Elizabet Lilia Estallo

Models for Predicting Aedes aegypti Larval Indices Based on Satellite Images and Climatic Variables

ABSTRACT Forecasting models were developed for predicting Aedes aegypti larval indices in an endemic area for dengue (cities of Tartagal and Orán, northwestern Argentina), based on the Breteau and House indices and environmental variables considered with and without time lags. Descriptive models were first developed for each city and each index by multiple linear regressions, followed by a regional model including both cities together. Finally, two forecasting regional models (FRM) were developed and evaluated. FRM2 for the Breteau index and House index fit the data significantly better than FRM1. An evaluation of these models showed a higher correlation FRM1 than for FRM2 for the Breteau index (R = 0.83 and 0.62 for 3 months; R = 0.86 and 0.67 for 45 days) and the House index (R = 0.85 and 0.79 for 3 months; R = 0.79 and 0.74 for 45 days). Early warning based on these forecasting models can assist health authorities to improve vector control.

New records of mosquito species (Diptera: Culicidae) from Neuquén and La Rioja provinces, Argentina.

Relata-se a presenca de Aedes aegypti ao sul de seu limite atual de distribuicao na Argentina, na cidade de Neuquen, provincia de Neuquen. Ovitrampas foram instaladas de dezembro/2009 a abril/2010. A distribuicao geografica de Culex eduardoi, Psorophora ciliata e Ps. cingulata aumenta, incluindo novos registros para duas provincias.The presence of Aedes aegypti is reported beyond its current limit of distribution in Argentina, in the city of Neuquén, Neuquén Province. Ovitraps were placed to collect Ae. aegypti eggs between December 2009 and April 2010. The geographical distribution of Culex eduardoi, Psorophora ciliata and Ps. cingulata is extended with new records from two provinces.

Spatio-temporal dynamics of dengue 2009 outbreak in Córdoba City, Argentina.

During 2009 the biggest dengue epidemic to date occurred in Argentina, affecting almost half the country. We studied the spatio-temporal dynamics of the outbreak in the second most populated city of the country, Córdoba city. Confirmed cases and the results of an Aedes aegypti monitoring during the outbreak were geolocated. The imported cases began in January, and the autochthonous in March. Thirty-three percent of the 130 confirmed cases were imported, and occurred mainly at the center of the city. The autochthonous cases were more frequent in the outskirts, specially in the NE and SE. Aedes aegypti infestation showed no difference between neighborhoods with or without autochthonous cases, neither between neighborhoods with autochthonous vs. imported cases. The neighborhoods with imported cases presented higher population densities. The majority of autochthonous cases occurred at ages between 25 and 44 years old. Cases formed a spatio-temporal cluster of up to 20 days and 12km. According to a mathematical model that estimates the required number of days needed for transmission according to daily temperature, the number of cases begun to fall when more than 15.5 days were needed. This may be a coarse estimation of mean mosquito survival in the area, provided that the study area is close to the global distribution limit of the vector, and that cases prevalence was very low.

Effectiveness of normalized difference water index in modelling Aedes aegypti house index

The application of remotely sensed data to public health has increased in Argentina in the past few years, especially to study vector-borne viral diseases such as dengue. The normalized difference vegetation index (NDVI) has been widely used for remote sensing of vegetation as well as the brightness temperature (BT) for many years. Another environmental variable obtained from satellites is the normalized difference water index (NDWI) for remote sensing of the status of the vegetation liquid water from space. The aim of the present article was to test the effectiveness of NDWI together with other satellite and meteorological data to develop two forecasting models, namely the SATMET (satellite and meteorological variables) model and the SAT (satellite environmental variables) model. The models were developed and validated by dividing the data file into two sets: the data between January 2001 and April 2004 were used to construct the models and the data between May 2004 and May 2005 were used to validate them. The regression analysis for the SATMET and SAT models showed an adjusted R 2 of 0.82 and 0.79, respectively. To validate the models, a correlation between the estimates and the observations was obtained for both the SATMET model (r = 0.57) and the SAT model (r = 0.64). Both models showed the same root mean square error (RMSE) of 0.04 and, therefore, the same forecasting power. For this reason, these models may have applications as decision support tools in assisting public health authorities in the control of Aedes aegypti and risk management planning programmes.

