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• Journal article
  Walters M, Korenromp E, Yakusik A, Wanyeki I, Kaboré A, Poimouribou A, Ki C, Dao C, Bambara P, Derme S, Ouedraogo T, Tang KH, Boily MC, Mahy M, Imai-Eaton Jet al., 2024,

  Guidance for triangulating data and estimates of HIV prevalence among pregnant women and coverage of PMTCT using the Spectrum AIDS Impact Module

  , JAIDS: Journal of Acquired Immune Deficiency Syndromes, Vol: 97, Pages: 439-449, ISSN: 1525-4135

  Background: Most countries use the Spectrum AIDS Impact Module (Spectrum-AIM), antenatal care routine HIV testing, and antiretroviral treatment data to estimate HIV prevalence among pregnant women. Non-representative programme data may lead to inaccurate estimates HIV prevalence and treatment coverage for pregnant women. Setting: 154 countries and subnational locations across 126 countries.Methods: Using 2023 UNAIDS HIV estimates, we calculated three ratios: (1) HIV prevalence among pregnant women to all women 15-49y (prevalence), (2) ART coverage before pregnancy to women 15-49y ART coverage (ART pre-pregnancy), and (3) ART coverage at delivery to women 15-49y ART coverage (PMTCT coverage). We developed an algorithm to identify and adjust inconsistent results within regional ranges in Spectrum-AIM, illustrated using Burkina Faso’s estimates.Results: In 2022, the mean regional ratio of prevalence among pregnant women to all women ranged from 0.68 to 0.95. ART coverage pre-pregnancy ranged by region from 0.40 to 1.22 times ART coverage among all women. Mean regional PMTCT coverage ratios ranged from 0.85 to 1.51. The prevalence ratio in Burkina Faso was 1.59, above the typical range 0.62-1.04 in western and central Africa. Antenatal clinics reported more PMTCT recipients than estimated HIV-positive pregnant women from 2015 to 2019. We adjusted inputted PMTCT programme data to enable consistency of HIV prevalence among pregnant women from programmatic routine HIV testing at antenatal clinics with values typical for Western and central Africa. Conclusion: These ratios offer Spectrum-AIM users a tool to gauge the consistency of their HIV prevalence and treatment coverage estimates among pregnant women with other countries in the region.

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• Journal article
  Grant R, de Kraker MEA, Buetti N, Jackson H, Abbas M, Sobel JA, Sommerstein R, Eder M, Balmelli C, Troillet N, Schreiber PW, Jent P, Senn L, Flury D, Tschudin-Sutter S, Buettcher M, Suveges M, Urbini L, Keiser O, Roder U, Harbarth S, Zanella M-C, CH SUR Study Group Cet al., 2024,

  In-hospital Outcomes of Healthcare-associated Coronavirus Disease 2019 (Omicron) Versus Healthcare-associated Influenza: A Retrospective, Nationwide Cohort Study in Switzerland

  , CLINICAL INFECTIOUS DISEASES, ISSN: 1058-4838
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• Journal article
  Geismar C, White PJ, Cori A, Jombart Tet al., 2024,

  Sorting out assortativity: when can we assess the contributions of different population groups to epidemic transmission?

  , PLoS One, Vol: 19, ISSN: 1932-6203

  Characterising the transmission dynamics between various population groups is critical for implementing effective outbreak control measures whilst minimising financial costs and societal disruption. While recent technological and methodological advances have made individual-level transmission chain data increasingly available, it remains unclear how effectively this data can inform group-level transmission patterns, particularly in small, rapidly saturating outbreak settings. We introduce a novel framework that leverages transmission chain data to estimate group transmission assortativity; this quantifies the extent to which individuals transmit within their own group compared to others. Through extensive simulations mimicking nosocomial outbreaks, we assessed the conditions under which our estimator performs effectively and established guidelines for minimal data requirements in small outbreak settings where saturation may occur rapidly. Notably, we demonstrate that detecting and quantifying transmission assortativity is most reliable when at least 30 cases have been observed in each group, before reaching their respective epidemic peaks.

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• Journal article
  Nash R, Bhatia S, Morgenstern C, Doohan P, Jorgensen D, McCain K, McCabe R, Nikitin D, Forna A, Cuomo-Dannenburg G, Hicks J, Sheppard R, Naidoo T, van Elsland S, Geismar C, Rawson T, Leuba S, Wardle J, Routledge I, Fraser K, Imai-Eaton N, Cori A, Unwin HJTet al., 2024,

  Ebola virus disease mathematical models and epidemiological parameters: a systematic review

