110 resultados para log-series distribution
em Scielo Saúde Pública - SP
Resumo:
The specimen distribution pattern of a species can be used to characterise a population of interest and also provides area-specific guidance for pest management and control. In the municipality of Dracena, in the state of São Paulo, we analysed 5,889 Lutzomyia longipalpis specimens collected from the peridomiciles of 14 houses in a sector where American visceral leishmaniasis (AVL) is transmitted to humans and dogs. The goal was to analyse the dispersion and a theoretical fitting of the species occurrence probability. From January-December 2005, samples were collected once per week using CDC light traps that operated for 12-h periods. Each collection was considered a sub-sample and was evaluated monthly. The standardised Morisita index was used as a measure of dispersion. Adherence tests were performed for the log-series distribution. The number of traps was used to adjust the octave plots. The quantity of Lu. longipalpis in the sector was highly aggregated for each month of the year, adhering to a log-series distribution for 11 of the 12 months analysed. A sex-stratified analysis demonstrated a pattern of aggregated dispersion adjusted for each month of the year. The classes and frequencies of the traps in octaves can be employed as indicators for entomological surveillance and AVL control.
Resumo:
Diversidade de formigas epigéicas (Hymenoptera, Formicidae) em ambientes no Centro-Oeste do Brasil. Foi comparada, através do uso de índices de diversidade e modelos de abundância de espécies, a diversidade das comunidades de formigas epigéicas que ocorrem em duas estruturas vegetacionais diferentes: mata nativa e cultura de eucalipto. Para a captura das formigas foram utilizadas 800 armadilhas de solo do tipo pitfall, em oito amostras distintas. Um total de 85 espécies, distribuídas em 36 gêneros de sete subfamílias foram coletadas nos dois ambientes, sendo que destas, 83 ocorreram na mata nativa e 60 na cultura de eucalipto. A diversidade de espécies de formigas calculada pelo índice de Simpson não foi significativamente diferente entre os ambientes, ao contrário do resultado obtido a partir da aplicação do índice de Shannon, o qual indicou maior diversidade de espécies na mata nativa. O modelo log-series não se ajustou satisfatoriamente aos dados das comunidades de formigas encontradas na cultura de eucalipto e na mata nativa, mas o modelo log-normal mostrou-se adequado para descrever a estrutura das comunidades dos dois ambientes. O modelo broken-stick, que representa uma comunidade bem estruturada, ajustou-se apenas aos dados da mata nativa.
Resumo:
Introduction Vector seasonality knowledge is important for monitoring and controlling of vector-borne diseases. Lutzomyia longipalpis (Lu. longipalpis) is the main vector of Leishmania (Leishmania) infantum Nicolle, 1908, which is the causative agent of visceral leishmaniasis in the Americas. Methods Lu. longipalpis was monitored for 3 consecutive nights each month using light traps from the Centers for Disease Control in the peridomiciles and intradomiciles of 18 residences from January 2005 to December 2012 in the urban area of Dracena, a medium-sized city located in the western region of São Paulo, Brazil. Results A total of 54,820 Lu. longipalpis specimens were collected, and the proportion of positive samples was significantly higher in the peridomiciles than in the intradomiciles (p<0.05) in all 8 years of the study, except for 2005. The vector was present in all study years in the 9 sub-regions of the city, and the male/female ratio ranged from 3.19 to 4.26. The greatest vector abundance occurred in the first semester and peaked in March, confirming its seasonality. Conclusions The maintenance of this high abundance over an 8-year surveillance period demonstrates the vector adaptation to the urban conditions of the city. These characteristics present a major challenge for preventing human and canine contact with the vector and, consequently, controlling the spread of disease.
