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ارائه مدل خط‌مشی‌گذاری شواهدمحور برای پیشگیری از انتشار کرونا ویروس (نمونه‌کاوی: شهر تهران) | ||
| مدیریت دولتی | ||
| دوره 13، شماره 2، 1400، صفحه 212-232 اصل مقاله (946.6 K) | ||
| نوع مقاله: مقاله علمی پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jipa.2021.318593.2905 | ||
| نویسندگان | ||
| امیرمحمد َشریفی1؛ مهدی عبدالحمید* 2؛ ُسحر بابایی3؛ یاسر سبحانی فرد4 | ||
| 1دانشجوی دکتری، گروه مدیریت تکنولوژی، دانشکده مدیریت، اقتصاد و مهندسی پیشرفت، دانشگاه علم و صنعت ایران، تهران، ایران. | ||
| 2استادیار، گروه مدیریت و فلسفه علم و فناوری، دانشکده مدیریت، اقتصاد و مهندسی پیشرفت دانشگاه علم و صنعت ایران، تهران، ایران. | ||
| 3دانشجوی دکتری، گروه مدیریت دولتی، دانشکده مدیریت و حسابداری دانشگاه علامه طباطبائی، تهران، ایران. | ||
| 4استادیار، گروه مدیریت و مهندسی کسب‌وکار، دانشکده مدیریت، اقتصاد و مهندسی پیشرفت، دانشگاه علم و صنعت ایران، تهران، ایران. | ||
| چکیده | ||
| هدف: هدف این پژوهش، پیشنهاد مداخله خط‌مشی به نهادهای مسئول، به‌منظور پیشگیری از انتشار ویروس کروناست. پاندمی کووید 19 اثرگذارترین بیماری از ابتدای سال 2020 است که علاوه بر مرگ‌ومیر بسیار، اثرهای اقتصادی و اجتماعی زیادی نیز در پی داشته است. پژوهشگران بسیاری برای درمان و تهیه واکسن آن تلاش می‌کنند؛ اما یکی از اقدام‌های اساسی، پیشگیری از آن است؛ زیرا پیشگیری سریع‌ترین راه کاهش مرگ‌ومیر و تبعات منفی آن محسوب می‌شود. روش: با حداکثر استفاده از داده‌های حداقلی در کشور و در نظرگرفتن قواعد جدید حاکم بر رفتار این ویروس، از رویکرد خط‌مشی‌گذاری شواهدمحور و مدل‌سازی عامل‌مبنا استفاده شده است که چهار مرحله ساخت شبیه‌ساز، کالیبره‌کردن آن، اعتبارسنجی و استفاده از آن برای تخمین چگونگی تکامل بیماری همه‌گیر را شامل می‌شود. یافته‌ها: به‌منظور تعیین عوامل اصلی مؤثر بر پیشگیری، چهار سناریو سیاستی، شامل قرنطینه عمومی، عدم مداخله، مداخله منفعل و مداخله هوشمند بررسی شد. در شبیه‌سازی سناریوهای سیاستی، عامل‌های میزان حرکت و میزان سرایت، به نسبت تغییر می‌کند. نتایج شبیه‌سازی نشان داد که کاهش 50درصدی میزان حرکت، کاهش بیش از ۸۰ درصد تعداد مبتلایان را در پی خواهد داشت و کاهش ۱۰درصد سرایت در قالب مداخله هوشمند، به کاهش 30 درصدی تعداد مبتلایان منجر خواهد شد. نتیجه‌گیری: در نهایت، دو عامل میزان حرکت و میزان سرایت، به‌عنوان عوامل مهم انتشار ویروس کرونا شناسایی شد. از این رو، پیشنهاد می‌شود که نهادهای مسئول برای کاهش سریع‌تر میزان شیوع کرونا، بر طراحی مداخله هوشمند مرتبط با کاهش این دو عامل تمرکز کنند. | ||
| کلیدواژه‌ها | ||
| کرونا؛ شبیه‌سازی؛ خط‌مشی‌گذاری شواهدمحور؛ پیشگیری؛ مدل‌سازی عامل‌مبنا | ||
| عنوان مقاله [English] | ||
| Presenting an Evidence-Based Policymaking Model to Prevent the Coronavirus Diffusion (Case Study: Tehran) | ||
| نویسندگان [English] | ||
| Amir Mohammad Sharifi1؛ Mahdi Abdolhamid2؛ Sahar Babaei3؛ Yaser Sobhanifard4 | ||
| 1Ph.D. Candidate, Department of Technology Management, School of Management, Economics and Progress Engineering, Iran University of Science and Technology, Tehran, Iran. | ||
| 2Assistant Prof., Department of Management and Philosophy of Science and Technology, School of Management, Economics and Progress Engineering Iran University of Science and Technology, Tehran, Iran. | ||
| 3Ph.D. Candidate, Department of Public Management, Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran. | ||
| 4Assistant Prof., Department of Management and Business Engineering, School of Management, Economics and Progress Engineering Iran University of Science and Technology, Tehran, Iran. | ||
| چکیده [English] | ||
| Objective: The purpose of this paper is to suggest intervention routes to responsible institutions in order to prevent the diffusion of coronavirus. The covid 19 pandemic is the most effective disease since the beginning of 2020, which in addition to many deaths, has had many economic and social effects. Many researchers are trying to treat and develop a vaccine, but one of the most basic measures is prevention because prevention is the fastest way to reduce mortality and its negative consequences. Methods: For this purpose, with the maximum use of minimal data in the country and considering the new rules governing the behavior of this virus, the evidence-based policy-making method and Agent-based modeling have been used, which includes four steps of simulator construction, calibration, Validation, and its use to estimate how the disease is evolving. Results: In order to determine the main factors affecting the prevention, four policy scenarios including general quarantine, non-intervention, passive intervention and intelligent intervention were examined. In simulating policy scenarios, the factors of movement rate and transmission risk change proportionally. The quarantine in an optimistic state itself includes four categories of scenarios based on different quarantine methods, and finally, the stop and treatment-related scenarios were also examined. The simulation results showed that a 50% reduction in the movement rate would lead to a reduction of more than 80% in the number of patients, and a 10% decrease in the transmission risk index would lead to a 30% reduction in the number of patients. Conclusion: Finally, two factors of movement rate and transmission risk index were identified as the most important factors in the diffusion of coronavirus. Therefore, it is suggested that the responsible institutions focus on designing intelligent interventions related to the reduction of these two factors in order to reduce the prevalence of corona more quickly. | ||
| کلیدواژه‌ها [English] | ||
| Corona, Simulation, Evidence-based policy, Prevention, Agent-based modeling | ||
| مراجع | ||
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