Arbovirus Transmission Predictions Are Affected by Both Temperature Data Source and Modeling Methodologies across Cities in Colombia.

Weather variables has been described as major drivers of vector proliferation and arbovirus transmission. Among them, temperature has consistently been found to be impactful in transmission dynamics, and models that incorporate temperature have been widely used to evaluate and forecast transmission or arboviruses like dengue, zika, or chikungunya virus. Further, there is growing evidence of the importance of micro-environmental temperatures in driving transmission of Aedes aegypti-borne viruses, as these mosquitoes tend to live within domiciles. Yet there is still a considerable gap in our understanding of how accounting for micro-environmental temperatures in models varies from the use of other widely-used, macro-level temperature measures. This effort combines field-collected data of both indoor and outdoor household associated temperatures and weather station temperature data from three Colombian cities to describe the relationship between the measures representing temperature at the micro- and macro-levels. These data indicate that weather station data may not accurately capture the temperature profiles of indoor micro-environments. However, using these data sources, the basic reproductive number for arboviruses was calculated by means of three modeling efforts to investigate whether temperature measure differences translated to differential transmission predictions. Across all three cities, it was determined that the modeling method was more often impactful rather than the temperature data-source, though no consistent pattern was immediately clear. This suggests that temperature data sources and modeling methods are important for precision in arbovirus transmission predictions, and more studies are needed to parse out this complex interaction.

The changing risk of vector-borne diseases: Global satellite remote sensing and geospatial surveillance at the forefront.

Not available.

Use of Geospatial Surveillance and Response Systems for Vector-Borne Diseases in the Elimination Phase.

The distribution of diseases caused by vector-borne viruses and parasites are restricted by the environmental requirements of their vectors, but also by the ambient temperature inside the host as it influences the speed of maturation of the infectious agent transferred. The launch of the Soil Moisture Active Passive (SMAP) satellite in 2015, and the new ECOSTRESS instrument onboard the International Space Station (ISS) in 2018, established the leadership of the National Aeronautics Space Administration (NASA) in ecology and climate research by allowing the structural and functional classification of ecosystems that govern vector sustainability. These advances, and the availability of sub-meter resolution data from commercial satellites, contribute to seamless mapping and modelling of diseases, not only at continental scales (1 km²) and local community or agricultural field scales (15⁻30 m²), but for the first time, also at the habitat⁻household scale (<1 m²). This communication presents current capabilities that are related to data collection by Earth-observing satellites, and draws attention to the usefulness of geographical information systems (GIS) and modelling for the study of important parasitic diseases.

Geohealth: biology based mapping of vector borne disease in the Americas using NASA satellite data / Geosaúde: mapeamento da biologia das doenças vetoriais nas Américas utilizando dados de satélites da NASA

Implementation of a geospatial surveillance and response system data resource for vector borne disease in the Americas (GeoHealth) will be tested using NASA satellite data, geographic information systems and ecological niche modeling to characterize the environmental suitability and potential for spread of endemic and epizootic vector borne diseases. The initial focus is on developing prototype geospatial models for visceral leishmaniasis, an expanding endemic disease in Latin America, and geospatial models for dengue and other Aedes aegypti borne arboviruses (zika, chikungunya), emerging arboviruses with potential for epizootic spread from Latin America and the Caribbean and establishment in North America. Geospatial surveillance and response system open resource data bases and models will be made available, with training courses, to other investigators interested in mapping and modeling other vector borne diseases in the western hemisphere and contributing brokered data to an expanding GeoHealth data resource as part of the NASA AmeriGEOSS initiative.(AU)

