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After the mass campaign of Measles and Rubella vaccination in 2003 in Iran, the cases of measles and rubella infection decreased but still, the cases of rash and fever were reported. It is worth noting that some other viral infections show signs similar to measles and rubella such as some arboviruses. Considering the epidemic outbreak of arbovirus infections in countries neighbouring Iran, we performed this study to estimate the possibility of chikungunya and dengue fever among measles and rubella IgM negative patients presenting with rash and fever from December 2016 to November 2017 in the National Measles Laboratory at Tehran University of Medical Sciences. Serum samples were selected at random from patients from eight provinces. The presence of DENV IgM and CHIKV IgM was examined by enzyme-linked immunosorbent assay. Of the 1306 sera tested, 210 were CHIKV seropositive and 82 were dengue seropositive. Statistical analysis demonstrated a significant increase in the CHIKV IgM antibody seropositivity rate in Kerman (OR = 2.07, 95% CI: 1.10–3.92; P = 0.024) and Fars (OR = 1.77, 95% CI: 1.06–2.93; P = 0.027). The DENV and CHIKV seropositivity rate in summer is higher than in other seasons (P < 0.01). Our seropositive samples suggest possible CHIKV and DENV infection in Iran. It is likely that these viruses are circulating in Iran and there is a need to study vector carriage of these two viruses.
Different countries, especially Brazil, that have faced recurrent dengue epidemics for decades and chikungunya epidemics since 2014, have had to restructure their health services to combat a triple epidemic of arboviruses – Zika, dengue and Chikungunya – transmitted by the same vector, mainly Aedes aegypti, in 2015–2016. Several efforts have been made to better understand these three arboviruses. Spatial analysis plays an important role in the knowledge of disease dynamics. The knowledge of the patterns of spatial diffusion of these three arboviruses during an epidemic can contribute to the planning of surveillance actions and control of these diseases. This study aimed to identify the spatial diffusion processes of these viruses in the context of the triple epidemic in 2015–2016 in Rio de Janeiro, Brazil. Two study designs were used: cross-sectional and ecological. Sequential Kernel maps, nearest-neighbour ratios calculated cumulatively over time, Moran global autocorrelation correlograms, and local autocorrelation changes over time were used to identify spatial diffusion patterns. The results suggested an expansion diffusion pattern for the three arboviruses during 2015–2016 in Rio de Janeiro. These findings can be considered for more effective control measures and for new studies on the dynamics of these three arboviruses.
Dengue is a widespread vector-borne disease believed to affect between 100 and 390 million people every year. The interaction between vector, host and pathogen is influenced by various climatic factors and the relationship between dengue and climatic conditions has been poorly explored in India. This study explores the relationship between El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and dengue cases in India. Additionally, distributed lag non-linear model was used to assess the delayed effects of climatic factors on dengue cases. The weekly dengue cases reported by the Integrated Disease Surveillance Program (IDSP) over India during the period 2010–2017 were analysed. The study shows that dengue cases usually follow a seasonal pattern, with most cases reported in August and September. Both temperature and rainfall were positively associated with the number of dengue cases. The precipitation shows the higher transmission risk of dengue was observed between 8 and 15 weeks of lag. The highest relative risk (RR) of dengue was observed at 60 mm rainfall with a 12-week lag period when compared with 40 and 80 mm rainfall. The RR of dengue tends to increase with increasing mean temperature above 24 °C. The largest transmission risk of dengue was observed at 30 °C with a 0–3 weeks of lag. Similarly, the transmission risk increases more than twofold when the minimum temperature reaches 26 °C with a 2-week lag period. The dengue cases and El Niño were positively correlated with a 3–6 months lag period. The significant correlation observed between the IOD and dengue cases was shown for a 0–2 months lag period.
