Bayesian Spatio-Temporal Modeling of the Dynamics of COVID-19 Deaths in Peru.

Amid the COVID-19 pandemic, understanding the spatial and temporal dynamics of the disease is crucial for effective public health interventions. This study aims to analyze COVID-19 data in Peru using a Bayesian spatio-temporal generalized linear model to elucidate mortality patterns and assess the impact of vaccination efforts. Leveraging data from 194 provinces over 651 days, our analysis reveals heterogeneous spatial and temporal patterns in COVID-19 mortality rates. Higher vaccination coverage is associated with reduced mortality rates, emphasizing the importance of vaccination in mitigating the pandemic's impact. The findings underscore the value of spatio-temporal data analysis in understanding disease dynamics and guiding targeted public health interventions.

Ethnic-Regional Differences in the Allocation of High Complexity Spending in Brazil: Time Analysis 2010-2019.

The following paper presents as a research problem the ethnic-regional differences in the allocation of high complexity spending in Brazil in an analysis from 2010 to 2019. This is a descriptive research in which a generalized linear model (GLM) was developed to analyze these hospital expenditures with high complexity procedures. The total spending on high complexity procedures in Brazil has increased over the past decade. The study shows that the lowest average expenditures are found in the North and Northeast regions. When comparing the spending between different ethnicities, it was observed that the only decrease between the years 2010 and 2019 was in the amount spent on procedures in indigenous people. The spending on male patients was significantly higher compared to female patients. The highest expenditures, on the other hand, are concentrated in the regions of state capitals favoring the strengthening of hub municipalities. Geographic inequalities in access still persist, even with most states already offering almost all procedures. The Brazilian territory is very heterogeneous and needs to organize its health system by regions, therefore integrated public policies and economic and social development are urgently needed.

Epidemiological Study of the Occurrence of Typhus Group Rickettsia Natural Infection in Domiciliated Dogs from a Rural Community in South-Eastern Mexico.

The aim is to describe the Typhus group (TG) Rickettsia infection in dogs and to identify factors associated with this infection. We collected blood samples and gathered exposure and clinical data of 142 dogs from a rural community of Yucatan. The Rickettsia group was determined by semi-nested PCR. Generalized linear models with binomial error distribution were used to model the associated factors from the dog sample for risk ratio (RR) estimation. Thirty-four dogs (23.9%) showed molecular evidence of TG Rickettsia DNA. The multivariate model showed that mixed-breed dogs (RR = 0.06) and dogs that had received antiparasitic treatment (RR = 0.049) had a lower risk of getting infected, taking as reference the purebred group and the non-treated dogs, respectively. Looking at variable interactions, adult dogs without outdoor activities had a lower infection risk than puppies (RR = 0.26). Among dogs with antiparasitic treatment, females had a higher infection risk than male dogs (RR = 26.2). The results showed enzootic TG Rickettsia circulation in dogs of a rural community. The factors outdoor activities, age and previous antiparasitic treatment, as well as the clinical variables signs of hemorrhages and epistaxis, were associated with a less chance of natural infection in the studied dogs. Prevention and control of the enzootic transmission risk of TG Rickettsia should help to reduce the potential zoonotic transmission of this pathogen.

Farm management practices, biosecurity and influenza a virus detection in swine farms: a comprehensive study in colombia.

Biosecurity protocols (BP) and good management practices are key to reduce the risk of introduction and transmission of infectious diseases into the pig farms. In this observational cross-sectional study, survey data were collected from 176 pig farms with inventories over 100 sows in Colombia. We analyzed a complex survey dataset to explore the structure and identify clustering patterns using Multiple Correspondence Analysis (MCA) of swine farms in Colombia, and estimated its association with Influenza A virus detection. Two principal dimensions contributed to 27.6% of the dataset variation. Farms with highest contribution to dimension 1 were larger farrow-to-finish farms, using self-replacement of gilts and implementing most of the measures evaluated. In contrast, farms with highest contribution to dimension 2 were medium to large farrow-to-finish farms, but implemented biosecurity in a lower degree. Additionally, two farm clusters were identified by Hierarchical Cluster Analysis (HCA), and the odds of influenza A virus detection was statistically different between clusters (OR 7.29, CI: 1.7,66, p = < 0.01). Moreover, after logistic regression analysis, three important variables were associated with higher odds of influenza detection: (1) "location in an area with a high density of pigs", (2) "farm size", and (3) "after cleaning and disinfecting, the facilities are allowed to dry before use". Our results revealed two clustering patterns of swine farms. This systematic analysis of complex survey data identified relationships between biosecurity, husbandry practices and influenza status. This approach helped to identify gaps on biosecurity and key elements for designing successful strategies to prevent and control swine respiratory diseases in the swine industry.

Estimation of actual evapotranspiration in barley crop through a generalized linear model.

Evapotranspiration is a key variable of the water cycle. Its calculation requires several ground data that frequently are not available. This study contains a detailed method and measurements of meteorological and energy balance variables that can be used to estimate the daily actual evapotranspiration (ETa). A linear generalized model is obtained to calculate the ETa from common variables measured in meteorological stations. The method showed a good performance over a barley crop of easthern Argentine Pampas and can be applied and tested in other great plains. Measurements of soil-plant-atmosphere are included The routines to reproduce the method are included The generalized method allows the calculation of daily ETa over crops and was tested over barley crops.

Trace elements in pelagic Sargassum species in the Mexican Caribbean: Identification of key variables affecting arsenic accumulation in S. fluitans.

Since 2014, the Mexican Caribbean beaches have received massive influxes of the brown seaweed Sargassum (S. fluitans III, S. natans I and S. natans VIII), causing serious ecological and economic effects. Concentrations of arsenic (As), cadmium (Cd), copper (Cu), iron (Fe), lead (Pb), and zinc (Zn) were determined over an annual cycle in pelagic Sargassum species from massive influxes into the Mexican Caribbean. The contribution of trace elements, polysaccharides (alginate and fucoidans), and their main functional groups (uronic acids and sulfate) to arsenic content in Sargassum fluitans - the most abundant species in the Sargassum influx - is discussed. Arsenic was recorded in all samples, yielding mean concentrations of 74.2 ± 2.84 mg kg-1. Significant differences were found between species for As, Cu, Fe, and Pb, but not for Cd and Zn; also, S. fluitans showed significant differences in metal content between seasons for all elements, as well as in alginate and uronic acids from fucoidan. The season of the year, copper, iron, uronic acids, and sulfate content in fucoidan were the main variables associated with arsenic accumulation in S. fluitans as evidenced with a Generalized Linear Model. Arsenic content in Sargassum biomass exceeded the maximum allowable level in the rainy season; therefore, the content of this trace element should be carefully monitored for safe usage of Sargassum biomass.

Estimating hidden populations by transferring knowledge from geographically misaligned levels.

The estimation of hidden sub-populations is a hard task that appears in many fields. For example, public health planning in Brazil depends crucially of the number of people who holds a private health insurance plan and hence rarely uses the public services. Different sources of information about these sub-populations may be available at different geographical levels. The available information can be transferred between these different geographic levels to improve the estimation of the hidden population size. In this study, we propose a model that use individual level information to learn about the dependence between the response variable and explanatory variables by proposing a family of link functions with asymptotes that are flexible enough to represent the real aspects of the data and robust to departures from the model. We use the fitted model to estimate the size of the sub-population at any desired level. We illustrate our methodology estimating the sub-population that uses the public health system in each neighborhood of large cities in Brazil.

Univariate Analysis of Short-Chain Fatty Acids Related to Sudden Infant Death Syndrome.

Sudden infant death syndrome (SIDS) is defined as the death of a child under one year of age, during sleep, without apparent cause, after exhaustive investigation, so it is a diagnosis of exclusion. SIDS is the principal cause of death in industrialized countries. Inborn errors of metabolism (IEM) have been related to SIDS. These errors are a group of conditions characterized by the accumulation of toxic substances usually produced by an enzyme defect and there are thousands of them and included are the disorders of the ß-oxidation cycle, similarly to what can affect the metabolism of different types of fatty acid chain (within these, short chain fatty acids (SCFAs)). In this work, an analysis of postmortem SCFAs profiles of children who died due to SIDS is proposed. Initially, a set of features containing SCFAs information, obtained from the NIH Common Fund's National Metabolomics Data Repository (NMDR) is submitted to an univariate analysis, developing a model based on the relationship between each feature and the binary output (death due to SIDS or not), obtaining 11 univariate models. Then, each model is validated, calculating their receiver operating characteristic curve (ROC curve) and area under the ROC curve (AUC) value. For those features whose models presented an AUC value higher than 0.650, a new multivariate model is constructed, in order to validate its behavior in comparison to the univariate models. In addition, a comparison between this multivariate model and a model developed based on the whole set of features is finally performed. From the results, it can be observed that each SCFA which comprises of the SFCAs profile, has a relationship with SIDS and could help in risk identification.

