tetano
Editor, Senior Moderator
J Infect Public Health
. 2023 Oct 18;16(12):2068-2078.
doi: 10.1016/j.jiph.2023.10.016. Online ahead of print. Factors associated with COVID-19 brought-in deaths: A data-linkage comparative cross-sectional study
Ameerah Su'ad Abdul Shakor[SUP] 1 [/SUP], Ely Zarina Samsudin[SUP] 2 [/SUP], Xin Wee Chen[SUP] 3 [/SUP], Muhammad Haikal Ghazali[SUP] 4 [/SUP]
Affiliations
Background: The phenomenon of Coronavirus disease 2019 (COVID-19) brought-in-dead (BID), i.e., COVID-19 deaths occurring outside hospital settings, suggests missed opportunities for life-saving care. However, much is still unknown with regards to its potential determinants. The present study aimed to examine the factors associated with COVID-19 BID by integrating new variables from multiple databases.
Methods: This multi-database comparative cross-sectional study examined COVID-19 in-patient deaths (IPD) and COVID-19 BID (n = 244 in each group) in Selangor, Malaysia. BID cases, IPD cases, and their sociodemographic, clinical, and health behaviour factors were identified from the COVID-19 mortality investigation reports submitted to the Selangor State Health Department between 14 February 2022 and 31 March 2023. Data linkage was used to connect three open-source databases-GitHub-MOH, Socioeconomic Data and Applications Center, and OpenStreetMap-and identify health infrastructure and geospatial factors. The groups were compared using chi-square tests, independent t-tests, and logistic regression analyses to identify factors associated with COVID-19 BID.
Results: The COVID-19 IPD and BID cases were comparable. After adjusting for confounders, non-Malaysian nationality (AOR: 3.765, 95% CI: 1.163, 12.190), obesity (AOR: 5.272, 95% CI: 1.131, 24.567), not seeking treatment while unwell (AOR: 5.385, 95% CI: 3.157, 9.186), and a higher percentage of COVID-19-dedicated beds occupied on the date of death (AOR: 1.165, 95% CI: 1.078, 1.259) were associated with increased odds of COVID-19 BID. On the other hand, being married (AOR: 0.396, 95% CI: 0.158, 0.997) and the interaction between the percentage of COVID-19-dedicated beds occupied and the percentage of ventilators in use (AOR: 0.996, 95% CI: 0.994, 0.999) emerged as protective factors.
Conclusion: These findings indicated that certain groups have higher odds of COVID-19 BID and thus, require closer monitoring. Considering that COVID-19 BID is influenced by various elements beyond clinical factors, intensifying public health initiatives and multi-organisational collaboration is necessary to address this issue.
Keywords: Brought-in-dead; Data linkage; Geographic information system; Mortality; Pandemic.
. 2023 Oct 18;16(12):2068-2078.
doi: 10.1016/j.jiph.2023.10.016. Online ahead of print. Factors associated with COVID-19 brought-in deaths: A data-linkage comparative cross-sectional study
Ameerah Su'ad Abdul Shakor[SUP] 1 [/SUP], Ely Zarina Samsudin[SUP] 2 [/SUP], Xin Wee Chen[SUP] 3 [/SUP], Muhammad Haikal Ghazali[SUP] 4 [/SUP]
Affiliations
- PMID: 37950972
- DOI: 10.1016/j.jiph.2023.10.016
Background: The phenomenon of Coronavirus disease 2019 (COVID-19) brought-in-dead (BID), i.e., COVID-19 deaths occurring outside hospital settings, suggests missed opportunities for life-saving care. However, much is still unknown with regards to its potential determinants. The present study aimed to examine the factors associated with COVID-19 BID by integrating new variables from multiple databases.
Methods: This multi-database comparative cross-sectional study examined COVID-19 in-patient deaths (IPD) and COVID-19 BID (n = 244 in each group) in Selangor, Malaysia. BID cases, IPD cases, and their sociodemographic, clinical, and health behaviour factors were identified from the COVID-19 mortality investigation reports submitted to the Selangor State Health Department between 14 February 2022 and 31 March 2023. Data linkage was used to connect three open-source databases-GitHub-MOH, Socioeconomic Data and Applications Center, and OpenStreetMap-and identify health infrastructure and geospatial factors. The groups were compared using chi-square tests, independent t-tests, and logistic regression analyses to identify factors associated with COVID-19 BID.
Results: The COVID-19 IPD and BID cases were comparable. After adjusting for confounders, non-Malaysian nationality (AOR: 3.765, 95% CI: 1.163, 12.190), obesity (AOR: 5.272, 95% CI: 1.131, 24.567), not seeking treatment while unwell (AOR: 5.385, 95% CI: 3.157, 9.186), and a higher percentage of COVID-19-dedicated beds occupied on the date of death (AOR: 1.165, 95% CI: 1.078, 1.259) were associated with increased odds of COVID-19 BID. On the other hand, being married (AOR: 0.396, 95% CI: 0.158, 0.997) and the interaction between the percentage of COVID-19-dedicated beds occupied and the percentage of ventilators in use (AOR: 0.996, 95% CI: 0.994, 0.999) emerged as protective factors.
Conclusion: These findings indicated that certain groups have higher odds of COVID-19 BID and thus, require closer monitoring. Considering that COVID-19 BID is influenced by various elements beyond clinical factors, intensifying public health initiatives and multi-organisational collaboration is necessary to address this issue.
Keywords: Brought-in-dead; Data linkage; Geographic information system; Mortality; Pandemic.