O desenvolvimento de uma vacina para o controle da dengue é uma prioridade em todo o mundo. O domínio helicase da proteína NS3 (NS3H) viral alberga epítopos reconhecidos por linfócitos T citotóxicos, os quais tem papel importante na eliminação de células infectadas. Esse trabalho propôs a obtenção de uma forma recombinante, produzida em linhagens de Escherichia coli, da NS3H do DENV2 com características similares à proteína nativa e sua utilização como um potencial antígeno vacinal. A NS3H foi obtida na forma solúvel, foi reconhecida por anticorpos de camundongos e de humanos infectados e foi capaz de interagir com o RNA viral. Camundongos imunizados com NS3H coadministrada com diferentes adjuvantes desenvolveram respostas imunológicas específicas mas não foram protegidos após desafio. Em conjunto, os resultados indicam que a proteína NS3H recombinante preserva conformação e determinantes antigênicos da proteína viral nativa e pode ser útil em estudos sobre a biologia viral e na busca de estratégias anti-virais voltadas para o controle da dengue. / The development of a dengue vaccine is a worldwide priority. The helicase domain of viral NS3 protein (NS3H) preserves epitopes recognized by cytotoxic T lymphocytes, which plays an important role in the elimination of infected cells. This study aimed the generation of a recombinant NS3H form of a type 2 dengue virus (DENV2) lineage, in Escherichia coli strains, with properties similar to the native protein and its use as a potential vaccine antigen. The NS3H was obtained in soluble form, was recognized by antibodies from mice and human subjects and was able to interact with the viral RNA. Mice immunized with NS3H combined with different adjuvants developed specific immune responses but did not confer protection to a lethal challenge. Altogether, the results indicate that the recombinant NS3H protein preserves conformational and antigenic determinants of the native protein and may be a useful tool for studies dealing with the DENV biology and the search for anti-virus approaches.

Neste estudo, baseado na análise de séries temporais para um período de 8 anos, correlacionou-se os casos de dengue com as variáveis climáticas das cidades da Baixada Santista (sudeste brasileiro) e de Cingapura (sudeste asiático). O estudo foi feito com o uso de um modelo de regressão de Poisson (MRP), que considera os casos de dengue como a variável dependente e as variáveis climáticas: precipitação, temperatura (máxima e mínima) e umidade relativa (máxima e mínima) como as variáveis independentes. Também foi utilizada a Análise de Componentes Principais (ACP) para escolher as variáveis que influenciam no aumento do número de casos de dengue nas cidades estudadas. A CP1 (componente principal 1) foi representada pelas temperaturas (máxima e mínima) e a precipitação e a CP2 (componente principal 2) pela umidade relativa (máxima e mínima). Calculou-se o acréscimo dos novos casos de dengue e o risco relativo de ocorrência da doença por influência de cada uma das variáveis climáticas. Na Baixada Santista, os maiores valores de precipitação e temperatura ocorrem nos meses de dezembro e janeiro (verão) e o aumento dos casos de dengue ocorre nos meses de março a maio (outono). Para Cingapura, a diminuição da precipitação e o aumento da temperatura ocorrem nos meses de março a maio (pré-monção de sudoeste), e, portanto, observa-se o aumento dos casos de dengue nos meses de junho a outubro (monção de sudoeste). Os resultados foram: em Cingapura, para 2oC a 10oC de variação na temperatura (máxima e mínima), houve um aumento médio dos casos de dengue de 22,2% a 184,6% (máxima) e de 26,1% a 230,3% (mínima). O risco relativo médio foi de 1,2% a 2,9% e de 1,3% a 3,3%, respectivamente. Para precipitação, a variação de 5mm a 55mm, houve o aumento dos casos de dengue de 5,6% a 83,2%, sendo e o risco relativo médio foi de 1,06% a 1,83%. A umidade relativa após a análise de correlação foi descartada no uso do modelo de regressão de Poisson por apresentar uma correlação muito baixa. Para a Baixada Santista, a variação da temperatura de 2oC a 10oC apresentou um acréscimo médio nos casos de dengue de 19,6% a 154,4% (máxima) e de 18,2% a 145,4% (mínima). O risco relativo médio foi de 1,20% a 2,54% e de 1,18% a 2,45%, respectivamente. A variação da precipitação de 5mm a 55mm apresentou um aumento dos casos de dengue de 3,92% a 53,10%. A umidade relativa mínima variando de 