RNRamya Naraharisetti

Ramya Naraharisetti

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Ramya Naraharisetti has a total of 16 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Timing of Infection as a Key Driver of Racial/Ethnic Disparities in Coronavirus Disease 2019 Mortality Rates During the Prevaccine Period

    by Ramya Naraharisetti, Rob Trangucci, Krzysztof Sakrejda, Nina B Masters, Ryan Malosh, Emily T Martin, Marisa Eisenberg, Bruce Link, Joseph N S Eisenberg, Jon Zelner

    Disparities in coronavirus disease 2019 mortality are driven by inequalities in group-specific incidence rates (IRs), case fatality rates (CFRs), and their interaction. For emerging infections, such as severe acute respiratory syndrome coronavirus 2, group-specific IRs and CFRs change on different time scales, and inequities in these measures may reflect different social and medical mechanisms. To be useful tools for public health surveillance and policy, analyses of changing mortality rate disparities must independently address changes in IRs and CFRs. However, this is rarely done. In this analysis, we examine the separate contributions of disparities in the timing of infection—reflecting differential infection risk factors such as residential segregation, housing, and participation in essential work—and declining CFRs over time on mortality disparities by race/ethnicity in the US state of Michigan. We used detailed case data to decompose race/ethnicity-specific mortality rates into their age-specific IR and CFR components during each of 3 periods from March to December 2020. We used these estimates in a counterfactual simulation model to estimate that that 35% (95% credible interval, 30%–40%) of deaths in black Michigan residents could have been prevented if these residents were infected along the timeline experienced by white residents, resulting in a 67% (61%–72%) reduction in the mortality rate gap between black and white Michigan residents during 2020. These results clearly illustrate why differential power to “wait out” infection during an infectious disease emergency—a function of structural racism—is a key, underappreciated, driver of inequality in disease and death from emerging infections.

  • Invited Commentary: To Make Long-Term Gains Against Infection Inequity, Infectious Disease Epidemiology Needs to Develop a More Sociological Imagination

    by Jon Zelner, Ramya Naraharisetti, Sarah Zelner

    In a recent article in the Journal, Noppert et al. (Am J Epidemiol. 2023;192(3):475–482) articulated in detail the mechanisms connecting high-level “fundamental social causes” of health inequity to inequitable infectious disease outcomes, including infection, severe disease, and death. In this commentary, we argue that while intensive focus on intervening mechanisms is welcome and necessary, it cannot occur in isolation from examination of the way that fundamental social causes—including racism, socioeconomic inequity, and social stigma—sustain infection inequities even when intervening mechanisms are addressed. We build on the taxonomy of intervening mechanisms laid out by Noppert et al. to create a road map for strengthening the connection between fundamental cause theory and infectious disease epidemiology and discuss its implications for future research and intervention.


  • Open Access

    Racial disparities in COVID-19 mortality are driven by unequal infection risks

    by Jon Zelner, Rob Trangucci, Ramya Naraharisetti, Alex Cao, Ryan Malosh, Kelly Broen, Nina Masters, Paul Delamater

    Background: As of August 5, 2020, there were more than 4.8M confirmed and probable cases and 159K deaths attributable to SARS-CoV-2 in the United States, with these numbers undoubtedly reflecting a significant underestimate of the true toll. Geographic, racial-ethnic, age and socioeconomic disparities in exposure and mortality are key features of the first and second wave of the U.S. COVID-19 epidemic. Methods: We used individual-level COVID-19 incidence and mortality data from the U.S. state of Michigan to estimate age-specific incidence and mortality rates by race/ethnic group. Data were analyzed using hierarchical Bayesian regression models, and model results were validated using posterior predictive checks. Findings: In crude and age-standardized analyses we found rates of incidence and mortality more than twice as high than Whites for all groups other than Native Americans. Of these, Blacks experienced the greatest burden of confirmed and probable COVID-19 infection (Age-standardized incidence = 1,644/100,000 population) and mortality (age-standardized mortality rate 251/100,000). These rates reflect large disparities, as Blacks experienced age-standardized incidence and mortality rates 5.6 (95% CI = 5.5, 5.7) and 6.9 (6.5, 7.3) times higher than Whites, respectively. We also found that the bulk of the disparity in mortality between Blacks and Whites is driven by dramatically higher rates of COVID-19 infection across all age groups, particularly among older adults, rather than age-specific variation in case-fatality rates. Interpretation: This work suggests that well-documented racial disparities in COVID-19 mortality in hard-hit settings, such as the U.S. state of Michigan, are driven primarily by variation in household, community and workplace exposure rather than case-fatality rates. Funding: This work was supported by a COVID-PODS grant from the Michigan Institute for Data Science (MIDAS) at the University of Michigan. The funding source had no role in the preparation of this manuscript.