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Understanding the incidence of disease is often crucial for public policy decision-making, as observed during the COVID-19 pandemic. Estimating incidence is challenging, however, when the definition of incidence relies on tests that imperfectly measure disease, as in the case when assays with variable performance are used to detect the SARS-CoV-2 virus. To our knowledge, there are no pragmatic methods to address the bias introduced by the performance of labs in testing for the virus. In the setting of a longitudinal study, we developed a maximum likelihood estimation-based approach to estimate laboratory performance-adjusted incidence using the expectation-maximization algorithm. We constructed confidence intervals (CIs) using both bootstrapped-based and large-sample interval estimator approaches. We evaluated our methods through extensive simulation and applied them to a real-world study (TrackCOVID), where the primary goal was to determine the incidence of and risk factors for SARS-CoV-2 infection in the San Francisco Bay Area from July 2020 to March 2021. Our simulations demonstrated that our method converged rapidly with accurate estimates under a variety of scenarios. Bootstrapped-based CIs were comparable to the large-sample estimator CIs with a reasonable number of incident cases, shown via a simulation scenario based on the real TrackCOVID study. In more extreme simulated scenarios, the coverage of large-sample interval estimation outperformed the bootstrapped-based approach. Results from the application to the TrackCOVID study suggested that assuming perfect laboratory test performance can lead to an inaccurate inference of the incidence. Our flexible, pragmatic method can be extended to a variety of disease and study settings., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

There is a public health need to understand how different frequencies of COVID-19 booster vaccines may mitigate the risk of severe COVID-19, while accounting for waning of protection and differential risk by age and immune status. By analyzing United States COVID-19 surveillance and seroprevalence data in a microsimulation model, here we show that more frequent COVID-19 booster vaccination (every 6-12 months) in older age groups and the immunocompromised population would effectively reduce the burden of severe COVID-19, while frequent boosters in the younger population may only provide modest benefit against severe disease. In persons 75+ years, the model estimated that annual boosters would reduce absolute annual risk of severe COVID-19 by 199 (uncertainty interval: 183-232) cases per 100,000 persons, compared to a one-time booster vaccination. In contrast, for persons 18-49 years, the model estimated that annual boosters would reduce this risk by 14 (10-19) cases per 100,000 persons. Those with prior infection had lower benefit of more frequent boosting, and immunocompromised persons had larger benefit. Scenarios with emerging variants with immune evasion increased the benefit of more frequent variant-targeted boosters. This study underscores the benefit of considering key risk factors to inform frequency of COVID-19 booster vaccines in public health guidance and ensuring at least annual boosters in high-risk populations., (© 2024. The Author(s).)

Background: Preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2_ infections in healthcare workers (HCWs) is critical for healthcare delivery. We aimed to estimate and characterize the prevalence and incidence of coronavirus disease 2019 (COVID-19) in a US HCW cohort and to identify risk factors associated with infection., Methods: We conducted a longitudinal cohort study of HCWs at 3 Bay Area medical centers using serial surveys and SARS-CoV-2 viral and orthogonal serological testing, including measurement of neutralizing antibodies. We estimated baseline prevalence and cumulative incidence of COVID-19. We performed multivariable Cox proportional hazards models to estimate associations of baseline factors with incident infections and evaluated the impact of time-varying exposures on time to COVID-19 using marginal structural models., Results: A total of 2435 HCWs contributed 768 person-years of follow-up time. We identified 21 of 2435 individuals with prevalent infection, resulting in a baseline prevalence of 0.86% (95% confidence interval [CI], .53%-1.32%). We identified 70 of 2414 incident infections (2.9%), yielding a cumulative incidence rate of 9.11 cases per 100 person-years (95% CI, 7.11-11.52). Community contact with a known COVID-19 case was most strongly correlated with increased hazard for infection (hazard ratio, 8.1 [95% CI, 3.8-17.5]). High-risk work-related exposures (ie, breach in protective measures) drove an association between work exposure and infection (hazard ratio, 2.5 [95% CI, 1.3-4.8). More cases were identified in HCWs when community case rates were high., Conclusions: We observed modest COVID-19 incidence despite consistent exposure at work. Community contact was strongly associated with infections, but contact at work was not unless accompanied by high-risk exposure., Competing Interests: Potential conflicts of interest . S. B. D. has received coronavirus disease 2019 (COVID-19) research funding from Gilead and the National Institutes of Health (NIH) and has served as a consultant to and received non–COVID-19 research funding from Genentech, Basilea, and the NIH. G. W. R. has received grant funding from the Centers for Disease Control and Prevention and the California Department of Public Health, has served as a consultant regarding adverse events for Moderna, and has provided expert declarations and depositions for the California Department of Justice. Y. M. has received funding from Pfizer (grants C3671008 and C4591007), the NIH (grants U54 MD010724, U54 MD010724-05S1, R21AI148810, P30AG059307, and 000522211-022), the Bill & Melinda Gates Foundation (grant OPP1113682), and the Chan Zuckerberg Foundation (grant 12089sc); has served as an advisor for and received payment or honoraria from the American Academy of Pediatrics; and has served on a data safety monitoring board for Pfizer. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2022. Published by Oxford University Press for the Infectious Diseases Society of America.)