2% a 10%, o acréscimo dos casos de dengue foi 7,7% a 49,4%, sendo que o risco relativo foi de 1,08% a 1,49%. Assim, após várias análises, a temperatura mínima foi um dos preditores para ocorrência do aumento dos casos de dengue em Cingapura, sendo que há uma influência bem particular da precipitação, na qual, atua significativamente no período seco (pré-monção de sudoeste). Enquanto que na Baixada Santista as influências mais significativas foram da temperatura (máxima e mínima) e precipitação, que desenvolvem conjuntamente um bom cenário de atuação do vetor no período do outono / In this study, based on time series analysis for a period of eight years, correlated dengue cases with climatic variables in the cities of Santos (southeastern Brazil) and Singapore (Southeast Asia). The study was done using a Poisson regression model (PRM), which considers the cases of dengue as the dependent variable and climatic variables: precipitation, temperature (maximum and minimum) and relative humidity (maximum and minimum) as the independent variables. Also we used the Principal Component Analysis (PCA) to select the variables that influence the increase in the number of dengue cases in the cities studied. The PC1 (principal component 1) was represented by the temperatures (maximum and minimum) and precipitation and the PC2 (principal component 2) the relative humidity (maximum and minimum). We calculated the addition of new dengue cases and relative risk of disease influenced by each variable climate. In Baixada Santista, the highest values of precipitation and temperature occur in the months of December and January (summer) and the increase in dengue cases occur in the months from March to May (autumn). For Singapore, the decrease in precipitation and temperature increase occurring in the months March to May (southwest inter-monsoon) and hence there is an increase of dengue cases in the months from June to October (southwest monsoon). The results were in Singapore for 2oC to 10oC change in temperature (maximum and minimum), there was an average increase of dengue cases from 22.2% to 184.6% (maximum) and 26.1% at 230 3% (minimum). The average relative risk was 1.2% to 2.9% and 1.3% to 3.3%, respectively. For precipitation, the range of 5mm to 55mm, there was an increase of dengue cases from 5.6% to 83.2%, with and average relative risk was 1.06% to 1.83%. The relative humidity after the correlation analysis was discarded in the use of Poisson regression model for presenting a very low correlation. For Baixada Santista, the variation of temperature of 2oC to 10oC showed an average increase in the dengue cases from 19.6% to 154.4% (maximum) and 18.2% to 145.4% (minimum). The average relative risk is 1.20% to 2.54% and 1.18% to 2.45%, respectively. The variation in the precipitation of 5mm to 55mm showed an increase in dengue cases from 3.92% to 53.10%. The minimum relative humidity ranging from 2% to 10%, the increase of dengue cases was 7.7% to 49.4%, and the relative risk was 1.08% to 1.49%. Thus, after several analyzes, the minimum temperature was one of the predictors for the occurrence of the increase of dengue cases in Singapore, and there is a very particular influence of the precipitation, in which it acts significantly in the dry season (southwest inter-monsoon). While in Baixada Santista were the most significant influences of temperature (maximum and minimum) and precipitation, which jointly develop a good field of action of the vector in the autumn

Made available in DSpace on 2016-08-10T10:53:41Z (GMT). No. of bitstreams: 1 ADRIANE FEITOSA VALADARES.pdf: 954155 bytes, checksum: a974324b3ec7a29cee64b580f03ab47f (MD5) Previous issue date: 2012-11-27 / Dengue is a growing public health issue worldwide. As a result of their environmental, climatic and social characteristics, tropical countries are those most affected. The objectives of the present study conducted in the state of Tocantins, Brazil, were: to identify the demographic characteristics of notified and confirmed cases of dengue; to calculate the incidence rate of confirmed cases of dengue; to investigate the correlation between confirmed cases and the number of hospitalizations for this disease; to correlate the number of hospitalizations and the number of severe cases; to describe the circulating serotypes identified; to investigate the correlation between the house infestation index and the incidence rate of