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Across all our engagements, our goal is the same:
To meaningfully combine geographics, demographics, and health outcomes data to produce actionable, community-level insights.
Our Story
Founded in Maine by two public health leaders.
During their decades working in public health, Ken and Kevin kept encountering the frustration of needing to make community-level decisions without crucial local data. Without access to high-quality data at the community level, health officials and organizations often miss insights and trends that should be in plain sight.
​This lack of localized data can lead to ineffective decisions and inefficient use of limited resources and taxpayer funds. Early in the COVID response, Ken and Kevin sat on opposite sides of the country -- Ken in Marin County, California and Kevin at the New York City Department of Health and Mental Hygiene. But they were both working on the same problem: trying to identify and map the multigenerational households in their jurisdictions.
Marin and New York City possessed the resources to task epidemiologists with identifying this critical household type, but Ken and Kevin recognized that many of the country's public health departments and other community organizations did not. Additionally, the simultaneous analysis to pinpoint multigenerational households was done using the same, publicly-available datasets - a massive inefficiency.​
Apriqot aims to solve both of these pain points - the absence of quality local data to inform decision making and the limited resources of many community-serving organizations - by making highly-actionable, localized population estimates accessible to the stakeholders who need them most. ​
Apriqot was formally founded in 2023 and was embedded at Northeastern's Roux Institute in the inaugural class of the Future of Healthcare Founders Residency.
Why Are We Called Apriqot?
The shared language of data and fruit.
There are many different reasons why we’re called Apriqot.
First, we like apricots!
But we also named our company Apriqot because apricots kept coming up while we developed the idea. For example, Apriqot establishes and maintains many copies of the places we are characterizing, kind of like an ORCHARD. And within each characterization (a TREE) there are many individuals (like the APRICOTS). We also call the process of bringing in users’ local data and merging it with our data GRAFTING, and some of the methods we use to produce estimates sometimes include KERNEL methods.
Also, we like that apricot is a color, which makes some decisions a lot easier (e.g., what color should our logo be?)
And apricots have a nice blush to them, which makes them look a little like people.
But the real reason we are called Apriqot is a bit more "mathy." In public health, one typically uses p for the probability of having some condition or disease. If you are talking about a lot of people in community, then pit would be the probability of the ith person have the disease at time t. And if you wanted to talk about the average probability, you might use pot, pronounced “p naught t,” as the average probability of having the disease at time t. So the chance of not having a condition is 1-p, but that is also called q. So qot is the average probability of not having the condition or disease in the community– the probability of being well. That is the “-qot.”
And we added that to one of the most boring names that we thought of and didn’t use as our company name: “Applied Population Research Inc.” 🥱
And that is why we’re called Apriqot. Now if we could just figure out how it’s pronounced - ape-ricot or ah-pricot… Let us know what you think.
Proud Partners with:
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