BackgroundArboviral infections are a public health concern and an escalating problem worldwide. Estimating the burden of these diseases represents a major challenge that is complicated by the large number of unapparent infections, especially those of dengue fever. Serological surveys are thus required to identify the distribution of these diseases and measure their impact. Therefore, we undertook a scoping review of the literature to describe and summarize epidemiological practices, findings and insights related to seroprevalence studies of dengue, chikungunya and Zika virus, which have rapidly expanded across the globe in recent years.Methodology/Principal findingsRelevant studies were retrieved through a literature search of MEDLINE, WHOLIS, Lilacs, SciELO and Scopus (2000 to 2018). In total, 1389 publications were identified. Studies addressing the seroprevalence of dengue, chikungunya and/or Zika written in English or French and meeting the inclusion and exclusion criteria were included. In total, 147 studies were included, from which 185 data points were retrieved, as some studies used several different samples. Most of the studies were exclusively conducted on dengue (66.5%), but 16% were exclusively conducted on chikungunya, and 7 were exclusively conducted on Zika; the remainder were conducted on multiple arboviruses. A wide range of designs were applied, but most studies were conducted in the general population (39%) and in households (41%). Although several assays were used, enzyme-linked immunosorbent assays (ELISAs) were the predominant test used (77%). The temporal distribution of chikungunya studies followed the virus during its rapid expansion since 2004. The results revealed heterogeneity of arboviruses seroprevalence between continents and within a given country for dengue, chikungunya and Zika viruses, ranging from 0 to 100%, 76% and 73% respectively.Conclusions/SignificanceSerological surveys provide the most direct measurement for defining the immunity landscape for infectious diseases, but the methodology remains difficult to implement. Overall, dengue, chikungunya and Zika serosurveys followed the expansion of these arboviruses, but there remain gaps in their geographic distribution. This review addresses the challenges for researchers regarding study design biases. Moreover, the development of reliable, rapid and affordable diagnosis tools represents a significant issue concerning the ability of seroprevalence surveys to differentiate infections when multiple viruses co-circulate.
Zika virus (ZIKV) infection has been associated with complications during pregnancy. Although the presence of symptoms might be a risk factor for complication, the proportion of ZIKV-infected pregnant women with symptoms remains unknown. Following the emergence of ZIKV in French Guiana, all pregnancies in the territory were monitored by RT-PCR and/or detection of ZIKV antibodies. Follow-up data collected during pregnancy monitoring interviews were analysed from 1 February to 1 June 2016. We enrolled 3,050 pregnant women aged 14–48 years and 573 (19%) had laboratory-confirmed ZIKV infection. Rash, arthralgia, myalgia and conjunctival hyperaemia were more frequently observed in ZIKV-positive women; 23% of them (95% confidence interval (CI): 20–27) had at least one symptom compatible with ZIKV infection. Women 30 years and older were significantly more likely to have symptoms than younger women (28% vs 20%). The proportion of symptomatic infections varied from 17% in the remote interior to 35% in the urbanised population near the coast (adjusted risk ratio: 1.6; 95% CI: 1.4–1.9.). These estimates put findings on cohorts of symptomatic ZIKV-positive pregnant women into the wider context of an epidemic with mainly asymptomatic infections. The proportion of symptomatic ZIKV infections appears to vary substantially between populations.
BackgroundDuring the last decade, French Guiana has been affected by major dengue fever outbreaks. Although this arbovirus has been a focus of many awareness campaigns, very little information is available about beliefs, attitudes and behaviors regarding vector-borne diseases among the population of French Guiana. During the first outbreak of the chikungunya virus, a quantitative survey was conducted among high school students to study experiences, practices and perceptions related to mosquito-borne diseases and to identify socio-demographic, cognitive and environmental factors that could be associated with the engagement in protective behaviors.Methodology/Principal FindingsA cross-sectional survey was administered in May 2014, with a total of 1462 students interviewed. Classrooms were randomly selected using a two-stage selection procedure with cluster samples. A multiple correspondence analysis (MCA) associated with a hierarchical cluster analysis and with an ordinal logistic regression was performed. Chikungunya was less understood and perceived as a more dreadful disease than dengue fever. The analysis identified three groups of individual protection levels against mosquito-borne diseases: “low” (30%), “moderate” (42%) and “high” (28%)”. Protective health behaviors were found to be performed more frequently among students who were female, had a parent with a higher educational status, lived in an individual house, and had a better understanding of the disease.Conclusions/SignificanceThis study allowed us to estimate the level of protective practices against vector-borne diseases among students after the emergence of a new arbovirus. These results revealed that the adoption of protective behaviors is a multi-factorial process that depends on both sociocultural and cognitive factors. These findings may help public health authorities to strengthen communication and outreach strategies, thereby increasing the adoption of protective health behaviors, particularly in high-risk populations.
