What does equitable global health research and delivery look like? Tackling Infections to Benefit Africa (TIBA) partnership as a case study.

There is a current global push to identify and implement best practice for delivering maximum impact from development research in low-income and middle-income countries. Here, we describe a model of research and capacity building that challenges traditional approaches taken by western funders in Africa. Tackling Infections to Benefit Africa (TIBA) is a global health research and delivery partnership with a focus on strengthening health systems to combat neglected tropical diseases, malaria and emerging pathogens in Africa. Partners are academic and research institutions based in Ghana, Sudan, Rwanda, Uganda, Kenya, Tanzania, Zimbabwe, Botswana, South Africa and the UK. Fifteen other African countries have participated in TIBA activities. With a starting budget of under £7 million, and in just 4 years, TIBA has had a verified impact on knowledge, policy practice and capacity building, and on national and international COVID-19 responses in multiple African countries. TIBA's impact is shown in context-specific metrics including: strengthening the evidence base underpinning international policy on neglected tropical diseases; 77% of research publications having Africa-based first and/or last authors; postgraduate, postdoctoral and professional training; career progression for African researchers and health professionals with no net brain drain from participating countries; and supporting African institutions. Training in real-time SARS-CoV-2 viral genome sequencing provided new national capabilities and capacities that contributed to both national responses and global health security through variant detection and tracking. TIBA's experience confirms that health research for Africa thrives when the agenda and priorities are set in Africa, by Africans, and the work is done in Africa. Here, we share 10 actionable recommendations for researchers and funders from our lessons learnt.

Peptide microarray IgM and IgG screening of pre-SARS-CoV-2 human serum samples from Zimbabwe for reactivity with peptides from all seven human coronaviruses: a cross-sectional study

Summary Background SARS-CoV-2 infections and deaths have been lower in Africa than in other continents, which could be attributed to previous exposure to other pathogens that induce protective cross-immunity or modify the immune phenotype. We aimed to identify and characterise pre-existing cross-reactive immune responses to SARS-CoV-2 in an African population. Methods In this cross-sectional study, we determined the prevalence of SARS-CoV-2 serological cross-reactivity of 339 previously collected pre-pandemic (2000–19) serum samples from adults living in four villages in Zimbabwe (Mupfure, Mutoko, Chiredzi, and Murewa). We tested samples with a COVID-19 rapid diagnostic test then screened for cross-reactivity with peptides from the proteomes of seven human coronaviruses. We compared peptide location, coverage, and intensity and matched peptides predicted to be B-cell epitopes to the Human Immune Epitope Database (HIED). Findings Pre-SARS-CoV-2 serum samples from Mupfure and Murewa showed an overall prevalence of cross-reactivity with the SARS-CoV-2 rapid diagnostic test of 31·9% (95% CI 26·93–37·11). Peptide analysis of samples from all four villages highlighted complex IgM and IgG response profiles against peptides in the spike, nucleocapsid, and polyprotein 1AB proteins across all coronaviruses. Interrogating SARS-CoV-2 peptides recognised by IgG and IgM from the Zimbabwean serum samples against the HIED showed that most were either unique to SARS-CoV-2 or shared only with other betacoronaviruses. However, some SARS-CoV-2 peptides shared motifs with antigens from pathogens endemic to Zimbabwe, including Trypanosoma spp and Plasmodium spp, plant and food immunogens, and human autoantigens. Interpretation The effect of these cross-reactive antibodies on SARS-CoV-2 infection or COVID-19 is unknown;however, these antibodies should be considered when interpreting SARS-CoV-2 seroepidemiology studies and evaluating outcomes of COVID-19 vaccine trials in Africa. This study also calls for further characterisation of SARs-CoV-2 immune phenotypes and responses in African populations. Funding Scottish Funding Council Global Challenges Research Fund Grant at the University of Edinburgh;UK National Institute for Health Research.

Predictors of human-infective RNA virus discovery in the United States, China, and Africa, an ecological study.

