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Goldstein, Edward

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Goldstein

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Goldstein, Edward
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    Depletion-of-susceptibles bias in influenza vaccine waning studies: how to ensure robust results
    (Cambridge University Press, 2019-08-12) Lipsitch, Marc; Goldstein, Edward; Ray, G. Thomas; Fireman, Bruce
    Vaccine effectiveness (VE) studies are subject to biases due to depletion of at-risk persons or of highly susceptible persons at different rates from different groups (depletion-of-susceptibles bias), a problem that can also lead to biased estimates of waning effectiveness, including spurious inference of waning when none exists. An alternative study design to identify waning is to study only vaccinated persons, and compare for each day the incidence in persons with earlier or later dates of vaccination. Prior studies suggested under what conditions this alternative would yield correct estimates of waning. Here we define the depletion-of-susceptibles process formally and show mathematically that for influenza vaccine waning studies, a randomized trial or corresponding observational study that compares incidence at a specific calendar time among individuals vaccinated at different times before the influenza season begins will not be vulnerable depletion-of-susceptibles bias in its inference of waning under the null hypothesis that none exists, and will - if waning does actually occur - underestimate the extent of waning. Such a design is thus robust in the sense that a finding of waning in that inference framework reflects actual waning of vaccine-induced immunity. We recommend such a design for future studies of waning, whether observational or randomized.
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    Estimating the hospitalization burden associated with influenza and respiratory syncytial virus in New York City, 2003–2011
    (John Wiley & Sons, Ltd, 2015) Goldstein, Edward; Greene, Sharon K; Olson, Donald R; Hanage, William; Lipsitch, Marc
    Background: Hospitalization burden associated with influenza and respiratory syncytial virus (RSV) is uncertain due to ambiguity in the inference methodologies employed for its estimation. Objectives: Utilization of a new method to quantitate the above burden. Methods: Weekly hospitalization rates for several principal diagnoses from 2003 to 2011 in New York City by age group were regressed linearly against incidence proxies for the major influenza subtypes and RSV adjusting for temporal trends and seasonal baselines. Results: Average annual rates of influenza-associated respiratory hospitalizations per 100 000 were estimated to be 129 [95% CI (79, 179)] for age <1, 36·3 (21·6, 51·4) for ages 1–4, 10·6 (7·5, 13·7) for ages 5–17, 25·6 (21·3, 29·8) for ages 18–49, 65·5 (54·0, 76·9) for ages 50–64, 125 (105, 147) for ages 65–74, and 288 (244, 331) for ages ≥75. Additionally, influenza had a significant contribution to hospitalization rates with a principal diagnosis of septicemia for ages 5–17 [0·76 (0·1, 1·4)], 18–49 [1·02 (0·3, 1·7)], 50–64 [4·0 (1·7, 6·3)], 65–74 [8·8 (2·2, 15·6)], and ≥75 [38·7 (25·7, 52·9)]. RSV had a significant contribution to the rates of respiratory hospitalizations for age <1 [1900 (1740, 2060)], ages 1–4 [117 (70, 167)], and ≥75 [175 (44, 312)] [including chronic lower respiratory disease, 90 (43, 140)] as well as pneumonia & influenza hospitalizations for ages 18–49 [6·2 (1·1, 11·3)] and circulatory hospitalizations for ages ≥75 [199 (13, 375)]. Conclusions: The high burden of RSV hospitalizations among young children and seniors age ≥75 suggests the need for additional control measures such as vaccination to mitigate the impact of annual RSV epidemics. Our estimates for influenza-associated hospitalizations provide further evidence of the burden of morbidity associated with influenza, supporting current guidelines regarding influenza vaccination and antiviral treatment.