dengue; and to investigate the correlation between environmental factors such as mean annual temperature and mean rainfall with the annual incidence rate of dengue. This was an ecological, longitudinal study conducted by evaluating secondary data for the 2000- 2010 period obtained from the Brazilian Ministry of Health s notifiable diseases database, the yellow fever and dengue database, the localities database, the hospital admissions database and from the dengue and yellow fever management unit of the Tocantins State Health Department. The mean temperatures in degrees Celsius and the mean rainfall in millimeters were supplied by the National Meteorology Institute. The data on viral isolation and serotyping were obtained from the Tocantins Central Public Health Laboratory. The inclusion criterion adopted in this study consisted of municipalities in the state of Tocantins with populations of more than 100,000 inhabitants in this case, Palmas and Araguaína. A total of 48,246 suspected cases of dengue were notified during the period and 23,614 (49%) were confirmed. Of these, 118 (0.5%) were classified as severe cases and 7 deaths occurred (5.9%). The highest prevalence of the disease occurred in females (52.9%), in individuals of 20-39 years of age (46.5%), in those living in urban areas (97.6%) and in brown-skinned individuals (51.5%). There was a statistically significant difference (p<0.05) between the variables evaluated. The highest incidence of dengue occurred in 2007; however, the greatest number of severe cases registered was in 2008, although no deaths were recorded. Of the hospitalized patients, 13% were classified as severe cases. There was a positive and significant correlation between the number of confirmed cases and the number of hospitalizations (r = 0.77; p < 0.05), as well as between hospitalizations and severe cases (r = 0.79; p < 0.05). The serotypes isolated were DENV 1, DENV 2 and DENV 3. There was a positive, albeit non-significant, correlation between the house infestation index and the incidence of the disease (r = 0.59; p > 0.05). With respect to the abiotic factors, no correlation was found between mean rainfall or mean annual temperature and the incidence rate. In conclusion, the highest incidence of dengue occurred in 2007 and the greatest number of severe cases occurred in 2008, albeit with no deaths. These findings indicate that dengue affects predominantly females, individuals of 20-39 years of age, brown-skinned individuals and those residing in urban areas. The correlation between confirmed cases and hospitalizations was significant, as was the correlation between hospitalizations and severe cases of dengue. The serotypes identified were DENV 1, DENV 2 and DENV 3. More than one serotype was circulating simultaneously. The correlations between mean rainfall and the incidence rate and between mean temperature and the incidence rate were not statistically significant. / A dengue é um problema crescente de saúde pública mundial. Os países tropicais são os mais atingidos em razão de suas características ambientais, climáticas e sociais. Os objetivos deste estudo foram: Identificar as características demográficas dos casos notificados e confirmados da dengue; Calcular o coeficiente de incidência dos casos confirmados da dengue; Investigar a associação entre os casos confirmados da dengue e o número de internações por este agravo, assim como correlacionar o número de internações por dengue e o número de casos graves; descrever os sorotipos circulantes identificados; investigar a associação entre o índice de infestação predial e o coeficiente de incidência da dengue; investigar a associação entre os fatores ambientais como temperatura anual média e precipitação pluviométrica média com o coeficiente de incidência anual da dengue. Tratase de um estudo ecológico e longitudinal com a utilização de dados secundários referentes ao período de 2000 a 2010, obtidos do Sistema de Informação de Agravos de Notificação; Sistema de Informação de Febre Amarela e Dengue, Sistema de Informação de Localidades. Sistema de Informação Hospitalar e da Gerência do Núcleo de Dengue e Febre Amarela da Secretaria de Estado da Saúde do Tocantins. As médias de temperatura em graus Celsius e de precipitação pluviométrica em milímetros foram fornecidas pelo Instituto Nacional de Meteorologia. Os dados referentes ao isolamento viral e sorotipagem foram obtidos no Laboratório Central