Mark Jit
Mark Jit
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Chair and Professor of the Department of Global and Environmental Health
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Professional overview
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Mark Jit is the inaugural chair and a professor in the Department of Global and Environmental Health. He was formerly head of the Department of Infectious Disease Epidemiology & Dynamics and co-director of the Global Health Economics Centre (GHECO) at the London School of Hygiene & Tropical Medicine (LSHTM). He holds honorary appointments at LSHTM as well as the University of Hong Kong (HKU) and the National University of Singapore (NUS).
Dr. Jit’s research focuses on epidemiological and economic modeling of vaccines to support evidence-based public health decision making. He has published papers covering a range of vaccine-preventable or potentially vaccine-preventable diseases including COVID-19, measles, HPV, pneumococcus, rotavirus, influenza, Group B Streptococcus, dengue, EV71 and RSV as well as methodological papers advancing the ways vaccines are evaluated. This work has influenced many of the major changes to immunization policy in countries around the world. Dr. Jit has served on a number of expert advisory committees in the UK as well as for international organizations such as the World Health Organization. He also organises or contributes to academic and professional courses on vaccine modeling, economics and decision science around the world.
Dr. Jit received his BSc and PhD in Mathematics from University College London, specializing in mathematical biology, and a Master of Public Health degree from King’s College London.
Visit Dr. Jit's Google Scholar's page to learn more about his research portfolio.
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Education
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BSc, Mathematics, University College LondonPhD, Mathematics, University College LondonMPH, Public Health, King's College London
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Honors and awards
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Clarivate Highly Cited Researcher (20222023)Fellow of the Academy of Medical Sciences (2023)Training Fund Award, Health Protection Agency (2007)Andrew Rosen Prize, University College London (1999)Institute of Mathematics and its Applications Award (1998)Departmental Research Studentship, University College London (1998)Student Union Commendation, University College London (1997)Fillon Prize, University College London (1996)Pathfinder Award, University College London (1995)
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Publications
Publications
Changes in social contacts in England during the COVID-19 pandemic between March 2020 and March 2021 as measured by the CoMix survey: A repeated cross-sectional study
Failed generating bibliography.AbstractPublication year
2022Journal title
PLoS MedicineVolume
19Issue
3AbstractBackground During: the Coronavirus Disease 2019 (CAU OVID-19): pandemic, the United Kingdom government imposed public health policies in England to reduce social contacts in hopes of curbing virus transmission. We conducted a repeated cross-sectional study to measure contact patterns weekly from March 2020 to March 2021 to estimate the impact of these policies, covering 3 national lockdowns interspersed by periods of less restrictive policies. Methods and findings The repeated cross-sectional survey data were collected using online surveys of representative samples of the UK population by age and gender. Survey participants were recruited by the online market research company Ipsos MORI through internet-based banner and social media ads and email campaigns. The participant data used for this analysis are restricted to those who reported living in England. We calculated the mean daily contacts reported using a (clustered) bootstrap and fitted a censored negative binomial model to estimate age-stratified contact matrices and estimate proportional changes to the basic reproduction number under controlled conditions using the change in contacts as a scaling factor. To put the findings in perspective, we discuss contact rates recorded throughout the year in terms of previously recorded rates from the POLYMOD study social contact study. The survey recorded 101,350 observations from 19,914 participants who reported 466,710 contacts over 53 weeks. We observed changes in social contact patterns in England over time and by participants’ age, personal risk factors, and perception of risk. The mean reported contacts for adults 18 to 59 years old ranged between 2.39 (95% confidence interval [CI] 2.20 to 2.60) contacts and 4.93 (95% CI 4.65 to 5.19) contacts during the study period. The mean contacts for school-age children (5 to 17 years old) ranged from 3.07 (95% CI 2.89 to 3.27) to 15.11 (95% CI 13.87 to 16.41). This demonstrates a sustained decrease in social contacts compared to a mean of 11.08 (95% CI 10.54 to 11.57) contacts per participant in all age groups combined as measured by the POLYMOD social contact study in 2005 to 2006. Contacts measured during periods of lockdowns were lower than in periods of eased social restrictions. The use of face coverings outside the home has remained high since the government mandated use in some settings in July 2020. The main limitations of this analysis are the potential for selection bias, as participants are recruited through internet-based campaigns, and recall bias, in which participants may under- or over-report the number of contacts they have made.Comparative assessment of methods for short-term forecasts of COVID-19 hospital admissions in England at the local level
Failed generating bibliography.AbstractPublication year
2022Journal title
BMC MedicineVolume
20Issue
1AbstractBackground: Forecasting healthcare demand is essential in epidemic settings, both to inform situational awareness and facilitate resource planning. Ideally, forecasts should be robust across time and locations. During the COVID-19 pandemic in England, it is an ongoing concern that demand for hospital care for COVID-19 patients in England will exceed available resources. Methods: We made weekly forecasts of daily COVID-19 hospital admissions for National Health Service (NHS) Trusts in England between August 2020 and April 2021 using three disease-agnostic forecasting models: a mean ensemble of autoregressive time series models, a linear regression model with 7-day-lagged local cases as a predictor, and a scaled convolution of local cases and a delay distribution. We compared their point and probabilistic accuracy to a mean-ensemble of them all and to a simple baseline model of no change from the last day of admissions. We measured predictive performance using the weighted interval score (WIS) and considered how this changed in different scenarios (the length of the predictive horizon, the date on which the forecast was made, and by location), as well as how much admissions forecasts improved when future cases were known. Results: All models outperformed the baseline in the majority of scenarios. Forecasting accuracy varied by forecast date and location, depending on the trajectory of the outbreak, and all individual models had instances where they were the top- or bottom-ranked model. Forecasts produced by the mean-ensemble were both the most accurate and most consistently accurate forecasts amongst all the models considered. Forecasting accuracy was improved when using future observed, rather than forecast, cases, especially at longer forecast horizons. Conclusions: Assuming no change in current admissions is rarely better than including at least a trend. Using confirmed COVID-19 cases as a predictor can improve admissions forecasts in some scenarios, but this is variable and depends on the ability to make consistently good case forecasts. However, ensemble forecasts can make forecasts that make consistently more accurate forecasts across time and locations. Given minimal requirements on data and computation, our admissions forecasting ensemble could be used to anticipate healthcare needs in future epidemic or pandemic settings.Comparing human and model-based forecasts of COVID-19 in Germany and Poland
