Aye Thinzar Oo

[Aye Thinzar Oo]

To identify the reasons for non-use of bednets, qualitative follow-up methods such as focus group discussions and in-depth interviews should be employed to explore potential barriers, including cost, discomfort, cultural beliefs, perceived low malaria risk, and limited awareness. In addition, incorporating open-ended questions into a revised survey instrument would help capture respondents’ explanations in their own words.

[Aye Thinzar Oo]

I think for me, by combining the identified by:
Sex: Female
Appearance: cute big ears
Study Major: Biomedical and Health Informatics
Study place: Faculty of Tropical Medicine, Mahidol University
Status:MSc BHI student for the 2024 academic year and the only female student from Myanmar in this year.
Place of residence: Myanmar (Burma)

[Aye Thinzar Oo]

In my opinion, TAM suggests that if a new technology is easier to use, it is likely to be perceived as more useful than the old technology.
For example, replacing a paper-based patient record or a complex EHR with a new EHR that has simple menus, fewer data-entry steps, and auto-fill features makes it easier for health workers to complete information. As a result, they perceive the new system as more useful because it saves time, reduces errors, and improves workflow.

[Aye Thinzar Oo]

Let me share my opinion on the Health information system, external variables influencing perceived ease of use and perceived usefulness include health workers’ computer skills, system interface design and reliability, availability of training and technical support. And infrastructure factors such as internet connectivity and electricity availability. Poor internet access and no electricity can reduce perceived ease of use, even if the system is well-designed.

[Aye Thinzar Oo]

Efficacy: measures whether an intervention works under ideal conditions.
E.g. A new electronic medical record (EMR) system is tested in a pilot project with well-trained staff, good internet access and strong technical support. Under these optimal conditions, the EMR system shows significant improvement in data accuracy.

Effectiveness: how well the intervention performs in a real-world setting.
E.g. When the EMR system is rolled out to the health facilities with limited internet connectivity, high workload, and varying staff skills, the data quality is improved, but not much in the pilot.

Efficiency evaluates whether outcomes are achieved with optimal use of resources.
E.g. In this case, the EMR system reduces paper costs and reporting time and decreases staff workload. It will result in better outcomes with fewer resources.

[Aye Thinzar Oo]

1. Improving the effectiveness of digital contact-tracing applications requires collecting only essential public health data, supported by appropriate technology, strong data protection, and clear privacy protocols.

2. Countries with limited internet access or technological capacity, digital COVID-19 tools can be adapted through some solutions such as SMS, offline data collection software with delayed synchronization, and integration with existing community-based or paper-based surveillance systems used by health volunteers or health workers.

[Aye Thinzar Oo]

It can be considered another confounder, that living in urban or rural areas. Younger people are moving to live in urban centers for education and employment. Since urban environments have a higher population density, this leads to more frequent contacts through public transport, shared living spaces, and lifestyle changes. Therefore, the observed active contact pattern may be attributable to the living environment.

[Aye Thinzar Oo]

Case-Fatality rate
Definition: The case-fatality rate is the proportion of persons with a particular condition (cases) who die from that condition. It is a measure of the severity of the condition.
Formula: (Number of cause-specific deaths among the incident cases / total number of incident cases) x 100
Usefulness: It is widely used to measure disease severity, helps to compare lethality between different diseases.

Reference:
https://archive.cdc.gov/www_cdc_gov/csels/dsepd/ss1978/lesson3/section3.html

[Aye Thinzar Oo]

The intervention that I am considering is vaccination. This is a powerful public health tool that, in the context of the model, will be introduced to represent the real-world vaccine rollout in Myanmar during the third wave.
In the SIRV framework, vaccination is an intervention that changes the flow of individuals between compartments.
Vaccination Rate: This is the speed at which the vaccine is administered to the population. During Myanmar’s third wave, the vaccination rate was low to moderate.
Vaccine Efficacy and effectiveness: Different vaccines have different levels of effectiveness.
Efficacy Against Infection: This reduces the likelihood that a vaccinated person will become infected if exposed to the virus. Even with high efficacy, breakthrough infections can occur.
Efficacy Against Severe Disease: This reduces the likelihood that an infected person will develop severe illness, require hospitalization, or die. This is a critical metric for demonstrating how vaccination alleviates the burden on the healthcare system, which was severely strained in Myanmar during the third wave.