de Saúde Pública do Tocantins. Foi adotado como critério de inclusão municípios com população acima de 100.000 habitantes, neste caso, Palmas e Araguaína. Foram notificadas 48.246 suspeitos de dengue, sendo confirmadas 23.614 (49%), destes 118 (0,5%) foram classificados como casos graves de dengue, e 07 óbitos (5,9%). A maior prevalência da doença ocorreu entre pessoas do sexo feminino (52,9%), na faixa etária de 20 a 39 anos (46,5%), que viviam na zona urbana (97,6%) e da raça parda (51,5%). Houve diferença significativa (p<0,05) entre as variáveis estudadas. A maior incidência da dengue ocorreu em 2007, porém, o maior registro de casos graves foi em 2008, sem registro de óbitos. Dos pacientes internados, 13% foram classificados como caso grave. Houve associação positiva e significativa entre os casos confirmados e número de internações (r=0,77 p<0,05), bem como entre as internações e casos graves (r=0,79 p<0,05). Os sorotipos isolados foram DENV 1, DENV 2 e DENV 3. Houve associação positiva, porém, não significativa entre o índice de infestação predial e a incidência da doença (r= 0,59 p>0,05). Em relação aos fatores abióticos não houve associação significativa entre a precipitação pluviométrica média e o coeficiente de incidência, assim como em entre a temperatura anual média e o coeficiente de incidência. Conclusão: A maior incidência de dengue ocorreu em 2007 e o maior número de casos graves em 2008, sem ocorrência de óbito. Conclui-se que a dengue acomete predominantemente pessoas do sexo feminino, com idade entre 20 39 anos, raça parda, e que residem na zona urbana. A associação foi significativa entre os casos confirmados e internações, assim como, entre internações e casos graves. Os sorotipos virais identificados foram DENV 1, DENV 2 e DENV 3. Ocorreu circulação simultânea de mais de um sorotipo. A associação não foi significativa entre a precipitação pluviométrica média e o coeficiente de incidência, assim como entre temperatura e o coeficiente de incidência

A dengue é uma doença que afeta milhões de pessoas e possui um número significativo de mortes. Não há nenhum tratamento vacinal legalizado para uso. As estratégias vacinais contra a dengue baseadas em proteínas não estruturais têm demonstrado serem mais seguras do que as baseadas em proteínas estruturais. A proteína não estrutural 5 (NS5) do vírus dengue é a proteína mais conservada entre os quatro sorotipos e desempenha um papel crucial na replicação viral. Neste estudo, foi gerada uma forma recombinante da NS5 expressa em E. coli com propriedades antigênicas preservados. As condições de cultura foram optimizadas, o que permitiu a expressão dessa proteína na forma solúvel. A imunização de camundongos Balb/c com a NS5 sozinha ou em combinação com um adjuvante (poli (I:C)) promoveu o aumento da sobrevida de camundongos após desafio letal com DENV2. A combinação da NS5 com poli (I:C) emulsionado em Montanide 720 levou a expansão de linfócitos T CD8+ específicos. Os resultados indicam que a proteína NS5 obtida preserva determinantes antigênicos da proteína nativa e pode ser uma ferramenta útil para estudos sobre a biologia do DENV, busca de drogas antivirais e desenvolvimento de vacinas. / Dengue fever is a disease affecting millions of people worldwide and causing a significant number of deaths. There are no effective treatments or vaccine approaches capable of preventing such infection. Anti-DENV vaccine strategies based on nonstructural proteins as antigens have been shown to be safer than those based on structural proteins. The DENV nonstructural protein 5 (NS5), plays a crucial role in viral replication. In this study, we generated a recombinant form of DENV2 NS5 expressed in E. coli in high amounts and with preserved antigenic properties with regard to the native protein. Culture conditions were optimized in order to allow expression of NS5 as a soluble protein. The immunization of Balb/c mice using this protein alone or in combination with poly (I:C) led to increased survival after intracranial challenge with the DENV2 JHA1 strain. The combination of the protein with poly (I:C) emulsified in Montanide 720 led to the activation of NS5-specific CD8+ T lymphocytes. Altogether, the results indicate that the recombinant NS5 protein preserves antigenic determinants of the native protein and may be a useful tool for studies dealing with the DENV\'s biology, search for anti-viral drugs and vaccine development.