Failed generating bibliography.AbstractPublication year
2022Journal title
PLoS computational biologyVolume
18Issue
9AbstractForecasts based on epidemiological modelling have played an important role in shaping public policy throughout the COVID-19 pandemic. This modelling combines knowledge about infectious disease dynamics with the subjective opinion of the researcher who develops and refines the model and often also adjusts model outputs. Developing a forecast model is difficult, resource- and time-consuming. It is therefore worth asking what modelling is able to add beyond the subjective opinion of the researcher alone. To investigate this, we analysed different real-time forecasts of cases of and deaths from COVID-19 in Germany and Poland over a 1-4 week horizon submitted to the German and Polish Forecast Hub. We compared crowd forecasts elicited from researchers and volunteers, against a) forecasts from two semi-mechanistic models based on common epidemiological assumptions and b) the ensemble of all other models submitted to the Forecast Hub. We found crowd forecasts, despite being overconfident, to outperform all other methods across all forecast horizons when forecasting cases (weighted interval score relative to the Hub ensemble 2 weeks ahead: 0.89). Forecasts based on computational models performed comparably better when predicting deaths (rel. WIS 1.26), suggesting that epidemiological modelling and human judgement can complement each other in important ways.Considering equity in priority setting using transmission models: Recommendations and data needs
AbstractQuaife, M., Medley, G. F., Jit, M., Drake, T., Asaria, M., Van Baal, P., Baltussen, R., Bollinger, L., Bozzani, F., Brady, O., Broekhuizen, H., Chalkidou, K., Chi, Y. L., Dowdy, D. W., Griffin, S., Haghparast-Bidgoli, H., Hallett, T., Hauck, K., Hollingsworth, T. D., … Gomez, G. B. (n.d.).Publication year
2022Journal title
EpidemicsVolume
41AbstractObjectives: Disease transmission models are used in impact assessment and economic evaluations of infectious disease prevention and treatment strategies, prominently so in the COVID-19 response. These models rarely consider dimensions of equity relating to the differential health burden between individuals and groups. We describe concepts and approaches which are useful when considering equity in the priority setting process, and outline the technical choices concerning model structure, outputs, and data requirements needed to use transmission models in analyses of health equity. Methods: We reviewed the literature on equity concepts and approaches to their application in economic evaluation and undertook a technical consultation on how equity can be incorporated in priority setting for infectious disease control. The technical consultation brought together health economists with an interest in equity-informative economic evaluation, ethicists specialising in public health, mathematical modellers from various disease backgrounds, and representatives of global health funding and technical assistance organisations, to formulate key areas of consensus and recommendations. Results: We provide a series of recommendations for applying the Reference Case for Economic Evaluation in Global Health to infectious disease interventions, comprising guidance on 1) the specification of equity concepts; 2) choice of evaluation framework; 3) model structure; and 4) data needs. We present available conceptual and analytical choices, for example how correlation between different equity- and disease-relevant strata should be considered dependent on available data, and outline how assumptions and data limitations can be reported transparently by noting key factors for consideration. Conclusions: Current developments in economic evaluations in global health provide a wide range of methodologies to incorporate equity into economic evaluations. Those employing infectious disease models need to use these frameworks more in priority setting to accurately represent health inequities. We provide guidance on the technical approaches to support this goal and ultimately, to achieve more equitable health policies.Cost-effectiveness of Respiratory Syncytial Virus Disease Prevention Strategies: Maternal Vaccine Versus Seasonal or Year-Round Monoclonal Antibody Program in Norwegian Children
AbstractLi, X., Bilcke, J., Fernández, L. V., Bont, L., Willem, L., Wisløff, T., Jit, M., & Beutels, P. (n.d.).Publication year
2022Journal title
Journal of Infectious DiseasesVolume
226Page(s)
S95-S101AbstractBackground. Every winter, respiratory syncytial virus (RSV) disease results in thousands of cases in Norwegian children under 5 years of age. We aim to assess the RSV-related economic burden and the cost-effectiveness of upcoming RSV disease prevention strategies including year-round maternal immunization and year-round and seasonal monoclonal antibody (mAb) programs. Methods. Epidemiological and cost data were obtained from Norwegian national registries, while quality-adjusted life-years (QALYs) lost and intervention characteristics were extracted from literature and phase 3 clinical trials. A static model was used and uncertainty was accounted for probabilistically. Value of information was used to assess decision uncertainty. Extensive scenario analyses were conducted, including accounting for long-term consequences of RSV disease. Results. We estimate an annual average of 13 517 RSV cases and 1572 hospitalizations in children under 5, resulting in 79.6 million Norwegian kroner (~€8 million) treatment costs. At €51 per dose for all programs, a 4-month mAb program for neonates born in November to February is the cost-effective strategy for willingness to pay (WTP) values up to €40 000 per QALY gained. For higher WTP values, the longer 6-month mAb program that immunizes neonates from October to March becomes cost-effective. Sensitivity analyses show that year-round maternal immunization can become a cost-effective strategy if priced lower than mAb. Conclusions. Assuming the same pricing, seasonal mAb programs are cost-effective over year-round programs in Norway. The timing and duration of the cost-effective seasonal program are sensitive to the pattern of the RSV season in a country, so continued RSV surveillance data are essential.COVID-19 impact on routine immunisations for vaccine-preventable diseases: Projecting the effect of different routes to recovery
AbstractToor, J., Li, X., Jit, M., Trotter, C. L., Echeverria-Londono, S., Hartner, A. M., Roth, J., Portnoy, A., Abbas, K., Ferguson, N. M., & AM Gaythorpe, K. (n.d.).Publication year
2022Journal title
VaccineVolume
40Issue
31Page(s)