Distribution of the acoustic occurrence of dolphins during the summers 2011 to 2015 in the Upper Gulf of California, Mexico.

Baseline knowledge of spatial and temporal distribution patterns is essential for cetacean management and conservation. Such knowledge is particularly important in areas where gillnet fishing occurs, as the Upper Gulf of California, which increases the probability of bycatch of cetaceans. In this area, the vaquita porpoise (Phocoena sinus) has been widely studied, but the knowledge of other cetaceans is scarce and based on traditional visual survey methods. We used data collected by an array of acoustic click detectors (C-PODs) during the summers 2011 to 2015 to analyze the distribution of dolphins in the Vaquita Refuge in the Upper Gulf of California. We recorded 120,038 echolocation click trains of dolphins during 12,371 days of recording effort at 46 sampling sites. Based on simultaneous visual and acoustic data, we estimated a false positive acoustic detection rate of 19.4%. Dolphin acoustic activity varied among sites, with higher activity in the east of the Vaquita Refuge. Acoustic activity was higher at night than during the day. We used negative binomial generalized linear models to study the count of clicks of dolphins in relation to spatial, temporal, physical, biological and anthropogenic explanatory variables. The best model selected for the response variable included sampling site, day-night condition, and vertical component of tide speed. Patterns in the spatial distribution of predicted acoustic activity of dolphins were similar to the acoustic activity observed per sampling season. Higher acoustic activity was predicted at night, but the tide speed variable was not relevant under this condition. Acoustic activity patterns could be related to the availability of prey resources since echolocation click trains are associated with foraging activities of dolphins. This is the first study of the distribution of dolphins in Mexico using medium-term systematic passive acoustic monitoring, and the results can contribute to better management to the natural protected area located in the Upper Gulf of California.

Towards the optimization of botanical insecticides research: Aedes aegypti larvicidal natural products in French Guiana.

Natural products have proven to be an immeasurable source of bioactive compounds. The exceptional biodiversity encountered in Amazonia, alongside a rich entomofauna and frequent interactions with various herbivores is the crucible of a promising chemodiversity. This prompted us to search for novel botanical insecticides in French Guiana. As this French overseas department faces severe issues linked to insects, notably the strong incidence of vector-borne infectious diseases, we decided to focus our research on products able to control the mosquito Aedes aegypti. We tested 452 extracts obtained from 85 species originating from 36 botanical families and collected in contrasted environments against an Ae. aegypti laboratory strain susceptible to all insecticides, and a natural population resistant to both pyrethroid and organophosphate insecticides collected in Cayenne for the most active of them. Eight species (Maytenus oblongata Reissek, Celastraceae; Costus erythrothyrsus Loes., Costaceae; Humiria balsamifera Aubl., Humiriaceae; Sextonia rubra (Mez) van der Werff, Lauraceae; Piper hispidum Sw., Piperaceae; Laetia procera (Poepp.) Eichl., Salicaceae; Matayba arborescens (Aubl.) Radlk., Sapindaceae; and Cupania scrobitulata Rich., Sapindaceae) led to extracts exhibiting more than 50% larval mortality after 48 h of exposition at 100 µg/mL against the natural population and were considered active. Selectivity and phytochemistry of these extracts were therefore investigated and discussed, and some active compounds highlighted. Multivariate analysis highlighted that solvents, plant tissues, plant family and location had a significant effect on mortality while light, available resources and vegetation type did not. Through this case study we highlighted that plant defensive chemistry mechanisms are crucial while searching for novel insecticidal products.

Longitudinal Analysis of Ventilation Perfusion Mismatch in Congenital Diaphragmatic Hernia Survivors.

