vinh Chau N, Ho V, Luxemburger C, et al. (2002) Assessment of the factors associated with flavivirus seroprevalence in a population in Southern Vietnam. Epidemiol Infect 128: 213–220.
- 51. Espinoza-Gomez F, Hernandez-Suarez CM, Rendon-Ramirez R, Carrillo-Alvarez ML, Flores-Gonzalez JC (2003) [Interepidemic transmission of dengue in the city of Colima, Mexico]. Salud Publica Mex 45: 365–370.
- 52. Teixeira Mda G, Barreto ML, Costa Mda C, Ferreira LD, Vasconcelos PF, et al. (2002) Dynamics of dengue virus circulation: a silent epidemic in a complex urban area. Trop Med Int Health 7: 757–762.
- 53. Vasconcelos PF, Lima JW, da Rosa AP, Timbo MJ, da Rosa ES, et al. (1998) [Dengue epidemic in Fortaleza, Ceara: randomized seroepidemiologic survey]. Rev Saude Publica 32: 447–454.
- 54. Mondini A, Chiaravalloti-Neto F (2008) Spatial correlation of incidence of dengue with socioeconomic, demographic and environmental variables in a Brazilian city. Sci Total Environ 393: 241–248.
- 55. Mondini A, Chiaravalloti Neto F (2007) [Socioeconomic variables and dengue transmission]. Rev Saude Publica 41: 923–930.
- 56. Gubler DJ (1998) Dengue and dengue hemorrhagic fever. Clin Microbiol Rev 11: 480–496.


text:
A few weeks ago I was in a seminar with a group of non-native speakers of English. The tutor a Native English speaker asked a question and got an answer. The tutor then said 'Yeeeeees.' The intonation told me that the answer was, in fact, wrong. Despite it being a wrong answer, I watched as some of the other participants wrote down the answer believing it to be correct; after all the tutor had nodded and said yes.
A few weeks earlier, in my own training session a colleague said they were surprised about my correction technique. I'd said 'Good idea but…. no!' with a smile but a firm no. Nobody was in any doubt - the answer was wrong, but my colleague felt I had been too harsh.
I wonder which our students/conference participants would prefer.

subset: commoncrawl


text:
The best diet plan for overall health may not cost a thing.
A new ranking of diets by U.S. News & World Report gives top honors for best overall diet to the DASH (Dietary Approaches to Stop Hypertension) diet.Originally developed by the National Heart, Lung, and Blood Institute to lower blood pressure, the diet plan is available free online.
Experts also ranked top diets in seven other categories, including weight loss, diabetes, heart-healthy, commercial, easiest to follow, plant-based, and healthy eating.
Weight Watchers won best weight loss diet as well as easiest to follow and best commercial diet.
The DASH diet tied with The Biggest Loser diet as the best diet plan to prevent and manage diabetes. The DASH diet was also named best diet for healthy eating, while the Mediterranean diet won best plant-based diet.
Ranking the Best DietsThe rankings are based on reviews of 29 diets by a panel of experts in diet, nutrition, obesity, food psychology, diabetes, and heart disease.
The panel rated each diet's effectiveness in the following seven categories:
- How easy it is to follow
- Short-term weight loss
- Long-term weight loss
- Nutritional completeness
- Safety
- Diabetes prevention and management
- Heart disease prevention
Researchers then converted the experts' ratings to scores and stars from 5 (highest) to 1 (lowest).
The results showed many diets that topped the rankings are already household names, like Weight Watchers and Jenny Craig. But others, such as the DASH and TLC diets, are lesser-known plans developed by government researchers.
Here are the top overall and best weight loss diets, and what the experts had to say about them. There were three-way ties in the top five in both categories based on the diets' star ratings.
Best Overall Diets1. DASH Diet (4.1 stars) -- The blood-pressure-lowering diet beat out other better-known diets for its nutritional completeness, safety, ability to prevent and control diabetes, and promote heart health.
2. TLC Diet (4.0 stars) -- The National Institutes of Health created the Therapeutic Lifestyle Changes diet to lower cholesterol levels. Experts say it's a well-rounded, healthy diet, but it requires a "do-it-yourself" approach as opposed to the hand-holding provided by some commercial diet plans.
3. Mayo Clinic Diet (3.9 stars) -- This diet plan got high marks for its safety and nutrition. Experts say it is moderately effective for weight loss.
3. Mediterranean Diet (3.9 stars) -- With an emphasis on fruits, vegetables, olive oil, and other healthy foods, the diet got some of the highest scores for nutrition. But experts say some Americans might have a problem sticking to a diet that requires giving up processed foods and sugary drinks.
3. Weight Watchers (3.9 stars) -- Experts said the commercial weight loss diet plan was the easiest to stick to thanks to a strong emphasis on emotional support.