4142-4149AbstractOver the past two decades, vaccination programmes for vaccine-preventable diseases (VPDs) have expanded across low- and middle-income countries (LMICs). However, the rise of COVID-19 resulted in global disruption to routine immunisation activities. Such disruptions could have a detrimental effect on public health, leading to more deaths from VPDs, particularly without mitigation efforts. Hence, as routine immunisation activities resume, it is important to estimate the effectiveness of different approaches for recovery. We apply an impact extrapolation method developed by the Vaccine Impact Modelling Consortium to estimate the impact of COVID-19-related disruptions with different recovery scenarios for ten VPDs across 112 LMICs. We focus on deaths averted due to routine immunisations occurring in the years 2020–2030 and investigate two recovery scenarios relative to a no-COVID-19 scenario. In the recovery scenarios, we assume a 10% COVID-19-related drop in routine immunisation coverage in the year 2020. We then linearly interpolate coverage to the year 2030 to investigate two routes to recovery, whereby the immunization agenda (IA2030) targets are reached by 2030 or fall short by 10%. We estimate that falling short of the IA2030 targets by 10% leads to 11.26% fewer fully vaccinated persons (FVPs) and 11.34% more deaths over the years 2020–2030 relative to the no-COVID-19 scenario, whereas, reaching the IA2030 targets reduces these proportions to 5% fewer FVPs and 5.22% more deaths. The impact of the disruption varies across the VPDs with diseases where coverage expands drastically in future years facing a smaller detrimental effect. Overall, our results show that drops in routine immunisation coverage could result in more deaths due to VPDs. As the impact of COVID-19-related disruptions is dependent on the vaccination coverage that is achieved over the coming years, the continued efforts of building up coverage and addressing gaps in immunity are vital in the road to recovery.Date of introduction and epidemiologic patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Mogadishu, Somalia: Estimates from transmission modelling of satellite-based excess mortality data in 2020
AbstractKoltai, M., Checchi, F., Warsame, A., Bashiir, F., Freemantle, T., Reeve, C., Williams, C., Jit, M., Flasche, S., Davies, N. G., Aweis, A., Ahmed, M., & Dalmar, A. (n.d.).Publication year
2022Journal title
Wellcome Open ResearchVolume
6AbstractBackground: In countries with weak surveillance systems, confirmed coronavirus disease 2019 (COVID-19) deaths are likely to underestimate the pandemic's death toll. Many countries also have incomplete vital registration systems, hampering excess mortality estimation. Here, we fitted a dynamic transmission model to satellite imagery data of cemeteries in Mogadishu, Somalia during 2020 to estimate the date of introduction and other epidemiologic parameters of the early spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in this low-income, crisis-affected setting. Methods: We performed Markov chain Monte Carlo (MCMC) fitting with an age-structured compartmental COVID-19 model to provide median estimates and credible intervals for the date of introduction, the basic reproduction number ( R 0 ) and the effect of non-pharmaceutical interventions (NPIs) up to August 2020. Results: Under the assumption that excess deaths in Mogadishu March-August 2020 were attributable to SARS-CoV-2 infections, we arrived at median estimates of November-December 2019 for the date of introduction and low R 0 estimates (1.4-1.7) reflecting the slow and early rise and long plateau of excess deaths. The date of introduction, the amount of external seeding, the infection fatality rate (IFR) and the effectiveness of NPIs are correlated parameters and not separately identifiable in a narrow range from deaths data. Nevertheless, to obtain introduction dates no earlier than November 2019 a higher population-wide IFR (≥0.7%) had to be assumed than obtained by applying age-specific IFRs from high-income countries to Somalia's age structure. Conclusions: Model fitting of excess mortality data across a range of plausible values of the IFR and the amount of external seeding suggests an early SARS-CoV-2 introduction event may have occurred in Somalia in November-December 2019. Transmissibility in the first epidemic wave was estimated to be lower than in European settings. Alternatively, there was another, unidentified source of sustained excess mortality in Mogadishu from March to August 2020.Determinants of RSV epidemiology following suppression through pandemic contact restrictions
AbstractKoltai, M., Krauer, F., Hodgson, D., Van Leeuwen, E., Treskova-Schwarzbach, M., Jit, M., & Flasche, S. (n.d.).Publication year
2022Journal title
EpidemicsVolume
40AbstractIntroduction: COVID-19 related non-pharmaceutical interventions (NPIs) led to a suppression of RSV circulation in winter 2020/21 in the UK and an off-season resurgence in Summer 2021. We explore how the parameters of RSV epidemiology shape the size and dynamics of post-suppression resurgence and what we can learn about them from the resurgence patterns observed so far. Methods: We developed an age-structured dynamic transmission model of RSV and sampled the parameters governing RSV seasonality, infection susceptibility and post-infection immunity, retaining simulations fitting the UK's pre-pandemic epidemiology by a set of global criteria consistent with likelihood calculations. From Spring 2020 to Summer 2021 we assumed a reduced contact frequency, returning to pre-pandemic levels from Spring 2021. We simulated transmission forwards until 2023 and evaluated the impact of the sampled parameters on the projected trajectories of RSV hospitalisations and compared these to the observed resurgence. Results: Simulations replicated an out-of-season resurgence of RSV in 2021. If unmitigated, paediatric RSV hospitalisation incidence in the 2021/22 season was projected to increase by 30–60% compared to pre-pandemic levels. The increase was larger if infection risk was primarily determined by immunity acquired from previous exposure rather than age-dependent factors, exceeding 90 % and 130 % in 1–2 and 2–5 year old children, respectively. Analysing the simulations replicating the observed early outbreak in 2021 in addition to pre-pandemic RSV data, we found they were characterised by weaker seasonal forcing, stronger age-dependence of infection susceptibility and higher baseline transmissibility. Conclusion: COVID-19 mitigation measures in the UK stopped RSV circulation in the 2020/21 season and generated immunity debt leading to an early off-season RSV epidemic in 2021. A stronger dependence of infection susceptibility on immunity from previous exposure increases the size of the resurgent season. The early onset of the RSV resurgence in 2021, its marginally increased size relative to previous seasons and its decline by January 2022 suggest a stronger dependence of infection susceptibility on age-related factors, as well as a weaker effect of seasonality and a higher baseline transmissibility. The pattern of resurgence has been complicated by contact levels still not back to pre-pandemic levels. Further fitting of RSV resurgence in multiple countries incorporating data on contact patterns will be needed to further narrow down these parameters and to better predict the pathogen's future trajectory, planning for a potential expansion of new immunisation products against RSV in the coming years.Differential health impact of intervention programs for time-varying disease risk: a measles vaccination modeling study
AbstractPortnoy, A., Hsieh, Y. L., Abbas, K., Klepac, P., Santos, H., Brenzel, L., Jit, M., & Ferrari, M. (n.d.).Publication year
2022Journal title
BMC MedicineVolume
20Issue