Background: Households have emerged as important venues for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. Little is known, however, regarding the magnitude and determinants of household transmission in increasingly vaccinated populations., Methods: From September 2020 to January 2022, symptomatic nonhospitalized individuals with SARS-CoV-2 infection by RNA detection were identified within 5 days of symptom onset; all individuals resided with at least 1 other SARS-CoV-2-uninfected household member. These infected persons (cases) and their household members (contacts) were subsequently followed with questionnaire-based measurement and serial nasal specimen collection. The primary outcome was SARS-CoV-2 infection among contacts., Results: We evaluated 42 cases and their 74 household contacts. Among the contacts, 32 (43%) became infected, of whom 5 (16%) were asymptomatic; 81% of transmissions occurred by 5 days after the case's symptom onset. From 21 unvaccinated cases, 14-day cumulative incidence of SARS-CoV-2 infection among contacts was 18/40 (45% [95% confidence interval {CI}, 29%-62%]), most of whom were unvaccinated. From 21 vaccinated cases, 14-day cumulative incidence of SARS-CoV-2 infection was 14/34 (41% [95% CI, 25%-59%]) among all contacts and 12/29 (41% [95% CI, 24%-61%]) among vaccinated contacts. At least 1 comorbid condition among cases and 10 or more days of RNA detection in cases were associated with increased risk of infection among contacts., Conclusions: Among households including individuals with symptomatic SARS-CoV-2 infection, both vaccinated-to-vaccinated and unvaccinated-to-unvaccinated transmission of SARS-CoV-2 to household contacts was common. Because vaccination alone did not notably reduce risk of infection, household contacts will need to employ additional interventions to avoid infection., Competing Interests: Potential conflicts of interest. M. B. H. reports funding support from the CDC. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (Published by Oxford University Press on behalf of Infectious Diseases Society of America 2022.)

The impact of vaccination on SARS-CoV-2 infectiousness is not well understood. We compared longitudinal viral shedding dynamics in unvaccinated and fully vaccinated adults. SARS-CoV-2-infected adults were enrolled within 5 days of symptom onset and nasal specimens were self-collected daily for two weeks and intermittently for an additional two weeks. SARS-CoV-2 RNA load and infectious virus were analyzed relative to symptom onset stratified by vaccination status. We tested 1080 nasal specimens from 52 unvaccinated adults enrolled in the pre-Delta period and 32 fully vaccinated adults with predominantly Delta infections. While we observed no differences by vaccination status in maximum RNA levels, maximum infectious titers and the median duration of viral RNA shedding, the rate of decay from the maximum RNA load was faster among vaccinated; maximum infectious titers and maximum RNA levels were highly correlated. Furthermore, amongst participants with infectious virus, median duration of infectious virus detection was reduced from 7.5 days (IQR: 6.0-9.0) in unvaccinated participants to 6 days (IQR: 5.0-8.0) in those vaccinated (P = 0.02). Accordingly, the odds of shedding infectious virus from days 6 to 12 post-onset were lower among vaccinated participants than unvaccinated participants (OR 0.42 95% CI 0.19-0.89). These results indicate that vaccination had reduced the probability of shedding infectious virus after 5 days from symptom onset., Competing Interests: The authors have declared that no competing interests exist.