text:
Parish Groups
We are blessed to have an abundance of groups affilitiated to our parish. We have provided links to websites and email contact details where available.
Details are as follows;
Churches Together
Churches Together rep is Andrew Mead:
and Barbara Rowland:
is also a rep. The C of E, St James on Church St and the Methodist Church on Bank Street work together with Baptist Church and Salvation Army and St Joseph's to promote co-operation amongst the Christian Community. Mary Wilkinson of St Joseph's writes the Minutes. (Each Church provides a secretary for a year on a rota basis)
Friendship club contact:
Sue Grafton
01937 583834
Members meet on 3rd Thursday of the month in the church hall. There are usually 30-40 attendees who meet for a talk by an invited speaker, followed by a chat over tea and cakes. A good opportunity to get to know people and to enjoy some company. Transport can be arranged.
Flowers contact:
Claire Slater
or Margaret McNulty about 9 ladies are on the rota, new helpers always welcome. Church pays for the flowers but you can provide your own. The group joins together at Christmas & Easter to decorate the church. They do not arrange wedding flowers.
Church cleaning contact:
Barbara Rowland:
deals with the rota, new helpers always welcome. The more helpers there are the less everyone has to do.
St Joseph's Golf group:
Chris Wotherspoon
01937 588097
or email:
. Two games of Golf, in May and September played at Wetherby Golf Club, Linton. Posters to advertise games are posted in the Narthex. About 20-30 players attend. There is a dinner after each game which non players are very welcome to attend.
a group of parishioners who support children in an African village. Money raised is used to pay for schooling, food etc. Dorothy and Jim Hill and Davida and Peter Hamilton 07768 991124 actually go out to visit the project and report back to the Parish via a newsletter. Contact: Jim Hill
01423 358949
re fundraising and 49er club.
Lay Associates
of the Holy Family contact Alan Dinsdale
01937 583709
. There are currently about 12 lay members who meet on the 3rd Thursday of the month, contact Alan for details. The order was founded by sisters of the Holy Family of Bordeaux who are involved with education, nursing and social work. Lay members help by praying and supporting in whatever way they can.
Martha and Mary
meetings usually every 3rd Monday various venues. (Planning meeting in January)There are about 20 members and about 10- 16 at each meeting with speakers, occasionalretreats and discussions also Stations of the Cross. Contact via Sue Grafton a few of the members also belong the sewing group.
Mature Movers
(run by Catholic care) a gentle exercise class for mature people (men and women) - takes place in the church hall on every Thursday afternoon except when there is a friendship club meeting. Please contact Paualin McElwee via the church office.
Men's Rosary group:
led by Rev Charlie Conner, Deacon, every 1st and 3rd Thursday. Charlie is usually in attendance at 10am Mass and can be contacted after the Mass.
Mother's Prayers
every Monday 9.15-9.45 in church contact Mary Wilkinson
01937 520071
Five or six mothers attend and is part of a worldwide group. They use specific payers from a booklet, there is usually a Scripture reading and maybe a couple of hymns.
Refreshments after Sunday 10am Mass
. Sue Grafton organises the rota. New helpers always welcome and especially anyone who would like to introduce newcomers to the Parish to other Parishioners. Contact Sue
01937 583834
RCIA- Rite of Christian Initiation of Adults
Meetings are held on a Wednesday 8-9pm in the upper room in church. Meetings are from September to Easter but not during school holidays. The meetings are for any Catholics in the Parish (or from other parishes nearby) who wish to strengthen their faith, for those who want to learn about the Catholic Faith and for those who are thinking of converting to the Catholic Faith. The contact is Liz Vickerstaff
01937 520135
contact Helen Salomon
01937 918443 or 07786505577
, email
Meetings of women in the parish on Monday mornings, various venues. They say the Rosary and then discuss a particular topic.
St Vincent de Paul
SVP (Society of Saint Vincent de Paul.)
The local Conference is part of an International charity which seeks to help those in need by providing practical help, and support. They provide a befriending service to the elderly, housebound and others in need. They can provide transport to Mass, arrange placements at children's camp and family holidays. They also work with the local Foodbank and community SVP projects in Leeds such as the St Vincent support centre and St Jude's furniture store. Surplus, good quality household items can be collected by calling
01274 726790
. Donations of clothing and bedding can be bagged and left in the clothes bin on the Ginnel at the back of the church. Meetings held in the upper room at church every Monday at 7.30pm, new members always welcome contact is:
Mini Vinnies is a group of children at St Joseph's school who seek to emulate SVP. They helped at an afternoon tea in the Parish hall. Contact is through school.
Walking Group:
Maura Hunt
01937 360174
walks on 2nd and 4th Wednesday of each month, more information from Maura
Women's world day of prayer:
At the moment there is no representative for this group. If you would be interested in "taking this on" please contact Canon Nunan.
Youth Mass contacts:
Marie Holland
and Sue Streatfield
. Masses about every 6 weeks, during term time, with a rehearsal before Mass.
Youth and Family group:
a new group in the Parish they have put together a programme of events for families and children in the Parish please contact: Gizella Horner
07905 825323
Teams of Our Lady
Teams of Our Lady:
There are 3 or 4 teams within the Parish comprising of couples who meet up each month for a simple meal, prayer and meditation, various venues. (This is a global church activity) Please contact Alison Kusinski for details:
St Joseph's Wetherby Youth & Family Programme
Parish Groups
Youth Links
Inportant and Useful Information
Contact Us
Katangi Update 2013
Local Area
About the area
The sacrament of the church
Anointing of the sick
Holy Order
Mass Times
Mon: No Mass Today
Tue: 9.15am
Wed: 9.15am
Thu: 11am
Fri: 9.15am
Sat: 11am; 6pm Vigil
Sun: 10am
St Joseph's Wetherby - 20 Westgate, Wetherby, West Yorkshire Telephone 01937582283


