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• Journal article
  Belman S, Pesonen H, Croucher NJ, Bentley SD, Corander Jet al., 2024,

  Estimating between-country migration in pneumococcal populations

  , G3-GENES GENOMES GENETICS, Vol: 14, ISSN: 2160-1836
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• Journal article
  Khurana MP, Scheidwasser-Clow N, Penn MJ, Bhatt S, Duchene DAet al., 2024,

  The Limits of the Constant-rate Birth-Death Prior for Phylogenetic Tree Topology Inference

  , SYSTEMATIC BIOLOGY, Vol: 73, Pages: 235-246, ISSN: 1063-5157
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• Journal article
  Shattock AJ, Johnson HC, Sim SY, Carter A, Lambach P, Hutubessy RCW, Thompson KM, Badizadegan K, Lambert B, Ferrari MJ, Jit M, Fu H, Silal SP, Hounsell RA, White RG, Mosser JF, Gaythorpe KAM, Trotter CL, Lindstrand A, O'Brien KL, Bar-Zeev Net al., 2024,

  Contribution of vaccination to improved survival and health: modelling 50 years of the Expanded Programme on Immunization

  , LANCET, Vol: 403, Pages: 2307-2316, ISSN: 0140-6736
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• Journal article
  Manley H, Bayley T, Danelian G, Burton L, Finnie T, Charlett A, Watkins NA, Birrell P, De Angelis D, Keeling M, Funk S, Medley G, Pellis L, Baguelin M, Ackland GJ, Hutchinson J, Riley S, Panovska-Griffiths Jet al., 2024,

  Combining models to generate consensus medium-term projections of hospital admissions, occupancy and deaths relating to COVID-19 in England

  , ROYAL SOCIETY OPEN SCIENCE, Vol: 11, ISSN: 2054-5703
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• Journal article
  Akullian A, Akulu R, Aliyu G, Anam F, Guichard A-C, Ayles H, Baggaley R, Bansi-Matharu L, Baptiste SL, Bershteyn A, Cambiano V, Carter A, Chotun N, Citron DT, Crowley S, Dalal S, Edun O, Fraser C, Galvani AP, Garnett GP, Glabius R, Godfrey-Faussett P, Grabowski MK, Gray GE, Hargreaves JR, Imai-Eaton JW, Johnson LF, Kaftan D, Kagaayi J, Kataika E, Kilonzo N, Kirungi WL, Korenromp EL, Kouton M-H, Lucie Abeler-Dörner L, Mahy M, Mangal TD, Martin-Hughes R, Matsikure S, Meyer-Rath G, Mishra S, Mmelesi M, Mohammed A, Moolla H, Morrison MR, Moyo S, Mudimu E, Mugabe M, Murenga M, Ng'ang'a J, Olaifa Y, Phillips AN, Pickles MREH, Probert WJM, Ramaabya D, Rautenbach SP, Revill P, Shakarishvili A, Sheneberger R, Smith J, Stegling C, Stover J, Tanser F, Taramusi I, ten Brink D, Whittles LK, Zaidi Iet al., 2024,

  The HIV response beyond 2030: preparing for decades of sustained HIV epidemic control in eastern and southern Africa

  , The Lancet, ISSN: 0140-6736
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• Journal article
  Mandal S, Bhatia V, Bhargava A, Rijal S, Arinaminpathy Net al., 2024,

  The potential impact on tuberculosis of interventions to reduce undernutrition in the WHO South-East Asian Region: a modelling analysis

