01494nas a2200253   4500000000100000008004100001260002500042653002300067653002100090653002500111653002500136653001700161100001500178700001600193700001200209700001600221700001300237245009200250856006200342300001400404490000600418520079100424022002501215       2024                            d  bFair East Publishers10aBig Data Analytics10aMachine learning10aEpidemic Forecasting10aPublic Health Policy10aData Privacy1 a Igwama GT1 a Olaboye JA1 aMaha CC1 aAjegbile MD1 a Abdul S00aBig data analytics for epidemic forecasting: Policy Frameworks and technical approaches  uhttps://fepbl.com/index.php/ijarss/article/view/1334/1566  a1449-14600 v63 a<p>This review paper explores the intersection of big data analytics and epidemic forecasting, highlighting both technical approaches and policy frameworks. It delves into data collection methods from IoT, mobile data, and social media. It discusses analytical techniques such as machine learning and predictive modelling. The paper also addresses the regulatory and ethical considerations necessary for effective data use, emphasizing the need for adaptive policy frameworks to support innovation. The importance of international collaboration and global initiatives for data integration and sharing is underscored. By integrating advanced analytics with robust policies, the potential for enhanced epidemic forecasting and proactive public health responses is significant.&nbsp;</p>
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