Neste estudo, baseado na análise de séries temporais para um período de 8 anos, correlacionou-se os casos de dengue com as variáveis climáticas das cidades da Baixada Santista (sudeste brasileiro) e de Cingapura (sudeste asiático). O estudo foi feito com o uso de um modelo de regressão de Poisson (MRP), que considera os casos de dengue como a variável dependente e as variáveis climáticas: precipitação, temperatura (máxima e mínima) e umidade relativa (máxima e mínima) como as variáveis independentes. Também foi utilizada a Análise de Componentes Principais (ACP) para escolher as variáveis que influenciam no aumento do número de casos de dengue nas cidades estudadas. A CP1 (componente principal 1) foi representada pelas temperaturas (máxima e mínima) e a precipitação e a CP2 (componente principal 2) pela umidade relativa (máxima e mínima). Calculou-se o acréscimo dos novos casos de dengue e o risco relativo de ocorrência da doença por influência de cada uma das variáveis climáticas. Na Baixada Santista, os maiores valores de precipitação e temperatura ocorrem nos meses de dezembro e janeiro (verão) e o aumento dos casos de dengue ocorre nos meses de março a maio (outono). Para Cingapura, a diminuição da precipitação e o aumento da temperatura ocorrem nos meses de março a maio (pré-monção de sudoeste), e, portanto, observa-se o aumento dos casos de dengue nos meses de junho a outubro (monção de sudoeste). Os resultados foram: em Cingapura, para 2oC a 10oC de variação na temperatura (máxima e mínima), houve um aumento médio dos casos de dengue de 22,2% a 184,6% (máxima) e de 26,1% a 230,3% (mínima). O risco relativo médio foi de 1,2% a 2,9% e de 1,3% a 3,3%, respectivamente. Para precipitação, a variação de 5mm a 55mm, houve o aumento dos casos de dengue de 5,6% a 83,2%, sendo e o risco relativo médio foi de 1,06% a 1,83%. A umidade relativa após a análise de correlação foi descartada no uso do modelo de regressão de Poisson por apresentar uma correlação muito baixa. Para a Baixada Santista, a variação da temperatura de 2oC a 10oC apresentou um acréscimo médio nos casos de dengue de 19,6% a 154,4% (máxima) e de 18,2% a 145,4% (mínima). O risco relativo médio foi de 1,20% a 2,54% e de 1,18% a 2,45%, respectivamente. A variação da precipitação de 5mm a 55mm apresentou um aumento dos casos de dengue de 3,92% a 53,10%. A umidade relativa mínima variando de 2% a 10%, o acréscimo dos casos de dengue foi 7,7% a 49,4%, sendo que o risco relativo foi de 1,08% a 1,49%. Assim, após várias análises, a temperatura mínima foi um dos preditores para ocorrência do aumento dos casos de dengue em Cingapura, sendo que há uma influência bem particular da precipitação, na qual, atua significativamente no período seco (pré-monção de sudoeste). Enquanto que na Baixada Santista as influências mais significativas foram da temperatura (máxima e mínima) e precipitação, que desenvolvem conjuntamente um bom cenário de atuação do vetor no período do outono / In this study, based on time series analysis for a period of eight years, correlated dengue cases with climatic variables in the cities of Santos (southeastern Brazil) and Singapore (Southeast Asia). The study was done using a Poisson regression model (PRM), which considers the cases of dengue as the dependent variable and climatic variables: precipitation, temperature (maximum and minimum) and relative humidity (maximum and minimum) as the independent variables. Also we used the Principal Component Analysis (PCA) to select the variables that influence the increase in the number of dengue cases in the cities studied. The PC1 (principal component 1) was represented by the temperatures (maximum and minimum) and precipitation and the PC2 (principal component 2) the relative humidity (maximum and minimum). We calculated the addition of new dengue cases and relative risk of disease influenced by each variable climate. In Baixada Santista, the highest values of precipitation and temperature occur in the months of December and January (summer) and