Skip to content

pixelatedk/predicting-VL-outbreaks

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

29 Commits
 
 
 
 

Repository files navigation

How can we use predictive modelling and computational biology to predict future outbreaks of NTDs (Neglected Tropical Diseases) in under-resourced communities?

Original research created by InViro Labs (Arya Bari, Marlene Bucher, Vicky Kuang)

Advisory Board: Dr Lindsey Fiddes (Biomedical Engineering at UofT) and Dr. Natasha Christie-Holmes (Emerging Pandemic and Infections Consortium), PhD Candidate Lindsey Stern (BME)

we propose a sentinel surveillance tracking system using pre-existing HIV patient care infrastructure.

our three-tier solution which...

  1. first, quantifies a median time lead using HIV-patients (whom display symptoms of visceral leishmaniasis earlier than normal asymptomatic carriers)
Screenshot 2026-01-26 at 1 08 23 AM
  1. then, predicts geographical hotspots of future spread depending on weather conditions, soil moisture, humidity, and most importantly -- known diagnoses of VL using HIV-sentinel cases. (demo attached in repo)
Screenshot 2026-01-26 at 1 41 17 AM
  1. before allowing local scientists to then geographically locate areas for xenomonitoring via qPCR testing. which empowers public health officials to accurately identify the spread of distinct VL strands up to six months prior to symptomatic infection in the broader population.

Full Pitch Presented as Finalists at BioCatalyst 2026 LeadTime by Inviro Labs. .pdf

About

proof of concept produced with colab: we presented this in the jan 2026 undergraduate biomedical engineering case comp. abstract submitted in support of IAS 2026 delegacy.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors