Emergency preparedness for public health threats, surveillance, modelling &amp; forecasting

Bedi, Jasbir Singh; Vijay, Deepthi; Dhaka, Pankaj; Gill, Jatinder Paul Singh; Barbuddhe, S. B.

doi:10.4103/ijmr.ijmr_653_21

Cited by 5 publications

(5 citation statements)

References 97 publications

(110 reference statements)

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“…This paper delves into the multifaceted dimensions of technology in healthcare preparedness, examining its impact on surveillance, diagnostics, treatment, communication, and the overarching potential to mitigate the impact of emerging health threats. One of the cornerstone elements of healthcare preparedness is the ability to detect and monitor emerging health threats swiftly (Bedi et al, 2021). Technology has revolutionized disease surveillance by enabling real-time tracking and analysis of health data.…”

Section: Technology In Healthcare Preparednessmentioning

confidence: 99%

Pandemic Epidemiology: A Comprehensive Review of Covid-19 Lessons and Future Healthcare Preparedness

Olufunke Omotayo,

Muridzo Muonde,

Tolulope O Olorunsogo

et al. 2024

imsrj

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This comprehensive review examines the epidemiology of the COVID-19 pandemic, shedding light on pivotal lessons learned and their implications for future healthcare preparedness. Analyzing the global landscape of the virus, the review delves into transmission dynamics, risk factors influencing severe outcomes, and the effectiveness of diverse public health interventions. It provides a nuanced exploration of the challenges encountered by healthcare systems worldwide, elucidating strengths and vulnerabilities brought to the forefront by the pandemic. The study underscores the need for a multifaceted approach to healthcare preparedness, emphasizing the critical importance of integrated surveillance systems, agile response mechanisms, and the implementation of evidence-based strategies. Drawing on experiences from diverse regions, the review identifies key lessons in pandemic management, showcasing successful strategies and innovative interventions that have proven effective in curbing the virus's spread. Moreover, the review examines the role of vaccination campaigns in shaping the trajectory of the pandemic and emphasizes the vital contribution of technology in bolstering healthcare resilience. As the world grapples with the long-term effects of COVID-19, this review aims to distill essential insights that can inform future pandemic preparedness efforts. By synthesizing knowledge gleaned from the challenges posed by COVID-19, this comprehensive analysis offers a foundation for evidence-based strategies, guiding global healthcare systems towards enhanced readiness to confront and mitigate the impact of future infectious threats. Keywords: Pandemic, Epidemiology, COVID-19, Healthcare, Review.

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Section: Technology In Healthcare Preparednessmentioning

confidence: 99%

Pandemic Epidemiology: A Comprehensive Review of Covid-19 Lessons and Future Healthcare Preparedness

Olufunke Omotayo,

Muridzo Muonde,

Tolulope O Olorunsogo

et al. 2024

imsrj

View full text Add to dashboard Cite

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“…Globally, the significance of robust surveillance in the battle against zoonotic diseases is crucial. Surveillance systematically generates critical data that underpin strategic efforts to confine, manage, and alleviate the impact on susceptible human and animal populations [ 30 ]. Early detection assumes significant importance in the containment of infections within their geographical origin and is a necessity accentuated by the contemporary global mobility of populations.…”

Section: Prioritizing Surveillance Of Zoonotic Diseasesmentioning

confidence: 99%

“… Standardized and adaptable protocols: Standardized laboratory protocols ensure consistency and reliability in diagnostic procedures and foster seamless collaboration among personnel. Designed to be adaptable, these protocols should respond to evolving research needs by ensuring rigorous and responsive diagnostic processes [ 30 ]. …”

Section: Need For Multisectoral Collaboration For Zoonotic Disease Su...mentioning

confidence: 99%

Surveillance and response strategies for zoonotic diseases: a comprehensive review

Sharan,

Vijay,

Yadav

et al. 2023

Science in One Health

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“…Predictive modelling has become a cornerstone in public health, especially concerning disease outbreaks. This scientific approach uses statistical techniques and algorithms to analyze historical data and predict future events (Bedi, Vijay, Dhaka, Gill, & Barbuddhe, 2021;Xiong, Hu, & Wang, 2021). Predictive modelling harnesses various data sources in infectious diseases, including epidemiological, environmental, and socio-economic data, to forecast disease outbreaks' likelihood, spread, and impact (Basu & Sen, 2023;Naraharisetti, 2023).…”

Section: Introductionmentioning

confidence: 99%

Predictive Modeling for Disease Outbreaks: A Review of Data Sources and Accuracy

Scholastica Ijeh,

Chioma Anthonia Okolo,

Jeremiah Olawumi Arowoogun

et al. 2024

imsrj

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This review explores the dynamic field of predictive modelling for disease outbreaks, focusing on the data sources, modelling techniques, accuracy, challenges, and future directions integral to its advancement. It underscores the significance of diverse data sources, including epidemiological, environmental, social media, and mobility data. It also discusses various modelling approaches, from statistical models to advanced machine learning algorithms and network analysis. The review highlights the critical role of accuracy and validation in predictive models, alongside the challenges posed by data quality, model complexity, and the ethical use of personal data. It outlines promising research avenues, such as improving data collection methods, integrating novel data sources like genomic data, and leveraging emerging technologies such as AI and IoT to enhance predictive capabilities. This comprehensive overview emphasizes the importance of predictive modelling in informing public health decisions and the continuous need for innovation and collaboration to address the complex dynamics of disease outbreaks. Keywords: Predictive Modeling, Disease Outbreaks, Data Sources, Machine Learning, Public Health, Emerging Technologies.

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Emergency preparedness for public health threats, surveillance, modelling & forecasting

Cited by 5 publications

References 97 publications

Pandemic Epidemiology: A Comprehensive Review of Covid-19 Lessons and Future Healthcare Preparedness

Pandemic Epidemiology: A Comprehensive Review of Covid-19 Lessons and Future Healthcare Preparedness

Surveillance and response strategies for zoonotic diseases: a comprehensive review

Predictive Modeling for Disease Outbreaks: A Review of Data Sources and Accuracy

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