Estimating the Cumulative Incidence of SARS-CoV-2 Infection and the Infection Fatality Ratio in Light of Waning Antibodies

Shioda, Kayoko; Lau, Max S. Y.; Kraay, Alicia N M; Nelson, Kristin N.; Siegler, Aaron J; Sullivan, Patrick S.; Collins, Matthew H.; Weitz, Joshua S.; Lopman, Benjamin A.

doi:10.1097/ede.0000000000001361

Cited by 68 publications

(64 citation statements)

References 25 publications

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“…To estimate the cumulative incidence of SARS-CoV-2 infection through the median date of sampling (November 2, 2020), we adjusted the statewide seroprevalence estimate to account for antibody waning below a detectable level. In this analysis, we used a Bayesian model that has been previously described [ 12 ]. Briefly, it estimates the timing of infections based on (1) an external estimate of time from symptom onset to seroconversion [ 21 ], (2) estimated time from seroconversion to seroreversion from New York City [ 12 ], (3) time series data on COVID-19-related deaths reported to the CDPH through February 10, 2021, and (4) the distribution of timing of symptom onset to deaths in California.…”

Section: Methodsmentioning

confidence: 99%

“…In this analysis, we used a Bayesian model that has been previously described [ 12 ]. Briefly, it estimates the timing of infections based on (1) an external estimate of time from symptom onset to seroconversion [ 21 ], (2) estimated time from seroconversion to seroreversion from New York City [ 12 ], (3) time series data on COVID-19-related deaths reported to the CDPH through February 10, 2021, and (4) the distribution of timing of symptom onset to deaths in California. The model is calibrated with the statewide seroprevalence data estimated from this analysis.…”

Section: Methodsmentioning

confidence: 99%

“…In addition to period seroprevalence during August–December 2020, we estimated cumulative incidence, the IFR, and the percentage of infections that were reported. Given the common finding in serosurveys of waning detectable antibodies over time [ 9–11 ], we applied a model [ 12 ] to adjust the seroprevalence estimate for antibody waning.…”

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confidence: 99%

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SARS-CoV-2 Cumulative Incidence and Period Seroprevalence: Results From a Statewide Population-Based Serosurvey in California

Lamba

Bradley

Shioda

et al. 2021

Open Forum Infectious Diseases

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Background California has reported the largest number of COVID-19 cases of any U.S. state, with more than 3.5 million confirmed as of March 2021. However, the full breadth of SARS-CoV-2 transmission in California is unknown since reported cases only represent a fraction of all infections. Methods We conducted a population-based serosurvey, utilizing mailed, home-based SARS-CoV-2 antibody testing along with a demographic and behavioral survey. We weighted data from a random sample to represent the adult California population and estimated period seroprevalence overall and by participant characteristics. Seroprevalence estimates were adjusted for waning antibodies to produce statewide estimates of cumulative incidence, the infection fatality ratio (IFR), and the reported fraction. Results California’s SARS-CoV-2 weighted seroprevalence during August–December 2020 was 4.6% (95% CI: 2.8–7.4%). Estimated cumulative incidence as of November 2, 2020 was 8.7% (95% CrI: 6.4%–11.5%), indicating 2,660,441 adults (95% CrI: 1,959,218–3,532,380) had been infected. The estimated IFR was 0.8% (95% CrI: 0.6%–1.0%), and the estimated percentage of infections reported to the California Department of Public Health was 31%. Disparately high risk for infection was observed among persons of Hispanic/Latinx ethnicity and people with no health insurance and who reported working outside the home. Conclusions We present the first statewide SARS-CoV-2 cumulative incidence estimate among adults in California. As of November 2020, approximately one in three SARS-CoV-2 infections in California adults had been identified by public health surveillance. When accounting for unreported SARS-CoV-2 infections, disparities by race/ethnicity seen in case-based surveillance persist.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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SARS-CoV-2 Cumulative Incidence and Period Seroprevalence: Results From a Statewide Population-Based Serosurvey in California

Lamba

Bradley

Shioda

et al. 2021

Open Forum Infectious Diseases

Self Cite

View full text Add to dashboard Cite

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“…Although we enrolled a variety of medical professions, enrollment was based on convenience sampling and the numbers of laboratorians and physicians participating in the study are relatively low. Lastly, it is not known if the low prevalence surveyed at one PLOS ONE point in time in this study reflects low infection among the HCPs or the waning of immunity [19,20].…”

