Population age as a key factor in the COVID-19 pandemic dynamics (preprint)

The population and governments of many countries are losing interest in the SARS-CoV-2 infection, the number of tests and the number of new cases detected is sharply decreasing. To compare the accumulated numbers CC of cases and deaths DC per million and to answer the question why the less vaccinated Africa has accumulated 36 times lower CC values and 15 times lower DC values than Europe, simple statistical analysis have been performed. CC and DC values demonstrated rather strong correlation with the median age of populations. One-year increment in the median year yields 12-18 thousand increase in CC values and 52-83 increase in DC values. Zero-COVID countries succeed to have much lower numbers of deaths per capita and case fatality ratios DC/CC.

Scenario modelling for diminished influenza seasons during 2020/2021 and 2021/2022 in England (preprint)

Background There has been concern throughout the COVID-19 pandemic over highly stressed healthcare capacities being further pressured by seasonal influenza epidemics. Interventions to tackle the spread of SARS-CoV-2, the causative agent of COVID-19, have unsettled the respiratory pathogen landscape, including worldwide patterns of influenza activity. The implications of these disruptions for subsequent influenza seasons has been uncertain. Methods To conduct scenario analyses ahead of the 2020/2021 and 2021/2022 influenza seasons in England, we used a pre-existing age-structured, multi-strain compartmental model of influenza transmission and case severity, which included propagation of immunity between influenza seasons and had been previously fit to historical data. For the pre-2020/2021 influenza season, our scenarios varied the level of vaccine uptake and the inclusion/exclusion of nonpharmaceutical interventions (NPIs). We estimated the relative amount of health episode occurrences: symptomatic cases resulting in a GP consultation, hospital inpatient admissions, fatalities. In the pre-2021/2022 influenza season analysis, compared with a counterfactual case where influenza activity remained at historic levels in the 2020/2021 influenza season, we estimated the change in the same set of health episode occurrences in the 2021/2022 influenza season when assuming there was no influenza in circulation during the 2020/2021 influenza season. Results Attaining coverage of 75% in target groups for the 2020/2021 influenza season reduced health episode occurrences by 40–50% when compared to maintaining the 2019/2020 vaccination programme coverage and uptake levels. Having NPIs maintained throughout the entire influenza season saw 60-80% reductions in severe case outcomes. Combining an expanded vaccination programme and the use of NPIs could suppress the seasonal influenza epidemic, with reductions as much as 90–100%. In the absence of influenza transmission during the 2020/2021 influenza season, under our modelling assumption of mixing patterns returning to pre-2020 levels we projected a compensatory influenza epidemic with 1.2 to 2.2 times as many severe health episode occurrences in the subsequent 2021/2022 influenza season. Conclusions In the context of the time the work was originally conducted, the modelled scenarios indicated how bolstering vaccine coverage and reduction in contacts could likely allay resurgent seasonal influenza epidemics. Our analyses of the winter pressures that may be inflicted by other respiratory infections during the COVID-19 pandemic are one example of the modelling insights provided to the Scientific Pandemic Influenza Group on Modelling, Operational sub-group (SPI-M-O) for the Scientific Advisory Group for Emergencies (SAGE) in the UK.

Patterns of Reported Infection and Reinfection of SARS-CoV-2 in England (preprint)

One of the key features of any infectious disease is whether infection generates long-lasting immunity or whether repeated reinfection is common. In the former, the long-term dynamics are driven by the birth of susceptible individuals while in the latter the dynamics are governed by the speed of waning immunity. Between these two extremes a range of scenarios is possible. During the early waves of SARS-CoV-2, the underlying paradigm was for long-lasting immunity, but more recent data and in particular the 2022 Omicron waves have shown that reinfection can be relatively common. Here we investigate reported SARS-CoV-2 cases in England, partitioning the data into four main waves, and consider the temporal distribution of first and second reports of infection. We show that a simple low-dimensional statistical model of random (but scaled) reinfection captures much of the observed dynamics, with the value of this scaling, k , providing information of underlying epidemiological patterns. We conclude that there is considerable heterogeneity in risk of reporting reinfection by wave, age-group and location. The high levels of reinfection in the Omicron wave (we estimate that 18% of all Omicron cases had been previously infected, although not necessarily previously reported infection) point to reinfection events dominating future COVID-19 dynamics.

