The present document is being prepared as a companion handbook to Hands-on workshop on Spatial Epidemiology using R during 51st Annual National Conference of Indian Association of Preventive and Social Medicine (IAPSMCON 2024).

India has launched phase 2 of COVID vaccination program. To fasten the progress of vaccination program, selected private hospitals have been made vaccination centres. “States can use 10,000 hospitals under AB-PMJAY and 687 hospitals under CGHS as Covid-19 vaccination centres (CVCs), who may recover a charge subject to a ceiling of ₹250 per person per dose,” according to the Union health ministry. This webpage has been created for you to easily find the vaccination centre near you.

Information from models to understand outbreak situation: An illustrative example using COVID-19 data.

Handling increasing complexities for Infectious Disease Modeling using R

Illustration: Infected Cohort models using R

Steps in Infectious Disease Modeling

Spatial interpolation using kriging in R

Spatial Interpolation using Inverse Distance Weighing (IDW) in R

Estimation of spatial variation in risk using kernel smoothing in R

Spatial Data Visualisation in R

The present document has been prepared to provide a brief introduction to infectious disease modelling using free and open source solutions such as “R”. The document is not a complete overview of the infectious disease modelling aspects but provides a jumpstart for interested readers to perform mathematical modelling using R. We have created this document as a prelude to the three hour Faculty Development Program (FDP) at the School of Public Health (SPH) of the Kalinga Institute for Industrial Technology (KIIT), Bhubaneswar, India on “Modelling Infectious Diseases using the principles of reproducible research.”

String variables or text data requires preprocessing to carry out meaningful analysis. Using stringr package in R, the same can be done efficiently and in a reproducible manner.

Random number generation using R

Automated bibliography extraction from PubMed using R

Word Cloud formation for text analytics using R

Handling missing data using R

The code focuses on six functions of tidyr viz gather, spread, separate, unite, complete and fill

Data visualisation using ggplot2 package in R

Data transformation using dplyr package in R

Food poising outbreak investigation using R

Map making in R

This document was prepared as an introductory session to Public Health Professionals attending a workshop