1AbstractBackground: Dynamic modeling is commonly used to evaluate direct and indirect effects of interventions on infectious disease incidence. The risk of secondary outcomes (e.g., death) attributable to infection may depend on the underlying disease incidence targeted by the intervention. Consequently, the impact of interventions (e.g., the difference in vaccination and no-vaccination scenarios) on secondary outcomes may not be proportional to the reduction in disease incidence. Here, we illustrate the estimation of the impact of vaccination on measles mortality, where case fatality ratios (CFRs) are a function of dynamically changing measles incidence. Methods: We used a previously published model of measles CFR that depends on incidence and vaccine coverage to illustrate the effects of (1) assuming higher CFR in “no-vaccination” scenarios, (2) time-varying CFRs over the past, and (3) time-varying CFRs in future projections on measles impact estimation. We used modeled CFRs in alternative scenarios to estimate measles deaths from 2000 to 2030 in 112 low- and middle-income countries using two models of measles transmission: Pennsylvania State University (PSU) and DynaMICE. We evaluated how different assumptions on future vaccine coverage, measles incidence, and CFR levels in “no-vaccination” scenarios affect the estimation of future deaths averted by measles vaccination. Results: Across 2000–2030, when CFRs are separately estimated for the “no-vaccination” scenario, the measles deaths averted estimated by PSU increased from 85.8% with constant CFRs to 86.8% with CFRs varying 2000–2018 and then held constant or 85.9% with CFRs varying across the entire time period and by DynaMICE changed from 92.0 to 92.4% or 91.9% in the same scenarios, respectively. By aligning both the “vaccination” and “no-vaccination” scenarios with time-variant measles CFR estimates, as opposed to assuming constant CFRs, the number of deaths averted in the vaccination scenarios was larger in historical years and lower in future years. Conclusions: To assess the consequences of health interventions, impact estimates should consider the effect of “no-intervention” scenario assumptions on model parameters, such as measles CFR, in order to project estimated impact for alternative scenarios according to intervention strategies and investment decisions.Dosing interval strategies for two-dose COVID-19 vaccination in 13 middle-income countries of Europe: Health impact modelling and benefit-risk analysis
Failed generating bibliography.AbstractPublication year
2022Journal title
The Lancet Regional Health - EuropeVolume
17AbstractBackground: In settings where the COVID-19 vaccine supply is constrained, extending the intervals between the first and second doses of the COVID-19 vaccine may allow more people receive their first doses earlier. Our aim is to estimate the health impact of COVID-19 vaccination alongside benefit-risk assessment of different dosing intervals in 13 middle-income countries (MICs) of Europe. Methods: We fitted a dynamic transmission model to country-level daily reported COVID-19 mortality in 13 MICs in Europe (Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Georgia, Republic of Moldova, Russian Federation, Serbia, North Macedonia, Turkey, and Ukraine). A vaccine product with characteristics similar to those of the Oxford/AstraZeneca COVID-19 (AZD1222) vaccine was used in the base case scenario and was complemented by sensitivity analyses around efficacies similar to other COVID-19 vaccines. Both fixed dosing intervals at 4, 8, 12, 16, and 20 weeks and dose-specific intervals that prioritise specific doses for certain age groups were tested. Optimal intervals minimise COVID-19 mortality between March 2021 and December 2022. We incorporated the emergence of variants of concern (VOCs) into the model and conducted a benefit-risk assessment to quantify the tradeoff between health benefits versus adverse events following immunisation. Findings: In all countries modelled, optimal strategies are those that prioritise the first doses among older adults (60+ years) or adults (20+ years), which lead to dosing intervals longer than six months. In comparison, a four-week fixed dosing interval may incur 10.1% [range: 4.3% - 19.0%; n = 13 (countries)] more deaths. The rapid waning of the immunity induced by the first dose (i.e. with means ranging 60-120 days as opposed to 360 days in the base case) resulted in shorter optimal dosing intervals of 8-20 weeks. Benefit-risk ratios were the highest for fixed dosing intervals of 8-12 weeks. Interpretation: We infer that longer dosing intervals of over six months could reduce COVID-19 mortality in MICs of Europe. Certain parameters, such as rapid waning of first-dose induced immunity and increased immune escape through the emergence of VOCs, could significantly shorten the optimal dosing intervals. Funding: World Health Organization.Effectiveness of a pay-it-forward intervention compared with user-paid vaccination to improve influenza vaccine uptake and community engagement among children and older adults in China: a quasi-experimental pragmatic trial
AbstractWu, D., Jin, C., Bessame, K., Tang, F. F. Y., Ong, J. J., Wang, Z., Xie, Y., Jit, M., Larson, H. J., Chantler, T., Lin, L., Gong, W., Yang, F., Jing, F., Wei, S., Cheng, W., Zhou, Y., Ren, N., Qiu, S., … Tucker, J. D. (n.d.).Publication year
2022Journal title
The Lancet Infectious DiseasesVolume
22Issue
10Page(s)
1484-1492AbstractBackground: China has low seasonal influenza vaccination rates among priority populations. In this study, we aimed to evaluate a pay-it-forward strategy to increase influenza vaccine uptake in rural, suburban, and urban settings in China. Methods: We performed a quasi-experimental pragmatic trial to examine the effectiveness of a pay-it-forward intervention (a free influenza vaccine and an opportunity to donate financially to support vaccination of other individuals) to increase influenza vaccine uptake compared with standard-of-care user-paid vaccination among children (aged between 6 months and 8 years) and older people (≥60 years) in China. Recruitment took place in the standard-of-care group until the expected sample size was reached and then in the pay-it-forward group in primary care clinics from a rural site (Yangshan), a suburban site (Zengcheng), and an urban site (Tianhe). Participants were introduced to the influenza vaccine by project staff using a pamphlet about influenza vaccination and were either asked to pay out-of-pocket at the standard market price (US$8·5–23·2; standard-of-care group) or to donate any amount anonymously (pay-it-forward group). Participants had to be eligible to receive an influenza vaccine and to have not received an influenza vaccine in the past year. The primary outcome was vaccine uptake. Secondary outcomes were vaccine confidence and costs (from the health-care provider perspective). Regression methods compared influenza vaccine uptake and vaccine confidence between the two groups. This trial is registered with ChiCTR, ChiCTR2000040048. Findings: From Sept 21, 2020, to March 3, 2021, 300 enrolees were recruited from patients visiting three primary care clinics. 55 (37%) of 150 people in the standard-of-care group (40 [53%] of 75 children and 15 [20%] of 75 older adults) and 111 (74%) of 150 in the pay-it-forward group (66 [88%] of 75 children and 45 [60%] of 75 older adults) received an influenza vaccine. People in the pay-it-forward group were more likely to receive an influenza vaccine compared with those in the standard-of-care group (adjusted odds ratio [aOR] 6·7 [95% CI 2·7–16·6] among children and 5·0 [2·3–10·8] among older adults). People in the pay-it-forward group had greater confidence in vaccine safety (aOR 2·2 [95% CI 1·2–3·9]), importance (3·1 [1·6–5·9]), and effectiveness (3·1 [1·7–5·7]). In the pay-it-forward group, 107 (96%) of 111 participants donated money for subsequent vaccinations. The pay-it-forward group had a lower economic cost (calculated as the cost without subtraction of donations) per person vaccinated (US$45·60) than did the standard-of-care group ($64·67). Interpretation: The pay-it-forward intervention seemed to be effective in improving influenza vaccine uptake and community engagement. Our data have implications for prosocial interventions to enhance influenza vaccine uptake in countries where influenza vaccines are available for a fee. Funding: Bill & Melinda Gates Foundation and the UK National Institute for Health Research.Effectiveness of CoronaVac and BNT162b2 COVID-19 mass vaccination in Colombia: A population-based cohort study
