Working with NFHS data in R
A practical guide to NFHS microdata in R: access, variable names, survey weights, the survey design object, and weighted state estimates with confidence intervals.
Bayesian disease mapping in R with INLA
A step-by-step guide to fitting a BYM2 disease-mapping model with R-INLA, from the neighbour graph to relative-risk and exceedance maps.
Short Course in Epidemiology: Concepts and Methods
Course site for the epidemiology short course at the Interdisciplinary Centre for Public Health, IISc Bengaluru, run with the London School of Hygiene and Tropical Medicine (21 to 25 September 2026).
Pre-Conference Workshop: Reproducible and AI-Augmented Medical Education Research
A two-day pre-conference workshop on reproducible and AI-augmented medical education research in R, with slide decks on data wrangling, visualisation and Quarto.
Three-Day Workshop on Reproducible and AI-aided Health Data Analysis at IQRAA
A multi-day data analysis workshop series in R, including an AI-basics module and a hands-on EDA module using tidyverse verbs on a WHO tuberculosis dataset.
Three-Day Workshop on Manuscript Preparation and Research Communication
Sessions on writing the Materials and Methods and Results sections, tables and figures, and avoiding plagiarism.
Pre-Conference Workshop on Infectious Disease Modeling (IDM)
A hands-on, R-based pre-conference workshop on infectious disease modeling, built around collaborative group modeling activities at JHAPSMCON-2026.
Spatial Epidemiology using R
A structured 4-day hands-on workshop on spatial epidemiology in R, covering spatial concepts, map-making, exploratory spatial data analysis, clustering, and interactive visualisation, with a participant handbook.
Health Technology Assessment using R
A hands-on workshop on conducting health technology assessment in R, covering decision-analytic and economic modelling. Participants learn to build decision trees and Markov models, run probabilistic sensitivity analyses, and produce reproducible cost-effectiveness outputs.
R Workshop (BioEngineeR)
An introductory hands-on R and Quarto session that walks participants through building their first Quarto report and rendering it to HTML, Word, and PDF.
Introduction to Health Data Science
A teaching module introducing health data science with R and the tidyverse, featuring exercises, group activities, and a worked COVID-19 Kerala data analysis.
National Workshop on Health Data Analytics using R
A 3-day national hands-on workshop on health data analytics using R, combining concepts with coding. Cohort 2, delivered at AIIMS Mangalagiri for clinicians and public-health professionals.
Gender Inequities in COVID-19 Vaccinations
This post looks into the COVID-19 vaccinations in India and the respective states. The data is downloaded from COVID-19 India Tracker Website as provided in the data sources section in the methodology. Total Vaccinations ## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8 ## Returning the palette you asked for with that many colors ## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8 ## Returning the palette you asked for with that many colors Inequity in Vaccine Delivery among the genders vaccine_gender_fig <- vaccine_df %>% filter(State == "India") %>% plot_ly(x = ~ Date, y = ~females_prop, type = "scatter", mode = "lines") %>% layout(showlegend = FALSE) %>% add_trace(y = ~males_prop, type = "scatter", mode = "lines", name = "Male") %>% layout(yaxis = list(title = 'Proportion of Total Vaccinations')) vaccine_gender_fig
First Wave vs Second Wave
The abrupt onset of the second wave of COVID-19 in India has taken the country by storm. With over 4,00,000 cases being reported daily, India has over 37,00,000 active cases as of 12, May 2021. This post aims to estimate the epidemiological parameters of COVID-19 epidemic in India during the first and second waves. As discussed in the previous post, India’s epidemic curve suggests an ongoing second wave of COVID-19 infections in the country.
COVID-19 Epidemic in India
The importance of epidemic curves in epidemiology in understanding and visualising the onset and progression of an epidemic is immense. It provides key insights in terms of the magnitude of the disease, the mode of transmission, trends over time and the incubation period. The below interactive plot is variant of the epidemic curve of COVID-19 in India. By default, the weekly average of daily cases, recovered and deaths is presented in the plot.