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    Population effect of influenza vaccination under co-circulation of non-vaccine variants and the case for a bivalent A/H3N2 vaccine component
    (Elsevier BV, 2017) Worby, Colin; Wallinga, Jacco; Lipsitch, Marc; Goldstein, Edward
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    Temporally Varying Relative Risks for Infectious Diseases
    (Ovid Technologies (Wolters Kluwer Health), 2017) Goldstein, Edward; Pitzer, Virginia E.; O’Hagan, Justin J.; Lipsitch, Marc
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    Examining the role of different age groups, and of vaccination during the 2012 Minnesota pertussis outbreak
    (Nature Publishing Group, 2015) Worby, Colin; Kenyon, Cynthia; Lynfield, Ruth; Lipsitch, Marc; Goldstein, Edward
    There is limited information on the roles of different age groups during pertussis outbreaks. Little is known about vaccine effectiveness against pertussis infection (both clinically apparent and subclinical), which is different from effectiveness against reportable pertussis disease, with the former influencing the impact of vaccination on pertussis transmission in the community. For the 2012 pertussis outbreak in Minnesota, we estimated odds ratios for case counts in pairs of population groups before vs. after the epidemic’s peak. We found children aged 11–12y, 13–14y and 8–10y experienced the greatest rates of depletion of susceptible individuals during the outbreak’s ascent, with all ORs for each of those age groups vs. groups outside this age range significantly above 1, with the highest ORs for ages 11–12y. Receipt of the fifth dose of DTaP was associated with a decreased relative role during the outbreak’s ascent compared to non-receipt [OR 0.16 (0.01, 0.84) for children aged 5, 0.13 (0.003, 0.82) for ages 8–10y, indicating a protective effect of DTaP against pertussis infection. No analogous effect of Tdap was detected. Our results suggest that children aged 8–14y played a key role in propagating this outbreak. The impact of immunization with Tdap on pertussis infection requires further investigation.
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    Estimating Incidence Curves of Several Infections Using Symptom Surveillance Data
    (Public Library of Science, 2011) Goldstein, Edward; Cowling, Benjamin J.; Aiello, Allison E.; Takahashi, Saki; King, Gary; Lu, Ying; Lipsitch, Marc
    We introduce a method for estimating incidence curves of several co-circulating infectious pathogens, where each infection has its own probabilities of particular symptom profiles. Our deconvolution method utilizes weekly surveillance data on symptoms from a defined population as well as additional data on symptoms from a sample of virologically confirmed infectious episodes. We illustrate this method by numerical simulations and by using data from a survey conducted on the University of Michigan campus. Last, we describe the data needs to make such estimates accurate.
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    Excess mortality impact of two epidemics of pandemic influenza A(H1N1pdm09) virus in Hong Kong
    (Blackwell Publishing Ltd, 2013) Wu, Peng; Goldstein, Edward; Ho, Lai-Ming; Wu, Joseph T; Tsang, Thomas; Leung, Gabriel M; Cowling, Benjamin J
    Hong Kong experienced two large epidemics of pandemic influenza A(H1N1pdm09). We used regression methods to estimate the excess mortality associated with each epidemic. The first epidemic of H1N1pdm09 peaked in September 2009 and was associated with 2·13 [95% confidence interval (CI): −8·08, 11·82] excess all-cause deaths per 100 000 population. The second epidemic of H1N1pdm09 in early 2011 was associated with 4·72 [95% CI: −0·70, 10·50] excess deaths per 100 000 population. More than half of the estimated excess all-cause deaths were attributable to respiratory causes in each epidemic. The reasons for substantial impact in the second wave remain to be clarified.
