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Follow-up studies on mobility patterns
I would consider studying the association between cross-border mobility and hospitalization due to COVID-19. Based on their history of hospitalisation after the travel period, individuals who cross the border will be compared to those who do not travel. This analysis may provide insights into whether cross-border movement significantly impacts the severity of COVID-19. If a strong association is found, policymakers could consider imposing stricter travel restrictions. Additionally, prioritizing vaccination supplies for border villages might be an effective strategy to prevent transmission.
Government restrictions on mobility patterns
Changes in mobility patterns were observed across different intervals during the study. A very low median value of RoG (Radius of Gyration), indicating reduced movement, was found in Intervals 3 and 4. These intervals represent the periods when the government began tightening restrictions and eventually implemented widespread travel bans.
During these restricted periods, male participants travelled more than females, whereas the opposite trend was observed in Intervals 1, 2, and 5. Health personnel and government officials had seen the highest levels of mobility compared to the general population during the restriction periods to ensure the travel restriction.
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Barriers for mobile app users
One probable limitation for users in operating the mobile app was the requirement to download the app and register an account. Several challenges, including user acceptance and ease of use, were key barriers to mobile app adoption. As a result, we observed a much lower response rate from participants using the mobile app compared to the web-based tool. Additionally, digital literacy and comfort-to-use issues had a greater negative impact on the older population compared to individuals in their 30s.
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The major advantages of using vaccination apps were higher user acceptance and perception of using the apps. Many studies concluded that a significant percentage of participants highly accepted the application and found that it increased user perception of finding vaccine information and knowledge.
The other advantage of using apps was that they promoted vaccine coverage when it was compared to the time before using the apps. 4 studies clearly highlighted the fact that it significantly increased vaccination rates. On the other hand, the other 2 studies showed no significant benefit, and 3 studies mentioned no significant level of difference between the control group and vaccine group. Thus, those figures did not clearly distinguish between the benefits and drawbacks.
When it comes to users’ decision-making of using the apps, 7 out of 8 studies proved that a significant increase was seen in their beliefs and intention to accept vaccination. But 3 studies also warned that the apps may interfere with the users from the acceptance of vaccines.
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1) I created an avatar and uploaded a photo of the COVID-19 dashboard in a shared space. I believe that it is attractive and pleasing to the viewers than the traditional way of sharing a presentation and graph. I see several advantages and positives that virtual shared space could bring in the future. However, some features are necessary to improve, such as the ability to view a graph with better resolution. I think that I can’t visualise a graph clearly in the shared space. I also need to familiarise myself with the tool of virtual shared space, and I spend several hours uploading a graph.
2) It could be advantageous to both academics and professionals because we can interact with each other by sending a message or a direct call, no matter how far apart we live in different locations and time zones. It draws more attention from participants, so we use it as an alternative tool to attract the audience. It can be beneficial in some circumstances that a presenter wants to anonymise their identity for some reasons, and the audience also does not wish to reveal their true identity.
3) My avatar in the shared space!
https://snipboard.io/LOihe6.jpg
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My Personal Experience
I successfully set up the DIY VR headset by following the tutorial video by Ajarn Lokachet. It was a great experience, and the device itself was exciting to try. I installed some apps and watched VR videos using the headset. One of the things I enjoyed most was watching 3D videos on YouTube. I also explored some content using the ‘VR Video’ app downloaded from the Apple App Store, but I later discovered that it was a paid application. Additionally, I tried the Google Cardboard app; however, the magnet function on my VR headset didn’t work properly, so I couldn’t select buttons within the app.
I really enjoyed experiencing virtual reality, especially when exploring the Dinosaur Park, horror movies, nature walks, and space explorations. However, I found the magnet function to be a major limitation and it didn’t work well with any of the apps I tried. Another issue was comfort: wearing the headset for more than five minutes caused discomfort around the pressure points on my face. I also felt a bit dizzy when watching horror or action movies in VR, especially during fast-paced scenes.Linked with the Lecture
Using the VR headset, I was able to observe stereoscopic vision as I noticed the depth between objects in the virtual environment. I also experienced a sense of realism, one of the psychological factors mentioned in the lecture. Some of the VR movies I tried were navigated by head movements, which enhanced the immersive experience. I could clearly perceive the depth of objects in the videos, and the audio quality was also impressive when using with earbuds. Some apps, such as the VR Videos app, used head-tilt navigation, allowing me to move through the content more lively. In certain environments, like space exploration or nature walk, the experience felt incredibly pleasing, and it did not make me feel dizzy.
