Ryan E. Wiegand

Background: Use of rapid diagnostic tests (RDTs) may bias vaccine effectiveness (VE) estimates from test-negative design (TND) studies. We conducted individual-level simulations using national, US COVID-19 surveillance data to assess potential bias at varying likelihoods of visiting a healthcare facility and prevalence of RDT use. Methods: Twenty-one scenarios that varied the probabilities of visiting a healthcare facility and RDT use by vaccination status were simulated. VE was calculated as 100 × (1 − odds ratio), comparing the odds of symptomatic SARS-CoV-2 infection between vaccinated and unvaccinated groups of people. VE estimates were compared to VE estimates from simulations without RDT testing to calculate the bias in percentage points (pp). Results: VE was underestimated when either vaccinated people were more likely (probability of .5) than unvaccinated people (probability of .3) to visit a healthcare facility after a positive RDT [−5.8%age points (pp); 95% uncertainty interval (UI): −9.1, −2.4] or unvaccinated people were more likely than vaccinated people to visit a healthcare facility after a negative RDT (bias = −6.1 pp; UI: −9.9, −2.5). Conversely, VE was overestimated when either vaccinated people were more likely than unvaccinated people to visit a healthcare facility after a negative RDT (bias = 5.2; UI: 2.4, 7.7) or unvaccinated people were more likely than vaccinated people to visit a healthcare facility after a positive RDT (bias = 8.4 pp; UI: 5.6, 11.3). Conclusion: VE estimates against symptomatic SARS-CoV-2 infection from a TND may be under- or overestimated, depending on differences in RDT usage between vaccination groups.

Vaccination can be a useful intervention for reducing infectious disease burden. Estimating numbers of vaccine-prevented health outcomes is one approach to quantifying the benefits of vaccination. Here we improve a method described by Foppa et al. (1) that assumes vaccination has only direct effects, that is, it cannot prevent infection or onward transmission of the disease. We rederive this method and derive an improved method that increases estimation accuracy with minimal additional analytical complexity. To evaluate the improved method, we simulated disease outbreaks and compared the accuracy of the two methods for estimating prevented disease outcomes. In 84% of simulations performed over a wide parameter space, the improved method had an equal or smaller estimation error compared to the original Foppa method, with 7.9-fold smaller mean error and 44-fold smaller standard deviation of errors. Our study improves a method for estimating prevented burden when assuming vaccination has only direct effects.

Objective: Nursing home residents have been disproportionately impacted by respiratory virus-related morbidity and mortality due to inherent vulnerability and communal living environments. This study aims to identify nursing homes with higher infection rates during a period of intense SARS-CoV-2 transmission and explore facility-level characteristics potentially associated with infection surges. Design: A longitudinal k-means clustering approach followed by exploratory regression analyses. Setting: U.S. Nursing homes reporting to the Centers for Disease Control and Prevention’s National Healthcare Safety Network (NHSN). Methods: A longitudinal k-means method (kmlShape) classified the facilities based on their weekly SARS-CoV-2 incidence rate epidemic curve, identifying two categories (low vs high infection peak) based on the magnitude of infection peaks. A logistic regression model with bootstrapping was developed to assess facility characteristics associated with higher SARS-CoV-2 infection surges. Results: Among 11,990 nursing homes analyzed, 9,058 were classified as having a low infection peak, while 2,932 had a high infection peak. Nursing homes that are for-profit (OR = 1.570, 95% bootstrap confidence interval [BCI] 1.441–1.807), with high staff turnover (OR = 1.292, 95% BCI 1.154–1.451), or located in areas with higher social vulnerability (OR = 1.457, 95% BCI 1.239–1.880) were more likely to experience high infection peaks. Nursing homes with higher residents’ vaccination coverage (OR = .321, 95% BCI .248–.380) and located in urban areas were less likely to experience high infection peaks. Conclusions: The facility-level characteristics associated with lower SARS-CoV-2 infection peaks may indicate resiliency and help evaluate the capacity of nursing homes to endure stressors such as respiratory viruses and other communicable illnesses.

Background: Malaria prevalence data are not collected with the resolution or frequency required to tailor malaria control interventions to the local level. Routine malaria test-positivity data from screening pregnant women attending antenatal clinics (ANC) has been shown to correlate with sub-national malaria prevalence estimates obtained via household surveys. This approach may become increasingly important given uncertainty around funding for traditional survey platforms such as Demographic Health Surveys (DHS). We assessed whether rapid diagnostic test (RDT) results from ANC screening correlated with monthly malaria prevalence data from all-age household surveys in health facility catchment areas in western Kenya.Methods: Monthly likelihood of malaria RDT test-positivity among women attending their first ANC visit was compared to RDT results from community-based, all-age, year-round continuous malaria indicator household surveys (cMIS) in the same catchment area. Statistical models were used to associate monthly facility-catchment odds of RDT positivity from the ANC data, accounting for gravidity, with odds of positivity from cMIS data.Findings: From January 2016 to December 2021, 6,994 pregnant women attending ANC and 11,525 participants aged ≥1 month from cMIS contributed to the analysis. A model assuming a constant odds ratio between ANC test-positivity and cMIS prevalence identified malaria dynamics across the study area, including declines after long-lasting insecticidal net distributions and increases in prevalence during COVID-19-related disruptions.Interpretation: In addition to indicating malaria infection in pregnancy, monthly ANC-based screening data were associated with malaria RDT prevalence in surrounding communities. This suggests the potential to use test-positivity data from pregnant women attending ANC for tracking community-level malaria dynamics at finer spatial scales than previously achieved. The continuity of ANC screening during the pandemic highlights its potential as a resilient surveillance tool to monitor changes in transmission in near-real-time at higher resolution than currently feasible through prevalence surveys, especially amid reductions to global funding for such platforms.