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    Predicting the Epidemic Sizes of Influenza A/H1N1, A/H3N2, and B: A Statistical Method
    (Public Library of Science (PLoS), 2011) Goldstein, Edward; Cobey, Sarah; Takahashi, Saki; Miller, Joel C.; Lipsitch, Marc
    BACKGROUND: The epidemic sizes of influenza A/H3N2, A/H1N1, and B infections vary from year to year in the United States. We use publicly available US Centers for Disease Control (CDC) influenza surveillance data between 1997 and 2009 to study the temporal dynamics of influenza over this period. METHODS AND FINDINGS: Regional outpatient surveillance data on influenza-like illness (ILI) and virologic surveillance data were combined to define a weekly proxy for the incidence of each strain in the United States. All strains exhibited a negative association between their cumulative incidence proxy (CIP) for the whole season (from calendar week 40 of each year to calendar week 20 of the next year) and the CIP of the other two strains (the complementary CIP) from the start of the season up to calendar week 2 (or 3, 4, or 5) of the next year. We introduce a method to predict a particular strain's CIP for the whole season by following the incidence of each strain from the start of the season until either the CIP of the chosen strain or its complementary CIP exceed certain thresholds. The method yielded accurate predictions, which generally occurred within a few weeks of the peak of incidence of the chosen strain, sometimes after that peak. For the largest seasons in the data, which were dominated by A/H3N2, prediction of A/H3N2 incidence always occurred at least several weeks in advance of the peak. CONCLUSION: Early circulation of one influenza strain is associated with a reduced total incidence of the other strains, consistent with the presence of interference between subtypes. Routine ILI and virologic surveillance data can be combined using this new method to predict the relative size of each influenza strain's epidemic by following the change in incidence of a given strain in the context of the incidence of cocirculating strains. Please see later in the article for the Editors' Summary.
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    Reconstructing influenza incidence by deconvolution of daily mortality time series
    (Proceedings of the National Academy of Sciences, 2009) Goldstein, Edward; Dushoff, J.; Ma, Junling; Plotkin, J. B.; Earn, D. J. D.; Lipsitch, Marc
    We propose a mathematically straightforward method to infer the incidence curve of an epidemic from a recorded daily death curve and time-to-death distribution; the method is based on the Richardson-Lucy deconvolution scheme from optics. We apply the method to reconstruct the incidence curves for the 1918 influenza epidemic in Philadelphia and New York State. The incidence curves are then used to estimate epidemiological quantities, such as daily reproductive numbers and infectivity ratios. We found that during a brief period before the official control measures were implemented in Philadelphia, the drop in the daily number of new infections due to an average infector was much larger than expected from the depletion of susceptibles during that period; this finding was subjected to extensive sensitivity analysis. Combining this with recorded evidence about public behavior, we conclude that public awareness and change in behavior is likely to have had a major role in the slowdown of the epidemic even in a city whose response to the 1918 influenza epidemic is considered to have been among the worst in the U.S.
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    Pre-dispensing of antivirals to high-risk individuals in an influenza pandemic
    (Wiley-Blackwell, 2010) Goldstein, Edward; Miller, Joel C.; O’Hagan, Justin J.; Lipsitch, Marc
    We consider the net benefits of pre-dispensing antivirals to high-risk individuals during an influenza pandemic, where the measure of the benefit is the number of severe outcomes (such as deaths or hospitalizations) prevented by antivirals in the whole population. One potential benefit of pre-dispensing is that individuals to whom antivirals have been pre-dispensed may be able to initiate treatment earlier than if they had to wait to obtain and fill a prescription, reducing their risk of progression to severe disease. If this benefit exceeds the side effects of misuse for the category of individuals to whom antivirals were pre-dispensed, and if antiviral supply exceeds overall population demand (which appears relevant for several countries including US in the 2009 H1N1 pandemic), pre-dispensing a quantity of antivirals not exceeding the difference between supply and demand is always beneficial. In this study, we consider the net benefits of pre-dispensing antivirals under various scenarios, including demand exceeding supply, and derive mathematical conditions under which antiviral pre-dispensing is advantageous on balance. For individuals whose relative risk of severe outcome is high enough, such as immunosuppressed individuals (particularly children) and possibly individuals with neurological disorders, pre-dispensing is always beneficial at a given level of antiviral stockpile with modest assumptions on the relative benefit of early treatment by a pre-dispensed course, regardless of the overall population demand for antivirals during the course of an epidemic. Making additional assumptions on either the overall population demand for antivirals (which appear relevant for the 2009 H1N1 pandemic) or on the relative benefit of pre-dispensing would make pre-dispensing net beneficial with inclusion of a larger number of persons such as pregnant women and morbidly obese adults.