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Understanding the underlying causes of maternal death across all regions of the world is essential to inform policies and resource allocation to reduce the mortality burden. However, in many countries of the world there exists very little data on the causes of maternal death, and data that do exist do not capture the entire population of risk. In this paper we present a Bayesian hierarchical multinomial model to estimate maternal cause of death distributions globally, regionally and for all countries worldwide. The framework combines data from various sources to inform estimates, including data from civil registration and vital systems, smaller-scale surveys and studies, and high-quality data from confidential enquiries and surveillance systems. The framework accounts of varying data quality and coverage, and allows for situations where one or more causes of death are missing. We illustrate the results of the model on three case study countries that have different data availability situations: Canada, Nigeria and the United States.
In this paper, we clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of the neural activity, as expected, but it can also promote neural reacti
Though they may offer valuable patient and disease information that is impossible to study in a randomized trial, clinical disease registries also require special care and attention in causal inference. Registry data may be incomplete, inconsistent,
Cell fate decisions in multicellular organisms are precisely coordinated, leading to highly reproducible macroscopic outcomes of developmental processes. The origins of this reproducibility can be found at the molecular level during the earliest stag
We explore what causes business cycles by analyzing the Japanese industrial production data. The methods are spectral analysis and factor analysis. Using the random matrix theory, we show that two largest eigenvalues are significant. Taking advantage
Empirical analysis results about the possible causes leading to non-citation may help increase the potential of researchers work to be cited and editorial staffs of journals to identify contributions with potential high quality. In this study, we con