Dengue infection in China has increased dramatically in recent years. Guangdong province (main city Guangzhou) accounted for more than 94% of all dengue cases in the 2014 outbreak. Currently, there is no existing effective vaccine and most efforts of control are focused on the vector itself. This study aimed to evaluate different dengue management strategies in a region where this disease is emerging. This work was done by establishing a dengue simulation model for Guangzhou to enable the testing of control strategies aimed at vector control and vaccination. For that purpose, the computer-based dengue simulation model (DENSiM) together with the Container-Inhabiting Mosquito Simulation Model (CIMSiM) has been used to create a working dengue simulation model for the city of Guangzhou. In order to achieve the best model fit against historical surveillance data, virus introduction scenarios were run and then matched against the actual dengue surveillance data. The simulation model was able to predict retrospective outbreaks with a sensitivity of 0.18 and a specificity of 0.98. This new parameterisation can now be used to evaluate the potential impact of different control strategies on dengue transmission in Guangzhou. The knowledge generated from this research would provide useful information for authorities regarding the historic patterns of dengue outbreaks, as well as the effectiveness of different disease management strategies.
Dengue fever is a disease with increasing incidence, now occurring in some regions which were not previously affected. Ribeirão Preto and São Paulo, municipalities in São Paulo state, Brazil, have been highlighted due to the high dengue incidences especially after 2009 and 2013. Therefore, the current study aims to analyse the temporal behaviour of dengue cases in the both municipalities and forecast the number of disease cases in the out-of-sample period, using time series models, especially SARIMA model. We fitted SARIMA models, which satisfactorily meet the dengue incidence data collected in the municipalities of Ribeirão Preto and São Paulo. However, the out-of-sample forecast confidence intervals are very wide and this fact is usually omitted in several papers. Despite the high variability, health services can use these models in order to anticipate disease scenarios, however, one should interpret with prudence since the magnitude of the epidemic may be underestimated.
Our objective was to determine the frequency of zika (ZIKV), chikungunya (CHIKV) and dengue (DENV) virus coinfection and describe the mortality cases that occurred during the epidemiologic surveillance of the ZIKV epidemic in Colombia. We analysed all cases of suspected ZIKV infection that were reported to the National Institute of Health (October 2015–December 2016). DENV, CHIKV and ZIKV RNA were detected in serum or tissue samples using polymerase chain reaction assay. Medical records of the fatal cases were reviewed. We identified that 23 871 samples were processed. The frequency of viral agents was 439 (1.84%) for DENV, 257 (1.07%) for CHIKV and 10118 (42.38%) for ZIKV. Thirty-four (0.14%) cases of coinfection were identified. The CHIKV–ZIKV coinfection was present in 28 cases (82.3%), DENV–CHIKV in three (8.8%) and DENV–ZIKV in three (8.8%). Seven (20.6%) coinfection cases were fatal (two DENV–CHIKV cases and five CHIKV–ZIKV cases). Two cases were foetal deaths and the others were related to neurological syndrome and sepsis. In conclusion, the frequency of arbovirus coinfection during epidemic of ZIKV was low, and CHIKV–ZIKV coinfection was the most common. Mortality was high among coinfection patients. The role of each virus in the mortality cases of coinfection warrants further studies.
This study sets an example of an economic evaluation of a model dengue vaccination strategy for Sri Lanka, following a mandatory pre-vaccination screening strategy.
A decision analytic Markov model was developed to estimate the cost-effectiveness of a predicted dengue vaccination strategy over a time horizon of 10 years. The cost effectiveness of dengue vaccination strategy for seropositive individuals was estimated in terms of incremental cost effectiveness ratio (ICER) (cost per additional quality adjusted life-year [QALY]). District-specific ICER values and the budget impact for dengue vaccine were estimated with appropriate sensitivity analyses, also taking the variability of the pre-vaccination screening test performance into consideration.
The ICER for the predicted vaccination strategy following pre-vaccination screening was 4,382 USD/QALY for Sri Lanka. There was a significant regional variation in vaccine cost effectiveness. The disaggregated regional incidence of dengue and the need to perform pre-vaccination screening affects the cost effectiveness estimates significantly, where a safer version of the vaccine has the potential to become cost saving in high incidence districts.
The cost effectiveness of the predicted dengue vaccination strategy following pre-vaccination screening showed a significant regional variation across the districts of Sri Lanka. District-wise disease incidence and the need for pre-vaccination screening was found to be the most significant factors affecting the cost effectiveness of the vaccine.
