East Africa in Numbers — Part 1: Child and Maternal Health
Preamble
It’s no secret that we are living in one of the most prosperous times since the inception of the universe. We have eradicated deadly diseases, uplifted millions from abject poverty and prolonged lives for many elderly and specially-abled individuals. More information about this tremendous progress can be found here At Crossroads with the Past.
But how distributed is this progress? Is it being skewed by China’s Economic miracle or Indian’s Rapid progress over the last few decades? Who is being left behind in this great leap forward? Of course, the answer to this question can take up the best part of a higher doctorate's thesis. Throughout this series, I hope to cover this progress from the perspective of East Africa, comprising of 11 sub-Saharan countries.
In the fast part of the series, I would cover Child and Maternal Health indicators in the region. Although the World Bank, which is my source for this analysis, tracks many indicators for this topic. I had to be selective and include indicators that are both (i) covered for all 11 countries and (ii) covered for a lengthy period of time ideally >20 years.
As the first step in any data analysis projects is business understanding, I had to understand the importance of each indicator and how it contributed to the bigger picture. The following indicators are covered in this analysis.
- Number of infant deaths
- Mortality rate, under-5 (per 1,000 live births)
- Immunization against diphtheria, pertussis, and tetanus (% of children ages 12–23 months)
- Number of maternal deaths
The next step was understandably data-gathering and I had to rely on good ol scraping
Scraping & Merging the Data
The data is gathered and curated by the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) and they have a nice portal for downloading country specific data. But since I was interested in downloading the data for 11 countries, I had to automate the downloading process. One challenge I faced was downloading all the 11 files into specific folder where I can then read and merge from. After reading the Selenium docs, I figured I can set up browser preferences before initializing the selenium driver. Fortunately, the scraping part was pretty-straightforward due to the simplicity and structure of the portal. I did all my scraping in only 6 lines of code.
for country in countries:
searchInput=driver.find_element(By.ID, "q2").send_keys(f'{country} - Health')
driver.find_element(By.CLASS_NAME,'button').send_keys(Keys.ENTER)
country_indicator_link=driver.find_element(By.XPATH,'/html/body/div[7]/div/div[3]/div/div/div/div/div/div/section/div[1]/div[2]/div/div/ul/li[1]/div/div/div/div[1]/div[1]/a').click()
country_indicator_download=driver.find_element(By.XPATH,'/html/body/div[7]/div/div[3]/div/div[2]/div/div/div[2]/div[3]/div[1]/div/ul/li[1]/div[3]/a[1]').click()
home_btn=driver.find_element(By.XPATH,'/html/body/div[6]/div/nav/div[2]/div/div[1]/div[1]/a').click()After the download process, the next task was to merge all the indicators into one file. Again, Python streamlines this and I did all my merging in only 4 lines of code.
Visualizing the Indicators
After cleaning the data, renaming columns and viewing standard data frame info, I used Plotly to visualize the data.
Infant Deaths
Infant deaths, defined as the death of an infant before their first birthday, has seen remarkable decline worldwide. 5 million neonatal deaths were recorded in 1990 compared to 2.4 million in 2020 (WHO Fact Sheet, 2021). Sub-Saharan Africa, which our 11 countries are situated in, had the highest number of infant deaths. As can be seen in the stacked-bar chart below, this trend is on the fall. Out of the 11 countries in question, Ethiopia had the highest infant death. I suspect this might be a case of Ethiopia’s population being high than other countries. This is further strengthened by Djibouti having the lowest number of infant deaths in the region. Djibouti has the lowest population in the region.
Mortality rate, under-5 (per 1,000 live births)
The probability that a child would lose their life before hitting the age of 5 per 1000 live births. This trend has declined 59% globally from being 0.093 in 1990 to 0.038 in 2020 (UNICEF Child Data, 2021). Somalia has the highest mortality rate for children under the age of five in the region whereas Kenya has the lowest mortality rate in the region.
Immunization against diphtheria, pertussis, and tetanus (% of children ages 12–23 months)
This indicator measures the percentage of children between the ages of 12 and 23 months who have received 3 doses of vaccines against diphtheria, pertussis, and tetanus. This has greatly gained ground going from 76% in 1990 to 83% in 2020 worldwide. East Africa has also noticed similar trend. Rwanda has the highest immunization rate for children of that age whilst Somalia having the lowest.
Number of maternal deaths
The annual number of female deaths from any cause related to or aggravated by pregnancy or its management (excluding accidental or incidental causes) during pregnancy and childbirth or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy. This has declined by 34% globally. Ethiopia has the highest fatality rate for maternity in the region, with Djibouti averaging the lowest.
Conclusion
The region has been progressing albeit slowly in improving child and maternal health. Globally, it is still lagging behind in crucial areas like immunization and leading in unwanted areas like number of infant deaths. To objectively compare these countries, more variables are needed e.g. population size and health facilities available. Through the second part of this series, I hope to make an objective comparison. Stay tuned for the link.
The link to the github repo containing data and the ipynb file : NajibAbdullahi/EastAfricaHealth (github.com)
