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
A systematised review and evidence synthesis on the broader societal impact of vaccines against Salmonella
Failed retrieving data from NYU Scholars.A vaccine chatbot intervention for parents to improve HPV vaccination uptake among middle school girls: a cluster randomized trial
Failed retrieving data from NYU Scholars.Cost-effectiveness analysis of switching from a bivalent to a nonavalent HPV vaccination programme in China: a modelling study
Failed retrieving data from NYU Scholars.Social contact patterns and their impact on the transmission of respiratory pathogens in rural China
AbstractLiang, Y., You, Q., Wang, Q., Yang, X., Zhong, G., Dong, K., Zhao, Z., Liu, N., Yan, X., Lu, W., Peng, C., Zhou, J., Lin, J., Litvinova, M., Jit, M., Ajelli, M., Yu, H., & Zhang, J. (n.d.).Publication year
2025Journal title
Infectious Disease ModellingVolume
10Issue
2Page(s)
439-452AbstractIntroduction: Social contact patterns significantly influence the transmission dynamics of respiratory pathogens. Previous surveys have quantified human social contact patterns, yielding heterogeneous results across different locations. However, significant gaps remain in understanding social contact patterns in rural areas of China. Methods: We conducted a pioneering study to quantify social contact patterns in Anhua County, Hunan Province, China, from June to October 2021, when there were minimal coronavirus disease-related restrictions in the area. Additionally, we simulated the epidemics under different assumptions regarding the relative transmission risks of various contact types (e.g., indoor versus outdoor, and physical versus non-physical). Results: Participants reported an average of 12.0 contacts per day (95% confidence interval: 11.3–12.6), with a significantly higher number of indoor contacts compared to outdoor contacts. The number of contacts was associated with various socio-demographic characteristics, including age, education level, income, household size, and travel patterns. Contact patterns were assortative by age and varied based on the type of contact (e.g., physical versus non-physical). The reproduction number, daily incidence, and infection attack rate of simulated epidemics were remarkably stable. Discussion: We found many intergenerational households and contacts that pose challenges in preventing and controlling infections among the elderly in rural China. Our study also underscores the importance of integrating various types of contact pattern data into epidemiological models and provides guidance to public health authorities and other major stakeholders in preparing and responding to infectious disease threats in rural China.Vaccination strategies against wild poliomyelitis in polio-free settings: Outbreak risk modelling study and cost-effectiveness analysis
Failed retrieving data from NYU Scholars.A health technology assessment of COVID-19 vaccination for Nigerian decision-makers: Identifying stakeholders and pathways to support evidence uptake
Failed retrieving data from NYU Scholars.A Scoping Review and Taxonomy of Epidemiological-Macroeconomic Models of COVID-19
AbstractBonnet, G., Pearson, C. A., Torres-Rueda, S., Ruiz, F., Lines, J., Jit, M., Vassall, A., & Sweeney, S. (n.d.).Publication year
2024Journal title
Value in HealthVolume
27Issue
1Page(s)
104-116AbstractObjectives: The COVID-19 pandemic placed significant strain on many health systems and economies. Mitigation policies decreased health impacts but had major macroeconomic impact. This article reviews models combining epidemiological and macroeconomic projections to enable policy makers to consider both macroeconomic and health objectives. Methods: A scoping review of epidemiological-macroeconomic models of COVID-19 was conducted, covering preprints, working articles, and journal publications. We assessed model methodologies, scope, and application to empirical data. Results: We found 80 articles modeling both the epidemiological and macroeconomic outcomes of COVID-19. Model scope is often limited to the impact of lockdown on health and total gross domestic product or aggregate consumption and to high-income countries. Just 14% of models assess disparities or poverty. Most models fall under 4 categories: compartmental-utility-maximization models, epidemiological models with stylized macroeconomic projections, epidemiological models linked to computable general equilibrium or input-output models, and epidemiological-economic agent-based models. We propose a taxonomy comparing these approaches to guide future model development. Conclusions: The epidemiological-macroeconomic models of COVID-19 identified have varying complexity and meet different modeling needs. Priorities for future modeling include increasing developing country applications, assessing disparities and poverty, and estimating of long-run impacts. This may require better integration between epidemiologists and economists.An Application of an Initial Full Value of Vaccine Assessment Methodology to Measles-Rubella MAPs for Use in Low- and Middle-Income Countries
