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During the rainy season of 2001, the incidence of the dengue vectors Aedes aegypti and Ae. albopictus was examined in different habitats of two cities (Rio de Janeiro and Nova Iguaçu) in Rio de Janeiro State, Brazil, and in two cities (Palm Beach and Boca Raton) in Florida. Oviposition trap collections were performed in urban, suburban, and rural habitats in both areas. Our hypothesis that the abundances and frequencies of occurrence of Ae. aegypti and Ae albopictus are affected in opposite ways by increasing urbanization was only partially supported. City, habitat, and their interaction significantly affected the abundance of both species. Cities with high abundance of Ae. aegypti also had a high abundance of Ae. albopictus. The two species were most abundant in the cities of Rio de Janeiro state and the lowest in Boca Raton. Habitat had a significant but opposite effect on the abundances of Ae. aegypti and Ae. albopictus. In general, Ae. aegypti was most prevalent in highly urbanized areas and Ae. albopictus in rural, suburban, and vegetated urban areas in Rio de Janeiro state and Florida. However, abundances of the two species were similar in most suburban areas. Analyses of frequencies of occurrence showed an unexpected high level of co-occurrence of both species in the same oviposition trap. Despite the different geographical origins of Ae. albopictus in Brazil and the United States, the habitats used by this recent invader are remarkably similar in the two countries.

Experimental releases of female Aedes (Stegomyia) aegypti and Aedes (Stegomyia) albopictus were performed in August and September 1999, in

The first confirmed case of Zika virus infection in the Americas was reported in Northeast Brazil in May 2015, although phylogenetic studies indicate virus introduction as early as 2013. Zika rapidly spread across Brazil and to more than 50 other countries and territories on the American continent. The Aedes aegypti mosquito is thought to be the principal vector responsible for the widespread transmission of the virus. However, sexual transmission has also been reported. The explosively emerging epidemic has had diverse impacts on population health, coinciding with cases of Guillain–Barré Syndrome and an unexpected epidemic of newborns with microcephaly and other neurological impairments. This led to Brazil declaring a national public health emergency in November 2015, followed by a similar decision by the World Health Organization three months later. While dengue virus serotypes took several decades to spread across Brazil, the Zika virus epidemic diffused within months, extending beyond the area of permanent dengue transmission, which is bound by a climatic barrier in the south and low population density areas in the north. This rapid spread was probably due to a combination of factors, including a massive susceptible population, climatic conditions conducive for the mosquito vector, alternative non-vector transmission, and a highly mobile population. The epidemic has since subsided, but many unanswered questions remain. In this article, we provide an overview of the discovery of Zika virus in Brazil, including its emergence and spread, epidemiological surveillance, vector and non-vector transmission routes, clinical complications, and socio-economic impacts. We discuss gaps in the knowledge and the challenges ahead to anticipate, prevent, and control emerging and re-emerging epidemics of arboviruses in Brazil and worldwide.

BackgroundRio de Janeiro, Brazil, experienced a severe dengue fever epidemic in 2008. This was the worst epidemic ever, characterized by a sharp increase in case-fatality rate, mainly among younger individuals. A combination of factors, such as climate, mosquito abundance, buildup of the susceptible population, or viral evolution, could explain the severity of this epidemic. The main objective of this study is to model the spatial patterns of dengue seroprevalence in three neighborhoods with different socioeconomic profiles in Rio de Janeiro. As blood sampling coincided with the peak of dengue transmission, we were also able to identify recent dengue infections and visually relate them to Aedes aegypti spatial distribution abundance. We analyzed individual and spatial factors associated with seroprevalence using Generalized Additive Model (GAM).Methodology/Principal FindingsThree neighborhoods were investigated: a central urban neighborhood, and two isolated areas characterized as a slum and a suburban area. Weekly mosquito collections started in September 2006 and continued until March 2008. In each study area, 40 adult traps and 40 egg traps were installed in a random sample of premises, and two infestation indexes calculated: mean adult density and mean egg density. Sera from individuals living in the three neighborhoods were collected before the 2008 epidemic (July through November 2007) and during the epidemic (February through April 2008). Sera were tested for DENV-reactive IgM, IgG, Nested RT-PCR, and Real Time RT-PCR. From the before–after epidemics paired data, we described seroprevalence, recent dengue infections (asymptomatic or not), and seroconversion. Recent dengue infection varied from 1.3% to 14.1% among study areas. The highest IgM seropositivity occurred in the slum, where mosquito abundance was the lowest, but household conditions were the best for promoting contact between hosts and vectors. By fitting spatial GAM we found dengue seroprevalence hotspots located at the entrances of the two isolated communities, which are commercial activity areas with high human movement. No association between recent dengue infection and household's high mosquito abundance was observed in this sample.Conclusions/SignificanceThis study contributes to better understanding the dynamics of dengue in Rio de Janeiro by assessing the relationship between dengue seroprevalence, recent dengue infection, and vector density. In conclusion, the variation in spatial seroprevalence patterns inside the neighborhoods, with significantly higher risk patches close to the areas with large human movement, suggests that humans may be responsible for virus inflow to small neighborhoods in Rio de Janeiro. Surveillance guidelines should be further discussed, considering these findings, particularly the spatial patterns for both human and mosquito populations.