Dengue fever (DF) is one of the world's most disabling mosquito-borne diseases, with a variety of approaches available to model its spatial and temporal dynamics. This paper aims to identify and compare the different spatial and spatio-temporal Bayesian modelling methods that have been applied to DF and examine influential covariates that have been reportedly associated with the risk of DF. A systematic search was performed in December 2017, using Web of Science, Scopus, ScienceDirect, PubMed, ProQuest and Medline (via Ebscohost) electronic databases. The search was restricted to refereed journal articles published in English from January 2000 to November 2017. Thirty-one articles met the inclusion criteria. Using a modified quality assessment tool, the median quality score across studies was 14/16. The most popular Bayesian statistical approach to dengue modelling was a generalised linear mixed model with spatial random effects described by a conditional autoregressive prior. A limited number of studies included spatio-temporal random effects. Temperature and precipitation were shown to often influence the risk of dengue. Developing spatio-temporal random-effect models, considering other priors, using a dataset that covers an extended time period, and investigating other covariates would help to better understand and control DF transmission.
Dengue fever (DF) has been a growing public-health concern in China since its emergence in Guangdong Province in 1978. Of all the regions that have experienced dengue outbreaks in mainland China, the city of Guangzhou is the most affected. This study aims to investigate the potential risk factors for dengue virus (DENV) transmission in Guangzhou, China, from 2006 to 2014. The impact of risk factors on DENV transmission was qualified by the q-values calculated using a novel spatial-temporal method, the GeoDetector model. Both climatic and socioeconomic factors were considered. The impacts on DF incidence of each single factor and the interaction of two factors were analysed. The results show that the number of days with rainfall of the month before last has the highest determinant power, with a q-value of 0.898 (P < 0.01); the q-values of the other factors related to temperature and precipitation were around 0.38–0.50. Integrating a Pearson correlation analysis, nonlinear associations were found between the DF incidence in Guangzhou and the climatic factors considered. The coupled impact of the different variables considered was enhanced compared with their individual effects. In addition, an increased number of tourists in the city were associated with a high incidence of DF. This study demonstrates that the number of rain days in a month has great influence on the DF incidence of the month after next; the temperature and precipitation have nonlinear impacts on the DF incidence in Guangzhou; both the domestic and overseas tourists coming to the city increase the risk of DENV transmission. These findings are useful in the risk assessment of DENV transmission, to predict DF outbreaks and to implement preventive DF reduction strategies.
Vaccinating monkeys against yellow fever (YF) has been a common practice in the beginning of the 17D vaccine development. Although it may seem strange at first sight, vaccinating monkeys as a public health strategy is, we think, feasible and theoretically could eliminate the infection among non-human primates, interrupting the virus circulation (or significantly reducing it) and therefore reducing the risk of spilling over to the human population. We propose a series of studies that could demonstrate (or not) the efficacy and feasibility of vaccinating non-human primates YF reservoirs living in green areas of urban centres to cut off or curb the virus circulation that recurrently spill over to the human population. Therefore, vaccinating monkeys in relatively small green areas of the urban centres is perhaps the ultimate solution for the Brazilian recurrent YF epizootics.
PUFA might modulate inflammatory responses involved in the development of severe dengue. We aimed to examine whether serum PUFA concentrations in patients diagnosed with dengue fever (DF) were related to the risk of progression to dengue haemorrhagic fever/dengue shock syndrome (DHF/DSS). A secondary aim was to assess correlations between fatty acids (FA) and inflammatory biomarkers in patients with DF. We conducted a prospective case–control study nested within a cohort of patients who were diagnosed with DF and followed during the acute episode. We compared the distribution of individual FA (% of total FA) at onset of fever between 109 cases who progressed to DHF/DSS and 235 DF non-progressing controls using unconditional logistic regression. We estimated correlations between baseline FA and cytokine concentrations and compared FA concentrations between the acute episode and >1 year post-convalescence in a subgroup. DHA was positively related to progression to DHF/DSS (multivariable adjusted OR (AOR) for DHA in quintile 5 v. 1=5·34, 95 % CI 2·03, 14·1; Ptrend=0·007). Dihomo-γ-linolenic acid (DGLA) was inversely associated with progression (AOR for quintile 5 v. 1=0·30, 95 % CI 0·13, 0·69; Ptrend=0·007). Pentadecanoic acid concentrations were inversely related to DHF/DSS. Correlations of PUFA with cytokines at baseline were low. PUFA were lower during the acute episode than in a disease-free period. In conclusion, serum DHA in patients with DF predicts higher odds of progression to DHF/DSS whereas DGLA and pentadecanoic acid predict lower odds.
