Double coverage and demand for health care: Evidence from quantile regression

An individual experiences double coverage when he bene ts from more than one health insurance plan at the same time. This paper examines the impact of such supplementary insurance on the demand for health care services. Its novelty is that within the context of count data modelling and without imposing restrictive parametric assumptions, the analysis is carried out for di¤erent points of the conditional distribution, not only for its mean location. Results indicate that moral hazard is present across the whole outcome distribution for both public and private second layers of health insurance coverage but with greater magnitude in the latter group. By looking at di¤erent points we unveil that stronger double coverage e¤ects are smaller for high levels of usage. We use data for Portugal, taking advantage of particular features of the public and private protection schemes on top of the statutory National Health Service. By exploring the last Portuguese Health Survey, we were able to evaluate their impacts on the consumption of doctor visi

Clinical patterns and seasonal trends in respiratory syncytial virus hospitalizations in São Paulo, Brazil

The respiratory viruses are recognized as the most frequent lower respiratory tract pathogens for infants and young children in developed countries but less is known for developing populations. The authors conducted a prospective study to evaluate the occurrence, clinical patterns, and seasonal trends of viral infections among hospitalized children with lower respiratory tract disease (Group A). The presence of respiratory viruses in children's nasopharyngeal was assessed at admission in a pediatric ward. Cell cultures and immunofluorescence assays were used for viral identification. Complementary tests included blood and pleural cultures conducted for bacterial investigation. Clinical data and radiological exams were recorded at admission and throughout the hospitalization period. To better evaluate the results, a non- respiratory group of patients (Group B) was also constituted for comparison. Starting in February 1995, during a period of 18 months, 414 children were included- 239 in Group A and 175 in Group B. In Group A, 111 children (46.4%) had 114 viruses detected while only 5 children (2.9%) presented viruses in Group B. Respiratory Syncytial Virus was detected in 100 children from Group A (41.8%), Adenovirus in 11 (4.6%), Influenza A virus in 2 (0.8%), and Parainfluenza virus in one child (0.4%). In Group A, aerobic bacteria were found in 14 cases (5.8%). Respiratory Syncytial Virus was associated to other viruses and/or bacteria in six cases. There were two seasonal trends for Respiratory Syncytial Virus cases, which peaked in May and June. All children affected by the virus were younger than 3 years of age, mostly less than one year old. Episodic diffuse bronchial commitment and/or focal alveolar condensation were the clinical patterns more often associated to Respiratory Syncytial Virus cases. All children from Group A survived. In conclusion, it was observed that Respiratory Syncytial Virus was the most frequent pathogen found in hospitalized children admitted for severe respiratory diseases. Affected children were predominantly infants and boys presenting bronchiolitis and focal pneumonias. Similarly to what occurs in other subtropical regions, the virus outbreaks peak in the fall and their occurrence extends to the winter, which parallels an increase in hospital admissions due to respiratory diseases.

Seasonal variation of hepatitis A virus infection in the city of Rio de Janeiro, Brazil

Hepatitis A virus (HAV) infection constitutes a major public health problem in Brazil. The transmission of HAV is primarily by fecal-oral route so the water is an important vehicle of HAV dissemination. There is a great incidence of acute cases of hepatitis A in some areas of Brazil however the seasonal variation of these cases was not documented. The aim of this study was to determine the seasonality of HAV infection in Rio de Janeiro. From January 1999 to December 2001, 1731 blood samples were collected at the National Reference Center for Hepatitis Viruses in Brazil (NRCHV). These samples were tested by a commercial enzyme-immunoassay to detect anti-HAV IgM antibodies. Yearly positive rates were 33.74% in 1999, 32.19% in 2000, and 30.63% in 2001. A seasonal variation was recognized with the highest incidence in spring and summer. Furthermore a seasonal increase in incidence of HAV infection was found during the rainy season (December to March) because the index of rains is very high. It is concluded that HAV infections occur all year round with a peak during hot seasons with great number of rains.

Stackelberg leadership with demand uncertainty in a differentiated duopoly

On a symmetric differentiated Stackelberg duopoly model in which there is asymmetric demand information owned by leading and follower firms, we show that the leading firm does not necessarily have advantage over the following one. The reason for this is that the second mover can adjust its output level after observing the realized demand, while the first mover chooses its output level only with the knowledge of demand distribution.

Quantity-setting competition under uncertain demand

We consider a quantity-setting duopoly model, and we study the decision to move first or second, by assuming that. the firms produce homogeneous goods and that. there is some demand uncertainty. The competitive phase consists of two periods, and in either period, the firms can make a production decision that is irreversible. As far as the firms are allowed to choose (non-cooperatively) the period they make the decision, we study the circumstances that favour sequential rather than simultaneous decisions.

