Biology Reference
In-Depth Information
attributes than described in Table 13.2, especially with an emphasis on pre-
serving data integrity. The data gathered (health records of patient disease
and syndrome) by the healthcare workers from the provider will be stored in
this database. The same data will be used in the event detection analysis.
13.5.2.3 Analysis for Detection of Events
Periodically, daily, every other day, or weekly, health officials will analyze
the data for a given time frame to monitor and detect any emerging health
threats. They may also execute other detection algorithms or processes for
detection of possible adverse events. The users (detection and monitoring
staff, namely, health officials) will need to filter the dataset through various
combinations of selected parameters identified in Table 13.4.
13.5.2.4 Alerting and Reporting of Emerging Disease Outbreaks
Table 13.5 states the requirements for the production of weekly disease surveil-
lance reports such as the Weekly Epidemiological Report and issuing alerts of
potential threats such as emerging disease outbreaks. The health official issuing
the alert will extract a summary of the weekly report (e.g., Weekly Epidemiological
Report) and send the report to the healthcare workers each week, via e-mail, for
example. In the event of detecting a significant health threat, the resources asso-
ciated with detection and monitoring (e.g., Chief Epidemiologist) will notify the
decision makers (e.g., Medical Officer of Health or Regional Epidemiologist) of
the potential threat. Thereafter, the decision maker will decide the priority level
and authorize the detection and monitoring staff to issue a bulletin (alert) to those
health officials in the vulnerable areas. The weekly reports are regarded as low-
or high-priority bulletins (reports) and the immediate notifications (alerts) are
regarded as urgent-priority bulletins (Dias et al. 2007, Anderson et al. 2007).
13.6. Conclusions
The Tamil Nadu morbidity report's granularity of information is more so
than the Sri Lankan weekly epidemiological report. Doctors in both coun-
tries use charts and admission or outpatient registries where a large por-
tion of patients' data can be collected. Pervasive mobile technology can easily
be leveraged in Asia (Zainudeen and De Silva 2007, Zenith 2008), while the
expensive detection- and decision-assisting software (Sabhnani et al. 2005)
must be located centrally; both mobile and server technologies must be easily
scalable. The ICT system's success is highly dependent on the availability of
data. It is uncertain at this point as to whether even the data available can be
retrieved without political intervention/disruption or societal objection.