Epidemiological impact and cost-effectiveness analysis of COVID-19 vaccination in Kenya (preprint)

ABSTRACT Background Few studies have assessed the benefits of COVID-19 vaccines in settings where most of the population had been exposed to SARS-CoV-2 infection. Methods We conducted a cost-effectiveness analysis of COVID-19 vaccine in Kenya from a societal perspective over a 1.5-year time frame. An age-structured transmission model assumed at least 80% of the population to have prior natural immunity when an immune escape variant was introduced. We examine the effect of slow (18 months) or rapid (6 months) vaccine roll-out with vaccine coverage of 30%, 50% or 70% of the adult (> 18 years) population prioritizing roll-out in over 50-year olds (80% uptake in all scenarios). Cost data were obtained from primary analyses. We assumed vaccine procurement at $7 per dose and vaccine delivery costs of $3.90-$6.11 per dose. The cost-effectiveness threshold was USD 919. Findings Slow roll-out at 30% coverage largely targets over 50-year-olds and resulted in 54% fewer deaths (8,132(7,914 to 8,373)) than no vaccination and was cost-saving (ICER=US$-1,343 (-1,345 to - 1,341) per DALY averted). Increasing coverage to 50% and 70%, further reduced deaths by 12% (810 (757 to 872) and 5% (282 (251 to 317) but was not cost-effective, using Kenya’s cost-effectiveness threshold ($ 919.11). Rapid roll-out with 30% coverage averted 63% more deaths and was more cost-saving (ICER=$-1,607 (-1,609 to -1,604) per DALY averted) compared to slow roll-out at the same coverage level, but 50% and 70% coverage scenarios were not cost-effective. Interpretation With prior exposure partially protecting much of the Kenyan population, vaccination of young adults may no longer be cost-effective. KEY QUESTIONS What is already known? The COVID-19 pandemic has led to a substantial number of cases and deaths in low-and middle-income countries. COVID-19 vaccines are considered the main strategy of curtailing the pandemic. However, many African nations are still at the early phase of vaccination. Evidence on the cost-effectiveness of COVID-19 vaccines are useful in estimating value for money and illustrate opportunity costs. However, there is a need to balance these economic outcomes against the potential impact of vaccination. What are the new findings? In Kenya, a targeted vaccination strategy that prioritizes those of an older age and is deployed at a rapid rollout speed achieves greater marginal health impacts and is better value for money. Given the existing high-level population protection to COVID-19 due to prior exposure, vaccination of younger adults is less cost-effective in Kenya. What do the new findings imply? Rapid deployment of vaccines during a pandemic averts more cases, hospitalisations, and deaths and is more cost-effective. Against a context of constrained fiscal space for health, it is likely more prudent for Kenya to target those at severe risk of disease and possibly other vulnerable populations rather than to the whole population.

Comparison of the 2021 COVID-19 Roadmap Projections against Public Health Data in England (preprint)

Control and mitigation of the COVID-19 pandemic in England has relied on a combination of vaccination and non-pharmaceutical interventions (NPIs). Some of these NPIs are extremely costly (economically and socially), so it was important to relax these promptly without overwhelming already burdened health services. The eventual policy was a Roadmap of four relaxation steps throughout 2021, taking England from lock-down to the cessation of all restrictions on social interaction. In a series of six Roadmap documents generated throughout 2021, models assessed the potential risk of each relaxation step. Here we show that the model projections generated a reliable estimation of medium-term hospital admission trends, with the data points up to September 2021 generally lying within our 95% prediction intervals. The greatest uncertainties in the modelled scenarios came from vaccine efficacy estimates against novel variants, and from assumptions about human behaviour in the face of changing restrictions and risk.