OBJECTIVE: To determine the natural history of pulmonary function for survivors of congenital diaphragmatic hernia (CDH). STUDY DESIGN: This was a retrospective cohort study of survivors of CDH born during 1991-2016 and followed at our institution. A generalized linear model was fitted to assess the longitudinal trends of ventilation (V), perfusion (Q), and V/Q mismatch. The association between V/Q ratio and body mass index percentile as well as functional status was also assessed with a generalized linear model. RESULTS: During the study period, 212 patients had at least one V/Q study. The average ipsilateral V/Q of the cohort increased over time (P < .01), an effect driven by progressive reduction in relative perfusion (P = .012). A higher V/Q ratio was correlated with lower body mass index percentile (P < .001) and higher probability of poor functional status (New York Heart Association class III or IV) (P = .045). CONCLUSIONS: In this cohort of survivors of CDH with more severe disease characteristics, V/Q mismatch worsens over time, primarily because of progressive perfusion deficit of the ipsilateral side. V/Q scans may be useful in identifying patients with CDH who are at risk for poor growth and functional status.

Leaf count overdispersion in coffee seedlings / Superdispersão relacionado a contagem de folhas em mudas de cafeeiro

Coffee crops play an important role in Brazilian agriculture, with a high level of social and economic participation resulting from the jobs created in the supply chain and from the income obtained by producers and the revenue generated for the country from coffee bean export. In coffee plant growth, leaves have a determinant role in higher production; therefore, the leaf count per plant provides relevant information to producers for adequate crop management, such as foliar fertilizer applications. To describe count data, the Poisson model is the most commonly employed model; when count data show overdispersion, the negative binomial model has been determined to be more adequate. The objective of this study was to compare the fitness of the Poisson and negative binomial models to data on the leaf count per plant in coffee seedlings. Data were collected from an experiment with a randomized block design with 30 treatments and three replicates and four plants per plot. Data from only one treatment, in which the number of leaves was counted over time, were employed. The first count was conducted on 8 April 2016, and the other counts were performed 18, 32, 47, 62, 76, 95, 116, 133, and 153 days after the first evaluation, for a total of ten measurements. The fitness of the models was assessed based on deviance values and simulated envelopes for residuals. Results of fitness assessment indicated that the Poisson model was inadequate for describing the data due to overdispersion. The negative binomial model adequately fitted the observations and was indicated to describe the number of leaves of coffee plants. Based on the negative binomial model, the expected relative increase in the number of leaves was 0.9768% per day.(AU)

A cultura do café desempenha papel relevante na agricultura do Brasil, com expressiva participação social e econômica tanto pelos empregos gerados na cadeia produtiva, bem como pela renda obtida pelos produtores e pelas divisas geradas para o país na exportação do grão. No crescimento das plantas de café, as folhas desempenham papel decisivo para que tenha maior produção, portanto a contagem do número de folhas por planta fornece informações importantes aos produtores para o manejo adequado da cultura como, por exemplo, a aplicação de adubações foliares. Em geral, na descrição de dados obtidos por contagem, o modelo mais utilizado é o Poisson, sendo que quando os dados apresentam superdispersão, o modelo Binomial Negativo tem se mostrado mais adequado. O objetivo deste trabalho foi comparar o ajuste dos modelos de Poisson e Binomial Negativo em dados de contagens do número de folhas por planta em mudas do cafeeiro. Os dados foram obtidos de um experimento usando o delineamento em blocos casualizados com trinta tratamentos e três repetições com quatro plantas por parcela. Foram utilizados os dados de apenas um tratamento no qual foi feita a contagem do número de folhas ao longo do tempo. A primeira avaliação foi feita em 8 de abril de 2016 e as demais aos 18, 32, 47, 62, 76, 95, 116, 133 e 153 dias após a primeira avaliação, totalizando dez medidas. A adequação dos mesmos foi verificada com base nos valores da Deviance e no envelope simulado para os resíduos. Os resultados do ajuste indicaram que o modelo Poisson foi inadequado para descrição dos dados devido a superdispersão. O modelo Binomial Negativo se ajustou adequadamente e foi indicado para descrever o número de folhas das plantas do cafeeiro. Com base no modelo Binomial Negativo o aumento relativo esperado para o número de folhas foi de 0,9768% para cada dia.(AU)

Evaluating elbow osteoarthritis within the prehistoric Tiwanaku state using generalized estimating equations (GEE).

