Carvalho, M. S. | bioRxiv Science

bioRxiv2019

Rainfall and other meteorological factors as drivers of urban transmission of leptospirosis

BackgroundLeptospirosis is an important public health problem affecting vulnerable urban slum populations in developing country settings. However, the complex interaction of meteorological factors driving the temporal trends of leptospirosis remain incompletely understood.\n\nMethods and findingsFrom 1996 to 2010, we investigated the association between the weekly incidence of leptospirosis and climatic variables in the city of Salvador, Brazil by using a dynamic generalized linear model that accounted for time lags, overall trend and seasonal variation. Our model showed an increase of leptospirosis cases associated with rainfall, lower temperature and higher humidity. There was a lag of one-to-two weeks between weekly values for significant meteorological variables and leptospirosis incidence. Independent of the season, a weekly cumulative rainfall of 20 mm increased the risk of the leptospirosis by 10% compared to a week without rain. Finally, over the 14 year study period the incidence of leptospirosis decreased significantly by four fold (12.8 versus 3.6 per 100,000 people), independently of variations in climate.\n\nConclusionsStrategies to control leptospirosis should focus on avoiding contact with contaminated sources of Leptospira as well as on increasing awareness in the population and health professionals within the short time window after both low-level and extreme rainfall events. Increased leptospirosis incidence was restricted to one-to-two weeks after those events suggesting that infectious Leptospira survival may be limited to short time intervals.\n\nAuthor SummaryTo determine the role of meteorological variables, seasonal variation and temporal trends in the incidence of leptospirosis, we investigated the time series of leptospirosis incidence amongst residents of Salvador, Brazil, from 1996 to 2010. Exploratory and confirmatory statistical methods detected associations between meteorological factors and disease incidence. Results showed the importance of extreme meteorological conditions, particularly rainfall, as short-term predictors of leptospirosis incidence. In addition, we found a long-term decreasing trend of in disease incidence over the observation period.

epidemiology↗

bioRxiv2019

Space-time clusters of dengue, chikungunya, and Zika cases in the city of Rio de Janeiro

Brazil is a dengue-endemic country where all four dengue virus serotypes circulate and cause seasonal epidemics. Recently, chikungunya and Zika viruses were also introduced. In Rio de Janeiro city, the three diseases co-circulated for the first time in 2015-2016, resulting in what is known as the triple epidemic. In this study, we identify space-time clusters of dengue, chikungunya, and Zika, to understand the dynamics and interaction between these simultaneously circulating arboviruses in a densely populated and heterogeneous city.\n\nWe conducted a spatio-temporal analysis of weekly notified cases of the three diseases in Rio de Janeiro city (July 2015 - January 2017), georeferenced by 160 neighbourhoods, using Kulldorffs scan statistic with discrete Poisson probability models.\n\nThere were 26549, 13662, and 35905 notified cases of dengue, chikungunya, and Zika, respectively. The 17 dengue clusters and 15 Zika clusters were spread all over the city, while the 14 chikungunya clusters were more concentrated in the North and Downtown areas. Zika clusters persisted over a longer period of time. The multivariate scan statistic - used to analyse the three diseases simultaneously - detected 17 clusters, nine of which included all three diseases.\n\nThis is the first study exploring space-time clustering of dengue, chikungunya, and Zika in an intraurban area. In general, the clusters did not coincide in time and space. This is probably the result of the competition between viruses for host resources, and of vector-control attitudes promoted by previous arbovirus outbreaks. The main affected area - the North region - is characterised by a combination of high population density and low human development index, highlighting the importance of targeting interventions in this area. Spatio-temporal scan statistics have the potential to direct interventions to high-risk locations in a timely manner and should be considered as part of the municipal surveillance routine as a tool to optimize prevention strategies.\n\nAuthor summaryDengue, an arboviral disease transmitted by Aedes mosquitoes, has been endemic in Brazil for decades, but vector-control strategies have not led to a significant reduction in the disease burden and were not 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 2015-2016, 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 due to competition between viruses for host resources, and change in behaviour of the human population (e.g. intensified vector-control activities in response to increasing cases of a particular arbovirus). Neighbourhoods with high population density and social vulnerability should be considered as important targets for interventions. Particularly in the North region, where clusters of the three diseases exist and the first chikungunya cluster occurred. The use of space-time cluster detection can direct intensive interventions to high-risk locations in a timely manner.

epidemiology↗