  , The Lancet Regional Health - Southeast Asia, ISSN: 2772-3682

  BackgroundUndernutrition is a major risk factor for TB incidence in the WHO South-East (SE) Asia Region. We examined the potential impact of addressing undernutrition as a preventive measure, for reducing TB burden in region.MethodsWe developed a deterministic, compartmental mathematical model, capturing undernutrition and its associated excess risk of TB, amongst countries in the Region. We simulated two types of interventions: (i) nutritional rehabilitation amongst all close contacts of TB patients, and (ii) an illustrative, population-wide scenario where 30% of people with undernutrition would be nutritionally rehabilitated each year. We also simulated this impact with additional measures to improve the TB care cascade.FindingsThe impact of nutritional interventions varies by country. For example, in India nutritional rehabilitation of 30% of undernourished population each year would avert 15.9% (95% Uncertainty Intervals (UI) 11.8–21.3) of cumulative incidence between 2023 and 2030, contrasting with 4.8% (95% UI 2.9–9.5) for Bhutan, which has only 10.9% prevalence of undernutrition. Reductions in cumulative mortality range from 11.6% (95% UI 8.2–17.1) for Bhutan, to 26.0% (95% UI 22.4–30.8) for India. Comparable incremental reductions in TB burden arise when combined with measures to improve the TB care cascade. Overall, nutritional interventions in the general population would increase incidence reductions by 2–3 fold, and mortality reductions by 5–6 fold, relative to targeting only contacts.InterpretationNutritional interventions could cause substantial reductions in TB burden in the Region. Their health benefits extend well beyond TB, underlining their importance for public health.FundingNone.

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• Journal article
  Turner H, Kura K, Roth B, Kuesel AC, Kinrade S, Basanez MGet al., 2024,

  An updated economic assessment of moxidectin treatment strategies for onchocerciasis elimination

  , Clinical Infectious Diseases, Vol: 78, Pages: S138-S145, ISSN: 1058-4838

  Background:Concerns that annual mass administration of ivermectin, the predominant strategy for onchocerciasis control/elimination, may not lead to elimination of parasite transmission (EoT) in all endemic areas, has increased interest in alternative treatment strategies. One such strategy is moxidectin. We performed an updated economic assessment of moxidectin- relative to ivermectin-based strategies.Methods:We investigated annual and biannual community-directed treatment with ivermectin (aCDTI, bCDTI) and moxidectin (aCDTM, bCDTM) implemented with minimal or enhanced coverage (65% or 80% of the total population taking the drug, respectively) in intervention-naïve areas with 30%, 50% or 70% microfilarial baseline prevalence (representative of hypo-, meso- and hyperendemic areas). We compared programmatic delivery costs for the number of treatments achieving 90% probability of EoT (EoT90), calculated with the individual-based stochastic transmission model EPIONCHO-IBM. We used the costs for 40 years of programme delivery when EoT90 was not reached earlier. Delivery costs do not include the drug costs. Results:aCDTM and bCDTM achieved EoT90 with lower programmatic delivery costs than aCDTI with one exception: aCDTM with minimal coverage did not achieve EoT90 in hyperendemic areas within 40 years. With minimal coverage, bCDTI delivery costs as much or more than aCDTM and bCDTM. With enhanced coverage, programmatic delivery costs for aCDTM and bCDTM were lower than for aCDTI and bCDTI. Conclusions:Moxidectin-based strategies could accelerate progress towards EoT and reduce programmatic delivery costs compared to ivermectin-based strategies. The costs of moxidectin to national programmes are needed to quantify whether delivery cost reductions will translate into overall programme cost reduction.

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• Journal article
  Kura K, Mutono N, Basáñez M-G, Collyer BS, Coffeng LE, Thumbi SM, Anderson RMet al., 2024,

  How does treatment coverage and proportion never treated influence the success of Schistosoma mansoni elimination as a public health problem by 2030?

  , Clinical Infectious Diseases, Vol: 78, Pages: S126-S130, ISSN: 1058-4838

  BackgroundThe 2030 target for schistosomiasis is elimination as a public health problem (EPHP), achieved when the prevalence of heavy-intensity infection among school-aged children (SAC) reduces to <1%. To achieve this, the new World Health Organization guidelines recommend a broader target of population to include pre-SAC and adults. However, the probability of achieving EPHP should be expected to depend on patterns in repeated uptake of mass drug administration by individuals.MethodsWe employed 2 individual-based stochastic models to evaluate the impact of school-based and community-wide treatment and calculated the number of rounds required to achieve EPHP for Schistosoma mansoni by considering various levels of the population never treated (NT). We also considered 2 age-intensity profiles, corresponding to a low and high burden of infection in adults.ResultsThe number of rounds needed to achieve this target depends on the baseline prevalence and the coverage used. For low- and moderate-transmission areas, EPHP can be achieved within 7 years if NT ≤10% and NT <5%, respectively. In high-transmission areas, community-wide treatment with NT <1% is required to achieve EPHP.ConclusionsThe higher the intensity of transmission, and the lower the treatment coverage, the lower the acceptable value of NT becomes. Using more efficacious treatment regimens would permit NT values to be marginally higher. A balance between target treatment coverage and NT values may be an adequate treatment strategy depending on the epidemiological setting, but striving to increase coverage and/or minimize NT can shorten program duration.

