COVID-19 and Comparative Health Policy Learning; the Experience of 10 Countries.

BACKGROUND: Since December 2019, the world has been facing one of the most critical health threats of the last decades. In March 2021, the official number of deaths passed 2.6 million worldwide. Most countries have developed policies to control the disease. Nevertheless, countries have experienced different outcomes related to their various adapted policies. Complementing our first report, in this article, we report our findings of comparing the policies adopted to combat coronavirus disease 2019 (COVID-19) in Iran, with those from nine selected countries, including China, Japan, South Korea, Singapore, Germany, the United States, the United Kingdom, Spain, and Italy, to draw evidence-informed policy lessons. METHODS: This is a qualitative study conducted based on document analysis related to COVID-19 policies in Iran and nine selected countries. Using a deductive approach, data were extracted and analyzed based on the components of the WHO Building Blocks Framework. Finally, we compared the Iranian policies with the nine selected countries. RESULTS: Documents analysis revealed a spectrum of policies, which have led to a variety of outcomes. Based on our findings, three main strategies (widespread testing, comprehensive contact tracing, and timely measures) were the most effective directions to combat COVID-19. CONCLUSION: The experience of the first and second waves of COVID-19 showed that the risk of coronavirus is serious and will continue until a vaccine or decisive treatment is achieved. Therefore, countries are required to adopt appropriate and tailored policies to deal with this crisis effectively. Applying the experiences from the previous waves is essential for more efficient performance in the likely upcoming waves.

The District Health Information System (DHIS2): A literature review and meta-synthesis of its strengths and operational challenges based on the experiences of 11 countries.

BACKGROUND: Health information systems offer many potential benefits for healthcare, including financial benefits and for improving the quality of patient care. The purpose of District Health Information Systems (DHIS) is to document data that are routinely collected in all public health facilities in a country using the system. OBJECTIVE: The aim of this study was to examine the strengths and operational challenges of DHIS2, with a goal to enable decision makers in different counties to more accurately evaluate the outcomes of introducing DHIS2 into their particular country. METHOD: A review of the literature combined with the method of meta-synthesis was used to source information and interpret results relating to the strengths and operational challenges of DHIS2. Databases (Embase, PubMed, Scopus and Google Scholar) were searched for documents related to strengths and operational challenges of DHIS2, with no time limit up to 8 April 2017. The review and evaluation of selected studies was conducted in three stages: title, abstract and full text. Each of the selected studies was reviewed carefully and key concepts extracted. These key concepts were divided into two categories of strengths and operational challenges of DHIS2. Then, each category was grouped based on conceptual similarity to achieve the main themes and sub-themes. Content analysis was used to analyse extracted data. RESULTS: Of 766 identified citations, 20 studies from 11 countries were included and analysed in this study. Identified strengths in the DHIS were represented in seven themes (with 21 categories): technical features of software, proper management of data, application flexibility, networking and increasing the satisfaction of stakeholders, development of data management, increasing access to information and economic benefits. Operational challenges were identified and captured in 11 themes (with 18 categories): funds; appropriate communication infrastructure; the need for the existence of appropriate data; political, cultural, social and structural infrastructure; manpower; senior managers; training; using academic potentials; definition and standardising the deployment processes; neglect to application of criteria and clinical guidelines in the use of system; data security; stakeholder communications challenges and the necessity to establish a pilot system. CONCLUSION: This study highlighted specific strengths in the technical and functional aspects of DHIS2 and also drew attention to particular challenges and concerns. These results provide a sound evidence base for decision makers and policymakers to enable them to make more accurate decisions about whether or not to use the DHIS2 in the health system of their country.

Lung Cancer Prevalence in Iran by Histologic Subtypes.

BACKGROUND: Prevalence statistics are essential for cancer control in addition to incidence and mortality data. As we know, there is no published report regarding lung cancer (LC) prevalence in Iran. Herein, we provide model-based estimates of limited time LC prevalence in Iran, 2015. MATERIALS AND METHODS: Incidence numbers of LC were extracted from Iranian National Cancer Registry reports for 2003-2009. Trends were analyzed by joinpoint regression, assuming a logarithmic poisson model. Incidence numbers were projected up to 2015, using linear regression models which were trained by corrected annual percentage changes. A Monte Carlo-based model was generated, and absolute survival rates, number of incident cases, and incompleteness of Iranian cancer registry for LC were included into it. Limited-time prevalence (within 1, 2-3, and 4-5 years from diagnosis) and its respective 95% uncertainty level (UL) were estimated by age, gender, and histopathological type. RESULTS: Five-year prevalence was estimated to be 4.21 (95% UL: 3.37-5.38) per 100,000 adult person, with a male:female ratio of 2.01. Estimated number of patients within 1, 2-3, and 4-5 years from diagnosis were 1871 (1497-2392), 993 (770-1285), and 420 (322-550), respectively. Most prevalent form of LC were squamous cell carcinoma (802; 579-999) and adenocarcinoma (319; 230-389) in males and females, respectively. CONCLUSION: According to our results, the most plausible estimates of number of alive LC patients within initial treatment, clinical follow-up, and cure phases were 2392, 1285, and 550 cases in Iran in 2015.

Predicting effective factors on eating behaviors in the prevention of cardiovascular disease based on the PRECEDE model.

BACKGROUND AND AIM: Changes in eating behavior can reduce the risk of developing cardiovascular disease. The aim of this study was to predict the effective factors of eating behaviors in the prevention of cardiovascular disease using the PRECEDE model. METHODS: This cross-sectional study was performed on 400 subjects aged from 20 to 60 years old in Kerman, Iran in 2016. The participants were selected using a multistage random sampling method. A self-administered questionnaire including questions regarding demographic characteristics, eating behavior, and PRECEDE model constructs were completed by the participants. Data were analyzed using SPSS 22 and STATA 12. For data analysis, Spearman correlation coefficient, univariate and multiple median regression were applied. The predictive power of the model constructs was determined by analysis of artificial neural networks. RESULTS: Among participants, the score of knowledge was high (84.15±10.7), and the scores of perceived self-efficacy (59.1±16.57), reinforcing factors (60.66±14.01), enabling factors (56.5±12.91), and eating behavior (62.1±14.7) were intermediate, and the score of attitude was low (47.84±7.67). Attitude, self-perceived efficacy, enabling factors, and knowledge predicted 32%, 30%, 26%, and 0.93% of participants' eating behavior respectively. The relationship between all variables and eating behavior was positive and significant (p<0.0001). Perceived self-efficacy had the most, and reinforcing factors the least correlation with eating behavior. CONCLUSION: According to the results of this study, self-efficacy, attitude, and enabling factors were the main predicting factors for eating behaviors; therefore, to prevent cardiovascular disease and enhance healthy eating behavior, it is recommended to change attitude, and enhance self-efficacy and enabling factors in the community.