The balancing role of distribution speed against varying efficacy levels of COVID-19 vaccines under variants

Optimization Modeling for Pandemic Vaccine Supply Chain Management: A Review and Future Research Opportunities

During various stages of the COVID-19 pandemic, countries implemented diverse vaccine management approaches, influenced by variations in infrastructure and socio-economic conditions. This article provides a comprehensive overview of optimization models developed by the research community throughout the COVID-19 era, aimed at enhancing vaccine distribution and establishing a standardized framework for future pandemic preparedness. These models address critical issues such as site selection, inventory management, allocation strategies, distribution logistics, and route optimization encountered during the COVID-19 crisis. A unified framework is employed to describe the models, emphasizing their integration with epidemiological models to facilitate a holistic understanding. This article also summarizes evolving nature of literature, relevant research gaps, and authors' perspectives for model selection. Finally, future research scopes are detailed both in the context of modeling and solutions approaches.

Influenza A, like Omicron SARS-CoV-2, Is Similarly Detected in Saliva or Nasopharyngeal Samples via RT-qPCR

After the Coronavirus pandemic, the importance of virus surveillance was highlighted, reinforcing the constant necessity of discussing and updating the methods for collection and diagnoses, including for other respiratory viruses. Although the nasopharyngeal swab is the gold-standard sample for detecting and genotyping SARS-CoV-2 and Influenza viruses, its collection is uncomfortable and requires specialized teams, which can be costly. During the pandemic, non-invasive saliva samples proved to be a suitable alternative for SARS-CoV-2 diagnosis, but for Influenza virus the use of this sample source is not recognized yet. In addition, most SARS-CoV-2 comparisons were conducted before the Omicron variant emerged. Here, we aimed to compare Influenza A and Omicron RT-qPCR analysis of nasopharyngeal swabs and saliva self-collection in paired samples from 663 individuals. We found that both nasopharyngeal swab and saliva collection are efficient for the diagnosis of Omicron (including sub-lineages) and for Influenza A, with high sensitivity and accuracy (>90%). The kappa index is 0.938 for Influenza A and 0.905 for SARS-CoV-2. These results showed excellent agreement between the two samples reinforcing saliva samples as a reliable source for detecting Omicron and highlighting saliva as a valid sample source for Influenza detection, considering this cheaper and more comfortable alternative.

Narrative Review of the Evolution of COVID-19 Vaccination Recommendations in Countries in Latin America, Africa and the Middle East, and Asia

The rapid rollout of vaccines to combat the coronavirus disease 2019 (COVID-19) pandemic over the past 2 years has resulted in the use of various vaccine platforms and regional differences in COVID-19 vaccine implementation strategies. The aim of this narrative review was to summarize evolving COVID-19 vaccine recommendations in countries in Latin America, Asia, and Africa and the Middle East across various vaccine platforms, age groups, and specific subpopulations. Nuances in primary and booster vaccination schedules were evaluated, and the preliminary impact of such diverse vaccination strategies are discussed, including key vaccine effectiveness data in the era of Omicron-lineage variants. Primary vaccination rates for included Latin American countries were 71-94% for adults and between 41% and 98% for adolescents and children; rates for first booster in adults were 36-85%. Primary vaccination rates for adults in the included Asian countries ranged from 64% in the Philippines to 98% in Malaysia, with corresponding booster rates varying from 9% in India to 78% in Singapore; for adolescents and children, primary vaccination rates ranged from 29% in the Philippines to 93% in Malaysia. Across included African and Middle Eastern countries, primary vaccination rates in adults varied widely from 32% in South Africa to 99% in the United Arab Emirates; booster rates ranged from 5% in South Africa to 60% in Bahrain. Evidence from the regions studied indicates preference of using an mRNA vaccine as a booster on the basis of safety and effectiveness of observed real-world data, especially during circulation of Omicron lineages. Vaccination against COVID-19 remains of paramount importance to reduce the burden of disease; strategies to overcome vaccine inequity, fatigue, hesitancy, and misinformation and to ensure adequate access and supply are also important.