Dengue dynamics in Rio de Janeiro, Brazil, as in many dengue-endemic regions of the world, is seasonal, with peaks during the wet-hot months. This temporal pattern is generally attributed to the dynamics of its mosquito vector Aedes aegypti (L.). The objectives of this study were to characterize the temporal pattern of Ae. aegypti population dynamics in three neighborhoods of Rio de Janeiro and its association with local meteorological variables; and to compare positivity and density indices obtained with ovitraps and MosquiTraps. The three neighborhoods are distinct in vegetation coverage, sanitation, water supply, and urbanization. Mosquito sampling was carried out weekly, from September 2006 to March 2008, a period during which large dengue epidemics occurred in the city. Our results show peaks of oviposition in early summer 2007 and late summer 2008, detected by both traps. The ovitrap provided a more sensitive index than MosquiTrap. The MosquiTrap detection threshold showed high variation among areas, corresponding to a mean egg density of approximately 25-52 eggs per ovitrap. Both temperature and rainfall were significantly related to Ae. aegypti indices at a short (1 wk) time lag. Our results suggest that mean weekly temperature above 22-24 degrees C is strongly associated with high Ae. aegypti abundance and consequently with an increased risk of dengue transmission. Understanding the effects of meteorological variables on Ae. aegypti population dynamics will help to target control measures at the times when vector populations are greatest, contributing to the development of climate-based control and surveillance measures for dengue fever in a hyperendemic area.

IntroductionThe mosquito Aedes aegypti, vector of dengue, chikungunya and yellow fever viruses, is an important target of vector control programs in tropical countries. Most mosquito surveillance programs are still based on the traditional household larval surveys, despite the availability of new trapping devices. We report the results of a multicentric entomological survey using four types of traps, besides the larval survey, to compare the entomological indices generated by these different surveillance tools in terms of their sensitivity to detect mosquito density variation.MethodsThe study was conducted in five mid-sized cities, representing variations of tropical climate regimens. Surveillance schemes using traps for adults (BG-Sentinel, Adultrap and MosquiTRAP) or eggs (ovitraps) were applied monthly to three 1 km2 areas per city. Simultaneously, larval surveys were performed. Trap positivity and density indices in each area were calculated and regressed against meteorological variables to characterize the seasonal pattern of mosquito infestation in all cities, as measured by each of the four traps.ResultsThe House Index was consistently low in most cities, with median always 0. Traps rarely produced null indices, pointing to their greater sensitivity in detecting the presence of Ae. aegypti in comparison to the larval survey. Trap positivity indices tend to plateau at high mosquito densities. Despite this, both indices, positivity and density, agreed on the seasonality of mosquito abundance in all cities. Mosquito seasonality associated preferentially with temperature than with precipitation even in areas where temperature variation is small.ConclusionsAll investigated traps performed better than the House Index in measuring the seasonal variation in mosquito abundance and should be considered as complements or alternatives to larval surveys. Choice between traps should further consider differences of cost and ease-of-use.

Abstract. We performed bimonthly mosquito larval collections during 1 year, in an agricultural settlement in the Brazilian Amazon, as well as an analysis of malaria incidence in neighboring houses. Water collections located at forest fringes were more commonly positive for Anopheles darlingi larvae and Kulldorff spatial analysis pinpointed significant larval clusters at sites directly beneath forest fringes, which were called larval "hotspots." Remote sensing identified 43 "potential" hotspots. Sampling of these areas revealed an 85.7% positivity rate for A. darlingi larvae. Malaria was correlated with shorter distances to potential hotpots and settlers living within 400 m of potential hotspots had a 2.60 higher risk of malaria. Recently arrived settlers, usually located closer to the tip of the triangularly shaped deforestation imprints of side roads, may be more exposed to malaria due to their proximity to the forest fringe. As deforestation progresses, transmission decreases. However, forest remnants inside deforested areas conferred an increased risk of malaria. We propose a model for explaining frontier malaria in the Amazon: because of adaptation of A. darlingi to the forest fringe ecotone, humans are exposed to an increased transmission risk when in proximity to these areas, especially when small dams are created on naturally running water collections.