Co-circulation of Chikungunya and Dengue viral infections (CHIKV and DENV) have been reported mainly due to transmission by common Aedes vector. The purpose of the study was to identify and characterise the circulating strains of CHIKV and DENV in DENV endemic region of New Delhi during 2016. CHIKV and DENV were identified in the blood samples (n = 130) collected from suspected patients by RT-PCR. CHIKV was identified in 26 of 65 samples (40%). Similarly, DENV was detected in 48 of 120 samples (40%). Co-infection with both the viruses was identified in five (9%) of the samples. Interestingly, concurrent infection with DENV, CHIKV and Plasmodium vivax was detected in two samples. CHIKV strains (n = 11) belonged to the ECSA genotype whereas DENV-3 sequences (n = eight) clustered in Genotype III by phylogenetic analysis. Selection pressure of E1 protein of CHIKV and CprM protein of DENV-3 revealed purifying selection with four and two positive sites, respectively. Four amino acids of the CHIKV were positively selected and had high entropy suggesting probable variations. Co-circulation of both viruses in DENV endemic regions warrants effective monitoring of these emerging pathogens via comprehensive surveillance for implementation of effective control measures.
Dengue virus type 3 genotype III (DENV-3/III) is widely distributed in most dengue-endemic regions. It emerged in Malaysia in 2008 and autochthonously spread in the midst of endemic DENV-3/I circulation. The spread, however, was limited and the virus did not cause any major outbreak. Spatiotemporal distribution study of DENV-3 over the period between 2005 and 2011 revealed that dengue cases involving DENV-3/III occurred mostly in areas without pre-existing circulating DENV-3. Neutralisation assays performed using sera of patients with the respective infection showed that the DENV-3/III viruses can be effectively neutralised by sera of patients with DENV-3 infection (50% foci reduction neutralisation titres (FRNT50) > 1300). Sera of patients with DENV-1 infection (FRNT50 ⩾ 190), but not sera of patients with DENV-2 infection (FRNT50 ⩽ 50), were also able to neutralise the virus. These findings highlight the possibility that the pre-existing homotypic DENV-3 and the cross-reacting heterotypic DENV-1 antibody responses could play a role in mitigating a major outbreak involving DENV-3/III in the Klang Valley, Malaysia.
Aedes aegypti, historically known as yellow fever (YF) mosquito, transmits a great number of other viruses such as Dengue, West Nile, Chikungunya, Zika, Mayaro and perhaps Oropouche, among others. Well established in Africa and Asia, Aedes mosquitoes are now increasingly invading large parts of the American continent, and hence the risk of urban YF resurgence in the American cities should because of great concern to public health authorities. Although no new urban cycle of YF was reported in the Americas since the end of an Aedes eradication programme in the late 1950s, the high number of non-vaccinated individuals that visit endemic areas, that is, South American jungles where the sylvatic cycle of YF is transmitted by canopy mosquitoes, and return to Aedes-infested urban areas, increases the risk of resurgence of the urban cycle of YF. We present a method to estimate the risk of urban YF resurgence in dengue-endemic cities. This method consists in (1) to estimate the number of Aedes mosquitoes that explains a given dengue outbreak in a given region; (2) calculate the force of infection caused by the introduction of one infective individual per unit area in the endemic area under study; (3) using the above estimates, calculate the probability of at least one autochthonous YF case per unit area produced by one single viraemic traveller per unit area arriving from a YF endemic or epidemic sylvatic region at the city studied. We demonstrate that, provided the relative vector competence, here defined as the capacity to being infected and disseminate the virus, of Ae. aegypti is greater than 0.7 (with respect to dengue), one infected traveller can introduce urban YF in a dengue endemic area.
Dengue is the fastest spreading mosquito-transmitted disease in the world. In China, Guangzhou City is believed to be the most important epicenter of dengue outbreaks although the transmission patterns are still poorly understood. We developed an autoregressive integrated moving average model incorporating external regressors to examine the association between the monthly number of locally acquired dengue infections and imported cases, mosquito densities, temperature and precipitation in Guangzhou. In multivariate analysis, imported cases and minimum temperature (both at lag 0) were both associated with the number of locally acquired infections (P < 0.05). This multivariate model performed best, featuring the lowest fitting root mean squared error (RMSE) (0.7520), AIC (393.7854) and test RMSE (0.6445), as well as the best effect in model validation for testing outbreak with a sensitivity of 1.0000, a specificity of 0.7368 and a consistency rate of 0.7917. Our findings suggest that imported cases and minimum temperature are two key determinants of dengue local transmission in Guangzhou. The modelling method can be used to predict dengue transmission in non-endemic countries and to inform dengue prevention and control strategies.
