tetano
Editor, Senior Moderator
Infect Dis Model
. 2024 Feb 8;9(2):387-396.
doi: 10.1016/j.idm.2024.01.009. eCollection 2024 Jun. Spatio-temporal clustering analysis of COVID-19 cases in Johor
Fong Ying Foo[SUP] 1 [/SUP], Nuzlinda Abdul Rahman[SUP] 1 [/SUP], Fauhatuz Zahroh Shaik Abdullah[SUP] 1 [/SUP], Nurul Syafiah Abd Naeeim[SUP] 1 [/SUP]
Affiliations
At the end of the year 2019, a virus named SARS-CoV-2 induced the coronavirus disease, which is very contagious and quickly spread around the world. This new infectious disease is called COVID-19. Numerous areas, such as the economy, social services, education, and healthcare system, have suffered grave consequences from the invasion of this deadly virus. Thus, a thorough understanding of the spread of COVID-19 is required in order to deal with this outbreak before it becomes an infectious disaster. In this research, the daily reported COVID-19 cases in 92 sub-districts in Johor state, Malaysia, as well as the population size associated to each sub-district, are used to study the propagation of COVID-19 disease across space and time in Johor. The time frame of this research is about 190 days, which started from August 5, 2021, until February 10, 2022. The clustering technique known as spatio-temporal clustering, which considers the spatio-temporal metric was adapted to determine the hot-spot areas of the COVID-19 disease in Johor at the sub-district level. The results indicated that COVID-19 disease does spike in the dynamic populated sub-districts such as the state's economic centre (Bandar Johor Bahru), and during the festive season. These findings empirically prove that the transmission rate of COVID-19 is directly proportional to human mobility and the presence of holidays. On the other hand, the result of this study will help the authority in charge in stopping and preventing COVID-19 from spreading and become worsen at the national level.
Keywords: COVID-19; Disease mapping; Hot-spot areas; Scan statistics; Spatio-temporal clustering; Sub-district level.
. 2024 Feb 8;9(2):387-396.
doi: 10.1016/j.idm.2024.01.009. eCollection 2024 Jun. Spatio-temporal clustering analysis of COVID-19 cases in Johor
Fong Ying Foo[SUP] 1 [/SUP], Nuzlinda Abdul Rahman[SUP] 1 [/SUP], Fauhatuz Zahroh Shaik Abdullah[SUP] 1 [/SUP], Nurul Syafiah Abd Naeeim[SUP] 1 [/SUP]
Affiliations
- PMID: 38385018
- PMCID: PMC10879677
- DOI: 10.1016/j.idm.2024.01.009
At the end of the year 2019, a virus named SARS-CoV-2 induced the coronavirus disease, which is very contagious and quickly spread around the world. This new infectious disease is called COVID-19. Numerous areas, such as the economy, social services, education, and healthcare system, have suffered grave consequences from the invasion of this deadly virus. Thus, a thorough understanding of the spread of COVID-19 is required in order to deal with this outbreak before it becomes an infectious disaster. In this research, the daily reported COVID-19 cases in 92 sub-districts in Johor state, Malaysia, as well as the population size associated to each sub-district, are used to study the propagation of COVID-19 disease across space and time in Johor. The time frame of this research is about 190 days, which started from August 5, 2021, until February 10, 2022. The clustering technique known as spatio-temporal clustering, which considers the spatio-temporal metric was adapted to determine the hot-spot areas of the COVID-19 disease in Johor at the sub-district level. The results indicated that COVID-19 disease does spike in the dynamic populated sub-districts such as the state's economic centre (Bandar Johor Bahru), and during the festive season. These findings empirically prove that the transmission rate of COVID-19 is directly proportional to human mobility and the presence of holidays. On the other hand, the result of this study will help the authority in charge in stopping and preventing COVID-19 from spreading and become worsen at the national level.
Keywords: COVID-19; Disease mapping; Hot-spot areas; Scan statistics; Spatio-temporal clustering; Sub-district level.