Using Machine Learning to Efficiently Vaccinate Homebound Patients Against COVID-19: A Real-time Immunization Campaign

In March 2021, the New York City Department of Health and Mental Hygiene (NYCDOHMH) received a supply of single-dose Janssen COVID-19 vaccines to vaccinate the city's patients who are homebound, but they needed assistance to identify and reach this population [1,2]. Mount Sinai Visiting Doctors (MSVD) is a large home-based primary care program serving more than 1200 patients who are homebound throughout Manhattan. We partnered with NYCDOHMH to vaccinate patients in our program. The administrative team generally schedules routine home visits based on zip codes, using 12 unique catchment areas covering all of Manhattan. This existing zoning system was inadequate for vaccination purposes for several reasons, mainly because these zones were too large. Furthermore, the additional task of manually scheduling patients by zone would be overwhelming for administrative staff, especially given the temporal constraints of the Janssen vaccine (ie, doses expired in 6 hours). In response, we developed a system to geographically cluster patients to efficiently vaccinate our homebound patients against COVID-19.