Effect of vaccination patterns and vaccination rates on the spread and mortality of the COVID-19 pandemic

Objectives

Acquiring herd immunity through vaccination is the best way to curb the COVID-19 infection. Many countries have attempted to reach the herd immunity threshold as early as possible since the commencement of vaccination at the end of 2020. The purpose of this study is to (1) examine whether the pattern of vaccination rates affects the spread of COVID-19 and the consequent mortality and (2) investigate the level of cumulative vaccination rates that can begin to have an impact on reducing the spread and mortality of the pandemic.

Methods

This study selected 33 countries with higher vaccination rates as its sample set, classifying them into three groups as per vaccination patterns.

Results

The results showed that vaccination patterns have a significant impact on reducing spread and mortality. The full-speed vaccination pattern showed greater improvement in the spread of the COVID-19 pandemic than the other two patterns, while the striving vaccination pattern improved the most in terms of mortality. Secondly, the spread and mortality of the COVID pandemic started to significantly decline when the average cumulative vaccination rate reached 29.06 doses per 100 people and 7.88 doses per 100 people, respectively.

Conclusion

The study highlights the important role of vaccination patterns and the VTMR in reducing the epidemic spread and mortality.

A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior

Vaccines for COVID-19 have allowed countries to combat the spread of the disease. However, new variants have resulted in significant spikes in cases and raised severe health and economic concerns. We present a COVID-19 model to predict coupled effects of vaccine multiple-dose roll-out strategies, vaccine efficacy, waning immunity, population level of caution, sense of safety, under-reporting of cases, and highly prevalent variants such as the Delta (B.1.617.2) and Omicron (B.1.1.529). The modeling framework can incorporate new variants as they emerge to give critical insights into the new cases and guide public policy decision-making concerning vaccine roll-outs and reopening strategies. The model is shown to recreate the history of COVID-19 for five countries (Germany, India, Japan, South Africa, and the United States). Parameters for crucial aspects of the pandemic, such as population behavior, new variants, vaccination, and waning immunity, can be adjusted to predict pandemic scenarios. The model was used to conduct trend analysis to simulate pandemic dynamics taking into account the societal level of caution, societal sense of safety, and the proportions of individuals vaccinated with first, second, and booster doses. We used the results of serological testing studies to estimate the actual number of cases across countries. The model allows quantification of otherwise hard to quantify aspects such as the infectious power of variants and the effectiveness of government mandates and population behavior. Some example cases are presented by investigating the competitive nature of COVID variants and the effect of different vaccine distribution strategies between immunity groups.

The Impact of Testing Capacity and Compliance With Isolation on COVID-19: A Mathematical Modeling Study

Introduction

Diagnostic tests can play an important role in reducing the transmission of infectious respiratory diseases, particularly during a pandemic. The potential benefit of diagnostic testing depends on at least 4 factors: (1) how soon testing becomes available after the beginning of the pandemic and (2) at what capacity; (3) compliance with isolation after testing positive; and (4) compliance with isolation when experiencing symptoms, even in the absence of testing.

Methods

To understand the interplay between these factors and provide further insight into policy decisions for future pandemics, we developed a compartmental model and simulated numerous scenarios using the dynamics of COVID-19 as a case study.

Results

Our results quantified the significant benefits of early start of testing and high compliance with isolation. Early start of testing, even with low testing capacity over time, could significantly slow down the disease spread if compliance with isolation is high. By contrast, when the start of testing was delayed, the benefit of testing on reducing infection spread was limited, even when testing capacity was high; the additional testing capacity required increased superlinearly for each day of delay to achieve a similar infection attack rate as in starting testing earlier.

Conclusions

Our study highlighted the importance of the early start of testing and public health messaging to promote isolation compliance when needed for an ongoing effective response to COVID-19 and future pandemics.