Learning from the COVID-19 pandemic to strengthen routine immunization systems

Kate Causey and Jonathan F Mosser discuss what can be learnt from the observed impacts of the COVID-19 pandemic on routine immunisation systems.

In the final months of 2021, deaths due to the Coronavirus Disease 2019 (COVID-19) surpassed 5 million globally [1]. Available data suggest that even this staggering figure may be a substantial underestimate of the true toll of the pandemic [2]. Beyond mortality, it may take years to fully quantify the direct and indirect impacts of the COVID-19 pandemic such as disruptions in preventive care services. In an accompanying research study in PLOS Medicine, McQuaid and colleagues report on the uptake of routine childhood immunizations in 2020 in Scotland and England during major pandemic-related lockdowns [3]. This adds to a growing body of literature quantifying the impact of the COVID-19 pandemic on routine health services and childhood immunization [4,5], which provides important opportunities to learn from early pandemic experiences as immunization systems face ongoing challenges.McQuaid and colleagues compared weekly or monthly data on vaccine uptake in Scotland and England from January to December of 2020 to the rates observed in 2019 to estimate the changes in uptake before, during, and after COVID-19 pandemic lockdowns in each country. The authors included 2 different preschool immunizations, each with multiple doses. They found significantly increased uptake within 4 weeks of eligibility during the lockdown and postlockdown periods in Scotland for all 5 vaccine dose combinations examined: During lockdown, percentage point increases ranged from 1.3% to 14.3%. In England, there were significant declines in uptake during the prelockdown, lockdown, and postlockdown periods for all 4 vaccine dose combinations examined. However, declines during lockdown were small, with percentage point decreases ranging from −0.5% to −2.1%. Due to the nature of the data available, the authors were unable to account for possible seasonal variation in vaccine delivery, control for important individual-level confounders or effect modifiers such as child sex and parental educational attainment, or directly compare outcomes across the 2 countries.These findings stand in contrast to the documented experience of many other countries, where available data suggest historic disruptions in routine childhood vaccination coverage, particularly during the first months of pandemic-related lockdowns [5,6]. Supply side limitations such as delayed shipments of vaccines and supplies [7], inadequate personal protective equipment [8], staff shortages [9], and delayed or canceled campaigns and introductions [9] threatened vaccine delivery. Furthermore, fear of exposure to COVID-19 at vaccination centers [10], misinformation about vaccine safety [8], and lockdown-related limitations on travel to facilities [9,10] reduced demand. In polls of country experts conducted by WHO, UNICEF, and Gavi, the Vaccine Alliance throughout the second quarter of 2020, 126 of 170 countries reported at least some disruption to routine immunization programs [10,11]. Global estimates suggest that millions more children missed doses of important vaccines than would have in the absence of the COVID-19 pandemic [5,6]. While many vaccine programs showed remarkable resilience in the second half of 2020, with rates of vaccination returning to or even exceeding prepandemic levels [5,6], disruptions to immunization services persisted into 2021 in many countries [12].As the authors discuss, it is critical to pinpoint the specific program policies and strategies that contributed to increased uptake in Scotland and only small declines in England and, more broadly, to the rapid recovery of vaccination rates observed in many other countries. McQuaid and colleagues cite work suggesting that increased flexibility in parental working patterns during lockdowns, providing mobile services or public transport to vaccine centers, and sending phone- and mail-based reminders are strategies that may have improved uptake of timely vaccination in Scotland during this period [13]. Similarly, immunization programs around the world have employed a broad range of strategies to maintain or increase vaccination during the pandemic. Leaders in Senegal, Paraguay, and Sri Lanka designed and conducted media campaigns to emphasize the importance of childhood immunization even during lockdown [8,14,15]. Although many programs delayed mass campaigns in the spring of 2020, multiple countries were able to implement campaigns by the summer of 2020 [8,16–20]. In each of these examples, leaders responded quickly to meet the unique challenges presented by the COVID-19 pandemic in their communities.Increased data collection and tracking systems are essential for efficient and effective responses as delivery programs face challenges. When concern arose for pandemic-related disruptions to immunization services, public health decision-makers in Scotland and England responded by increasing the frequency and level of detail in reports of vaccine uptake and by making these data available for planning and research. The potential for robust data systems to inform real-time decision-making is not limited to high-income countries. For instance, the Nigerian National Health Management Information System released an extensive online dashboard shortly after the onset of the pandemic, documenting the impact of COVID-19 on dozens of indicators of health service uptake, including 16 related to immunization [21]. Vaccination data systems that track individual children and doses, such as the reminder system in Scotland, allow for highly targeted responses. Similarly, in Senegal, Ghana, and in Karachi, Pakistan, healthcare workers have relied on existing or newly implemented tracking systems to identify children who have missed doses and provide text message and/or phone call reminders [8,22,23]. Investing in robust routine data systems allows for rapid scale-up of data collection, targeted services to those who miss doses, and a more informed response when vaccine delivery challenges arise.Policy and program decision-makers must learn from the observed impacts of the COVID-19 pandemic on health systems and vaccine delivery. The study by McQuaid and colleagues provides further evidence that vaccination programs in England and Scotland leveraged existing strengths and identified novel strategies to mitigate disruptions and deliver vaccines in the early stages of the pandemic. However, the challenges posed by the pandemic to routine immunization services continue. To mitigate the risk of outbreaks of measles and other vaccine-preventable diseases, strategies are needed to maintain and increase coverage, while ensuring that children who missed vaccines during the pandemic are quickly caught up. The accompanying research study provides important insights into 2 countries where services were preserved—and even increased—in the early pandemic. To meet present and future challenges, we must learn from early pandemic successes such as those in Scotland and England, tailor solutions to improve vaccine uptake, and strengthen data systems to support improved decision-making.     

