Education & Certifications


  • MPH, University of California, Berkeley, Epidemiology and Biostatistics (2021)
  • BA, University of California, Berkeley, Public Health and Data Science (2020)

All Publications


  • City-wide school-located influenza vaccination: A retrospective cohort study. Vaccine Benjamin-Chung, J., Arnold, B. F., Mishra, K., Kennedy, C. J., Nguyen, A., Pokpongkiat, N. N., Djajadi, S., Seth, A., Klein, N. P., Hubbard, A. E., Reingold, A., Colford, J. M. 2021

    Abstract

    BACKGROUND: We measured the effectiveness of a city-wide school-located influenza vaccination (SLIV) program implemented in over 102 elementary schools in Oakland, California.METHODS: We conducted a retrospective cohort study among Kaiser Permanente Northern California (KPNC) members of all ages residing in either the intervention or a multivariate-matched comparison site from September 2011 - August 2017. Outcomes included medically attended acute respiratory illness (MAARI), influenza hospitalization, and Oseltamivir prescriptions. We estimated difference-in-differences (DIDs) in 2014-15, 2015-16, and 2016-17 using generalized linear models and adjusted for race, ethnicity, age, sex, health plan, and language.RESULTS: Pre-intervention member characteristics were similar between sites. The proportion of KPNC members vaccinated for influenza by KPNC or the SLIV program was 8-11% higher in the intervention site than the comparison site during the intervention period. Among school-aged children, SLIV was associated with lower Oseltamivir prescriptions per 1,000 (DIDs: -3.5 (95% CI -5.5, -1.5) in 2015-16; -4.0 (95% CI -6.5, -1.6) in 2016-17) but not with other outcomes. SLIV was associated with lower MAARI per 1,000 in adults 65+years (2014-15: -13.2, 95% CI -23.2, -3.2; 2015-16: -21.5, 95% CI -31.1, -11.9; 2016-17: -13.0, 95% CI -23.2, -2.9). There were few significant associations with other outcomes among adults.CONCLUSIONS: A city-wide SLIV intervention was associated with higher influenza vaccination coverage, lower Oseltamivir prescriptions in school-aged children, and lower MAARI among people over 65years, suggesting possible indirect effects of SLIV among older adults.

    View details for DOI 10.1016/j.vaccine.2021.08.099

    View details for PubMedID 34535312

  • Evaluation of a city-wide school-located influenza vaccination program in Oakland, California, with respect to vaccination coverage, school absences, and laboratory-confirmed influenza: A matched cohort study PLOS MEDICINE Benjamin-Chung, J., Arnold, B. F., Kennedy, C. J., Mishra, K., Pokpongkiat, N., Nguyen, A., Jilek, W., Holbrook, K., Pan, E., Kirley, P. D., Libby, T., Hubbard, A. E., Reingold, A., Colford, J. M. 2020; 17 (8): e1003238

    Abstract

    It is estimated that vaccinating 50%-70% of school-aged children for influenza can produce population-wide indirect effects. We evaluated a city-wide school-located influenza vaccination (SLIV) intervention that aimed to increase influenza vaccination coverage. The intervention was implemented in ≥95 preschools and elementary schools in northern California from 2014 to 2018. Using a matched cohort design, we estimated intervention impacts on student influenza vaccination coverage, school absenteeism, and community-wide indirect effects on laboratory-confirmed influenza hospitalizations.We used a multivariate matching algorithm to identify a nearby comparison school district with pre-intervention characteristics similar to those of the intervention school district and matched schools in each district. To measure student influenza vaccination, we conducted cross-sectional surveys of student caregivers in 22 school pairs (2017 survey, N = 6,070; 2018 survey, N = 6,507). We estimated the incidence of laboratory-confirmed influenza hospitalization from 2011 to 2018 using surveillance data from school district zip codes. We analyzed student absenteeism data from 2011 to 2018 from each district (N = 42,487,816 student-days). To account for pre-intervention differences between districts, we estimated difference-in-differences (DID) in influenza hospitalization incidence and absenteeism rates using generalized linear and log-linear models with a population offset for incidence outcomes. Prior to the SLIV intervention, the median household income was $51,849 in the intervention site and $61,596 in the comparison site. The population in each site was predominately white (41% in the intervention site, 48% in the comparison site) and/or of Hispanic or Latino ethnicity (26% in the intervention site, 33% in the comparison site). The number of students vaccinated by the SLIV intervention ranged from 7,502 to 10,106 (22%-28% of eligible students) each year. During the intervention, influenza vaccination coverage among elementary students was 53%-66% in the comparison district. Coverage was similar between the intervention and comparison districts in influenza seasons 2014-2015 and 2015-2016 and was significantly higher in the intervention site in seasons 2016-2017 (7%; 95% CI 4, 11; p < 0.001) and 2017-2018 (11%; 95% CI 7, 15; p < 0.001). During seasons when vaccination coverage was higher among intervention schools and the vaccine was moderately effective, there was evidence of statistically significant indirect effects: The DID in the incidence of influenza hospitalization per 100,000 in the intervention versus comparison site was -17 (95% CI -30, -4; p = 0.008) in 2016-2017 and -37 (95% CI -54, -19; p < 0.001) in 2017-2018 among non-elementary-school-aged individuals and -73 (95% CI -147, 1; p = 0.054) in 2016-2017 and -160 (95% CI -267, -53; p = 0.004) in 2017-2018 among adults 65 years or older. The DID in illness-related school absences per 100 school days during the influenza season was -0.63 (95% CI -1.14, -0.13; p = 0.014) in 2016-2017 and -0.80 (95% CI -1.28, -0.31; p = 0.001) in 2017-2018. Limitations of this study include the use of an observational design, which may be subject to unmeasured confounding, and caregiver-reported vaccination status, which is subject to poor recall and low response rates.A city-wide SLIV intervention in a large, diverse urban population was associated with a decrease in the incidence of laboratory-confirmed influenza hospitalization in all age groups and a decrease in illness-specific school absence rate among students in 2016-2017 and 2017-2018, seasons when the vaccine was moderately effective, suggesting that the intervention produced indirect effects. Our findings suggest that in populations with moderately high background levels of influenza vaccination coverage, SLIV programs are associated with further increases in coverage and reduced influenza across the community.

    View details for DOI 10.1371/journal.pmed.1003238

    View details for Web of Science ID 000563452200004

    View details for PubMedID 32810149

    View details for PubMedCentralID PMC7433855

  • Substantial underestimation of SARS-CoV-2 infection in the United States. Nature communications Wu, S. L., Mertens, A. N., Crider, Y. S., Nguyen, A. n., Pokpongkiat, N. N., Djajadi, S. n., Seth, A. n., Hsiang, M. S., Colford, J. M., Reingold, A. n., Arnold, B. F., Hubbard, A. n., Benjamin-Chung, J. n. 2020; 11 (1): 4507

    Abstract

    Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic response. Confirmed COVID-19 case counts in the U.S. do not capture the total burden of the pandemic because testing has been primarily restricted to individuals with moderate to severe symptoms due to limited test availability. Here, we use a semi-Bayesian probabilistic bias analysis to account for incomplete testing and imperfect diagnostic accuracy. We estimate 6,454,951 cumulative infections compared to 721,245 confirmed cases (1.9% vs. 0.2% of the population) in the United States as of April 18, 2020. Accounting for uncertainty, the number of infections during this period was 3 to 20 times higher than the number of confirmed cases. 86% (simulation interval: 64-99%) of this difference is due to incomplete testing, while 14% (0.3-36%) is due to imperfect test accuracy. The approach can readily be applied in future studies in other locations or at finer spatial scale to correct for biased testing and imperfect diagnostic accuracy to provide a more realistic assessment of COVID-19 burden.

    View details for DOI 10.1038/s41467-020-18272-4

    View details for PubMedID 32908126

    View details for PubMedCentralID PMC7481226