Access to recreational physical activities, particularly in outdoor spaces, has been a crucial outlet for physical and mental health during the COVID-19 pandemic. There is a need to understand how conducting these activities modulates the risk of SARS-CoV-2 infection. In this case-control study of unvaccinated individuals conducted in San Francisco, California, the odds of testing positive to SARS-CoV-2 were lower for those who conducted physical activity in outdoor locations (adjusted odds ratio [aOR]: 0.16, 95% confidence interval [CI]: 0.05, 0.40) in the two weeks prior to testing than for those who conducted no activity or indoor physical activity only. Individuals who visited outdoor parks, beaches, or playgrounds also had lower odds of testing positive to SARS-CoV-2 (aOR: 0.28, 95% CI: 0.11, 0.68) as compared with those who did not visit outdoor parks, beaches, or playgrounds. These findings, albeit in an unvaccinated population, offer observational data to support pre-existing ecological studies that suggest that activity in outdoor spaces lowers COVID-19 risk.

Importance: Despite widespread vaccination against COVID-19 in the United States, there are limited empirical data quantifying their public health impact in the population., Objective: To estimate the number of COVID-19 cases, hospitalizations, and deaths directly averted because of COVID-19 vaccination in California., Design, Setting, and Participants: This modeling study used person-level data provided by the California Department of Public Health (CDPH) on COVID-19 cases, hospitalizations, and deaths as well as COVID-19 vaccine administration from January 1, 2020, to October 16, 2021. A statistical model was used to estimate the number of COVID-19 cases that would have occurred in the vaccine era (November 29, 2020, to October 16, 2021) in the absence of vaccination based on the ratio of the number of cases among the unvaccinated (aged <12 years) and vaccine-eligible groups (aged ≥12 years) before vaccine introduction. Vaccine-averted COVID-19 cases were estimated by finding the difference between the projected and observed number of COVID-19 cases. Averted COVID-19 hospitalizations and deaths were assessed by applying estimated hospitalization and case fatality risks to estimates of vaccine-averted COVID-19 cases. As a sensitivity analysis, a second independent model was developed to estimate the number of vaccine-averted COVID-19 outcomes by applying published data on vaccine effectiveness to data on COVID-19 vaccine administration and estimated risk of COVID-19 over time., Exposure: COVID-19 vaccination., Main Outcomes and Measures: Number of COVID-19 cases, hospitalizations, and deaths estimated to have been averted because of COVID-19 vaccination., Results: There were 4 585 248 confirmed COVID-19 cases, 240 718 hospitalizations, and 70 406 deaths in California from January 1, 2020, to October 16, 2021, during which 27 164 680 vaccine-eligible individuals aged 12 years and older were reported to have received at least 1 dose of a COVID-19 vaccine in the vaccine era (79.5% of the eligible population). The primary model estimated that COVID-19 vaccination averted 1 523 500 (95% prediction interval [PI], 976 800-2 230 800) COVID-19 cases in California, corresponding to a 72% (95% PI, 53%-91%) relative reduction in cases because of vaccination. COVID-19 vaccination was estimated to have averted 72 930 (95% PI, 53 250-99 160) hospitalizations and 19 430 (95% PI, 14 840-26 230) deaths during the study period. The alternative model identified comparable findings., Conclusions and Relevance: This study provides evidence of the public health benefit of COVID-19 vaccination in the United States and further supports the urgency for continued vaccination.

