The Indonesian Hajj surveillance system: development and use

Abstract

The paper describes the development of the Indonesian Hajj surveillance system from 1950 to 2011 and highlights its potential use in hajj health research. It evolved from a basic registry of hajj pilgrims and number of Hajj-associated deaths (1950 to 1988) to an incident reporting system which collected demographic data with morbidity (pre-existing diseases) and mortality information which uses 21 International Classification of Disease (ICD) broad based groupings. It further evolved into a web based system with an additional android service which used the SMS gateway for data transmission and a manual back up system. From 1989 to 1996, the formal manual collection of basic mortality information started. However interruptions in data collection occurred on the years of 1997 and 1999 to 2003. Only in 2004, mortality information resumed until now. In 2008, the first mobile Java based SMS (short messaging service) surveillance system was implemented and used by mobile medical teams assigned to Indonesian Hajj groups. In 2010, the new updated system included pre-existing disease data on individual hajj pilgrims were collected in addition to mortality surveillance data. The recent improvements to the surveillance system have allowed for its use in: tracking imported/exported infectious diseases; promoting health via educating Hajj pilgrims; and identifying high risk pilgrims to reduce mortality and morbidity. From 2004 to 2011, data for mortality in Indonesian pilgrims could be used to evaluate verbal autopsies (M. Pane et al., 2013) during the Hajj, and even describe long term mortality patterns in Indonesian Hajj pilgrims (Masdalina. Pane, Kong, Imari, Glass, & Samaan, -). Future challenges include how raw data is processed and merged with the legacy system; ICD updates; cause of death determination by medical personnel; interruptions/updates to current mobile technologies; changes to surveillance software and hardware; and possibly the use of algorithms to assist medical teams.