Aung Thura Htoo

I think for me, by combining following variables would be able to recognize me.
Sex: male
Appearance: long hair
Study Major: Biomedical and Health Informatics
Study place: Faculty of Tropical Medicine, Mahidol University
Place of residence: Myanmar (Burma)

To understand why they are not using bed nets in more detail, I will do a follow-up qualitative study on ‘barriers against bed nets’. Qualitative method is a good fit for this type of study, that tries to uncover on the social, behavioral, and physical factors influencing on the barriers against using bed nets. In the study, key informant…[Read more]

External variables that might influence an individuals’ perceived ease of use or perceived usefulness of a new technology are:

1. Digital Literacy – (people with higher digital literacy might be more confident in perceived ease of use)

2. Peer Use or Pressure (Co-worker effect – social norm) – (people who see their co-workers using the system…[Read more]

Hello Cing, thank you for your presentation and the demo of what blockchain is.

Q1: As discussed in the seminar, I found it hard to comply with the right to be forgotten when using blockchain technology. However, I believe that being able to strictly control whom to give access to would be a great step towards the regulation.

Q2: I believe that…[Read more]

Efficacy, effectiveness, and efficiency are important outcomes in m experimental studies.

Efficacy: It answers how much that intervention produces an effect under controlled environments and circumstances. E.g. Testing a vaccine in a laboratory conditions (90% efficacy)

Effectiveness: It answers how much that intervention produces an effect in…[Read more]

Hello, I think digital literacy (adoption of the apps) could be a potential confounder in this case. It satisfies all three criteria of a confounder. Firstly, it is associated with the exposure (age): younger adults are more likely to have higher digital literacy compared to older adults. Secondly, it is associated with the outcome (active contact…[Read more]

1. Case-Fatality Rate (CFR)

Definition: The case-fatality rate measures the proportion of individuals diagnosed with a particular disease who died from that disease within a specific time frame.
Formula: CFR = (number of deaths from a specific disease/total number of diagnosed cases) x 100
Usefulness: It can used to assess the severity or…[Read more]

Hello Ajarn, thank you for clarifying the role of cross validation.

Hello Ajarn, I am sorry that I could not make the meeting on Thursday morning. My question is: when the dataset is small, first use cross validation (CV), then train the model on split train data from CV, and test the model on split test data from CV?

Then when the model is large, split the data into train and test data, and train and test…[Read more]

Hello Aye, thank you for sharing your model and explanation. I believe adding vaccination as a compartment into your existing model of SIR, can provide more comprehensive views on how they interplay. How and where do you plan to find the parameters necessary for your vaccination compartment?

Hello Tanaphum, thank you for sharing your intervention of choice for your model. Having a vaccination class can add more understanding on how the population in your SIRS model.

Dear Cing, thank you for your question. In my model, I used residual half-life instead of overall duration of residual effect so that I can model the continuous change by considering the decaying rate as residual half-life.

Hello Wannisa, thank you for sharing your intervention of choice. I believe both interventions are relevant to your model of interest. Additionally, not only the efficacy of the treatment, but also the coverage and how well the patients adhere to standard treatments can also affect your model.

Hello Wannisa, yes, it could be better if seasonal patterns can be incorporated into the model. However, my model only accounts for temperature, so it can only show seasonal patterns of mosquito population dynamics affected by temperature.

Hello Cing, thank you for sharing your interesting model. You have used incubation period in your model, most of the time, latent period is used when model the change from the exposed to infectious stage. I believe latent period can be longer or shorter than incubation period depending on the nature of the infection. A person can be asymptomatic…[Read more]

Hello Alex, thank you for sharing your model of interest. Malaria has been one of the persistent infectious disease in the rural and hilly areas. It would be great to see how the model plays out. My question is since malaria is vector-borne disease, will you model the transmission link between human and vector?

Hello Wannisa, thank you for sharing your modeling topic. I find it quite interesting. By any chance, do you have any flow diagram of your transmission model? Would it be coupled between compartments as you consider co-infections with TB.

Hello Wannisa, thank you for your questions. The biting rate is also temperature dependent in the model. The function will be extracted from one of the references (Traoré et al., 2021). I will only need the value of temperature at that period to calculate the biting rate.

Since my model is the population growth model of Anopheles, my consideration for interventions would be ‘Indoor Residual Spraying’ (IRS). It involves spraying of mosquito resting places such as doors and ceilings with long-lasting (residual) insecticides. It aims to kill adult mosquito. So, in my compartmental model, it will target on adult…[Read more]