1.Acceptance towards social network information system for earlier detection of Influenza outbreak
Muhammad Hafiz Bin Sulaiman ; Azimatun Noor Aizuddin ; Rozita Hod ; Sharifa Ezat Wan Puteh
The Medical Journal of Malaysia 2021;76(2):145-150
Introduction: Influenza outbreak causes high economic
burden to Malaysia and other countries in South East Asia.
Scientists have found a relatively new way to detect
influenza outbreaks early thus reducing the burden of
disease by early intervention. This new technology is a
social network information system which uses Facebook or
Twitter data to detect potential influenza cases. Such system
is good to be developed by the Malaysian government as it
can detect influenza outbreaks three weeks earlier than the
normal pathway. However, to implement this we require
good evidence that the development will be accepted by
potential users.
Objective: This study was looking at the acceptance towards
using social network information system among public
health workers.
Materials and Method: This study was done on 205
Malaysian One Health University Network (MyOHUN)
members through email and physical survey.
Results: Results show that 62.4% public health workers
accepted the use technology. The acceptance was shown to
be associated with performance expectancy (p<0.05).
However, unlike the very famous Unified Theory of
Acceptance and Use of Technology (UTAUT) model, the
acceptance of social network information system was not
associated with effort expectancy, social factors, facilitating
conditions and socio-demographic factors. Therefore, it is
suggested that social network information system be
developed by the authorities in Malaysia, and be developed
in a way that the system could strongly increase
performance in detection of outbreak earlier than the current
normal pathways. As such the system to be accepted and
used, it must be sensitive, specific and be able to detect
influenza outbreak early
Conclusion: The development of social network information
system is feasible as it is highly accepted and it’s potential
to improve early detection of influenza outbreak.