Surveillance and Data Analysis

Introduction

Effective surveillance and data analysis are fundamental to the fight against malaria. These activities provide real-time insights into disease trends, support strategic decisions, and allow programs to respond quickly to changes in malaria transmission patterns. By systematically gathering and analyzing data, health programs can track the impact of interventions, detect outbreaks early, and allocate resources efficiently. This chapter will guide you through the key components of malaria surveillance and the analytical tools used to transform data into actionable knowledge, empowering program staff to make informed, data-driven decisions.

The topics covered here complement those taught in the Foundational Data Skills, Foundational R and Foundational Epidemiology Knowledge modules so make sure you have covered these topics first!

Learning Objectives

By the end of this chapter, you should be able to:

1. Understand the role of malaria surveillance in monitoring and controlling the disease and recognize different surveillance methods.

2. Identify and describe common data collection methods used in malaria surveillance, including health facility reporting, community-based surveillance, and surveys.

3. Apply basic data analysis techniques for describing, visualizing, and interpreting malaria data trends and spatial patterns.

4. Assess the quality and reliability of surveillance data through quality checks and understand how data limitations can impact decision-making.

5. Communicate and use data effectively to support malaria control strategies, prioritize high-burden areas, and engage stakeholders.