An Epidemic of Sylvatic Yellow Fever in the Southeast Region of Maranhao State, Brazil, 1993–1994: Epidemiologic and Entomologic Findings

Ministério da Saúde. Fundação Nacional de Saúde. Instituto Evandro Chagas. Belém, PA, Brasil.Ministério da Saúde. Fundação Nacional de Saúde. Instituto Evandro Chagas. Belém, PA, Brasil.Ministério da Saúde. Fundação Nacional de Saúde. Instituto Evandro Chagas. Belém, PA, Brasil/ Institut Français de Recherche Scientifique pour le Developpement. Marseille, France.Ministério da Saúde. Fundação Nacional de Saúde. Instituto Evandro Chagas. Belém, PA, Brasil.Ministério da Saúde. Fundação Nacional de Saúde. Instituto Evandro Chagas. Belém, PA, Brasil.Ministério da Saúde. Fundação Nacional de Saúde. Instituto Evandro Chagas. Belém, PA, Brasil.Ministério da Saúde. Fundação Nacional de Saúde. Instituto Evandro Chagas. Belém, PA, Brasil / Institut Français de Recherche Scientifique pour le Developpement. Marseille, France.Ministério da Saúde. Fundação Nacional de Saúde. Instituto Evandro Chagas. Belém, PA, BrasilMinistério da Saúde. Fundação Nacional de Saúde. Instituto Evandro Chagas. Belém, PA, Brasil.Yellow fever virus transmission was very active in Maranhao State in Brazil in 1993 and 1994. An investigation was carried out to evaluate the magnitude of the epidemic. In 1993, a total of 932 people was examined for yellow fever from Maranhao: 70 were positive serologically, histopathologically, and/or by virus isolation, and another four cases were diagnosed clinically and epidemiologically. In Mirador (17,565 inhabitants), the incidence was 3.5 per 1,000 people (case fatality rate [number of deaths/number of cases diagnosed] = 16.4 percent), while in a rural yellow fever risk area (14,659 inhabitants), the incidence was 4.2 and the case-fatality rate was 16.1 percent (10 of 62). A total of 45.2 percent (28 of 62) asymptomatic infections were registered. In 1994, 49 serum samples were obtained and 16 cases were confirmed (two by virus isolation, two by seroconversion, and 12 by serology). No fatal cases were reported. In 1993, 936 potential yellow fever vectors were captured in Mirador and a single strain was isolated from a pool of Haemagogus janthinomys (infection rate = 0.16 percent). In 1994, 16 strains were isolated from 1,318 Hg. janthinomys (infection rate = 1.34 percent) and one Sabethes chloropterus (infection rate = 1.67 percent). Our results suggest that this was the most extensive outbreak of yellow fever in the last 20 years in Brazil. It is also clear that the lack of vaccination was the principal reason for the epidemic, which occurred between April and June, during the rainy season, a period in which the mosquito population in the forest increases

Climate change and the emergence of vector-borne diseases in Europe: Case study of dengue fever

Background: Dengue fever is the most prevalent mosquito-borne viral disease worldwide. Dengue transmission is critically dependent on climatic factors and there is much concern as to whether climate change would spread the disease to areas currently unaffected. The occurrence of autochthonous infections in Croatia and France in 2010 has raised concerns about a potential re-emergence of dengue in Europe. The objective of this study is to estimate dengue risk in Europe under climate change scenarios. Methods. We used a Generalized Additive Model (GAM) to estimate dengue fever risk as a function of climatic variables (maximum temperature, minimum temperature, precipitation, humidity) and socioeconomic factors (population density, urbanisation, GDP per capita and population size), under contemporary conditions (1985-2007) in Mexico. We then used our model estimates to project dengue incidence under baseline conditions (1961-1990) and three climate change scenarios: short-term 2011-2040, medium-term 2041-2070 and long-term 2071-2100 across Europe. The model was used to calculate average number of yearly dengue cases at a spatial resolution of 10 × 10 km grid covering all land surface of the currently 27 EU member states. To our knowledge, this is the first attempt to model dengue fever risk in Europe in terms of disease occurrence rather than mosquito presence. Results: The results were presented using Geographical Information System (GIS) and allowed identification of areas at high risk. Dengue fever hot spots were clustered around the coastal areas of the Mediterranean and Adriatic seas and the Po Valley in northern Italy. Conclusions: This risk assessment study is likely to be a valuable tool assisting effective and targeted adaptation responses to reduce the likely increased burden of dengue fever in a warmer world

Climate-Based Models for Understanding and Forecasting Dengue Epidemics

Dengue fever is a major public health problem in the tropics and subtropics. Since no vaccine exists, understanding and predicting outbreaks remain of crucial interest. Climate influences the mosquito-vector biology and the viral transmission cycle. Its impact on dengue dynamics is of growing interest. We analyzed the epidemiology of dengue in Noumea (New Caledonia) from 1971 to 2010 and its relationships with local and remote climate conditions using an original approach combining a comparison of epidemic and non epidemic years, bivariate and multivariate analyses. We found that the occurrence of outbreaks in Noumea was strongly influenced by climate during the last forty years. Efficient models were developed to estimate the yearly risk of outbreak as a function of two meteorological variables that were contemporaneous (explicative model) or prior (predictive model) to the outbreak onset. Local threshold values of maximal temperature and relative humidity were identified. Our results provide new insights to understand the link between climate and dengue outbreaks, and have a substantial impact on dengue management in New Caledonia since the health authorities have integrated these models into their decision making process and vector control policies. This raises the possibility to provide similar early warning systems in other countries

Complex Processes from Dynamical Architectures with Time-Scale Hierarchy

The idea that complex motor, perceptual, and cognitive behaviors are composed of smaller units, which are somehow brought into a meaningful relation, permeates the biological and life sciences. However, no principled framework defining the constituent elementary processes has been developed to this date. Consequently, functional configurations (or architectures) relating elementary processes and external influences are mostly piecemeal formulations suitable to particular instances only. Here, we develop a general dynamical framework for distinct functional architectures characterized by the time-scale separation of their constituents and evaluate their efficiency. Thereto, we build on the (phase) flow of a system, which prescribes the temporal evolution of its state variables. The phase flow topology allows for the unambiguous classification of qualitatively distinct processes, which we consider to represent the functional units or modes within the dynamical architecture. Using the example of a composite movement we illustrate how different architectures can be characterized by their degree of time scale separation between the internal elements of the architecture (i.e. the functional modes) and external interventions. We reveal a tradeoff of the interactions between internal and external influences, which offers a theoretical justification for the efficient composition of complex processes out of non-trivial elementary processes or functional modes