Resumo:
The main object of the present paper consists in giving formulas and methods which enable us to determine the minimum number of repetitions or of individuals necessary to garantee some extent the success of an experiment. The theoretical basis of all processes consists essentially in the following. Knowing the frequency of the desired p and of the non desired ovents q we may calculate the frequency of all possi- ble combinations, to be expected in n repetitions, by expanding the binomium (p-+q)n. Determining which of these combinations we want to avoid we calculate their total frequency, selecting the value of the exponent n of the binomium in such a way that this total frequency is equal or smaller than the accepted limit of precision n/pª{ 1/n1 (q/p)n + 1/(n-1)| (q/p)n-1 + 1/ 2!(n-2)| (q/p)n-2 + 1/3(n-3) (q/p)n-3... < Plim - -(1b) There does not exist an absolute limit of precision since its value depends not only upon psychological factors in our judgement, but is at the same sime a function of the number of repetitions For this reasen y have proposed (1,56) two relative values, one equal to 1-5n as the lowest value of probability and the other equal to 1-10n as the highest value of improbability, leaving between them what may be called the "region of doubt However these formulas cannot be applied in our case since this number n is just the unknown quantity. Thus we have to use, instead of the more exact values of these two formulas, the conventional limits of P.lim equal to 0,05 (Precision 5%), equal to 0,01 (Precision 1%, and to 0,001 (Precision P, 1%). The binominal formula as explained above (cf. formula 1, pg. 85), however is of rather limited applicability owing to the excessive calculus necessary, and we have thus to procure approximations as substitutes. We may use, without loss of precision, the following approximations: a) The normal or Gaussean distribution when the expected frequency p has any value between 0,1 and 0,9, and when n is at least superior to ten. b) The Poisson distribution when the expected frequecy p is smaller than 0,1. Tables V to VII show for some special cases that these approximations are very satisfactory. The praticai solution of the following problems, stated in the introduction can now be given: A) What is the minimum number of repititions necessary in order to avoid that any one of a treatments, varieties etc. may be accidentally always the best, on the best and second best, or the first, second, and third best or finally one of the n beat treatments, varieties etc. Using the first term of the binomium, we have the following equation for n: n = log Riim / log (m:) = log Riim / log.m - log a --------------(5) B) What is the minimun number of individuals necessary in 01der that a ceratin type, expected with the frequency p, may appaer at least in one, two, three or a=m+1 individuals. 1) For p between 0,1 and 0,9 and using the Gaussean approximation we have: on - ó. p (1-p) n - a -1.m b= δ. 1-p /p e c = m/p } -------------------(7) n = b + b² + 4 c/ 2 n´ = 1/p n cor = n + n' ---------- (8) We have to use the correction n' when p has a value between 0,25 and 0,75. The greek letters delta represents in the present esse the unilateral limits of the Gaussean distribution for the three conventional limits of precision : 1,64; 2,33; and 3,09 respectively. h we are only interested in having at least one individual, and m becomes equal to zero, the formula reduces to : c= m/p o para a = 1 a = { b + b²}² = b² = δ2 1- p /p }-----------------(9) n = 1/p n (cor) = n + n´ 2) If p is smaller than 0,1 we may use table 1 in order to find the mean m of a Poisson distribution and determine. n = m: p C) Which is the minimun number of individuals necessary for distinguishing two frequencies p1 and p2? 1) When pl and p2 are values between 0,1 and 0,9 we have: n = { δ p1 ( 1-pi) + p2) / p2 (1 - p2) n= 1/p1-p2 }------------ (13) n (cor) We have again to use the unilateral limits of the Gaussean distribution. The correction n' should be used if at least one of the valors pl or p2 has a value between 0,25 and 0,75. A more complicated formula may be used in cases where whe want to increase the precision : n (p1 - p2) δ { p1 (1- p2 ) / n= m δ = δ p1 ( 1 - p1) + p2 ( 1 - p2) c= m / p1 - p2 n = { b2 + 4 4 c }2 }--------- (14) n = 1/ p1 - p2 2) When both pl and p2 are smaller than 0,1 we determine the quocient (pl-r-p2) and procure the corresponding number m2 of a Poisson distribution in table 2. The value n is found by the equation : n = mg /p2 ------------- (15) D) What is the minimun number necessary for distinguishing three or more frequencies, p2 p1 p3. If the frequecies pl p2 p3 are values between 0,1 e 0,9 we have to solve the individual equations and sue the higest value of n thus determined : n 1.2 = {δ p1 (1 - p1) / p1 - p2 }² = Fiim n 1.2 = { δ p1 ( 1 - p1) + p1 ( 1 - p1) }² } -- (16) Delta represents now the bilateral limits of the : Gaussean distrioution : 1,96-2,58-3,29. 