Reference
https://www.who.int/news-room/feature-stories/detail/vaccine-efficacy-effectiveness-and-protection
https://pmc.ncbi.nlm.nih.gov/articles/PMC10399871/

[Aye Thinzar Oo]

From the Week 1 discussion, I selected the topic: “How do varying vaccination rates affect the persistence of the COVID-19 third wave in Myanmar?” COVID-19 is the infectious disease caused by the novel coronavirus known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2).
During the third wave in Myanmar, access to vaccines was extremely limited. The wave began in late May 2021 and peaked in July–August 2021, with very high test-positivity rates and widespread transmission across townships. The healthcare system was severely strained, marked by oxygen shortages, lack of hospital beds and medicines, and many patients being treated at home or dying outside hospitals. The public health response and vaccine rollout were further disrupted by the political crisis following February 2021. Several vaccines were approved for use in Myanmar, including Moderna, Covishield, Pfizer, Sinovac, and Sinopharm. Vaccination rollout began in early 2021, but the process was disrupted and coverage remained low to moderate during the June–August 2021 surge.
In considering vaccine effectiveness, two dimensions are important:
1.Protection against infection, which reduces susceptibility and transmission.
2.Protection against hospitalization and severe disease, which reduces severity and deaths.
A suitable framework for investigating the persistence of COVID-19 under varying vaccination rates is the SIR (Susceptible–Infectious–Recovered) and Vaccinated. In this model:
•S (Susceptible): individuals who can contract the disease.
•I (Infectious): individuals who can transmit the virus to others.
•R (Recovered): individuals who have recovered and gained immunity.
•V (Vaccinated): individuals who have received one or two doses (with different levels of protection).
Vaccination reduces susceptibility, severity, and transmission. The model, therefore, incorporates both vaccination rates and vaccine efficacy. Different vaccines have different levels of efficacy, which directly impacts disease spread and persistence.
The main purpose of vaccination is to reduce the overall disease burden and transmission. However, Myanmar faced many challenges during the third wave, including difficulties in vaccine distribution and limited vaccination among healthcare providers.
Source of data
Country Office Annual Report 2021 Myanmar – UNICEF
Myanmar Ministry of Health and Sports, Myanmar (For official case counts and vaccination data, though this data may be challenging to find or verify due to the political situation).
Reference:
https://www.unicef.org/media/117271/file/Myanmar-2021-COAR.pdf
https://covid19.trackvaccines.org/country/myanmar/
https://pubmed.ncbi.nlm.nih.gov/37841829/

[Aye Thinzar Oo]

The disease I am familiar with is COVID-19, and I would like to explore its transmission dynamics and impacts in Myanmar in the context of vaccination.

Research Question: What is the impact of varying vaccination rates and vaccine efficacy on the long-term persistence and potential elimination of COVID-19 in a population?

[Aye Thinzar Oo]

1. The author examined the suicide issue in Thailand due to an increasing trend and a rate exceeding 6 suicides per 100,000 inhabitants. Thailand’s situation is distinct from other countries because of its unique cultural, social, and economic contexts. Possible contributing factors include economic conditions (e.g., income levels, unemployment rate) and social influences.
2. Let me pick one potential risk factor that the author mentions in the paper is “Other Social factors that contributed to the higher suicide rates were divorce rate”.
One social factor the author identifies as contributing to higher suicide rates is the divorce rate. The study found that provinces such as Saraburi, Pathumthani, Samutprakan, Chonburi, Rayong, and Phuket had an average divorce rate exceeding 8 couples per 1,000 households. In Thailand, higher divorce rates are observed in more educated and economically prosperous societies. These areas also tend to have a higher proportion of female-headed households, ranging from 31% to 45%. The social and emotional strain of marital dissolution, combined with potential economic and familial instability, can increase suicide risk.
3. Statistical modeling used in studying the epidemiological and spatial aspects of the suicide rate in Thailand according to a data-driven approach. The data used in the province comparison of the divorce rate. The divorce rates showed that the findings of other social backgrounds statistically had an impact on the suicide rates.

