Epidemiology and long-term clinical characteristics of COVID-19 in Amsterdam, the Netherlands Lessons learned and considerations for the future Elke Wynberg
Financial support for printing of this thesis was kindly provided by the Public Health Service of Amsterdam (GGD Amsterdam) and the SBOH. Layout and printing by Ridderprint, www.ridderprint.nl of Ridderprint, the Netherlands. Cover design: Elke Wynberg. Background photograph of the Bahamas from outer space taken by NASA astronaut Scott Kelly, during his “Year in Space” mission in 2015. ISBN: 978-94-6483-286-0 Copyright © 2023 by Elke Wynberg. All rights reserved. No parts of this thesis may be reproduced, stored, or transmitted in any way without prior permission of the author.
Epidemiology and long-term clinical characteristics of COVID-19 in Amsterdam, the Netherlands Lessons learned and considerations for the future ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. ir. P.P.C.C. Verbeek ten overstaan van een door het College voor Promoties ingestelde commissie, in het openbaar te verdedigen in de Agnietenkapel op woensdag 4 oktober 2023, te 16.00 uur door Elke Wynberg geboren te Voorschoten
Promotiecommissie Promotores: prof. dr. M. Prins AMC-UvA prof. dr. M.D. de Jong AMC-UvA Copromotor: dr. T. Leenstra RIVM Overige leden: prof. dr. J.A. Knoop AMC-UvA prof. dr. C.O. Agyemang AMC-UvA dr. S. van den Hof RIVM prof. dr. J.T. van Dissel Universiteit Leiden prof. dr. W.J. Wiersinga AMC-UvA dr. J.L.A. Hautvast Radboudumc Faculteit der Geneeskunde
TABLE OF CONTENTS Chapter 1: General introduction 11 Part 1: Epidemiology and long-term clinical features of COVID-19 in Amsterdam, the Netherlands 34 Chapter 2: Hospitalisation rates differed by city district and ethnicity during the first wave of COVID-19 in Amsterdam, the Netherlands 37 Chapter 3: COVID-19 burden differed by city district and ethnicity during the pre-vaccination era in Amsterdam, the Netherlands 67 Chapter 4: Evolution of COVID-19 symptoms during the first 12 months after illness onset 97 Chapter 5: Severe fatigue in the first year following SARS-CoV-2 infection: A prospective cohort study 135 Part 2: In-depth characterisation of long COVID: Trajectories and possible pathogenesis 170 Chapter 6: Two-year trajectories of COVID-19 symptoms and their association with illness perception: A prospective cohort study in Amsterdam, the Netherlands 172 Chapter 7: Inflammatory profiles are associated with long COVID up to 6 months after illness onset: a prospective cohort study of patients with mild to critical COVID-19 207 Chapter 8: The effect of SARS-CoV-2 vaccination on post-acute COVID-19 syndrome (PASC): A prospective cohort study 239 Chapter 9: General discussion 269 Chapter 10: Summaries in English and Dutch 299 Appendix 311
ABBREVIATIONS ARGOS Amsterdam Regional Genomic Epidemiology & Outbreak Surveillance CBS Central Bureau for Statistics CFR Case fatality rate COVID-19 Coronavirus disease 2019 ECDC European Centre of Disease Control EMA European Medicines Agency HCoV Human coronavirus HELIUS Healthy Life in an Urban Setting HIC High-income country HIV Human immunodeficiency virus HPAI Highly pathogenic avian influenza IL Interleukin IP Interferon gamma inducible protein IQR Interquartile range JAK Janus kinase LCI National Institute of Infectious Disease Control LMIC Low- and middle-income country MERS Middle Eastern Respiratory Syndrome mRNA Messenger ribonucleic acid NICE National Institute for Health & Care Excellence NPIs Non-pharmaceutical interventions PASC Post-acute sequelae of COVID-19 PACS Post-acute COVID-19 syndrome PCR Polymerase chain reaction PHEIC Public Health Emergency of International Concern PHSA Public Health Service of Amsterdam PICS Post-intensive care syndrome R&D Research and development RIVM National Institute for Public Health and the Environment
SARS-CoV Severe acute respiratory syndrome coronavirus SARS-CoV-1 Severe acute respiratory syndrome coronavirus 1 SARS-CoV-2 Severe acute respiratory syndrome coronavirus 2 SFQ Short Fatigue Questionnaire SIDS Small Island Developing State STROBE Strengthening the reporting of observational studies in epidemiology TNF Tumour necrosis factor UMC University Medical Centers VoC Variant of concern WGS Whole genome sequencing WHO World Health Organization ZonMw Netherlands Organisation for Health Research and Development
FOREWORD Looking back on over three years since the first reported cases of coronavirus disease 2019 (COVID-19), the impact that the pandemic has had on the world is almost unfathomable. Every reader of this thesis will have their own personal COVID-19 story, often including difficult experiences. Yet, in the midst of these challenging times, the COVID-19 pandemic also spurred innovation, scientific teamwork, and action on several important public health issues that were laid bare during this crisis. It acted as a pivotal moment during which achievements in research were made possible due to a combination of political backing, rapid financing, and commitment from the scientific community. These achievements were also reliant on many study participants willing to take part in clinical trials and observational studies. As an early-career physician-scientist, I was given the unique opportunity during the COVID-19 pandemic to develop my skills as both a public health doctor and a researcher interested in emerging infections. Together with a highly motivated and interdisciplinary team, we aimed to help tackle pressing research questions during the COVID-19 crisis – the results of which are presented in this thesis. In reading this work, I hope to provide insight into my perspective on the lessons learned from the COVID-19 pandemic and considerations for the future.
GENERAL INTRODUCTION
Chapter 1 12 1.1 A CORONAVIRUS PANDEMIC Historical accounts demonstrate that pandemics have long affected humankind[1]. Perhaps surprisingly, it was only in 2015 that experts met at the World Health Organization (WHO) headquarters in Geneva to generate a list of priority diseases with pandemic potential, for which research and development (R&D) of vaccines and therapeutics were urgently needed. In this R&D priority list, emphasis was placed on pathogens for which no or limited diagnostic tools and treatment options existed, including two coronaviruses that had recently demonstrated their pandemic potential: severe acute respiratory syndrome coronavirus (SARS-CoV, hereafter “SARS-CoV-1”) and Middle Eastern respiratory syndrome coronavirus (MERS-CoV)[2]. Despite the steps taken in 2015, gaps in our pandemic preparedness framework remained, allowing for the emergence and subsequent global spread of SARS-CoV-2 in 2020. At the time of writing, more than half a billion cases of SARS-CoV-2 infection and almost 7 million COVID-19 deaths have been reported worldwide[3] – both expected to be gross underestimations. In the general introduction, I present the epidemiological, clinical and virological features of COVID-19 in the Netherlands and worldwide, our current understanding of ‘long COVID’, and the aims of this thesis. 1.2 COVID-19 WORLDWIDE AND IN THE NETHERLANDS Initial spread of SARS-CoV-2 globally On 31 December 2019, the WHO’s outbreak surveillance system first noticed an unofficial report that raised concern. This report described a cluster of patients who had been hospitalised with atypical pneumonia and shared an epidemiological link to the Huanan Seafood Wholesale Market in Wuhan, China[4]. Following verification of the statement, further investigation quickly identified that human-to-human transmission had taken place[5], sparking urgent questions regarding the transmissibility and virulence of the causal agent. In subsequent weeks, the full genetic sequence of SARS-CoV-2 was shared online[6], enabling the development of diagnostic polymerase chain reaction (PCR) tests. As more countries began testing symptomatic individuals travelling from areas where transmission had been confirmed, exponential global spread of the virus was revealed. The WHO declared a Public Health Emergency of International Concern (PHEIC) on 30 January 2020[7], at which stage the total confirmed case numbers had already risen to almost 10,000 and the novel coronavirus had spread to more than 18 countries[8] (Figure 1.1).
General introduction 13 1 Figure 1.1. Epidemic curve of confirmed COVID-19 cases worldwide, by date of report and WHO region from 30 December 2019 through 30 April 2020[9] As SARS-CoV-2 spread internationally during the first months of 2020, experts looked to the characteristics of SARS-CoV-1 to make predictions about the likelihood of the outbreak to become a global pandemic. We now know, however, that several key differences between SARS-CoV-1 and -2 meant that the latter posed a far greater threat. Firstly, rapid replication of the SARS-CoV-2 in the upper respiratory tract during the incubation period results in a high viral load up to 48 hours before the onset of any symptoms[10], the pre-symptomatic phase, when an individual may continue to have close contact with others. This contrasts with SARS-CoV-1, where the viral load peaked after the onset of symptoms[11, 12], allowing individuals to be isolated before becoming most infectious. Secondly, SARS-CoV-2, unlike SARS-CoV-1, can result in very mild illness or even asymptomatic infection in a substantial proportion of the population[13]. The contribution of such mildly symptomatic and asymptomatic cases to COVID-19 transmission on a population level has been a topic of intense speculation due to its profound implications for public health policy. Evidence suggests that even those lacking (overt) symptoms may, albeit to a lesser extent, pass SARS-CoV-2 on to others[14]. Therefore, during the first months of the pandemic, when testing was generally restricted to those with severe symptoms such as fever, individuals with mild disease probably played a key role in driving largely undetected circulation of the virus. Finally, SARS-CoV-2 exhibited a shorter incubation period of COVID-19 compared to
Chapter 1 14 SARS-CoV-1, with an interval between exposure to the virus and onset of symptoms of only 3-6 days. This hampered timely identification and isolation of an exponentially growing number of infected individuals, creating a major challenge for public health services. Owing to these unique features, SARS-CoV-2 was not successfully contained by case-finding and isolation measures rolled out during the first months of 2020. The outbreak was declared a pandemic on 11 March 2020[15]. SARS-CoV-2: origins, virology, and clinical presentation Most human coronaviruses (including HCoV-NL63, HCoV-229E and HCoV-OC43) result in mild disease, although complications can occur in infants, the elderly and immunocompromised individuals[16]. Understanding how these coronaviruses and their more virulent relatives, SARS-CoV-1 and MERS-CoV, spilled over into the human population provides important lessons about the zoonotic origin of SARS-CoV-2. For instance, ancestors of HCoV-NL63, HCoV-229E[17], SARS-CoV-1, and MERS-CoV[18] have been identified in bats, suggesting further evolution of these early strains produced viruses capable of infecting humans. Interestingly, evidence from molecular clock analyses and clinical case descriptions suggest that the so-called 1890 Russian influenza pandemic may actually have been caused by a bovine-to-human spill-over of HCoVOC43[19]. Specifically, central nervous system symptoms reported during this pandemic are more in keeping with neurotropism of HCoV-OC43 than the clinical features of influenza. Previous understanding of the spill-over from animals to humans of other human coronavirus has thus helped lay the foundation for research into the origins of SARS-CoV-2[4]. Subsequent in-depth analyses have suggested that individuals working in stalls selling live animals in the Huanan Seafood Market could have been infected through intense exposure to, or subsequent consumption of, infected intermediary hosts[20]. Investment in early molecular and clinical studies generated essential knowledge about SARS-CoV-2. Several studies demonstrated that SARS-CoV-2 binds to the same receptor as SARS-CoV-1 in the respiratory tract, ACE-2[21]. However, the SARS-CoV-2 receptor binding domain (RBD) has distinct structural features that explain the higher affinity of SARS-CoV-2 for ACE-2 compared to SARS-CoV-1[22]. After entering epithelial cells and replicating intracellularly, SARS-CoV-2 infection may present with a wide spectrum of clinical features. Respiratory symptoms may include anosmia/ageusia, rhinorrhoea and sore throat, with or without non-specific systemic features such as fatigue, myalgia and fever. Individuals who develop severe disease (initially estimated to be approximately one-fifth of infected non-immune adults[23, 24]; Figure 1.2) tend to deteriorate
General introduction 15 1 approximately one week after illness onset, presenting with dyspnoea and hypoxaemia secondary to acute respiratory distress syndrome (ARDS)[25]. Histopathological studies have demonstrated alveolar damage and fibrin formation in the lungs of hospitalised COVID-19 patients[26]. In addition, severe COVID-19 is characterised by a cytokine storm which may present with thromboembolic complications (such as a stroke or pulmonary embolism) due to microthrombi formation, septic shock and respiratory failure[27]. Due to limited testing during the first months of the pandemic, however, it was difficult to estimate exactly what proportion of infections resulted in severe disease. Initial crude estimates of the case fatality rate (CFR) of COVID-19 were also hampered by delayed reporting of deaths[28] and a case definition that was – due to overreliance on existing knowledge of SARS-CoV-1 – biased towards capturing those with more severe disease. Most initial estimates suggested that, in a fully-susceptible population, the CFR of SARS-CoV-2 infection was lower than that of SARS-CoV-1 and MERS-CoV, but higher than that of seasonal influenza[29]. These estimates have since been influenced by natural and vaccine-derived immunity and viral evolution. Risk factors for COVID-19 hospitalisation and mortality are most notably increased age, cardiovascular comorbidities, obesity, and pregnancy[30, 31]. Figure 1.2. Disease severity pyramid of COVID-19 in 2020[23]* * This figure shows estimated disease severity proportions of the COVID-19 wild-type (Wuhan) variant, prior to the acquirement of natural or vaccine-derived population immunity, and emergence of other variants of concern (VoCs).
Chapter 1 16 Public health response and medical interventions In the absence of vaccines and therapeutic tools during the first months of the pandemic, non-pharmaceutical interventions (NPIs) were the primary way to reduce the impact of SARS-CoV-2 in 2020[32]. Public health policy aimed to use NPIs for both containment (diagnosing and interrupting transmission through isolation of cases and quarantine of contacts) and mitigation (implementing population-wide contact restrictions and bolstering healthcare and essential services to reduce hospitalisation and case fatality rates) of the pathogen. Coupling such interventions with clear and timely communication of essential information was crucial for explaining the need for radical disease control measures[33, 34] and thus help achieve high compliance. Public health measures were soon aided by evidence – developed at record speed – to support the use of therapeutics, adding to our toolkit to reduce the impact of COVID-19. Ground-breaking clinical trials such as the RECOVERY Trial investigated the effect of existing licensed drugs on adverse outcomes of COVID-19. Dexamethasone (an affordable, off-licence medicine also available in low- and middle-income countries [LMICS]) was shown to reduce 28-day mortality among hospitalised patients requiring respiratory support[35]. Other therapies such as interleukin (IL)-6 receptor antagonists[36], janus kinase (JAK) inhibitors[37] and anti-viral agents[38], also improved clinical outcomes of patients hospitalised with COVID-19. The rapid development of this knowledge was a fantastic example of interdisciplinary efforts between virologists, clinicians and epidemiologists, and had direct impact on reducing serious consequences of infection. Whilst these medical breakthroughs reduced COVID-associated morbidity and mortality among those admitted to hospital for COVID-19, it was the development of numerous effective vaccines that helped to prevent severe disease and thereby lessen pressures on tertiary care. Three vaccines had been approved by the European Medicines Agency (EMA) by early 2021: BNT162b2 (developed by BioNTech and Pfizer)[39], ChAdOx1 (developed by AstraZeneca)[40] and mRNA-1273 (developed by Moderna)[41]. In the first year of vaccine roll-out alone, it is estimated that tens of millions of deaths were prevented by vaccination[42]. Nonetheless, the potential impact of vaccination has not been fully realised, owing to both reduced access to vaccination in low-income settings and persistent vaccine scepticism worldwide[43]. Whilst the COVID-19 landscape in 2023 is vastly different from 2020, these enduring challenges continue to undermine our ability to prevent all adverse outcomes of COVID-19.
General introduction 17 1 COVID-19 in the Netherlands: The first wave SARS-CoV-2 infection was declared a Group A notifiable disease in the Netherlands on 28 January 2020. Classification as a Group A pathogen mandates that both suspected and confirmed cases must be notified, and grants public health professionals legal capacity to implement mandatory isolation (of cases), quarantine (of contacts) and diagnostic investigation[44]. The full extent of the potential impact of SARS-CoV-2 in Europe was first demonstrated in northern Italy in February and March 2020, when the rapid spread of the virus led to the hospitalisation of thousands of patients, overwhelming hospital capacity[45]. During the same time period, many Dutch citizens travelled to Italian ski resorts as well as surrounding regions such as Austria and Switzerland; further expansion beyond the Italian epicentre was later demonstrated to have taken place earlier than initially thought[46]. The first notified case of COVID-19 in the Netherlands on 27 February 2020 had an epidemiological link to Lombardy[47]. However, a highly restrictive case definition (based on strict geographic and clinical criteria) was used at that time to allocate scarce tests. It is therefore possible that undetected importation of COVID-19 had already occurred. Between 27 February and 12 March 2020, attempts were made by regional public health services in the Netherlands to contain the spread of the virus through rigorous source and contact tracing. It quickly became apparent, however, that with a rapidly growing number of active cases, each with many contacts, sustaining this intensity of response was unfeasible with existing human resources. This realisation was confirmed by the emergence of cases without a travel history to a defined high-risk country or an epidemiological link to another known case, indicating widespread domestic transmission. The Dutch government therefore implemented a series of public health regulations from 12-15 March 2020 onwards to limit ongoing community transmission, reducing the incidence of severe COVID-19 and mitigating the impact on acute hospital care. These regulations included, for instance, travel restrictions, and the closure of non-essential stores, schools, universities, and other public services to minimise social contact[48]. By 1 June 2020, the National Institute for Public Health and the Environment (RIVM) had recorded 46,000 notified cases (disproportionately hospitalised individuals tested prior to or at admission) and almost 6,000 deaths due to COVID-19[49].
Chapter 1 18 Figure 1.3. Public health regulations announced on 12 March 2020 [in Dutch][50]
General introduction 19 1 Subsequent phases of the pandemic, locally and globally Following the first surge of COVID-19 cases worldwide, numerous subsequent waves of the pandemic occurred globally. Each regional wave was characterised by specific features, owing to the constant evolution of the virus and fluctuating population immunity over time. As such, the risk-benefit balance of restrictions had to be constantly re-evaluated, recognising the impact of long-term lockdowns on mental health[51], education[52], and the economy[53]. The rise of numerous new variants of concern (VoC), each of which demonstrated changes in either transmissibility, virulence, or escape from existing immunity, required repeated epidemiological assessments. The Delta variant (Pango lineage B.1.617.2), for instance, is likely to have arisen in India[54] and was first imported in the Netherlands by young adults who had celebrated finishing high school by travelling together to Portugal and Spain. This variant caused international concern due to its increased virulence[54]. Fortunately, vaccination was repeatedly demonstrated to be effective in protecting against hospitalisation with a Delta variant infection[55]. In contrast, in December 2021, the Omicron variant (B.1.1.529) was found to have developed numerous mutations related to antibody escape[56], but less frequently led to severe disease and hospitalisation compared to the Delta variant – although elderly individuals remained at highest risk[57]. At the time of writing, a combination of viral evolution towards less virulent variants (Omicron sub-variants; Pango lineages BA.1 to XBB1.9), high levels of humoral and cellmediated immunity in the Dutch population (through natural, vaccine-derived and hybrid immunisation), and advances in the clinical management of COVID-19 patients, means that COVID-specific restrictions have been lifted in the Netherlands since March 2022[59] and replaced by general measures for the prevention of respiratory pathogens.
Chapter 1 20 Figure 1.4. Proportion of total notified COVID-19 cases in the Netherlands estimated to result from infection with SARS-CoV-2 sub-variants between December 2020 and April 2023[58] 1.3 WHAT IS ‘LONG COVID’? Origins In May 2020, the first signals that some individuals may experience persistent symptoms following COVID-19 came to light[60]. Communities on social media shared experiences of their long-term symptoms after COVID-19, which often had considerable impact on their
General introduction 21 1 ability to resume normal activities. In addition, patient-researchers (often healthcare workers who had occupational exposure to SARS-CoV-2) such as those of the Patient-Led Research Collaborative[61] aimed to ensure long COVID featured on the COVID-19 research agenda and that patients’ lived experience were reflected in research. Crucially, it became clear that individuals with long COVID were not only patients with severe or critical disease requiring mechanical ventilation in hospital (for whom persisting symptoms could be explained by post-intensive care fatigue syndrome [PICS]). Long COVID seemed to also affect young individuals with mild COVID-19 and without any pre-existing comorbidities. Although some parallels were drawn with other post-infectious fatigue syndromes (such as Lyme disease[62] or infectious mononucleosis[63]), it soon became apparent that the full constellation of symptoms experienced by long COVID patients was perhaps more complex. Definitions In December 2020, the National Institute of Health and Care Excellence (NICE) proposed one of the first clinical definitions of long COVID. NICE considered COVID-19 patients with symptoms that persisted more than 12 weeks after illness onset, which were not explained by an alternative cause, to have developed the condition[64]. The WHO soon followed, using a Delphi consensus method to characterise the condition according to a minimum duration of symptoms and the impact of the condition on quality of life[65]. Although alternative terms such as post-COVID syndrome and post-acute sequelae of COVID-19 (PASC) were introduced by researchers, the broader term ‘long COVID’ remained the preferred term for many individuals due to its origins in the patient-led research community. Challenges in researching long COVID A lack of consensus on the definition of long COVID continues to create several challenges when researching the condition. These hurdles will be discussed in more detail in the general discussion. However, it is important to keep several key concepts in mind when reading Chapter 4-8 of this thesis. Firstly, the absence of a universally adopted definition of long COVID hinders the extent to which results from different studies can be compared and consolidated. Secondly, studies differ as to which symptoms the authors consider relevant to the condition, leading to information bias between studies. The probability of a study participant reporting one or more symptoms is clearly higher when including more than 50 symptoms[66] as opposed to fewer than 10[67]. Thirdly, several different long COVID phenotypes have been described. This has led researchers to question whether long COVID represents one pathophysiological process or several different, possibly co-existing, conditions. This may account for inconsistent findings in basic science studies attempting to identify signature
Chapter 1 22 biomarkers or distinct histopathological properties for the condition. Finally, there is a striking lack of long COVID studies originating from low-resource settings, and research conducted in high-resource settings is not always representative of marginalised communities. Given these drawbacks, it is likely that we have only scratched the surface of our knowledge on long COVID. Further investigation of this ‘silent pandemic’[68] will require years of dedicated and collaborated efforts, during which time an urgent need exists for support and information for the individuals currently living with long COVID. 1.4 DATA SOURCES COVID-19 surveillance data of notified cases In Chapter 2 and Chapter 3 of this thesis, routinely collected COVID-19 notification data linked to municipality records were used. Notification data were collected as laboratories and hospitals alerted the regional Public Health Service of Amsterdam (PHSA, or “GGD Amsterdam” in Dutch) of any positive SARS-CoV-2 diagnosis, in accordance with Dutch Public Health Law (see Section 1.2). Following notification, the contact tracing team gathered additional information (such as date of illness onset, hospitalisation status, occupation) by telephone. For the purpose of our research, these notification data were consequently matched to registration data from the municipality records of the City of Amsterdam (BRP) to retrieve postal code of residence and the country of birth of a notified individual and their parents, in order to infer migration background. It is important to note that notification data, similarly to all forms of data collected via passive surveillance, are affected by selection bias. During the time period presented in Chapter 2 and Chapter 3 of this thesis (February 2020 to January 2021), for example, the criteria for eligibility for testing varied considerably. During the first COVID-19 wave, described in Chapter 2, tests were restricted to severely-ill individuals and healthcare professionals. Following 1 June 2020 (this thesis, Chapter 3), access to testing services was expanded but remained susceptible to selection bias from access and intention to testing. On the other hand, criteria for admission to hospital are based on more objective parameters and are therefore less prone (although not fully) to changes over time. We therefore utilised rates of COVID-19 hospitalisation instead of SARS-CoV-2 infection as a less biased measure by which to compare COVID-19 burden between groups. Please note that individuals with a migration background are categorised into ‘Western’ and ‘non-Western’ in Chapter 2 of this thesis, but as ‘European background’ and ‘nonEuropean background’ in Chapter 3. Around the time of data analysis, the Dutch Central Bureau for Statistics (CBS) was in the process of reclassifying migration background in order to make it more objective, focussed on the individual rather than their parents,
General introduction 23 1 durable and nuanced (with multiple sub-categories)[69]. The change in terminology used reflects our recognition in moving away from the terms ‘Western’ and ‘non-Western’ and towards the new categorisation by geographical region[70]. Many other studies on migration background in Amsterdam have chosen to override these overly broad classifications altogether and rather categorize individuals with a migration background according to the most common countries of origin (such as Ghana, Turkey, Morocco, Suriname[71-73]), in order to identify unique characteristics of each community. The RECoVERED Cohort Study Study background As the first wave of COVID-19 was unfolding in the Netherlands, researchers at the PHSA and the Amsterdam Universities Medical Centres (AUMC) had the foresight to realise that setting up a prospective cohort study of COVID-19 patients at all levels of disease severity would be the most rigorous way to investigate sequelae of this new disease. The PHSA and AUMC had extensive experience in the running of large collaborative cohort studies (such as the Amsterdam Cohort Studies on HIV[74] and the Healthy Life in an Urban Setting [HELIUS][75]), including biobanking. After securing funds, facilitated by rapid funding opportunities from the government-funded Netherlands Organisation for Health Research and Development (ZonMw), and gaining ethical approval from the local medical ethical board, the first study participant was enrolled in the RECoVERED Cohort Study on 11 May 2020. Study aims The overall aims of the RECoVERED study were to identify the viro-immunological, clinical and psychosocial sequelae of COVID-19. As knowledge of COVID-19 grew within the scientific community, specific sub-objectives with direct practical implications were additionally identified. For instance, determining the occurrence of ‘long COVID’ in our cohort and identifying baseline risk factors became a research priority once the first reports of the condition came to light. In addition, RECoVERED served as a platform through which to determine the immunological effect of COVID-19 vaccination in those with naturally-acquired immunity from previous infection[76], which was an urgent research gap during the COVID-19 vaccination campaign and led to adjustment of the national vaccination guidelines[77]. The rich dataset created through the collection of biological samples, measurement of clinical parameters such as lung function tests, and completion of numerous validated sociopsychosocial questionnaires allowed for this adaptability (Figure 1.5).
Chapter 1 24 Figure 1.5. Data collection throughout the RECoVERED Cohort Study
General introduction 25 1 Key study strengths and limitations Further key details of study design, population and data collection are presented according to an abbreviated version of the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) Checklist in Table 1 of the Appendix to Chapter 1. Whilst reading this thesis, it is important to keep several key strengths and weaknesses of the RECoVERED cohort in mind. Advantages of the study design were its inclusion across a wide spectrum of initial disease severity, collection of a broad and interdisciplinary array of outcomes, frequent (monthly) symptom questionnaires from illness onset onwards, and long follow-up time. These features enabled the RECoVERED cohort to paint a detailed picture of the long-term clinical characteristics of SARS-CoV-2 infection, from illness onset up to two years later, among both non-hospitalised and hospitalised individuals. Importantly, by identifying non-hospitalised individuals from notification data, we overcame possible selection bias resulting from health-seeking behaviour that may be introduced by enrolling persons visiting primary care clinics for their symptoms. However, our cohort also has several limitations, two of which are particularly important to highlight as they have featured prominently in academic discussions in the literature concerning long COVID research over the past three years. Firstly, the RECoVERED cohort did not enroll a SARS-CoV-2-negative control group. We therefore cannot be sure to what extent our outcomes of interest are caused by infection, by public health restrictions, or both. This limitation is particularly important when considering non-specific outcomes such as self-reported fatigue, which may have numerous co-existing causes. Secondly, as the cohort was initiated at the start of the pandemic, we lack pre-COVID-19 data on study participants’ symptoms (for instance, symptoms due to pre-existing comorbidities) and pre-infection biological samples. As such, we were unable to perform any comparative analyses before and after COVID-19 within the same individuals. These two limitations are not unique to the RECoVERED cohort; indeed, only a handful of large prospective cohort studies with pre-COVID-19 measurements and/or SARS-CoV-2-negative controls exist. This serves to highlight the challenges faced in drawing conclusions about long COVID, and will be discussed in further detail in the general discussion (this thesis, Chapter 9). 1.5 AIMS OF THESIS The overarching objective of this thesis is to outline the features of the COVID-19 pandemic in Amsterdam, the Netherlands, from both an epidemiological and clinical perspective. A particular focus is placed on characterising long COVID.
Chapter 1 26 Part 1: Epidemiological and long-term clinical features of COVID-19 in Amsterdam, the Netherlands In Part 1 of this thesis, we aim to describe the epidemiology and symptomatology of SARS-CoV-2 infection and highlight the clinical features of long COVID. In Chapters 2 and Chapter 3, differences in hospitalisation rates by city district and migration background during the first and second waves of COVID-19 in Amsterdam, the Netherlands, are evaluated. In Chapter 4, the evolution of symptoms among participants of the RECoVERED cohort study during both the acute phase and up to 12 months after illness onset are presented. Subsequently, in Chapter 5, the proportion of RECoVERED participants with severe fatigue is assessed. Part 2: In-depth characterisation of long COVID: Trajectories and possible pathogenesis In Part 2 of this thesis, we conduct an in-depth characterisation of long COVID, with an emphasis on describing trajectories of different clinical features over time, exploring possible biological mechanisms of disease, and examining the potential for COVID-19 vaccination as a treatment for long COVID. In Chapter 6, two-year trajectories of long COVID symptoms in the RECoVERED cohort, and their associated with illness perception, are presented. We then describe the association between long COVID and inflammatory markers at 3 and 6 months after illness onset in Chapter 7, and explore possible early biomarkers for ongoing long COVID at 6 months. Finally, we investigate the possible therapeutic effect of SARS-CoV-2 vaccination on long COVID symptoms in Chapter 8, supplementing this with a comparative analysis of antibody dynamics between study participants with and without long COVID. In Chapter 9, I place the findings listed above into context and highlight future research priorities stemming from the themes discussed.
General introduction 27 1 REFERENCES: 1. Piret J, Boivin G. Pandemics Throughout History. Frontiers in Microbiology 2021; 11. 2. WHO. WORKSHOP ON PRIORITIZATION OF PATHOGENS. World Health Organization (WHO) 2015; Blueprint for R&D preparedness and response to public health emergencies due to highly infectious pathogens. 3. WHO. WHO Coronavirus (COVID-19) Dashboard. 2022; World Health Organization. 4. Pro-MED. Undiagnosed pneumonia - China (HU): Request For Information, 2019 30 Dec 2019. 5. Tan W, Zhao X, Ma X, et al. A Novel Coronavirus Genome Identified in a Cluster of Pneumonia Cases - Wuhan, China 2019-2020. China CDC Wkly 2020; 2(4): 61-2. 6. Chan JF, Yuan S, Kok KH, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. (1474-547X (Electronic)). 7. WHO. Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel coronavirus (2019-nCoV). Available at: https://www.who.int/news/item/30-01-2020-statement-on-the-second-meeting-of-theinternational-health-regulations-(2005)-emergency-committee-regarding-the-outbreak-ofnovel-coronavirus-(2019-ncov). Accessed 6 June. 8. WHO. Novel Coronavirus(2019-nCoV) Situation Report - 10. Geneva, Switzerland, 2020. 9. WHO. Coronavirus disease 2019 (COVID-19) Situation Report – 101. Geneva, Switzerland, 2020 30 April 2020. 10. Gandhi M, Yokoe DS, Havlir DV. Asymptomatic Transmission, the Achilles’ Heel of Current Strategies to Control Covid-19. New England Journal of Medicine 2020; 382(22): 2158-60. 11. Cheng PK, Wong Da Fau - Tong LKL, Tong Lk Fau - Ip S-M, et al. Viral shedding patterns of coronavirus in patients with probable severe acute respiratory syndrome. (1474-547X (Electronic)). 12. Peiris JS, Chu Cm Fau - Cheng VCC, Cheng Vc Fau - Chan KS, et al. Clinical progression and viral load in a community outbreak of coronavirus-associated SARS pneumonia: a prospective study. (0140-6736 (Print)). 13. Boyton RJ, Altmann DM. The immunology of asymptomatic SARS-CoV-2 infection: what are the key questions? Nature Reviews Immunology 2021; 21(12): 762-8. 14. Mugglestone MA, Ratnaraja NV, Bak A, et al. Presymptomatic, asymptomatic and postsymptomatic transmission of SARS-CoV-2: joint British Infection Association (BIA), Healthcare Infection Society (HIS), Infection Prevention Society (IPS) and Royal College of Pathologists (RCPath) guidance. BMC Infectious Diseases 2022; 22(1): 453. 15. WHO. WHO Director-General’s opening remarks at the media briefing on COVID-19 - 11 March 2020. In: (WHO) WHO. Geneva, Switzerland, 2020. 16. Cui J, Li F, Shi Z-L. Origin and evolution of pathogenic coronaviruses. Nature Reviews Microbiology 2019; 17(3): 181-92. 17. Tao Y, Shi M, Chommanard C, et al. Surveillance of Bat Coronaviruses in Kenya Identifies Relatives of Human Coronaviruses NL63 and 229E and Their Recombination History. LID - 10.1128/JVI.01953-16 [doi] LID - e01953-16. (1098-5514 (Electronic)). 18. Hu B, Ge X, Wang L-F, Shi Z. Bat origin of human coronaviruses. Virology Journal 2015; 12(1): 221.
Chapter 1 28 19. Vijgen L, Keyaerts E Fau - Moës E, Moës E Fau - Thoelen I, et al. Complete genomic sequence of human coronavirus OC43: molecular clock analysis suggests a relatively recent zoonotic coronavirus transmission event. (0022-538X (Print)). 20. Worobey M, Levy JI, Serrano LM, et al. The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19 pandemic. Science 0(0): abp8715. 21. Zamorano Cuervo N, Grandvaux N. ACE2: Evidence of role as entry receptor for SARS-CoV-2 and implications in comorbidities. eLife 2020; 9: e61390. 22. Wan Y, Shang J, Graham R, Baric RS, Li F. Receptor Recognition by the Novel Coronavirus from Wuhan: an Analysis Based on Decade-Long Structural Studies of SARS Coronavirus. J Virol 2020; 94(7): e00127-20. 23. Baker T, Schell CO, Petersen DB, et al. Essential care of critical illness must not be forgotten in the COVID-19 pandemic. The Lancet 2020; 395(10232): 1253-4. 24. Wu Z, McGoogan JM. Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. JAMA 2020; 323(13): 1239-42. 25. Lamers MM, Haagmans BL. SARS-CoV-2 pathogenesis. Nature Reviews Microbiology 2022; 20(5): 270-84. 26. Menter TA-O, Haslbauer JD, Nienhold R, et al. Postmortem examination of COVID-19 patients reveals diffuse alveolar damage with severe capillary congestion and variegated findings in lungs and other organs suggesting vascular dysfunction. (1365-2559 (Electronic)). 27. Montazersaheb S, Hosseiniyan Khatibi SM, Hejazi MS, et al. COVID-19 infection: an overview on cytokine storm and related interventions. Virology Journal 2022; 19(1): 92. 28. WHO. Estimating mortality from COVID-19. In: (EPP) EaPPaP. Geneva, Switzerland: World Health Organization (WHO), 2020. 29. Ahammed TA-O, Anjum AA-OX, Rahman MM, Haider NA-O, Kock R, Uddin MA-O. Estimation of novel coronavirus (COVID-19) reproduction number and case fatality rate: A systematic review and meta-analysis. (2398-8835 (Electronic)). 30. Berlin DA, Gulick RM, Martinez FJ. Severe Covid-19. New England Journal of Medicine 2020; 383(25): 2451-60. 31. Iacobucci G. Covid-19: Severe infection in pregnancy significantly increases risks, study shows. BMJ 2022; 376: o480. 32. Mendez-Brito A, El Bcheraoui C, Pozo-Martin F. Systematic review of empirical studies comparing the effectiveness of non-pharmaceutical interventions against COVID-19. Journal of Infection 2021; 83(3): 281-93. 33. Threats IoMUFoM. Ethical and Legal Considerations in Mitigating Pandemic Disease: Workshop Summary. Strategies for Disease Containment. Washington (DC): National Academies Press (US), 2007. 34. Brooks SK, Webster RK, Smith LE, et al. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. The Lancet 2020; 395(10227): 912-20. 35. Group TRC. Dexamethasone in Hospitalised Patients with Covid-19. New England Journal of Medicine 2020; 384(8): 693-704. 36. Gordon AA-OX, Mouncey PA-O, Al-Beidh F, et al. Interleukin-6 Receptor Antagonists in Critically Ill Patients with Covid-19. (1533-4406 (Electronic)).
General introduction 29 1 37. Marconi VC, Ramanan AV, de Bono S, et al. Efficacy and safety of baricitinib for the treatment of hospitalised adults with COVID-19 (COV-BARRIER): a randomised, double-blind, parallel-group, placebo-controlled phase 3 trial. The Lancet Respiratory Medicine 2021; 9(12): 1407-18. 38. Beigel JH, Tomashek KM, Dodd LE, et al. Remdesivir for the Treatment of Covid-19 — Final Report. New England Journal of Medicine 2020; 383(19): 1813-26. 39. Polack FP, Thomas SJ, Kitchin N, et al. Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine. New England Journal of Medicine 2020; 383(27): 2603-15. 40. Voysey M, Costa Clemens SA, Madhi SA, et al. Single-dose administration and the influence of the timing of the booster dose on immunogenicity and efficacy of ChAdOx1 nCoV-19 (AZD1222) vaccine: a pooled analysis of four randomised trials. The Lancet 2021; 397(10277): 881-91. 41. Baden LR, El Sahly HM, Essink B, et al. Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine. New England Journal of Medicine 2020; 384(5): 403-16. 42. Watson OJ, Barnsley G, Toor J, Hogan AB, Winskill P, Ghani AC. Global impact of the first year of COVID-19 vaccination: a mathematical modelling study. The Lancet Infectious Diseases 2022; 22(9): 1293-302. 43. Lazarus JV, Karim SSA, Batista C, Rabin K, El-Mohandes A. Vaccine inequity and hesitancy persist—we must tackle both. BMJ 2023; 380: p8. 44. Bijkerk PH, G.B.; van der Plas, S.M.; Siebbeles, M.F.; Timen, A.; van ‘t Veen, A.; van Vliet, J.A.; Westerhof, G.R. Melden van infectieziekten conform de Wet publieke gezondheid (2008). Amesfoort: RIVM, 2008. Report No.: 978 90 6960 206 6. 45. Rosenbaum L. Facing Covid-19 in Italy — Ethics, Logistics, and Therapeutics on the Epidemic’s Front Line. New England Journal of Medicine 2020; 382(20): 1873-5. 46. Desson Z, Lambertz L, Peters JW, Falkenbach M, Kauer L. Europe’s Covid-19 outliers: German, Austrian and Swiss policy responses during the early stages of the 2020 pandemic. Health Policy and Technology 2020; 9(4): 405-18. 47. Man diagnosed with coronavirus (COVID-19) in the Netherlands. Ministry of Health, Welfare and Sport: Government of the Netherlands, 2020. 48. New measures to stop spread of coronavirus in the Netherlands. Ministry of Health, Welfare and Sport: Government of the Netherlands, 2020. 49. Epidemiologische situatie COVID-19 in Nederland 1 juni 2020. Ministry of Health, Welfare and Sport: Government of the Netherlands, 2020. 50. Rijksoverheid. Nieuwe maatregelen tegen verspreiding coronavirus in Nederland. 2020. 51. Santomauro DF, Mantilla Herrera AM, Shadid J, et al. Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. The Lancet 2021; 398(10312): 1700-12. 52. Garcia EW, Elaine. COVID-19 and student performance, equity, and U.S. education policy. Economic Policy Institute 2020. 53. Brodeur A, Gray D, Islam A, Bhuiyan S. A literature review of the economics of COVID-19. J Econ Surv 2021: 10.1111/joes.12423. 54. Twohig KA, Nyberg T, Zaidi A, et al. Hospital admission and emergency care attendance risk for SARS-CoV-2 delta (B.1.617.2) compared with alpha (B.1.1.7) variants of concern: a cohort study. The Lancet Infectious Diseases 2022; 22(1): 35-42.
