Forecast of acute respiratory infections: expected nonepidemic mobidity in Cuba

A forecast of nonepidemic morbidity due to acute respiratory infections were carry out by using time series analysis. The data consisted of the weekly reports of medical patient consultation from ambulatory facilities from the whole country. A version of regression model was fitted to the data. Using this approach, we were able to detect the starting data of the epidemic under routine surveillance conditions for various age groups. It will be necessary to improve the data reporting system in order to introduce these procedures at the local health center level, as well as on the provincial level.

Weather requirements and rain forecast to time fungicide application for Fusarium head blight control in wheat

The aim of this study was to determine the minimum conditions of wetness duration and mean temperature required for Fusarium head blight infection in wheat. The weather model developed by Zoldan (2008) was tested in field experiments for two wheat cultivars grown in 2005 (five sowing dates) and 2006 (six sowing dates) in 10 m² plots with three replicates. The disease was assessed according to head incidence (HI), spikelet incidence (SI), and the interaction between these two methods was called head blight severity (HBS). Starting at the beginning of anthesis, air temperature and head wetness duration were daily recorded with an automatic weather station. With the combination of these two factors, a weather favorability table was built for the disease occurrence. Starting on the day of flowering beginning (1 - 5% fully exserted anthers), the sum of daily values for infection favorability (SDVIF) was calculated by means of a computer program, according to Zoldan (2008) table. The initial symptoms of the disease were observed at 3.7% spikelet incidence, corresponding to 2.6 SVDFI. The infection occurs in wheat due to rainfall which results in spike wetting of > 61.4 h duration. Rainfall events forecast can help time fungicide application to control FHB. The name of this alert system is proposed as UPF-scab alert.

Analysis and forecast of the storage needs of soybeans in Brazil

The existence of a minimum storage capacity of grains as a condition for the maintenance of regulator physical stocks has been used as a strategic factor in the agribusiness expansion. However, in Brazil the storage infrastructure has not followed the growth of the agricultural sector. This fact is evident in the case of soybeans that currently represent 49% of grain production in the country, whose volume production has been increasing significantly over the years. This study aimed to predict the futureneeds of static storage capacity of soybeans from historical data to estimate the investment needed to install storage units in Brazil for the next five years. A statistic analysis of collected data allowed a forecast and identification of the number of storage units that should be installed to meet the storage needs of soybeans in the next five years. It was concluded that by 2015 the soybean storage capacity should be 87 million tons, and to store 49% of soybeans produced, 1,104 storage units should be installed at a cost of R$ 442 million.

Economic burden of expected epidemiological changes in diseases related to tobacco, Mexico

OBJECTIVE: To determine health care costs and economic burden of epidemiological changes in diseases related to tobacco consumption. METHODS: A time-series analysis in Mexico (1994-2005) was carried out on seven health interventions: chronic obstructive pulmonary diseases, lung cancer with and without surgical intervention, asthma in smokers and non-smokers, full treatment course with nicotine gum, and full treatment course with nicotine patch. According with Box-Jenkins methodology, probabilistic models were developed to forecast the expected changes in the epidemiologic profile and the expected changes in health care services required for selected interventions. Health care costs were estimated following the instrumentation methods and validated with consensus technique. RESULTS: A comparison of the economic impact in 2006 vs. 2008 showed 20-90% increase in expected cases depending on the disease (p<0.05), and 25-93% increase in financial requirements (p<0.01). The study data suggest that changes in the demand for health services for patients with respiratory diseases related to tobacco consumption will continue showing an increasing trend. CONCLUSIONS: In economic terms, the growing number of cases expected during the study period indicates a process of internal competition and adds an element of intrinsic competition in the management of preventive and curative interventions. The study results support the assumption that if preventive programs remain unchanged, the increasing demands for curative health care may cause great financial and management challenges to the health care system of middle-income countries like Mexico.

An appraisal of the epidemiology of Trypanosoma cruzi serology in Brazil

A large bibliographic survey provided data on Trypanosoma cruzi serology covering the period l948-l984. Epidemiological-demographic methods provided an estimate of 11% for the prevalenceof positive serology in Brazil, by 1984. Significant temporal trends were observed for most of the Brazilian geographical regions as well as for Brazil, as a whole. The parabolic curve that fit best for the entire country, indicates that by 1991, the incidence of new positive serology would be close to zero. This conclusion needs further fine-adjustment, since the forecast point is somewhat distant from the measured period.

The feasibility of forecasting influenza epidemics in Cuba

A large influenza epidemic took place in Havana during the winter of 1988. The epidemiologic surveillance unit of the Pedro Kouri Institute of Tropical Medicine detected the begining of the epidemic wave. The Rvachev-Baroyan mathematical model of the geographic spread of an epidemic was used to forecast this epidemic under routine conditions of the public health system. The expected number of individuals who would attend outpatient services, because of influenza-like illness, was calculated and communicated to the health authorities within enough time to permit the introduction of available control measures. The approximate date of the epidemic peak, the daily expected number of individuals attending medical services, and the approximate time of the end of the epidemic wave were estimated. The prediction error was 12%. The model was sufficienty accurate to warrant its use as a pratical forecasting tool in the Cuban public health system.

Predictors of local malaria outbreaks: an approach to the development of an early warning system in Colombia

Risk factor surveillance is a complementary tool of morbidity and mortality surveillance that improves the likelihood that public health interventions are implemented in a timely fashion. The aim of this study was to identify population predictors of malaria outbreaks in endemic municipalities of Colombia with the goal of developing an early warning system for malaria outbreaks. We conducted a multiple-group, exploratory, ecological study at the municipal level. Each of the 290 municipalities with endemic malaria that we studied was classified according to the presence or absence of outbreaks. The measurement of variables was based on historic registries and logistic regression was performed to analyse the data. Altitude above sea level [odds ratio (OR) 3.65, 95% confidence interval (CI) 1.34-9.98], variability in rainfall (OR 1.85, 95% CI 1.40-2.44) and the proportion of inhabitants over 45 years of age (OR 0.17, 95% CI 0.08-0.38) were factors associated with malaria outbreaks in Colombian municipalities. The results suggest that environmental and demographic factors could have a significant ability to predict malaria outbreaks on the municipal level in Colombia. To advance the development of an early warning system, it will be necessary to adjust and standardise the collection of required data and to evaluate the accuracy of the forecast models.

Soybean crop area estimation by Modis/Evi data

The objective of this work was to develop a procedure to estimate soybean crop areas in Rio Grande do Sul state, Brazil. Estimations were made based on the temporal profiles of the enhanced vegetation index (Evi) calculated from moderate resolution imaging spectroradiometer (Modis) images. The methodology developed for soybean classification was named Modis crop detection algorithm (MCDA). The MCDA provides soybean area estimates in December (first forecast), using images from the sowing period, and March (second forecast), using images from the sowing and maximum crop development periods. The results obtained by the MCDA were compared with the official estimates on soybean area of the Instituto Brasileiro de Geografia e Estatística. The coefficients of determination ranged from 0.91 to 0.95, indicating good agreement between the estimates. For the 2000/2001 crop year, the MCDA soybean crop map was evaluated using a soybean crop map derived from Landsat images, and the overall map accuracy was approximately 82%, with similar commission and omission errors. The MCDA was able to estimate soybean crop areas in Rio Grande do Sul State and to generate an annual thematic map with the geographic position of the soybean fields. The soybean crop area estimates by the MCDA are in good agreement with the official agricultural statistics.

Rice yield estimation based on weather conditions and on technological level of production systems in Brazil

The objective of this work was to evaluate an estimation system for rice yield in Brazil, based on simple agrometeorological models and on the technological level of production systems. This estimation system incorporates the conceptual basis proposed by Doorenbos & Kassam for potential and attainable yields with empirical adjusts for maximum yield and crop sensitivity to water deficit, considering five categories of rice yield. Rice yield was estimated from 2000/2001 to 2007/2008, and compared to IBGE yield data. Regression analyses between model estimates and data from IBGE surveys resulted in significant coefficients of determination, with less dispersion in the South than in the North and Northeast regions of the country. Index of model efficiency (E1') ranged from 0.01 in the lower yield classes to 0.45 in higher ones, and mean absolute error ranged from 58 to 250 kg ha‑1, respectively.

Tendências temporais de índices de vegetação nos campos do Pampa do Brasil e do Uruguai

O objetivo deste trabalho foi avaliar a redução do vigor vegetativo da cobertura vegetal do Pampa do Brasil e do Uruguai, por meio da identificação de tendências negativas em séries temporais de imagens. Utilizaram-se séries temporais de imagens de NDVI/EVI do sensor Modis, de 2000 a 2011; imagens de índices de umidade do solo do "climate forecast system reanalysis"; e dados de precipitação pluvial de estações meteorológicas. O estudo quantificou tendências lineares e não lineares nas séries de NDVI e EVI, em áreas de campos. Na tendência monotônica de Mann-Kendall, a 5% de probabilidade, 81,9% da área total estudada foi significativa com o NDVI, e 74,8%, com o EVI; no entanto, o EVI apresentou contraste superior na estimativa dos parâmetros. Os resultados mostraram maior sinal negativo a oeste, com valores médios de R²>0,15, r<-0,3 e τ <-0,15 na tendência dos índices de vegetação, e tendência decrescente para NDVI, EVI e precipitação pluvial, com menores valores médios de umidade do solo. A tendência negativa dos índices de vegetação, relacionada à combinação da ocorrência de deficit hídrico em solos rasos com o sobrepastoreio, indica alterações no padrão de cobertura vegetal do Pampa, com redução do vigor vegetativo.

