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https://github.com/hrc-123/vector-borne-diseases

Vector borne diseases
https://github.com/hrc-123/vector-borne-diseases

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Vector borne diseases

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README 

        
![coverpage](https://github.com/HRC-123/Vector-Borne-Diseases/assets/98754211/9df2e5ac-8e28-4644-8680-1cf99cc8bb7c)

# VECTOR-GUARD

### District level Vector-Borne Disease Prediction Model for Punjab

*Vector Guard is an innovative machine learning and web-based application designed to revolutionize the prediction and management of vector-borne diseases in Punjab, India. By leveraging advanced machine learning techniques, particularly Ridge Regression, the project aims to significantly reduce the impact of diseases like Malaria. The application empowers public health officials with precise and timely predictions, enabling proactive interventions that can save lives and resources. The 30% improvement in prediction accuracy achieved by Vector Guard underscores its potential to transform public health strategies and outcomes in the region.*







![Why need](https://github.com/HRC-123/Vector-Borne-Diseases/assets/98754211/5be72dda-1779-4bc4-a81b-330735e0dc97)

* **Vector-borne diseases account for more than 17% of all infectious diseases, causing more than 700 000 deaths annually. They can be caused by either parasites, bacteria or viruses**

* **Limited Local Prediction:** Existing disease prediction websites (e.g., WHO) lack state-specific data, making them unsuitable for Punjab.

* **Public Health Need:** Vector-borne diseases pose a serious health threat if left untreated.

* **Data Gap:** Historical disease case data not readily available online.

* **Project Impact:**

  - Improved disease awareness in Punjab.

  - More accurate prediction of outbreaks.

  - Potential to save lives through early intervention.

  - Filling the data gap on vector-borne diseases in Punjab.



# Baisc Structure 

### UML diagram

![UML](https://github.com/HRC-123/Vector-Borne-Diseases/assets/98754211/ae00cd9f-fe3a-44c6-835a-e9c7ee79c2b2)




* The goal is to provide a localized, accurate, and user-friendly platform for predicting vector-borne disease outbreaks.

* The development of Vector Guard involves several steps, including:

  * Data collection

  * Preprocessing

  * Model training

  * Deployment

* Initially, a large dataset of weather data and historical disease cases from 2017 to 2020 is collected.

* This dataset is then pre-processed to ensure accuracy and consistency.

* Next, the Ridge Regression algorithm is trained on the pre-processed dataset.

  * This involves using historical data to learn the patterns and correlations between weather conditions and disease outbreaks.

  * The model undergoes several iterations of training and testing to optimize its predictive accuracy.

* Once the training is complete, the model is deployed on the Vector Guard web application.

* Users can access the platform to get predictions on potential disease outbreaks based on current weather conditions and historical data.

  * This can help healthcare providers and government agencies to implement timely interventions and reduce the impact of vector-borne diseases.

* Overall, Vector Guard aims to improve public health outcomes by providing accurate and timely predictions of vector-borne disease outbreaks, facilitating early intervention and management.





# how to fetch the code

### npm init -y

### Clone or download the zip file

### npm i ejs express express-ejs-layouts express-flash-messages express-session method-override mongoose path nodemon or 

# npm install



### npm start



### Open any browser and type : localhost:1234 or hostname:1234