Mohammadi Esmaeil, Azmin Mehrdad, Fattahi Nima, Ghasemi Erfan, Azadnajafabad Sina, Rezaei Negar, Rashidi Mohammad-Mahdi, Keykhaei Mohammad, Zokaei Hossein, Rezaei Nazila, Haghshenas Rosa, Kaveh Farzad, Pakatchian Erfan, Jamshidi Hamidreza, Farzadfar Farshad
Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Digit Health. 2022 Feb 9;8:20552076221076252. doi: 10.1177/20552076221076252. eCollection 2022 Jan-Dec.
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.
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.
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.
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.
在此次疫情期间，基于带有空间信息的大数据源开发监测系统比以往任何时候都更加必要。在此，我们展示了一种将交易空间信息与新冠疫情重要登记信息相结合以评估疾病传播的新技术的试点结果。
我们将伊朗全国实验室确诊的新冠疫情登记数据库与2020年2月至3月销售点设备的金融交易数据库合并，作为我们的训练数据源。空间信息用于绘制患病个体的地图和行动轨迹。我们利用与销售点设备相关的行业协会来检查金融交易动态和隔离措施的有效性。
在研究期间，新冠疫情登记中有174428例确诊病例并伴有交易信息。他们总共进行了13924982笔金融交易，每人平均每天1.2笔。除杂货店和药店外，所有行业协会的“风险”交易都呈下降趋势。后者在实施封锁后呈下降趋势。不同城市是疾病传播的热点地区，因为在这些城市进行了许多“高风险”交易，其中德黑兰（主要是其市中心社区）和乌尔米耶湖以南的城市最为突出。封锁表明疾病的传播性逐渐降低。
金融交易可轻易用于疫情监测。此类迭代的半实时结果可为政策制定者、行业协会负责人和普通民众提供信息，以便他们打造更安全的出行和商业空间。
