Siriluk Dungdawadueng

From my point of view, TAM suggests that ease of use alone is not enough for people to accept a new technology. When a new system replaces an old one, users need to feel that it is at least as useful, or even more useful, in helping them get their work done. Even if a system is easier to learn, people may hesitate to switch if they feel it slows…[Read more]

In my opinion, perceived ease of use and usefulness are often shaped more by context than by the technology itself. For example, users with low digital literacy may find a simple app difficult if they lack confidence with smartphones. Limited internet access or slow systems can also make a tool feel frustrating rather than helpful.

I also think…[Read more]

Hello Alex, thank you for your presentation. 😊

Discussion point 1
In my view, the evaluation should go beyond demand-side outcomes. Assessing supply-side processes—such as data collection practices, data quality, and user experience of the digital tools—is critical, as these factors strongly shape data reliability, service efficiency, and the rea…[Read more]

Experimental studies evaluate interventions using three key outcome measures:

1. Efficacy refers to whether an intervention works under ideal, controlled conditions (like in a laboratory or clinical trial). Efficacy asks “Does it work?”.
–> Example: A new vaccine shows 95% protection in a controlled clinical trial.

2. Effectiveness measures…[Read more]

I’d say social media engagement and social activities could be a major confounder here. Think about it – young adults are way more into hanging out at cafes, bars, concerts, and parties compared to older folks. They’re constantly meeting up with friends and going to events. So even if age itself doesn’t directly cause more contacts, their active…[Read more]

Case-Fatality Rate
Definition: The case-fatality rate (CFR) is the proportion of people diagnosed with a particular disease who die from that disease within a specified time period. It measures the severity or lethality of a disease among those who have been identified as having it.

How to Calculate:
CFR = (Number of deaths from a specific…[Read more]

1. What types of personal information are acceptable to collect in order to improve the performance and efficiency of digital contact-tracing apps? (For example: location data, Bluetooth proximity data, health status, or symptom reports.)

In my opinion, the type of data we collect really depends on how each country balances privacy and public…[Read more]

Q1. Why is a multidimensional like the HVI mentioned in the study more effective than conventional, single factor measures of socioeconomic status in revealing the complex contextual health inequities? And which factors do you choose to have in HVI in your country?

The HVI proves more effective than single-factor measures because health…[Read more]

Q1. Given regulations like GDPR (“right to be forgotten”), can a blockchain technology based on immutability (the inability to delete) ever be fully compliant with healthcare privacy laws?

In my view, pure blockchain can’t fully comply with GDPR because its immutability prevents data from being deleted, which conflicts with the “right to be forg…[Read more]

1) How does this study challenge the traditional use of weather-station data (temperature) in vector models?

From what I understood after reading the paper, this study really challenges the common assumption that weather-station temperature represents the actual conditions mosquitoes experience. Traditionally, vector models use ambient…[Read more]

Hi Nang Phyoe, Your malaria surveillance system is clearly presented with a strong rationale, well-defined case definition, and effective data flow. The focus on stakeholder involvement and system evaluation shows good planning and sustainability. To further improve, you may add real-time data reporting, GIS mapping for hotspot tracking, and…[Read more]

Hi Kevin, your presentation clearly shows a strong understanding of COVID-19 surveillance. The integration of passive, active, sentinel, syndromic, and event-based approaches is excellent and ensures timely detection. I like the use of digital tools for real-time reporting and your attention to legal, ethical, and stakeholder collaboration.…[Read more]

Hi Wah Eah Lwin, Your presentation on the malaria surveillance system in Thailand is very informative and well-structured. I particularly appreciate how you linked the national malaria elimination goal (by 2026) with the rising trend of P. vivax and P. falciparum cases, which effectively highlights the urgency of strengthening surveillance. The…[Read more]

In my opinion, Prime Minister Lee Hsien Loong and President Donald Trump showed very different communication styles during the COVID-19 pandemic when viewed through the six principles of CREC.

I think PM Lee was a strong communicator. His speeches were clear, calm, and easy to understand. He avoided technical terms and explained the situation in…[Read more]

After reading “The Evolution of Public Health Emergency Management” (Rose et al., 2017), I think Thailand has made progress in digital health development, especially in disease surveillance and communication systems. However, there are still areas that need improvement to strengthen our preparedness for future pandemics.

One theme that still nee…[Read more]

1. Which outbreaks were declared as PHEIC?
From what I read in the documents, WHO has declared these major ones:

2009 H1N1 (Swine Flu) – This was declared in April 2009 and lasted until August 2010
2014 Polio – Still ongoing actually, they reassess it every 3 months
2014 Ebola in West Africa – This was really serious – over 28,600 people infected…[Read more]

Omoleke and de Kiev’s evaluation revealed that the AEFI surveillance system in Kebbi State had major weaknesses affecting sensitivity and representativeness. From a public health perspective, I think the most serious design limitation is under-reporting due to passive surveillance and limited stakeholder participation. Many healthcare workers m…[Read more]

I think information technology really makes outbreak investigation much more efficient and accurate. In the past, everything relied on paper and manual reports, which took a long time. But now, with digital tools, each step can be done faster and more collaboratively.

For example:

During data collection, mobile apps or online systems help health…[Read more]