An assessment of the vaccination of school-aged children in England (preprint)

Background Children and young persons are known to have a high number of close interactions, often within the school environment, which can facilitate rapid spread of infection; yet for SARS-CoV-2 it is the elderly and vulnerable that suffer the greatest health burden. Vaccination, initially targeting the elderly and vulnerable but later expanded to the entire adult population, has been transformative in the control of SARS-CoV-2 in England. However, early concerns over adverse events and the lower risk associated with infection in younger individuals means that the expansion of the vaccine programme to those under 18 year of age needs to be rigorously and quantitatively assessed. Methods Here, using a bespoke mathematical model matched to case and hospital data for England, we consider the potential impact of vaccinating 12-17 and 5-11 year olds. This analysis is reported from an early model (generated in June 2021) that formed part of the evidence base for the decisions in England, and a later model (from November 2021) that benefits from a richer understanding of vaccine efficacy, greater knowledge of the Delta variant wave and uses data on the rate of vaccine administration. For both models we consider the population wide impact of childhood vaccination as well as the specific impact on the age-group targeted for vaccination. Results Projections from June suggested that an expansion of the vaccine programme to those 12-17 years old could generate substantial reductions in infection, hospital admission and deaths in the entire population, depending on population behaviour following the relaxation of control measures. The benefits within the 12-17 year old cohort were less marked, saving between 656 and 1077 (95% prediction interval 281-2260) hospital admissions and between 22 and 38 (95% PI 9-91) deaths depending on assumed population behaviour. For the more recent model, the benefits within this age group are reduced, saving on average 631 (95% PI 304-1286) hospital admissions and 11 (95% PI 5-28) deaths for 80% vaccine uptake, while the benefits to the wider population represent a reduction of 8-10% in hospital admissions and deaths. The vaccination of 5-11 year olds is projected to have a far smaller impact, in part due to the later roll-out of vaccines to this age-group. Conclusions Vaccination of 12-17 year olds and 5-11 year olds is projected to generate a reduction in infection, hospital admission and deaths for both the age-groups involved and the population in general. For any decision involving childhood vaccination, these benefits needs to be balanced against potential adverse events from the vaccine, the operational constraints on delivery and the potential for diverting resources from other public health campaigns.

Short-term Projections based on Early Omicron Variant Dynamics in England (preprint)

Throughout the ongoing COVID-19 pandemic, the worldwide transmission and replication of SARS-COV-2, the causative agent of COVID-19 disease, has resulted in the opportunity for multiple mutations to occur that may alter the virus transmission characteristics, the effectiveness of vaccines and the severity of disease upon infection. The Omicron variant (B.1.1.529) was first reported to the WHO by South Africa on 24 November 2021 and was declared a variant of concern by the WHO on 26 November 2021. The variant was first detected in the UK on 27 November 2021 and has since been reported in a number of countries globally where it is frequently associated with rapid increase in cases. Here we present analyses of UK data showing the earliest signatures of the Omicron variant and mathematical modelling that uses the UK data to simulate the potential impact of this variant in the UK. In order to account for the uncertainty in transmission advantage, vaccine escape and severity at the time of writing, we carry out a sensitivity analysis to assess the impact of these variant characteristics on future risk.

Waning, Boosting and a Path to Endemicity for SARS-CoV-2 (preprint)

In many countries, an extensive vaccination programme has substantially reduced the public-health impact of SARS-CoV-2, limiting the number of hospital admissions and deaths compared to an unmitigated epidemic. Ensuring a low-risk transition from the current situation to one in which SARS-CoV-2 is endemic requires maintenance of high levels of population immunity. The observed waning of vaccine efficacy over time suggests that booster doses may be required to maintain population immunity especially in the most vulnerable groups. Here, using data and models for England, we consider the dynamics of COVID-19 over a two-year time-frame, and the role that booster vaccinations can play in mitigating the worst effects. We find that boosters are necessary to suppress the imminent wave of infections that would be generated by waning vaccine efficacy. Projecting further into the future, the optimal deployment of boosters is highly sensitive to their long-term action. If protection from boosters wanes slowly (akin to protection following infection) then a single booster dose to the over 50s may be all that is needed over the next two-years. However, if protection wanes more rapidly (akin to protection following second dose vaccination) then annual or even biannual boosters are required to limit subsequent epidemic peaks an reduce the pressure on public health services.

