Cumulative incidence of SARS-CoV-2 infections among adults in Georgia, USA, August-December 2020

Correcting for Antibody Waning in Cumulative Incidence Estimation From Sequential Serosurveys

Serosurveys are a widely used tool to estimate the cumulative incidence-the fraction of a population that has been infected by a given pathogen. These surveys rely on serological assays that measure the level of pathogen-specific antibodies. Because antibody levels are waning, the fraction of previously infected individuals that have seroreverted increases with time past infection. To avoid underestimating the true cumulative incidence, it is therefore essential to correct for waning antibody levels. We present an empirically supported approach for seroreversion correction in cumulative incidence estimation when sequential serosurveys are conducted in the context of a newly emerging infectious disease. The correction is based on the observed dynamics of antibody titers in seropositive cases and validated using several in silico test scenarios. Furthermore, through this approach we revise a previous cumulative incidence estimate relying on the assumption of an exponentially declining probability of seroreversion over time, of severe acute respiratory syndrome coronavirus 2, of 76% in Manaus, Brazil, by October 2020 to 47.6% (95% confidence region: 43.5-53.5). This estimate has implications, for example, for the proximity to herd immunity in Manaus in late 2020.

Use of surveillance data to elucidate household clustering of SARS-CoV-2 in Fulton County, Georgia a major metropolitan area

BACKGROUND

Households are important for SARS-CoV-2 transmission due to high intensity exposure in enclosed spaces over prolonged durations. We quantified and characterized household clustering of COVID-19 cases in Fulton County, Georgia.

METHODS

We used surveillance data to identify all confirmed COVID-19 cases in Fulton County. Household clustered cases were defined as cases with matching residential address. We described the proportion of COVID-19 cases that were clustered, stratified by age over time and explore trends in age of first diagnosed case within households and subsequent household cases.

RESULTS

Between June 1, 2020 and October 31, 2021, 31,449(37%) of 106,233 cases were clustered in households. Children were the most likely to be in household clusters than any other age group. Initially, children were rarely (∼ 10%) the first cases diagnosed in the household but increased to almost 1 of 3 in later periods.

DISCUSSION

One-third of COVID-19 cases in Fulton County were part of a household cluster. Increasingly children were the first diagnosed case, coinciding with temporal trends in vaccine roll-out among the elderly and the return to in-person schooling in Fall 2021. Limitations include restrictions to cases with a valid address and unit number and that the first diagnosed case may not be the infection source for the household.

Estimating severe acute respiratory coronavirus virus 2 (SARS-CoV-2) seroprevalence from residual clinical blood samples, January-March 2021

We describe severe acute respiratory coronavirus virus 2 (SARS-CoV-2) IgG seroprevalence and antigenemia among patients at a medical center in January-March 2021 using residual clinical blood samples. The overall seroprevalences were 17% by infection and 16% by vaccination. Spent or residual samples are a feasible alternative for rapidly estimating seroprevalence or monitoring trends in infection and vaccination.

Seroprevalence of SARS-CoV-2 antibody among urban Iranian population: findings from the second large population-based cross-sectional study

Background

The first large serosurvey in Iran found a SARS-CoV-2 antibody seroprevalence of 17.1% among the general population in the first wave of the epidemic by April, 2020. The purpose of the current study was to assess the seroprevalence of COVID-19 infection among Iranian general population after the third wave of the disease.

Methods

This population-based cross-sectional study was conducted on 7411 individuals aged ≥10 years old in 16 cities across 15 provinces in Iran between January and March, 2021. We randomly sampled individuals registered in the Iranian electronic health record system based on their national identification numbers and invited them by telephone to a healthcare center for data collection. Presence of SARS-CoV-2-specific IgG and IgM antibodies was assessed using the SARS-CoV-2 ELISA kits. The participants were also asked about their recent COVID-19-related symptoms, including cough, fever, chills, sore throat, headache, dyspnea, diarrhea, anosmia, conjunctivitis, weakness, myalgia, arthralgia, altered level of consciousness, and chest pain. The seroprevalence was estimated after adjustment for population weighting and test performance.

Results

The overall population-weighted seroprevalence adjusted for test performance was 34.2% (95% CI 31.0-37.3), with an estimated 7,667,874 (95% CI 6,950,412-8,362,915) infected individuals from the 16 cities. The seroprevalence varied between the cities, from the highest estimate in Tabriz (39.2% [95% CI 33.0-45.5]) to the lowest estimate in Kerman (16.0% [95% CI 10.7-21.4]). In the 16 cities studied, 50.9% of the seropositive individuals did not report a history of symptoms suggestive of COVID-19, implying an estimation of 3,902,948 (95% CI 3,537,760-4,256,724) asymptomatic infected individuals.

