A Year of Spatio-Temporal Clusters of COVID-19 in Indonesia

Jumadi, Jumadi; Fikriyah, Vidya Nahdhiyatul; Hadibasyir, Hamim Zaky; Priyono, Kuswaji Dwi; Musiyam, Muhammad; Mardiah, Andri N. R.; Rohman, Arif; Hasyim, Hamzah; Ibrahim, Mohd Hairy

doi:10.2478/quageo-2022-0013

Cited by 8 publications

(6 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Meanwhile, environmental characteristics like the altitude of the residence and its distance from the sea were extracted from the Google Earth application, a tool that offers geospatial data with high levels of accuracy [ 38 ]. Data pertaining to the province's population density was obtained from the local statistical center bureau of the respective province, with the most recent data available from the year 2020 [ 39 ]. All the gathered data were in categorical format.…”

Section: Methodsmentioning

confidence: 99%

Analyzing socio-environmental determinants of bone and soft tissue cancer in Indonesia

Romadhon,

Kurniati,

Jumadi

et al. 2024

BMC Cancer

Self Cite

View full text Add to dashboard Cite

Background This study is designed to explore the potential impact of individual and environmental residential factors as risk determinants for bone and soft tissue cancers, with a particular focus on the Indonesian context. While it is widely recognized that our living environment can significantly influence cancer development, there has been a notable scarcity of research into how specific living environment characteristics relate to the risk of bone and soft tissue cancers. Methods In a cross-sectional study, we analyzed the medical records of oncology patients treated at Prof. Suharso National Referral Orthopedic Hospital. The study aimed to assess tumor malignancy levels and explore the relationships with socio-environmental variables, including gender, distance from the sea, sunrise time, altitude, and population density. Data were gathered in 2020 from diverse sources, including medical records, Google Earth, and local statistical centers. The statistical analyses employed Chi-square and logistic regression techniques with the support of Predictive Analytics SoftWare (PASW) Statistics 18. Results Both bivariate and multivariate analyses revealed two significant factors associated with the occurrence of bone and soft tissue cancer. Age exhibited a statistically significant influence (OR of 5.345 and a p-value of 0.000 < 0.05), indicating a robust connection between cancer development and age. Additionally, residing within a distance of less than 14 km from the sea significantly affected the likelihood of bone and soft tissue cancers OR 5.604 and p-value (0.001 < 0.05). Conclusions The study underscores the strong association between age and the development of these cancers, emphasizing the need for heightened vigilance and screening measures in older populations. Moreover, proximity to the sea emerges as another noteworthy factor influencing cancer risk, suggesting potential environmental factors at play. These results highlight the multifaceted nature of cancer causation and underscore the importance of considering socio-environmental variables when assessing cancer risk factors. Such insights can inform more targeted prevention and early detection strategies, ultimately contributing to improved cancer management and patient outcomes.

show abstract

Section: Methodsmentioning

confidence: 99%

Analyzing socio-environmental determinants of bone and soft tissue cancer in Indonesia

Romadhon,

Kurniati,

Jumadi

et al. 2024

BMC Cancer

Self Cite

View full text Add to dashboard Cite

show abstract

“…Meanwhile, environmental characteristics like the altitude of the residence and its distance from the sea were extracted from the Google Earth application, a tool that offers geospatial data with high levels of accuracy [28]. Data pertaining to the province's population density was obtained from the local statistical center bureau of the respective province, with the most recent data available from the year 2020 [29]. All the gathered data were in categorical format.…”

Section: Tumor Malignancy Classi Cationmentioning

confidence: 99%

Analyzing Socio-Environmental Determinants of Bone and Soft Tissue Cancer in Indonesia