2) No table was prepared for the relatively rare cases of a comparison of threes or more frequencies below 0,1 and in such cases extremely high numbers would be required. E) A process is given which serves to solve two problemr of informatory nature : a) if a special type appears in n individuals with a frequency p(obs), what may be the corresponding ideal value of p(esp), or; b) if we study samples of n in diviuals and expect a certain type with a frequency p(esp) what may be the extreme limits of p(obs) in individual farmlies ? I.) If we are dealing with values between 0,1 and 0,9 we may use table 3. To solve the first question we select the respective horizontal line for p(obs) and determine which column corresponds to our value of n and find the respective value of p(esp) by interpolating between columns. In order to solve the second problem we start with the respective column for p(esp) and find the horizontal line for the given value of n either diretly or by approximation and by interpolation. 2) For frequencies smaller than 0,1 we have to use table 4 and transform the fractions p(esp) and p(obs) in numbers of Poisson series by multiplication with n. Tn order to solve the first broblem, we verify in which line the lower Poisson limit is equal to m(obs) and transform the corresponding value of m into frequecy p(esp) by dividing through n. The observed frequency may thus be a chance deviate of any value between 0,0... and the values given by dividing the value of m in the table by n. In the second case we transform first the expectation p(esp) into a value of m and procure in the horizontal line, corresponding to m(esp) the extreme values om m which than must be transformed, by dividing through n into values of p(obs). F) Partial and progressive tests may be recomended in all cases where there is lack of material or where the loss of time is less importent than the cost of large scale experiments since in many cases the minimun number necessary to garantee the results within the limits of precision is rather large. One should not forget that the minimun number really represents at the same time a maximun number, necessary only if one takes into consideration essentially the disfavorable variations, but smaller numbers may frequently already satisfactory results. For instance, by definition, we know that a frequecy of p means that we expect one individual in every total o(f1-p). If there were no chance variations, this number (1- p) will be suficient. and if there were favorable variations a smaller number still may yield one individual of the desired type. r.nus trusting to luck, one may start the experiment with numbers, smaller than the minimun calculated according to the formulas given above, and increase the total untill the desired result is obtained and this may well b ebefore the "minimum number" is reached. Some concrete examples of this partial or progressive procedure are given from our genetical experiments with maize.
Resumo:
Attempting to review the species of sandflies in the series oswaldoi of the subgenus Helcocyrtomyia, we examined 7650 specimens collected in different Brazilian regions during 35 years and deposited in the collection of the Centro de Pesquisas René Rachou, FIOCRUZ, Belo Horizonte, MG. As main results of this study new species of Helcocyrtomyia were described (Lutzomya pusilla and Lutzomya capixaba), in addition to the females of Lutzomyia ferreirana and Lutzomyia peresi; which had been described only by the males. The geographic distribution of the material examined is also presented.
Resumo:
Continuing to review the subgenus Helcocyrtomyia (Diptera, Psychodidae, Phlebotomiane) some specimens of sandflies from the vexator series were examined. Taxonomic remarks, geographic distribution and drawings of those species are presented.
Resumo:
Objective Analyzing the geographical distribution of the tuberculosis (TB), its incidence and prevalence and TB-HIV coinfection in the districts of Porto Alegre from 2007 to 2011. Method An ecological, descriptive study of time series that used descriptive and geoprocessing techniques. Results In total, were recorded 3,369 incident cases and 3,998 prevalent cases of pulmonary TB. In both contexts, there was predominance of cases in males and in Caucasians. Seventeen districts showed prevalence rates above 79.2 cases/100,000 inhabitants, considering that 15 of them had incidence rates above 73.7 cases/100,000 inhabitants. The TB-HIV coinfection rates reached 67% in some districts, which is above the city average value (30%). Conclusion The distribution analysis showed that the reformulation and restructuring of policies and health services in Porto Alegre are essential.
Resumo:
Is it possible to build predictive models (PMs) of soil particle-size distribution (psd) in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index). The PMs explained more than half of the data variance. This performance is similar to (or even better than) that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas. Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available. Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd) of soils in regions of complex geology.