text:
Philadelphia: Thousands of demonstrators took to Philadelphia's sweltering streets, cheering, chanting and beating drums in the first major protests ahead of the Democratic National Convention, as the city wilted during a heat wave.
Throngs of Bernie Sanders supporters on Sunday marched down a main thoroughfare to show their support of him and disdain for Hillary Clinton ahead of the convention.
Chanting "Hell No, DNC, we won't vote for Hillary" and "This is what democracy looks like," the marchers headed from City Hall down Broad Street, the main north-south artery that leads from the city centre to the convention site about four miles away.
Though planned for months, Sunday's marches came as fractures appeared in the party that had been trying to display a show of unity in recent weeks. Debbie Wasserman Schultz resigned on Sunday as Democratic Party chair over an email suggesting the DNC had played favourites for Clinton during the primary. It was a stunning leadership shakeup as party officials gather in Philadelphia to nominate Clinton.
The Democrats had been trying to avoid the divide that was apparent in Cleveland during the Republican National Convention last week. But the hacked emails, published by Wikileaks, further fired up Sanders supporters, who long accused the party of favouring Clinton despite officially being neutral.
Sanders had called for Wasserman Schultz's resignation, and said on Sunday night she made the right decision for the party's future by resigning.
Darcy Samek, 54, travelled alone from Minneapolis to protest through the four-day convention. She said Wasserman Schultz has been a "miserable failure" who needed to be gone.
"Everyone kind of knew (the Democratic party was against Bernie Sanders), but that doesn't mean it will change now that it's proven. It's just more of the same," she said.
Philadelphia Police Commissioner Richard Ross and other officers walked alongside Sanders protesters. Ross said he liked what he saw on Sunday: a peaceful protest.
The heat wave that descended on the city was showing no mercy, with temperatures reaching the high 90s and the city under an "excessive heat" warning by the National Weather Service. It's expected to peak on Monday, the convention's first day, with temperatures possibly hitting 100 degrees, but feeling 108.
Firstpost is now on WhatsApp. For the latest analysis, commentary and news updates, sign up for our WhatsApp services. Just go to Firstpost.com/Whatsapp and hit the Subscribe button.
Updated Date: Jul 25, 2016 08:19:06 IST


text:
Smart Talk is a daily, live, interactive program featuring conversations with newsmakers and experts in a variety of fields and exploring a wide range of issues and ideas, including the economy, politics, health care, education, culture, and the environment. Smart Talk airs live every week day at 9 a.m. on WITF's 89.5 and 93.3.
Listen to Smart Talk live online from 9-10 a.m. weekdays and at 7 p.m. (Repeat of 9 a.m. program)
Host: Scott LaMar
Radio Smart Talk for Wednesday, January 30:
Preparing a tax return is usually an annual chore that most people don't look forward to. The process has been made somewhat easier in recent years though as more taxpayers abandon the paperwork and file electronically or have tax preparers or accountants do all the dirty work. It all may seem worth it if it's determined a refund is on the way.
Preparing your taxes may not be a simple this year and you have the Congress of the United States to thank. The last-minute deal that avoided the so-called fiscal cliff also resulted in some delays and a few changes as well.
For example, Wednesday is the first day the IRS will accept tax returns electronically.
Other changes this year include exemptions for dependents, standard deductions have increased, and the child tax credit is now permanent.
On Wednesday's Radio Smart Talk, Certified Public Accouncant John Steffee joins us to answer your tax questions.
Do you have a tax question? Put it in the comments section below.
Wednesday's program is part of witf's Moneyworks series.
Listen to the program:
Certified Public Accountant John Steffee answers listeners' questions about filing their taxes.
Tagged under 2012 tax returns, John Steffee, Moneyworksback to top
E-mail from Sam:
"1. What is name of tax form that I should be receiving for IRA distribution?
2. I won several thousand last year from a local company as a prize. Will I be getting a 1099 in the mail? The company reported the winnings on their side."
E-mail from Manuel:
"I filed on 1/24. TurboTax sent the forms in, and I got a message that the IRS had accepted my return, however, the first date the IRS would process was 1/30/13."
E-mail from Jen:
"You said the IRS was not accepting returns from people with kids in college that are claiming the tuition credit. Why not? Are there changes to this credit, and when will they start accepting them?"
When your guest refers to health care costs in the form of premiums be sure to include wether the premium has already been tax deffered. In my example my total $16,000 annual in premium costs are taxen out before tax deductions in pay. I believe that's said and done, I cannot include that in any other tax deduction favor such as the over 7.5% correct?
E-mail from Christopher:
"If you take a standard deduction (using 1040ez form) can you also deduct donations to charitable organizations? Or must you itemize?"
Regarding the discussion of claiming as dependents those for whom you provide the majority of support and who earn less than ~$3,800/year: Is this new?
This fits both of our kids, now 23 and 20. The 23 y/o graduated from college at age 22, but has not yet found a job. The 20 y/o is still in college. We support them. We use TurboTax and stopped claiming them as dependents when TurboTax said they were too old (was that age 19?). Thus for several years we have not claimed the now 23 y/o, and this year we wouldn't have claimed the 20 y/o. Should we go back and file amended returns on the basis that we did/do support them and that they did/do not earn income?
Question from Deb:
Are there still Federal tax breaks for energy saving home improvements?
Call us weekdays between 9 and 10 a.m. at
Email us at
Post a comment to our Facebook page
Follow us on Twitter
Support for WITF is provided by:


