Levels and Trends of Maternal Mortality and Morbidity by Cause in North Africa and Middle East, 1990 to 2019: An Analysis for the Global Burden of Disease Study 2019

Background: Since 1990, the maternal mortality significantly decreased at global scale as well as the North Africa and Middle East. However, estimates for mortality and morbidity by cause and age at national scale in this region are not available. Method(s): This study is part of the Global Burden of Diseases, Injuries, and Risk Factors study (GBD) 2019. Here we report maternal mortality and morbidity by age and cause across 21 countries in the region from 1990 to 2019. Result(s): Between 1990 and 2019, maternal mortality ratio (MMR) dropped from 148.8 (129.6-171.2) to 94.3 (73.4-121.1) per 100 000 live births in North Africa and Middle East. In 1990, MMR ranged from 6.0 (5.3-6.8) in Kuwait to 502.9 (375.2-655.3) per 100 000 live births in Afghanistan. Respective figures for 2019 were 5.1 (4.0-6.4) in Kuwait to 269.9 (195.8-368.6) in Afghanistan. Percentages of deaths under 25 years was 26.0% in 1990 and 23.8% in 2019. Maternal hemorrhage, indirect maternal deaths, and other maternal disorders rank 1st to 3rd in the entire region. Ultimately, there was an evident decrease in MMR along with increase in socio-demographic index from 1990 to 2019 in all countries in the region and an evident convergence across nations. Conclusion(s): MMR has significantly declined in the region since 1990 and only five countries (Afghanistan, Sudan, Yemen, Morocco, and Algeria) out of 21 nations didn't achieve the Sustainable Development Goal (SDG) target of 70 deaths per 100 000 live births in 2019. Despite the convergence in trends, there are still disparities across countries.Copyright © 2022 Academy of Medical Sciences of I.R. Iran. All rights reserved.

A New Container Throughput Forecasting Paradigm under COVID-19

COVID-19 has imposed tremendously complex impacts on the container throughput of ports, which poses big challenges for traditional forecasting methods. This paper proposes a novel decomposition-ensemble forecasting method to forecast container throughput under the impact of major events. Combining this with change-point analysis and empirical mode decomposition (EMD), this paper uses the decomposition-ensemble methodology to build a throughput forecasting model. Firstly, EMD is used to decompose the sample data of port container throughput into multiple components. Secondly, fluctuation scale analysis is carried out to accurately capture the characteristics of the components. Subsequently, we tailor the forecasting model for every component based on the mode analysis. Finally, the forecasting results of all the components are combined into one aggregated output. To validate the proposed method, we apply it to a forecast of the container throughput of Shanghai port. The results show that the proposed forecasting model significantly outperforms its rivals, including EMD-SVR, SVR, and ARIMA.