Literature DB >> 33936324

Forecasting Social Distancing impact on COVID-19 in Jakarta using SIRD Model.

Alexander A S Gunawan1.   

Abstract

Coronavirus disease 2019 (COVID-19) is a new emerging disease and a pandemic causing a high number of deaths. It is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) and transmitted via droplets. Several countries including Indonesia had applied social distancing to reduce the disease transmission. In this study, we were using two groups, with social distancing and without social distancing represented by quarantine parameter Q. We predict the peak number in both groups using Susceptible-Infected-Recovered-Deceased (SIRD) model. The aims of this study are to compare the peak number of cases in groups with and without social distancing cases in Jakarta. This study result in a lower peak number and longer days of disease period in group with strict social distancing than in groups without social distancing, the current case number represent quarantine parameter Q 0.4 of SIRD Model. We suggest applying strict social distancing in Jakarta considering the duration, health standard, and other factors affecting COVID-19 cases.
© 2021 The Author(s). Published by Elsevier B.V.

Entities:  

Keywords:  COVID-19; Jakarta; SIRD; social distancing

Year:  2021        PMID: 33936324      PMCID: PMC8072599          DOI: 10.1016/j.procs.2021.01.053

Source DB:  PubMed          Journal:  Procedia Comput Sci


  8 in total

1.  COVID-19 and Indonesia.

Authors:  Siti Setiati; Muhammad Khifzhon Azwar
Journal:  Acta Med Indones       Date:  2020-01

Review 2.  Reproduction numbers of infectious disease models.

Authors:  Pauline van den Driessche
Journal:  Infect Dis Model       Date:  2017-06-29

3.  A novel coronavirus outbreak of global health concern.

Authors:  Chen Wang; Peter W Horby; Frederick G Hayden; George F Gao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

4.  A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version).

Authors:  Ying-Hui Jin; Lin Cai; Zhen-Shun Cheng; Hong Cheng; Tong Deng; Yi-Pin Fan; Cheng Fang; Di Huang; Lu-Qi Huang; Qiao Huang; Yong Han; Bo Hu; Fen Hu; Bing-Hui Li; Yi-Rong Li; Ke Liang; Li-Kai Lin; Li-Sha Luo; Jing Ma; Lin-Lu Ma; Zhi-Yong Peng; Yun-Bao Pan; Zhen-Yu Pan; Xue-Qun Ren; Hui-Min Sun; Ying Wang; Yun-Yun Wang; Hong Weng; Chao-Jie Wei; Dong-Fang Wu; Jian Xia; Yong Xiong; Hai-Bo Xu; Xiao-Mei Yao; Yu-Feng Yuan; Tai-Sheng Ye; Xiao-Chun Zhang; Ying-Wen Zhang; Yin-Gao Zhang; Hua-Min Zhang; Yan Zhao; Ming-Juan Zhao; Hao Zi; Xian-Tao Zeng; Yong-Yan Wang; Xing-Huan Wang
Journal:  Mil Med Res       Date:  2020-02-06

5.  Estimates of the ongoing need for social distancing and control measures post-"lockdown" from trajectories of COVID-19 cases and mortality.

Authors:  Mike Lonergan; James D Chalmers
Journal:  Eur Respir J       Date:  2020-07-23       Impact factor: 16.671

6.  Utility of Substandard Face Mask Options for Health Care Workers During the COVID-19 Pandemic.

Authors:  Alaa Abd-Elsayed; Jay Karri
Journal:  Anesth Analg       Date:  2020-07       Impact factor: 5.108

7.  Aerosol and Surface Stability of SARS-CoV-2 as Compared with SARS-CoV-1.

Authors:  Neeltje van Doremalen; Trenton Bushmaker; Dylan H Morris; Myndi G Holbrook; Amandine Gamble; Brandi N Williamson; Azaibi Tamin; Jennifer L Harcourt; Natalie J Thornburg; Susan I Gerber; James O Lloyd-Smith; Emmie de Wit; Vincent J Munster
Journal:  N Engl J Med       Date:  2020-03-17       Impact factor: 91.245

8.  Data-based analysis, modelling and forecasting of the COVID-19 outbreak.

Authors:  Cleo Anastassopoulou; Lucia Russo; Athanasios Tsakris; Constantinos Siettos
Journal:  PLoS One       Date:  2020-03-31       Impact factor: 3.240

  8 in total

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