[Aye Thinzar Oo]

Thank you for your guidance, Wannisa, and Aung. Firstly, I updated the R version. Then, I installed ‘fmesher’ and installed INLA with this link==> install.packages(“INLA”,repos = “https://inla.r-inla-download.org/R/stable”, dep = TRUE)
Now I am okay and started playing INLA and to complete week 1 assignment.

[Aye Thinzar Oo]

I had still trouble installing th INLA package, see the following error message.
* installing *binary* package ‘INLA’ …
Warning in system(paste(“cp -R .”, shQuote(instdir), “|| (“, TAR, “cd – .| (cd”, :
‘cp’ not found
ERROR: installing binary package failed
* removing ‘C:/Users/Administrator/AppData/Local/R/win-library/4.4/INLA’
Warning in install.packages :
installation of package ‘INLA’ had non-zero exit status
Trying from this link https://www.r-inla.org/download-install and I also try the Wannisa mention link, but can’t solve it on my window.
I am still trying to install INLA package.
Thanks.

[Aye Thinzar Oo]

Incorporating location into epidemiological studies has historically been difficult due to challenges in gathering and analyzing spatial data. Spatial epidemiology, an interdisciplinary field, requires expertise in epidemiology, geography, statistics, and computer science (particularly GIS) to effectively analyze disease patterns across geographic areas.

The place where an individual lives or works is considered a potential disease determinant because it can reveal spatial patterns and provide insights into disease distribution. Geographical epidemiology uses this information to explore environmental factors, social conditions, and access to healthcare that may influence health outcomes.

[Aye Thinzar Oo]

3. What factors influence user satisfaction with vaccination apps?
From the reading of articles, I would like to share some information that is my opinion.
User satisfaction with vaccination apps is shaped by five main factors: the quality of content, app functionality, overall user experience, service attitude, and data privacy. Privacy is the most crucial factor. Users show the greatest dissatisfaction with the management of their personal information within the app. Users expressed the greatest dissatisfaction regarding how their personal information was managed.

[Aye Thinzar Oo]

How did government restrictions affect mobility patterns?

The government restriction on movement affected dimensions of human mobility related to COVID-19 transmission. The local government in Tak province announced the closure of the Friendship Bridge entry and exit restrictions and checkpoints were widely established on main roads to control nationwide curfew between 10pm and 4am.

The interval 4: period of most restricted travel: 4 April 2020 to 3 May 2020(30 days).
For the data analyses using radius of gyration (RoG) metric,
the RoG values were consistently lower during nighttime hours than during the day-time. During the curfew hours, the RoG declined to markedly low values in Intervals 3 and 4.

In the Cross-border and village boundary mobility analysis : decrease in the number of trips, and particularly in the number of long trips. Comparing the number of trips between Interval 1, the least restricted, and Interval 4, the most restricted, It can see a decrease in short trips of 32% and a decrease in long trips of 70%.

International cross-border movement from Thailand into Myanmar, the number of cross-border trips per participant, broken downs into long and short trips. The number of trips in Interval 1 was roughly double that in the other intervals, including Interval 5.

[Aye Thinzar Oo]

How did the web-based platform compare to the mobile app?

Mobile apps typically deliver faster performance and can operate offline, providing potential advantages in security. However, web-based platforms—while requiring an internet connection—often reach a broader audience and can encourage higher levels of user engagement.

In the context of AEFI reporting during the 2020 seasonal influenza vaccination campaign, both a web-based notification platform and a mobile app were used. Of the 2,408 individuals who agreed to participate in the RCT, 1,196 were assigned to the CANVAS (web) arm and 1,212 to the CANImmunize (app) arm. Demographic data from the referenced articles indicated a higher usage rate for web-based notifications compared to the mobile app, suggesting the web platform had greater utility in vaccine safety surveys and user interface effectiveness.

Ease of use was higher among web-based notification platform users. The funding suggests that a web-based survey link is an acceptable approach for active participant-centered AEFI reporting and improves the acceptability and usability of app-based reporting.

[Aye Thinzar Oo]

Hi everyone,
From this article, I’d like to share my thoughts on two of the questions.
What were the significant benefits reported by the studies?
Childhood vaccinations, accessible via mobile platforms according to the study, offer key benefits. While the evidence supporting the effectiveness of childhood vaccination apps in specific areas is limited, the technology presents an opportunity for improved vaccine delivery.
How do user perceptions of vaccination apps vary?
User perceptions of vaccination apps vary based on some factors, such as technology knowledge, education, usage, and familiarity with the apps.