AbstractPaternina-Caicedo, A., Jit, M., Alvis-Guzmán, N., Fernández, J. C., Hernández, J., Paz-Wilches, J. J., Rojas-Suarez, J., Dueñas-Castell, C., Alvis-Zakzuk, N. J., Smith, A. D., & Hoz-Restrepo, F. D. L. (n.d.).Publication year
2022Journal title
The Lancet Regional Health - AmericasVolume
12AbstractBackground: In February 2021, Colombia began mass vaccination against COVID-19 using mainly BNT162b2 and CoronaVac vaccines. We aimed to estimate vaccine effectiveness (VE) to prevent COVID-19 symptomatic cases, hospitalization, critical care admission, and deaths in a cohort of 796,072 insured subjects older than 40 years in northern Colombia, a setting with a high SARS-CoV-2 transmission. Methods: We identified individuals vaccinated between March 1st of 2021 and August 15th of 2021. We included symptomatic cases, hospitalizations, critical care admissions, and deaths in patients with confirmed COVID-19 as main outcomes. We calculated VE for each outcome from the hazard ratio in Cox proportionally hazards regressions (adjusted by age, sex, place of residence, diabetes, human immunodeficiency virus, cancer, hypertension, tuberculosis, neurological diseases, and chronic renal disease), with 95% confidence intervals (CI). Findings: A total of 719,735 insured participants of 40 and more years were followed. We found 21,545 laboratory-confirmed symptomatic COVID-19 among unvaccinated population, along with 2874 hospitalizations, 1061 critical care admissions, and 1329 deaths, for a rate of 207.2 per million person-days, 27.1 per million person-days, 10.0 per million person-days, and 12.5 per million person-days, respectively. We found CoronaVac was not effective for any outcome in subjects above 80 years old; but for people 40-79 years of age, we found two doses of CoronaVac reduced hospitalization (33.1%; 95% CI, 14.5–47.7), critical care admission (47.2%; 95% CI, 18.5–65.8), and death (55.7%; 95% CI, 32.5–70.0). We found BNT162b2 was effective for all outcomes in the entire population of subjects above 40 years of age, significantly declining for subjects ≥80 years. Interpretation: Two doses of either CoronaVac in population between 40 and 79 years of age, or BNT162b2 among vaccinated above 40 years old significantly reduced deaths of confirmed COVID-19 in a cohort of individuals from Colombia. Vaccine effectiveness for CoronaVac and BNT162b2 declined with increasing age. Funding: UK National Institute for Health Research, the European Union's Horizon 2020 research and innovation programme, and the Bill & Melinda Gates Foundation.Every Country, Every Family: Time to Act for Group B Streptococcal Disease Worldwide
AbstractLawn, J. E., Chandna, J., Paul, P., Jit, M., Trotter, C., Lambach, P., & Ter-Meulen, A. S. (n.d.).Publication year
2022Journal title
Clinical Infectious DiseasesVolume
74Page(s)
S1-S4AbstractThe global burden of Group B Streptococcus (GBS) was estimated for 2015 prompting inclusion of GBS as a priority in the Global Meningitis Roadmap. New estimates for the year 2020 and a WHO report analysing the full value of GBS maternal vaccines has been launched to advance evidence based decision making for multiple stakeholders. In this first of a 10-article supplement, we discuss the following (1) gaps in evidence and action, (2) new evidence in this supplement, and (3) what actions can be taken now and key research gaps ahead. We call for investment in the research pipeline, notably description, development, and delivery, in order to accelerate progress and address the large burden of GBS for every family in every country.Exploring the subnational inequality and heterogeneity of the impact of routine measles immunisation in Africa
AbstractEcheverria-Londono, S., Hartner, A. M., Li, X., Roth, J., Portnoy, A., Sbarra, A. N., Abbas, K., Ferrari, M., Fu, H., Jit, M., Ferguson, N. M., & Gaythorpe, K. A. (n.d.).Publication year
2022Journal title
VaccineVolume
40Issue
47Page(s)
6806-6817AbstractDespite vaccination being one of the most effective public health interventions, there are persisting inequalities and inequities in immunisation. Understanding the differences in subnational vaccine impact can help improve delivery mechanisms and policy. We analyse subnational vaccination coverage of measles first-dose (MCV1) and estimate patterns of inequalities in impact, represented as deaths averted, across 45 countries in Africa. We also evaluate how much this impact would improve under more equitable vaccination coverage scenarios. Using coverage data for MCV1 from 2000–2019, we estimate the number of deaths averted at the first administrative level. We use the ratio of deaths averted per vaccination from two mathematical models to extrapolate the impact at a subnational level. Next, we calculate inequality for each country, measuring the spread of deaths averted across its regions, accounting for differences in population. Finally, using three more equitable vaccination coverage scenarios, we evaluate how much impact of MCV1 immunisation could improve by (1) assuming all regions in a country have at least national coverage, (2) assuming all regions have the observed maximum coverage; and (3) assuming all regions have at least 80% coverage. Our results show that progress in coverage and reducing inequality has slowed in the last decade in many African countries. Under the three scenarios, a significant number of additional deaths in children could be prevented each year; for example, under the observed maximum coverage scenario, global MCV1 coverage would improve from 76% to 90%, resulting in a further 363(95%CrI:299–482) deaths averted per 100,000 live births. This paper illustrates that estimates of the impact of MCV1 immunisation at a national level can mask subnational heterogeneity. We further show that a considerable number of deaths could be prevented by maximising equitable access in countries with high inequality when increasing the global coverage of MCV1 vaccination.Feasibility of measles and rubella vaccination programmes for disease elimination: a modelling study
AbstractWinter, A. K., Lambert, B., Klein, D., Klepac, P., Papadopoulos, T., Truelove, S., Burgess, C., Santos, H., Knapp, J. K., Reef, S. E., Kayembe, L. K., Shendale, S., Kretsinger, K., Lessler, J., Vynnycky, E., McCarthy, K., Ferrari, M., & Jit, M. (n.d.).Publication year
2022Journal title
The Lancet Global HealthVolume
10Issue
10Page(s)