Conclusions

Nearly one in three individuals were exposed to SARS-CoV-2 in the studied cities by March 2021. The seroprevalence increased about two-fold between April, 2020, and March, 2021.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13464-7.

Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Seroprevalence in Decedents Undergoing Forensic Postmortem Examination: Feasibility for 
Real-Time Pandemic Surveillance

Background

Population-based seroprevalence studies offer comprehensive characterization of coronavirus disease 2019 (COVID-19) spread, but barriers exist and marginalized populations may not be captured. We assessed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody seroprevalence among decedents in Maryland over 6 months in 2020.

Methods

Data were collected on decedents undergoing forensic postmortem examination in Maryland from 24 May through 30 November 2020 from whom a blood specimen could be collected. Those with available blood specimens were tested with the CoronaCHEK lateral flow antibody assay. We assessed monthly seroprevalence compared to the statewide estimated number of cases and proportion of positive test results (testing positivity). We used Poisson regression with robust variance to estimate adjusted prevalence ratios (aPRs) with 95% confidence intervals (CIs) for associations of demographic characteristics, homelessness, and manner of death with SARS-CoV-2 antibodies.

Results

Among 1906 decedents, 305 (16%) were positive for SARS-CoV-2 antibodies. Monthly seroprevalence increased from 11% to 22% over time and was consistently higher than state-level estimates of testing positivity. Hispanic ethnicity was associated with 2- to 3.2-fold higher seropositivity (P < .05) irrespective of sex. Deaths due to motor vehicle crash were associated with 62% increased seropositivity (aPR, 1.62 [95% CI, 1.15–2.28]) vs natural manner of death. Though seroprevalence was lower in decedents of illicit drug overdose vs nonoverdose in early months, this shifted, and seroprevalence was comparable by November 2020.

Conclusions

Decedents undergoing forensic postmortem examination, especially those dying due to motor vehicle trauma, may be a sentinel population for COVID-19 spread in the general population and merits exploration in other states/regions.

Post-lockdown changes of age-specific susceptibility and its correlation with adherence to social distancing measures

Social distancing measures are effective in reducing overall community transmission but much remains unknown about how they have impacted finer-scale dynamics. In particular, much is unknown about how changes of contact patterns and other behaviors including adherence to social distancing, induced by these measures, may have impacted finer-scale transmission dynamics among different age groups. In this paper, we build a stochastic age-specific transmission model to systematically characterize the degree and variation of age-specific transmission dynamics, before and after lifting the lockdown in Georgia, USA. We perform Bayesian (missing-)data-augmentation model inference, leveraging reported age-specific case, seroprevalence and mortality data. We estimate that overall population-level transmissibility was reduced to 41.2% with 95% CI [39%, 43.8%] of the pre-lockdown level in about a week of the announcement of the shelter-in-place order. Although it subsequently increased after the lockdown was lifted, it only bounced back to 62% [58%, 67.2%] of the pre-lockdown level after about a month. We also find that during the lockdown susceptibility to infection increases with age. Specifically, relative to the oldest age group (> 65+), susceptibility for the youngest age group (0–17 years) is 0.13 [0.09, 0.18], and it increases to 0.53 [0.49, 0.59] for 18–44 and 0.75 [0.68, 0.82] for 45–64. More importantly, our results reveal clear changes of age-specific susceptibility (defined as average risk of getting infected during an infectious contact incorporating age-dependent behavioral factors) after the lockdown was lifted, with a trend largely consistent with reported age-specific adherence levels to social distancing and preventive measures. Specifically, the older groups (> 45) (with the highest levels of adherence) appear to have the most significant reductions of susceptibility (e.g., post-lockdown susceptibility reduced to 31.6% [29.3%, 34%] of the estimate before lifting the lockdown for the 6+ group). Finally, we find heterogeneity in case reporting among different age groups, with the lowest rate occurring among the 0–17 group (9.7% [6.4%, 19%]). Our results provide a more fundamental understanding of the impacts of stringent lockdown measures, and finer evidence that other social distancing and preventive measures may be effective in reducing SARS-CoV-2 transmission. These results may be exploited to guide more effective implementations of these measures in many current settings (with low vaccination rate globally and emerging variants) and in future potential outbreaks of novel pathogens.