Stackelberg duopoly with demand uncertainty

We consider a symmetric Stackelberg model in which there is asymmetric demand information owned by first and second movers. We analyse the advantages of leadership and flexibility, and prove that when the leading firm faces demand uncertainty, but the follower does not, the first mover does not necessarily have advantage over the second mover. Moreover, we show that the advantage of one firm over the other depends upon the demand fluctuation and also upon the degree of substitutability of the products.

Flexibility and leadership advantages in a model with uncertain demand

We consider a differentiated Stackelberg model with demand uncertainty only for the first mover. We study the advantages of flexibility over leadership as the degree of the differentiation of the goods changes.

Demand Response Programs Design and Use Considering Intensive Penetration of Distributed Generation

Further improvements in demand response programs implementation are needed in order to take full advantage of this resource, namely for the participation in energy and reserve market products, requiring adequate aggregation and remuneration of small size resources. The present paper focuses on SPIDER, a demand response simulation that has been improved in order to simulate demand response, including realistic power system simulation. For illustration of the simulator’s capabilities, the present paper is proposes a methodology focusing on the aggregation of consumers and generators, providing adequate tolls for the demand response program’s adoption by evolved players. The methodology proposed in the present paper focuses on a Virtual Power Player that manages and aggregates the available demand response and distributed generation resources in order to satisfy the required electrical energy demand and reserve. The aggregation of resources is addressed by the use of clustering algorithms, and operation costs for the VPP are minimized. The presented case study is based on a set of 32 consumers and 66 distributed generation units, running on 180 distinct operation scenarios.

A multi-objective model for scheduling of short-term incentive-based demand response programs offered by electricity retailers

In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem.

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

Fexofenadine is Efficacious and Safe in Children (Aged 6-11 Years) with Seasonal Allergic Rhinitis

Background: This is the first prospective, randomized, doubleblind, placebo-controlled study showing statistical improvement of an H1-antihistamine in children with seasonal allergic rhinitis in all symptoms throughout the entire treatment period. Objective: This randomized, placebo-controlled, parallelgroup,double-blind study was performed to assess the efficacy and safety of fexofenadine in children with seasonal allergic rhinitis. Methods: This study was conducted at 148 centers in 15 countries. Nine hundred thirty-five children (aged 6-11 years) were randomized and treated with either fexofenadine HCl 30 mg (n = 464) or placebo (n = 471) tablets twice a day for 14 days. Individual symptoms (sneezing; rhinorrhea; itchy nose, mouth, throat, and/or ears; itchy, watery, and/or red eyes; and nasal congestion) were assessed at baseline and then daily at 7:00 AM and 7:00 PM (±1 hour) during the double-blind treatment period. Each total symptom score was the sum of all symptoms, excluding nasal congestion. The primary efficacy variable was the change from baseline in the average of the daily 12-hour evening reflective total symptom scores throughout the double-blind treatment. Safety was evaluated from adverse-event reporting, vital signs, physical examinations, and clinical laboratory data at screening and study end point.

SEASONAL DISTRIBUTION OF MALARIA VECTORS (DIPTERA: CULICIDAE) IN RURAL LOCALITIES OF PORTO VELHO, RONDÔNIA, BRAZILIAN AMAZON

We conducted a survey of the malaria vectors in an area where a power line had been constructed, between the municipalities of Porto Velho and Rio Branco, in the states of Rondônia and Acre, respectively. The present paper relates to the results of the survey of Anopheles fauna conducted in the state of Rondônia. Mosquito field collections were performed in six villages along the federal highway BR 364 in the municipality of Porto Velho, namely Porto Velho, Jaci Paraná, Mutum Paraná, Vila Abunã, Vista Alegre do Abunã, and Extrema. Mosquito captures were performed at three distinct sites in each locality during the months of February, July, and October 2011 using a protected human-landing catch method; outdoor and indoor captures were conducted simultaneously at each site for six hours. In the six sampled areas, we captured 2,185 mosquitoes belonging to seven Anopheles species. Of these specimens, 95.1% consisted of Anopheles darlingi, 1.8% An. triannulatus l.s., 1.7% An. deaneorum, 0.8% An. konderi l.s., 0.4 An. braziliensis, 0.1% An. albitarsis l.s., and 0.1% An. benarrochi. An. darlingi was the only species found in all localities; the remaining species occurred in sites with specific characteristics.

The effect of demand information sharing in a supply chain under demand uncertainty: a simulation study

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial