Data Gaps Hamper Fight Against Pandemic
The ability of the United States to monitor outbreaks is critical in achieving effective and timely decisions before and during a public health emergency. But a recent study found that current systems to detect outbreaks at an early stage may have critical data gaps that leave out low-income communities, which are usually hardest hit by disease outbreaks.
Lead author Samuel V. Scarpino, who heads the Emergent Epidemics Lab at Northeastern University, said, “We found that the model was highly accurate for individuals who lived in neighborhoods in the upper three-fourths of income distribution, and was inaccurate for individuals who live in the lowest quartile.” Their findings cast doubt on U.S. capacity to detect an uptick infections among the most socioeconomically vulnerable populations at an early enough phase to respond.
“It's important to point out that individuals in this lowest quartile have about twice the rate of hospitalizations, so a much higher burden of disease, than do individuals in other ZIP codes,” Scarpino added, and they are less likely to have access to affordable health care services.