e1412-e1422AbstractBackground: Marked reductions in the incidence of measles and rubella have been observed since the widespread use of the measles and rubella vaccines. Although no global goal for measles eradication has been established, all six WHO regions have set measles elimination targets. However, a gap remains between current control levels and elimination targets, as shown by large measles outbreaks between 2017 and 2019. We aimed to model the potential for measles and rubella elimination globally to inform a WHO report to the 73rd World Health Assembly on the feasibility of measles and rubella eradication. Methods: In this study, we modelled the probability of measles and rubella elimination between 2020 and 2100 under different vaccination scenarios in 93 countries of interest. We evaluated measles and rubella burden and elimination across two national transmission models each (Dynamic Measles Immunisation Calculation Engine [DynaMICE], Pennsylvania State University [PSU], Johns Hopkins University, and Public Health England models), and one subnational measles transmission model (Institute for Disease Modeling model). The vaccination scenarios included a so-called business as usual approach, which continues present vaccination coverage, and an intensified investment approach, which increases coverage into the future. The annual numbers of infections projected by each model, country, and vaccination scenario were used to explore if, when, and for how long the infections would be below a threshold for elimination. Findings: The intensified investment scenario led to large reductions in measles and rubella incidence and burden. Rubella elimination is likely to be achievable in all countries and measles elimination is likely in some countries, but not all. The PSU and DynaMICE national measles models estimated that by 2050, the probability of elimination would exceed 75% in 14 (16%) and 36 (39%) of 93 modelled countries, respectively. The subnational model of measles transmission highlighted inequity in routine coverage as a likely driver of the continuance of endemic measles transmission in a subset of countries. Interpretation: To reach regional elimination goals, it will be necessary to innovate vaccination strategies and technologies that increase spatial equity of routine vaccination, in addition to investing in existing surveillance and outbreak response programmes. Funding: WHO, Gavi, the Vaccine Alliance, US Centers for Disease Control and Prevention, and the Bill & Melinda Gates Foundation.Group B streptococcus infection during pregnancy and infancy: estimates of regional and global burden
Failed generating bibliography.AbstractPublication year
2022Journal title
The Lancet Global HealthVolume
10Issue
6Page(s)
e807-e819AbstractBackground: Group B streptococcus (GBS) colonisation during pregnancy can lead to invasive GBS disease (iGBS) in infants, including meningitis or sepsis, with a high mortality risk. Other outcomes include stillbirths, maternal infections, and prematurity. There are data gaps, notably regarding neurodevelopmental impairment (NDI), especially after iGBS sepsis, which have limited previous global estimates. In this study, we aimed to address this gap using newly available multicountry datasets. Methods: We collated and meta-analysed summary data, primarily identified in a series of systematic reviews published in 2017 but also from recent studies on NDI and stillbirths, using Bayesian hierarchical models, and estimated the burden for 183 countries in 2020 regarding: maternal GBS colonisation, iGBS cases and deaths in infants younger than 3 months, children surviving iGBS affected by NDI, and maternal iGBS cases. We analysed the proportion of stillbirths with GBS and applied this to the UN-estimated stillbirth risk per country. Excess preterm births associated with maternal GBS colonisation were calculated using meta-analysis and national preterm birth rates. Findings: Data from the seven systematic reviews, published in 2017, that informed the previous burden estimation (a total of 515 data points) were combined with new data (17 data points) from large multicountry studies on neurodevelopmental impairment (two studies) and stillbirths (one study). A posterior median of 19·7 million (95% posterior interval 17·9–21·9) pregnant women were estimated to have rectovaginal colonisation with GBS in 2020. 231 800 (114 100–455 000) early-onset and 162 200 (70 200–394 400) late-onset infant iGBS cases were estimated to have occurred. In an analysis assuming a higher case fatality rate in the absence of a skilled birth attendant, 91 900 (44 800–187 800) iGBS infant deaths were estimated; in an analysis without this assumption, 58 300 (26 500–125 800) infant deaths from iGBS were estimated. 37 100 children who recovered from iGBS (14 600–96 200) were predicted to develop moderate or severe NDI. 40 500 (21 500–66 200) maternal iGBS cases and 46 200 (20 300–111 300) GBS stillbirths were predicted in 2020. GBS colonisation was also estimated to be potentially associated with considerable numbers of preterm births. Interpretation: Our analysis provides a comprehensive assessment of the pregnancy-related GBS burden. The Bayesian approach enabled coherent propagation of uncertainty, which is considerable, notably regarding GBS-associated preterm births. Our findings on both the acute and long-term consequences of iGBS have public health implications for understanding the value of investment in maternal GBS immunisation and other preventive strategies. Funding: Bill & Melinda Gates Foundation.Human papillomavirus vaccine effectiveness by number of doses: Updated systematic review of data from national immunization programs
AbstractMarkowitz, L. E., Drolet, M., Lewis, R. M., Lemieux-Mellouki, P., Pérez, N., Jit, M., Brotherton, J. M., Ogilvie, G., Kreimer, A. R., & Brisson, M. (n.d.).Publication year
2022Journal title
VaccineVolume
40Issue
37Page(s)
5413-5432AbstractBackground: Human papillomavirus (HPV) vaccines were first licensed as a three-dose series. Two doses are now widely recommended in some age groups; there are data suggesting high efficacy with one dose. We updated a systematic literature review of HPV vaccine effectiveness by number of doses in observational studies. Methods: We searched Medline and Embase databases from January 1, 2007, through September 29, 2021. Data were extracted and summarized in a narrative synthesis. We also conducted quality assessments for bias due to selection, information, and confounding. Results: Overall, 35 studies were included; all except one were conducted within the context of a recommended three-dose schedule. Evaluations were in countries that used bivalent HPV vaccine (seven), quadrivalent HPV vaccine (27) or both (one). Nine evaluated effectiveness against HPV infection, ten anogenital warts, and 16 cervical abnormalities. All studies were judged to have moderate or serious risk of bias. The biases rated as serious would likely result in lower effectiveness with fewer doses. Investigators attempted to control for or stratify by potentially important variables, such as age at vaccination. Eight studies evaluated impact of buffer periods (lag time) for case counting and 10 evaluated different intervals between doses for two-dose vaccine recipients. Studies that stratified by vaccination age found higher effectiveness with younger age at vaccination, although differences were not all formally tested. Most studies found highest estimates of effectiveness with three doses; significant effectiveness was found among 28/29 studies that evaluated three doses, 19/29 that evaluated two doses, and 18/30 that evaluated one dose. Some studies that adjusted or stratified analyses by age at vaccination found similar effectiveness with three, two and one doses. Conclusion: Observational studies of HPV vaccine effectiveness have many biases. Studies examining persons vaccinated prior to sexual activity and using methods to reduce sources of bias are needed for valid effectiveness estimates.In Elimination Settings, Measles Antibodies Wane After Vaccination but Not After Infection: A Systematic Review and Meta-Analysis
AbstractBolotin, S., Osman, S., Hughes, S. L., Ariyarajah, A., Tricco, A. C., Khan, S., Li, L., Johnson, C., Friedman, L., Gul, N., Jardine, R., Faulkner, M., Hahné, S. J., Heffernan, J. M., Dabbagh, A., Rota, P. A., Severini, A., Jit, M., Durrheim, D. N., … Crowcroft, N. S. (n.d.).Publication year
