Zoonotic spillover risk mapping for Bangladesh
Combine livestock density, land-use change, and reported human case data to build a district-level spillover risk surface. Deliverable: a reproducible R/Python pipeline plus a mapped risk index.
Research
Our Projects
Every BORA project is chosen on one test: can a motivated student with a laptop produce a defensible, publishable result from open data? If yes, it is a BORA project.
Illustrative project slate. These are the project types the five tracks
are scoped to produce. Live cohort projects will be listed here with their team, mentor,
GitHub repository, and output status once the pilot cohort begins.
Track 1
One Health & Public Health
Cross-sector outbreak reconstruction
Reconstruct a past outbreak using human, veterinary, and environmental records together, and document where the three sectors failed to share signal in time.
Track 2
Infectious Disease Epidemiology
Outbreak trend modelling — measles and dengue
Fit time-series models to open national case data, quantify seasonality, and test whether reported surges exceed expected baselines.
R₀ estimation from open case data
Estimate the effective reproduction number across waves and districts, with explicit treatment of reporting delay and under-ascertainment.
Track 3
AMR & Genomic Surveillance
Whole-genome analysis of public AMR isolates
Pull South Asian isolate genomes from public repositories, run standardised assembly and AMR-gene detection, and compare resistance profiles by host and source.
Resistome mapping across the food chain
Map resistance-gene carriage from farm to market to clinic using existing published sequence data, and identify where the strongest overlap sits.
Tracks 4 & 5
Omics, Veterinary, Agriculture & Fisheries
RNA-seq reanalysis
Reanalyse published transcriptomic datasets with modern pipelines and test whether the original conclusions hold.
Comparative genomics
Compare regional isolate genomes against global references to locate lineage-specific variation.
Livestock disease-burden mapping
Quantify reported livestock disease burden by district and correlate it with production loss estimates.
Fisheries production–export gap
Reconcile national production statistics against export records to size the unexplained gap.
Systematic reviews & meta-analysis
Pooled prevalence and resistance estimates for Bangladesh-specific questions with no current synthesis.
Your proposal
Bring a question. If it runs on open data and survives moderator review, it becomes a cohort project. Pitch it →
Standards
How a project becomes real
01
Proposed
A mentor or student writes a one-page scope: question, dataset, method, expected output.
02
Validated
A moderator checks feasibility, ethics, and whether the data genuinely exists and is open.
03
Staffed
A team of 4–5 students is assigned under a core mentor, with tasks split explicitly.
04
Published
Code to GitHub, manuscript to a preprint server or journal, entry to the BORA archive.