| Hello HN, I built a dashboard to track Nipah Virus (NiV) spillover events in India and Bangladesh because official data is often buried in PDFs or local vernacular news. The Architecture (Running for $0/mo): Frontend: Static HTML/Tailwind hosted on Cloudflare Pages. Backend: A Cloudflare Worker triggered by a Cron job (every 4 hours). Ingestion: Scrapes RSS feeds for keywords related to encephalitis and NiV. Analysis: Passes headlines to Google Gemini 1.5 Flash (via free API) to extract location data and filter out noise. Database: Google Sheets (fetched as CSV). The AI drafts rows as "Pending," and I manually flip them to "Active" to update the map. Why I built it: Existing global maps often lag by days. By using LLMs to parse local news, I can often detect "Active Clusters" 24-48 hours before they appear on global health aggregate sites. Link: https://nipahwatch.com Feedback on the "Sheet-as-Database" approach or the visualization is welcome. |