text:
When the weather is cold outside we just like to be cozy around at home and have have some warm and spicy food. Chili is something well suited for a quick'n'healthy dinner on a cold evening. The pressure cooker cooks your beans perfectly and the Vitamix makes the perfect puréed soup base which gives it a slow cooked feel without using a slow cooker, or spending the whole day in the kitchen to get the slow cooked feel for your chili. Addition of okra will give an interesting texture, and of course okra is a diabetic friendly and heart healthy vegetable which everyone is trying include in their meals these days. As Indians we are so fortunate to have grown up eating okra in so many different ways, one more is always a welcome addition :-). Go for this warm okra Chili on a chilly night...!!!
- Black beans - 1/3 cup
- Red kidney beans - 1/3 cup
- White vaal beans - 1/3 cup
- Okra - 30 (medium)
- Tomato - 1 cup (chopped)
- Garlic - 2-3 Tbs (minced)
- Onion - 1/4 cup (chopped)
- Paprika - 2 Tbs
- Oregano - 2 Tbs
- Cumin seeds - 1 tsp
- Black pepper corns - 1/2 tsp
- Chile de arbol - 1 (or use equivalent amount of red chilly powder)
- EV Olive oil - 2 Tbs
- Sea salt - as per taste
- Soak beans for 8-12 hours or overnight. Drain soaked beans and cook with about 3 1/2 - 4 cups of water. Pressure cooker works best.
- To make soup base: heat olive on medium heat and add cumin seeds, black pepper, chile (if using) minced garlic and chopped onion. Roast till onion is slightly pink and garlic is roasted well. Add chopped tomato, oregano, paprika, red chilly powder (if using) cook till tomato is soft, for about 3-4 minutes. Switch off and let it cool. Purée this along with a scoop of cooked beans and some cooking liquid from beans. This is your soup base.
- Wash okra and trim edges. Cut into an inch long pieces.
- In a soup pot, add okra and cooked beans along with all remaining liquid from cooking beans. Cook on medium heat till okra is almost done.
- Add the puréed soup base and salt. Simmer on low-medium heat for about 5-10 minutes till all flavors combine well and okra is cooked enough. Adjust seasoning and switch off.
- Serve warm with chopped cilantro and toasted quinoa.
- Enjoy!!
Okra Tips: If you want to reduce the slimy texture of okra, wash and cut okra ahead of time and spread them on a clean kitchen towel.You can also in addition, sauté them in a tablespoon of olive oil before adding to the chili.
For toasted quinoa topping:
- Quinoa - 1/2 cup
- Lemon juice - 1 Tbs
- Sea salt - 1/4 tsp
- In a pan dry roast quinoa till you hear continuous popping (about 4-5 minutes on medium heat).
- Cook with about a cup of water, lemon juice and salt, till well done and you can fluff the quinoa with a fork.
Sharing this on:
Healthy Happy Green Natural Party@UrbanNaturale


text:
FATED LOVE (Stone Pack book3)
by Harper Phoenix
#Unforgettable #CantFightFate #PNRomance
Cover design by
Just Write. Creations/JM Walker
Howard Clarke is the enforcer of the pack,
he's second in command,
and the pack has always come first.
Until her…
Willow is new to the Stone Pack,
their chemistry is off the charts
and their feelings mutual…
Howard has given up fighting the inevitable,
realizing that he's just fighting fate… but can it last?
Fate brought them together, but is HIS Love strong enough for the two of them?
*Add to your TBR*