Section: Discussionmentioning

confidence: 99%

Sero-surveillance for SARS-CoV-2 infection among healthcare providers in four hospitals in Thailand one year after the first community outbreak

et al. 2021

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Background Thailand was the first country outside China to report SARS-CoV-2 infected cases. Since the detection of the first imported case on January 12th, 2020 to the time this report was written, Thailand experienced two waves of community outbreaks (March-April 2020 and December 2020-March 2021). We examined prevalence of SARS-CoV-2 seropositivity among healthcare providers (HCPs) in four hospitals approximately one year after SARS-CoV-2 first detected in Thailand. By March 2021, these hospitals have treated a total of 709 coronavirus disease 2019 (COVID-19) patients. Methods Blood specimens, collected from COVID-19 unvaccinated HCPs during January-March 2021, were tested for the presence of SARS-CoV-2 immunoglobulin G (IgG) antibodies to nucleocapsid (IgG-nucleocapsid) and spike (IgG-spike) proteins using Euroimmune® enzyme-linked immunosorbent assays. Results Of 600 HCPs enrolled, 1 (0.2%) tested positive for the SARS-CoV-2 IgG-spike antibodies, but not the IgG-nucleocapsid. Conclusion The presence of SARS-CoV-2 IgG antibodies was rare in this sample of HCPs, suggesting that this population remains susceptible to SARS-CoV-2 infection.

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“…To identify R individuals, facilities could use antibody tests, vaccination status or presume immunity within 6 months of recovery from confirmed infection. Since antibody status is maintained for an extended period of time, antibody testing could be done at a lower frequency than diagnostic testing [26].…”

Section: Testingmentioning

confidence: 99%

Modeling shield immunity to reduce COVID-19 transmission in long-term care facilities

Lucía-Sanz

Măgălie

Rodriguez-Gonzalez

et al. 2021

Preprint

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Nursing homes and other long-term care facilities in the United States have experienced severe COVID-19 outbreaks and elevated mortality rates, often following upon the inadvertent introduction of SARS-CoV-2. Following FDA emergency use approval, widespread distribution of vaccines has resulted in rapid reduction in COVID-19 cases in vulnerable, older populations. Yet, vaccination coverage remains incomplete amongst residents and healthcare workers. As such, mitigation and prevention strategies are needed to reduce the ongoing risk of transmission and mortality amongst vulnerable, nursing home populations. One such strategy is that of ′shield immunity′, in which recovered individuals increase their contact rates and therefore shield individuals who remain susceptible to infection. Here, we adapt recent population-scale shield immunity models to a network context. To do so, we evaluate network-based shield immunity by evaluating how restructured interactions in a bipartite network (e.g., between healthcare workers and long-term care residents) affects SARS-CoV-2 epidemic dynamics. First, we identify a series of rewiring principles that leverage viral testing, antibody testing, and vaccination information to reassign immunized healthcare workers to care for infected residents while retaining workload balance amidst an outbreak. We find a significant reduction in outbreak size when using infection and immune-based cohorting as a weekly intervention. Second, we also identify a preventative strategy using shield-immunity rewiring principles, by assigning susceptible healthcare workers to care for cohorts of immunized residents; this strategy reduces the risk that an inadvertent introduction of SARS-CoV-2 into the facility via a healthcare worker spreads to susceptible residents. Network-based epidemic modeling reveals that preventative rewiring can control the size of outbreaks at levels similar to that of isolation of infectious healthcare workers. Overall, this assessment of shield immunity provides further support for leveraging infection and immune status in network-based interventions to control and prevent the spread of COVID-19.

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Estimating the Cumulative Incidence of SARS-CoV-2 Infection and the Infection Fatality Ratio in Light of Waning Antibodies

Abstract: Supplemental Digital Content is available in the text.

Cited by 68 publications

References 25 publications

SARS-CoV-2 Cumulative Incidence and Period Seroprevalence: Results From a Statewide Population-Based Serosurvey in California

SARS-CoV-2 Cumulative Incidence and Period Seroprevalence: Results From a Statewide Population-Based Serosurvey in California

Sero-surveillance for SARS-CoV-2 infection among healthcare providers in four hospitals in Thailand one year after the first community outbreak

Modeling shield immunity to reduce COVID-19 transmission in long-term care facilities

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