Data Visualization

Blog of the Data Visualization & Communication Course at OSB-AUB

This is my favorite part about analytics: Taking boring flat data and bringing it to life through visualization” John Tukey

Primary Healthcare Centers in Lebanon

Primary Healthcare Centers in Lebanon

Since I started working in the healthcare sector I’ve always been interested in knowing more about this industry. As such, while exploring the WDI Data I studied several healthcare indicators and it turns out – Lebanon is doing better than we thought! I was intrigued to know what’s beyond those indicators, and luckily I found a detailed dataset about Primary Health Care Centers in Lebanon on The Humanitarian Data Exchange, I was surprised to know we had this many centers.

Could this visualization be a sign of a sound healthcare system ?
Did this awareness in healthcare aid us in containing the Covid-19?
Do you think there is a better future for the healthcare system for Lebanon, or will it be worst?

Personally, I am optimistic..

So here are some things I didn’t know:

  • There are 174 Operational Primary Healthcare Centers in Lebanon
  • There are 25 PHC funded by UNHCR
  • There are 100 PHC that provide subsidized services.
  • Nabatieh has 0 operational PHCs.
  • The North governorate has the highest number of operational PHC: 36


In this dashboard, I prepared – using Tableau – a map that shows the different Operational PHC locations in Lebanon filtered by UNHCR Funding. Alongside it, is a bar chart showing the percentage of operational PHC in each Governorate. Finally, at the bottom, you can find a stacked bar chart representing the number of operational PHC per governorate, highlighting those who offer subsidized services.

Hospital Beds Availability and COVID-19

Hospital Beds Availability and COVID-19

Accommodating the Covid-19 Sick Patients within Hospital Beds has been the main challenge worldwide for poor and rich countries alike and for countries with strong healthcare systems and weak healthcare systems alike. Securing these beds is a life or death situation for the Covid-19 critically ill patients who need special intensive care beds. This visulaization will show you the distribution of intensive care patients by country and will show you that the more hospital beds available per 1,000 poulation the lower the Covid-10 mortalility rates.

As per the scatter diagram, countries with higher number of beds per 1,000 population have maintained lower Covid-19 mortality rate even after they went into the peak of Covid-19; best example being Japan with only 4 dead per 1 million population. This is contrasted with England for example which, even prior to reaching the peak of Covid-19, had a high Covid-19 mortality rate of 305 per million. In Japan, there are 13.4 beds per 1000 population whereas in England there are only 2.8 beds per 1000 population.

As per the heat map, we find that Brazil, Iran, Vietnam and Thailand are having the highest percent of critical care patients. Also, this map shows that Lebanon has a 6.53% of critical Covid-19 cases.

The History and Future of Fertility in different regions

The History and Future of Fertility in different regions

The fertility mutates from region to another and it is related to the culture, education level and civilization. It also decreases from year to year because of civilization, weather, and human life style.

This Dash compares 3 different countries USA: Advance country , Lebanon : Arab region and Africa:third world and shows that all the countries will have the same fertility rate in the future.

Data source:

Health status by Region

Health status by Region

As the World is today coping with the new virus COVID-19 that spread five months ago, leading to millions of deaths behind, it has been proven that health is the most important component on the human life, and that the existence of advanced, progressive and up to date health care and health centers are crucial for an efficient health assistance for a whole given nation. As such, I found in the World bank dataset some indicators that were efficient enough to picture the correlation between health expenditures and the lifetime of infants and adults.

We can spot how health expenditure per capita varies from region to region, leaving a considerable influence on life expectancy. In fact, Europe, that has the highest health expenditure(1,200,000 $), has the highest life expectancy recording 77 years. Africa that has 61,347$ expenditures, expects an average age for its population equal to 56 years. This is very logical since the absence of social welfare, health care, and the limited number of sanitarian and health centers prevents ill people from having their medical treatments’ needs, which therefore leads to their death. However, a third indicator was included which is the infant mortality rate that has a negative relationship with the health expenditure. We can notice that Europe has the lowest rate 0.7% compared to Africa that has 6.7% mortality rate among infants. Thus, we can conclude that Europe which has the highest health expenditures has the lowest infants mortality rate because of the provision of vaccinations, and frequent followups with doctors. Whereas, in Africa, where there are a lot of diseases, there is lack of medical personnel and machinery used to assess and diagnose ill children, or infected pregnant women.

Thus, the integration of technology in health and sanitarian sector and the presence of social welfare and well-prepared medical centers proved to have a positive relationship with the health and the lifetime of people, including children.

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