Bayesian time-varying autoregressive models of COVID-19 epidemics

The COVID-19 pandemic has highlighted the importance of reliable statistical models which, based on the available data, can provide accurate forecasts and impact analysis of alternative policy measures. Here we propose Bayesian time-dependent Poisson autoregressive models that include time-varying coefficients to estimate the effect of policy covariates on disease counts. The model is applied to the observed series of new positive cases in Italy and in the United States. The results suggest that our proposed models are capable of capturing nonlinear growth of disease counts. We also find that policy measures and, in particular, closure policies and the distribution of vaccines, lead to a significant reduction in disease counts in both countries.     

COVID-19: From pathogenesis models to the first drug trials

The number of people infected with SARS-CoV-2, and sadly dying from COVID-19, has exploded, and so the amount of literature on the novel coronavirus and the disease it causes has increased proportionately. The case numbers in some countries are beyond the epidemic peak, but the uncertainty about a second wave keeps politicians and societies under pressure. Appropriate decision-making and winning support from the population depends on precise scientific information rather than leaving the field to scaremongers of all proveniences. This mini-review is an update of earlier reports (Brüssow, Microb Biotechnol 2020a;13:607; Brüssow, Microb Biotechnol 2020b; https://doi.org/10.1111/1751-7915.13592 ).     