Poluição das águas por herbicidas utilizados no cultivo do arroz irrigado na região central do estado do Rio Grande do Sul, Brasil: predição teórica e monitoramento

This article presents an evaluation of the pollution of river water by herbicides used in the culture of irrigated rice in Rio Grande do Sul State, Brazil. Firstly, a theoretical evaluation was made using the approaches suggested by EPA-USA, the "Groundwater Ubiquity Score" index and the Goss method to estimate the pollution possibilities. Afterwards, a monitoring program was established for the rivers of the area from 2001 to 2003 to investigate the presence of herbicide residues. The results indicate that the herbicides clomazone and propanil are the ones with larger presence and frequency in the analyzed samples. The theoretical forecast was confirmed by the results of the monitoring program.

Análise screening de vinhos empregando um analisador fluxo-batelada, espectroscopia UV-VIS e quimiometria

A simple, robust, versatile, high analytical frequency method was proposed to check if a sample of wine is within the range of standards set by the manufacturer, using the UV-VIS spectroscopy, multivariate analysis and a flow-batch analyzer. Two hundred and fifty-two samples of wines were analyzed. The results from the application of Hierachical Cluster Analysis (HCA) to the matrix of the data involving all samples show the formation of fifteen types of wine. A Soft Independent Modelling of Class Analogy (SIMCA) model was constructed and used to classify the samples of the overall forecast. As a result, it is observed that the prediction was performed with a success rate of 99.2% for a confidence level of 95%. This shows that the proposed methodology can be used as an effective tool for classifying of samples of wines.

Epidemiology of apple leaf spot

Apple leaf spot (ALS) caused by Colletotrichum spp. is a major disease of apple (Malus domestica) in Southern Brazil. The epidemiology of this disease was studied in experiments carried out in the counties of Passo Fundo and Vacaria, State of Rio Grande do Sul, from February 1998 to October 2000. The disease was found in all the six apple orchards sampled in the growing seasons of 1997/98 and 1998/99. The fungus isolates associated with ALS fit the characteristics of C. gloeosporioides (75%), C. acutatum (8%), and Colletotrichum sp. (17%). The pathogen overwintered in dormant buds and twigs but not in dropped leaves or fruit mummies. Two sprays of copper oxychloride (at 0.3%) reduced the fungus initial inoculum by 65-84.6% in buds and 85.6-93.7% in twigs, but had no effect on the early season progress of the disease. Disease severity increased proportionally to elevation of temperature from 14 to 26-28 °C. At 34 °C, however, infection was completely inhibited. The duration of leaf wetness required for infection ranged from two hours at 30 °C to 32 h at 16 °C. The relationship of temperature (T) and leaf wetness (W) to disease severity (Y) was represented by the model equation Y = 0.00145[((T-13)1.78)((34.01-T )1.09)] * 25/[1+14 exp(-0.137W)], R² = 0.73 and P < 0.0001. Currently, this information is being used to manage the disease and to validate a forecast system for ALS.

A risk infection simulation model for fusarium head blight of wheat

Fusarium Head Blight (FHB) is a disease of great concern in wheat (Triticum aestivum). Due to its relatively narrow susceptible phase and environmental dependence, the pathosystem is suitable for modeling. In the present work, a mechanistic model for estimating an infection index of FHB was developed. The model is process-based driven by rates, rules and coefficients for estimating the dynamics of flowering, airborne inoculum density and infection frequency. The latter is a function of temperature during an infection event (IE), which is defined based on a combination of daily records of precipitation and mean relative humidity. The daily infection index is the product of the daily proportion of susceptible tissue available, infection frequency and spore cloud density. The model was evaluated with an independent dataset of epidemics recorded in experimental plots (five years and three planting dates) at Passo Fundo, Brazil. Four models that use different factors were tested, and results showed all were able to explain variation for disease incidence and severity. A model that uses a correction factor for extending host susceptibility and daily spore cloud density to account for post-flowering infections was the most accurate explaining 93% of the variation in disease severity and 69% of disease incidence according to regression analysis.

Influence of temperature and leaf wetness duration in the severity of Cercospora leaf spot of beet

ABSTRACT In the present study, the influence of temperature (15, 20, 25, 30 and 35°C) and leaf wetness period (6, 12, 24 and 48 hours) on the severity of Cercospora leaf spot of beet, caused by Cercospora beticola, was studied under controlled conditions. Lesion density was influenced by temperature and leaf wetness duration (P<0.05). Data were subjected to nonlinear regression analysis. The generalized beta function was used for fitting the disease severity and temperature data, while a logistic function was chosen to represent the effect of leaf wetness on the severity of Cercospora leaf spot. The response surface resultant of the product of the two functions was expressed as ES = 0.0001105 * (((x-8)2.294387) * ((36-x)0.955017)) * (0.39219/(1+25.93072 * exp (-0.16704*y))), where: ES represents the estimated severity value (0.1); x, the temperature (ºC) and y, the leaf wetness duration (hours). This model should be validated under field conditions to assess its use as a computational forecast system for Cercospora leaf spot of beet.