Unveiling the Seasonal Trends of Chickenpox Outbreaks in Hungary: An Analysis of the Hungarian Chickenpox Cases Dataset

Chickenpox is a highly infectious disease caused by the varicella-zoster virus. It is one of the most prevalent childhood diseases and can affect individuals of all ages. In Hungary, the Hungarian National Epidemiology Center collects daily counts of chickenpox cases to monitor the spread of the disease. In this blog post, we will explore the seasonal patterns of chickenpox in Hungary using the Hungarian Chickenpox Cases dataset. The data was collected by the National Epidemiology Center of Hungary and made available by the UCI Machine Learning Repository.

Data Link: https://archive.ics.uci.edu/ml/datasets/Hungarian+Chickenpox+Cases

This dataset contains 523 rows of different dates showing chicken pox cases in 20 cities in Hungary.

The data dictionary for the above dataset is as follows:

1. Year: the year of the weekly report (2005-2015)

2. Week: the week of the year of the weekly report (1–52)

3. Total cases: the total number of reported chickenpox cases in Hungary in that week.

4. Child cases 0–4: the number of reported chickenpox cases in children aged 0–4 years in that week.

5. Child cases 5–9: the number of reported chickenpox cases in children aged 5–9 years in that week.

6. Child cases 10–14: the number of reported chickenpox cases in children aged 10–14 years in that week.

The machine learning tools used here for analysis are multiple linear regression and ARIMA.

1. Multiple linear regression: Multiple linear regression is a statistical technique used to analyze the relationship between two or more independent variables and a dependent variable. It is a form of linear regression where the dependent variable is modeled as a linear combination of multiple independent variables.

In this dataset, multiple linear regression has been used to see how many cases are contributed by different cities in Hungary in a particular year.?

2. ARIMA : ARIMA stands for Autoregressive Integrated Moving Average. It is a popular time series analysis method used to model and forecast time series data. The ARIMA model is a combination of three components: autoregression (AR), differencing (I), and moving average (MA). The AR component captures the relationship between the current value of the time series and its previous values. The MA component captures the relationship between the current value of the time series and the error term, which is the difference between the actual value and the predicted value based on the AR component. The I component involves diffencing the time series to make it stationary, which means that its statistical properties are constant over time.

By Multiple Linear regression, we get to know that among 20 cities, only 7 cities are hotspots for Chicken pox cases in Hungary viz. Budapest, Békés,Komárom-Esztergom,Nógrád,Pest,Tolna and Veszprém.

ARIMA for Budapest: Being the capital of Hungary and the 9th most populous city in Europe, the number of cases from this city causes a major outbreak of chicken pox in the whole country. Through ARIMA, we learned that the latest peak for this city was in 524 weeks.

ARIMA for Békés: Békés is located in the south-eastern part of Hungary, thus having a high population density, which causes a high rise in chicken pox cases.Through ARIMA, we learned that the newest peak was at 523 weeks.

ARIMA for Komárom-Esztergom: Komárom-Esztergom is located in northwestern Hungary and is known for its historic cities, such as Esztergom, which was the capital of Hungary in the Middle Ages and is the seat of the Catholic Church in Hungary. The county is also home to the town of Komárom, which is situated on the Danube River and has a rich military history.?Thus, being a tourist hotspot in a country causes it to be a hotspot for chicken pox too.

The newest peak for this city was in 523 weeks.

ARIMA for Nógrád: Nógrád is located in northern Hungary and is known for its scenic landscapes, including the Cserhát and Mátra mountains. Thus, this city, too, being a tourist hotspot, results in becoming a hotspot for chicken pox.

The newest peak for this city was in 524 weeks.

ARIMA for Pest: Pest is located in central Hungary and is known for its cultural and historical significance, as it includes the city of Budapest and many of its suburbs. The county also includes a number of small towns and villages, as well as several natural reserves and recreational areas. The population of Pest has been growing steadily over the past several years, with an average annual growth rate of 0.7% between 2016 and 2020. Thus, an increasing population causes chicken pox outbreaks.

As per ARIMA, the newest peak arrived at 523 weeks.

ARIMA for Tolna: Tolna is located in central-southern Hungary and is known for its wine production, as well as its natural and cultural attractions, such as the Gemenc Forest and the medieval castle of Szekszárd. The county seat is the city of Szekszárd. Thus, the busiest city results in high cases of chicken pox.

As per ARIMA, the newest peak arrived in 526 weeks.

ARIMA for Veszprém: Veszprém is located in western Hungary and is known for its natural beauty, including Lake Balaton, the largest lake in Central Europe. The county seat is the city of Veszprém, which has a population of approximately 62,000 people and is known for its historic castle and charming old town. The population of Veszprém has been growing steadily over the past several years, with an average annual growth rate of 0.5% between 2016 and 2020. Thus, a tourist spot with a high population causes high cases of chicken pox.

As per ARIMA, the peak arrived at 523 weeks.

Hungary has been experiencing a high number of chickenpox cases, particularly in the past few years. The data shows that this increase has been observed across several counties in Hungary, with Budapest and Pest having the highest number of reported cases. The factors contributing to this increase could include a lack of vaccination, increased travel, and more people coming into contact with the virus. Additionally, population density and age demographics may also play a role.

To address this issue, it is important for individuals to get vaccinated and to take precautions to avoid spreading the virus. This includes staying home when sick, practicing good hygiene, and avoiding contact with people who are known to have the virus. Healthcare providers can also play a key role in preventing the spread of chickenpox by identifying cases early, providing treatment, and educating patients about prevention strategies. By taking these steps, we can help reduce the incidence of chickenpox in Hungary and improve the overall health of the population.