COVID-19 in patients undergoing long-term dialysis in Ontario

BACKGROUND:Patients undergoing long-term dialysis may be at higher risk of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and of associated disease and mortality. We aimed to describe the incidence, risk factors and outcomes for infection in these patients in Ontario, Canada.METHODS:We used linked data sets to compare disease characteristics and mortality between patients receiving long-term dialysis in Ontario who were diagnosed SARS-CoV-2 positive and those who did not acquire SARS-CoV-2 infection, between Mar. 12 and Aug. 20, 2020. We collected data on SARS-CoV-2 infection prospectively. We evaluated risk factors for infection and death using multivariable logistic regression analyses.RESULTS:During the study period, 187 (1.5%) of 12 501 patients undergoing dialysis were diagnosed with SARS-CoV-2 infection. Of those with SARS-CoV-2 infection, 117 (62.6%) were admitted to hospital and the case fatality rate was 28.3%. Significant predictors of infection included in-centre hemodialysis versus home dialysis (odds ratio [OR] 2.54, 95% confidence interval [CI] 1.59–4.05), living in a long-term care residence (OR 7.67, 95% CI 5.30–11.11), living in the Greater Toronto Area (OR 3.27, 95% CI 2.21–4.80), Black ethnicity (OR 3.05, 95% CI 1.95–4.77), Indian subcontinent ethnicity (OR 1.70, 95% CI 1.02–2.81), other non-White ethnicities (OR 2.03, 95% CI 1.38–2.97) and lower income quintiles (OR 1.82, 95% CI 1.15–2.89).INTERPRETATION:Patients undergoing long-term dialysis are at increased risk of SARS-CoV-2 infection and death from coronavirus disease 2019. Special attention should be paid to addressing risk factors for infection, and these patients should be prioritized for vaccination.

As of Aug. 20, 2020, in Ontario, Canada’s most populous province, almost 41 000 people had tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19),¹ which represented 0.3% of the provincial population. Close to 2800 people had died, a case fatality rate of 6.8%.²Patients undergoing dialysis have high rates of comorbid conditions, are often older adults, have varying degrees of immunosuppression and are more likely to reside in long-term care, which puts them at risk of both acquiring SARS-CoV-2 and developing complicated disease.^3,4 Furthermore, in Ontario, those who receive in-centre hemodialysis typically have 3 treatments per week in outpatient units located in or affiliated with hospitals, and the consequent inability to fully self-isolate means that patients undergoing hemodialysis likely have an even higher risk of SARS-CoV-2 infection.^3,4 Recent studies support this but do not compare infection rates with those in the local population of patients not undergoing dialysis.^5–10 Several studies have reported SARS-CoV-2 infection in single or multicentre cohorts of patients undergoing dialysis,^5–10 but we are unaware of any that have identified risk factors for infection at the level of a large region. Some studies have found that patients with SARS-CoV-2 infection who are undergoing dialysis are at high risk of severe illness and death.^6–10     

Deep Transfer Learning Based Classification Model for COVID-19 Disease

The COVID-19 infection is increasing at a rapid rate, with the availability of limited number of testing kits. Therefore, the development of COVID-19 testing kits is still an open area of research. Recently, many studies have shown that chest Computed Tomography (CT) images can be used for COVID-19 testing, as chest CT images show a bilateral change in COVID-19 infected patients. However, the classification of COVID-19 patients from chest CT images is not an easy task as predicting the bilateral change is defined as an ill-posed problem. Therefore, in this paper, a deep transfer learning technique is used to classify COVID-19 infected patients. Additionally, a top-2 smooth loss function with cost-sensitive attributes is also utilized to handle noisy and imbalanced COVID-19 dataset kind of problems. Experimental results reveal that the proposed deep transfer learning-based COVID-19 classification model provides efficient results as compared to the other supervised learning models.     

Predictions of COVID-19 dynamics in the UK: Short-term forecasting and analysis of potential exit strategies