Cluster detection with random neighbourhood covering: application to invasive Group A Streptococcal disease (preprint)

The rapid detection of outbreaks is a key step in the effective control and containment of infectious diseases. In particular, the identification of cases which might be epidemiologically linked is crucial in directing outbreak-containment efforts shaping the intervention of public health authorities. Often this requires the detection of clusters of cases whose numbers exceed those expected by a background of sporadic cases. Quantifying exceedances rapidly is particularly challenging when only few cases are typically reported in a precise location and time. To address such important public health concerns, we present a general method which can detect spatio-temporal deviations from a Poisson point process and estimate the odd of an isolate being part of a cluster. This method can be applied to diseases where detailed geographical information is available. In addition, we propose an approach to explicitly take account of delays in microbial typing. As a case study, we considered invasive group A Streptococcus infection events as recorded and typed by Public Health England from 2015 to 2020.

Quantifying within-school SARS-CoV-2 transmission and the impact of lateral flow testing in secondary schools in England (preprint)

Background To control within-school SARS-CoV-2 transmission in England, secondary school pupils have been encouraged to participate in twice weekly mass testing via lateral flow device tests (LFTs) from 8th March 2021, to complement an isolation of close contacts policy in place since 31st August 2020. Strategies involving the isolation of close contacts can lead to high levels of absences, negatively impacting pupils. Methods We fit a stochastic individual-based model of secondary schools to both community swab testing data and secondary school absences data. By simulating epidemics in secondary schools from 31st August 2020 until 21st May 2021, we quantify within-school transmission of SARS-CoV-2 in secondary schools in England, the impact of twice weekly mass testing on within-school transmission, and the potential impact of alternative strategies to the isolation of close contacts in reducing pupil absences. Findings The within-school reproduction number, R school , has remained below 1 from 31st August 2020 until 21st May 2021. Twice weekly mass testing using LFTs have helped to control within-school transmission in secondary schools in England. A strategy of serial contact testing alongside mass testing substantially reduces absences compared to strategies involving isolating close contacts, with only a marginal increase in within-school transmission. Interpretation Secondary school control strategies involving mass testing have the potential to control within-school transmission while substantially reducing absences compared to an isolation of close contacts policy.

COVID-19 Transmission Dynamics Underlying Epidemic Waves in Kenya (preprint)

Policy decisions on COVID-19 interventions should be informed by a local, regional and national understanding of SARS-CoV-2 transmission. Epidemic waves may result when restrictions are lifted or poorly adhered to, variants with new phenotypic properties successfully invade, or when infection spreads to susceptible sub-populations. Three COVID-19 epidemic waves have been observed in Kenya. Using a mechanistic mathematical model we explain the first two distinct waves by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of a new higher-transmissibility variant. Reopening schools led to a minor increase in transmission between the second and third waves. Our predictions of current population exposure in Kenya (∼75% June 1st) have implications for a fourth wave and future control strategies. One Sentence Summary COVID-19 spread in Kenya is explained by mixing heterogeneity and a variant less constrained by high population exposure

Coughs, Colds and “Freshers’ Flu” Survey in the University of Cambridge, 2007-2008 (preprint)

Universities provide many opportunities for the spread of infectious respiratory illnesses. Students are brought together into close proximity from all across the world and interact with one another in their accommodation, through lectures and small group teaching and in social settings. The COVID-19 global pandemic has highlighted the need for sufficient data to help determine which of these factors are important for infectious disease transmission in universities and hence control university morbidity as well as community spillover. We describe the data from a previously unpublished self-reported university survey of coughs, colds and flu-like symptoms collected in Cambridge, UK, during winter 2007-2008. The online survey collected information on symptoms and socio-demographic, academic and lifestyle factors. There were 1076 responses, 97% from University of Cambridge students (5.7% of the total university student population), 3% from staff and <1% from other participants, reporting onset of symptoms between September 2007 and March 2008. Undergraduates are seen to report symptoms earlier in the term than postgraduates; differences in reported date of symptoms are also seen between subjects and accommodation types, although these descriptive results could be confounded by survey biases. Despite the historic and exploratory nature of the study, this is one of few recent detailed datasets of flu-like infection in a university context and is especially valuable to share now to improve understanding of potential transmission dynamics in universities during the current COVID-19 pandemic.

