Khaing Zin Zin Htwe

Thank you for your feedback, and you have good points. Integration of GIS can ensure better Epidemiological analysis. And also, getting consent from patients is a necessary step.

The presentation is very attractive including the contents and design. The system itself especially data flow diagram is comprehensive. And I would like to thank you for giving a perfect example of syndromic approach to surveillance. For evaluation indicators, I would like to add usability because in my opinion, all members of the community…[Read more]

Thank you for the presentation especially about clear case definition including ICD codes. What I would like to comment is that adding event-based surveillance such as web search data, school absentee would be beneficial to the system.

As I have always interested in AMR, this presentation introduced very good points to consider. And thank you for giving source to GLASS. One question I would like to ask is that what would be the role of active surveillance in AMR. Passive surveillance is approachable in healthcare settings. I would really appreciate your answer in active…[Read more]

Dear Sara, thank you for your question. Hepatitis alone can be diagnosed with clinical signs and symptoms such as jaundice, painful enlarged liver, and with imaging and laboratory testing for liver enzymes. However, to know the cause of it (e.g., HBV, HCV), we need laboratory confirmation. For testing criteria, WHO recommends testing of all people…[Read more]

It is beneficial to consider big data issue beforehand. I wish there be a day where big data analysis no longer requires high technical skills.

It is true that with decisions based on wrong data, we would have to face with their consequences. It is very crucial to evaluate the system regularly so that right decisions can be made.

As the name “early” suggests, the main challenge would be timeliness. For remote areas where resources and network coverage are lacking, it is a challenge to synchronize real-time data.
Another challenge would be development of complex algorithms where there is no definite threshold. Moreover, without reliable baseline data, shooting early alarms…[Read more]

The following issues need to be considered when trying to reach this goal:

Data quality: to reduce errors associated with data manipulation, to prevent losing the richness of information found in unstructured data by data standardization
Interoperability: to easily share or exchange high volume, heterogenous and widely distributed data
Data…[Read more]

I also heard President Trump talking about the pandemic ending soon which is false reassuring and not proper messaging. When communicating uncertainty, he should have avoided such things.

First, PM of Singapore covered all the recommendations for risk communication by WHO. Both his verbal and non-verbal communication during this speech was a perfect example of communicating during public health emergencies.
Second, President Trump is a good communicator in gaining trust of the public especially by emphasizing on the availability of…[Read more]

WHO has declared the following diseases as PHEIC:
1. H1N1/Swine flu (2009)
2. Wild polio virus (2014)
3. Ebola virus disease (2014 and 2019)
4. Zika virus (2016)
5. COVID-19 (2020)
These outbreaks have been declared as PHEIC because they are extraordinary events which require international response. Moreover, they spread internationally with…[Read more]

The article reflects the real situation of global air pollution which is causing varieties of environmental and health problems.
With the current rate of increase in air pollution in ASEAN countries, we might have to face it, in the near future, as a public health emergency like India has. Air pollution is included under technological…[Read more]

If the cases are over-reported, the data might falsely call for response which can lead to human resources and budget loss. If the cause of overestimate is due to unclear case definition, antibiotics might be wrongly administered leading to drug resistance, which in turn causes poor health status of the people and increased health cost.
On the…[Read more]

Thank you for pointing out how the low quality of data can have negative impact on all levels of management, and also how the research findings might also be affected.

It is a great idea to bring up the importance of IT in communication between teams and organization. I’m sure forming a rapid response team will be a lot easier and faster with the use of mobile technology.

According to the previous video, malaria surveillance system in Thailand is a very good example to highlight the role of IT in outbreak investigation. IT assists in almost every step of the process:
– Lab confirmation is made easier and faster with the use of IT. And to confirm case excess from normal expectancy, electronic database will help to…[Read more]

It’s a great idea to monitor animals. If we can also perform surveillance on unusual behaviors and deaths of those animals, maybe it can provide hints to future outbreaks (e.g., monitoring rat falls for plague).

It’s undeniable that my country too has weak systems to support research and other studies with data. It would be better if we could strengthen that function of surveillance systems.