2022Journal title
Journal of Infectious DiseasesVolume
226Issue
7Page(s)
1127-1139AbstractBackground: We conducted a systematic review to assess whether measles humoral immunity wanes in previously infected or vaccinated populations in measles elimination settings. Methods: After screening 16 822 citations, we identified 9 articles from populations exposed to wild-type measles and 16 articles from vaccinated populations that met our inclusion criteria. Results: Using linear regression, we found that geometric mean titers (GMTs) decreased significantly in individuals who received 2 doses of measles-containing vaccine (MCV) by 121.8 mIU/mL (95% confidence interval [CI], -212.4 to -31.1) per year since vaccination over 1 to 5 years, 53.7 mIU/mL (95% CI, -95.3 to -12.2) 5 to 10 years, 33.2 mIU/mL (95% CI, -62.6 to -3.9), 10 to 15 years, and 24.1 mIU/mL (95% CI, -51.5 to 3.3) 15 to 20 years since vaccination. Decreases in GMT over time were not significant after 1 dose of MCV or after infection. Decreases in the proportion of seropositive individuals over time were not significant after 1 or 2 doses of MCV or after infection. Conclusions: Measles antibody waning in vaccinated populations should be considered in planning for measles elimination.Integrating economic and health evidence to inform Covid-19 policy in low- and middle- income countries
AbstractVassall, A., Sweeney, S., Barasa, E., Prinja, S., Keogh-Brown, M. R., Tarp Jensen, H., Smith, R., Baltussen, R., M. Eggo, R., & Jit, M. (n.d.). In Wellcome Open Research (1–).Publication year
2022Volume
5AbstractCovid-19 requires policy makers to consider evidence on both population health and economic welfare. Over the last two decades, the field of health economics has developed a range of analytical approaches and contributed to the institutionalisation of processes to employ economic evidence in health policy. We present a discussion outlining how these approaches and processes need to be applied more widely to inform Covid-19 policy; highlighting where they may need to be adapted conceptually and methodologically, and providing examples of work to date. We focus on the evidential and policy needs of low- and middle-income countries; where there is an urgent need for evidence to navigate the policy trade-offs between health and economic well-being posed by the Covid-19 pandemic.Long-Term Health-Related Quality of Life in Non-Hospitalized Coronavirus Disease 2019 (COVID-19) Cases With Confirmed Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection in England: Longitudinal Analysis and Cross-Sectional Comparison With Controls
AbstractSandmann, F. G., Tessier, E., Lacy, J., Kall, M., Van Leeuwen, E., Charlett, A., Eggo, R. M., Dabrera, G., Edmunds, W. J., Ramsay, M., Campbell, H., Amirthalingam, G., & Jit, M. (n.d.).Publication year
2022Journal title
Clinical Infectious DiseasesVolume
75Issue
1Page(s)
E962-E973AbstractBackground: We aimed to quantify the unknown losses in health-related quality of life of coronavirus disease 2019 (COVID-19) cases using quality-adjusted lifedays (QALDs) and the recommended EQ-5D instrument in England. Methods: Prospective cohort study of nonhospitalized, polymerase chain reaction (PCR)-confirmed severe acute respiratory syndrome coronavirus 2-positive (SARS-CoV-2-positive) cases aged 12-85 years and followed up for 6 months from 1 December 2020, with cross-sectional comparison to SARS-CoV-2-negative controls. Main outcomes were QALD losses; physical symptoms; and COVID-19-related private expenditures. We analyzed results using multivariable regressions with post hoc weighting by age and sex, and conditional logistic regressions for the association of each symptom and EQ-5D limitation on cases and controls. Results: Of 548 cases (mean age 41.1 years; 61.5% female), 16.8% reported physical symptoms at month 6 (most frequently extreme tiredness, headache, loss of taste and/or smell, and shortness of breath). Cases reported more limitations with doing usual activities than controls. Almost half of cases spent a mean of £18.1 on nonprescription drugs (median: £10.0), and 52.7% missed work or school for a mean of 12 days (median: 10). On average, all cases lost 13.7 (95% confidence interval [CI]: 9.7, 17.7) QALDs, whereas those reporting symptoms at month 6 lost 32.9 (95% CI: 24.5, 37.6) QALDs. Losses also increased with older age. Cumulatively, the health loss from morbidity contributes at least 18% of the total COVID-19-related disease burden in the England. Conclusions: One in 6 cases report ongoing symptoms at 6 months, and 10% report prolonged loss of function compared to pre-COVID-19 baselines. A marked health burden was observed among older COVID-19 cases and those with persistent physical symptoms.Measuring the effects of COVID-19-related disruption on dengue transmission in southeast Asia and Latin America: a statistical modelling study
Failed generating bibliography.AbstractPublication year
2022Journal title
The Lancet Infectious DiseasesVolume
22Issue
5Page(s)
657-667AbstractBackground: The COVID-19 pandemic has resulted in unprecedented disruption to society, which indirectly affects infectious disease dynamics. We aimed to assess the effects of COVID-19-related disruption on dengue, a major expanding acute public health threat, in southeast Asia and Latin America. Methods: We assembled data on monthly dengue incidence from WHO weekly reports, climatic data from ERA5, and population variables from WorldPop for 23 countries between January, 2014 and December, 2019 and fit a Bayesian regression model to explain and predict seasonal and multi-year dengue cycles. We compared model predictions with reported dengue data January to December, 2020, and assessed if deviations from projected incidence since March, 2020 are associated with specific public health and social measures (from the Oxford Coronavirus Government Response Tracer database) or human movement behaviours (as measured by Google mobility reports). Findings: We found a consistent, prolonged decline in dengue incidence across many dengue-endemic regions that began in March, 2020 (2·28 million cases in 2020 vs 4·08 million cases in 2019; a 44·1% decrease). We found a strong association between COVID-19-related disruption (as measured independently by public health and social measures and human movement behaviours) and reduced dengue risk, even after taking into account other drivers of dengue cycles including climatic and host immunity (relative risk 0·01–0·17, p<0·01). Measures related to the closure of schools and reduced time spent in non-residential areas had the strongest evidence of association with reduced dengue risk, but high collinearity between covariates made specific attribution challenging. Overall, we estimate that 0·72 million (95% CI 0·12–1·47) fewer dengue cases occurred in 2020 potentially attributable to COVID-19-related disruption. Interpretation: In most countries, COVID-19-related disruption led to historically low dengue incidence in 2020. Continuous monitoring of dengue incidence as COVID-19-related restrictions are relaxed will be important and could give new insights into transmission processes and intervention options. Funding: National Key Research and Development Program of China and the Medical Research Council.Modelling the medium-term dynamics of SARS-CoV-2 transmission in England in the Omicron era
Failed generating bibliography.AbstractPublication year
2022Journal title
Nature communicationsVolume
13Issue