[Aye Thinzar Oo]

It is my first time using and exploring VR. It is difficult for me, but my kid and I enjoy playing with it. I think it can be useful for an electronic poster presentation at an academic conference. But some people like me , not family with this. it needs to be take time to use freindly.
My screen is here

[Aye Thinzar Oo]

Personal Experience
Firstly, I watched VR videos on YouTube and other VR apps in my mobile phone.
I set up the VR headset by following the tutorial video. After that, I tried the Google Cardboard app, VR roller coaster, and a dinosaur from YouTube. That is the first time I’ve watched a VR video. It’s not very comfortable for me, but my baby enjoys it with your VR, Arjan. But for a baby, it wouldn’t be good for them to use for a long time, I think.

Link with the concepts of the Lecture
Yes, I feel stereoscopic vision. When I wore the VR with lenses, I got motion sickness, and I think I need to get familiar with VR devices.
My phone is bigger than the VR cardboard size. I think it will be compatible with high-pixel and good-quality resolution smartphones, which makes to feel like watching better experiences.
User comfort, including visual function and motion sickness, also plays a critical role. A good VR experience depends on these factors for success. I believe VR technology offers many valuable benefits.
https://drive.google.com/file/d/14_kfYP2hQxDP12eQYpk-YwAAW3h_xyB3/view
https://drive.google.com/file/d/1uYELb3_u5qdBREIyJVcqi8UgobPFILKc/view
https://drive.google.com/file/d/16XkAFZIn_9kqB5SugszMh635APwr9EJg/view

[Aye Thinzar Oo]

1. Visualization and Experimentation

https://snipboard.io/UGAolT.jpg
In the above screenshot, it can be seen: (a) connection loss (b) when I did the lab test at my home, it was raining and windy so the temperature and humidity is the same (c) when I changed the state of sensor and put on the hot water status.
2. Challenges & Solutions
It was a challenge for me, I couldn’t connect easily with my Google sheet data to show the result. I took one day and I was stopping, and I was finding the connection issue (plug in/ unplug the USB port and checking the connecting port). But still can’t solve. I tried another way on my home Wi-fi connection, and I got an idea to change the wi-fi connection. I changed and used my mobile phone hotspot connection, and after connecting with the mobile hotspot, it was working.
3. Ideas for Improvement & Application
I think, it needs to improve in the sensor device, it can connect network connection no need to have more speed. In my opinion, when the sensor device shows a blue color alert, it can send a notification to Google Sheets. It can be used with email notification, which will be better.

[Aye Thinzar Oo]

I choose the articles of “A Secure IoT-Based Healthcare System With Body Sensor Networks”
KUO-HUI YEH, (Senior Member, IEEE)
National Dong Hwa University, Hualien 97401, Taiwan
Corresponding author: K-H. Yeh (khyeh@gms.ndhu.edu.tw)
https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7779108
Summary:
The IoT-based healthcare system using body sensor networks is introduced, comprising two authentication processes among the smart objects, the local processing unit and the backend server. (he system initialization phase and the authentication phase)
In the system initialization phase, security will be included and shared across communication entities (wearable bio-sensors, the LPU and the BSN server via a secure channel).
– Security parameters received during the registration phase are under a secure channel.
– The LPU (local processing unit) and sensors are equipped with secure storage.
-The sensors to LPU and LPU to BSN (Body Sensor Network) channels are insecure, which means the transmitted data may be sniffed out In the next two authentication phases presented for securing all the communication and data exchanges among communication entities.
Key:
– Security parameters received during the registration phase are under a secure channel,
-the LPU(local Processing Unit) and sensors are equipped with secure storage
– BSN server is trusted and all the database accesses are safe
– A trusted third party exists to support the public key infrastructure
Challenges:
– computation cost of smart objects and network heterogeneity,
– In the healthcare system, two communication channels, i.e. ‘‘sensors to LPU’’ and ‘‘LPU to BSN server,’’ are focused on, since the openness of these two channels means it cannot be guaranteed that all the data transmissions on them are secure. An attacker (or hacker) may therefore wish to launch malicious behaviors, such as bio-data eavesdropping on a specific person and entity counterfeiting for purposes of spoofing, on these insecure channels. The result could be huge and unpredictable losses.