Resumo:
Rust, caused by Puccinia psidii, is one of the most important diseases affecting eucalyptus in Brazil. This pathogen causes disease in mini-clonal garden and in young plants in the field, especially in leaves and juvenile shoots. Favorable climate conditions for infection by this pathogen in eucalyptus include temperature between 18 and 25 ºC, together with at least 6-hour leaf wetness periods, for 5 to 7 consecutive days. Considering the interaction between the environment and the pathogen, this study aimed to evaluate the potential impact of global climate changes on the spatial distribution of areas of risk for the occurrence of eucalyptus rust in Brazil. Thus, monthly maps of the areas of risk for the occurrence of this disease were elaborated, considering the current climate conditions, based on a historic series between 1961 and 1990, and the future scenarios A2 and B2, predicted by IPCC. The climate conditions were classified into three categories, according to the potential risk for the disease occurrence, considering temperature (T) and air relative humidity (RH): i) high risk (18 < T < 25 ºC and RH > 90%); ii) medium risk (18 < T < 25 ºC and RH < 90%; T< 18 or T > 25 ºC and RH > 90%); and iii) low risk (T < 18 or T > 25 ºC and RH < 90%). Data about the future climate scenarios were supplied by GCM Change Fields. In this study, the simulation model Hadley Centers for Climate Prediction and Research (HadCm3) was adopted, using the software Idrisi 32. The obtained results led to the conclusion that there will be a reduction in the area favorable to eucalyptus rust occurrence, and such a reduction will be gradual for the decades of 2020, 2050 and 2080 but more marked in scenario A2 than in B2. However, it is important to point out that extensive areas will still be favorable to the disease development, especially in the coldest months of the year, i.e., June and July. Therefore, the zoning of areas and periods of higher occurrence risk, considering the global climate changes, becomes important knowledge for the elaboration of predicting models and an alert for the integrated management of this disease.
Resumo:
This study aimed to describe the probabilistic structure of the annual series of extreme daily rainfall (Preabs), available from the weather station of Ubatuba, State of São Paulo, Brazil (1935-2009), by using the general distribution of extreme value (GEV). The autocorrelation function, the Mann-Kendall test, and the wavelet analysis were used in order to evaluate the presence of serial correlations, trends, and periodical components. Considering the results obtained using these three statistical methods, it was possible to assume the hypothesis that this temporal series is free from persistence, trends, and periodicals components. Based on quantitative and qualitative adhesion tests, it was found that the GEV may be used in order to quantify the probabilities of the Preabs data. The best results of GEV were obtained when the parameters of this function were estimated using the method of maximum likelihood. The method of L-moments has also shown satisfactory results.
Resumo:
Hepatitis C virus (HCV) infection is widespread and responsible for more than 60% of chronic hepatitis cases. HCV presents a genetic variability which has led to viral classification into at least 6 genotypes and a series of subtypes. These variants present characteristic geographical distribution, but their association with different responses to treatment with interferon and severity of disease still remains controversial. The aim of this study was to investigate the patterns of distribution of HCV genotypes among different exposure categories in Brazil. Two hundred and fifty anti-HCV positive samples were submitted to HCV-RNA detection by RT-PCR and their genotype was determined by restriction fragment length polymorphism (RFLP) analysis. In addition, the genotype/subtype of 60 samples was also determined by a reverse hybridization assay. HCV 1 was the most prevalent (72.0%), followed by type 3 (25.3%), HCV 2 (2.0%) and HCV 4 (0.7%). The HCV genotype distribution varied among the different exposure categories, with HCV 1 being more frequent among blood donors, hemophiliacs and hemodialysis patients. A high frequency of HCV 3 was observed in cirrhotic patients, blood donors from the South of Brazil and injecting drug users (IDUs). The general distribution of the HCV genotype in Brazil is similar to that in other regions of the world.
Resumo:
Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.
Resumo:
Fungal diseases are important factors limiting common bean yield. White mold is one of the main diseases caused by soil pathogens. The objective of this study was to quantify the distribution of a fungicide solution sprayed into the canopy of bean plants by spectrophotometry, using a boom sprayer with and without air assistance. The experiment was arranged in a 2 x 2 x 2 factorial (two types of nozzles, two application rates, and air assistance on and off) randomized block design with four replications. Air assistance influenced the deposition of solution on the bean plant and yield increased significantly with the increased rate of application and air assistance in the boom sprayer.