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      Space–time dynamics of a triple epidemic: dengue, chikungunya and Zika clusters in the city of Rio de Janeiro

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          Abstract

          Dengue, an arboviral disease transmitted by Aedes mosquitoes, has been endemic in Brazil for decades. However, vector-control strategies have not led to a significant reduction in the disease burden and have not been sufficient to prevent chikungunya and Zika entry and establishment in the country. In Rio de Janeiro city, the first Zika and chikungunya epidemics were detected between 2015 and 2016, coinciding with a dengue epidemic. Understanding the behaviour of these diseases in a triple epidemic scenario is a necessary step for devising better interventions for prevention and outbreak response. We applied scan statistics analysis to detect spatio-temporal clustering for each disease separately and for all three simultaneously. In general, clusters were not detected in the same locations and time periods, possibly owing to competition between viruses for host resources, depletion of susceptible population, different introduction times and change in behaviour of the human population (e.g. intensified vector-control activities in response to increasing cases of a particular arbovirus). Simultaneous clusters of the three diseases usually included neighbourhoods with high population density and low socioeconomic status, particularly in the North region of the city. The use of space–time cluster detection can guide intensive interventions to high-risk locations in a timely manner, to improve clinical diagnosis and management, and pinpoint vector-control measures.

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          Most cited references35

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          Evaluating cluster alarms: a space-time scan statistic and brain cancer in Los Alamos, New Mexico.

          This article presents a space-time scan statistic, useful for evaluating space-time cluster alarms, and illustrates the method on a recent brain cancer cluster alarms in Los Alamos, NM. The space-time scan statistic accounts for the preselection bias and multiple testing inherent in a cluster alarm. Confounders and time trends can be adjusted for. The observed excess of brain cancer in Los Alamos was not statistically significant. The space-time scan statistic is useful as a screening tool for evaluating which cluster alarms merit further investigation and which clusters are probably chance occurrences.
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            Vectorial Capacity of Aedes aegypti: Effects of Temperature and Implications for Global Dengue Epidemic Potential

            Dengue is a mosquito-borne viral disease that occurs mainly in the tropics and subtropics but has a high potential to spread to new areas. Dengue infections are climate sensitive, so it is important to better understand how changing climate factors affect the potential for geographic spread and future dengue epidemics. Vectorial capacity (VC) describes a vector's propensity to transmit dengue taking into account human, virus, and vector interactions. VC is highly temperature dependent, but most dengue models only take mean temperature values into account. Recent evidence shows that diurnal temperature range (DTR) plays an important role in influencing the behavior of the primary dengue vector Aedes aegypti. In this study, we used relative VC to estimate dengue epidemic potential (DEP) based on the temperature and DTR dependence of the parameters of A. aegypti. We found a strong temperature dependence of DEP; it peaked at a mean temperature of 29.3°C when DTR was 0°C and at 20°C when DTR was 20°C. Increasing average temperatures up to 29°C led to an increased DEP, but temperatures above 29°C reduced DEP. In tropical areas where the mean temperatures are close to 29°C, a small DTR increased DEP while a large DTR reduced it. In cold to temperate or extremely hot climates where the mean temperatures are far from 29°C, increasing DTR was associated with increasing DEP. Incorporating these findings using historical and predicted temperature and DTR over a two hundred year period (1901–2099), we found an increasing trend of global DEP in temperate regions. Small increases in DEP were observed over the last 100 years and large increases are expected by the end of this century in temperate Northern Hemisphere regions using climate change projections. These findings illustrate the importance of including DTR when mapping DEP based on VC.
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              Zika, chikungunya and dengue: the causes and threats of new and re-emerging arboviral diseases

              The recent emergence and re-emergence of viral infections transmitted by vectors—Zika, chikungunya, dengue, Japanese encephalitis, West Nile, yellow fever and others—is a cause for international concern. Using as examples Zika, chikungunya and dengue, we summarise current knowledge on characteristics of the viruses and their transmission, clinical features, laboratory diagnosis, burden, history, possible causes of the spread and the expectation for future epidemics. Arboviruses are transmitted by mosquitoes, are of difficult diagnosis, can have surprising clinical complications and cause severe burden. The current situation is complex, because there is no vaccine for Zika and chikungunya and no specific treatment for the three arboviruses. Vector control is the only comprehensive solution available now and this remains a challenge because up to now this has not been very effective. Until we develop new technologies of control mosquito populations, the globalised and urbanised world we live in will remain vulnerable to the threat of successive arbovirus epidemics.
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                Author and article information

                Journal
                Proc Biol Sci
                Proc. Biol. Sci
                RSPB
                royprsb
                Proceedings of the Royal Society B: Biological Sciences
                The Royal Society
                0962-8452
                1471-2954
                9 October 2019
                9 October 2019
                9 October 2019
                : 286
                : 1912
                : 20191867
                Affiliations
                [1 ]Escola Nacional de Saúde Pública Sergio Arouca (ENSP), Oswaldo Cruz Foundation , Rio de Janeiro, Brazil
                [2 ]Programa de Computação Científica (PROCC), Oswaldo Cruz Foundation , Rio de Janeiro, Brazil
                [3 ]Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine , London, UK
                [4 ]Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine , London, UK
                [5 ]Barcelona Institute for Global Health (ISGlobal) , Barcelona, Spain
                Author notes

                Electronic supplementary material is available online at https://doi.org/10.6084/m9.figshare.c.4673105.

                Author information
                http://orcid.org/0000-0001-9012-9382
                http://orcid.org/0000-0002-3289-3195
                http://orcid.org/0000-0003-3939-7343
                http://orcid.org/0000-0002-9566-0284
                Article
                rspb20191867
                10.1098/rspb.2019.1867
                6790786
                31594497
                fc75da5f-551e-41a9-92e0-fa2230050691
                © 2019 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : 9 August 2019
                : 13 September 2019
                Funding
                Funded by: Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, http://dx.doi.org/10.13039/501100004586;
                Award ID: E_26/201.356/2014
                Funded by: Conselho Nacional de Desenvolvimento Científico e Tecnológico, http://dx.doi.org/10.13039/501100003593;
                Award ID: 304101/2017-6
                Funded by: Royal Society, http://dx.doi.org/10.13039/501100000288;
                Award ID: Dorothy Hodgkin Fellowship
                Funded by: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, http://dx.doi.org/10.13039/501100002322;
                Award ID: Finance code 001
                Categories
                1001
                87
                Ecology
                Research Article
                Custom metadata
                October 9, 2019

                Life sciences
                dengue,zika,chikungunya,cluster analysis,spatio-temporal analysis
                Life sciences
                dengue, zika, chikungunya, cluster analysis, spatio-temporal analysis

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