02155nas a2200181 4500000000100000008004100001260003200042653002500074653001500099653002200114653001600136100001200152700001200164245005500176520169900231022002501930020001801955 2025 d bSpringer Nature Switzerland10aDisease surveillance10aMonitoring10aTropical diseases10aInnovations1 aOgwu MC1 aIzah SC00aInnovations in Disease Surveillance and Monitoring3 a

The surveillance and monitoring of tropical diseases are vital components of public health strategies aimed at reducing the burden of these diseases on vulnerable populations. This chapter explores innovations in surveillance technologies that enhance the detection, monitoring, and management of tropical diseases. The focus is on emerging tools such as remote sensing, Geographic Information Systems (GIS), data analytics, predictive modeling, and community-based surveillance systems, which have significantly transformed traditional surveillance methodologies. For example, remote sensing and GIS technologies provide detailed spatial and temporal data to map disease spread, support outbreak prediction, and enable early detection, improving response efforts. Integrating big data, artificial intelligence (AI), and machine learning facilitates predictive modeling that enhances outbreak forecasting and optimizes resource allocation. Community-based surveillance leveraging mobile platforms empowers local populations to participate in real-time disease monitoring, particularly in remote areas where formal healthcare infrastructure may be limited. Despite the potential of these innovations, key challenges such as data privacy concerns, technological accessibility, and integrating new tools with existing systems remain. Future developments in disease surveillance will require addressing these challenges, refining existing technologies, and fostering collaboration across health networks to ensure sustainable and effective disease control. The continued evolution of surveillance technologies holds great promise for effectively managing and eliminating tropical diseases.

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