A implementação de uma fonte de dados de vigilância e um sistema de resposta geoespacial para doenças transmitidas por vetores nas Américas (GeoHealth) será testada utilizando dados provenientes de satélites da NASA, sistemas de informações geográficas e modelagem do nicho ecológico, para caracterizar a suceptibilidade ambiental e o potencial de dispersão de doenças endêmicas e epizooticas transmitidas por vetores vetores. O foco inicial será o desenvolvimento de protótipos de modelos geoespaciais para a leishmaniose visceral, uma doença endêmica e em expansão na América Latina, e modelos geoespaciais para dengue e outros transmitidos pelo Aedes aegypti (zika, chikungunya), arbovírus emergentes com potencial para disseminação epizoótica pela América Latina e Caribe e estabelecimento na América do Norte. Sistemas de vigilância e resposta geoespacial e modelos de recursos em bases de dados abertas serão diponibilizados, com cursos de treinamento, para outros pesquisadores interessados em mapear e modelar outras doenças transmitidas por vetores no hemisfério ocidental e contribuir intermediando dados para uma fonte de dados GeoHealth em expansão, como parte da Iniciativa AmeriGEOSS, da NASA. (AU)

A thermodynamic paradigm for using satellite based geophysical measurements in public health applications / Um paradigma termodinâmico para o uso de medidas geofísicas baseadas em satélites e suas aplicações em saúde pública

A thermodynamic paradigm for studying disease vector's habitats & life cycles using NASA's remote sensing data is being proposed. NASA's current and planned satellite missions provide measurements of the critical environmental measures environmental state functions important to vector & disease life cycles such as precipitation, soil moisture, temperature, vapor pressure deficits, wet/dry edges, and solar radiation. Satellite data provide landscape scale process functions represented by land use/cover mapping and actual measurements of ecological functions/structure: canopy cover, species, phenology, and aquatic plant coverage. These measurements are taken in a spatial context and provide a time series of data to track changes in time. Global public health is entering a new informational age through the use of spatial models of disease vector/host ecologies driven by the use of remotely sensed data to measure environmental and structural factors critical in determining disease vector habitats, distributions, life cycles, and host interactions. The vector habitat microclimates can be quantified in terms of the surface energy budget measured by satellites. The epidemiological equations (processes) can be adapted and modified to explicitly incorporate environmental factors and interfaces required by a specific disease and its vector/host cycle. Remote sensing can be used to measure or evaluate or estimate both environment (state functions) and interface (process functions). It is critical that the products of remote sensing must be expressed in a way they can be integrated directly into the epidemiological equations. (AU)

Um paradigma termodinâmico para estudar os habitats e ciclos de vida dos vetores de doenças utilizando dados de sensoriamento remoto da NASA está sendo proposto. As missões atuais e planejadas para os satélites da NASA fornecem medições das funções críticas ambientais e funções do estado ambiental, importantes para os ciclos de vida de vetores e doenças, como precipitação, umidade do solo, temperatura, déficits de pressão do vapor, bordas úmidas/secas e radiação solar. Os dados de satélite fornecem as funções dos processos na escala da paisagem, representada pelo mapeamento do uso/cobertura da terra e medições reais das funções/estruturas ecológicas: cobertura do dossel, espécies, fenologia e cobertura de plantas aquáticas. Essas medições são feitas em um contexto espacial e fornecem uma série temporal de dados para rastrear dinâmica das mudanças. A saúde pública global está entrando em uma nova era informacional através do uso de modelos espaciais para vetores/hospedeiros de doenças, impulsionados pelo uso de dados de sensoriamento remoto, para medir fatores ambientais e estruturais críticos na determinação de habitats de vetores de doenças, distribuições, ciclos de vida e interações com o hospedeiro. Os microclimas dos habitats vetoriais podem ser quantificados em termos do orçamento de energia superficial, medidos por satélites. As equações epidemiológicas (processos) podem ser adaptadas e modificadas para incorporar explicitamente fatores e interfaces ambientais requeridos por uma doença específica e o ciclo do seu vetor/hospedeiro. O sensoriamento remoto pode ser usado para medir ou avaliar, ou mesmo estimar tanto o ambiente (funções do seu estado) quanto a interface (funções de seus processos). É fundamental que os produtos de sensoriamento remoto sejam expressos de forma a integrá-los diretamente às equações epidemiológicas. (AU)