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• Journal article
  Kura K, Stolk WA, Basáñez M-G, Collyer BS, de Vlas SJ, Diggle PJ, Gass K, Graham M, Hollingsworth TD, King JD, Krentel A, Anderson RM, Coffeng LEet al., 2024,

  How does the proportion of never treatment influence the success of mass drug administration programs for the elimination of lymphatic filariasis?

  , Clinical Infectious Diseases, Vol: 78, Pages: S93-S100, ISSN: 1058-4838

  BackgroundMass drug administration (MDA) is the cornerstone for the elimination of lymphatic filariasis (LF). The proportion of the population that is never treated (NT) is a crucial determinant of whether this goal is achieved within reasonable time frames.MethodsUsing 2 individual-based stochastic LF transmission models, we assess the maximum permissible level of NT for which the 1% microfilaremia (mf) prevalence threshold can be achieved (with 90% probability) within 10 years under different scenarios of annual MDA coverage, drug combination and transmission setting.ResultsFor Anopheles-transmission settings, we find that treating 80% of the eligible population annually with ivermectin + albendazole (IA) can achieve the 1% mf prevalence threshold within 10 years of annual treatment when baseline mf prevalence is 10%, as long as NT <10%. Higher proportions of NT are acceptable when more efficacious treatment regimens are used. For Culex-transmission settings with a low (5%) baseline mf prevalence and diethylcarbamazine + albendazole (DA) or ivermectin + diethylcarbamazine + albendazole (IDA) treatment, elimination can be reached if treatment coverage among eligibles is 80% or higher. For 10% baseline mf prevalence, the target can be achieved when the annual coverage is 80% and NT ≤15%. Higher infection prevalence or levels of NT would make achieving the target more difficult.ConclusionsThe proportion of people never treated in MDA programmes for LF can strongly influence the achievement of elimination and the impact of NT is greater in high transmission areas. This study provides a starting point for further development of criteria for the evaluation of NT.

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• Journal article
  Vasconcelos A, King JD, Nunes-Alves C, Anderson R, Argaw D, Basáñez M-G, Bilal S, Blok DJ, Blumberg S, Borlase A, Brady OJ, Browning R, Chitnis N, Coffeng LE, Crowley EH, Cucunubá ZM, Cummings DAT, Davis CN, Davis EL, Dixon M, Dobson A, Dyson L, French M, Fronterre C, Giorgi E, Huang C-I, Jain S, James A, Kim SH, Kura K, Lucianez A, Marks M, Mbabazi PS, Medley GF, Michael E, Montresor A, Mutono N, Mwangi TS, Rock KS, Saboyá-Díaz M-I, Sasanami M, Schwehm M, Spencer SEF, Srivathsan A, Stawski RS, Stolk WA, Sutherland SA, Tchuenté L-AT, de Vlas SJ, Walker M, Brooker SJ, Hollingsworth TD, Solomon AW, Fall ISet al., 2024,

  Accelerating progress towards the 2030 neglected tropical diseases targets: how can quantitative modeling support programmatic decisions?

  , Clinical Infectious Diseases, Vol: 78, Pages: S83-S92, ISSN: 1058-4838

  Over the past decade, considerable progress has been made in the control, elimination, and eradication of neglected tropical diseases (NTDs). Despite these advances, most NTD programs have recently experienced important setbacks; for example, NTD interventions were some of the most frequently and severely impacted by service disruptions due to the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modeling can help inform selection of interventions to meet the targets set out in the NTD road map 2021-2030, and such studies should prioritize questions that are relevant for decision-makers, especially those designing, implementing, and evaluating national and subnational programs. In September 2022, the World Health Organization hosted a stakeholder meeting to identify such priority modeling questions across a range of NTDs and to consider how modeling could inform local decision making. Here, we summarize the outputs of the meeting, highlight common themes in the questions being asked, and discuss how quantitative modeling can support programmatic decisions that may accelerate progress towards the 2030 targets.

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