Efforts to suppress transmission of SARS-CoV-2 in the UK have seen non-pharmaceutical interventions being invoked. The most severe measures to date include all restaurants, pubs and cafes being ordered to close on 20th March, followed by a “stay at home” order on the 23rd March and the closure of all non-essential retail outlets for an indefinite period. Government agencies are presently analysing how best to develop an exit strategy from these measures and to determine how the epidemic may progress once measures are lifted. Mathematical models are currently providing short and long term forecasts regarding the future course of the COVID-19 outbreak in the UK to support evidence-based policymaking. We present a deterministic, age-structured transmission model that uses real-time data on confirmed cases requiring hospital care and mortality to provide up-to-date predictions on epidemic spread in ten regions of the UK. The model captures a range of age-dependent heterogeneities, reduced transmission from asymptomatic infections and produces a good fit to the key epidemic features over time. We simulated a suite of scenarios to assess the impact of differing approaches to relaxing social distancing measures from 7th May 2020 on the estimated number of patients requiring inpatient and critical care treatment, and deaths. With regard to future epidemic outcomes, we investigated the impact of reducing compliance, ongoing shielding of elder age groups, reapplying stringent social distancing measures using region based triggers and the role of asymptomatic transmission. We find that significant relaxation of social distancing measures from 7th May onwards can lead to a rapid resurgence of COVID-19 disease and the health system being quickly overwhelmed by a sizeable, second epidemic wave. In all considered age-shielding based strategies, we projected serious demand on critical care resources during the course of the pandemic. The reintroduction and release of strict measures on a regional basis, based on ICU bed occupancy, results in a long epidemic tail, until the second half of 2021, but ensures that the health service is protected by reintroducing social distancing measures for all individuals in a region when required. Our work confirms the effectiveness of stringent non-pharmaceutical measures in March 2020 to suppress the epidemic. It also provides strong evidence to support the need for a cautious, measured approach to relaxation of lockdown measures, to protect the most vulnerable members of society and support the health service through subduing demand on hospital beds, in particular bed occupancy in intensive care units.     

COVID-19: vaccination problems

This minireview addresses problems of financing the vaccine development, regulatory questions, the ethics and efficacy of vaccine prioritization strategies and the coverage of variant viruses by current vaccines. Serious adverse effects observed with adenovirus vectored vaccines and mRNA vaccines in mass vaccination campaigns are reported. The ethical problems of continuing with placebo controlled vaccine trials and alternative clinical trial protocols are discussed as well as concrete vaccination issues such as the splitting of doses, the delaying of the second dose, the immunization with two different vaccine types and the need of vaccinating seropositive subjects. Strategies to increase vaccine acceptance in the population are shortly mentioned.     

COVID-19 one year later: a retrospect of CRISPR-Cas system in combating COVID-19

Coronavirus disease 2019 (COVID-19), an infectious disease caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has posed a persistent global threat. The transmission of SARS-CoV-2 is wide and swift. Rapid detection of the viral RNA and effective therapy are imperative to prevent the worldwide spread of the new infectious disease. Clustered Regularly-Interspaced Short Palindromic Repeats (CRISPR)- CRISPR-associated protein (Cas) system is an RNA-directed adaptive immune system, and it has been transformed into a gene editing tool. Applications of CRISPR-Cas system involves in many fields, such as human gene therapy, drug discovery and disease diagnosis. Under the background of COVID-19 pandemic, CRISPR-Cas system shows hidden capacity to fight the emergency in many aspects. This review will focus on the role of gene editing in COVID-19 diagnosis and treatment. We will describe the potential use of CRISPR-Cas-based system in combating COVID-19, from diagnosis to treatment. Furthermore, the limitation and perspectives of this novel technology are also evaluated.     

Focus: Health Equity: COVID-19 Healthcare Inequity: Lessons Learned from Annual Influenza Vaccination Rates to Mitigate COVID-19 Vaccine Disparities

The COVID-19 pandemic has infected 33 million Americans and resulted in more than 600,000 deaths as of late Spring 2021. Black, Indigenous, and Latinx (BIL) people are disproportionately infected, hospitalized, and dying. Effective vaccines were rapidly developed and have been widely available in the United States since their initial rollout in late 2020-early 2021 but vaccination rates in BIL communities have remained low compared with non-BIL communities. Limited access to the vaccine, lack of customized information, and mistrust of the medical system, all contribute to vaccine hesitancy and low vaccination rates. Regrettably, COVID-19 is not the only vaccine-preventable illness with racial/ethnic inequities. Similar inequities are seen with the seasonal influenza vaccine. We review the racial/ethnic health disparities in COVID-19 illness and vaccination rates and what inequities contribute to these disparities. We use evidence from the seasonal influenza vaccination efforts to inform potential strategies to attenuate these inequities. The development of effective and sustainable strategies to improve vaccination rates and reduce factors that result in health inequities is essential in managing current and future pandemics and promoting improved health for all communities.     