Weather Variability Associated with Aedes (Stegomyia) aegypti (Dengue Vector) Oviposition Dynamics in Northwestern Argentina.

This study aims to develop a forecasting model by assessing the weather variability associated with seasonal fluctuation of Aedes aegypti oviposition dynamic at a city level in Orán, in northwestern Argentina. Oviposition dynamics were assessed by weekly monitoring of 90 ovitraps in the urban area during 2005-2007. Correlations were performed between the number of eggs collected weekly and weather variables (rainfall, photoperiod, vapor pressure of water, temperature, and relative humidity) with and without time lags (1 to 6 weeks). A stepwise multiple linear regression analysis was performed with the set of meteorological variables from the first year of study with the variables in the time lags that best correlated with the oviposition. Model validation was conducted using the data from the second year of study (October 2006- 2007). Minimum temperature and rainfall were the most important variables. No eggs were found at temperatures below 10°C. The most significant time lags were 3 weeks for minimum temperature and rains, 3 weeks for water vapor pressure, and 6 weeks for maximum temperature. Aedes aegypti could be expected in Orán three weeks after rains with adequate min temperatures. The best-fit forecasting model for the combined meteorological variables explained 70 % of the variance (adj. R2). The correlation between Ae. aegypti oviposition observed and estimated by the forecasting model resulted in rs = 0.80 (P < 0.05). The forecasting model developed would allow prediction of increases and decreases in the Ae. aegypti oviposition activity based on meteorological data for Orán city and, according to the meteorological variables, vector activity can be predicted three or four weeks in advance.

Prevention of dengue outbreaks through Aedes aegypti oviposition activity forecasting method.

Dengue has affected the north provinces of Argentina, mainly Salta province. The 2009 outbreak, with 5 deaths and >27,000 infected, was the most important, and the first to extend into the central area of the country. This article includes research on seasonal Aedes aegypti abundance variation in Orán City (Salta province), and determination of the date of mosquito population increase and an estimation of the date of maximum rate of increase as well as the intrinsic rate of natural increase (r), to detect the optimal time to apply vector control measures. Between September 2005 and March 2007, ovitraps were randomly distributed in the city to collect Ae. aegypti eggs. The variation observed in the number of collected eggs was described by fitting a third-degree polynomial by the least square method, allowing to determine the time when population increase began (week 1), after the temperate and dry season. Eggs were collected throughout the year, with the highest variation in abundance during the warm and rainy season, and the maximum value registered in February 2007. The rate of increase of the number of eggs laid per week peaked between weeks 9 and 10 after the beginning of the population increase (week 1). Week 1 depends on temperature, it occurs after getting over the thermal threshold and the needed accumulation of 160 degree-day is reached. Consequently, week 1 changes depending on temperature. Peak abundance of eggs during 2005-2006 was recorded on week 15 (after week 1); during 2006-2007, the peak was observed on week 22. Estimation of the intrinsic rate of natural increase (r) of Ae. aegypti is useful not only to determine optimal time to apply vector control measures with better cost-benefit, but also to add an insecticide control strategy against the vector to diminish the possibility of resistance.

MODIS Environmental Data to Assess Chikungunya, Dengue, and Zika Diseases Through Aedes (Stegomia) aegypti Oviposition Activity Estimation

Aedes aegypti is the main vector for Chikungunya, Dengue, and Zika viruses in Latin America and it represents a main threat for our region. Taking into account this situation, several efforts have been done to use remote sensing to support public health decision making. Moderate resolution imaging spectroradiometer (MODIS) sensor provides moderate-resolution remote sensing products; therefore, we explore the application of MODIS products to vector-borne disease problems in Argentina. We develop temporal forecasting models of Ae. aegypti oviposition, and we include its validation and its application to the 2016 Dengue outbreak. Temporal series (10/2005 to 09/2007) from MODIS products of normalized difference vegetation index and diurnal land surface temperature were built. Two linear regression models were developed: model 1 which uses environmental variables with time lag and model 2 uses environmental variables without time lags. Model 2 was the best model (AIC = 112) with high correlation (r = 0.88, p <; 0.05) between observed and predicted data. We can suggest that MODIS products could be a good tool for estimating both Ae. aegypti oviposition activity and risks for Ae. aegypti-borne diseases. That statement is also supported by model results for 2016 when a dengue outbreak that started unusually earlier this season. If such activity could be forecast by a model based on remote sensing data, then a potential outbreak could be predicted.