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BackgroundDengue fever epidemic dynamics are driven by complex interactions between hosts, vectors and viruses. Associations between climate and dengue have been studied around the world, but the results have shown that the impact of the climate can vary widely from one study site to another. In French Guiana, climate-based models are not available to assist in developing an early warning system. This study aims to evaluate the potential of using oceanic and atmospheric conditions to help predict dengue fever outbreaks in French Guiana.Methodology/Principal FindingsLagged correlations and composite analyses were performed to identify the climatic conditions that characterized a typical epidemic year and to define the best indices for predicting dengue fever outbreaks during the period 1991–2013. A logistic regression was then performed to build a forecast model. We demonstrate that a model based on summer Equatorial Pacific Ocean sea surface temperatures and Azores High sea-level pressure had predictive value and was able to predict 80% of the outbreaks while incorrectly predicting only 15% of the non-epidemic years. Predictions for 2014–2015 were consistent with the observed non-epidemic conditions, and an outbreak in early 2016 was predicted.Conclusions/SignificanceThese findings indicate that outbreak resurgence can be modeled using a simple combination of climate indicators. This might be useful for anticipating public health actions to mitigate the effects of major outbreaks, particularly in areas where resources are limited and medical infrastructures are generally insufficient.
Local variation in the density of Anopheles mosquitoes and the risk of exposure to bites are essential to explain the spatial and temporal heterogeneities in the transmission of malaria. Vector distribution is driven by environmental factors. Based on variables derived from satellite imagery and meteorological observations, this study aimed to dynamically model and map the densities of Anopheles darlingi in the municipality of Saint-Georges de l’Oyapock (French Guiana). Longitudinal sampling sessions of An. darlingi densities were conducted between September 2012 and October 2014. Landscape and meteorological data were collected and processed to extract a panel of variables that were potentially related to An. darlingi ecology. Based on these data, a robust methodology was formed to estimate a statistical predictive model of the spatial-temporal variations in the densities of An. darlingi in Saint-Georges de l’Oyapock. The final cross-validated model integrated two landscape variables—dense forest surface and built surface—together with four meteorological variables related to rainfall, evapotranspiration, and the minimal and maximal temperatures. Extrapolation of the model allowed the generation of predictive weekly maps of An. darlingi densities at a resolution of 10-m. Our results supported the use of satellite imagery and meteorological data to predict malaria vector densities. Such fine-scale modeling approach might be a useful tool for health authorities to plan control strategies and social communication in a cost-effective, targeted, and timely manner.
In French Guiana, malaria vector control and prevention relies on indoor residual spraying and distribution of long lasting insecticidal nets. These measures are based on solid epidemiological evidence but reveal a poor understanding of the vector. The current study investigated the behaviour of both vectors and humans in relation to the ongoing prevention strategies. In 2012 and 2013, Anopheles mosquitoes were sampled outdoors at different seasons and in various time slots. The collected mosquitoes were identified and screened for Plasmodium infection. Data on human behaviour and malaria episodes were obtained from an interview. A total of 3,135 Anopheles mosquitoes were collected, of which Anopheles darlingi was the predominant species (96.2%). For the December 2012-February 2013 period, the Plasmodium vivax infection rate for An. darlingi was 7.8%, and the entomological inoculation rate was 35.7 infective bites per person per three-month span. In spite of high bednet usage (95.7%) in 2012 and 2013, 52.2% and 37.0% of the participants, respectively, had at least one malaria episode. An. darlingi displayed heterogeneous biting behaviour that peaked between 20:30 and 22:30; however, 27.6% of the inhabitants were not yet protected by bednets by 21:30. The use of additional individual and collective protective measures is required to limit exposure to infective mosquito bites and reduce vector densities.
BackgroundIn French Guiana, Mosquito Magnet® Liberty Plus trap baited with octenol (MMoct) has been proposed for sampling Anopheles darlingi after comparison with CDC light trap and Human landing catch (HLC). However, other available lures were not tested. The current study compared MMoct and MM baited with Lurex™ (MMlur) to HLC, and analysed entomological data from MMoct collection with malaria cases to facilitate malaria surveillance.MethodsTwo independent experiments were conducted during 2012 and 2013 in Saint-Georges town, French Guiana. The first experiment used Latin square design to compare MMoct and MMlur to HLC between 18:30 to 22:30 and 05:00 to 07:00. Parity rate was determined for An. darlingi from each sampling system. In the second experiment, a 24:00 hour collection was done for four consecutive days during the first week of each month and every four days for the rest of the month using MMoct. Portion of the 24 hour collection was dissected for parity rate. All anophelines were screened for Plasmodium infection by PCR. Data for number of malaria cases was analysed for association with density of An. darlingi.ResultsIn the first experiment, 3,721 anopheline mosquitoes were collected over 21 nights. Of these, 95.7% was identified morphologically to five species and An. darlingi contributed 98.4%, mainly from HLC (75.1%, CI 95% [73.2-77.0]) than MMoct (14.1%, CI 95% [12.6-15.7]) and MMlur (10.8%, CI 95% [9.4-12.2]). Species richness was highest in HLC meanwhile species diversity index was greatest in MMoct. MMoct collected more parous An. darlingi than HLC (p < 0.0001) and MMlur (p = 0.0021). The second experiment amounted to 2035 females, 60.8% belonging to 10 species. Anopheles darlingi constituted 85.0% of the species and had parity rate of 52.3%. Specimens were uninfected with Plasmodium. Density of An. darlingi best correlated with malaria cases observed six weeks later (p = 0.0016; r = 0.4774).ConclusionThough MMoct and MMlur performed well in sampling An. darlingi, MMoct captured more species and, therefore, would be useful for surveillance. Even if it collected mostly parous mosquitoes, MMoct proved useful in collecting entomological data required for predicting malaria emergence. It is a potential replacement for HLC.
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