text:
Particle Physics
Finding the Higgs boson was the last piece in physicists' model of matter. But Tracey Logan discovers there's much more for them to find out at the Large Hadron Collider.
Finding the Higgs boson on July 4th 2012 was the last piece in physicists' Standard model of matter. But Tracey Logan discovers there's much more for them to find out at the Large Hadron Collider. To start with there is a lot of work to establish what kind of Higgs boson it is.
Tracey visits CERN and an experiment called LHCb which is trying to find out why there's a lot more matter than anti-matter in the universe today. Dr Tara Shears of Liverpool University is her guide.
Tracey also talks to physicists who are hoping to find dark matter in the debris of the collisions at the LHC. Scientists know there's plenty of dark matter in the universe, from its effects on galaxies, but they don't know what it is. Tracey discovers that this fact isn't stopping the particle physicists carrying out experiments.
(Image: Scientists in front of a screen at CERN during the restart of the Large Hadron Collider in 2009, Credit: AFP/Getty)
Last on
More episodes
- Mon 10 Dec 2012 19:32GMT
- Tue 11 Dec 2012 00:32GMT
- Tue 11 Dec 2012 04:32GMT
- Tue 11 Dec 2012 11:32GMT
- Sun 16 Dec 2012 01:32GMT


text:
Guaranteeing A Successful Marketing Campaign With Email Marketing Services
The economy nowadays does not really promise a successful marketing campaign; companies need to be aware the funds they have to spend when it comes to printing out, distributing and renting space to put their advertisements up. This is why the internet has become a great economical medium for marketing. Email marketing services can achieve exponentially high success rates in marketing. Usually, advertising online means the use of email, but there are many ways to advertise. There are many ways that services for email marketing are utilized besides just to send mails. One of the many methods in getting better results can be derived out of advertising campaigns is to analyze the reports. Email marketing services are reputed to offer services that give detailed reports about customers and what type of products they prefer and what they are looking for in terms of services. With services for email marketing, studying the reports and deriving conclusions can be used in order to devise the next marketing strategy and what is needed to improve the qualities of products and services.
Email marketing services has another way to get better product rates and that is by personalizing each messages. Similar formats of newsletters can be bland and customers and prospects would not bother opening these advertisements; if each letter is creative enough to catch the recipients' eye. Observing data is also used by services for email marketing, since there might be a coincidence that the type of email address that are being used could be erroneous or no longer active. If the contact data are not correct, then the conquests for online marketing are wasted. Email marketing service also helps companies in being more specific and more focused about their advertising campaigns; it saves time and money. With the convenience of the internet and online marketing services, there is a better way to send out bulk emails in a blink of an eye.
Apart from convenience, the internet also holds a vast list of contacts. It is not advisable to randomly send out advertisements to contacts. With the business email list, companies have a much more targeted niche of contacts. Having a good emaillist for business allows companies to approach their customers and prospects better since they are very certain of what they should present.
In order to keep always keep in touch with these contacts, the contact database should also be updated with any changes. Having dead contacts is no way to advertise if companies wants positive results.


text:
From GamesReviews.com:
"There have been a number of attempts to bring the MMO to consoles and they have, by and large, been unsuccessful. Instead of building a game to play with a controller in front of the TV from scratch, developers instead adapt a game built around dozens of keyboard keys and a mouse. They're often surprised when that doesn't work.
Defiance is a game that brings together the spirit of third person multiplayer gaming and the massive, persistent world of the MMO, and it does it so successfully you might begin to question why it wasn't possible before. This feels like..."


text: Looking for a tasty treat but don't want to lose all your points for the day? Check out this Chocolate Espresso Mousse Shots recipe that Weight Watchers has for free on their site. The recipe is free for all, not just members and looks very easy to make.Claim Deal »


text:
The Cherokee have a wonderful shopping village on the reservation that is filled with little shops, eating places, and river you can raft down. This place is called Saunooke Village! The river park is close-by.
Each of the seasons has a different view of the Reservation and surrounding areas. Turning leaves in the fall, a dusting of snow in the winter, spring flowers, and even summer time rafting!
Craftsmanship is simply detailed and creative! You can find anything from books to bird houses, and herbs to wood flutes. There are also souvenirs and trinkets to must-haves and baubles to gift to others. Saunooke Village is a great place to find treasures for holiday's and birthday's that are original. These stores and shops delight shoppers and offer many fine hand-worked items to dazzle your family and friends.
Nearby you will find the Great Smoky Mountain Park Cherokee entrance, Mingus Mill, Mingus Falls, large grazing elk, and so much more. This majestic area is scenic, worthy of a photo shoot, great for hikers and explorers, filled with winding and twisting roads, filled with interesting shops, holds some terrific eatery places, holds a Cherokee museum, entices many to their casino for gambling, and hosts the Great Cherokee Native Americans!
Your historical visit awaits any family, individual, or group. You might just be surprised at all the Cherokee have to offer visitors and locals!
~Kris Williams
And now my special deal of the day…
Perfect for those Fish lovers, fishermen, and cooks…
100 Salmon Recipes
This eBook has some delicious recipes all about Salmon! Main dishes to appetizers and much more. And the best thing about this eBook is that you can RESELL it, with MRR, and make money reselling it to others!