I believe VR technology offers many valuable benefits. Without a doubt, we will continue to see significant developments in VR applications—for example, allowing families and friends to explore virtual environments together, helping patients understand their medical conditions through visual simulations, or enabling users to experience historic sites in other countries from their own homes. -
1. Visualization and Experimentation
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The above diagram shows the temperature and humidity changes I recorded inside my house. I tested the system under normal room conditions and the air conditioning. Before operating the AC, the temperature was 32 °C with a relative humidity of 72%. After turning on the AC, I continued recording to compare the two conditions. The temperature dropped rapidly to 27.3 °C within 15–20 minutes. I also observed several spikes in the middle of the humidity line graph, which I believe occurred when I was near the sensor. This may have caused the humidity levels to rise and fluctuate slightly, probably due to exhalation and perspiration.2. Challenges and solutions
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I properly set up the DHT22 sensor and microcontroller using jumper wires, then connected them to my laptop via a USB connector. The setup went smoothly as per Ajarn’s instructions, and I didn’t encounter any major technical difficulties. At first, I expected to re-run the code in the Arduino IDE every time I powered on the system. However, I discovered that once the code was deployed using the App Script extension, it automatically began recording data to the Google Sheet as soon as the sensor was connected to my computer.
When I import the value “50000” in place of the delay() function in the script, the interval between each measurement is prolonged to nearly 60 seconds, so it is recorded around only once per every minute.3. Ideas for improvement and application
To improve the system, I would suggest implementing notification features such as email alerts or other forms of warnings when the temperature or humidity exceeds desired levels. This system could be particularly useful in places like pharmacies or food storage warehouses, where maintaining standard temperature and humidity is critical. As mentioned earlier, if the system alerts users when these levels are higher than standard thresholds, designated personnel can intervene promptly to bring them back under control.
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I selected an article that describes the application of IoT in monitoring glucose levels in diabetic patients. The title is “An IoT-based non-invasive glucose level monitoring system using Raspberry Pi,” and it was organised by Antonoi Alarcon-Prededs et al. for the research article. The link to the article can be found below.
https://www.mdpi.com/2076-3417/9/15/3046
It is an intriguing topic discussed on monitoring glucose with a non-invasive method. The research’s primary objective is to avoid frequently pricking the finger, which causes pain and discomfort. The estimated results would be monitored not only by users but also by health workers. Raspberry Pi Zero (RPi) attached to a visible laser beam and a Raspberry Pi Camera are the main components in developing the system that was designed to fit in a special glove. Rpi captures the pictures of a patient’s fingertip and sends the signals through the internet. The artificial neural network (ANN) was applied to process the output data. Finally, the data was validated with laboratory blood tests in terms of mean absolute error (10.37%) and Clarke grid error (90.32%). The validated results were promising, with a Clarke error grid zone percentage of A = 90.32% and B = 9.68%, which is competitive with those found in previous studies. Estimated blood glucose records can also be collected by an electronic device such as a smartphone.
Challenges: The main challenge mentioned in the article was that the device system was quite large, which might be inconvenient to be applied by users daily. However, the device can be minimised by improving printed circuit boards and using smaller batteries. Variations in skin colour of participants were not examined in this research. The other challenge in developing this device could include that optical receiving sensor relied on reflection, refraction, dispersion and absorption of the light beam, which could be different between indivdiuals and even from time to time in a same person particularly affected by extreme temperature, sweating, impaired blood circulation due to age/disease.
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Having data standards for clinical research is advantageous in the health sector because researcher or institutions can study the dataset and results of their counterparts’s research projects. Those were maintained in a standard set of formats and codes so that every researcher is able to follow the study to understand the findings and compare them with other results.
One major benefit of data standards that I’d like to highlight is the data interoperability of clinical databases. When the clinical data are kept in a similar system, patient information can be integrated seamlessly from different areas, allowing researchers more time to focus on data management, analyze the results and compare the findings with other research. It somehow promotes data transparency and integrity, contributing to data reusability and reproducibility for other investigators in the future.
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I only got involved in some small research which former non-government organizations organized. Almost all the research was correlated with public health activities such as identifying health-seeking behaviour and practice, disease prevention and access to health care, hygiene promotion, environmental health etc. As I mentioned in the previous discussion, those research were carried out primarily with the existing workforce and resources in the organizations. Thus, some vital steps in data management were not executed in a proper plan.
Generally, data were collected by paper documents through volunteers or community health workers. Those records were imported into an electronic database by data officers. It is widely accepted that maintaining user authentication and access control was crucial in many organisations. Still, some did not impose strictly the regulations and employers involved in the electronic data importing process to accomplish the survey in the predefined timeline. Edit checks and logical errors were validated mainly by the assigned employers but automatic consistency checks and finding invalid errors were neglected, partly due to inadequate technical support. Data were backed up only in the server in the corresponding office although it should be kept on the cloud or distant office for safety and security. Those were the challenges that I encountered in the non-government sector.
Managing the research data in the organisations was implemented through EpiData and R software. Epidata was applied converting paper-based records to digital formats which was later evaluated by statistical analysis tool, R software.
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When I learned in the lectures on the data management process of clinical trials, it was quite systematic in handling and managing research data with proper workflow and availability of designated staff. In comparison to the community survey that I conducted before, it did not meet some of the standards and practices which are required to achieve reliable and high-quality data.
Some important steps comprised in our data management process were protocol discussion, data design, data acquisition, CRT development, data management plan, access control, database setup, pilot testing, quality control and quality assurance, survey report and document archiving. Some of the steps have been ignored or left out in the data management process because of the limited timeframe of the program and the scarcity of resources within the organisation.
