Project - AMOR DE MÃE

Contents

• Introduction
• Data
• Methodology
• Tooling
• Concluisions
• Acknowledgments
• References

Introduction

This project is the result of module 2, of the Bootcamp in Data Science applied (second edition) proposed by Alura and apoint to some analysis about the numbers of vaccines in pregnant women and fetal deaths from 1994 to 2019 in Brazil and the northeastern states of the country. These data are available in two official website of Brazilian government:

• Data about vaccine, were found in the official website of Brazilian Healthcare System: DATASUS
• Data about fetal death, were found in the official website of Brazilian Institute of Geography and Statistics: IBGE

Based on this I'll analyze the vaccine curve in Brazil and in the states(with a focus on the northeastern states), seeking to answers and trying to understand the dynamics of the relationship between vaccines and fetal deaths in Brazil.

Vaccines x Fetal Death

The Vacination of pregnant women its priority to World Health Organization (WHO), and represents the first love act between a mother and your baby. The vaccines prevant some complicantion in the birth moment and the diseases development during the child's growth. The maternal antibodies are very important to the baby health in the first 12 months of the pregnancy, when it still in the mother womb. The antibodies provided by the mother, protect the baby, until it can be vaccinated and develops his own immune defenses.

According to the Brazil Ministry Health , the vaccination of women pregnant reduces the numbers of fetal deaths, wich can be definide as the baby's deaths due to complications during the childbirth or the pragnancy. Besides to influence in the bith rate, the fetal death can be an indicator that help a visualization of spatial distribution, and the quality of woman health assistance. So the vaccination is responsable for avoiding problemns like:

• Congenital malformations and pregnancy damage (abortion, premature birth...);

• Pregnant women and babies, constitue a high risk group for the influenza virus, and vacination can avoid the hospitalization and severe respiratory conditions caused by the virus;

• Whitout Knowing it, woman can transmit the Hepatitis B virus, to your baby;

Vaccines analyzed

In this project there was four vaccines it was analyzed:

• Hepatitis-B:
  • The vaccination protects against the contamination for hepatitis virus, and avoid problemns such as liver inflamation, that can cronify and cause cancer and cirrhosis.
• DT:
  • The Vaccination protect against the diphtheria and tetanus.
• DTPA:
  • The Vaccination protect against the diphtheria, tetanus and whooping cough.
• Yellow Fever:
  • The Yellow Fever vaccination in pregnant women its a particular case, since the immunizing against the yellow fever, its made by the live virus. But acoording to the Center of Imunization for the Hospital and Maternity Santa Joana (São Paulo), and the website Vacinas para Gravidas (Vaccines for Pregnant woman, in literal traduction) such as the old people, pregnant woman hardly can develop the complication by the vaccines, and this particular vaccine it's used in special localities, when was developed many cases of yellow fever.

Data

The data used in this analysis was obtained from the DATASUS aplication TABNET, and the IBGE aplication SIDRA on Jun 06, 2021, and you can find them, here on my repositorie. The datasets chosen have an incompatibility of the dates, and for that I decided divide them in 2 groups of the vaccines curves, wich is:

• Group 1
  • The vacines curves from 1994 to March 2021:
    • Hepatitis-B and Yellow Fever
• Group 2
  • The vacines curves from 2013 to March 2021:
    • DTPA and DT
      And this information is used to:
  • To compare the progression of each vacine curve in Brasil;
  • To demonstrate the mosts affecteds states, with a focus on the Northeastern states. The Five dataset analysed here, was the numbers cases of fetal deaths ranges from 2003 to 2019, in Brasil
• Number of Deaths for Dengue Cases ranges from January 2008 to March 2021: And this information is used to:
  • To make the comparative studies above;
  • And was used to make a statiscal aproximation, of the percentage of vaccines numbers/fetal deaths, by the year.

A detailed description of each vaccine curve dataset and its meaning is also provided in the DATASUS website, you can find here

Methodology

• The datasets are analysed following the logic of approximation of the scale, when the first moment I looking for the distribution of the vaccine curve and fetal deaths per year, in the country.

• The Second part I'll analyse the same datasets across the brazilian states, trying to find some correlation, and understanding the distribution of vaccine and fetal deaths in the northeastern states.

• Finally I'will analysed the distibution the same datasets but, in this last part the data will spatialized in a map, considering the most critical year's and all brazilian states.

With this we were able to made some conclusions about the variables observerd, you cand find them in the Conclusion

Tooling (Libraries and Technology)

This project are made in the python 3.8.5, used the Collab the cloud storage services of google, Google Collaboratory.The libraries used here, were:

• Pandas, the main librarie of data analysis in Python, used to manipulate and help in statiscal conclusion about the datasets;
• Numpy, using to heandle missing data;
• date, to transform columns in date type;
• Seabornd,Matplotlib.pyplot, for plotting of the charts;
• Geopandas, for plotting the map.

Conclusion

After this analysis, I have found some conclusions:

• The years with most numbers concentrations about de vaccine's curves and fetal deaths is the period that goes from 2015 to 2018;

• About numbers of fetal deaths proporcional to number of vaccines, i conclue that some regions like Southeast and Northeast have a low rate of deaths numbers (and that it's a good news). When we look to the plotted maps, we can observe the concentrations of this numbers in the South and North region of the country;

• The analisys focused in northeast states, it was important to understand the distribution of this data in a region apparently unaffected. When we observed the charts with proporcional numbers, we can understand that some states have an expressive numbers of fetal deaths like Ceará, Pernambuco, Sergipe and Bahia

To advance in the analisys

• One good idea, it will be looking the anual evolution of the cases, in other brazilian region and states.

• Other thing that will enhace the project, its looking for dataset most recent, and about the numbers of influenza vaccine curve, once it's are one of most important imunno for pregnant woman and babys. Unfortunately I can't find informantion about this data in DATASUS website.

Acknowledgments

This project as said before, was proposed as a second project in the Alura's Bootcamp, as an introduction to the Data Science world.

So I'm gonna say thank you one more time to Guilherme and Thiago, for the knowledge passed on to the students, and to ScubaTeam and all the comunity it was created on the discord.

You guys helped me so many times!! THANK YOU :)

References

1. Papers:

1.1. Paper1 - VACINAÇÃO DA GESTANTE NO PRÉ-NATAL – Revisão integrativa da literatura

1.2. Paper2 - Atenção Pré-Natal no Município de Quixadá-CE segundo indicadores de processo do SISPRENATAL

1.3. Paper3 - Paism: um marco na abordagem da saúde reprodutiva no Brasil

1.4. Paper4 - Avaliação da cobertura e indicadores do Programa de Humanização do Pré-natal e Nascimento no município de Salvador, Bahia, Brasil

2. Articels and specialized health sites

2.1. Artcle1 - CALENDÁRIO DE VACINAÇÃO SBIm GESTANTE

2.2. Article2 - Manual de Vigilância do Óbito Infantil e Fetal e do Comitê de Prevenção do Óbito Infantil e Fetal

2.3. Article3 - vacina febre amarela(atenuada)5 e 10 doses

2.4. Article4 - Vacina da febre amarela em gestantes: quando tomar

2.5. Article5 - Vacinas para Gravidas

Contact

If you have any tips or suggestions, feel free to contact me here:

And before I forget...

...viva o SUS :)