A key public health question during any disease outbreak when limited vaccine is available is who should be prioritized for early vaccination. Most vaccine prioritization analyses only consider variation in risk of infection and death by a single risk factor, such as age. We provide a more granular approach with stratification by demographics, risk factors, and location. We use this approach to compare the impact of different COVID-19 vaccine prioritization strategies on COVID-19 cases, deaths and disability-adjusted life years (DALYs) over the first 6 months of vaccine rollout, using California as a case example. We estimate the proportion of cases, deaths and DALYs averted relative to no vaccination for strategies prioritizing vaccination by a single risk factor and by multiple risk factors (e.g. age, location). When targeting by a single risk factor, we find that age-based targeting averts the most deaths (62% for 5 million individuals vaccinated) and DALYs (38%) and targeting essential workers averts the least deaths (31%) and DALYs (24%) over the first 6 months of rollout. However, targeting by two or more risk factors simultaneously averts up to 40% more DALYs. Our findings highlight the potential value of multiple-risk-factor targeting of vaccination against COVID-19 and other infectious diseases, but must be balanced with feasibility for policy., (© 2022. The Author(s).)

Introduction: Geospatial temporal data derived from smartphones traditionally used for purposes of navigation may offer valuable information for public health surveillance and locational hot spotting. Our objective was to develop a web-based application, called Covidseeker, that captures continuous fine-grained geospatial temporal data from smartphones and leverages these data to study transmission patterns of COVID-19., Methods: This report describes the development of Covidseeker and the process by which it utilizes geospatial temporal data from smartphones and processes it into a usable format to study geospatial temporal patterns of COVID-19. We provide an overview of the design process, the principles, the software architecture, and the dashboard of the Covidseeker application and consider key challenges and strategic uses of capturing geospatial temporal data and the potential for future applications in outbreak surveillance., Results: A resource such as Covidseeker can support situational awareness by providing information about the location and timing of transmission of diseases such as COVID-19. Geospatial temporal data housed in smartphones hold tremendous potential to capture more depth about where and when transmission occurs and the patterns of human mobility that lead to increases in risk of COVID-19., Conclusion: An enormous and highly rich source of geospatial temporal information about human mobility can be used to provide highly localized discrete information that is difficult to capture by traditional sources. The architecture of Covidseeker can be applied to help track COVID-19 and should be integrated with traditional disease surveillance practices.

Background: Epidemics of COVID-19 in student populations at universities were a key concern for the 2020-2021 school year. The University of California (UC) System developed a set of recommendations to reduce campus infection rates. SARS-CoV-2 test results are summarized for the ten UC campuses during the Fall 2020 term., Methods: UC mitigation efforts included protocols for the arrival of students living on-campus students, non-pharmaceutical interventions, daily symptom monitoring, symptomatic testing, asymptomatic surveillance testing, isolation and quarantine protocols, student ambassador programs for health education, campus health and safety pledges, and lowered density of on-campus student housing. We used data from UC campuses, the UC Health-California Department of Public Health Data Modeling Consortium, and the U.S. Census to estimate the proportion of each campus' student populations that tested positive for SARS-CoV-2 and compared it to the fraction individuals aged 20-29 years who tested positive in their respective counties., Results: SARS-CoV-2 cases in campus populations were generally low in September and October 2020, but increased in November and especially December, and were highest in early to mid-January 2021, mirroring case trajectories in their respective counties. Many students were infected during the Thanksgiving and winter holiday recesses and were detected as cases upon returning to campus. The proportion of students who tested positive for SARS-CoV-2 during Fall 2020 ranged from 1.2% to 5.2% for students living on campus and was similar to students living off campus. For most UC campuses the proportion of students testing positive was lower than that for the 20-29-year-old population in which campuses were located., Conclusions: The layered mitigation approach used on UC campuses, informed by public health science and augmented perhaps by a more compliant population, likely minimized campus transmission and outbreaks and limited transmission to surrounding communities. University policies that include these mitigation efforts in Fall 2020 along with SARS-CoV-2 vaccination, may alleviate some local concerns about college students returning to communities and facilitate resumption of normal campus operations and in-person instruction., Competing Interests: No authors have competing interests