the increase in dengue cases occur in the months from March to May (autumn). For Singapore, the decrease in precipitation and temperature increase occurring in the months March to May (southwest inter-monsoon) and hence there is an increase of dengue cases in the months from June to October (southwest monsoon). The results were in Singapore for 2oC to 10oC change in temperature (maximum and minimum), there was an average increase of dengue cases from 22.2% to 184.6% (maximum) and 26.1% at 230 3% (minimum). The average relative risk was 1.2% to 2.9% and 1.3% to 3.3%, respectively. For precipitation, the range of 5mm to 55mm, there was an increase of dengue cases from 5.6% to 83.2%, with and average relative risk was 1.06% to 1.83%. The relative humidity after the correlation analysis was discarded in the use of Poisson regression model for presenting a very low correlation. For Baixada Santista, the variation of temperature of 2oC to 10oC showed an average increase in the dengue cases from 19.6% to 154.4% (maximum) and 18.2% to 145.4% (minimum). The average relative risk is 1.20% to 2.54% and 1.18% to 2.45%, respectively. The variation in the precipitation of 5mm to 55mm showed an increase in dengue cases from 3.92% to 53.10%. The minimum relative humidity ranging from 2% to 10%, the increase of dengue cases was 7.7% to 49.4%, and the relative risk was 1.08% to 1.49%. Thus, after several analyzes, the minimum temperature was one of the predictors for the occurrence of the increase of dengue cases in Singapore, and there is a very particular influence of the precipitation, in which it acts significantly in the dry season (southwest inter-monsoon). While in Baixada Santista were the most significant influences of temperature (maximum and minimum) and precipitation, which jointly develop a good field of action of the vector in the autumn

<p>Since Dengue fever (DF) and its related forms, Dengue Hemorrhagic fever (DHF) and Dengue Shock Syndrome (DSS) have become important health concerns worldwide, it is also imperative to develop methods which will help in the analysis of the incidences. Dengue fever cases are growing in number as it also invades widely, affecting larger number of countries and crossing climatic boundaries. Considering that the disease as of now has neither an effective vaccine nor a cure, monitoring in order to prevent or control is the resorted alternative. GIS and its related technologies offer a wealth of interesting capabilities towards achieving this goal.</p><p><strong> </strong></p><p>The intention of this study was to develop methods to describe dengue fever outbreaks taking Rio de Janeiro, Brazil as a case study. Careful study of Census data with appropriate attributes was made to find out their potential influence on dengue fever incidence in the various regions or census districts. Dengue incidence data from year 2000 to year 2008 reported by the municipal secretariat of Rio was used to extract the necessary census districts. Base map files in MapInfo format were converted to shape files.  Using ArcGIS it was possible to merge the dengue fever incidence data with the available base map file of the City of Rio according to corresponding census districts. Choropleth maps were then created using different attributes from which patterns and trends could be used to describe the characteristic of the outbreak with respect to the socio-economic conditions. Incidence data were also plotted in Excel to see temporal variations. Cluster analysis were performed with the Moran I technique on critical periods and years of dengue outbreak. Using the square root of dengue incidence from January to April 2002 and 2008, inverse distance was selected as the conceptualised spatial relationship, Euclidean distance as the distance method. More detailed analyses were then done on the selected critical years of dengue outbreak, (years 2002 and 2008), to investigate the influence of socio-economic variables on dengue incidence per census district.