OBJECTIVES: Studies of osteoarthritis (OA) in human skeletal remains can come with scalar problems. If OA measurement is noted as present or absent in one joint, like the elbow, results may not identify specific articular pathology data and the sample size may be insufficient to address research questions. If calculated on a per data point basis (i.e., each articular surface within a joint), results may prove too data heavy to comprehensively understand arthritic changes, or one individual with multiple positive scores may skew results and violate the data independence required for statistical tests. The objective of this article is to show that the statistical methodology Generalized Estimating Equations (GEE) can solve scalar issues in bioarchaeological studies. MATERIALS AND METHODS: Using GEE, a population-averaged statistical model, 1,195 adults from the core and one colony of the prehistoric Tiwanaku state (AD 500-1,100) were evaluated bilaterally for OA on the seven articular surfaces of the elbow joint. RESULTS: GEE linked the articular surfaces within each individual specimen, permitting the largest possible unbiased dataset, and showed significant differences between core and colony Tiwanaku peoples in the overall elbow joint, while also pinpointing specific articular surfaces with OA. Data groupings by sex and age at death also demonstrated significant variation. A pattern of elbow rotation noted for core Tiwanaku people may indicate a specific pattern of movement. DISCUSSION: GEE is effective and should be encouraged in bioarchaeological studies as a way to address scalar issues and to retain all pathology information.

Leaf count overdispersion in coffee seedlings / Superdispersão relacionado a contagem de folhas em mudas de cafeeiro

ABSTRACT: Coffee crops play an important role in Brazilian agriculture, with a high level of social and economic participation resulting from the jobs created in the supply chain and from the income obtained by producers and the revenue generated for the country from coffee bean export. In coffee plant growth, leaves have a determinant role in higher production; therefore, the leaf count per plant provides relevant information to producers for adequate crop management, such as foliar fertilizer applications. To describe count data, the Poisson model is the most commonly employed model; when count data show overdispersion, the negative binomial model has been determined to be more adequate. The objective of this study was to compare the fitness of the Poisson and negative binomial models to data on the leaf count per plant in coffee seedlings. Data were collected from an experiment with a randomized block design with 30 treatments and three replicates and four plants per plot. Data from only one treatment, in which the number of leaves was counted over time, were employed. The first count was conducted on 8 April 2016, and the other counts were performed 18, 32, 47, 62, 76, 95, 116, 133, and 153 days after the first evaluation, for a total of ten measurements. The fitness of the models was assessed based on deviance values and simulated envelopes for residuals. Results of fitness assessment indicated that the Poisson model was inadequate for describing the data due to overdispersion. The negative binomial model adequately fitted the observations and was indicated to describe the number of leaves of coffee plants. Based on the negative binomial model, the expected relative increase in the number of leaves was 0.9768% per day.

RESUMO: A cultura do café desempenha papel relevante na agricultura do Brasil, com expressiva participação social e econômica tanto pelos empregos gerados na cadeia produtiva, bem como pela renda obtida pelos produtores e pelas divisas geradas para o país na exportação do grão. No crescimento das plantas de café, as folhas desempenham papel decisivo para que tenha maior produção, portanto a contagem do número de folhas por planta fornece informações importantes aos produtores para o manejo adequado da cultura como, por exemplo, a aplicação de adubações foliares. Em geral, na descrição de dados obtidos por contagem, o modelo mais utilizado é o Poisson, sendo que quando os dados apresentam superdispersão, o modelo Binomial Negativo tem se mostrado mais adequado. O objetivo deste trabalho foi comparar o ajuste dos modelos de Poisson e Binomial Negativo em dados de contagens do número de folhas por planta em mudas do cafeeiro. Os dados foram obtidos de um experimento usando o delineamento em blocos casualizados com trinta tratamentos e três repetições com quatro plantas por parcela. Foram utilizados os dados de apenas um tratamento no qual foi feita a contagem do número de folhas ao longo do tempo. A primeira avaliação foi feita em 8 de abril de 2016 e as demais aos 18, 32, 47, 62, 76, 95, 116, 133 e 153 dias após a primeira avaliação, totalizando dez medidas. A adequação dos mesmos foi verificada com base nos valores da Deviance e no envelope simulado para os resíduos. Os resultados do ajuste indicaram que o modelo Poisson foi inadequado para descrição dos dados devido a superdispersão. O modelo Binomial Negativo se ajustou adequadamente e foi indicado para descrever o número de folhas das plantas do cafeeiro. Com base no modelo Binomial Negativo o aumento relativo esperado para o número de folhas foi de 0,9768% para cada dia.