[Aye Thinzar Oo]

I’ll share the final project assignment for week 4 with you. I use the dataset of patient data collected under the Thai-Myanmar border clinic in 2019.
Final Project
https://lookerstudio.google.com/u/0/reporting/48d49395-a564-4443-ae33-7b17cac91b58/page/7FtJF

[Aye Thinzar Oo]

Hello, Let me share week4 assignment,
Looker studio

https://lookerstudio.google.com/u/0/reporting/34805cd8-eb29-45c8-bedd-852e6820f7e0/page/uWlIF

[Aye Thinzar Oo]

Hello everyone, I would like to share week3 assignment of data visualization.
Please see the following Looker Studio Report link
Data visualization

And hope your additional feedback!

[Aye Thinzar Oo]

Let me share the COVID-19 circulation dashboard of Myanmar by WHO,
Link
the link is here: https://data.who.int/dashboards/covid19?m49=104
What I like: on that
The design effectively utilizes a single-page layout with color-coded bar charts, line graphs, and stacked bar charts. This color scheme, limited to various shades of blue, enhances clarity by visually representing trends and group differences.
What I don’t like, only my opinion,
However, some charts suffer from a lack of user-friendliness due to a single command applied universally, hindering easy comprehension. This uniformity, while potentially streamlining design, can compromise clarity and usability for specific chart types.

[Aye Thinzar Oo]

I’ve learned in Week4 Telemedicine, let me share with text summary.
Telemedicine is considered a subset of telehealth, specifically referring to clinical services.
Benefits
*. Quick access to care and easy access to specialists,
*. Convenience
*. cost saving
*. Reduce in-person visits for patients

Risks/Cons
*.limited technological access
*.limiations of remote area
*.security and privacy concerns
*.language barriers
*. In-person visit can be necessary (physical examinations,…)

Aware of telemedicine application (how to use…)
Telemedicine can lead to improved healthcare quality.

[Aye Thinzar Oo]

In week 3 Wrap-up discussion, let me share by text summary.
I have learned that implementing the Personal Data Protection Act (PDPA) within the healthcare sector is crucial. Because health information is highly sensitive and requires transparent handling, including providing individuals with access to personal data. Failure to comply with PDPA can result in significant penalties.

Furthermore, PDPA enhances data quality and integration. It safeguards personal data while allowing organizations to use data responsibly, such as restricting access to authorized healthcare professionals. International hospitals, in particular, should prioritize PDPA compliance.

[Aye Thinzar Oo]

Data Standards should be in every domain not only health sectors. If we have data standards in clinical research is improved and more benefits in data interoperability. And it can be easier to make communication within different systems using data standards like ICD, and SNOMED.

It can be shared and combined data from various studies. It also can reduce the risk of data misinterpretation and duplication of effort. Standardized clinical research data can increase the efficiency and accuracy of clinical trials.
Therefore, I believe that data standards can more facilitate and collaborate various domains.

[Aye Thinzar Oo]

I would like to improve Weight …… (kg/lbs)
By adding a unit It is easier for the data collector to understand.

[Aye Thinzar Oo]

I have experience in data collection at project sites, but not in a research setting. Volunteer staff and civil society organization(CSO) workers gathered data using paper-based documents. This information was then manually entered into an electronic database by the staff, organized by district/township. The project’s donor provided offline, Windows-based data entry software, which the staff used daily. They backed up the data and uploaded it to an online server. Project data officers then reviewed and analyzed the data from each district/township under user authentication. The use of offline software resulted in double data entry issues and data loss when the data entry laptop was broken or something was missing.
The data management system, relying on paper-based documents, presented security challenges. While a recovery process was available, involving online downloads and offline data entry, this approach lacked the necessary flexibility for the project’s workflow. Consequently, the data entry officer requested a transition to a web-based system for the next phase. Furthermore, the team’s reliance on Microsoft Excel for data rechecking, rather than specialized data analysis software, highlighted a deficiency in staff capacity building. This transition is to create a more flexible, secure, and efficient workflow.

