Advancing Localized Public Health Surveillance in Malaysia by Enhancing EIOS with Google COVID-19 Data Integration
Keywords:
Epidemic Intelligence, COVID-19, Infectious Disease, Targeted Health Intervention, EIOSAbstract
Epidemic intelligence has evolved from traditional manual reporting and field investigation methods to dynamic, real-time surveillance, driven by the 21st-century surge in digital data sources. Infectious diseases pose a significant global health threat, with traditional surveillance methods often facing delays in detecting and responding due to reliance on structured clinical data. The Covid-19 pandemic has emphasized the need for precise and actionable data to inform public health decisions. The current categorization of the Epidemic Intelligence from Open Sources (EIOS) system by country limits its ability to precisely track and monitor infectious diseases at more localized levels. This study focuses on enhancing the EIOS system by improving geographic data specifically for Malaysia. Currently, the EIOS platform, which incorporates data sources from Johns Hopkins University (JHU), the World Health Organization (WHO), and the Worldometers (WOM), provides country-level data that limits the effectiveness of localized interventions. This enhancement involves integrating state-level data in Malaysia from the Google Covid-19 Open Data Repository, which collects data automatically from authoritative sources, volunteers and contributors into the EIOS system. This paper presents the focus in Malaysia for better precision and effectiveness, in public health interventions. The suggested EIOS system will assist in sorting data based on dates,cases numbers,fatalities and data origins resultng in a more intricate and adaptable depiction of the pandemics advancement. The results of this study will offer insights and improvements for public health experts in Malaysia regarding the management and containment of infectious diseases at a local level.It will help optimize resource distribution and readiness efforts to mitigate the effects of outbreaks effectively.This improvement is intended to support targeted lockdowns and other public health interventions, in geographic areas with greater precision by enhancing geographical tracking capabilities.
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Agbehadji, I. E., Awuzie, B. O., Ngowi, A. B., & Millham, R. C. (2020). Review of big data analytics, artificial intelligence and nature-inspired computing models towards accurate detection of COVID-19 pandemic cases and contact tracing. In International Journal of Environmental Research and Public Health (Vol. 17, Issue 15, pp. 1–16). MDPI AG. https://doi.org/10.3390/ijerph17155330
Alo, U. R., Nkwo, F. O., Nweke, H. F., Achi, I. I., & Okemiri, H. A. (2022). Non-pharmaceutical interventions against covid-19 pandemic: Review of contact tracing and social distancing technologies, protocols, apps, security and open research directions. In Sensors (Vol. 22, Issue 1). MDPI. https://doi.org/10.3390/s22010280
Amin, K. H. A. K., Bujang, N. N. A., Abas, S. A., Zulkifli, N. I., Amir, S. A., Shah, S. M., Ganesan, V., Aziz, N. F., Jalaluddin, M. A., Wahil, M. S. A., Hasani, M. H. M., Ali, N. K. M., & Yusof, M. P. (2023). Epidemiology of COVID-19 cases and vaccination coverage in Seremban District, Malaysia, 2021. Western Pacific Surveillance and Response Journal, 14(2). https://doi.org/10.5365/wpsar.2023.14.2.985
Amira, N., Rosday, A., Azlina, K., Akil, K., Bidin, J., Sharif, N., & Chulan, M. (2023). Analyzing the Covid-19 Cases in Malaysia during the Transition to Endemic Phase. In Applied Mathematics and Computational Intelligence (Vol. 12, Issue 2).
Bhatia, S., Lassmann, B., Cohn, E., Desai, A. N., Carrion, M., Kraemer, M. U. G., Herringer, M., Brownstein, J., Madoff, L., Cori, A., & Nouvellet, P. (2021). Using digital surveillance tools for near real-time mapping of the risk of infectious disease spread. Npj Digital Medicine, 4(1). https://doi.org/10.1038/s41746-021-00442-3
CDC. (2024). Interim Clinical Considerations for Use of COVID-19 Vaccines in the United States. CDC. https://www.cdc.gov/vaccines/covid-19/clinical-considerations/interim-considerations-us.html
Ganser, I., Thiébaut, R., & Buckeridge, D. L. (2022). Global Variations in Event-Based Surveillance for Disease Outbreak Detection: Time Series Analysis. JMIR Public Health and Surveillance, 8(10). https://doi.org/10.2196/36211
Hamdan, N. E. A., Yassen, A. O., & Loganathan Fahrni, M. (2024). COVID-19 Booster Vaccination in Malaysia. Journal of Clinical and Health Sciences, 9(1), 6–14. https://doi.org/10.24191/jchs.v9i1.19570
Ismail, S., Mohammad Ilham Husaini Mohammad Nazeri, & Sharifah Fairuz Syed Mohamad. (2021). The Impact of Covid-19 on Online Teaching and Learning (TnL) Towards Teachers in Malaysia. Malaysian Journal of Science Health & Technology, 7(2), 15–22. https://doi.org/10.33102/mjosht.v7i2.169