Association between long-term exposure to ambient air pollution and COVID-19 severity: a prospective cohort study

Background:The tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system.Methods:We used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM_2.5), nitrogen dioxide (NO₂) and ground-level ozone (O₃), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals’ long-term exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage.Results:Among the 151 105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM_2.5 (1.70 μg/m³), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01–1.12), 1.09 (95% CI 0.98–1.21) and 1.00 (95% CI 0.90–1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO₂. We also estimated odds ratios of 1.15 (95% CI 1.06–1.23), 1.30 (95% CI 1.12–1.50) and 1.18 (95% CI 1.02–1.36) per interquartile range increase of 5.14 ppb in O₃ for hospital admission, ICU admission and death, respectively.Interpretation:Chronic exposure to air pollution may contribute to severe outcomes after SARS-CoV-2 infection, particularly exposure to O₃.

By November 2021, COVID-19 had caused more than 5 million deaths globally¹ and more than 29 400 in Canada.² The clinical manifestations of SARS-CoV-2 infection range from being asymptomatic to multiple organ failure and death. Identifying risk factors for COVID-19 severity is important to better understand etiological mechanisms and identify populations to prioritize for screening, vaccination and medical treatment. Risk factors for severity of COVID-19 include male sex, older age, pre-existing medical conditions and being from racialized communities.^3–5 More recently, ambient air pollution has been implicated as a potential driver of COVID-19 severity.^6–10Long-term exposure to ambient air pollution, a major contributor to global disease burden,¹¹ could increase the risk of severe COVID-19 outcomes by several mechanisms. Air pollutants can reduce individuals’ pulmonary immune responses and antimicrobial activities, boosting viral loads.⁸ Air pollution can also induce chronic inflammation and overexpression of the alveolar angiotensin-converting enzyme 2 (ACE) receptor,⁷ the key receptor that facilitates SARS-CoV-2 entry into cells.^12,13 Exposure to air pollution contributes to chronic conditions, such as cardiovascular disease, that are associated with unfavourable COVID-19 prognosis, possibly owing to persistent immune activation and excessive amplification of cytokine development.¹⁰ Thus, greater exposure to long-term air pollution may lead to severe COVID-19 outcomes.Reports exist of positive associations between long-term exposure to particulate matter with diameters equal to or smaller than 2.5 or 10 μm (PM_2.5 and PM₁₀), ground-level ozone (O₃) and nitrogen dioxide (NO₂), and metrics of COVID-19 severity (e.g., mortality and case fatality rate).^8–10 However, most studies to date have used ecological and cross-sectional designs, owing to limited access to individual data, which leads to ambiguity in interpreting the results, thus hindering their influence on policy. ^6,14 Ecological designs do not allow for disentangling the relative impacts of air pollution on individual susceptibility to infection and disease severity.¹⁴ Residual confounding by factors such as population mobility and social interactions is also problematic. Therefore, a cohort study with data on individuals with SARS-CoV-2 is a more appropriate design.^6,14 Studies that have used individual data were conducted in specific subpopulations^15,16 or populations with few severe cases,¹⁷ or had limited data on individual exposure to air pollutants.¹⁸ In Canada, 1 ecological study found a positive association between long-term exposure to PM_2.5 and COVID-19 incidence,¹⁹ but no published study has explored the association between air pollution and COVID-19 severity.We aimed to examine the associations between long-term exposure to 3 common air pollutants (PM_2.5, NO₂ and O₃) and key indicators of COVID-19 severity, including hospital admission, intensive care unit (ICU) admission and death, using a large prospective cohort of people with confirmed SARS-CoV-2 infection in Ontario, Canada, in 2020. The air contaminants PM_2.5, NO₂ and O₃ are regularly monitored by the Canadian government, and are key pollutants that are considered when setting air-quality policies. They originate from varying sources (NO₂ is primarily emitted during combustion of fuel, O₃ is primarily formed in air by chemical reactions of nitrogen oxides and volatile organic compounds, and PM_2.5 can be emitted during combustion or formed by reactions of chemicals like sulphur dioxide and nitrogen oxides in air) and they may affect human health differently.^20,21,22     