If I have a chance to restructure the data management workflow in our community survey, I will consider a few major critical measures to be included in managing data. Database security: Although we kept our collected surveys in secured rooms, those documents were exposed to many employees in the organization. A limited workforce force created several staff involved in the electronic data importing from paper-based documents. In addition, those confidential data were not stored as a backup appropriately and timely in separate locations or on the cloud as a disaster mitigation plan.
Edit check programming was not carried out sufficiently after designing the database with the data manager and technical staff. The electronic data should be validated automatically for logical errors, completeness of data and improper recording. Last but not least measures to improve my research were proper data archiving and data sharing. Due to our workload in the regular program activities, we did not pay much attention to data achieving process. We should have kept all necessary components of the survey at a single spot after the survey. Eventually, it is ethical and appropriate conduct to share our findings and results on the appropriate channels to strengthen credibility and enhance transparency.
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When I worked in the former organization, we conducted community survey data for determining knowledge, attitude and practice of local population behaviour regarding non-communicable diseases, reproductive and child health and WASH. The data were collected by survey questionnaires through volunteers, supervised by our organizational staff.
Household survey was conducted as in person interviews with participants through volunteer interviewers. Stratified random sampling method was applied based on community population data. The quantitative study method was utilized and the questionnaires were developed as close ended questions, recorded by paper based survey forms.
Although data were gathered through independent interviewers, those activities are supervised by the staff of the organization to help identifying the location of participants and monitor the performance. Thus, there was an concern of interviewer bias due to the presence of program staff while interviewing the participants. Communication gaps were encountered in the data collection process because some members of the community communicate in different ethnic languages. To minimize this gap, despite recruiting interviewers of different ethnic origin, recording the data in paper documents was another challenging task since the survey forms were designed only in two main languages.
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My apologies for the belated attempt in this week’s discussion.
1. Why was the author interested in investigating the suicide problem in Thailand during the time?
The researcher would like to identify the significant factors influencing the suicide rates in Thailand. It was based on the fact that the number of suicide cases had been rising, with the figure ranging between 3,600 and 4,000 cases annually from 2005 to 2014. The average suicide rate was higher than 6 cases per 100,000 population, particularly after 2011. A considerable number of studies had been conducted in developed countries to address the increasing trend of suicide. Thus, to explore the factors influencing the suicide rate in the Thailand context, the research was conducted as a cross-sectional study on how cultural, social and economic impacts have an influence over the population in different areas of the country.
2. Each of the students picks one potential risk factor mentioned in the paper and explains how the variable can contribute to the suicide rate.
I would rather choose alcohol as one of the highly significant factors that contribute to the increasing suicide rate. In the study, suicide rates were significantly related to alcohol consumption in Thailand.
It was also highlighted that alcohol consumption in both groups aged 20 and above and aged 15-19 were compared in two models to find out how alcohol abuse in both groups affected suicide.Alcohol intake in teenagers and grown-up populations was lower in the high economic status group, and it is believed that those groups belonged to higher education levels and seemed to follow the regulations on alcohol. In the given two models, suicide cases were significantly related to alcohol drinking in adults over 20 years old group and adolescent groups between 15 and 19 years old, respectively. Model-1 has shown that one unit of increasing adult population alcohol intake could result in higher suicide rates by 0.086, while one unit of the rising population aged 15-19 drinking explained 0.01 unit of increasing suicide rate in model-2. R2 values were 0.6 in model-1 and 0.59 in model-2, representing that around 60% of the total variations in suicide rates were explained by independent variables in the models. There was not much difference in the values of the two models.
The relation between the growing number of suicides and alcohol was probably due to a loss of self-control under the alcohol, which provoked uncontrolled and aggressive behaviour, and those could be rooted in chronic depression that the person might not disclose to others.
3. How statistical modeling can contribute to investigate the epidemiology and spatial aspects of Thai suicide problem?
Multiple linear regression statistic test was applied for both models in the paper to investigate the underlying risks of suicide. Provincial data were collated from different sectors to explore social and economic factors over dependent variables. Regression models scientifically demonstrated how social factors such as occupation, alcohol consumption, female as a head of household, divorce rate, and economic factors including income, debt and unemployment, were significantly related to the suicide rate in specific parts of the country and type of relation between. The prediction model estimated the suicide rate depending on changes in risk factors and it can alarm the public health authorities to address health issues timely. Appropriate intervention programs and regulation on negative factors can be established after prioritizing the significant factors from the model.
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• What are possible reasons locations in epidemiological research have not been incorporated as much as other components in epidemiological research? How can spatial epidemiology be considered as an interdisciplinary science?
Locations and area studies are not considered at the same level as other determinants in epidemiology. There were several constraints in the past, such as the availability of high-quality data and confidentiality issues explained in the paper. We have still found a lack of proper records regarding specific disease mortality data in some developing countries, which hinders the summarization of environmental health problems. Poor data quality has been experienced in disease diagnosis and registration, including the patient’s location, even in developed countries. Thus, exposure and duration to certain health events in a specific location are quite challenging to be inferred to relate to the occurrence of the disease. Similarly, before the HIPAA Act in 1996, secondary use of epidemiology data was limited for the purpose of healthcare analysis because several data were gathered for different reasons, leading to the restriction in the usage of spatial data.
