ABSTRACT
BACKGROUND: Development of surveillance systems based on big data sources with spatial information is necessitated more than ever during this pandemic. Here, we present our pilot results of a new technique for the incorporation of spatial information of transactions and a vital registry of COVID-19 to evaluate the disease spread. METHODS: We merged two databases of laboratory-confirmed national COVID-19 registry of Iran and financial transactions of point-of-sale devices from February to March 2020 as our training data sources. Spatial information was used for the visualization of maps and movements of sick individuals. We used the point-of-sale devices-related guild to check for the dynamics of financial transactions and effectiveness of quarantines. FINDINGS: In the study period, 174,428 confirmed cases were in the COVID-19 registry with accompanying transactions information. In total, 13,924,982 financial transactions were performed by them, with a mean of 1.2 per day for each person. All guilds had a decreasing pattern of "risky" transactions except for grocery stores and pharmacies. The latter showed a decreasing pattern by impose of lockdowns. Different cities were the hotspot of disease transmission as many "high-risk" transactions were performed in them, among which Tehran (mainly its central neighborhoods) and southern cities of Lake Urmia predominated. Lockdowns indicated that the disease gradually became less transmissible. INTERPRETATION: Financial transactions can be readily used for epidemics surveillance. Semi real-time results of such iterations can be informative for policy makers, guild owners, and general population to prepare safer commuting and merchandise spaces.
ABSTRACT
Purpose: Diabetes is one of the major comorbidities associated with COVID-19. We aimed to determine the clinical and epidemiological factors associated with the mortality of COVID-19 in diabetic patients in Iran, and also the impact of prescribed antiviral and antibiotics on patients' status. Methods: In this study, we used the national registry of hospitalized patients with Severe Acute Respiratory Syndrome (SARS) Symptoms with diabetes from February 18, 2020, to December 22, 2020. Demographic, clinical features, treatments, concurrent comorbidities, and their associations with mortality and severity outcomes were assessed using logistic regression. Results: 78,554 diabetic in-patients with SARS symptoms were included from 31 provinces of whom 37,338 were PCR positive for COVID-19. Older age and male gender are associated with COVID-19 mortality in diabetic patients. CVD is the most frequent comorbidity (42%). CVD, kidney disease, liver disease, and COPD are associated comorbidities which increased the risk of mortality. The mortality rate is higher in diabetic patients comparing to patients with no comorbidities, particularly in younger age groups. The frequency of antiviral, and antibiotics in COVID-19 positive patients was 34%, and 31%, respectively. Antibiotic treatment has no association with mortality in COVID-19 patients. Conclusions: Diabetic patients indicate higher mortality comparing to patients without any underlying comorbidities. Restrict strategies on increasing effective health care utilization must be considered in diabetic patients, especially in those with parallel underlying comorbidities. Regarding the antibiotic resistance issue and the noticeable use of antibiotics in diabetic patients, it is recommended to prioritize an antibiotic guideline prescription in COVID-19 patients for better stewardship by countries.