Assessing Atlantic sailfish catch rates based on Brazilian sport fishing tournaments (1996-2014) / Avaliação das taxas de captura do agulhão-vela baseado nos torneios de pesca esportiva brasileira (1996-2014)

In the present study, a generalized linear model (GLM), assuming a Tweedie distribution and log as link function, was used to generate a standardized catch per unit effort (CPUE) series for the sailfish caught by sport fishing boats based in São Paulo, Rio de Janeiro, Espírito Santo and Bahia States, from 1996 to 2014. The response variable was the number of sailfish caught per number of boats registered in the tournament per day. The following factors were tested in the analyses: "year", "month", and "local", representing the main effects of the explanatory variables. The overall pattern of the standardized catch rate indicates a relatively stable trend with a slight decline in the recent years, from 2009 to 2014.(AU)

No presente trabalho, um modelo linear generalizado (GLM) assumindo a distribuição de tweedie e função link log, foi utilizado para gerar uma série de captura por unidade de esforço (CPUE) para o agulhão-vela capturado pela pesca esportiva baseada nos estados de São Paulo, Rio de Janeiro, Espirito Santo e Bahia de 1996 a 2014. A variável resposta foi o número de agulhões-vela capturados pelo número de embarcações registradas por dia de torneio. Os seguintes fatores foram testados: "ano", "mês", e "local", representando as principais variáveis explicativas do modelo. O padrão geral da série de CPUE padronizada indica uma tendência relativamente estável com um leve declínio nos anos recentes entre 2009 e 2014.(AU)

Assessing Atlantic sailfish catch rates based on Brazilian sport fishing tournaments (1996-2014) / Avaliação das taxas de captura do agulhão-vela baseado nos torneios de pesca esportiva brasileira (1996-2014)

In the present study, a generalized linear model (GLM), assuming a Tweedie distribution and log as link function, was used to generate a standardized catch per unit effort (CPUE) series for the sailfish caught by sport fishing boats based in São Paulo, Rio de Janeiro, Espírito Santo and Bahia States, from 1996 to 2014. The response variable was the number of sailfish caught per number of boats registered in the tournament per day. The following factors were tested in the analyses: "year", "month", and "local", representing the main effects of the explanatory variables. The overall pattern of the standardized catch rate indicates a relatively stable trend with a slight decline in the recent years, from 2009 to 2014.

No presente trabalho, um modelo linear generalizado (GLM) assumindo a distribuição de tweedie e função link log, foi utilizado para gerar uma série de captura por unidade de esforço (CPUE) para o agulhão-vela capturado pela pesca esportiva baseada nos estados de São Paulo, Rio de Janeiro, Espirito Santo e Bahia de 1996 a 2014. A variável resposta foi o número de agulhões-vela capturados pelo número de embarcações registradas por dia de torneio. Os seguintes fatores foram testados: "ano", "mês", e "local", representando as principais variáveis explicativas do modelo. O padrão geral da série de CPUE padronizada indica uma tendência relativamente estável com um leve declínio nos anos recentes entre 2009 e 2014.

Estimación del descarte por exceso de captura en la pesquería industrial de cerco del stock Norte-Centro de la anchoveta peruana Engraulis ringens a partir de un programa de observación a bordo / Estimating discard excess catch in the industrial purse seine fisheries of the North-Center stock of the Peruvian anchoveta (Engraulis ringens) from an on-board observer program

