Mark Jit

Chair and Professor of the Department of Global and Environmental Health

Professional overview

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.

Education

BSc, Mathematics, University College London

PhD, Mathematics, University College London

MPH, Public Health, King's College London

Honors and awards

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)

Publications

Publications

A systematised review and evidence synthesis on the broader societal impact of vaccines against Salmonella

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A vaccine chatbot intervention for parents to improve HPV vaccination uptake among middle school girls: a cluster randomized trial

Hou, Z., Wu, Z., Qu, Z., Gong, L., Peng, H., Jit, M., Larson, H. J., Wu, J. T., & Lin, L. (n.d.).

Publication year

2025

Journal title

Nature Medicine

10.1038/s41591-025-03618-6

Abstract

Abstract

Conversational artificial intelligence, in the form of chatbots powered by large language models, offers a new approach to facilitating human-like interactions, yet its efficacy in enhancing vaccination uptake remains under-investigated. This study assesses the effectiveness of a vaccine chatbot in improving human papillomavirus (HPV) vaccination among female middle school students aged 12–15 years across diverse socioeconomic settings in China, where HPV vaccination is primarily paid out-of-pocket. A school-based cluster randomized trial was conducted from 18 January to 31 May 2024. The study included 2,671 parents from 180 middle school classes stratified by socioeconomic setting, school and grade level in Shanghai megacity, and urban and rural regions of Anhui Province. Participants were randomly assigned to either the intervention group (90 classes, 1,294 parents), which engaged with the chatbot for two weeks, or the control group (90 classes, 1,377 parents), which received usual care. The primary outcome was the receipt or scheduled appointment of the HPV vaccine for participants’ daughters. In intention-to-treat analyses, 7.1% of the intervention group met this outcome versus 1.8% of the control group (P < 0.001) over a two-week intervention period. In addition, there was a statistically significant increase in HPV vaccination-specific consultations with health professionals (49.1% versus 17.6%, P < 0.001), along with enhanced vaccine literacy (P < 0.001) and rumor discernment (P < 0.001) among participants using the chatbot. These findings indicate that the chatbot effectively increased vaccination and improved parental vaccine literacy, although further research is necessary to scale and sustain these gains. Clinical trial registration: NCT06227689.

Cost-effectiveness analysis of switching from a bivalent to a nonavalent HPV vaccination programme in China: a modelling study

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Social contact patterns and their impact on the transmission of respiratory pathogens in rural China

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Vaccination strategies against wild poliomyelitis in polio-free settings: Outbreak risk modelling study and cost-effectiveness analysis

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A health technology assessment of COVID-19 vaccination for Nigerian decision-makers: Identifying stakeholders and pathways to support evidence uptake

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A Scoping Review and Taxonomy of Epidemiological-Macroeconomic Models of COVID-19

Bonnet, G., Pearson, C. A., Torres-Rueda, S., Ruiz, F., Lines, J., Jit, M., Vassall, A., & Sweeney, S. (n.d.).

Publication year

2024

Journal title

Value in Health

Volume

27

Issue

1

Page(s)

104-116

10.1016/j.jval.2023.10.008

Abstract

Abstract

Objectives: 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

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An overview of the perspectives used in health economic evaluations

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Between now and later: a mixed methods study of HPV vaccination delay among Chinese caregivers in urban Chengdu, China

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Clinical coding of long COVID in primary care 2020–2023 in a cohort of 19 million adults: an OpenSAFELY analysis

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Publication year

2024

Journal title

EClinicalMedicine

Volume

72

10.1016/j.eclinm.2024.102638

Abstract

Abstract

Background: 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

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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

2024

Journal title

PLoS Medicine

Volume

21

Issue

7

10.1371/journal.pmed.1004429

COVID-19-related health utility values and changes in COVID-19 patients and the general population: a scoping review

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Effectiveness and efficiency of immunisation strategies to prevent RSV among infants and older adults in Germany: a modelling study

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Effects of sequential vs single pneumococcal vaccination on cardiovascular diseases among older adults: a population-based cohort study

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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

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Estimating the health effects of COVID-19-related immunisation disruptions in 112 countries during 2020–30: a modelling study

Hartner, A. M., Li, X., Echeverria-Londono, S., Roth, J., Abbas, K., Auzenbergs, M., De Villiers, M. J., Ferrari, M. J., Fraser, K., Fu, H., Hallett, T., Hinsley, W., Jit, M., Karachaliou, A., Moore, S. M., Nayagam, S., Papadopoulos, T., Perkins, T. A., Portnoy, A., … Gaythorpe, K. A. (n.d.).