Failed retrieving data from NYU Scholars.An overview of the perspectives used in health economic evaluations
AbstractSittimart, M., Rattanavipapong, W., Mirelman, A. J., Hung, T. M., Dabak, S., Downey, L. E., Jit, M., Teerawattananon, Y., & Turner, H. C. (n.d.).Publication year
2024Journal title
Cost Effectiveness and Resource AllocationVolume
22Issue
1AbstractThe term ‘perspective’ in the context of economic evaluations and costing studies in healthcare refers to the viewpoint that an analyst has adopted to define the types of costs and outcomes to consider in their studies. However, there are currently notable variations in terms of methodological recommendations, definitions, and applications of different perspectives, depending on the objective or intended user of the study. This can make it a complex area for stakeholders when interpreting these studies. Consequently, there is a need for a comprehensive overview regarding the different types of perspectives employed in such analyses, along with the corresponding implications of their use. This is particularly important, in the context of low-and-middle-income countries (LMICs), where practical guidelines may be less well-established and infrastructure for conducting economic evaluations may be more limited. This article addresses this gap by summarising the main types of perspectives commonly found in the literature to a broad audience (namely the patient, payer, health care providers, healthcare sector, health system, and societal perspectives), providing their most established definitions and outlining the corresponding implications of their uses in health economic studies, with examples particularly from LMIC settings. We then discuss important considerations when selecting the perspective and present key arguments to consider when deciding whether the societal perspective should be used. We conclude that there is no one-size-fits-all answer to what perspective should be used and the perspective chosen will be influenced by the context, policymakers'/stakeholders’ viewpoints, resource/data availability, and intended use of the analysis. Moving forward, considering the ongoing issues regarding the variation in terminology and practice in this area, we urge that more standardised definitions of the different perspectives and the boundaries between them are further developed to support future studies and guidelines, as well as to improve the interpretation and comparison of health economic evidence.Between now and later: a mixed methods study of HPV vaccination delay among Chinese caregivers in urban Chengdu, China
Failed retrieving data from NYU Scholars.Clinical coding of long COVID in primary care 2020–2023 in a cohort of 19 million adults: an OpenSAFELY analysis
Failed generating bibliography.AbstractPublication year
2024Journal title
EClinicalMedicineVolume
72AbstractBackground: Long COVID is the patient-coined term for the persistent symptoms of COVID-19 illness for weeks, months or years following the acute infection. There is a large burden of long COVID globally from self-reported data, but the epidemiology, causes and treatments remain poorly understood. Primary care is used to help identify and treat patients with long COVID and therefore Electronic Health Records (EHRs) of past COVID-19 patients could be used to help fill these knowledge gaps. We aimed to describe the incidence and differences in demographic and clinical characteristics in recorded long COVID in primary care records in England. Methods: With the approval of NHS England we used routine clinical data from over 19 million adults in England linked to SARS-COV-2 test result, hospitalisation and vaccination data to describe trends in the recording of 16 clinical codes related to long COVID between November 2020 and January 2023. Using OpenSAFELY, we calculated rates per 100,000 person-years and plotted how these changed over time. We compared crude and adjusted (for age, sex, 9 NHS regions of England, and the dominant variant circulating) rates of recorded long COVID in patient records between different key demographic and vaccination characteristics using negative binomial models. Findings: We identified a total of 55,465 people recorded to have long COVID over the study period, which included 20,025 diagnoses codes and 35,440 codes for further assessment. The incidence of new long COVID records increased steadily over 2021, and declined over 2022. The overall rate per 100,000 person-years was 177.5 cases in women (95% CI: 175.5–179) and 100.5 in men (99.5–102). The majority of those with a long COVID record did not have a recorded positive SARS-COV-2 test 12 or more weeks before the long COVID record. Interpretation: In this descriptive study, EHR recorded long COVID was very low between 2020 and 2023, and incident records of long COVID declined over 2022. Using EHR diagnostic or referral codes unfortunately has major limitations in identifying and ascertaining true cases and timing of long COVID. Funding: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).Contribution of vaccination to improved survival and health: modelling 50 years of the Expanded Programme on Immunization