En este trabajo se presenta la estimación del descarte por exceso de captura en la pesquería industrial de cerco del stock Norte-Centro de anchoveta peruana. Se define el descarte por exceso de captura, como la porción de captura que se arroja al mar cuando se ha capturado más de lo que la capacidad de bodega de la embarcación puede almacenar. El análisis de estimación para el periodo 2005 - 2014, se realizó a partir del "Programa de observadores a bordo de la flota de cerco" que ejecuta el Instituto del Mar del Perú (IMARPE), en donde 5 837 viajes, que representan el 1.6% de los viajes totales, fueron muestreados. Las metodologías utilizadas en la estimación fueron: Modelo Lineal Generalizado (GLM) y el Modelo Delta. Las estimaciones por el Modelo Delta y el GLM fueron diferentes en magnitudes pero similares en tendencias, sin embargo la evaluación del funcionamiento del Modelo Delta, indica que este modelo se ajusta mejor a los datos. El Modelo Delta estimó que la pesquería descarta por exceso de captura entre 2 954 y 199 164 toneladas, con un promedio de 121 312 toneladas para el periodo de estudio, el cual representó una tasa del 2.6% en relación a los desembarques. Se sugiere la incorporación de variables espaciales (p. ej. distancia a la costa, latitud, longitud), físicas (TSM) y del comportamiento del cardumen (p.e. agregación), para mejorar el análisis y comprender mejor el comportamiento de este tipo de descarte.

This paper presents estimates of the discard excess catch in the industrial purse seine fisheries of the North-Center stock of the Peruvian anchoveta (Engraulis ringens). Discard excess catch is defined as the portion of the catch that is thrown into the sea when has captured more than the hold capacity can store. The analysis is based on the "On-board observer of the purse seine vessels program" led by the Instituto del Mar del Peru (IMARPE), and in the period 2005 - 2014, 5837 trips were sampled, corresponding to 1.6% of the total trips. The methodologies used in the discard excess catch estimation were: Generalized Linear Model (GLM) and Delta Model. The estimations showed difference in magnitudes but similar trends, although the delta model appears to be a better alternative procedure for estimating the discard excess catch. The Delta Model estimated the purse seine fisheries discarded a range from 2954 to 199 164 tons, an average estimated 121 312 tons, which represent 2.6% of the landings in the period 2005 - 2014. Spatial variables (e.g. distance from the shore, latitude, longitude), physical (SST), and school behavior (e.g. fish aggregation) should be included to improve the analysis and a better understanding of the discard excess catch behavior.

Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle.

Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals.

Validation of the gravity model in predicting the global spread of influenza.

The gravity model is often used in predicting the spread of influenza. We use the data of influenza A (H1N1) to check the model's performance and validation, in order to determine the scope of its application. In this article, we proposed to model the pattern of global spread of the virus via a few important socio-economic indicators. We applied the epidemic gravity model for modelling the virus spread globally through the estimation of parameters of a generalized linear model. We compiled the daily confirmed cases of influenza A (H1N1) in each country as reported to the WHO and each state in the USA, and established the model to describe the relationship between the confirmed cases and socio-economic factors such as population size, per capita gross domestic production (GDP), and the distance between the countries/states and the country where the first confirmed case was reported (i.e., Mexico). The covariates we selected for the model were all statistically significantly associated with the global spread of influenza A (H1N1). However, within the USA, the distance and GDP were not significantly associated with the number of confirmed cases. The combination of the gravity model and generalized linear model provided a quick assessment of pandemic spread globally. The gravity model is valid if the spread period is long enough for estimating the model parameters. Meanwhile, the distance between donor and recipient communities has a good gradient. Besides, the spread should be at the early stage if a single source is taking into account.

Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr × Holstein F2 population.

Now a days, an important and interesting alternative in the control of tick-infestation in cattle is to select resistant animals, and identify the respective quantitative trait loci (QTLs) and DNA markers, for posterior use in breeding programs. The number of ticks/animal is characterized as a discrete-counting trait, which could potentially follow Poisson distribution. However, in the case of an excess of zeros, due to the occurrence of several noninfected animals, zero-inflated Poisson and generalized zero-inflated distribution (GZIP) may provide a better description of the data. Thus, the objective here was to compare through simulation, Poisson and ZIP models (simple and generalized) with classical approaches, for QTL mapping with counting phenotypes under different scenarios, and to apply these approaches to a QTL study of tick resistance in an F2 cattle (Gyr × Holstein) population. It was concluded that, when working with zero-inflated data, it is recommendable to use the generalized and simple ZIP model for analysis. On the other hand, when working with data with zeros, but not zero-inflated, the Poisson model or a data-transformation-approach, such as square-root or Box-Cox transformation, are applicable.