Publication year

2024

Journal title

The Lancet Global Health

Volume

12

Issue

4

Page(s)

e563-e571

10.1016/S2214-109X(23)00603-4

Abstract

Abstract

Background: There have been declines in global immunisation coverage due to the COVID-19 pandemic. Recovery has begun but is geographically variable. This disruption has led to under-immunised cohorts and interrupted progress in reducing vaccine-preventable disease burden. There have, so far, been few studies of the effects of coverage disruption on vaccine effects. We aimed to quantify the effects of vaccine-coverage disruption on routine and campaign immunisation services, identify cohorts and regions that could particularly benefit from catch-up activities, and establish if losses in effect could be recovered. Methods: For this modelling study, we used modelling groups from the Vaccine Impact Modelling Consortium from 112 low-income and middle-income countries to estimate vaccine effect for 14 pathogens. One set of modelling estimates used vaccine-coverage data from 1937 to 2021 for a subset of vaccine-preventable, outbreak-prone or priority diseases (ie, measles, rubella, hepatitis B, human papillomavirus [HPV], meningitis A, and yellow fever) to examine mitigation measures, hereafter referred to as recovery runs. The second set of estimates were conducted with vaccine-coverage data from 1937 to 2020, used to calculate effect ratios (ie, the burden averted per dose) for all 14 included vaccines and diseases, hereafter referred to as full runs. Both runs were modelled from Jan 1, 2000, to Dec 31, 2100. Countries were included if they were in the Gavi, the Vaccine Alliance portfolio; had notable burden; or had notable strategic vaccination activities. These countries represented the majority of global vaccine-preventable disease burden. Vaccine coverage was informed by historical estimates from WHO–UNICEF Estimates of National Immunization Coverage and the immunisation repository of WHO for data up to and including 2021. From 2022 onwards, we estimated coverage on the basis of guidance about campaign frequency, non-linear assumptions about the recovery of routine immunisation to pre-disruption magnitude, and 2030 endpoints informed by the WHO Immunization Agenda 2030 aims and expert consultation. We examined three main scenarios: no disruption, baseline recovery, and baseline recovery and catch-up. Findings: We estimated that disruption to measles, rubella, HPV, hepatitis B, meningitis A, and yellow fever vaccination could lead to 49 119 additional deaths (95% credible interval [CrI] 17 248–134 941) during calendar years 2020–30, largely due to measles. For years of vaccination 2020–30 for all 14 pathogens, disruption could lead to a 2·66% (95% CrI 2·52–2·81) reduction in long-term effect from 37 378 194 deaths averted (34 450 249–40 241 202) to 36 410 559 deaths averted (33 515 397–39 241 799). We estimated that catch-up activities could avert 78·9% (40·4–151·4) of excess deaths between calendar years 2023 and 2030 (ie, 18 900 [7037–60 223] of 25 356 [9859–75 073]). Interpretation: Our results highlight the importance of the timing of catch-up activities, considering estimated burden to improve vaccine coverage in affected cohorts. We estimated that mitigation measures for measles and yellow fever were particularly effective at reducing excess burden in the short term. Additionally, the high long-term effect of HPV vaccine as an important cervical-cancer prevention tool warrants continued immunisation efforts after disruption. Funding: The Vaccine Impact Modelling Consortium, funded by Gavi, the Vaccine Alliance and the Bill & Melinda Gates Foundation. Translations: For the Arabic, Chinese, French, Portguese and Spanish translations of the abstract see Supplementary Materials section.

Estimating the impact of vaccination: lessons learned in the first phase of the Vaccine Impact Modelling Consortium

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Evaluating Scope and Bias of Population-Level Measles Serosurveys: A Systematized Review and Bias Assessment

Sbarra, A. N., Cutts, F. T., Fu, H., Poudyal, I., Rhoda, D. A., Mosser, J. F., & Jit, M. (n.d.).

Publication year

2024

Journal title

Vaccines

Volume

12

Issue

6

10.3390/vaccines12060585

Abstract

Abstract

Background: 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

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Health impact and cost-effectiveness of vaccination using potential next-generation influenza vaccines in Thailand: a modelling study

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Health-Related Quality of Life and Economic Burden Among Hospitalized Children with Hand, Foot, and Mouth Disease: A Multiregional Study in China

Zhou, T., Hu, H., Gao, J., Yu, H., Jit, M., & Wang, P. (n.d.).

Publication year

2024

Journal title

PharmacoEconomics - Open

Volume

8

Issue

3

Page(s)

459-469

10.1007/s41669-023-00468-1

Abstract

Abstract

Background: 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

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How mathematical modelling can inform outbreak response vaccination

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