SARS-CoV-2 transmission and impacts of unvaccinated-only screening in populations of mixed vaccination status

The COVID-19 pandemic significantly impacted global mobility and mortality, prompting widespread vaccination efforts. While vaccines effectively reduce severe disease, breakthrough infections and transmission remain a concern, particularly with variants like Omicron. Early pandemic mitigation strategies focused on regular screening of the entire population. However, later proposals and implementations shifted towards testing only unvaccinated individuals, based on the assumption that they primarily drive transmission. This study questions this premise and analyzes the impact of such policies. The effectiveness of vaccines in reducing transmission is crucial. Vaccines reduce susceptibility to infection (VEi), the likelihood of onward transmission (VEt), and the risk of hospitalization (VEh). Prior SARS-CoV-2 infection also confers some immunity. The Omicron variant, however, demonstrated lower VEi and VEt values, impacting transmission dynamics. This study models SARS-CoV-2 spread in populations with mixed vaccination statuses, focusing on three key questions: 1) The contribution of vaccinated and unvaccinated populations to community spread and hospitalizations; 2) The effect of unvaccinated-only screening programs; and 3) The effectiveness of Delta-era screening strategies against variants like Omicron. The study aims to provide general principles rather than specific predictions, exploring a wide range of parameters and scenarios.

The literature review is implicitly incorporated into the introduction and discussion sections. The authors refer to studies on vaccine efficacy (e.g., effectiveness of mRNA vaccines against Delta and Omicron variants), the impact of prior infection on immunity, and the effectiveness of previous screening programs (both population-wide and targeted at unvaccinated individuals). They cite multiple studies demonstrating the effectiveness of vaccines in preventing severe disease and reducing transmission, along with studies showing the limitations of vaccines against variants and breakthrough infections. The authors also acknowledge the limited data available for Omicron-specific immunity parameters at the time of the study. Specific citations are provided in the reference list.

The study employs a continuous-time ordinary differential equation compartmental model with susceptible, exposed, infected, and recovered (SEIR) compartments, stratified into vaccinated (V) and unvaccinated (U) groups. The model further subdivides these groups based on prior SARS-CoV-2 infection, resulting in four categories: unvaccinated previously infected, unvaccinated naive, vaccinated naive, and vaccinated previously infected. The model considers four transmission modes: U↔U, V↔V, U↔V, and V↔U. Protective effects of vaccines (VEi, VEt, VEh) and prior infection (α, θ, h) are incorporated, accounting for reduced risks of infection, transmission, and hospitalization. A constant rate of external infection introduction (π) is also included. The model simulates outbreaks for a range of parameters, including R0 (basic reproduction number), vaccination rates, prior infection rates, and vaccine effectiveness. Different scenarios are considered, including those reflecting Delta and Omicron variant characteristics. Unvaccinated-only screening is modeled by increasing the removal rate of infected individuals from the unvaccinated compartments, reflecting the effect of testing and isolation. Universal screening is also modeled for comparison. Compliance rates and test sensitivity are varied to assess their impact on screening effectiveness. The authors employ a range of empirically estimated parameters for the delta variant and plausible parameters for the omicron variant to account for differences in transmission and disease parameters between them. The model also accounts for infection-acquired and vaccine-acquired immunity, as well as hybrid immunity, allowing for a more nuanced analysis of the interaction between vaccination and prior infection in shaping transmission dynamics. The sensitivity of the results to various assumptions about vaccine effectiveness is explored by comparing baseline conditions against alternative scenarios, each incorporating different values for VEi, VEt, and VEh parameters. This enables the authors to test the robustness of their findings against a broader range of possibilities. The authors use the effective reproduction number, R_eff, as a key metric for understanding and predicting the impact of screening. They provide equations which allow the prediction of the effectiveness of screening across a range of scenarios by combining the effective reproductive number with parameters for vaccine effectiveness, vaccination rates, and prior infection.

