Internal Migration Reconciliation for the Kintampo HDSS Core Datasets using Probabilistic Record Linkage Techniques

• Main Author: Adda, Robert Awiah
• Format: Others
• Language: en
• Published: 2018
• Online Access: https://hdl.handle.net/10539/25302

A research report submitted to the Faculty of Health Science in partial fulfillment of the requirements for the degree of Master of Science (MSc) in Epidemiology - Research Data Management March, 2018. === Internal migration reconciliation involves the tracking of internal migrants to link their places of origin and destination for each movement within a given Health and Demographic Surveillance Area (HDSS) site. This involves several related activities adopted to account for the time the person moves from one location to the other but, remaining under the HDSS surveillance. This poses a major challenge for longitudinal studies particularly Kintampo HDSS site, where manual data capture modality is still being used. For most HDSS sites, all data related operations rely much on an individual unique personal identifier which is issued to identify a resident member during registration. The identifier enables the data system to keep track of resident members over an extended period of time to enable an accurate estimation of the population under surveillance. Movement of resident members within the geographical boundaries of the surveillance areas must be tracked based on these personal identifiers. However, residents’ records may not be linked to each other in the event of multiple movements when the personal identifier cannot be recorded or is wrongly recorded. The effort in reconciling such cases of inconsistencies resulting from internal migration involves the printing of mismatched records for field supervisors to trace back to original locations to ascertain the identity of migrants. This process is very expensive as a full-time field supervisor is required and the reconciliation process is time demanding. In this project, we explored alternative automatic and cheaper method of reconciling all categories of discrepancies that exist in the internal migration datasets using the probabilistic record linking techniques.A theoretical foundation for probabilistic record linkage technology was provided and the sequential order was followed.The EM algorithm was used in the estimation of parameters. This research report demonstrate clearly that the probabilistic record linkage frame work by Fellegi and sunter is useful for HDSS internal migration reconciliation. The EM algorithm showed an improved performance in terms of linked records compare to the probabilistic framework. However, more work needs to done to explore other parameter estimation algorithm such as the Frequency-based EM algorithm. Such results can be compared to the results in this report. === LG2018