Chapter 1 30 55. McKeigue PM, McAllister DA, Hutchinson SJ, Robertson C, Stockton D, Colhoun HM. Vaccine efficacy against severe COVID-19 in relation to delta variant (B.1.617.2) and time since second dose in patients in Scotland (REACT-SCOT): a case-control study. The Lancet Respiratory Medicine 2022; 10(6): 566-72. 56. Cao Y, Wang J, Jian F, et al. Omicron escapes the majority of existing SARS-CoV-2 neutralizing antibodies. Nature 2022; 602(7898): 657-63. 57. Auvigne V, Vaux S, Strat YL, et al. Severe hospital events following symptomatic infection with Sars-CoV-2 Omicron and Delta variants in France, December 2021–January 2022: A retrospective, population-based, matched cohort study. eClinicalMedicine 2022; 48. 58. RIVM. Variants of the coronavirus SARS-CoV-2. Accessed 9 August 2022. 59. Tijdlijn van coronamaatregelen. Ministry of Health, Welfare and Sport Vol. 2022: Government of the Netherlands, 2022. 60. Callard F, Perego E. How and why patients made Long Covid. Soc Sci Med 2021; 268: 113426-. 61. Davis HE, Assaf GS, McCorkell L, et al. Characterizing long COVID in an international cohort: 7 months of symptoms and their impact. (2589-5370 (Electronic)). 62. Steere AC, Strle F, Wormser GP, et al. Lyme borreliosis. Nature Reviews Disease Primers 2016; 2(1): 16090. 63. Hickie I, Davenport T Fau - Wakefield D, Wakefield D Fau - Vollmer-Conna U, et al. Post-infective and chronic fatigue syndromes precipitated by viral and non-viral pathogens: prospective cohort study. (1756-1833 (Electronic)). 64. Excellence NIfHaC. COVID-19 rapid guideline: managing the longterm effects of COVID-19 (NG188) - Evidence reviews 2 and 3: prevalence, 2020 18 December 2020. 65. WHO. A clinical case definition of post COVID-19 condition by a Delphi consensus. World Health Organization (WHO) clinical case definition working group on post COVID-19 condition 2021. 66. Tran V-T, Porcher R, Pane I, Ravaud P. Course of post COVID-19 disease symptoms over time in the ComPaRe long COVID prospective e-cohort. Nature Communications 2022; 13(1): 1812. 67. Blomberg B, Mohn KG-I, Brokstad KA, et al. Long COVID in a prospective cohort of home-isolated patients. Nature Medicine 2021; 27(9): 1607-13. 68. Rajan SK, Kamlesh; Alwan, Nisreen; Steves, Claire; Greenhalgh, Trish; MacDermott, Nathalie; Sagan, Anna; McKee, Martin. In the wake of the pandemic: Preparing for Long COVID - Policy Brief 39. Geneva, Switzerland: World Health Organization, 2021. 69. CBS. 3. Achtergrond van de nieuwe indeling. Available at: https://www.cbs.nl/nl-nl/longread/ statistische-trends/2022/nieuwe-indeling-bevolking-naar-herkomst/3-achtergrond-van-denieuwe-indeling. Accessed 29 May. 70. CBS. 4.2.1 Vier niveaus. Available at: https://www.cbs.nl/nl-nl/longread/statistische-trends/2022/ nieuwe-indeling-bevolking-naar-herkomst/4-de-nieuwe-indeling-naar-geboren-in-nederlanden-herkomstland. Accessed 29 May 71. Campman SLB, A.; Coyer, L.; Schinkel, J.; Agyemang, C.; Galenkamp, H.; Koopman, A.; Chilunga, F.; Schim van der Loeff, M.; van Houtum, L.; Leenstra, T.; Stronks, K.; Prins, M. SARS-CoV-2 vaccination uptake in six ethnic groups living in Amsterdam, the Netherlands (P2729). 33rd European Conferences for Clinical Microbiology and Infectious Diseases (ECCMID). Copenhagen, 2023. 72. Chilunga FA-OX, Stoeldraijer L, Agyemang C, Stronks K, Harmsen C, Kunst AE. Inequalities in COVID-19 deaths by migration background during the first wave, interwave period and second wave of the COVID-19 pandemic: a closed cohort study of 17 million inhabitants of the Netherlands. LID - jech-2022-219521 [pii] LID - 10.1136/jech-2022-219521 [doi]. (1470-2738 (Electronic)).
General introduction 31 1 73. Coyer L, Boyd A, Schinkel J, et al. SARS-CoV-2 antibody prevalence and determinants of six ethnic groups living in Amsterdam, the Netherlands: a population-based cross-sectional study, June-October 2020. medRxiv 2021: 2021.03.08.21252788. 74. van Griensven GJ, de Vroome Em Fau - Goudsmit J, Goudsmit J Fau - Coutinho RA, Coutinho RA. Changes in sexual behaviour and the fall in incidence of HIV infection among homosexual men. (0959-8138 (Print)). 75. Snijder MB, Galenkamp H, Prins M, et al. Cohort profile: the Healthy Life in an Urban Setting (HELIUS) study in Amsterdam, The Netherlands. BMJ Open 2017; 7(12): e017873. 76. van Gils MJ, van Willigen HD, Wynberg E, et al. Single-dose SARS-CoV-2 vaccine in a prospective cohort of COVID-19 patients. medRxiv 2021: 2021.05.25.21257797. 77. Met één vaccinatie beschermd na doorgemaakte COVID-19-infectie. Ministry of Health, Welfare and Sport Vol. 2022: Government of the Netherlands, 2021.
Chapter 1 32 APPENDIX TO CHAPTER 1 Table 1. Abbreviated* STROBE checklist for cohort studies, applied to the RECoVERED Cohort Study STROBE Checklist Criterion Specific recommendation RECoVERED Cohort Study Background Rationale Explain the scientific background and rationale for the investigation being reported At the early stage of the pandemic, little was known about the clinical consequences of infection with SARS-CoV-2, a novel coronavirus Objectives State specific objectives, including any prespecified hypotheses To identify the viro-immunological, clinical and psychosocial sequelae of COVID-19 Methodology Study design Present key elements of study design early in the paper • Prospective enrolment of participants (within 7 days of diagnosis or hospital admission onwards) • A minority of participants with initially severe/critical COVID-19 were enrolled no later than 3 months after illness onset, to include individuals hospitalised during the ‘first wave’ of COVID-19 in the Netherlands (27 February to 1 June 2020) • Follow-up was initially defined at 12 months, and later extended to 24 months Setting Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection • Based in Amsterdam, the Netherlands • Study visits took place at the Public Health Service of Amsterdam (PHSA) and Amsterdam University Medical Centres (AUMC – location AMC) • Participants were enrolled from 11 May 2020 to 21 June 2021 • During the first month of follow-up, data collection took place: at the participants’ home (via home visits by trained study staff) or (for hospitalised participants) on the hospital ward • Subsequent visits took place at the study sites (PHSA or AMC), were biological sampling and outcome interviews took place (Figure 1.5) • Participants additionally completed monthly online surveys and a variety of psycho-social questionnaires at different time-points (Figure 1.5)
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