Background: The variation in the pathogen type as well as the spatial heterogeneity of predictors make the generality of any associations with pathogen discovery debatable. Our previous work confirmed that the association of a group of predictors differed across different types of RNA viruses, yet there have been no previous comparisons of the specific predictors for RNA virus discovery in different regions. The aim of the current study was to close the gap by investigating whether predictors of discovery rates within three regions-the United States, China, and Africa-differ from one another and from those at the global level. Methods: Based on a comprehensive list of human-infective RNA viruses, we collated published data on first discovery of each species in each region. We used a Poisson boosted regression tree (BRT) model to examine the relationship between virus discovery and 33 predictors representing climate, socio-economics, land use, and biodiversity across each region separately. The discovery probability in three regions in 2010-2019 was mapped using the fitted models and historical predictors. Results: The numbers of human-infective virus species discovered in the United States, China, and Africa up to 2019 were 95, 80, and 107 respectively, with China lagging behind the other two regions. In each region, discoveries were clustered in hotspots. BRT modelling suggested that in all three regions RNA virus discovery was better predicted by land use and socio-economic variables than climatic variables and biodiversity, although the relative importance of these predictors varied by region. Map of virus discovery probability in 2010-2019 indicated several new hotspots outside historical high-risk areas. Most new virus species since 2010 in each region (6/6 in the United States, 19/19 in China, 12/19 in Africa) were discovered in high-risk areas as predicted by our model. Conclusions: The drivers of spatiotemporal variation in virus discovery rates vary in different regions of the world. Within regions virus discovery is driven mainly by land-use and socio-economic variables; climate and biodiversity variables are consistently less important predictors than at a global scale. Potential new discovery hotspots in 2010-2019 are identified. Results from the study could guide active surveillance for new human-infective viruses in local high-risk areas. Funding: FFZ is funded by the Darwin Trust of Edinburgh (https://darwintrust.bio.ed.ac.uk/). MEJW has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 874735 (VEO) (https://www.veo-europe.eu/).

Impact on emergency and elective hospital-based care in Scotland over the first 12 months of the pandemic: interrupted time-series analysis of national lockdowns.

OBJECTIVES: COVID-19 has resulted in the greatest disruption to National Health Service (NHS) care in its over 70-year history. Building on our previous work, we assessed the ongoing impact of pandemic-related disruption on provision of emergency and elective hospital-based care across Scotland over the first year of the pandemic. DESIGN: We undertook interrupted time-series analyses to evaluate the impact of ongoing pandemic-related disruption on hospital NHS care provision at national level and across demographics and clinical specialties spanning the period 29 March 2020-28 March 2021. SETTING: Scotland, UK. PARTICIPANTS: Patients receiving hospital care from NHS Scotland. MAIN OUTCOME MEASURES: We used the percentage change of accident and emergency attendances, and emergency and planned hospital admissions during the pandemic compared to the average admission rate for equivalent weeks in 2018-2019. RESULTS: As restrictions were gradually lifted in Scotland after the first lockdown, hospital-based admissions increased approaching pre-pandemic levels. Subsequent tightening of restrictions in September 2020 were associated with a change in slope of relative weekly admissions rate: -1.98% (-2.38, -1.58) in accident and emergency attendance, -1.36% (-1.68, -1.04) in emergency admissions and -2.31% (-2.95, -1.66) in planned admissions. A similar pattern was seen across sex, socioeconomic status and most age groups, except children (0-14 years) where accident and emergency attendance, and emergency admissions were persistently low over the study period. CONCLUSIONS: We found substantial disruption to urgent and planned inpatient healthcare provision in hospitals across NHS Scotland. There is the need for urgent policy responses to address continuing unmet health needs and to ensure resilience in the context of future pandemics.

Severity of omicron variant of concern and effectiveness of vaccine boosters against symptomatic disease in Scotland (EAVE II): a national cohort study with nested test-negative design.

BACKGROUND: Since its emergence in November, 2021, in southern Africa, the SARS-CoV-2 omicron variant of concern (VOC) has rapidly spread across the world. We aimed to investigate the severity of omicron and the extent to which booster vaccines are effective in preventing symptomatic infection. METHODS: In this study, using the Scotland-wide Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) platform, we did a cohort analysis with a nested test-negative design incident case-control study covering the period Nov 1-Dec 19, 2021, to provide initial estimates of omicron severity and the effectiveness of vaccine boosters against symptomatic disease relative to 25 weeks or more after the second vaccine dose. Primary care data derived from 940 general practices across Scotland were linked to laboratory data and hospital admission data. We compared outcomes between infection with the delta VOC (defined as S-gene positive) and the omicron VOC (defined as S-gene negative). We assessed effectiveness against symptomatic SARS-CoV-2 infection, with infection confirmed through a positive RT-PCR. FINDINGS: By Dec 19, 2021, there were 23 840 S-gene-negative cases in Scotland, which were predominantly among those aged 20-39 years (11 732 [49·2%]). The proportion of S-gene-negative cases that were possible reinfections was more than ten times that of S-gene-positive cases (7·6% vs 0·7%; p<0·0001). There were 15 hospital admissions in S-gene-negative individuals, giving an adjusted observed-to-expected admissions ratio of 0·32 (95% CI 0·19-0·52). The booster vaccine dose was associated with a 57% (54-60) reduction in the risk of symptomatic S-gene-negative infection relative to individuals who tested positive 25 weeks or more after the second vaccine dose. INTERPRETATION: These early national data suggest that omicron is associated with a two-thirds reduction in the risk of COVID-19 hospitalisation compared with delta. Although offering the greatest protection against delta, the booster dose of vaccination offers substantial additional protection against the risk of symptomatic COVID-19 for omicron compared with 25 weeks or more after the second vaccine dose. FUNDING: Health Data Research UK, National Core Studies, Public Health Scotland, Scottish Government, UK Research and Innovation, and University of Edinburgh.

Adaptation, spread and transmission of SARS-CoV-2 in farmed minks and associated humans in the Netherlands.

In the first wave of the COVID-19 pandemic (April 2020), SARS-CoV-2 was detected in farmed minks and genomic sequencing was performed on mink farms and farm personnel. Here, we describe the outbreak and use sequence data with Bayesian phylodynamic methods to explore SARS-CoV-2 transmission in minks and humans on farms. High number of farm infections (68/126) in minks and farm workers (>50% of farms) were detected, with limited community spread. Three of five initial introductions of SARS-CoV-2 led to subsequent spread between mink farms until November 2020. Viruses belonging to the largest cluster acquired an amino acid substitution in the receptor binding domain of the Spike protein (position 486), evolved faster and spread longer and more widely. Movement of people and distance between farms were statistically significant predictors of virus dispersal between farms. Our study provides novel insights into SARS-CoV-2 transmission between mink farms and highlights the importance of combining genetic information with epidemiological information when investigating outbreaks at the animal-human interface.

Association between multimorbidity and mortality in a cohort of patients admitted to hospital with COVID-19 in Scotland.

OBJECTIVES: We investigated the association between multimorbidity among patients hospitalised with COVID-19 and their subsequent risk of mortality. We also explored the interaction between the presence of multimorbidity and the requirement for an individual to shield due to the presence of specific conditions and its association with mortality. DESIGN: We created a cohort of patients hospitalised in Scotland due to COVID-19 during the first wave (between 28 February 2020 and 22 September 2020) of the pandemic. We identified the level of multimorbidity for the patient on admission and used logistic regression to analyse the association between multimorbidity and risk of mortality among patients hospitalised with COVID-19. SETTING: Scotland, UK. PARTICIPANTS: Patients hospitalised due to COVID-19. MAIN OUTCOME MEASURES: Mortality as recorded on National Records of Scotland death certificate and being coded for COVID-19 on the death certificate or death within 28 days of a positive COVID-19 test. RESULTS: Almost 58% of patients admitted to the hospital due to COVID-19 had multimorbidity. Adjusting for confounding factors of age, sex, social class and presence in the shielding group, multimorbidity was significantly associated with mortality (adjusted odds ratio 1.48, 95%CI 1.26-1.75). The presence of multimorbidity and presence in the shielding patients list were independently associated with mortality but there was no multiplicative effect of having both (adjusted odds ratio 0.91, 95%CI 0.64-1.29). CONCLUSIONS: Multimorbidity is an independent risk factor of mortality among individuals who were hospitalised due to COVID-19. Individuals with multimorbidity could be prioritised when making preventive policies, for example, by expanding shielding advice to this group and prioritising them for vaccination.

COVID-19 hospital admissions and deaths after BNT162b2 and ChAdOx1 nCoV-19 vaccinations in 2·57 million people in Scotland (EAVE II): a prospective cohort study.

BACKGROUND: The UK COVID-19 vaccination programme has prioritised vaccination of those at the highest risk of COVID-19 mortality and hospitalisation. The programme was rolled out in Scotland during winter 2020-21, when SARS-CoV-2 infection rates were at their highest since the pandemic started, despite social distancing measures being in place. We aimed to estimate the frequency of COVID-19 hospitalisation or death in people who received at least one vaccine dose and characterise these individuals. METHODS: We conducted a prospective cohort study using the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) national surveillance platform, which contained linked vaccination, primary care, RT-PCR testing, hospitalisation, and mortality records for 5·4 million people (around 99% of the population) in Scotland. Individuals were followed up from receiving their first dose of the BNT162b2 (Pfizer-BioNTech) or ChAdOx1 nCoV-19 (Oxford-AstraZeneca) COVID-19 vaccines until admission to hospital for COVID-19, death, or the end of the study period on April 18, 2021. We used a time-dependent Poisson regression model to estimate rate ratios (RRs) for demographic and clinical factors associated with COVID-19 hospitalisation or death 14 days or more after the first vaccine dose, stratified by vaccine type. FINDINGS: Between Dec 8, 2020, and April 18, 2021, 2 572 008 individuals received their first dose of vaccine-841 090 (32·7%) received BNT162b2 and 1 730 918 (67·3%) received ChAdOx1. 1196 (<0·1%) individuals were admitted to hospital or died due to COVID-19 illness (883 hospitalised, of whom 228 died, and 313 who died due to COVID-19 without hospitalisation) 14 days or more after their first vaccine dose. These severe COVID-19 outcomes were associated with older age (≥80 years vs 18-64 years adjusted RR 4·75, 95% CI 3·85-5·87), comorbidities (five or more risk groups vs less than five risk groups 4·24, 3·34-5·39), hospitalisation in the previous 4 weeks (3·00, 2·47-3·65), high-risk occupations (ten or more previous COVID-19 tests vs less than ten previous COVID-19 tests 2·14, 1·62-2·81), care home residence (1·63, 1·32-2·02), socioeconomic deprivation (most deprived quintile vs least deprived quintile 1·57, 1·30-1·90), being male (1·27, 1·13-1·43), and being an ex-smoker (ex-smoker vs non-smoker 1·18, 1·01-1·38). A history of COVID-19 before vaccination was protective (0·40, 0·29-0·54). INTERPRETATION: COVID-19 hospitalisations and deaths were uncommon 14 days or more after the first vaccine dose in this national analysis in the context of a high background incidence of SARS-CoV-2 infection and with extensive social distancing measures in place. Sociodemographic and clinical features known to increase the risk of severe disease in unvaccinated populations were also associated with severe outcomes in people receiving their first dose of vaccine and could help inform case management and future vaccine policy formulation. FUNDING: UK Research and Innovation (Medical Research Council), Research and Innovation Industrial Strategy Challenge Fund, Scottish Government, and Health Data Research UK.

Predictors of COVID-19 epidemics in countries of the World Health Organization African Region.

Countries of the World Health Organization (WHO) African Region have experienced a wide range of coronavirus disease 2019 (COVID-19) epidemics. This study aimed to identify predictors of the timing of the first COVID-19 case and the per capita mortality in WHO African Region countries during the first and second pandemic waves and to test for associations with the preparedness of health systems and government pandemic responses. Using a region-wide, country-based observational study, we found that the first case was detected earlier in countries with more urban populations, higher international connectivity and greater COVID-19 test capacity but later in island nations. Predictors of a high first wave per capita mortality rate included a more urban population, higher pre-pandemic international connectivity and a higher prevalence of HIV. Countries rated as better prepared and having more resilient health systems were worst affected by the disease, the imposition of restrictions or both, making any benefit of more stringent countermeasures difficult to detect. Predictors for the second wave were similar to the first. Second wave per capita mortality could be predicted from that of the first wave. The COVID-19 pandemic highlights unanticipated vulnerabilities to infectious disease in Africa that should be taken into account in future pandemic preparedness planning.

Optimizing time-limited non-pharmaceutical interventions for COVID-19 outbreak control.

Retrospective analyses of the non-pharmaceutical interventions (NPIs) used to combat the ongoing COVID-19 outbreak have highlighted the potential of optimizing interventions. These optimal interventions allow policymakers to manage NPIs to minimize the epidemiological and human health impacts of both COVID-19 and the intervention itself. Here, we use a susceptible-infectious-recovered (SIR) mathematical model to explore the feasibility of optimizing the duration, magnitude and trigger point of five different NPI scenarios to minimize the peak prevalence or the attack rate of a simulated UK COVID-19 outbreak. An optimal parameter space to minimize the peak prevalence or the attack rate was identified for each intervention scenario, with each scenario differing with regard to how reductions to transmission were modelled. However, we show that these optimal interventions are fragile, sensitive to epidemiological uncertainty and prone to implementation error. We highlight the use of robust, but suboptimal interventions as an alternative, with these interventions capable of mitigating the peak prevalence or the attack rate over a broader, more achievable parameter space, but being less efficacious than theoretically optimal interventions. This work provides an illustrative example of the concept of intervention optimization across a range of different NPI strategies. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Segmentation and shielding of the most vulnerable members of the population as elements of an exit strategy from COVID-19 lockdown.

This study demonstrates that an adoption of a segmenting and shielding strategy could increase the scope to partially exit COVID-19 lockdown while limiting the risk of an overwhelming second wave of infection. We illustrate this using a mathematical model that segments the vulnerable population and their closest contacts, the 'shielders'. Effects of extending the duration of lockdown and faster or slower transition to post-lockdown conditions and, most importantly, the trade-off between increased protection of the vulnerable segment and fewer restrictions on the general population are explored. Our study shows that the most important determinants of outcome are: (i) post-lockdown transmission rates within the general and between the general and vulnerable segments; (ii) fractions of the population in the vulnerable and shielder segments; (iii) adherence to protective measures; and (iv) build-up of population immunity. Additionally, we found that effective measures in the shielder segment, e.g. intensive routine screening, allow further relaxations in the general population. We find that the outcome of any future policy is strongly influenced by the contact matrix between segments and the relationships between physical distancing measures and transmission rates. This strategy has potential applications for any infectious disease for which there are defined proportions of the population who cannot be treated or who are at risk of severe outcomes. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Real-time monitoring of COVID-19 in Scotland.

BACKGROUND: To manage the public health risk posed by COVID-19 and assess the impact of interventions, policymakers must be able to closely monitor the epidemic's trajectory. METHODS: Here we present a simple methodology based on basic surveillance metrics for monitoring the spread of COVID-19 and its burden on health services in Scotland. RESULTS: We examine how the dynamics of the epidemic have changed over time and assess the similarities and differences between metrics. DISCUSSION: We illustrate how our method has been used throughout the epidemic in Scotland, explore potential biases and conclude that our method has proven to be an effective tool for monitoring the epidemic's trajectory.

Interim findings from first-dose mass COVID-19 vaccination roll-out and COVID-19 hospital admissions in Scotland: a national prospective cohort study.

BACKGROUND: The BNT162b2 mRNA (Pfizer-BioNTech) and ChAdOx1 nCoV-19 (Oxford-AstraZeneca) COVID-19 vaccines have shown high efficacy against disease in phase 3 clinical trials and are now being used in national vaccination programmes in the UK and several other countries. Studying the real-world effects of these vaccines is an urgent requirement. The aim of our study was to investigate the association between the mass roll-out of the first doses of these COVID-19 vaccines and hospital admissions for COVID-19. METHODS: We did a prospective cohort study using the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19-EAVE II-database comprising linked vaccination, primary care, real-time reverse transcription-PCR testing, and hospital admission patient records for 5·4 million people in Scotland (about 99% of the population) registered at 940 general practices. Individuals who had previously tested positive were excluded from the analysis. A time-dependent Cox model and Poisson regression models with inverse propensity weights were fitted to estimate effectiveness against COVID-19 hospital admission (defined as 1-adjusted rate ratio) following the first dose of vaccine. FINDINGS: Between Dec 8, 2020, and Feb 22, 2021, a total of 1 331 993 people were vaccinated over the study period. The mean age of those vaccinated was 65·0 years (SD 16·2). The first dose of the BNT162b2 mRNA vaccine was associated with a vaccine effect of 91% (95% CI 85-94) for reduced COVID-19 hospital admission at 28-34 days post-vaccination. Vaccine effect at the same time interval for the ChAdOx1 vaccine was 88% (95% CI 75-94). Results of combined vaccine effects against hospital admission due to COVID-19 were similar when restricting the analysis to those aged 80 years and older (83%, 95% CI 72-89 at 28-34 days post-vaccination). INTERPRETATION: Mass roll-out of the first doses of the BNT162b2 mRNA and ChAdOx1 vaccines was associated with substantial reductions in the risk of hospital admission due to COVID-19 in Scotland. There remains the possibility that some of the observed effects might have been due to residual confounding. FUNDING: UK Research and Innovation (Medical Research Council), Research and Innovation Industrial Strategy Challenge Fund, Health Data Research UK.