Geohealth: biology based mapping of vector borne disease in the Americas using NASA satellite data / Geosaúde: mapeamento da biologia das doenças vetoriais nas Américas utilizando dados de satélites da NASA

Implementation of a geospatial surveillance and response system data resource for vector borne disease in the Americas (GeoHealth) will be tested using NASA satellite data, geographic information systems and ecological niche modeling to characterize the environmental suitability and potential for spread of endemic and epizootic vector borne diseases. The initial focus is on developing prototype geospatial models for visceral leishmaniasis, an expanding endemic disease in Latin America, and geospatial models for dengue and other Aedes aegypti borne arboviruses (zika, chikungunya), emerging arboviruses with potential for epizootic spread from Latin America and the Caribbean and establishment in North America. Geospatial surveillance and response system open resource data bases and models will be made available, with training courses, to other investigators interested in mapping and modeling other vector borne diseases in the western hemisphere and contributing brokered data to an expanding GeoHealth data resource as part of the NASA AmeriGEOSS initiative.

A implementação de uma fonte de dados de vigilância e um sistema de resposta geoespacial para doenças transmitidas por vetores nas Américas (GeoHealth) será testada utilizando dados provenientes de satélites da NASA, sistemas de informações geográficas e modelagem do nicho ecológico, para caracterizar a suceptibilidade ambiental e o potencial de dispersão de doenças endêmicas e epizooticas transmitidas por vetores vetores. O foco inicial será o desenvolvimento de protótipos de modelos geoespaciais para a leishmaniose visceral, uma doença endêmica e em expansão na América Latina, e modelos geoespaciais para dengue e outros transmitidos pelo Aedes aegypti (zika, chikungunya), arbovírus emergentes com potencial para disseminação epizoótica pela América Latina e Caribe e estabelecimento na América do Norte. Sistemas de vigilância e resposta geoespacial e modelos de recursos em bases de dados abertas serão diponibilizados, com cursos de treinamento, para outros pesquisadores interessados em mapear e modelar outras doenças transmitidas por vetores no hemisfério ocidental e contribuir intermediando dados para uma fonte de dados GeoHealth em expansão, como parte da Iniciativa AmeriGEOSS, da NASA.

A thermodynamic paradigm for using satellite based geophysical measurements in public health applications / Um paradigma termodinâmico para o uso de medidas geofísicas baseadas em satélites e suas aplicações em saúde pública

A thermodynamic paradigm for studying disease vector’s habitats & life cycles using NASA’s remote sensing data is being proposed. NASA’s current and planned satellite missions provide measurements of the critical environmental measures environmental state functions important to vector & disease life cycles such as precipitation, soil moisture, temperature, vapor pressure deficits, wet/dry edges, and solar radiation. Satellite data provide landscape scale process functions represented by land use/cover mapping and actual measurements of ecological functions/structure: canopy cover, species, phenology, and aquatic plant coverage. These measurements are taken in a spatial context and provide a time series of data to track changes in time. Global public health is entering a new informational age through the use of spatial models of disease vector/host ecologies driven by the use of remotely sensed data to measure environmental and structural factors critical in determining disease vector habitats, distributions, life cycles, and host interactions. The vector habitat microclimates can be quantified in terms of the surface energy budget measured by satellites. The epidemiological equations (processes) can be adapted and modified to explicitly incorporate environmental factors and interfaces required by a specific disease and its vector/host cycle. Remote sensing can be used to measure or evaluate or estimate both environment (state functions) and interface (process functions). It is critical that the products of remote sensing must be expressed in a way they can be integrated directly into the epidemiological equations.