</p><p> </p><p>Dengue incidence rate appeared to be higher during the rainy and warmer months between December and May. Outbreaks of dengue occurred in years 2002 and 2008 over the study period of year 2000 to 2008. Some factors included in the census data were influential in the dengue prevalence according to districts. Satisfactory results can be achieved by using this strategy as a quick method for assessing potential dengue attack, spread and possible enabling conditions. The method has the advantage where there is limited access to field work, less financial means for acquisition of data and other vital resources.</p><p>A number of difficulties were encountered during the study however and leaves areas where further work can be done for improvements. More variables would be required in order to make a complete and comprehensive description of influential conditions and factors.  There is still a gap in the analytical tools required for multi-dimensional investigations as the ones encountered in this study.  It is vital to integrate ‘GPS’ and ‘Remote Sensing’ in order to obtain a variety of up-to-date data with higher resolution.</p><p> </p>

This thesis undertakes analysis of members of the neighborhood anti-mosquito volunteer team which was co-established by the Kaohsiung City Gushan District Office and the Department of Health and finds members of the team have, for the most part, not sufficiently encouraged others to join or participate in dengue fever vector mosquito prevention. In addition, these team members lack proper concepts concerning individual prevention of dengue fever carrying mosquitoes. This study therefore advises anti-mosquito volunteers that anti-mosquito teams must emphasize education concerning environmental behavior, as well as increase public awareness of vector mosquito prevention and measures for individual prevention. In order to make dengue fever vector prevention more effective, it is necessary to start with environmental behavior. In addition to advocating for proper environmental behavior, education and information dissemination concerning environmental behavior must be strengthened so as to increase the effectiveness of the anti-mosquito volunteer workers in dengue fever vector prevention and allow them to attain better results. The possibility of a dengue fever epidemic is an annual threat to the health of the citizens in Southern Taiwan¡¦s Kaohsiung City. The most important tasks in creating a new precedent with respect to mosquito control are to determine how to utilize community and neighborhood anti-mosquito volunteer team resources, to increase efforts to instruct neighborhood citizens to rid their home environments of objects which can retain water, to rid communities of breading sites, to improve environmental sanitary conditions, and to continue advocating neighborhood environmental health works in order to lower vector density for dengue fever and reach the goal of having cleaner and healthier home environments. Needless to say, this type of policy requires the selfless contributions and enthusiastic participation of the community¡¦s citizens. With this in mind, we must ask whether assistance the government provides in can facilitate the effectiveness of anti-mosquito volunteer teams. In addition, we should inquire into what impressions anti-mosquito volunteers have concerning dengue fever vector prevention. This thesis examines the extent to which anti-mosquito volunteer team members¡¦ cognition of environmental literacy influences the effectiveness of dengue fever vector prevention through an analysis which examines the interaction between anti-mosquito volunteer team attributes, members¡¦ environmental literacy, and dengue fever vector prevention results. This study uses the questionnaire survey method and various statistics in compiling data and utilizes various statistical techniques to understand the relationship between these factors, find a clear policy direction, and make this work less arduous and more productive.

