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Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil.

ABSTRACT: Dengue is a re-emerging disease, currently considered the most important mosquito-borne arbovirus infection affecting humankind, taking into account both its morbidity and mortality. Brazil is considered an endemic country for dengue, such that more than 1,544,987 confirmed cases were notified in 2019, which means an incidence rate of 735 for every 100 thousand inhabitants. Climate is an important factor in the temporal and spatial distribution of vector-borne diseases, such as dengue. Thus, rainfall and temperature are considered macro-factors determinants for dengue, since they directly influence the population density of Aedes aegypti, which is subject to seasonal fluctuations, mainly due to these variables. This study examined the incidence of dengue fever related to the climate influence by using temperature and rainfall variables data obtained from remote sensing via artificial satellites in the metropolitan region of Rio de Janeiro, Brazil. The mathematical model that best fits the data is based on an auto-regressive moving average with exogenous inputs (ARMAX). It reproduced the values of incidence rates in the study period and managed to predict with good precision in a one-year horizon. The approach described in present work may be replicated in cities around the world by the public health managers, to build auxiliary operational tools for control and prevention tasks of dengue, as well of other arbovirus diseases.

SUBMITTER: Xavier LL

PROVIDER: S-EPMC8136695 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Due to the populations' susceptibility, DENV-4 introduction in 2010 led to the occurrence of explosive epidemics in the following years in Brazil. In 2011, DENV-4 was identified in Rio de Janeiro (RJ) and it was prevalent in 2012 and 2013. Here, we aimed to characterize clinical, epidemiological and laboratorial aspects of DENV-4 cases after this serotype introduction in an endemic scenario.Dengue suspected cases (n = 3727) were received and analyzed from January 2011 to December 2013, during outbreaks occurred in RJ, Brazil. Samples were submitted to virological, serological and molecular methods for case confirmation. DENV-4 cases (n = 705) were characterized according to the type of infection, disease severity and, viremia levels and NS1 antigenemia were accessed. Representative strains were partial sequenced for genotyping.DENV-4 was identified in 44.2% (705/1593) of dengue positive cases, virus isolated in 48.7% of the cases. Anti-DENV IgM was detected in 39.4% of the cases, however an increased detection was observed in cases with ?4 days of symptoms (57.0%). NS1 antigen was identified in 41.5% of DENV-4 cases however, after immune complexes dissociation, the detection significantly increased (87.6%). Females were more affected than males, so did children aged 11-15 years old. Primary cases were more frequently observed than secondary ones and most of them were classified as dengue. No differences on NS1 antigenemia and viraemia within the groups were observed. Despite the higher frequency of severe disease on individuals >65 years old, no differences were observed among the groups and type of infection. However, DENV-4 fatal cases were more frequent on secondary infections (57.1%). DENV-4 Genotype II was identified with a probable origin from Venezuela and Colombia.It has been shown that laboratorial diagnosis is still a reliable tool for the disease surveillance, detecting and confirming emerging epidemics. Despite the occurrence of secondary infections, most DENV-4 cases presented a mild disease. As RJ is endemic for dengue, high rates of secondary infections would be expected. Despite the existence of two genotypes, only Genotype II was identified in our study.

Project description: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.

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Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil.

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