Um paradigma termodinâmico para estudar os habitats e ciclos de vida dos vetores de doenças utilizando dados de sensoriamento remoto da NASA está sendo proposto. As missões atuais e planejadas para os satélites da NASA fornecem medições das funções críticas ambientais e funções do estado ambiental, importantes para os ciclos de vida de vetores e doenças, como precipitação, umidade do solo, temperatura, déficits de pressão do vapor, bordas úmidas/secas e radiação solar. Os dados de satélite fornecem as funções dos processos na escala da paisagem, representada pelo mapeamento do uso/cobertura da terra e medições reais das funções/estruturas ecológicas: cobertura do dossel, espécies, fenologia e cobertura de plantas aquáticas. Essas medições são feitas em um contexto espacial e fornecem uma série temporal de dados para rastrear dinâmica das mudanças. A saúde pública global está entrando em uma nova era informacional através do uso de modelos espaciais para vetores/hospedeiros de doenças, impulsionados pelo uso de dados de sensoriamento remoto, para medir fatores ambientais e estruturais críticos na determinação de habitats de vetores de doenças, distribuições, ciclos de vida e interações com o hospedeiro. Os microclimas dos habitats vetoriais podem ser quantificados em termos do orçamento de energia superficial, medidos por satélites. As equações epidemiológicas (processos) podem ser adaptadas e modificadas para incorporar explicitamente fatores e interfaces ambientais requeridos por uma doença específica e o ciclo do seu vetor/hospedeiro. O sensoriamento remoto pode ser usado para medir ou avaliar, ou mesmo estimar tanto o ambiente (funções do seu estado) quanto a interface (funções de seus processos). É fundamental que os produtos de sensoriamento remoto sejam expressos de forma a integrá-los diretamente às equações epidemiológicas.

Developing GIS-based eastern equine encephalitis vector-host models in Tuskegee, Alabama.

BACKGROUND: A site near Tuskegee, Alabama was examined for vector-host activities of eastern equine encephalomyelitis virus (EEEV). Land cover maps of the study site were created in ArcInfo 9.2 from QuickBird data encompassing visible and near-infrared (NIR) band information (0.45 to 0.72 microm) acquired July 15, 2008. Georeferenced mosquito and bird sampling sites, and their associated land cover attributes from the study site, were overlaid onto the satellite data. SAS 9.1.4 was used to explore univariate statistics and to generate regression models using the field and remote-sampled mosquito and bird data. Regression models indicated that Culex erracticus and Northern Cardinals were the most abundant mosquito and bird species, respectively. Spatial linear prediction models were then generated in Geostatistical Analyst Extension of ArcGIS 9.2. Additionally, a model of the study site was generated, based on a Digital Elevation Model (DEM), using ArcScene extension of ArcGIS 9.2. RESULTS: For total mosquito count data, a first-order trend ordinary kriging process was fitted to the semivariogram at a partial sill of 5.041 km, nugget of 6.325 km, lag size of 7.076 km, and range of 31.43 km, using 12 lags. For total adult Cx. erracticus count, a first-order trend ordinary kriging process was fitted to the semivariogram at a partial sill of 5.764 km, nugget of 6.114 km, lag size of 7.472 km, and range of 32.62 km, using 12 lags. For the total bird count data, a first-order trend ordinary kriging process was fitted to the semivariogram at a partial sill of 4.998 km, nugget of 5.413 km, lag size of 7.549 km and range of 35.27 km, using 12 lags. For the Northern Cardinal count data, a first-order trend ordinary kriging process was fitted to the semivariogram at a partial sill of 6.387 km, nugget of 5.935 km, lag size of 8.549 km and a range of 41.38 km, using 12 lags. Results of the DEM analyses indicated a statistically significant inverse linear relationship between total sampled mosquito data and elevation (R2 = -.4262; p < .0001), with a standard deviation (SD) of 10.46, and total sampled bird data and elevation (R2 = -.5111; p < .0001), with a SD of 22.97. DEM statistics also indicated a significant inverse linear relationship between total sampled Cx. erracticus data and elevation (R2 = -.4711; p < .0001), with a SD of 11.16, and the total sampled Northern Cardinal data and elevation (R2 = -.5831; p < .0001), SD of 11.42. CONCLUSION: These data demonstrate that GIS/remote sensing models and spatial statistics can capture space-varying functional relationships between field-sampled mosquito and bird parameters for determining risk for EEEV transmission.