{"id":129305,"date":"2022-04-13T08:52:12","date_gmt":"2022-04-13T01:52:12","guid":{"rendered":"http:\/\/210.57.208.200\/2022\/04\/13\/the-susceptible-infected-recovered-dead-model-for-long-term-identification-of-key-epidemiological-parameters-of-covid-19-in-indonesia\/"},"modified":"2022-04-18T14:48:37","modified_gmt":"2022-04-18T07:48:37","slug":"the-susceptible-infected-recovered-dead-model-for-long-term-identification-of-key-epidemiological-parameters-of-covid-19-in-indonesia","status":"publish","type":"post","link":"https:\/\/unair.ac.id\/en\/the-susceptible-infected-recovered-dead-model-for-long-term-identification-of-key-epidemiological-parameters-of-covid-19-in-indonesia\/","title":{"rendered":"The susceptible-infected-recovered-dead model for long-term identification of key epidemiological parameters of COVID-19 in Indonesia"},"content":{"rendered":"\n<p>The coronavirus (COVID-19) epidemic has spread massively to almost all countries including Indonesia, in just a few months. An important step to overcoming the COVID-19 outbreak is understanding its epidemiology through mathematical modeling intervention. The knowledge of epidemic dynamics patterns is an essential part of making timely decisions and preparing hospitals for the peak outbreak.<\/p>\n\n<p><div class=\"\" data-canvas-width=\"540.7217600000004\">In general, the conventional SIRD model can only simulate epidemiological patterns in the short-term period without involving optimization techniques and lacking detail in visualizing key parameters. In this study, unlike the SIRD model in general, the proposed SIRD model can explain and track the epidemic pattern in detail based on optimization technique. More specifically, some of the advantages are being able to: i) provide information regarding the key epidemiological parameters, ii) uncover the pattern of these outbreaks starting from the initial stages of spread until they fade out, iii) detect the infection peak of the pandemic, iv) identify the reproduction number, v) describe the rate of infection, recovery, and death, vi) adjust the lockdown time,<\/div>&#13;\n<div data-canvas-width=\"40.53056000000001\">vii) visualize the long-term prediction, and viii) identify the number of<\/div>&#13;\n<div data-canvas-width=\"172.99856000000003\">susceptible, infected, recovered, and dead people. Besides, the SIRD model implements an optimization technique to produce accurate prediction capabilities. These overall advantages are claimed to be the novelty<\/div>&#13;\n<div class=\"\" data-canvas-width=\"588.5164800000007\">of the proposed SIRD approach. Therefore, this study aimed to develop the SIRD model, which incorporates the key epidemiological parameters to model and estimate the long-term spread of the COVID-19 epidemic.<\/div><\/p>\n\n<p>Our model formulation is a data-based analysis by considering COVID-19 public data from March 2, 2020, to May 15, 2021. Based on the numerical analysis, the spread of the pandemic will begin to fade out after November 5, 2021. As a result of this COVID-19 attack, the cumulative number of infected people recovered people, and dead people sequentially is estimated to reach 3,200,000 people, 3,437,000 people. and 63,000 people, respectively.<\/p>\n\n<p>Besides, the key epidemiological parameter indicates that the average reproduction number  value of COVID-19 in Indonesia is 7.32. The long-term prediction of COVID-19 in Indonesia and its epidemiology can be well-described using the SIRD model. The model can be applied in specific regions or cities in understanding the epidemic pattern of COVID-19.<\/p>\n\n<p>Title:<\/p>\n\n<p>The susceptible-infected-recovered-dead model for long-term identification of key epidemiological parameters of COVID-19 in Indonesia<\/p>\n\n<p>Link: <a href=\"http:\/\/ijece.iaescore.com\/index.php\/IJECE\/article\/view\/26032\/15671\">http:\/\/ijece.iaescore.com\/index.php\/IJECE\/article\/view\/26032\/15671<\/a><\/p>\n\n<p>http:\/\/ijece.iaescore.com\/index.php\/IJECE\/article\/view\/26032<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The coronavirus (COVID-19) epidemic has spread massively to almost all countries including Indonesia, in just a few months. An important step to overcoming the COVID-19 outbreak is understanding its epidemiology through mathematical modeling intervention. The knowledge of epidemic dynamics patterns is an essential part of making timely decisions and preparing hospitals for the peak outbreak. [&hellip;]<\/p>\n","protected":false},"author":79,"featured_media":128577,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[49],"tags":[9001,4655],"class_list":["post-129305","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-scientific-article","tag-aip-en-2","tag-scientific-article"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>The susceptible-infected-recovered-dead model for long-term identification of key epidemiological parameters of COVID-19 in Indonesia - 51动漫 Official Website<\/title>\n<meta name=\"description\" content=\"The model can be applied in specific regions or cities in understanding the epidemic pattern of COVID-19\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/unair.ac.id\/en\/the-susceptible-infected-recovered-dead-model-for-long-term-identification-of-key-epidemiological-parameters-of-covid-19-in-indonesia\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The susceptible-infected-recovered-dead model for long-term identification of key epidemiological parameters of COVID-19 in Indonesia - 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