Background and Aims: Older people have higher rates of comorbidities and may experience more severe inflammatory responses; therefore, are at higher risk of death. Herein, we aimed to systematically review the mortality in coronavirus disease 2019 (COVID-19) patients and its predictors in this age group.Methods: We searched PubMed, Web of Science, and Science Direct using relevant keywords. Retrieved records underwent a two-step screening process consisting of title/abstract and full-text screenings to identify the eligible studies.Results: Summarizing findings of 35 studies demonstrated that older patients have higher mortality rates compared to the younger population. A review of articles revealed that increasing age, body mass index, a male gender, dementia, impairment or dependency in daily activities, presence of consolidations on chest X-ray, hypoxemic respiratory failure, and lower oxygen saturation at admission were risk factors for death. High D-dimer levels, 25-hydroxy vitamin D serum deficiencies, high C-reactive protein (≥5 mg/L) levels plus any other abnormalities of lymphocyte,

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Introduction Patients with immunodeficiency are usually more prone to worse outcomes of infectious diseases. However, there are some disagreements in the context of COVID-19, for example, in patients with human immunodeficiency virus (HIV). Herein, we aimed to systematically review the risk and predictors of COVID-19 mortality in people with primary or secondary immunodeficiency. Methods PubMed, Scopus, Web of Science, and Science Direct were searched. We followed a two-step screening process to identify eligible results. We first reviewed the title and abstract of the records and the unqualified studies were removed. Then, their full texts were evaluated based on their coherence with the purpose and inclusion/exclusion criteria, and those eligible for qualitative synthesis were included. Results Twenty-two articles were included, which investigated a total of 109,326 with primary or secondary immunodeficiencies. Three studies investigated the pediatric and infant population, while other studies were conducted on the adult population. Overall, studies on both primary and secondary immunodeficiency conflicted as some reported higher and some mentioned lower mortality rates in patients with immunodeficiency. Conclusions Overall, there were two points of view in both types of immunodeficiencies. The first is the classical viewpoint that all immunodeficient patients are at a higher risk of infection leading to a higher mortality rate. The second types of studies found that immunodeficiency might play a less important or even an inverse role in mortality rates by lowering the severity of the inflammatory response. However, it is important to take note to comorbidities, such as DM, HTN, CAD, ESRD, history of lower respiratory infection, etc., and demographic factors, such as obesity and age > 70 years, as they appear to influence the mortality rate, especially in patients with secondary immunodeficiency.

Non-communicable diseases represent 71% of all deaths worldwide. In 2015, Sustainable Development Goals, including target 3.4 of SDGs, were seated on the world agenda; “By 2030, reduce premature mortality from NCDs by one-third. More than half of the world’s countries are not on track to reach SDG 3.4, and the COVID-19 crisis has hampered the delivery of essential NCD services globally, which means the premature death of millions of people and indicates the need for capacity building for health systems. We designed a tool to measure the capacity of the National Center for Non-Communicable Disease and then presented the proposed policy package to enhance the national center’s organizational capacity. The data for this explanatory sequential mixed method study was collected using quantitative and qualitative approaches between February 2020 and December 2021. The tool for assessing organizational capacity for NCDs was developed, and its validity and reliability were measured. The developed tool assessed the organizational capacity by evaluating NCNCD’s managers and experts. Following the quantitative phase, a qualitative phase focused on the low-capacity points revealed by the tool. The causes of low capacity were investigated, as well as potential interventions to improve capacity. The developed tool comprises six main domains and eighteen subdomains, including (Governance, Organizational Management, Human Resources Management, Financial Management, Program Management, and Relations Management) which verified validity and reliability. In seven separate National Center for Non-Communicable Disease units, the organizational capacity was measured using the designed tool. (Cardiovascular disease and hypertension; diabetes; chronic respiratory disease; obesity and physical activity; tobacco and alcohol; nutrition; and cancers). The organizational management dimensions and the sub-dimensions of the organizational structure of the Ministry of Health and Medical Education and units affiliated with the national center, in all cases, were almost one of the main challenges that affected the country’s capacity to fight against NCDs. However, all units had a relatively good situation in terms of governance (mission statement, vision, and written strategic plan). The content analysis of experts’ opinions on the low-capacity subdomains highlighted challenges and recommended capacity-building interventions. Transparency in methods and processes is necessary to allocate funding among various health programs and evaluate their effects through cost-effectiveness indicators. This study identified weak points or areas where capacity building is required. The root causes of low capacity and interventions to build capacity are listed in each dimension of the tool. Some of the proposed interventions, such as strengthening organizational structures, have the potential to impact other domains. Improving organizational capacity for NCDs can assist countries to achieve national and global goals with greater efficiency.

Background Policymakers require precise, in-time information to make informed decisions in complex environments such as health systems. Artificial intelligence (AI) is a novel approach that makes collecting and analyzing data in complex systems more accessible. This study highlights recent research on AI's application and capabilities in health policymaking. Method PubMed, Scopus, and the Web of Science databases were investigated to find relevant studies from 2000 to 2023 using the keywords of "artificial intelligence" and "policymaking." Walt and Gilson's policy triangle framework was used for charting the data. Results The results revealed that using AI in health policy paved the way for novel analyses and innovative solutions for intelligent decision-making and data collection, potentially enhancing policymaking capacities, particularly in the evaluation phase. Moreover, it can be used to develop creative agendas with fewer political limitations and higher rationality, leading to better policies. Furthermore, AI provides the opportunity to make evidence-informed decisions by developing new platforms and toolkits. Most of the suggested AI solutions for health policy are not meant to replace experts but to make decision-making smarter. Conclusion Numerous approaches exist for AI to influence the health policymaking process. Leading health systems can benefit from AI's potential to expand the use of evidence-based policymaking in health systems.