  , Lancet Infectious Diseases, Vol: 24, Pages: E762-E773, ISSN: 1473-3099

  Ebola virus disease poses a recurring risk to human health. We conducted a systematic review (PROSPERO CRD42023393345) of Ebola virus disease transmission models and parameters published from database inception to July 7, 2023, from PubMed and Web of Science. Two people screened each abstract and full text. Papers were extracted with a bespoke Access database, 10% were double extracted. We extracted 1280 parameters and 295 models from 522 papers. Basic reproduction number estimates were highly variable, as were effective reproduction numbers, likely reflecting spatiotemporal variability in interventions. Random-effect estimates were 15·4 days (95% CI 13·2–17·5) for the serial interval, 8·5 days (7·7–9·2) for the incubation period, 9·3 days (8·5–10·1) for the symptom-onset-to-death delay, and 13·0 days (10·4–15·7) for symptom-onset-to-recovery. Common effect estimates were similar, albeit with narrower CIs. Case-fatality ratio estimates were generally high but highly variable, which could reflect heterogeneity in underlying risk factors. Although a substantial body of literature exists on Ebola virus disease models and epidemiological parameter estimates, many of these studies focus on the west African Ebola epidemic and are primarily associated with Zaire Ebola virus, which leaves a key gap in our knowledge regarding other Ebola virus species and outbreak contexts.

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• Journal article
  Shankar M, Hartner A-M, Arnold CRK, Gayawan E, Kang H, Kim J-H, Gilani GN, Cori A, Fu H, Jit M, Muloiwa R, Portnoy A, Trotter C, Gaythorpe KAMet al., 2024,

  How mathematical modelling can inform outbreak response vaccination

  , BMC INFECTIOUS DISEASES, Vol: 24
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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, Vol: 31, 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
  Wangdi K, Unwin HJT, Penjor K, Tsheten T, Tobgyal, Clements A, Gray D, Kotepui M, Bhatt S, Gething Pet al., 2024,

  Estimating the impact of imported malaria on local transmission in a near elimination setting: a case study from Bhutan

  , LANCET REGIONAL HEALTH - SOUTHEAST ASIA, Vol: 31, ISSN: 2772-3682
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• Journal article
  Kwok KO, Huynh T, Wei WI, Wong SYS, Riley S, Tang Aet al., 2024,

  Utilizing large language models in infectious disease transmission modelling for public health preparedness

  , COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, Vol: 23, Pages: 3254-3257, ISSN: 2001-0370
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• Journal article
  Smith DRM, Turner J, Fahr P, Attfield LA, Bessell PR, Donnelly CA, Gibb R, Jones KE, Redding DW, Asogun D, Ayodeji OO, Azuogu BN, Fischer WA, Jan K, Olayinka AT, Wohl DA, Torkelson AA, Dinkel KA, Nixon EJ, Pouwels KB, Hollingsworth TDet al., 2024,

  Health and economic impacts of Lassa vaccination campaigns in West Africa

  , NATURE MEDICINE, Vol: 30, ISSN: 1078-8956
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• Journal article
  Doohan P, Jorgensen D, Naidoo T, McCain K, Hicks J, McCabe R, Bhatia S, Charniga K, Cuomo-Dannenburg G, Hamlet A, Nash R, Nikitin D, Rawson T, Sheppard R, Unwin H, van Elsland S, Cori A, Morgenstern C, Imai Net al., 2024,

  Lassa fever outbreaks, mathematical models, and disease parameters: a systematic review and meta-analysis

  , The Lancet Global Health, Vol: 12, Pages: e1962-e1972, ISSN: 2214-109X

  BackgroundUnderstanding the epidemiological parameters and transmission dynamics of Lassa fever, a significant public health threat in west Africa caused by the rodent-borne Lassa virus, is crucial for informing evidence-based interventions and outbreak response strategies. Therefore, our study aimed to collate and enhance understanding of the key epidemiological parameters of Lassa fever.MethodsWe conducted a systematic review, searching PubMed and Web of Science for peer-reviewed studies published from database inception up to June 13, 2024, to compile and analyse key epidemiological parameters, mathematical models, and outbreaks of Lassa fever. English-language, peer-reviewed, original research articles were included if they reported on Lassa fever outbreak sizes, transmission models, viral evolution, transmission, natural history, severity, seroprevalence, or risk factors. Non-peer-reviewed literature was excluded. Data were extracted by two independent individuals from published literature, focusing on seroprevalence, transmissibility, epidemiological delays, and disease severity. We performed a meta-analysis to calculate pooled estimates of case-fatality ratios (CFRs) and the delay from symptom onset to hospital admission. This study is registered with PROSPERO (identifier number CRD42023393345).FindingsThe database search returned 5614 potentially relevant studies, and a further 16 studies were identified from backward citation chaining. After de-duplication and exclusion, 193 publications met our inclusion criteria and provided 440 relevant parameter estimates in total. Although Lassa virus is endemic in west Africa, the spatiotemporal coverage of general-population seroprevalence estimates (ranging from 2·6% [6/232] to 58·2% [103/177]) was poor, highlighting the spatial uncertainty in Lassa fever risk. Similarly, only four basic reproduction number estimates (ranging from 1·13 to 1·40) were available. We estimated a pooled total

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