Spatial epidemiology can be regarded as an interdisciplinary science, particularly in healthcare, because concepts and knowledge from several disciplines are applied in spatial epidemiology to allow us to understand the correlation between exposure in a certain area and disease outcome. Disease distribution, mapping, intervention and response, population migration, social status, etc, are integrated into this study to deal with health challenges and overcome health problems.• Explain why it is widely recognized that the place where an individual lives or works should be considered as a potential disease determinant and give some examples.
Estimating the degree of exposure to specific risks in an area is an essential element in predicting certain health outcomes. When someone lives close to a polluted river or ocean, his/her health might be severely affected by the source of waste or toxins. Depending on the pollution level, people close to the polluted water will likely suffer from respiratory diseases, skin infections and waterborne diseases. Contaminated water sources bring neighbouring pollution, not only acute infectious diseases but also causative agents/risks for chronic diseases. -
1. How can the decision tree model be integrated into clinical practice to assist surgeons in preoperative planning and decision-making?
We can apply the model in a clinical decision-support system to assist surgeons in planning and decision-making. After collection appropriate patient informations, the potential risks and complications will be estimated and rendered by the model. Thus, those alerts will warn surgeons so that they are informed with the proper information and are more likely to have chances to prepare and manage the possible complications for better outcomes.2. What are the potential benefits and limitations of using this model in a real-world clinical setting?
There are several benefits of using the decision tree model in real-world practice to assist surgeons. Patient outcomes would be estimated more accurately, and surgeons might have opportunities to prepare appropriate measures when a poor outcome is predicted. An individual surgical plan could be planned and performed to respond to the model estimation result. There will be minimal unexpected complications during or after operations as healthcare providers might have anticipated possible case scenarios and potential risks.
The limitations of the model are the requirement for vast amounts of patient data to predict patient outcomes more accurately. There might be a rejection of the reliability of the model by the healthcare providers or due to the overburden of the recording of additional patient information. Patient data privacy is another consideration to imply the model in a real world practice. -
1. What additional factors should be considered to identify barriers and unmet needs in health information seeking among youth for HIV/STI and RH than in the paper?
I will consider effective communication channels to reach the target group, such as social media and technology platforms, to identify the gaps in delivering health information to youth. Most of the group is familiar with digital devices and social websites. Delivering information from those platforms will have a significant impact on young adulthood. A reliable Facebook page or website/peer group platform to disseminate healthcare information and gather information on barriers and gaps in healthcare access could be an appropriate solution among young adults and KAPs.2. Which types of vulnerable people in your community are missing or left behind in receiving necessary health information, and why? How can we best reach these individuals and measure the real impact of health information on their health-seeking behaviors to ensure its effectiveness?
People living in remote areas of my country are another vulnerable and marginalized group in Myanmar because many of them have limitations in accessing healthcare services and health information. Again, I also believe technology is one way to receive appropriate health information with less resource use than any other means. It could be possible to monitor the number of people from those areas who use social media and request feedback or perform surveys online relating to their healthcare knowledge and behaviours. -
Please find my Covid-19 dashboard for the final assignment in the below link. There were three menu tabs on the main dashboard representing the three pages. On the first page, the general trend of confirmed cases, recovered cases and mortality cases were described. Different charts such as bar chart, bubble chart, area chart, etc. were applied along with vector icons to enhance visualization and to promote user’s interface. Each country’s respective figures can be chosen for the detail information on the second page. Final page showed the cumulative data of specific period.
https://lookerstudio.google.com/reporting/555b30bc-fe76-461b-8004-479e6ad35aa4
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I explored a WHO SEAR COVID-19 data visualisation dashboard representing 11 countries (India, Indonesia, Thailand, Bangladesh, Nepal, Sri Lanka, Myanmar, Maldives, Bhutan, Timor Leste, and the Democratic People’s Republic of Korea). The dashboard can be found in the link below.
https://experience.arcgis.com/experience/56d2642cb379485ebf78371e744b8c6a
The dashboard displays a wide range of data on a single area, which includes caseloads, deaths, new cases, epi curve, recent trends, vaccination and public health & social measures (PHSM) index in each country. Except for DPRK, each country’s data is updated regularly, either daily or weekly, depending on the data accessibility. Total cases and deaths were described in numbers and illustrated with trend charts for cumulative data on the right side of the dashboard. The most interesting figure on the dashboard was an epi curve in the middle comparing the new cases of each country from the beginning of the Covid era until the present. Each colour in an epi curve represents a single country, and it is customisable to include or exclude the countries in a chart to compare caseloads. The period on the graph is also adjustable to examine the number of cases in a specific timeframe.