Failed retrieving data from NYU Scholars.Cost-effectiveness of COVID rapid diagnostic tests for patients with severe/critical illness in low- and middle-income countries: A modeling study
Bonnet, G., Bimba, J., Chavula, C., Chifamba, H. N., Divala, T. H., Lescano, A. G., Majam, M., Mbo, D., Suwantika, A. A., Tovar, M. A., Yadav, P., Ekwunife, O., Mangenah, C., Ngwira, L. G., Corbett, E. L., Jit, M., & Vassall, A. (n.d.).Publication year
2024Journal title
PLoS MedicineVolume
21Issue
7COVID-19-related health utility values and changes in COVID-19 patients and the general population: a scoping review
AbstractMao, Z., Li, X., Jit, M., & Beutels, P. (n.d.).Publication year
2024Journal title
Quality of Life ResearchVolume
33Issue
6Page(s)
1443-1454AbstractPurpose: To summarise the diverse literature reporting the impact of COVID-19 on health utility in COVID-19 patients as well as in general populations being affected by COVID-19 control policies. Methods: A literature search up to April 2023 was conducted to identify papers reporting health utility in COVID-19 patients or in COVID-19-affected general populations. We present a narrative synthesis of the health utility values/losses of the retained studies to show the mean health utility values/losses with 95% confidence intervals. Mean utility values/losses for categories defined by medical attendance and data collection time were calculated using random-effects models. Results: In total, 98 studies—68 studies on COVID-19 patients and 30 studies on general populations—were retained for detailed review. Mean (95% CI) health utility values were 0.83 (0.81, 0.86), 0.78 (0.73, 0.83), 0.82 (0.78, 0.86) and 0.71 (0.65, 0.78) for general populations, non-hospitalised, hospitalised and ICU patients, respectively, irrespective of the data collection time. Mean utility losses in patients and general populations ranged from 0.03 to 0.34 and from 0.02 to 0.18, respectively. Conclusions: This scoping review provides a summary of the health utility impact of COVID-19 and COVID-19 control policies. COVID-19-affected populations were reported to have poor health utility, while a high degree of heterogeneity was observed across studies. Population- and/or country-specific health utility is recommended for use in future economic evaluation on COVID-19-related interventions.Effectiveness and efficiency of immunisation strategies to prevent RSV among infants and older adults in Germany: a modelling study
Failed retrieving data from NYU Scholars.Effects of sequential vs single pneumococcal vaccination on cardiovascular diseases among older adults: a population-based cohort study
Failed retrieving data from NYU Scholars.Equity impact of HPV vaccination on lifetime projections of cervical cancer burden among cohorts in 84 countries by global, regional, and income levels, 2010–22: a modelling study
Failed retrieving data from NYU Scholars.Estimating the health effects of COVID-19-related immunisation disruptions in 112 countries during 2020–30: a modelling study
Failed retrieving data from NYU Scholars.Estimating the impact of vaccination: lessons learned in the first phase of the Vaccine Impact Modelling Consortium
AbstractGaythorpe, K. A., Li, X., Clapham, H., Dansereau, E., Fitzjohn, R., Hinsley, W., Hogan, D., Jit, M., Mengistu, T., Perkins, T. A., Portnoy, A., Vynnycky, E., Woodruff, K., Ferguson, N. M., & Trotter, C. L. (n.d.). In Gates Open Research (1–).Publication year
2024Volume
8AbstractEstimates of the global health impact of immunisation are important for quantifying historical benefits as well as planning future investments and strategy. The Vaccine Impact Modelling Consortium (VIMC) was established in 2016 to provide reliable estimates of the health impact of immunisation. In this article we examine the consortium in its first five-year phase. We detail how vaccine impact was defined and the methods used to estimate it as well as the technical infrastructure required to underpin robust reproducibility of the outputs. We highlight some of the applications of estimates to date, how these were communicated and what their effect were. Finally, we explore some of the lessons learnt and remaining challenges for estimating the impact of vaccines and forming effective modelling consortia then discuss how this may be addressed in the second phase of VIMC. Modelled estimates are not a replacement for surveillance; however, they can examine theoretical counterfactuals and highlight data gaps to complement other activities. VIMC has implemented strategies to produce robust, standardised estimates of immunisation impact. But through the first phase of the consortium, critical lessons have been learnt both on the technical infrastructure and the effective engagement with modellers and stakeholders. To be successful, a productive dialogue with estimate consumers, producers and stakeholders needs to be underpinned by a rigorous and transparent analytical framework as well as an approach for building expertise in the short and long term.Evaluating Scope and Bias of Population-Level Measles Serosurveys: A Systematized Review and Bias Assessment