1AbstractEngland has experienced a heavy burden of COVID-19, with multiple waves of SARS-CoV-2 transmission since early 2020 and high infection levels following the emergence and spread of Omicron variants since late 2021. In response to rising Omicron cases, booster vaccinations were accelerated and offered to all adults in England. Using a model fitted to more than 2 years of epidemiological data, we project potential dynamics of SARS-CoV-2 infections, hospital admissions and deaths in England to December 2022. We consider key uncertainties including future behavioural change and waning immunity and assess the effectiveness of booster vaccinations in mitigating SARS-CoV-2 disease burden between October 2021 and December 2022. If no new variants emerge, SARS-CoV-2 transmission is expected to decline, with low levels remaining in the coming months. The extent to which projected SARS-CoV-2 transmission resurges later in 2022 depends largely on assumptions around waning immunity and to some extent, behaviour, and seasonality.Neurodevelopmental and growth outcomes after invasive Group B Streptococcus in early infancy: A multi-country matched cohort study in South Africa, Mozambique, India, Kenya, and Argentina
Failed generating bibliography.AbstractPublication year
2022Journal title
EClinicalMedicineVolume
47AbstractBackground: Data are limited regarding long-term consequences of invasive GBS (iGBS) disease in early infancy, especially from low- and middle-income countries (LMIC) where most cases occur. We aimed to estimate risk of neurodevelopmental impairment (NDI) in children with a history of iGBS disease. Methods: A multi-country matched cohort study was undertaken in South Africa, India, Mozambique, Kenya, and Argentina from October 2019 to April 2021. The exposure of interest was defined as a history of iGBS disease (sepsis or meningitis) before 90 days of age, amongst children now aged 1·5–18 years. Age and sex-matched, children without history of GBS were also recruited. Age-appropriate, culturally-adapted assessments were used to define NDI across multiple domains (cognitive, motor, hearing, vision, emotional-behaviour, growth). Pooled NDI risk was meta-analysed across sites. Association of iGBS exposure and NDI outcome was estimated using modified Poisson regression with robust variance estimator. Findings: Amongst 138 iGBS survivors and 390 non-iGBS children, 38·1% (95% confidence interval [CI]: 30·0% – 46·6%) of iGBS children had any NDI, compared to 21·7% (95% CI: 17·7% - 26·0%) of non- iGBS children, with notable between-site heterogeneity. Risk of moderate/severe NDI was 15·0% (95% CI: 3·4% - 30·8%) among GBS-meningitis, 5·6% (95% CI: 1·5% - 13·7%) for GBS-sepsis survivors. The adjusted risk ratio (aRR) for moderate/severe NDI among iGBS survivors was 1.27 (95% CI: 0.65, 2.45), when compared to non-GBS children. Mild impairment was more frequent in iGBS (27.6% (95% CI: 20.3 – 35.5%)) compared to non-GBS children (12.9% (95% CI: 9.7% - 16.4%)). The risk of emotional-behavioural problems was similar irrespective of iGBS exposure (aRR=0.98 (95% CI: 0.55, 1.77)). Interpretation: Our findings suggest that iGBS disease is on average associated with a higher risk of moderate/severe NDI, however substantial variation in risk was observed between sites and data are consistent with a wide range of values. Our study underlines the importance of long-term follow-up for at-risk neonates and more feasible, standardised assessments to facilitate diagnosis in research and clinical practice. Funding: This work was supported by a grant (INV-009018) from the Bill & Melinda Gates Foundation to the London School of Hygiene &Tropical Medicine.Now or later: Health impacts of delaying single-dose HPV vaccine implementation in a high-burden setting
AbstractBurger, E. A., Laprise, J. F., Sy, S., Regan, M. C., Prem, K., Jit, M., Brisson, M., & Kim, J. J. (n.d.).Publication year
2022Journal title
International Journal of CancerVolume
151Issue
10Page(s)
1804-1809AbstractWe aimed to quantify the health impact of immediate introduction of a single-dose human papillomavirus (HPV) vaccination program in a high-burden setting, as waiting until forthcoming trials are completed to implement single-dose HPV vaccination may result in health losses, particularly for cohorts who would age-out of vaccination eligibility. Two mathematical models fitted to a high-burden setting projected cervical cancer incidence rates associated with (a) immediate implementation of one-dose HPV vaccination vs (b) waiting 5 years for evidence from randomized trials to determine if one- or two-doses should be implemented. We conducted analyses assuming a single dose was either noninferior or inferior to two doses. The models projected that immediate implementation of a noninferior single-dose vaccine led to a 7.2% to 9.6% increase in cancers averted between 2021 to 2120, compared to waiting 5 years. Health benefits remained greater with immediate implementation despite an inferior single-dose efficacy (80%), but revaccination of one-dose recipients became more important assuming vaccine waning. Under most circumstances, immediate vaccination avoided health losses for those aging out of vaccine eligibility, leading to greater health benefits than waiting for more information in 5 years.Optimal health and economic impact of non-pharmaceutical intervention measures prior and post vaccination in England: a mathematical modelling study
AbstractTildesley, M. J., Vassall, A., Riley, S., Jit, M., Sandmann, F., Hill, E. M., Thompson, R. N., Atkins, B. D., Edmunds, J., Dyson, L., & Keeling, M. J. (n.d.).Publication year
2022Journal title
Royal Society Open ScienceVolume
9Issue
8AbstractBackground. Even with good progress on vaccination, SARS-CoV-2 infections in the UK may continue to impose a high burden of disease and therefore pose substantial challenges for health policy decision makers. Stringent government-mandated physical distancing measures (lockdown) have been demonstrated to be epidemiologically effective, but can have both positive and negative economic consequences. The duration and frequency of any intervention policy could, in theory, be optimized to maximize economic benefits while achieving substantial reductions in disease. Methods. Here, we use a pre-existing SARS-CoV-2 transmission model to assess the health and economic implications of different strengths of control through time in order to identify optimal approaches to non-pharmaceutical intervention stringency in the UK, considering the role of vaccination in reducing the need for future physical distancing measures. The model is calibrated to the COVID-19 epidemic in England and we carry out retrospective analysis of the optimal timing of precautionary breaks in 2020 and the optimal relaxation policy from the January 2021 lockdown, considering the willingness to pay (WTP) for health improvement. Results. We find that the precise timing and intensity of interventions is highly dependent upon the objective of control. As intervention measures are relaxed, we predict a resurgence in cases, but the optimal intervention policy can be established dependent upon the WTP per quality adjusted life year loss avoided. Our results show that establishing an optimal level of control can result in a reduction in net monetary loss of billions of pounds, dependent upon the precise WTP value. Conclusion. It is vital, as the UK emerges from lockdown, but continues to face an on-going pandemic, to accurately establish the overall health and economic costs when making policy decisions. We demonstrate how some of these can be quantified, employing mechanistic infectious disease transmission models to establish optimal levels of control for the ongoing COVID-19 pandemic.