[Aye Thinzar Oo]

Let me share what I learned in the code of ethics in health information week,

Link here: https://snipboard.io/6fYtkR.jpg

[Aye Thinzar Oo]

Based on your experience in data collection and management, I have been involved in data design (including variables and data fields), data collection processes, and data validation. I developed a health data entry platform and facilitated the transition from paper-based to electronic systems by training end-users.

I was also involved in database setup, programming edit checks, and managing access control. All data variables were based on donor reporting requirements, and I utilized an export function to extract data from the digitized system.

Additionally, if I have a chance, I would like to improve database lock and freeze functionalities in alignment with reporting timelines. Data standard/data coding management and Data Manipulation and Analysis steps also want to improve in the data management workflow more than other steps.

[Aye Thinzar Oo]

I have learnt data quality and the importance of taking precautions when applying AI tools in healthcare. It needs to use balancing AI and humans in healthcare. We need to think about the situation of using AI in health,
Link

[Aye Thinzar Oo]

Currently, my role involves collecting diverse healthcare data for research studies and summary reports to use related work requirements. While I’ve developed data collection tools for online and remote systems, this has primarily involved secondary data derived from hard copy records, encompassing both quantitative and qualitative information from facility and community settings.

My experience doesn’t extend to field-based data collection. However, after developing these tools, I trained end users, which revealed gaps in field-based data collection, such as language barriers, question interpretation, and communication between technical and research teams.

In conclusion, to address these gaps and gain practical experience for my study, I plan to conduct self-administered data collection and document my lessons learned.

[Aye Thinzar Oo]

I have learnt data quality and the importance of taking precautions when applying AI tools in healthcare. It needs to use balancing AI and humans in healthcare. We need to think about the situation of using AI in health,

Link: https://snipboard.io/v73Ihx.jpg

[Aye Thinzar Oo]

Hello Wannisa, thank you for your excellent suggestion. Adding disease severity as a variable is a good idea. It think, It will definitely provide a clearer and more robust picture of the vaccine’s effectiveness, moving beyond just case numbers. Thanks again for your valuable input!

[Aye Thinzar Oo]

Thank you for your feedback Arjan Pan. I will look into the relevant literature and try to frame it more specifically for my setting

[Aye Thinzar Oo]

Hello Tanaphum, thanks for your sharing. your plan sounds like interesting and well thought out. I like how you highlight the application of coding and computational methods rather than focusing on one disease—this makes your work widely applicable. It’s also great that you are already working on a malaria model.

[Aye Thinzar Oo]

Thanks for the great points! I agree that while descriptive epidemiology includes person, place, and time, earlier research mostly focused on individual factors and time trends. As you said, the lack of tools and data made it hard to study in detail. However, with advancements in technology and GIS, spatial epidemiology now plays a significantly larger role.

[Aye Thinzar Oo]

Hello Wannisa, Thank you for your suggestion. I need to improve the data visualization concept and the user interface, too.

[Aye Thinzar Oo]

Ohh, amazing, your dashboard is a very comprehensive and quite organized overview of recent earthquake responses.

[Aye Thinzar Oo]

Hello Well, your data visualization is very well organized. I got some information from your presentation.

[Aye Thinzar Oo]

Thank you for your sharing, yes, color using is easy to understand and that your thought red-green can improve, it will be more better.

[Aye Thinzar Oo]

Thank you for sharing Wannisa, your infographic is fascinating. I got from your Digital Storage and staff training that we need to focus on cyber security and awareness session.

[Aye Thinzar Oo]

Hi Aung, Thank you for sharing your experience with the data management process. It would be beneficial to develop a data recovery strategy, including regular backup integrity testing and outlining data restoration procedures. I think we need to consider proposing different backup locations for redundancy and business continuity. We would also consider documenting the existing procedures for clarity.

[Aye Thinzar Oo]

Thank you for your sharing and suggestions on data capture using electronic tools. While useful for basic data handling, spreadsheets could be carefully evaluated for long-term projects or those with stringent data requirements.

[Aye Thinzar Oo]

Thank you and I agree with your thoughts in working together with all health sectors and governments and non-government sectors using AI features.

[Aye Thinzar Oo]

Thank you Well, for your sharing infographic, I agree with you that support Role, AI can assist but doesn’t replace everywhere in healthcare sectors. And also Data Quality is very important in healthcare data.

[Author]

Posts