text:
|시간 제한
|메모리 제한
|맞은 사람
|정답 비율
|1 초
Little Yuan is two years old and she is learning about some triangles and quadrangles. She is such a smart girl that she soon realizes two triangles can form a quadrangle without overlapping each other. She picks up a lot of triangles and uses them to form some quadrangles. Unfortunately, she is not good at this kind of jigsaw game and makes some mistakes.
As her brother, you are curious about whether she has made a mistake when forming two triangles into a quadrangle. You are thinking about to write a program to determine it.
Notice that the quadrangle in this problem is defined as a simple polygon with four vertexes. And you may also assume that all triangles and quadrangle have positive area.
Note that two graphs are considered as the same if and only if they can overlap completely by shifting, rotation and flipping.
There are multiple test cases. The first line of input contains a single integer T denoting the number of test cases. (T <= 500)
For each test case, there are 10 lines in total.
The first 3*2 lines describe the two triangles. Each line with two integers denotes the coordinates of a point.
The next 4 lines describe the quadrangle in clockwise order or counter-clockwise order.
All coordinates are less than 15000 in absolute value.
For each test case, output "Yes" if the given triangles can form a quadrangle without overlapping, "No" otherwise.
2 0 0 0 1 1 0 0 0 0 1 1 0 -1 0 0 0 1 0 0 1 0 0 -1 1 1 0 0 0 0 1 1 0 -1 0 0 0 1 0 0 1
Case #1: Yes Case #2: No


text:
252 Used cars under $15,000 Augusta Georgia
1 Prices shown do not include taxes, license or a destination & handling charge. Destination charge for ILX, TLX and RLX is $965.00, NSX is $1800.00 and MDX and RDX is $995.00. Actual vehicles/accessory costs, labor and installation vary. Please consult your selected dealer.
Save Big on Used Vehicles in Augusta, Georgia
In addition to our amazing selection of low-priced pre-owned cars, you'll also find plenty of ways to experience extra savings at Acura of Augusta. Whether you take advantage of our used car specials or bargain inventory, or you value your trade and get top dollar for your used car, the opportunities for savings at our Augusta, GA dealership are always within reach. Ready to get started? Give us a call now and find out all the ways you can save on our incredible pre-owned inventory.
Wide Variety of Pre-Owned Cars, Trucks, SUVs & More at Acura of Augusta
Whether you choose a great used car from our certified pre-owned or pre-owned inventory, we guarantee you'll encounter a price that makes sense for your budget. And thanks to our team of highly skilled auto financing professionals, you won't have to navigate the car-buying process alone. To make the most of your money and our incredible selection of used inventory, do yourself a favor and get in contact with our used car dealership in Augusta, GA today.