COVID-19 crisis management in Luxembourg: Insights from an epidemionomic approach

We develop an epidemionomic model that jointly analyzes the health and economic responses to the COVID-19 crisis and to the related containment and public health policy measures implemented in Luxembourg. The model has been used to produce nowcasts and forecasts at various stages of the crisis. We focus here on two key moments in time, namely the deconfinement period following the first lockdown, and the onset of the second wave. In May 2020, we predicted a high risk of a second wave that was mainly explained by the resumption of social life, low participation in large-scale testing, and reduction in teleworking practices. Simulations conducted 5 months later reveal that managing the second wave with moderately coercive measures has been epidemiologically and economically effective. Assuming a massive third (or fourth) wave will not materialize in 2021, the real GDP loss due to the second wave will be smaller than 0.4 percentage points in 2020 and 2021.     

COVID-19 prevention and control strategies: learning from the Macau model

Background: Macau is a densely populated international tourist city. Compared to most tensely populated countries/territories, the prevalence and mortality of COVID-19 in Macau are lower. The experiences in Macau could be helpful for other areas to combat the COVID-19 pandemic. This article introduced the endeavours and achievements of Macau in combatting the COVID-19 pandemic.Method: Both qualitative and quantitative analysis methods were used to explore the work, measures, and achievements of Macau in dealing with the COVID-19 pandemic.Results: The results revealed that Macau has provided undifferentiated mask purchase reservation services, COVID-19 vaccination services to all residents and non-residents in Macau along with delivering multilingual services, in Chinese, English and Portuguese, to different groups of the population. To facilitate the travels of people, business and trades between Macau and mainland China, the Macau government launched the Macau Health Code System, which uses the health status declaration, residence history declaration, contact history declaration of the declarant to match various relevant backend databases within the health authority and provide a risk-related colour code operations. The Macau Health Code System connects to the Chinese mainland''s own propriety health code system seamlessly, whilst effectively protecting the privacy of the residents. Macau has also developed the COVID-19 Vaccination Appointment system, the Nucleic Acid Test Appointment system, the Port and Entry/Exit Quarantine system, the medical and other supporting systems.Conclusion: The efforts in Macau have achieved remarkable results in COVID-19 prevention and control, effectively safeguarding the lives and health of the people and manifesting the core principle of “serving the public”. The measures used are sustainable and can serve as an important reference for other countries/regions.     

Neuroinflammation and COVID-19

Coronavirus disease 2019 (COVID-19) has caused a historic pandemic of respiratory disease. COVID-19 also causes acute and post-acute neurological symptoms, which range from mild, such as headaches, to severe, including hemorrhages. Current evidence suggests that there is no widespread infection of the central nervous system (CNS) by SARS-CoV-2, thus what is causing COVID-19 neurological disease? Here, we review potential immunological mechanisms driving neurological disease in COVID-19 patients. We begin by discussing the implications of imbalanced peripheral immunity on CNS function. Next, we examine the evidence for dysregulation of the blood-brain barrier during SARS-CoV-2 infection. Last, we discuss the role myeloid cells may play in promoting COVID-19 neurological disease. Combined, we highlight the role of innate immunity in COVID-19 neuroinflammation and suggest areas for future research.     

COVID-19 mRNA vaccines

The ongoing COVID-19 pandemic and its unprecedented global societal and economic disruptive impact highlight the urgent need for safe and effective vaccines. Taking substantial advantages of versatility and rapid development, two m RNA vaccines against COVID-19 have completed late-stage clinical assessment at an unprecedented speed and reported positive results. In this review, we outline keynotes in m RNA vaccine development, discuss recently published data on COVID-19 m RNA vaccine candidates, focusing on those in clinical trials and analyze future potential challenges.