Network Evolution Stage
As the pandemic spread in each city, exponentially growing case counts, closed businesses, and stay-at-home orders revealed a dire need for PPE. A clinician in Stilton described a moment of realization in mid-March, “[The N-95 masks] weren’t coming in from the top, from the federal government… That’s when I realized that it’s gonna take a grassroots effort to be able to at least brace for the incoming surge.” Many informants in maker communities readily grasped the urgent need and prioritized expediency in their response, but they also came face to face with a scale they were ill-equipped to address. A volunteer maker in Midburg explained, “You have these institutional levels of [large hospitals] who can use in the order of 10,000 gowns in a single day. And for us, we were producing things in the order of dozens a day, one hundred a day.” Indeed, maker resources paled in comparison to the problems, and makers were small-scale, often unknown players compared to the large institutions they dealt with. Many came to see their efforts as a temporary “stop-gap” until more traditional supply chains could take over. The monthly involvement of our informants in PPE production and distribution activities illustrates the initial wave of maker response in March to June, followed by declining but continued participation by some (see Appendix C, Figure C2).
Response effectiveness. The maker networks in our cases responded rapidly to the need, launching production of cloth masks, face shields, and gowns in mid-March. This was weeks or months ahead of federal announcements that permitted emergency use authorization (EUA) for non-certified PPE (EUA dates were April 3, April 9, and May 22 for each type of PPE, respectively). Makers demonstrated their ability to produce a variety of the most urgently needed PPE and to adapt their designs based on local feedback (Dutton et al., 2006). In our data, the cumulative production in Midburg was the greatest across the widest variety of PPE types, while Edgeville produced the least amount and variety of PPE. Table 2 summarizes the quantities and types of PPE as well as the top categories of PPE recipients according to each case.
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Most makers targeted their initial PPE supplies for hospitals, which immediately presented challenges in terms of gaining permission to deliver supplies in the quantities needed. Private clinics and nursing homes were high on the list of recipients by volume of PPE received, although the targeted recipients varied between maker groups within each case. The next tier of recipients varied between cases, with the following categories uniquely emphasized by informants: first responders and food pantries (Midburg), individual citizens (Edgeville), poll workers during the U.S. election and the incarcerated population (Triport), and local schools (Stilton). Notably, informants from individual nodes did not always know where their PPE went if they relied on other parts of the network for distribution.
The lag between the initial recognition of local needs for PPE and federal EUAs exemplifies the dilemma for institutions between addressing the immediate void with non-authorized supplies of potentially unknown quality and origin or waiting for authorized supplies. Many institutions officially prohibited non-certified PPE, while others did not take an official stance. Many individual recipients and decision makers within institutions contended that “anything is better than nothing” when it came to being equipped with PPE. In our data, recipients’ opinions of the quality and usefulness of the PPE ranged from viewing it as superior to traditional supplies to viewing it as inadequate or counterproductive, although this feedback did not always reach the makers. In some cities, the negative or lukewarm response from recipients further heightened makers’ concerns about being perceived as lacking legitimacy.