The incidence and mortality rates of each country can be found in another tab of the dashboard. The PHSM index was compared with daily cases in the PHSM tab of the dashboard so that we could learn what measures had been implemented to tackle the disease outbreak in the community. Vaccination information in each country was clearly mentioned in a separate tab and can be compared with current population data.The dashboard’s limitation is that it uses different colours to indicate the new cases in each country. This could be quite confusing for first-time users, especially the general public, when it is first introduced. However, I believe using separate colours is meaningful in this dashboard because if the monochromatic colour is applied in the histogram, it can lead the audience to disorganised figures as the chart has to present ten different nations. The second point I mention is that it is appropriate to include the option to choose a certain timeframe from the calendar or by typing instead of the slider bar to be more precise.
Overall, the dashboard is simple and comprehensive for users and provides detailed information about COVID-19 in one area. The dashboard used appropriate graphs and tables with proper colours to deliver the information with better visualisation.
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This is my assignment infographic, which reflects on the personal health information that I learned in the course.
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The image below is what I learned in the AI and ethics course this week.
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I elaborated on the statement, “One should always use two-sided P values”, which is presented in No. 14 on page 342.
Whereas two-sided P values are commonly used in practice, the advantage of using one-sided P values is that there are fewer subjects and resources to underpin significance. Two-tailed P values divide the significance level and it contributes to both sides. Thus, each side of a two-tailed is only half as strong as those of a one-tailed test, which supports all the significance in one aspect. Although one-tailed tests enable more Type I errors, there are many situations in which a one-tailed test could validate the data while a researcher is fully aware of the drawbacks. When there is a very strong reason to validate that one variable is superior to the other, a one-sided test would be applied.
However, a one-sided test will not measure the hypothesis in the opposite direction, so variation can’t be concluded in that direction. In general, two-tailed P values verify the evidence that the control and variation are not the same, while one-sided P values prove that a variation is stronger than the control.
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I’m Phyo, and my most recent position was as a clinical manager in the non-governmental sector. In this role, I verified weekly and monthly clinic data, analyzed health status trends, and identified challenges within the project area. The health databases in my previous organization utilized Microsoft Access. The data could be extracted into either auto-generated or customizable Excel template reports. Thus, I have some knowledge in the area related to data analysis. Although I have taken a few courses about probability and statistics in the past, I did not have a chance to complete the entire course.
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Efficacy is the capacity of a given intervention to achieve the desired result under ideal or controlled conditions. A medication, for example, would improve a patient’s condition in an ideal environment where they are closely monitored and supervised for the expected outcome.
Effectiveness is the ability of an intervention to have a meaningful effect on patients in routine clinical conditions. Despite the treatment demonstrating efficacy with a noticeable improvement in an ideal situation, its intervention performance has to be tested under real-world conditions. Effectiveness trials show how well a treatment works in real situations.
Efficiency is doing things in the most economical way in terms of time, energy, and money. Once an effective intervention is found, it has to be improved by making it more efficient, or two identical effective interventions will be tested to find the most efficient one. In other words, efficiency is comparing an input to its output.
To sum up, when outcome measures are considered in a specific order, the particular intervention will be ensured first to achieve the desired effect/solution, even if its efficacy requires an ideal environment. Secondly, the intervention will be tested in real-life situations. Lastly, if it is effective, a more economical and efficient solution will eventually be developed.
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To analyze the respondents’ denying using bednets, I would consider a qualitative study, which can find out the concerns and negative behaviours behind the denial and why they are not using it in practice. A researcher can apply in-depth interviews and focus group discussions to identify the reasons and concerns in the study group. Learning about the respondents by observation is one approach to understanding attitudes and practices towards bednets. There will be the chance to learn from real-life situations to discover misinformation and barriers to using bednets.
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Various external variables influence a new technology’s perceived ease of use and usefulness. I think past experience, workplace relevance, and social influence could be significant distribution factors for a person’s attitude and behaviour.
Individuals with past experience in IT and digital proficiency will not limit their ability to apply new technology even when they experience complex features and additional functions in the early phase of launching a new tool. Moreover, if someone thoroughly understands new technology promoting performance on the job, it somehow impacts positively the perception of usefulness. Lastly, recommendations and encouragement from colleagues and close friends can boost the person’s interest and attention to using innovations due to social influence.
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TAM highlights that a new technology should be as useful as the replacing one to promote users’ acceptance and adoption. If the new technology brings functional improvements, enhanced design and competence with current tools, users will likely accept it as it improves their performance at work. If the new tech is easier to use, there can be a positive influence on user attitude and alleviate unnecessary concerns related to issues. Despite the ease of use contributing to users’ acceptance, usefulness should be deemed the most critical factor for users’ acceptability.
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I think the following non-identifiable data would narrow down the possibilities among others in a database. Those information are:
Sex – Male
Marital status – married
Year born – 1985
Education – MD
Current occupation – BHI student
Employment history – INGO staff
Place of residence – Thailand
Place of citizenship – Myanmar -
Infant mortality rate
Infant mortality rate is the rate of deaths among infants under one year old population.
Infant Mortality Rate = Number of deaths among under ones / Total number of live births * 1000
Infant mortality rate represents a child’s viability, which describes healthcare support, socioeconomic status and environmental situation in the child’s area.Neonatal mortality rate
Neonatal mortality rate is the rate of deaths among newborns within the first 28 days of life.
Neonatal Mortality Rate = Total number of deaths of newborns less than 28 days of life / total number of live births * 1000
Neonatal mortality rate is useful for monitoring maternal and newborn neonatal healthcare status and informing health authorities about intervention plans for desired health outcomes. -
From my perspective, young adults tend to live in an urban area than other age groups because of study or work. It contributes to the usage of contact tracing apps through public awareness. Secondly, it probably finding more contacts in young adults in urbanized areas for contracting infection due to population density. “Urbanization” is associated with the exposure we have studied, and it is not an intermediate step in the causal path between exposure and outcome. It is also a risk of having more contacts in the study. Thus, I think Urbanization is one of the confounders, which is a causal relationship with contact patterns.
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I remember the time when I worked in a refugee setting during the Covid pandemic. The most significant ethical principals was the decision-making concerning isolation and quarantine measures for infected cases and their contacts. As you may be aware, refugee environments are often densely populated, with shelters situated closely together, posing a high risk of rapid infection spread within a camp setting. In such circumstances, implementing isolation and quarantine measures was essential to curb the outbreak. However, a major concern developed when considering the impact on families, as restricting their movement during isolation or quarantine meant there would be no one available to assist care for basic needs, such as food and income. Thus, we collaborated with other partner agencies and local community leaders to support fresh food and ration supply during the isolation/quarantine period.
Local public health authorities strongly advocated for our organization to enforce isolation and quarantine for positive cases in the camps as a preventive measure against the spread of COVID-19. Meanwhile, we attempted to build trust and confidence within the community, actively engaging them in collaboration with our organization for isolation/quarantine activities. This involved effectively communicating the risks and providing crucial information transparently, with integrity and in a timely manner. Transparent, integral, and timely communication proved to be crucial in fostering community engagement and disseminating information regarding isolation and quarantine. The majority of individuals were more likely to accept and adhere to such decisions when the benefits of isolation/quarantine outweighed the drawbacks.
Secondly, the ethical principle is about when the Covid-19 vaccine started to roll out in the camp setting. As justice is one of the ethical principals in population health maximization, there must be fairness in the distribution of healthcare resources to mitigate disparities. Our responsibility was also to guarantee that every individual received the appropriate type and dosage of the vaccine without discrimination based on personal characteristics. We consistently conducted health education programs, disseminating information about vaccine benefits and potential side effects. This approach aimed to empower individuals to make informed decisions and willingly participate in vaccination campaigns. In such a way, we achieved a certain number of targets in the Covid vaccination program.
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Myanmar underwent political reform in 2016 and is committed to reach Universal Health Coverage (UHC) by 2030. The Ministry of Health and Sports (MOHS) has developed a National Health Plan (2017-2021) to strengthen the health system and support the implementation of UHC.
To ensure a comprehensive approach, MOHS brought inputs from both government and non-government stakeholders. Prior to the military coup in 2021, there were consistent positive efforts and improvements in promoting the health status of the population, including significant achievements in combating communicable diseases such as malaria, tuberculosis, and HIV/AIDS through increased budget investment in public health.Despite these efforts, Myanmar’s health system still faces several challenges, as the country is classified as a low- and middle-income country in the region. Life expectancy is the lowest among ASEAN countries, and there are significant geographic, ethnic, and socioeconomic inequalities that lead to disparities in accessing health services and financial risk protection. The Myanmar health budget contributes a very low percentage of the total budget, which results in households having to pay out-of-pocket for healthcare services. This drives the population into poverty and makes it difficult for people to obtain necessary healthcare services.
Additionally, the health system struggles with challenges in the availability and distribution of health assets, as well as failures in maintaining certain important functions. Limited oversight and leadership, as well as accountability, also pose challenges. Human resources are another critical issue in the health system, with shortages of trained personnel, inequitable distribution of healthcare workers, and difficulties in workforce distribution in rural areas. The lack of clear recruitment and deployment policies, along with unclarified roles and responsibilities of trained healthcare workers at all levels of the system, has led to extra workload and burnout.
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We have a shortage of qualified health informatics professionals in our country. There needs to be proper academic programs or universities offering health informatics graduate education to healthcare professionals. A strong partnership between the Myanmar health ministry and international academic programs is needed to provide online education to the existing government-sector workforce, particularly in remote areas. While some non-governmental organizations have attempted to develop health information systems to record patient information and share it among clinics, poor internet connectivity and error-prone processes make it challenging to maintain sustainability, negatively impacting the workforce. Lastly, the high initial cost of implementing eHealth or Electronic Medical Records (EMR) systems is a significant challenge for small organizations, who must balance their budgets to hire qualified health informatics professionals and invest in IT resources.
