Predicting airborne infection risk

Posted byPhilip A. Lederer MDPosted inpersonal ambient CO2 monitoring

I’m pleased that our research study, “Predicting airborne infection risk: Association between personal ambient carbon dioxide (CO2) level monitoring and incidence of tuberculosis infection in South African health workers,” was recently published in the journal Clinical Infectious Diseases.

The central idea of our paper is that health workers face high occupational TB risk. Increasing CO2 levels (indicative of poor ventilation and/or high occupancy) were associated with higher likelihood of health worker TB infection. Personal ambient CO2 monitoring may help target interventions to decrease TB transmission in healthcare facilities. It may also help health workers self-monitor occupational risk and has implications for other airborne infections including COVID-19.

I’m biased, but I think this area of research, personal ambient CO2 monitoring, should be given a priority for more funding. TB is still here, along with COVID-19, and new airborne infections are certain to emerge in the coming years. Personal CO2 monitoring is a way for health workers and the general public to potentially protect themselves.

Thanks to the co-authors, Ruvandhi Nathavitharana, Hridesh Mishra, Amanda Sullivan, Shelley Hurwitz, Jack Meintjes, Edward Nardell, and Grant Theron. I’d also like to give a particular thanks to Hridesh for his hard work on the technical aspects of the study, Ed for his vision and leadership, and Ruvandhi and Grant for their persistence and efforts taking this study across the finish line.

The research study took place in Cape Town, South Africa. The research is applicable globally.

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Published by Philip A. Lederer MD

Thanks for visiting my website! I was born in 1980 in Columbus, Ohio and live with my family in Jamaica Plain, Massachusetts. My training is in internal medicine, public health, and infectious diseases. I am an advocate, writer, and musician, and recently I completed my first marathon.

One thought on “Predicting airborne infection risk”

  1. Thank you for sharing ! I wonder about the potential for building low-cost, DIY, CO2 monitors using Raspberry Pi / Adruino and then also linking to maps. It might help administrators or other CDC or MOH staff to monitor locations with high CO2 and elevated “shared air”. It might be possible to have near-real-time maps using Python and low cost DIY tools — or even integrate with Aranet and commercial sensors.

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