RESUMO Objetivo: Estimar as taxas de notificação de casos de doença pelo coronavírus 2019 (COVID-19) para o Brasil em geral e em todos os estados. Métodos: Estimamos o número real de casos de COVID-19 utilizando o número de óbitos notificados no Brasil e em cada estado e a proporção entre casos e letalidade, conforme a Organização Mundial da Saúde. A proporção entre casos e letalidade prevista para o Brasil foi também ajustada segundo a pirâmide de idade populacional. Assim, a taxa de notificações pode ser definida como o número de casos confirmados (informados pelo Ministério da Saúde) dividido pelo número de casos previstos (estimado a partir do número de óbitos). Resultados: A taxa de notificação de COVID-19 no Brasil foi estimada em 9,2% (IC95%: 8,8% - 9,5%), sendo que, em todos os estados, as taxas encontradas foram inferiores a 30%. São Paulo e Rio de Janeiro, os estados mais populosos do país, mostraram baixas taxas de notificação (8,9% e 7,2%, respectivamente). A taxa de notificação mais alta ocorreu em Roraima (31,7%) e a mais baixa na Paraíba (3,4%). Conclusão: Os resultados indicam que a notificação de casos confirmados no Brasil é muito abaixo da encontrada em outros países que avaliamos. Assim, os responsáveis pela tomada de decisões, inclusive os governos, não têm conhecimento da real dimensão da pandemia, o que pode prejudicar a determinação das medidas de controle.

ABSTRACT Objective: To estimate the reporting rates of coronavirus disease 2019 (COVID-19) cases for Brazil as a whole and states. Methods: We estimated the actual number of COVID-19 cases using the reported number of deaths in Brazil and each state, and the expected case-fatality ratio from the World Health Organization. Brazil’s expected case-fatality ratio was also adjusted by the population’s age pyramid. Therefore, the notification rate can be defined as the number of confirmed cases (notified by the Ministry of Health) divided by the number of expected cases (estimated from the number of deaths). Results: The reporting rate for COVID-19 in Brazil was estimated at 9.2% (95%CI 8.8% - 9.5%), with all the states presenting rates below 30%. São Paulo and Rio de Janeiro, the most populated states in Brazil, showed small reporting rates (8.9% and 7.2%, respectively). The highest reporting rate occurred in Roraima (31.7%) and the lowest in Paraiba (3.4%). Conclusion: The results indicated that the reporting of confirmed cases in Brazil is much lower as compared to other countries we analyzed. Therefore, decision-makers, including the government, fail to know the actual dimension of the pandemic, which may interfere with the determination of control measures.

RESUMO Objetivo: Analisar as medidas adotadas por países que demonstraram controle sobre a transmissão da doença pelo novo coronavírus 2019 (COVID-19) e também como cada curva de casos acumulados se comportou após a implantação dessas medidas. Métodos: A metodologia adotada para este estudo compreendeu três fases: sistematização das medidas de controle adotadas por diferentes países, identificação dos pontos de inflexão na curva do crescimento do número de casos nesses países e análise específica dos dados brasileiros. Resultados: Observamos que China (excluindo-se Hubei), Hubei e Coreia do Sul foram eficazes na desaceleração das taxas de crescimento dos casos de COVID-19. A eficácia das medidas tomadas por esses países pode ser observada após 1 ou 2 semanas de sua aplicação. Na Itália e Espanha, foram tomadas medidas de controle em nível nacional em uma fase tardia da epidemia, o que pode ter contribuído para a elevada propagação da COVID-19. No Brasil, Rio de Janeiro e São Paulo adotaram medidas que podem ter sido eficazes na redução da rapidez da propagação do vírus, entretanto, só temos expectativa de ver seus efeitos no crescimento da curva nos próximos dias. Conclusão: Nossos resultados podem ajudar os responsáveis pela tomada de decisões em países em estágios relativamente precoces da epidemia, especialmente no Brasil, a compreenderem a importância das medidas de controle para desaceleração da curva de crescimento de casos confirmados.

ABSTRACT Objective: To analyse the measures adopted by countries that have shown control over the transmission of coronavirus disease 2019 (COVID-19) and how each curve of accumulated cases behaved after the implementation of those measures. Methods: The methodology adopted for this study comprises three phases: systemizing control measures adopted by different countries, identifying structural breaks in the growth of the number of cases for those countries, and analyzing Brazilian data in particular. Results: We noted that China (excluding Hubei Province), Hubei Province, and South Korea have been effective in their deceleration of the growth rates of COVID-19 cases. The effectiveness of the measures taken by these countries could be seen after 1 to 2 weeks of their application. In Italy and Spain, control measures at the national level were taken at a late stage of the epidemic, which could have contributed to the high propagation of COVID-19. In Brazil, Rio de Janeiro and São Paulo adopted measures that could be effective in slowing the propagation of the virus. However, we only expect to see their effects on the growth of the curve in the coming days. Conclusion: Our results may help decisionmakers in countries in relatively early stages of the epidemic, especially Brazil, understand the importance of control measures in decelerating the growth curve of confirmed cases.

ABSTRACT One of the most important activities in the oil and gas industry is the intervention in wellsfor maintenance services, which is necessary to ensure the constant production of oil. These interventions are carried out by workover rigs. Thus, the Workover Rig Scheduling Problem (WRSP) consists of finding the best schedule to service the wells while considering the limited number of rigs with the objective of minimizing the total production loss. In this study, a 0-1 integer linear programming model capable of efficiently solving the WRSP with a homogeneous fleet of rigs is proposed. Computational experiments were carried out using instances based on real cases in Brazil to compare the results obtained by the proposed model with the results reported by other methods. The proposed model was capable of solving all instances considered in a reduced computational time, including the large instances for which only approximatesolutions were presently known.

The theories of transaction cost economics (TCE) and the resource-based view (RBV) have been applied in studies of outsourcing. The research presented in this study was conducted to gain an understanding of why firms outsource their value chain activities, using a combined TCE and RBV perspective. The research assesses how six instant coffee firms in Brazil perceive the rationale for their outsourcing processes. The authors conclude that the two theories should be used together to determine a firm's frontiers, and they offer a mechanism for combining them. The results, relevant to both academics and practitioners, reveal that outsourcing should be defined at two stages: an initial strategic stage in which the activities that should be performed internally are identified, based on RBV, and a second stage in which the activities that can be performed externally are examined and those that should be outsourced are identified on the basis of both TCE and RBV. Insights relevant to practitioners include the importance of the executive leadership role in defining a firm's outsourcing strategy and the need for constant vigilance to prevent opportunism in relationships with trading partners.

This paper presents the application of a stochastic Benders decomposition algorithm for the problem of supply chain investment planning under uncertainty applied to the petroleum byproducts supply chain. The uncertainty considered is related with the unknown demand levels for oil products. For this purpose, a model was developed based on two-stage stochastic programming. It is proposed two different solution methodologies, one based on the classical cutting plane approach presented by Van Slyke & Wets (1969), and other, based on a multi cut extension of it, firstly introduced by Birge & Louveaux (1988). The methods were evaluated on a real sized case study. Preliminary numerical results obtained from computational experiments are encouraging.

The evaluation of suppliers’ performance is important for organizations because of the imperative role they play in the supply chains and the importance that purchasing functions have due to the outsourcing of activities which are not part of the company’s know-how. There is a need to work on the identification of practical problems concerning the design and implementation of supplier performance measurement systems (SPMS). This paper presents the most important factors in designing and implementing such systems through an action research in a multinational media enterprise. In addition to the details of the method and results of its application, the paper presents an analysis of processes and attributes that define the design of the proposed system. The authors aim to contribute to the academic literature in providing practical issues regarding SPMS.

La evaluación de los proveedores es importante para las organizaciones debido al papel preponderante que éstos cumplen en la dinámica de las cadenas de suministros y a la importancia estratégica que las funciones de compra tienen a raíz de la tercerización de los procesos que no forman parte del know-how de la empresa. No obstante, la literatura académica carece de trabajos concernientes al diseño e implementación de sistemas de medición de desempeño de proveedores (SMDP). En ese contexto, este artículo presenta los factores más importantes del diseño de un SMDP, resaltando, a través de un caso de estudio, los cuidados y recomendaciones que deben ser considerados. Además del detalle del método y los resultados de su aplicación, el artículo presenta el análisis de los procesos y atributos que definen el diseño del SMDP propuesto.