Comparison between one and two dose SARS-CoV-2 vaccine prioritisation for a fixed number of vaccine doses (preprint)

The swift development of SARS-CoV-2 vaccines has been met with worldwide commendation. How-ever, in the context of an ongoing pandemic there is an interplay between infection and vaccination. Whilst infection can grow exponentially, vaccination rates are generally limited by supply and logistics. With the first SARS-CoV-2 vaccines receiving medical approval requiring two doses, there has been scrutiny on the spacing between doses; an elongated period between doses allows more of the population to receive a first vaccine dose in the short-term generating wide-spread partial immunity. Focusing on data from England, we investigated prioritisation of a one dose or two dose vaccination schedule given a fixed number of vaccine doses and with respect to a measure of maximising averted deaths. We optimised outcomes for two different estimates of population size and relative risk of mortality for at-risk groups within the Phase 1 vaccine priority order. Vaccines offering relatively high protection from the first dose favour strategies that prioritise giving more people one dose, although with increasing vaccine supply eventually those eligible and accepting vaccination will receive two doses. Whilst optimal dose timing can substantially reduce the overall mortality risk, there needs to be careful consideration of the logistics of vaccine delivery.

Vaccination and Non-Pharmaceutical Interventions: When Can the UK Relax About COVID-19? (preprint)

Background: The announcement of efficacious vaccine candidates against SARS-CoV-2 has been met with worldwide acclaim and relief. Many countries already have detailed plans for vaccine targeting based on minimising severe illness, death and healthcare burdens. Normally, relatively simple relationships between epidemiological parameters, vaccine efficacy and vaccine uptake predict the success of any immunisation programme. However, the dynamics of vaccination against SARS-CoV-2 is made more complex by age-dependent factors, changing levels of infection and the potential relaxation of non-pharmaceutical interventions (NPIs) as the perceived risk declines. Methods: In this study we use an age-structured mathematical model, matched to a range of epidemiological data, which also captures the roll-out of a two-dose vaccination programme targeted at specific age groups. Findings: We consider the interaction between the UK vaccination programme and future re- laxation (or removal) of NPIs. Our predictions highlight the population-level risks of early relaxation leading to a pronounced wave of infection, hospital admissions and deaths. Only vaccines that offer high transmission-blocking efficacy with high uptake in the general population allow relaxation of NPIs without a huge surge in deaths. Interpretation: While the novel vaccines against SARS-CoV-2 offer a potential exit strategy for this outbreak, this is highly contingent on the transmission blocking action of the vaccine and the population uptake, both of which need to be carefully monitored as vaccine programmes are rolled out in the UK and other countries.Funding Statement: This research was funded by the National Institute for Health Research (NIHR) [Policy Research Programme, Mathematical & Economic Modelling for Vaccination and Immunisation Evaluation, and Emergency Response; NIHR200411], the Medical Research Council through the COVID- 19 Rapid Response Rolling Call [grant number MR/V009761/1] and through the JUNIPER modelling consortium [grant number EP/V030477/1]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Declaration of Interests: All authors declare that they have no competing interests.Ethics Approval Statement: The data were supplied from the CHESS database after anonymisation under strict data protection protocols agreed between the University of Warwick and Public Health England. The ethics of the use of these data for these purposes was agreed by Public Health England with the Government’s SPI-M(O) / SAGE committees.