West Nile virus affected nearly 2,000 people in Texas in 2012, killing 89. Neither state and local public health institutions nor the medical community were well prepared for the unprecedented outbreak. The virus is carried by mosquitoes and can cause paralysis and other neurological damage. Other diseases carried by insect vectors, like dengue fever, are poised to resurge or emerge in Texas. Suspected effects of climate change, like warmer winters, may contribute to the prevalence of such diseases and frequency of outbreaks. Adequate surveillance of human cases of these diseases is crucial to the public health response, but is hampered by a low level of diagnosis and reporting throughout the state and spotty vector surveillance by local entities. / text

Background: Dengue is a viral infectious disease that is transmitted by mosquitoes. The disease causes a significant health burden in tropical countries, and has been a public health burden in Singapore for several decades. Severe complications such as hemorrhage can develop and lead to fatal outcomes. Before tetravalent vaccine and drugs are available, vector control is the key component to control dengue transmission. Vector control activities need to be guided by surveillance of outbreak and implement timely action to suppress dengue transmission and limit the risk of further spread. This study aims to explore the feasibility of developing a dengue early warning system using temperature and rainfall as main predictors. The objectives were to 1) analyze the relationship between dengue cases and weather predictors, 2) identify the optimal lead time required for a dengue early warning, 3) develop forecasting models, and 4) translate forecasts to dengue risk indices. Methods: Poisson multivariate regression models were established to analyze relative risks of dengue corresponding to each unit change of weekly mean temperature and cumulative rainfall at lag of 1-20 weeks. Duration of vector control for localized outbreaks was analyzed to identify the time required by local authority to respond to an early warning. Then, dengue forecasting models were developed using Poisson multivariate regression. Autoregression, trend, and seasonality were considered in the models to account for risk factors other than temperature and rainfall. Model selection and validation were performed using various statistical methods. Forecast precision was analyzed using cross-validation, Receiver Operating Characteristics curve, and root mean square errors. Finally, forecasts were translated into stratified dengue risk indices in time series formats. Results: Findings showed weekly mean temperature and cumulative rainfall preceded higher relative risk of dengue by 9-16 weeks and that a forecast with at least 3 months would provide sufficient time for mitigation in Singapore. Results showed possibility of predicting dengue cases 1-16 weeks using temperature and rainfall; whereas, consideration of autoregression and trend further enhance forecast precision. Sensitivity analysis showed the forecasting models could detect outbreak and non-outbreak at above 90% with less than 20% false positive. Forecasts were translated into stratified dengue risk indices using color codes and indices ranging from 1-10 in calendar or time sequence formats. Simplified risk indices interpreted forecast according to annual alert and outbreak thresholds; thus, provided uniform interpretation. Significance: A prediction model was developed that forecasted a prognosis of dengue up to 16 weeks in advance with sufficient accuracy. Such a prognosis can be used as an early warning to enhance evidence-based decision making and effective use of public health resources as well as improved effectiveness of dengue surveillance and control. Simple and clear dengue risk indices improve communications to stakeholders.

p. 1-47 / Submitted by Santiago Fabio (fabio.ssantiago@hotmail.com) on 2013-04-22T17:57:28Z No. of bitstreams: 1 1111.pdf: 321783 bytes, checksum: adf8d30a1de03fb37e7da08aee32b4dd (MD5) / Approved for entry into archive by Maria Creuza Silva(mariakreuza@yahoo.com.br) on 2013-05-04T16:56:13Z (GMT) No. of bitstreams: 1 1111.pdf: 321783 bytes, checksum: adf8d30a1de03fb37e7da08aee32b4dd (MD5) / Made available in DSpace on 2013-05-04T16:56:13Z (GMT). No. of bitstreams: 1 1111.pdf: 321783 bytes, checksum: adf8d30a1de03fb37e7da08aee32b4dd (MD5) Previous issue date: 2008 / O principal objetivo deste estudo foi verificar a existência de relação entre os níveis do Índice de Infestação Predial (IIP) obtidos pelo LIRAa e a transmissão de dengue nas semanas posteriores a sua realização. Trata-se de estudo ecológico tendo como unidade de análise município, fonte de dados o SINAN e registros sobre o LIRAa, de 2003 a 2006, obtidos nas Secretarias Estaduais de Saúde. Observou-se correlação positiva estatisticamente significante entre o IIP e o Número da Reprodutibilidade Basal das Infecções - R0 (r= 0,36, p=0,002) e a Força de infecção - λ ( r = 0,35, p=0,002). Os resultados deste estudo reforçam a importância do LIRAa como sinal de alerta para os responsáveis pelas atividades de controle da dengue nos municípios, pois, indiretamente, foi demonstrado que IIP mais elevados nos meses que antecedem o verão podem resultar no maior número de casos na estação de maior transmissão da doença. / Salvador