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If I were in charge of a dataset in my country, I would definitely consider sharing it with appropriate researchers and institutions. Nowadays, the healthcare industry generates a substantial amount of patient data and information as electronic health records (EHRs), which can be utilized not only for healthcare supervision but also for medical research. These pools of data and information can provide evidence-based clinical decisions, transformative clinical research, clinical guidelines and treatments, and several benefits to the public and stakeholders. However, we must find a balance so as not to compromise the privacy and confidentiality of patients in scientific research. Laws and regulations must be enacted to safeguard patient information regarding to sharing information in research.
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Electronic medical records can offer several benefits over traditional paper-based medical records, but they also have some drawbacks. The following are the key advantages and disadvantages of using EMR in our clinical setting.
Benefits: It allows users to access patient information in real time so that the efficiency of healthcare providers is improved significantly by receiving and updating patient information with less downtime. By using EMR, hard files of patient registrations and records can be replaced as those used to take up huge physical space and have to be protected to safeguard privacy. It minimises handwriting errors and missing data records by alerting users of incomplete data.
Drawbacks: Initiating an EMR system at the beginning can be costly in terms of investment in software, hardware, training, and maintenance expenses. Staff are required to undergo comprehensive training before initiating the project which would hinder the existing workflow and cause extra workload. After a few months, well-trained staff could be a shortage in the organisation due to the high staff turnover rate. The last one concerns the confidentiality issue that was raised by the patients when the electronic system recorded their health information. Some patients are concerned that their identifications and health information can be breached and shared with other organisations without proper notice.
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After learning about the research, we have seen several opportunities in big health data. On the other hand, it has brought quite challenging issues that still need to be tackled to improve patient outcomes. Some top challenging issues describing the paper are missing data, selection bias, data analysis and training, and privacy issues.
Missing data: Those seriously impact analysis and give invalid results depending on the number of missing data. Several factors have contributed to generating missingness in the databases. Imputation techniques are one of the models that can correct missing data recommended in the paper. Another suggestion is to provide regular refresher training to staff for data validation so that a certain number of missing data can be reduced at each level.
Selection Bias: The risk of selection bias due to the inclusion of subjects from different geographic, insurance and medical history profiles were compared in this large-scale EHR analysis. Recording sampling methods and being transparent in reporting for selection bias in the analysis is recommended.
Data analysis and Training: EHR usually entails a large dataset to analyse multiple times to hypothesise an event’s significance eventually. It applies algorithms several times to handle the complexity. The government has to invest more in the sector to develop skilled staff in order to support the industry and provide regular training and workshops to widen the knowledge and skills of the staff in the statistical area.
Privacy and ethical issue: People who share their health data have the right to protect their privacy. Cybercrimes target private information to hack for several reasons and advantages. Setting up a robust security system is one of the solutions to defend hackers from unauthorised access to big health data. Sensitive information should be encrypted before it is shared with designated research.
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I believe that all four recommended points are highly acceptable to tackle corruption in the health sector. The initial step involves mobilizing key actors within the health system to identify the extent and character of corruption which is followed by protecting groups who are about to uncover corruption. Secondly, it highlights sorting the main actions to tackle corruption after summarizing the problems in the first step. A pragmatic problem-solving approach can be initiated by learning the driving factors in current practices. Thirdly, comprehensive involvement from various sectors is essential to handle corruption effectively. Lastly, it emphasizes the critical importance of further research on corruption in the health sector as essential work to prevent serious impacts and consequences for patients.
I have learned some anti-corruption approaches to transparency interventions in development projects using scorecards from community-led accountability programs established in Tanzania and Indonesia. The programs enabled communities to tackle some specific challenges and take appropriate actions to take accountability. (1) Another promising anti-corruption tool is regular audits to detect irregular practices in the health sector. It has been proved that there is a connection between corruption and the function of internal audit in Ghana after strengthening the internal audit agency. The extent and independence of the role of the internal audit team were directly related to the effectiveness of corruption reduction. It can be concluded that full implementation and assurance of the independence of the internal audit capacity can assist in combating administrative corruption. (2)Reference
1. Ash Center for Democratic Governance and Innovation. Citizen voices, community solutions: designing better transparency and accountability approaches to improve health. Cambridge (MA): Harvard Kennedy School; 2017.
2. Asiedu KF, Deffor EW. Fighting corruption by means of effective internal audit function: evidence from the Ghanaian public sector. Int J Auditing. 2017;21:82–99. -
Throughout my professional career, I have seen some initiatives for health system improvement in the southeastern region of Myanmar, through local community empowerment by non-government organizations. One of the well-known projects in the area is the ACE project (Advancing Community Empowerment project) funded by USAID. The primary goal of the project is to reduce community vulnerabilities not only in the health sector but also in the sectors of WASH, DRM, and livelihoods. The outcomes are to increase participation and leadership in the planning and delivery of services and other initiatives such as improving skills, knowledge, and strengthening engagement between service providers and communities. ACE’s health development model gave communities leadership roles in planning and delivering health services. It encourages community members to identify and address their health development needs, establish Village Health Committees (VHCs), and train community health volunteers.
