Dashboard en Salud

An end to end R pipeline modeling the relationship between COVID-19 case surges and national diagnostic device shortages (e.g., sodium citrate blood collection tubes). Combines JHU CSSE epidemiological time-series data with FDA medical device shortage data acquired via web scraping (rvest/httr) to overcome bot-blocking. Applies cross correlation (CCF) time-series analysis to identify a 5-day lag between case spikes and official shortage reporting insight informed by my background managing coagulation instrument supply chains in clinical laboratories during the pandemic. Built using R (tidyverse, rvest, httr, lubridate) following a reproducible data pipeline architecture (Obtain → Scrub → Explore → Model → Interpret, OSEMN framework).

schdcsdc

Week 8, Asim Maharjan

Kajian Berdasarkan Prinsip Persepsi Visual, Rasio Data-Tinta, dan Kejelasan Informasi (Materi: Unsur dan Jenis Visualisasi)