text:
Enter your search term & enter. Esc or X to close.
I. Treatment and Prevention
In accordance with the avowed purposes of NAADAC, The Association for Addiction Professionals—prompting and supporting the most appropriate and highest quality of care and treatment for chemically dependent clients/patients and their families—advocates and supports the development of policies and programs that promote the prevention and treatment of nicotine dependence on a par with alcoholism and drug dependence.
NAADAC understands that some cultures, such as First Nations People, use tobacco as a medicine in ceremonial practice. For that purpose, to honor and include cultural traditions and healing practices, NAADAC recognizes the difference between tobacco abuse and dependence and ceremonial tobacco use.
NAADAC recognizes the need for the addiction treatment community to adopt a consistent position on issues related to tobacco use and nicotine dependence, noting that nicotine addiction is especially prevalent among those who suffer from alcoholism and other drug dependencies1. Indeed, the relationship is so strong that intractable heavy smoking is a predictor of unrecognized alcohol abuse2. Tragically, tobacco-related diseases are the leading cause of death in patients previously treated for alcoholism and/or other non-nicotine drugs of dependence3. Nicotine dependence treatment is imperative in such high-risk patients4.
NAADAC recognizes that nicotine is a psychoactive drug and that its regular use can result in nicotine dependence and premature death5. It is estimated that 2.5 million people die worldwide each year because of tobacco use and that by 2020 the death toll will be at least 10 million if present trends in tobacco consumption continue6. In the United States, cigarettes kill 430,000 people directly each year7, and environmental tobacco smoke kills more than 53,0008.
The preponderance of data from USDHHS, WHO, the Surgeon General, the Environmental Protection Agency, CDC, the American Heart Association, the American Cancer Society, and the American Lung Association demonstrates that tobacco use (including smokeless tobacco) and exposure to environmental tobacco smoke (a class A carcinogen) are major contributors to illness, disability, and death. Cigarettes kill many more people than all other drugs and alcohol combined9. In fact, smoking kills more Americans each year than alcohol, cocaine, crack, heroin, homicide, suicide, fires, car accidents, and AIDS combined.
NAADAC regards nicotine addiction as a primary health problem, and recognizes tobacco-caused illnesses as the direct consequence of nicotine dependence. Just as alcoholism and other drug addictions have not always been viewed as primary diseases, the health profession has traditionally viewed tobacco use as a risk factor for other diseases, but not as a primary health problem itself. This approach has impeded rather than advanced the development of optimal treatment methods for clients addicted to nicotine.
NAADAC recommends that all patients presenting for substance abuse services be screened and assessed for tobacco use and, where applicable, that a tobacco or nicotine diagnosis, using DSM-IV or ICD 9 criteria, be made in the patient's chart.
NAADAC further recommends that tobacco dependence be included in the treatment plan for every patient to whom it applies. Furthermore, discharge plans should address all unresolved problems, including the use of tobacco, identified at admission or during treatment.
NAADAC recommends that information about the desirability of participating in self-help support groups such as Nicotine Anonymous (NicA) be made available to patients and family members.
NAADAC strongly supports and encourages the provision of tobacco education within the addictions treatment milieu. At a minimum, tobacco specific didactic sessions can be added to the existing alcohol and other drug, HIV/AIDS education, and health curriculum. More appropriately, in integrating tobacco treatment on a par with alcohol and other drug dependence treatment, nicotine dependence material can be incorporated into essentially every general education topic, i.e., use of chemicals to modify and control feelings, consequences of chemical use, etc.10
NAADAC further encourages addictions professionals to include tobacco education for family members of clients, as this will put them in a better position to support and encourage recovery from tobacco dependence for the patient. Family members who receive tobacco education also gain the opportunity to examine their own experiences with tobacco, which may encourage tobacco users to seek assistance in quitting and non-users to gain validation and support in setting healthy and appropriate limits regarding exposing themselves to environmental tobacco smoke pollution.
NAADAC acknowledges that addiction counselors need to demonstrate healthy lifestyles through role modeling. As our field moves towards treating tobacco dependence, we recommend that staff not be identifiable as tobacco users during working hours or when representing the treatment facility.
NAADAC acknowledges the change in recognition of tobacco as a drug of addiction and the conflict this may create for members in the role of addiction professional. Therefore, NAADAC encourages each state affiliate to develop assistance services for members who wish to address their tobacco use issues.
NAADAC strongly encourages that treatment facilities and the surrounding property be designated tobacco-free areas. NAADAC supports the prohibition of the use of tobacco products and spit tobacco within all buildings and on the grounds of all free-standing treatment facilities as well as in vehicles used to transport patients at any time.
NAADAC recommends that public and private sector treatment providers and employers offer tobacco-specific training as part of their general in-service training programs to all employees to explain the rationale for treating nicotine dependence within the addictions milieu.
NAADAC supports the emphasis on training of health care professionals, including addictions specialists, to regard tobacco dependence as a health issue that requires parity of treatment with alcohol and other drugs of dependence. NAADAC pledges to provide opportunities for training in tobacco dependence and to further suggest scientifically-based resources where addictions specialists might procure this training.
NAADAC supports making information about tobacco use and abuse available to the public. NAADAC encourages early teaching in the family and in schools about the risks associated with tobacco, including smokeless tobacco (SLT) and environmental tobacco smoke (ETS). NAADAC recommends prevention programs to educate members of the public about the dangers of tobacco use during pregnancy and lactation, and the effect of environmental tobacco smoke (ETS) on children.
II. Policy and Legal/Regulatory Issues
NAADAC supports the promotion of research into the causes, prevention, and treatment of nicotine addiction, including the natural history of tobacco dependence and the clinical management of nicotine replacement.
NAADAC endorses assigning the regulation of all nicotine-containing products intended for human consumption to the Food and Drug Administration and supports the regulation of cigarettes, smokeless tobacco and all nicotine-containing products as nicotine-delivery devices.
NAADAC advocates the strengthening of warning labels on tobacco products. NAADAC further advocates that warning labels be written in simple language and state the harm ETS causes others, the diseases caused by tobacco use, and the risk of addiction. In addition, NAADAC would like to see the warning labels placed more prominently and on a larger percentage of the package face of tobacco products.
NAADAC advocates the establishment of smoke-free policies in all health care facilities and in locations selected for workshops, clinics, seminars, and conferences that address health care issues and chemical dependency. NAADAC pledges that association-sponsored functions, meetings, seminars, and workshops will be smoke-free.
NAADAC encourages third-party reimbursement for the treatment of tobacco dependence by qualified health professionals who use clinically recognized methods.
NAADAC urges all institutions involved in health care, including addiction treatment facilities, to divest any tobacco industry holdings, since profits of this industry are in direct opposition to controlling the spread of this epidemic in children and adults.
NAADAC supports laws that limit access of tobacco products to minors and that make it illegal to give, sell, or provide tobacco products to minors.
1 Hurt, Eberman, Slade, and Karan, 1993
2 Hurt et al., 1994, pp. 867-872
3 Hurt et al., 1994, p. 1102
4 Hurt et al., 1994, p. 1097
5 U.S. Department of Health and Human Services (USDHSS], 1988; World Health Organization [WHO], 1995
6 Peto, Lopez, Boreham, Thun, and Heath, 1992
7 Centers for Disease Control and Prevention [CDC], 1993
8 Glantz and Parmley, 1991; USDHHS, 1986
9 Lynch and Bonnie, 1994
10 Rustin, 1998
Centers for Disease Control and Prevention (1993). Cigarette smoking: Attributable mortality and years of potential life lost-US, 1990. Morbidity and Mortality Weekly Report,42:33, 645-649.
Glantz, S.A., & Parmley, W.W. (1991). Passive smoking and heart disease: Epidemiology, physiology, and biochemistry. Circulation, 83:1-12.
Hurt, R.D., Offord, K.P., Croghan, I.T., Offord, K.P., Davis, L.J., Morse, R.M., Palomino, M.A., & Bruce, B.K. (1994). Nicotine dependency treatment during inpatient treatment for other addictions: A prospective clinical trial. Alcoholism: Clinical and Experimental Research, 18:4, 867-872.
Hurt, R.S., Eberman, K.M., Slade, J., & Karan, L. (1993). Treating nicotine dependence in patients with other addictive disorders. In C.T. Orleans & J. Slade (Eds.), Nicotine addiction: Principles and management. New York: Oxford University Press.
Lynch, B.S., & Bonnie, R.J. (Eds.) (1994). Growing up tobacco free: Preventing nicotine addiction in children and youths (p. 4). Washington, DC: National Academy Press.
Peto, R., Lopez, A.D., Boreham, J., Thun, M., & Heath, C. (1992) Mortality from tobacco in developed countries: Indirect estimation from national vital statistics. Lancet 339:1268-1278.
Rustin, T.A. (1998). Incorporating nicotine dependence treatment into addiction treatment, Journal of Addictive Diseases,17:1, 83-108.
U.S. Department of Health and Human Services (1986). The health consequences of involuntary smoking. DHHS Publication 87-8398. Washington, DC: Government Printing Office.
U.S. Department of Health and Human Services (1988). The health consequences of smoking: Nicotine addiction. DHHS Publication 88-8406. Washington, DC: Government Printing Office.
World Health Organization (1995). Guidelines for controlling and monitoring the tobacco epidemic.