We evaluated effectiveness of respiratory syncytial virus (RSV) vaccines against RSV-associated thromboembolic events among community-dwelling Medicare fee-for-service beneficiaries >65 years of age in the United States enrolled during October 1, 2023-March 30, 2024. RSV vaccines protected against RSV-associated thromboembolic events (effectiveness 79% [95% CI 74%-83%]) in the same season as vaccine receipt.

Objective: To assess differences in SARS-CoV-2 infection rates between patients receiving hemodialysis in outpatient centers (in-center) and those receiving dialysis in their homes (hemodialysis and peritoneal dialysis) from December 29, 2020, through May 9, 2023. Design: Retrospective cohort study. Setting: Outpatient dialysis facilities in the United States reporting to the Centers for Disease Control and Prevention’s National Healthcare Safety Network. Patients: Maintenance dialysis patients that received hemodialysis treatment at or were affiliated with outpatient dialysis facilities. Methods: SARS-CoV-2 infection rates were assessed by dialysis setting (in-center and home). Weeks were categorized as surge (rate of infection > median) and non-surge (rate of infection ≤ median) and by variant predominance. A negative binomial regression model with generalized estimating equations was constructed to examine differences in rates of infection among patients. Results: A total of 7,974 dialysis facilities reported 171,338 SARS-CoV-2 infections among patients. In-center hemodialysis patients had higher average rates of SARS-CoV-2 infection at 2.85 infections per 1000 patient-weeks than home patients at 1.69 infections per 1000 patient-weeks. During surge weeks, the differences in rates of infection between in-center and home patients were more pronounced than during non-surge weeks for all variant predominance categories: Delta (relative rate ratio (RRR) = 1.20, CI: 1.09–1.32), B.1 and Other (RRR = 1.11, CI: 1.02–1.22), and Omicron (RRR = 1.07, CI: 1.01–1.12). Conclusion: Rates of SARS-CoV-2 infection among patients receiving outpatient hemodialysis were persistently higher than rates among patients receiving dialysis treatments at home; these differences were more pronounced during surge weeks.

Background: Real-world COVID-19 vaccine effectiveness (VE) studies are investigating exposures of increasing complexity accounting for time since vaccination. These studies require methods that adjust for the confounding that arises when morbidities and demographics are associated with vaccination and the risk of outcome events. Methods based on propensity scores (PS) are well-suited to this when the exposure is dichotomous, but present challenges when the exposure is multinomial. Objective: This simulation study aimed to investigate alternative methods to adjust for confounding in VE studies that have a test-negative design. Methods: Adjustment for a disease risk score (DRS) is compared with multivariable logistic regression. Both stratification on the DRS and direct covariate adjustment of the DRS are examined. Multivariable logistic regression with all the covariates and with a limited subset of key covariates is considered. The performance of VE estimators is evaluated across a multinomial vaccination exposure in simulated datasets. Results: Bias in VE estimates from multivariable models ranged from –5.3% to 6.1% across 4 levels of vaccination. Standard errors of VE estimates were unbiased, and 95% coverage probabilities were attained in most scenarios. The lowest coverage in the multivariable scenarios was 93.7% (95% CI 92.2%-95.2%) and occurred in the multivariable model with key covariates, while the highest coverage in the multivariable scenarios was 95.3% (95% CI 94.0%-96.6%) and occurred in the multivariable model with all covariates. Bias in VE estimates from DRS-adjusted models was low, ranging from –2.2% to 4.2%. However, the DRS-adjusted models underestimated the standard errors of VE estimates, with coverage sometimes below the 95% level. The lowest coverage in the DRS scenarios was 87.8% (95% CI 85.8%-89.8%) and occurred in the direct adjustment for the DRS model. The highest coverage in the DRS scenarios was 94.8% (95% CI 93.4%-96.2%) and occurred in the model that stratified on DRS. Although variation in the performance of VE estimates occurred across modeling strategies, variation in performance was also present across exposure groups. Conclusions: Overall, models using a DRS to adjust for confounding performed adequately but not as well as the multivariable models that adjusted for covariates individually.

Background: Understanding protection against SARS-CoV-2 infection by vaccine and hybrid immunity is important for informing public health strategies as new variants emerge. Methods: We analyzed data from 3 cohort studies spanning 1 September 2022 to 31 July 2023 to estimate COVID-19 vaccine effectiveness (VE) against SARS-CoV-2 infection and symptomatic COVID-19 among adults with and without prior infection in the United States. Participants collected weekly nasal swabs irrespective of symptoms, participated in annual blood draws, and completed periodic surveys, which included vaccination status and infection history. Swabs were tested molecularly for SARS-CoV-2. VE was estimated by Cox proportional hazards models for the hazard ratios of infections, adjusting for covariates. VE was calculated considering prior infection and recency of vaccination. Results: Among 3344 adults, the adjusted VE of a bivalent vaccine against infection was 37.2% (95% CI, 12.3%–55.7%) within 7 to 59 days of vaccination and 21.1% (95% CI, −0.5% to 37.1%) within 60 to 179 days of vaccination when compared with participants who were unvaccinated or had received an original monovalent vaccine dose ≥180 days prior. Overall, the adjusted VE of a bivalent vaccine against infection, in conjunction with prior infection, was 62.2% (95% CI, 46.0%–74.5%) within 7 to 179 days of vaccination and 39.4% (95% CI, 12.5%–61.6%) at ≥180 days when compared with naive participants who were unvaccinated or had received a monovalent vaccine dose ≥180 days prior. Conclusions: Adults with prior infection and recent vaccination had high protection against infection and symptomatic illness. Recent vaccination alone provided moderate protection.