AbstractSbarra, A. N., Cutts, F. T., Fu, H., Poudyal, I., Rhoda, D. A., Mosser, J. F., & Jit, M. (n.d.).Publication year
2024Journal title
VaccinesVolume
12Issue
6AbstractBackground: Measles seroprevalence data have potential to be a useful tool for understanding transmission dynamics and for decision making efforts to strengthen immunization programs. In this study, we conducted a systematized review and bias assessment of all primary data on measles seroprevalence in low- and middle-income countries (as defined by World Bank 2021 income classifications) published from 1962 to 2021. Methods: On 9 March 2022, we searched PubMed for all available data. We included studies containing primary data on measles seroprevalence and excluded studies if they were clinical trials or brief reports, from only health-care workers, suspected measles cases, or only vaccinated persons. We extracted all available information on measles seroprevalence, study design, and seroassay protocol. We conducted a bias assessment based on multiple categories and classified each study as having low, moderate, severe, or critical bias. This review was registered with PROSPERO (CRD42022326075). Results: We identified 221 relevant studies across all World Health Organization regions, decades, and unique age ranges. The overall crude mean seroprevalence across all studies was 78.0% (SD: 19.3%), and the median seroprevalence was 84.0% (IQR: 72.8–91.7%). We classified 80 (36.2%) studies as having severe or critical overall bias. Studies from country-years with lower measles vaccine coverage or higher measles incidence had higher overall bias. Conclusions: While many studies have substantial underlying bias, many studies still provide some insights or data that could be used to inform modelling efforts to examine measles dynamics and programmatic decisions to reduce measles susceptibility.Global vaccine coverage and childhood survival estimates: 1990–2019
AbstractZhang, H., Patenaude, B., Zhang, H., Jit, M., & Fang, H. (n.d.).Publication year
2024Journal title
Bulletin of the World Health OrganizationVolume
102Issue
4Page(s)
276-287AbstractObjective To quantify the association between reduction in child mortality and routine immunization across 204 countries and territories from 1990 to 2019. Methods We used child mortality and vaccine coverage data from the Global Burden of Disease Study. We used a modified child survival framework and applied a mixed-effects regression model to estimate the reduction in deaths in children younger than 5 years associated with eight vaccines. Findings Between 1990 and 2019, the diphtheria–tetanus–pertussis (DTP), measles, rotavirus and Haemophilus influenzae type b vaccines were significantly associated with an estimated 86.9 (95% confidence interval, CI: 57.2 to 132.4) million fewer deaths in children younger than 5 years worldwide. This decrease represented a 24.2% (95% CI: 19.8 to 28.9) reduction in deaths relative to a scenario without vaccines. The DTP and measles vaccines averted 46.7 (95% CI: 30.0 to 72.7) million and 37.9 (95% CI: 25.4 to 56.8) million deaths, respectively. Of the total reduction in child mortality associated with vaccines, 84.2% (95% CI: 83.0 to 85.1) occurred in 73 countries supported by Gavi, the Vaccine Alliance, with an estimated 45.4 (95% CI: 29.8 to 69.2) million fewer deaths from 2000 to 2019. The largest reductions in deaths associated with these four vaccines were in India, China, Ethiopia, Pakistan and Bangladesh (in order of the size of reduction). Conclusion Vaccines continue to reduce childhood mortality significantly, especially in Gavi-supported countries, emphasizing the need for increased investment in routine immunization programmes.Health impact and cost-effectiveness of vaccination using potential next-generation influenza vaccines in Thailand: a modelling study
Failed retrieving data from NYU Scholars.Health-Related Quality of Life and Economic Burden Among Hospitalized Children with Hand, Foot, and Mouth Disease: A Multiregional Study in China
AbstractZhou, T., Hu, H., Gao, J., Yu, H., Jit, M., & Wang, P. (n.d.).Publication year
2024Journal title
PharmacoEconomics - OpenVolume
8Issue
3Page(s)
459-469AbstractBackground: Hand, foot, and mouth disease (HFMD) is an infectious disease with high morbidity and mortality rates among children under 5 years old. This study aimed to explore the health-related quality of life (HRQOL), economic burden, and related influencing factors among Chinese HFMD patients. Methods: From January to October 2019, a longitudinal cohort study of 296 hospitalized patients (≤ 5 years old) with HFMD and their guardians was conducted using the proxy version of the 5-level EQ-5D-Y (EQ-5D-Y-5L, Y-5L) in face-to-face interviews in Shanghai, Zhengzhou, and Kunming, representing three regions with different economic development levels. Multiple linear regression was used to explore the factors associated with HRQOL and costs. Results: The mean Y-5L health utility score (HUS) (standard