The study's key findings demonstrate that the effectiveness of unvaccinated-only screening programs is significantly dependent on population vaccination rates and the characteristics of the circulating SARS-CoV-2 variant. As vaccination rates increase, the proportion of transmission attributed to unvaccinated individuals decreases, and the relative importance of vaccine breakthrough infections increases. Three distinct regions of impact are identified: 1. **Region I:** Screening reduces the peak number of infections but does not fully control transmission. 2. **Region II:** Screening successfully controls transmission. 3. **Region III:** Screening has minimal impact because transmission is already controlled by high population immunity. The transition between these regions is strongly influenced by vaccination rates, prior infection rates, and vaccine effectiveness. High compliance with testing is crucial for effective screening. The study also highlights that while unvaccinated-only screening effectively reduces transmission from unvaccinated individuals, it doesn't significantly change the proportion of infections or hospitalizations resulting from vaccine breakthroughs. High vaccination rates lead to a majority of infections and hospitalizations being attributed to breakthrough cases. The effectiveness of unvaccinated-only screening is markedly lower for the Omicron variant compared to the Delta variant, due to Omicron's higher rates of reinfection and vaccine breakthrough. The study shows that unvaccinated-only screening cannot achieve R_eff < 1 for Omicron except under very specific conditions (low vaccination rates and high-frequency testing with near-perfect compliance). The study also uses an effective reproduction number (R_eff)-based analysis to predict the impact of both unvaccinated-only and universal screening programs on infections and hospitalizations, demonstrating the utility of this approach across various scenarios.

The findings challenge the assumption that unvaccinated individuals are the primary drivers of SARS-CoV-2 transmission in highly vaccinated populations. As vaccination rates increase, the focus should shift from targeting only unvaccinated individuals to mitigating vaccine breakthrough infections. The study emphasizes the importance of high compliance with screening programs to maximize their effectiveness. The results demonstrate that the effectiveness of unvaccinated-only screening is strongly context-dependent, highlighting the need for tailored strategies considering vaccination rates, variant characteristics, and compliance levels. The study's methodological approach, using R_eff analysis, offers a valuable tool for evaluating the potential impact of different screening programs and policies. The results underscore that reliance on unvaccinated-only screening as a primary mitigation strategy might be insufficient in settings with high vaccination coverage and concerning variants like Omicron. The study recommends a multifaceted approach, combining screening programs with other non-pharmaceutical interventions (NPIs) to effectively reduce transmission and hospitalizations. The work also calls for further research to improve understanding of the dynamic interplay between various immunity factors and the behavior of emerging variants in shaping transmission dynamics.

This study demonstrates that the effectiveness of unvaccinated-only SARS-CoV-2 screening programs depends critically on population immunity levels, vaccination rates, the specific variant circulating, and compliance with testing mandates. Unvaccinated-only screening is most effective in populations with relatively low vaccination rates, particularly when the effective reproduction number is close to 1. High compliance with testing is essential to achieving substantial reductions in infections and hospitalizations. For variants such as Omicron, with higher rates of breakthrough infections, unvaccinated-only screening is shown to be far less effective, particularly in populations with higher levels of vaccination. Future research should focus on evaluating the effectiveness of comprehensive mitigation strategies incorporating multiple NPI components, as well as exploring the interaction of population-level factors beyond immunity (such as contact patterns and behavioral responses) with screening effectiveness. Additionally, the dynamics of vaccine waning and emerging variants necessitate further modeling and real-world data analysis.

The study acknowledges several limitations. The model utilizes fixed parameters that are challenging to estimate accurately in real-world situations, especially regarding Omicron's characteristics. The assumption of perfect isolation following a positive test result may overestimate screening effectiveness. The model's well-mixed nature may not fully capture real-world heterogeneity in contact patterns and vaccination distributions. Finally, the study’s focus is on transmission reduction through testing, and it doesn’t fully address the broader benefits of testing (diagnosis, treatment, variant detection, etc.) or its potential to incentivize vaccination.