Are countries' precautionary actions against COVID-19 effective? An assessment study of 175 countries worldwide.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has affected many countries negatively, particularly in terms of their health care and financial systems. Numerous countries have attempted to employ precautions to address this pandemic. This study was aimed at exploring and assessing the early precautionary actions taken by 175 countries on six continents to prevent the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: An observational study utilizing available public data was conducted on the basis of data collected from December 31, 2019 until the end of April 2020 and then compared with data in January 2021. Several data were extracted, including information related to the date of the first reported case of SARS-CoV-2, total confirmed cases, total active cases and more. In addition, seven validated indicators were used to assess the countries' preparedness and precautionary actions. RESULTS: A total of 175 countries were included in the study. The total COVID-19 infection rate increased exponentially and rapidly in North America and Europe from March to April. The application of precautions (indicators) varied between countries. School closures, quarantines and curfews were the most-applied indicators among all countries. As for the relationship between the indicators and their effects on the infection rate, Italy and Spain were the top countries in Europe and adopted all the indicators. Nevertheless, they faced high infection rates: 239,639 and 205,463 COVID-19 cases in Spain and Italy, respectively. CONCLUSION: The precautionary actions might have played a role in limiting the spread of COVID-19 in several countries. However, many countries might not benefit from applying these indicators.

Real-world data in Saudi Arabia: Current situation and challenges for regulatory decision-making.

PURPOSE: To present the process of establishing a pharmacoepidemiological database in Saudi Arabia, challenges and models used. METHODS: The database establishment has started in 2017 by piloting the conversion of electronic health records of one hospital to the Observational Health Data Sciences and Informatics (OHDSI), Observational Medical Outcomes Partnership's Common Data Model (OMOP). RESULTS: During the pilot phase we have faced several challenges such as limited contribution in providing data by local medical institution due to uncertainty about data governance, diversity of systems used by hospitals, inconsistent coding of medical information, and limited awareness about data structure from participating hospital. The pilot phase was completed in 2019 containing information about patient attributes, medical care, therapies, and other additional services for around 130 000 patients in Saudi Arabia. The majority of patients were below the age of 50 years (89%), and acute respiratory infections were the most frequent diagnosis. The data quality was acceptable and no major anomalies were detected during the conversion. CONCLUSIONS: We demonstrated a successful creation of a pilot database using OHDSI Common Data Model. Our experience with the pilot database could be extended to other institutions to create a national dataset that could be used to generate real-world evidence.

Recording type 2 diabetes mellitus in a standardised central Saudi database: a retrospective validation study.

OBJECTIVES: This study was conducted to assess the validity of recording (and the original diagnostic practice) of type 2 diabetes mellitus at a hospital whose records were integrated to a centralised database (the standardised common data model (CDM) of the Saudi National Pharmacoepidemiologic Database (NPED)). DESIGN: A retrospective single-centre validation study. SETTINGS: Data of the study participants were extracted from the CDM of the NPED (only records of one tertiary care hospital were integrated at the time of the study) between 1 January 2013 and 1 July 2018. PARTICIPANTS: A random sample of patients with type 2 diabetes mellitus (≥18 years old and with a code of type 2 diabetes mellitus) matched with a control group (patients without diabetes) based on age and sex. OUTCOME MEASURES: The standardised coding of type 2 diabetes in the CDM was validated by comparing the presence of diabetes in the CDM versus the original electronic records at the hospital, the recording in paper-based medical records, and the physician re-assessment of diabetes in the included cases and controls, respectively. Sensitivity, specificity, positive predictive value and negative predictive value were estimated for each pairwise comparison using RStudio V.1.4.1103. RESULTS: A total of 437 random sample of patients with type 2 diabetes mellitus was identified and matched with 437 controls. Only 190 of 437 (43.0%) had paper-based medical records. All estimates were above 90% except for sensitivity and specificity of CDM versus paper-based records (54%; 95% CI 47% to 61% and 68%; 95% CI 62% to 73%, respectively). CONCLUSIONS: This study provided an assessment to the extent of which only type 2 diabetes mellitus code can be used to identify patients with this disease at a Saudi centralised database. A future multi-centre study would help adding more emphasis to the study findings.