deviation, SD), and visual analogue scale (VAS) score (SD) were 0.730 (0.140) and 60.33 (16.52) at admission and increased to 0.920 (0.120) and 89.95 (11.88) at discharge, respectively. The children from Shanghai had the lowest HUSs at admission and had the best health improvement. The mean hospitalization cost and total cost were 4037 CNY and 5157 CNY, respectively. The children from Shanghai had the highest hospitalization cost (4559 CNY) and total cost (5491 CNY). Multiple regression analysis suggested that medical insurance status, type of employment, residence type, and religious status were significantly associated with the baseline HUS and improvement in the HUS after treatment. Region, loss of work time, and length of stay had a significant impact on the hospitalization cost and total cost. Conclusion: Our findings demonstrate that HFMD could lead to poor HRQOL and the economic burden varies in different regions in China. Many pediatric patients still have physical or mental health problems shortly after treatment.Healthcare utilisation in people with long COVID: an OpenSAFELY cohort study
Failed generating bibliography.AbstractPublication year
2024Journal title
BMC MedicineVolume
22Issue
1AbstractBackground: Long COVID potentially increases healthcare utilisation and costs. However, its impact on the NHS remains to be determined. Methods: This study aims to assess the healthcare utilisation of individuals with long COVID. With the approval of NHS England, we conducted a matched cohort study using primary and secondary care data via OpenSAFELY, a platform for analysing anonymous electronic health records. The long COVID exposure group, defined by diagnostic codes, was matched with five comparators without long COVID between Nov 2020 and Jan 2023. We compared their total healthcare utilisation from GP consultations, prescriptions, hospital admissions, A&E visits, and outpatient appointments. Healthcare utilisation and costs were evaluated using a two-part model adjusting for covariates. Using a difference-in-difference model, we also compared healthcare utilisation after long COVID with pre-pandemic records. Results: We identified 52,988 individuals with a long COVID diagnosis, matched to 264,867 comparators without a diagnosis. In the 12 months post-diagnosis, there was strong evidence that those with long COVID were more likely to use healthcare resources (OR: 8.29, 95% CI: 7.74–8.87), and have 49% more healthcare utilisation (RR: 1.49, 95% CI: 1.48–1.51). Our model estimated that the long COVID group had 30 healthcare visits per year (predicted mean: 29.23, 95% CI: 28.58–29.92), compared to 16 in the comparator group (predicted mean visits: 16.04, 95% CI: 15.73–16.36). Individuals with long COVID were more likely to have non-zero healthcare expenditures (OR = 7.66, 95% CI = 7.20–8.15), with costs being 44% higher than the comparator group (cost ratio = 1.44, 95% CI: 1.39–1.50). The long COVID group costs approximately £2500 per person per year (predicted mean cost: £2562.50, 95% CI: £2335.60–£2819.22), and the comparator group costs £1500 (predicted mean cost: £1527.43, 95% CI: £1404.33–1664.45). Historically, individuals with long COVID utilised healthcare resources more frequently, but their average healthcare utilisation increased more after being diagnosed with long COVID, compared to the comparator group. Conclusions: Long COVID increases healthcare utilisation and costs. Public health policies should allocate more resources towards preventing, treating, and supporting individuals with long COVID.How mathematical modelling can inform outbreak response vaccination
AbstractShankar, M., Hartner, A. M., Arnold, C. R., Gayawan, E., Kang, H., Kim, J. H., Gilani, G. N., Cori, A., Fu, H., Jit, M., Muloiwa, R., Portnoy, A., Trotter, C., & Gaythorpe, K. A. (n.d.).Publication year
2024Journal title
BMC Infectious DiseasesVolume
24Issue
1AbstractMathematical models are established tools to assist in outbreak response. They help characterise complex patterns in disease spread, simulate control options to assist public health authorities in decision-making, and longer-term operational and financial planning. In the context of vaccine-preventable diseases (VPDs), vaccines are one of the most-cost effective outbreak response interventions, with the potential to avert significant morbidity and mortality through timely delivery. Models can contribute to the design of vaccine response by investigating the importance of timeliness, identifying high-risk areas, prioritising the use of limited vaccine supply, highlighting surveillance gaps and reporting, and determining the short- and long-term benefits. In this review, we examine how models have been used to inform vaccine response for 10 VPDs, and provide additional insights into the challenges of outbreak response modelling, such as data gaps, key vaccine-specific considerations, and communication between modellers and stakeholders. We illustrate that while models are key to policy-oriented outbreak vaccine response, they can only be as good as the surveillance data that inform them.