Using the dengue surveillance program, we prospectively collected data on all the suspected and confirmed cases of dengue in Barbados from 2006 to 2015. Data were analysed for demographic, seasonal and temporal dynamics of this disease in this country. The overall mean annual incidence rate of suspected and confirmed dengue over the study period was 0.49% (range 0.15%–0.99%) and 0.16% (range 0.05%−0.48%), respectively. There was a significant correlation between the mean monthly number of confirmed cases, the mean monthly rainfall and the mean monthly relative humidity percentage. Dengue in this population is predominantly an infection affecting children and young adults. The median age of the patients with both, suspected and confirmed dengue was 25 years and the highest proportion of cases was seen in the age group 0–15 years. The annual incidence rates of both the suspected and the confirmed cases showed an upward trend during the study period and this upward trend was more pronounced among children.
In 2007–2008, the city of Rio de Janeiro underwent an epidemiological change, with increases in the incidence in children and in severe forms of dengue. To describe the clinical profile and spatial distribution of dengue we performed an ecological study based on dengue surveillance data using the Brazilian classification (2005): dengue fever, dengue haemorrhagic fever (DHF) and dengue with complications. χ2 test was used to describe the clinical and socio-demographic variables (P < 0.05). Spatial distribution of incidence and case-fatality was explored with thematic maps, Moran and Geary indices (P < 0.05). Of the total of 151 527 dengue cases, 38 808 met the inclusion criteria; 42.4% <18 years; 22.9% dengue with complications and 2.7% DHF. Case-fatality was higher in infants (1.4%) and in DHF (7.7%). Bleeding was more frequent in adolescents and adults while plasma leakage was more common in preschoolers and schoolchildren. The highest incidence was found in the West Zone of the city, in a different area from that of the worst case-fatality (P < 0.05). Although the incidence of DHF was higher in schoolchildren, infants showed higher case-fatality. The area with the highest case-fatality did not present the highest incidence, which suggests problems in the organization of health services.
The number of dengue epidemics in Brazil has increased dramatically in the last 15 years. In this study, we analysed the seasonal patterns in the incidence of hospitalisations due to dengue across the different states of Brazil and compared these with the corresponding climatic patterns. We discovered that the seasonality of dengue hospitalisations in Brazil has a clear zonal gradient, characterised by the progression of primary peaks from West to East during the first half of the year, which may be associated with the increased vapour pressure and rainfall during this period, leading to increased mosquito abundance and activity. We also found that the proportion of children among hospitalised individuals was especially high during the peak outbreaks in 2007/2008 and 2010. This may be due to the emergence and spread of the new DENV-2 Southeast Asian genotype lineage II from 2007, which has probably arrived from the Caribbean and may have caused an increase in incidence and severity of the disease, particularly among children. Our findings may allow health systems to improve control interventions and contribute to reducing dengue morbidity and mortality by using integrated vector control in conjunction with early diagnosis and prompt supportive care.
The purpose of the present study was to reconstruct the phylogeny of dengue virus serotype 4 (DENV-4) that was circulating in Espírito Santo state, Brazil, in 2013 and 2014, and to discuss the epidemiological implications associated with this evolutionary hypothesis. Partial envelope gene of eight DENV-4 samples from Espírito Santo state were sequenced and aligned with 72 worldwide DENV-4 reference sequences from GenBank. A phylogenetic tree was reconstructed through Bayesian Inference and the Time of the Most Recent Common Ancestor was estimated. The study detected the circulation of DENV-4 genotype II in Espírito Santo state, which was closely related to strains from the states of Mato Grosso collected in 2012 and of São Paulo sampled in 2015. This cluster emerged around 2011, approximately 4 years after the entry of the genotype II in Brazil through its northern states, possibly imported from Venezuela and Colombia. This is so far the first phylogenetic study of the DENV-4 circulating in Espírito Santo state and shows the importance of an internal route of dengue viral circulation in Brazil to the introduction of the virus into this state.