Romadhon,

Kurniati,

Jumadi

et al. 2023

Preprint

View full text Add to dashboard Cite

Background This study is designed to explore the potential impact of individual and environmental residential factors as risk determinants for bone and soft tissue cancers, with a particular focus on the Indonesian context. While it is widely recognized that our living environment can significantly influence cancer development, there has been a notable scarcity of research into how specific living environment characteristics relate to the risk of bone and soft tissue cancers. Methods In a cross-sectional study, we analyzed the medical records of oncology patients treated at Prof. Suharso National Referral Orthopedic Hospital. The study aimed to assess tumor malignancy levels and explore the relationships with socio-environmental variables, including gender, distance from the sea, sunrise time, altitude, and population density. Data were gathered in 2020 from diverse sources, including medical records, Google Earth, and local statistical centers. The statistical analyses employed Chi-square and logistic regression techniques with the support of Predictive Analytics SoftWare (PASW) Statistics 18. Results Both bivariate and multivariate analyses revealed two significant factors associated with the occurrence of bone and soft tissue cancer. Age exhibited a statistically significant influence (aOR – adjusted odds ratios = 3.270, p = 0.000), indicating a robust connection between cancer development and age. Additionally, residing within a distance of less than 14 kilometers from the sea significantly affected the likelihood of bone and soft tissue cancers (aOR = 2.416, p = 0.029). Conclusions The study underscores the strong association between age and the development of these cancers, emphasizing the need for heightened vigilance and screening measures in older populations. Moreover, the proximity to the sea emerges as another noteworthy factor influencing cancer risk, suggesting potential environmental factors at play. These results highlight the multifaceted nature of cancer causation and underscore the importance of considering socio-environmental variables when assessing cancer risk factors. Such insights can inform more targeted prevention and early detection strategies, ultimately contributing to improved cancer management and patient outcomes.

show abstract

“…Therefore, it is necessary to conduct an analysis related to the dynamics of the regional economy in each regency/city of Central Kalimantan Province with a Spatio-temporal analysis using a Geographic Information System (GIS). The Spatio-temporal analysis is a method to observe changes in a particular place within a specified period (Jumadi, 2022). Spatial data with Spatio-temporal map visualization will make it easier to analyze the dynamics of the regional economy as the data can clearly describe the distribution of locations and economic dynamics that occurred from 2016 to 2021.…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Analysis of Regional Economic Dynamics Using Geographic Information System in Central Kalimantan Province

Afriyanti,

Amin,

Pramono

2023

Advances in Social Science, Education and Humanities Research

View full text Add to dashboard Cite

Central Kalimantan Province is a region with the lowest level of economic development when compared to other provinces on Kalimantan Island. The low level of economic growth is the basis for this research because several factors influence that. Spatio-Temporal Analysis of Regional Economic Dynamics Using a Geographic Information System (GIS) in Central Kalimantan Province is a method for analyzing regional economic development with the dimensions of location and time with the unit analysis used is each regency/city in Central Kalimantan Province. This study aims to analyze the Spatio-Temporal of regional economic development in Central Kalimantan Province, how the development of existing leading sectors, and the relationship or influence of the two. The method used is a quantitative method with Spatio-Temporal analysis using GIS. The data used is the Gross Regional Domestic Product (GRDP) of Central Kalimantan Province at constant market price by industrial origin in 2015-2021. The result of the study shows that economic development in Central Kalimantan Province between 2016-2021 was quite volatile and economic development in each regency/city experienced disparities. Fluctuating changes also occurred in the development of leading sectors. Overall, the growth rate and contribution of each sector were still less consistent. The leading sectors influence regional economic development, however, it is not viewed from the number of existing leading sectors, but from their contribution and consistency. In general, the leading sectors in each regency/city of Central Kalimantan Province have not been able to properly stimulate the regional economy.

show abstract

A Year of Spatio-Temporal Clusters of COVID-19 in Indonesia

Cited by 8 publications

References 14 publications

Analyzing socio-environmental determinants of bone and soft tissue cancer in Indonesia

Analyzing socio-environmental determinants of bone and soft tissue cancer in Indonesia

Analyzing Socio-Environmental Determinants of Bone and Soft Tissue Cancer in Indonesia

Spatio-Temporal Analysis of Regional Economic Dynamics Using Geographic Information System in Central Kalimantan Province

Contact Info

Product

Resources

About