Kamarul Aryffin, H. A., Sahbudin, M. A. Bin, Ali Pitchay, S., Ab Halim, H., & Kamaliah Sahbudin, I. (2024). Technological Trends in Epidemic Intelligence for Infectious Disease Surveillance: A Systematic Literature Review. [In progress]
Kasamatsu, A., Ota, M., Shimada, T., Fukusumi, M., Yamagishi, T., Samuel, A., Nakashita, M., Ukai, T., Kurosawa, K., Urakawa, M., Takahashi, K., Tsukada, K., Futami, A., Inoue, H., Omori, S., Kobayashi, M., Komiya, H., Shimada, T., Tabata, S., … Saito, T. (2021). Enhanced event-based surveillance for imported diseases during the Tokyo 2020 Olympic and Paralympic Games. Western Pacific Surveillance and Response Journal, 12(4). https://doi.org/10.5365/wpsar.2021.12.4.903
Lencucha, R., & Bandara, S. (2021). Trust, risk, and the challenge of information sharing during a health emergency. Globalization and Health, 17(1). https://doi.org/10.1186/s12992-021-00673-9
MacIntyre, C. R., Chen, X., Kunasekaran, M., Quigley, A., Lim, S., Stone, H., Paik, H. Y., Yao, L., Heslop, D., Wei, W., Sarmiento, I., & Gurdasani, D. (2023). Artificial intelligence in public health: the potential of epidemic early warning systems. In Journal of International Medical Research (Vol. 51, Issue 3). SAGE Publications Ltd. https://doi.org/10.1177/03000605231159335
Mahussin, N., Mohd Jaapar, A., & Mustafa, L. A. (2021). Volatility of Technology and Healthcare Sectors Before and During Covid-19 Pandemic. Malaysian Journal of Science Health & Technology, 7(2), 39–47. https://doi.org/10.33102/mjosht.v7i2.166
Mboussou, F., Ndumbi, P., Ngom, R., Kamassali, Z., Ogundiran, O., Van Beek, J., Williams, G., Okot, C., Hamblion, E. L., & Impouma, B. (2019). Infectious disease outbreaks in the African region: overview of events reported to the World Health Organization in 2018. Epidemiology and Infection, 147, e299. https://doi.org/10.1017/S0950268819001912
Md Nadzri, M. N., Md Zamri, A. S. S., Singh, S., Sumarni, M. G., Lai, C. H., Tan, C. V., Aris, T., Mohd Ibrahim, H., Gill, B. S., Mohd Ghazali, N., Md Iderus, N. H., Lim, M. C., Ahmad, L. C. R. Q., Kamarudin, M. K., Ahmad, N. A. R., Tee, K. K., & Zulkifli, A. A. (2024). Description of the COVID-19 epidemiology in Malaysia. Frontiers in Public Health, 12. https://doi.org/10.3389/fpubh.2024.1289622
Mohamad Shariff, N. S., & Nur Hayani Izzati Abd Hamid. (2021). Consumers’ Buying Behavior Towards Online Shopping During The Covid-19 Pandemic: An Empirical Study In Malaysia. Malaysian Journal of Science Health & Technology, 7(2), 1–7. https://doi.org/10.33102/mjosht.v7i2.164
Morgan, O., & Pebody, R. (2022). The WHO Hub for Pandemic and Epidemic Intelligence; supporting better preparedness for future health emergencies. In Eurosurveillance (Vol. 27, Issue 20). European Centre for Disease Prevention and Control (ECDC). https://doi.org/10.2807/1560-7917.ES.2022.27.20.2200385
Ricks, P. M., Njie, G. J., Dawood, F. S., Blain, A. E., Winstead, A., Popoola, A., Jones, C., Li, C., Fuller, J., Anantharam, P., Olson, N., Walker, A. T., Biggerstaff, M., Marston, B. J., Arthur, R. R., Bennett, S. D., & Moolenaar, R. L. (2022). Lessons Learned from CDC’s Global COVID-19 Early Warning and Response Surveillance System. Emerging Infectious Diseases, 28(13), S8–S16. https://doi.org/10.3201/EID2813.212544
Shausan, A., Nazarathy, Y., & Dyda, A. (2023). Emerging data inputs for infectious diseases surveillance and decision making. In Frontiers in Digital Health (Vol. 5). Frontiers Media SA. https://doi.org/10.3389/fdgth.2023.1131731
Soliman Ashraf, Alyafei Fawziya, & Elalaily Rania. (2020). The death rate for covid-19 is positively associated with gross domestic products. Acta Biomedica, 91(2), 224–225. https://doi.org/10.23750/abm.v91i2.9514
Syed Mohamad, S. N., Sharifah Fairuz Syed Mohamad, Shahrina Ismail, Fathima Begum Syed Mohideen, Fatin Ahza Rosli, & Nur Faraheen Abdul Rahman. (2021). Preparedness and Attributes of COVID-19 among Malaysian Public during the Movement Control Order. Malaysian Journal of Science Health & Technology, 7(2), 23–29. https://doi.org/10.33102/mjosht.v7i2.170
WHO. (2022). Public health surveillance for COVID-19 Key points. https://www.who.int/publications/i/item/WHO-2019-nCoV-SurveillanceGuidance-2022.2
Worldometer. (2024, May 14). Coronavirus (COVID-19) Mortality Rate. https://www.worldometers.info/coronavirus/coronavirus-death-rate/#correct
Yanagawa, M., Lorenzo, J. C., Fukusumi, M., Shimada, T., Kasamatsu, A., Ota, M., Nakashita, M., Kobayashi, M., Yamagishi, T., Samuel, A., Ukai, T., Kurosawa, K., Urakawa, M., Takahashi, K., Tsukada, K., Futami, A., Inoue, H., Omori, S., Komiya, H., … Olowokure, B. (2022). Use of Epidemic Intelligence from Open Sources for global event-based surveillance of infectious diseases for the Tokyo 2020 Olympic and Paralympic Games. Western Pacific Surveillance and Response Journal, 13(3). https://doi.org/10.5365/wpsar.2022.13.3.959.
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