Vaccines That Reduce Viral Shedding Do Not Prevent Transmission of H1N1 Pandemic 2009 Swine Influenza A Virus Infection to Unvaccinated Pigs.

Swine influenza A virus (swIAV) infection causes substantial economic loss and disease burden in humans and animals. The 2009 pandemic H1N1 (pH1N1) influenza A virus is now endemic in both populations. In this study, we evaluated the efficacy of different vaccines in reducing nasal shedding in pigs following pH1N1 virus challenge. We also assessed transmission from immunized and challenged pigs to naive, directly in-contact pigs. Pigs were immunized with either adjuvanted, whole inactivated virus (WIV) vaccines or virus-vectored (ChAdOx1 and MVA) vaccines expressing either the homologous or heterologous influenza A virus hemagglutinin (HA) glycoprotein, as well as an influenza virus pseudotype (S-FLU) vaccine expressing heterologous HA. Only two vaccines containing homologous HA, which also induced high hemagglutination inhibitory antibody titers, significantly reduced virus shedding in challenged animals. Nevertheless, virus transmission from challenged to naive, in-contact animals occurred in all groups, although it was delayed in groups of vaccinated animals with reduced virus shedding.IMPORTANCE This study was designed to determine whether vaccination of pigs with conventional WIV or virus-vectored vaccines reduces pH1N1 swine influenza A virus shedding following challenge and can prevent transmission to naive in-contact animals. Even when viral shedding was significantly reduced following challenge, infection was transmissible to susceptible cohoused recipients. This knowledge is important to inform disease surveillance and control strategies and to determine the vaccine coverage required in a population, thereby defining disease moderation or herd protection. WIV or virus-vectored vaccines homologous to the challenge strain significantly reduced virus shedding from directly infected pigs, but vaccination did not completely prevent transmission to cohoused naive pigs.

Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II): protocol for an observational study using linked Scottish national data.

INTRODUCTION: Following the emergence of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019 and the ensuing COVID-19 pandemic, population-level surveillance and rapid assessment of the effectiveness of existing or new therapeutic or preventive interventions are required to ensure that interventions are targeted to those at highest risk of serious illness or death from COVID-19. We aim to repurpose and expand an existing pandemic reporting platform to determine the attack rate of SARS-CoV-2, the uptake and effectiveness of any new pandemic vaccine (once available) and any protective effect conferred by existing or new antimicrobial drugs and other therapies. METHODS AND ANALYSIS: A prospective observational cohort will be used to monitor daily/weekly the progress of the COVID-19 epidemic and to evaluate the effectiveness of therapeutic interventions in approximately 5.4 million individuals registered in general practices across Scotland. A national linked dataset of patient-level primary care data, out-of-hours, hospitalisation, mortality and laboratory data will be assembled. The primary outcomes will measure association between: (A) laboratory confirmed SARS-CoV-2 infection, morbidity and mortality, and demographic, socioeconomic and clinical population characteristics; and (B) healthcare burden of COVID-19 and demographic, socioeconomic and clinical population characteristics. The secondary outcomes will estimate: (A) the uptake (for vaccines only); (B) effectiveness; and (C) safety of new or existing therapies, vaccines and antimicrobials against SARS-CoV-2 infection. The association between population characteristics and primary outcomes will be assessed via multivariate logistic regression models. The effectiveness of therapies, vaccines and antimicrobials will be assessed from time-dependent Cox models or Poisson regression models. Self-controlled study designs will be explored to estimate the risk of therapeutic and prophylactic-related adverse events. ETHICS AND DISSEMINATION: We obtained approval from the National Research Ethics Service Committee, Southeast Scotland 02. The study findings will be presented at international conferences and published in peer-reviewed journals.