text:
X-Twin Thunderjet takes to the skies
The X-Twin Thunderjet definitely has the looks, and according to the product description below, it also has the brawn to go along with its brain.
This ominous R/C flying machine looks meaner than a cybernetic vulture hearse (whatever that is) and it boasts twin duct-fan engines for serious kick-in-the-tailfin power. You can even vary its speed as it stalks the sky searching for enemy encampments. Or naughty duckie wucks and squirrels. Whatever. Once you get to grips with the controls you'll be soaring through thin air and pulling off mind-blowing twists and turns. Like its real life USAF counterpart, the sinister Thunderjet looks almost unreal. In fact it reminds us of Firefox, that lethally sophisticated jet from the dodgy Clint Eastwood film of the same name. Unlike Firefox, however, the X-Twin can't be controlled via thought impulses; you control the action with a twin-toggle, digital proportional transmitter that doubles up as a charging unit for its built-in lithium polymer battery. (20-30 minutes should give flight times of around 5 minutes).
Man, even if the Christmas season is still a good 9 months away, I want my X-Twin Thunderjet and I want it now! £24.95 from Firebox.


text:
iTito Themes Blog has started a new and exciting MVIA Gold Awards program. we are also excited to announce our first winners.
MVIA Rules:
1. Apps must receive a score of 4.5 or 5 out of 5 to receive a Gold Award.
Note: Click Icons to download app from the iTunes App Store or Android Market or Click Awarded Badge to read the full review.


text: So I have an xbox 360, and a 720P tv and a surround receiver. I bought an Apple TV spontaneously, assuming that if I didn't want it I'd just return it. I could just get Connect 360 for 20 bucks.. or I could pay (keep) the Apple TV for 250 w/ tax. I hate browsing through movies/tvshows/music on my xbox, the UI sucks in my opinion, the Apple TV's UI is beautiful and it navigates this very well There's no visualizer though! And I'll be using the music streaming for parties so it's cool to use the visualizer, which the 360 does. I will have 2 macs and 1 pc streaming to whichever device I use. Most of my content is not gotten through itunes, so it should work on the 360. 5.1 surround sound is a MUST. I've read that the 360 can only do 5.1 in a WMV container. So i'll need to convert all my stuff to wmv for 5.1 sound? I dont like having wmv files on my mac, I'm leaning towards just keeping the Apple TV b/c of it's Glorious integration w/ iTunes. I want to be able to watch all of my stuff through Front Row and on my AppleTV or 360, so I'd prefer to leave the movies in formats that are recognized by iTunes. I'm crazy right? Paying an extra 200+ just for the Apple ''experience''? Can I justify paying for the TV, when I already have a 360? EDIT: I also have a PS3 in my apartment.