POPULATION BIOLOGY, SOCIAL SCIENCES Correction for “Fine-scale spatial clustering of measles nonvaccination that increases outbreak potential is obscured by aggregated reporting data,” by Nina B. Masters, Marisa C. Eisenberg, Paul L. Delamater, Matthew Kay, Matthew L. Boulton, and Jon Zelner, which was first published October 26, 2020; 10.1073/pnas.2011529117 (Proc. Natl. Acad. Sci. U.S.A. 117, 28506–28514).
The authors note that Fig. 3 appeared incorrectly. The corrected figure and its legend appear below. The online version has been corrected. The authors also note that on page 28510, right column, 2nd full paragraph, “The expected outbreak size for simulations at 95% overall vaccination was predicted to be 3,886 (AR = 30.4%) cases using unaggregated data; 2,122 (AR = 16.6%) using tract-level aggregation, (45.4% reduction); 911 (AR = 7.1%) using neighborhood-level aggregation (76.5% reduction); and no secondary cases when aggregated to the quadrant level (99.9% reduction)” should instead appear as “The expected outbreak size for simulations at 95% overall vaccination was predicted to be 3,886 (AR = 30.4%) cases using unaggregated data; 2,122 (AR = 16.6%) using tract-level aggregation, (45.4% reduction); 911 (AR = 7.1%) using neighborhood-level aggregation (76.5% reduction); and 227.3 cases when aggregated to the quadrant level (94.2% reduction).” The online version has been corrected.
Fig. 3.
Impact of aggregation on estimated outbreak risk. Cumulative incidence at four different levels of vaccination coverage: 94, 95, 98, and 99%, including nonaggregated vaccination data (block-level) resolution to tract level (4-cell) resolution, to neighborhood (16 cell), and, finally, quadrant-level (64 cells) shows the reduction in estimated case burden as aggregation increases, a pattern that holds true across all levels of vaccination.