Background: Routine viral testing strategies for SARS-CoV-2 infection might facilitate safe airline travel during the COVID-19 pandemic and mitigate global spread of the virus. However, the effectiveness of these test-and-travel strategies to reduce passenger risk of SARS-CoV-2 infection and population-level transmission remains unknown., Methods: In this simulation study, we developed a microsimulation of SARS-CoV-2 transmission in a cohort of 100 000 US domestic airline travellers using publicly available data on COVID-19 clinical cases and published natural history parameters to assign individuals one of five health states of susceptible to infection, latent period, early infection, late infection, or recovered. We estimated a per-day risk of infection with SARS-CoV-2 corresponding to a daily incidence of 150 infections per 100 000 people. We assessed five testing strategies: (1) anterior nasal PCR test within 3 days of departure, (2) PCR within 3 days of departure and 5 days after arrival, (3) rapid antigen test on the day of travel (assuming 90% of the sensitivity of PCR during active infection), (4) rapid antigen test on the day of travel and PCR test 5 days after arrival, and (5) PCR test 5 days after arrival. Strategies 2 and 4 included a 5-day quarantine after arrival. The travel period was defined as 3 days before travel to 2 weeks after travel. Under each scenario, individuals who tested positive before travel were not permitted to travel. The primary study outcome was cumulative number of infectious days in the cohort over the travel period without isolation or quarantine (population-level transmission risk), and the key secondary outcome was the number of infectious people detected on the day of travel (passenger risk of infection)., Findings: We estimated that in a cohort of 100 000 airline travellers, in a scenario with no testing or screening, there would be 8357 (95% uncertainty interval 6144-12831) infectious days with 649 (505-950) actively infectious passengers on the day of travel. The pre-travel PCR test reduced the number of infectious days from 8357 to 5401 (3917-8677), a reduction of 36% (29-41) compared with the base case, and identified 569 (88% [76-92]) of 649 actively infectious travellers on the day of flight; the addition of post-travel quarantine and PCR reduced the number of infectious days to 2520 days (1849-4158), a reduction of 70% (64-75) compared with the base case. The rapid antigen test on the day of travel reduced the number of infectious days to 5674 (4126-9081), a reduction of 32% (26-38) compared with the base case, and identified 560 (86% [83-89]) actively infectious travellers; the addition of post-travel quarantine and PCR reduced the number of infectious days to 3124 (2356-495), a reduction of 63% (58-66) compared with the base case. The post-travel PCR alone reduced the number of infectious days to 4851 (3714-7679), a reduction of 42% (35-49) compared with the base case., Interpretation: Routine asymptomatic testing for SARS-CoV-2 before travel can be an effective strategy to reduce passenger risk of infection during travel, although abbreviated quarantine with post-travel testing is probably needed to reduce population-level transmission due to importation of infection when travelling from a high to low incidence setting., Funding: University of California, San Francisco., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: While risk of outdoor transmission of respiratory viral infections is hypothesized to be low, there are limited data on SARS-CoV-2 transmission in outdoor compared to indoor settings., Methods: We conducted a systematic review of peer-reviewed papers indexed in PubMed, EMBASE, and Web of Science and preprints in Europe PMC through 12 August 2020 that described cases of human transmission of SARS-CoV-2. Reports of other respiratory virus transmission were included for reference., Results: Five identified studies found a low proportion of reported global SARS-CoV-2 infections occurred outdoors (<10%) and the odds of indoor transmission was very high compared to outdoors (18.7 times; 95% confidence interval, 6.0-57.9). Five studies described influenza transmission outdoors and 2 adenovirus transmission outdoors. There was high heterogeneity in study quality and individual definitions of outdoor settings, which limited our ability to draw conclusions about outdoor transmission risks. In general, factors such as duration and frequency of personal contact, lack of personal protective equipment, and occasional indoor gathering during a largely outdoor experience were associated with outdoor reports of infection., Conclusions: Existing evidence supports the wide-held belief that risk of SARS-CoV-2 transmission is lower outdoors but there are significant gaps in our understanding of specific pathways., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)