Vaccination and Non-Pharmaceutical Interventions: When can the UK relax about COVID-19? (preprint)

Summary Background The announcement of efficacious vaccine candidates against SARS-CoV-2 has been met with worldwide acclaim and relief. Many countries already have detailed plans for vaccine targeting based on minimising severe illness, death and healthcare burdens. Normally, relatively simple relationships between epidemiological parameters, vaccine efficacy and vaccine uptake predict the success of any immunisation programme. However, the dynamics of vaccination against SARS-CoV-2 is made more complex by age-dependent factors, changing levels of infection and the potential relaxation of non-pharmaceutical interventions (NPIs) as the perceived risk declines. Methods In this study we use an age-structured mathematical model, matched to a range of epidemiological data in the UK, that also captures the roll-out of a two-dose vaccination programme targeted at specific age groups. Findings We consider the interaction between the UK vaccination programme and future relaxation (or removal) of NPIs. Our predictions highlight the population-level risks of early relaxation leading to a pronounced wave of infection, hospital admissions and deaths. Only vaccines that offer high infection-blocking efficacy with high uptake in the general population allow relaxation of NPIs without a huge surge in deaths. Interpretation While the novel vaccines against SARS-CoV-2 offer a potential exit strategy for this outbreak, this is highly contingent on the infection-blocking (or transmission-blocking) action of the vaccine and the population uptake, both of which need to be carefully monitored as vaccine programmes are rolled out in the UK and other countries. Research in context Evidence before this study Vaccination has been seen as a key tool in the fight against SARS-CoV-2. The vaccines already developed represent a major technological achievement and have been shown to generate significant immune responses, as well as offering considerable protection against disease. However, to date there is limited information on the degree of infection-blocking these vaccines are likely to induce. Mathematical models have already successfully been used to consider age- and risk-structured targeting of vaccination, highlighting the importance of prioritising older and high-risk individuals. Added value of this study Translating current knowledge and uncertainty of vaccine behaviour into meaningful public health messages requires models that fully capture the within-country epidemiology as well as the complex roll-out of a two-dose vaccination programme. We show that under reasonable assumptions for vaccine efficacy and uptake the UK is unlikely to reach herd immunity, which means that non-pharmaceutical interventions cannot be released without generating substantial waves of infection. Implications of all the available evidence Vaccination is likely to provide substantial individual protection to those receiving two doses, but the degree of protection to the wider population is still uncertain. While substantial immunisation of the most vulnerable groups will allow for some relaxation of controls, this must be done gradually to prevent large scale public health consequences.

Key Questions for Modelling COVID-19 Exit Strategies (preprint)

Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.

Forecasting the scale of the COVID-19 epidemic in Kenya (preprint)

Background The first COVID-19 case in Kenya was confirmed on March 13th, 2020. Here, we provide forecasts for the potential incidence rate, and magnitude, of a COVID-19 epidemic in Kenya based on the observed growth rate and age distribution of confirmed COVID-19 cases observed in China, whilst accounting for the demographic and geographic dissimilarities between China and Kenya. Methods We developed a modelling framework to simulate SARS-CoV-2 transmission in Kenya, KenyaCoV. KenyaCoV was used to simulate SARS-CoV-2 transmission both within, and between, different Kenyan regions and age groups. KenyaCoV was parameterized using a combination of human mobility data between the defined regions, the recent 2019 Kenyan census, and estimates of age group social interaction rates specific to Kenya. Key epidemiological characteristics such as the basic reproductive number and the age-specific rate of developing COVID-19 symptoms after infection with SARS-CoV-2, were adapted for the Kenyan setting from a combination of published estimates and analysis of the age distribution of cases observed in the Chinese outbreak. Results We find that if person-to-person transmission becomes established within Kenya, identifying the role of subclinical, and therefore largely undetected, infected individuals is critical to predicting and containing a very significant epidemic. Depending on the transmission scenario our reproductive number estimates for Kenya range from 1.78 (95% CI 1.44 - 2.14) to 3.46 (95% CI 2.81-4.17). In scenarios where asymptomatic infected individuals are transmitting significantly, we expect a rapidly growing epidemic which cannot be contained only by case isolation. In these scenarios, there is potential for a very high percentage of the population becoming infected (median estimates: >80% over six months), and a significant epidemic of symptomatic COVID-19 cases. Exceptional social distancing measures can slow transmission, flattening the epidemic curve, but the risk of epidemic rebound after lifting restrictions is predicted to be high.