However, following the Myanmar military coup in Feb 2021, several projects are required to rapidly adapt to emergency response measures while addressing the increasing basic needs, particularly in the health sector in the southeast region of Myanmar. Project adaptation in the context is needed with a high degree of flexibility in operational processes and procedures to reduce administrative constraints and more responsive mechanisms. Safety and security become significant concerns for staff in the area and alternative measures for monitoring are necessary to be considered. Due to feasibility issues for field-level staff, training from remote or virtual platforms is being used increasingly for training instead of in-person sessions. Banking and fund transfer challenges are recurrent and unpredictable in the region.
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I am currently learning an R-introductory course in the BHI program. I take it as a personal project in this scenario and 12-step project management benefits me in several ways in learning the course.
Define the project: I commit myself to learning additional R-course to have an in-depth understanding of the R-programming within a 3-month period.
Detail tasks: I blocked my time 4-5 hours a day on Sat and Sun every weekend in order to accomplish the course. If I am occupied with my other priorities on weekends, I will find my time on weekdays to catch up on the course.
Plan the running order and consider contingency: I arrange the order of the content and priorities in the course which needed to be completed in the provided timeframe. Add extra time to revision or spare time for myself in some months for contingency.
Gantt Chatt: A Gantt chart is developed for each topic I have to tackle each week/month and I will follow the plan as per the schedule.
Monitor progress & readjust the plan: I regularly review my progress in the Gantt chart and make adjustments if required to make sure I will complete the course in my committed timeframe.
Review the project: After completing the project, I will review the whole project to learn the strengths and the areas I need to develop so that I apply these experiences in my future personal development.
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I want to improve my evaluative listening skills, as emphasized in the Effective Listening Course on LinkedIn Learning. I find this challenging because effective listening involves simultaneously attentive listening and evaluating the content of the argument. As we progress in our careers, the ability to assess presentations from supervisees, vendors, and others becomes vital. To improve this skill, I plan to implement strategies such as minimizing distractions, refining mental filters, adopting effective note-taking methods, actively listening to the speaker, concentrating on content, and seeking clarification from presenters during discussions.
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As a team supervisor, I actively listen to the feedback and suggestions team members provide. Suppose I find that a suggestion would be appropriate in particular circumstances. In that case, I am willing to replace the planned schedule/activities with the suggested ones to support the active participation of team members. I believe that incorporating their suggestions fosters excitement and motivation within the team, as the ideas originate from the team members rather than senior-level staff. The team members also have a sense of ownership and accountability to contribute to the outcome and achievement.
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I agree with you that using virtual space is an effective way to draw attention as an alternative method. It also eliminates the need for physical attendance at a specific location or a fixed time commitment to participate in the event. However, there is still significant potential to expand VR spaces, particularly in enabling the sharing and visualization of 3D objects for users.
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I have a very similar perspective as well as experience in creating an avatar and uploading a graph in a shared space. But it is worth spending several hours to see the outcomes and to explore an alternate tool to present visualisation. I learned from you about several benefits of utilising a virtual environment in academics, such as collaborative learning and research presentations.
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Ko Aung Thura Htoo, thank you for your comment and for raising this concern. I would like to further clarify the Mean Absolute Error (MAE) mentioned in the article. The reported MAE of 10.37% corresponds to an average deviation of approximately ±10.37 mg/dL from the actual lab result. For example, if a diabetic patient has a blood glucose level of 110 mg/dL, the IoT system might predict a value between 100 and 120 mg/dL. While this prediction is not perfectly accurate, it falls within a reasonable and acceptable range for a non-invasive IoT-based system. I apologize for referring to it as 10.37% earlier, which may have caused confusion or misled readers.
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The system is simple yet effective and affordable, making it suitable for installation at home or in the office. If the RF transmitter is replaced with a more appropriate alternative, the device could become a reliable and cost-effective solution for home use. I think electricity is unlikely to be a major issue if the system or Wi-Fi are powered by a battery. The only essential requirement is a stable internet connection to notify homeowners in real time in the event of a break-in.
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I believe the device could help minimize the need for workforce and ensure seamless data sharing, particularly during outbreak periods. Applying the system in remote areas, where experts are not readily available, could significantly reduce human error. If it is designed to detect not only dengue but also other diseases, it would become a highly useful and reliable tool for disease detection in low-resource settings.
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We experienced common challenges such as data validation, documentation of analysis plan, etc for data management workflow although we applied different research methods. However, it is truly inspiring the way you appropriately handled the data management process from the beginning till the end. I understand that some of the important elements could be missing or incomplete due to our nature of work and the short survey timeframe in the non-government sector.
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Your final assignment project/dashboard is quite informative and valuable for users. What I like about your dashboard is that it comprises several visualization charts, such as scorecards, bubble charts, bar charts, line charts, etc., to display the respective figures regarding COVID-19 information. Appropriate use of a control button to select a specific time, continent, and country is also convenient for users, as it allows them to extract the desired information with just a touch of a button. Personally, I think it would seem best if you use the icons instead of photos to represent the scorecard data of confirmed, recovered and deaths. I feel that it is a distraction for users to use two/three photos, although those are miniature ones.
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