Karina Dian Lestari

The interventions I am considering putting in the model are the use of LLIN and IRS. Indonesian government has a national program to distribute LLINs as a malaria control. The coverage of LLIN and IRS in Rejang Lebong area will be based on the report from the National Malaria Control Program (NMCP).

From this meta-analysis study, the efficacy of…[Read more]

Yes, we will be focusing on Pf infection and the travellers are assumed to be naive to malaria in the model.

For modelling the risk of malaria for travelers to plantation area inside the forest in Rejang Lebong district, I will use the same compartments described in the following paper (https://malariajournal.biomedcentral.com/articles/10.1186/1475-2875-8-296#MOESM1). The only difference I made is I do not incorporate Latent Mosquito compartment,…[Read more]

Thank you for the feedback, Ajarn Pan. I’m interested in doing similar things to this paper https://malariajournal.biomedcentral.com/articles/10.1186/1475-2875-8-296#Sec8 which trying estimate the risk of non-immune individual acquiring falciparum malaria when traveling to the Amazon region of Brazil. Indonesia has similar forestry areas where the…[Read more]

I am interested in investigating the risk of getting malaria for travelers who travel to area with stable transmission. The area I am interested in is the forestry area in Sumatera island, such as Aceh and Bengkulu provinces.

1. Thailand had an increasing suicide rate as any other country. However, Thailand had a different economic and social-cultural context from the countries that are mentioned in the paper which mostly has industrial economy. In addition, there is only one study that has been done to address the problem.

2. Interesting finding in this study is that…[Read more]

1. Spatial epidemiology can be considered an interdisciplinary science since to use the method well, we need to have knowledge of the epidemiology of the disease, geography to understand the technical terms that are used, and statistics for doing the analysis. The reason why it is not utilized well might be:
– Limited knowledge of the use of…[Read more]

Hi Taro, your dashboard is clean and contains the necessary information. One thing to note, I realised that the date format is mm/dd/yyyy which sometimes can get confusing for some of your reader. I suggest the month is formatted to the name of the month to make it clearer. Thank you for sharing.

Hi all,

Kindly see my Power BI dashboard here. I choose to use a black background with some light text colour to make it contrast with the background. The one-page dashboard includes all the basic info about the COVID-19 situation such as confirmed, recovery, and death. The number on the tables is daily for people who are interested in seeing the…[Read more]

Hi all,

kindly see my updated Power BI dashboard for COVID-19 cases visualization. The first page of the dashboard gives us summary of total cases and total reporting country by using “Cards” tool. The rest of the pages show the different approach of visualisation, for example using Line Chart to visualise the growth of daily COVID-19 cases and…[Read more]

Hi all,

Kindly see my Power BI dashboard. This dashboard show Countries, GDP per capita and COVID-19 variables, such as daily cases, daily recovery, and daily death. The table is useful to make a comparison, for example between the GDP per capita and COVID-19 cases.

Thank you for sharing, Kansiri. I really like the map visualization on this dashboard. I also agree with your point of improvement, particularly on the colour of the dashboard. If I may add, the graph on the right side is nice but does not really need to be that big.

This is one example of a data visualization dashboard for COVID-19 cases https://www.worldometers.info/coronavirus/, developed by the collaboration of developer, researcher, and volunteer across the world. it is a simple and very informative dashboard that highlights the number of COVID-19 cases, deaths, and recovered cases. These numbers are also…[Read more]

Hi Yanin,

The CRF layout is clear and conscience. The appropriate units are provided, and the date and time format are clearly stated. However, I would say it is better to change the time format to 24 hours instead of 12 hours (AM/PM) to reduce human error (for example do not tick the appropriate AM/PM). Another thing that could be improved is…[Read more]

Hi Fajar,

The CRF layout is clear and conscience. The date and time format are clearly stated, and appropriate units are provided. It is nice to put the “not measured” checkbox to clear the confusion about whether the data is not entered or not done. I also like the idea to put the method of temperature check and blood pressure measurement. How…[Read more]

My suggestion is to delete the “Date of birth” field to avoid collecting participants’ privacy data.

The data will be easier to understand for a lot of people, not just the team that develops the database. It will also be easier if the researchers want to run different analyses in the future. Data cleaning will relatively take a shorter time.

I was involved in a clinical trial study that use OpenClinica as their database management. It has all the above-mentioned processes: audit trial/time stamp, user authentication and access control level, edit check and logical check, and data backup and recovery plan. My role in that study was only to be the user and did not involve in the…[Read more]