Satellite-derived NDVI, LST, and climatic factors driving the distribution and abundance of Anopheles mosquitoes in a former malarious area in northwest Argentina

ABSTRACT: Distribution and abundance of disease vectors are directly related to climatic conditions and environmental changes. Remote sensing data have been used for monitoring environmental conditions influencing spatial patterns of vector-borne diseases. The aim of this study was to analyze the effect of the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), and climatic factors (temperature, humidity, wind velocity, and accumulated rainfall) on the distribution and abundance of Anopheles species in northwestern Argentina using Poisson regression analyses. Samples were collected from December, 2001 to December, 2005 at three localities, Aguas Blancas, El Oculto and San Ramón de la Nueva Orán. We collected 11,206 adult Anopheles species, with the major abundance observed at El Oculto (59.11%), followed by Aguas Blancas (22.10%) and San Ramón de la Nueva Orán (18.79%). Anopheles pseudopunctipennis was the most abundant species at El Oculto, Anopheles argyritarsis predominated in Aguas Blancas, and Anopheles strodei in San Ramón de la Nueva Orán. Samples were collected throughout the sampling period, with the highest peaks during the spring seasons. LST and mean temperature appear to be the most important variables determining the distribution patterns and major abundance of An. pseudopunctipennis and An. argyritarsis within malarious areas.

Landscape determinants of Saint Louis encephalitis human infections in Córdoba city, Argentina during 2010.

Saint Louis encephalitis virus (SLEV) is endemic in Argentina. During 2005 an outbreak occurred in Córdoba. From January to April of 2010 a new outbreak occurred in Córdoba city with a lower magnitude than the one reported in 2005. Understanding the association of different landscape elements related to SLEV hosts and vectors in urban environments is important for identifying high risk areas for human infections, which was here evaluated. The current study uses a case-control approach at a household geographical location, considering symptomatic and asymptomatic human infections produced by SLEV during 2010 in Córdoba city. Geographical information systems and logistic regression analysis were used to study the distribution of infected human cases and their proximity to water bodies, vegetation abundance, agricultural fields and housing density classified as high/low density urban constructions. Population density at a neighborhood level was also analyzed as a demographic variable. Logistic regression analysis revealed vegetation abundance was significantly (p<0.01) associated with the presence of human infections by SLEV. A map of probability of human infections in Córdoba city was derived from the logistic model. The model highlights areas that are more likely to experience SLEV infections. Landscape variables contributing to the outbreak were the proximity to places with vegetation abundance (parks, squares, riversides) and the presence of low density urban constructions, like residential areas. The population density analysis shows that SLEV infections are more likely to occur when population density by neighborhood is lower. These findings and the predictive map developed could be useful for public health surveillance and to improve prevention of vector-borne diseases.

St. Louis Encephalitis virus mosquito vectors dynamics in three different environments in relation to remotely sensed environmental conditions.

In Argentina the St. Louis Encephalitis virus (SLEV) is an endemic and widely distributed pathogen transmitted by the cosmopolitan mosquito Culex quinquefasciatus. During two outbreaks in Córdoba city, in 2005 and 2010, Culex interfor was also found infected, but its role as vector of SLEV is poorly known. This mosquito species is distributed from central Argentina to southern Brazil. The primary aim of this study was to analyze the population dynamic of Cx. interfor and Cx. quinquefasciatus in three different environments (urban, suburban and non-urban) in relation to remotely sensed environmental data for vegetation (NDVI and NDWI) and temperature (brightness temperature). Cx. quinquefasciatus and Cx. interfor were found at the three sampled sites, being both the most abundant Culex species, with peaks in early and midsummer. Temporal distribution patterns of both mosquito species were highly correlated in a non-urban area of high SLEV risk transmission. Cx. quinquefasciatus and Cx. interfor were associated with the most urbanized site and the non-urban environment, respectively; high significant correlations were detected between vegetation indices and abundance of both mosquito species confirming these associations. These data provide a foundation for building density maps of these two SLEV mosquito vectors using remotely sensed data to help inform vector control programs.