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  • Journal article
    Charniga K, Park SW, Akhmetzhanov AR, Cori A, Dushoff J, Funk S, Gostic KM, Linton NM, Lison A, Overton CE, Pulliam JRC, Ward T, Cauchemez S, Abbott Set al., 2024,

    Best practices for estimating and reporting epidemiological delay distributions of infectious diseases

    , PLoS Computational Biology, Vol: 20, ISSN: 1553-734X

    Epidemiological delays are key quantities that inform public health policy and clinical practice. They are used as inputs for mathematical and statistical models, which in turn can guide control strategies. In recent work, we found that censoring, right truncation, and dynamical bias were rarely addressed correctly when estimating delays and that these biases were large enough to have knock-on impacts across a large number of use cases. Here, we formulate a checklist of best practices for estimating and reporting epidemiological delays. We also provide a flowchart to guide practitioners based on their data. Our examples are focused on the incubation period and serial interval due to their importance in outbreak response and modeling, but our recommendations are applicable to other delays. The recommendations, which are based on the literature and our experience estimating epidemiological delay distributions during outbreak responses, can help improve the robustness and utility of reported estimates and provide guidance for the evaluation of estimates for downstream use in transmission models or other analyses.

  • Journal article
    Bouverat C, Badjie J, Samateh T, Saidy T, Murray KA, Prentice AM, Maxwell N, Haines A, Vicedo Cabrera AM, Bonell Aet al., 2024,

    Integrating observational and modelled data to advance the understanding of heat stress effects on pregnant subsistence farmers in the gambia.

    , Sci Rep, Vol: 14

    Studies on the effect of heat stress on pregnant women are scarce, particularly in highly vulnerable populations. To support the risk assessment of pregnant subsistence farmers in the West Kiang district, The Gambia we conducted a study on the pathophysiological effects of extreme heat stress and assessed the applicability of heat stress indices. From ERA5 climate reanalysis we added location-specific modelled solar radiation to datasets of a previous observational cohort study involving on-site measurements of 92 women working in the heat. Associations between physiological and environmental variables were assessed through Pearson correlation coefficient analysis, mixed effect linear models with random intercepts per participant and confirmatory composite analysis. We found Pearson correlations between r-values of 0 and 0.54, as well as independent effects of environmental variables on skin- and tympanic temperature, but not on heart rate, within a confidence interval of 98%. Pregnant women experienced stronger pathophysiological effects from heat stress in their third rather than in their second trimester. Environmental heat stress significantly altered maternal heat strain, particularly under humid conditions above a 50% relative humidity threshold, demonstrating interactive effects. Based on our results, we recommend including heat stress indices (e.g. UTCI or WBGT) in local heat-health warning systems.

  • Other
    Delgado Vela J, Philo SE, Brown J, Taniuchi M, Cantrell M, Kossik A, Ramaswamy M, Ajjampur SS, Guerfali FZ, Holm RH, Meschke JS, Otero MCB, Pickering AJ, Rahman M, Shaw AG, Shrestha A, Sirikanchana K, Tevuzula VM, Halden RU, Boehm AB, Bibby Ket al., 2024,

    Moving beyond Wastewater: Perspectives on Environmental Surveillance of Infectious Diseases for Public Health Action in Low-Resource Settings.

  • Journal article
    Hancock PA, North A, Leach AW, Winskill P, Ghani AC, Godfray HCJ, Burt A, Mumford JDet al., 2024,

    The potential of gene drives in malaria vector species to control malaria in African environments

    , NATURE COMMUNICATIONS, Vol: 15
  • Journal article
    Pickles M, Mountain E, Bhattacharjee P, Kioko J, Musimbi J, Musyoki H, Gichangi P, Stannah J, Maheu-Giroux M, Becker M, Boily M-Cet al., 2024,

    Exploratory analysis of the potential impact of violence on HIV among female sex workers in Mombasa, Kenya: a mathematical modelling study

    , BMC Medicine, Vol: 22, ISSN: 1741-7015

    BackgroundUnderstanding the frequency of violence experienced by female sex workers (FSWs) and how violence contributes to HIV transmission can help improve HIV programs.MethodsUsing recent recommendations for modelling structural factors and associated causal pathways, we developed a HIV transmission dynamic model for FSWs and their clients in Mombasa, Kenya, mechanistically representing three types of violence (sexual violence, SV; physical violence, PV; police assault and arrest, PAA). Each type of violence affects HIV transmission through key mediators (condom non-use, HIV testing). We parameterized the model using data from a cross-sectional study of FSWs aged 15–24 recruited from a systematic geographical mapping sampling frame in Mombasa, Kenya (Cheuk E et al., Frontiers in Reproductive Health 2(7), 2020). Using this model, calibrated (and cross-validated) to HIV epidemiological and violence outcomes, we estimated the incidence of violence episodes, the contribution of violence to the HIV epidemic measured by the transmission population-attributable fraction, and the potential impact of possible violence interventions.ResultsThe median estimated incidence of PAA in 2023 among FSWs who had not previously experienced that type of violence was 0.20 (95% credible interval: 0.17–0.22) per person-year (ppy), about double the incidence of SV and PV (0.10 (0.09–0.11), 0.11 (0.09–0.12), respectively). The incidence of violence was higher among FSWs who had previously experienced violence: the incidence of recurrent PV was 2.65 (1.82–3.37) ppy, while the incidence of recurrent SV and PAA were 1.26 (0.80–1.67) and 1.37 (0.94–1.74 ppy, respectively. In this setting, we estimated that a median of 35.3% (3.4–55.8%) infections in FSWs and clients combined over the next 10 years may be due to all types of violence (and mediators), mainly through reduced condom use in FSWs who have ever experienced SV (34.6% (2.4–55.5%)).

  • Journal article
    Biggs J, Challenger J, Hellewell J, Churcher TS, Cook Jet al., 2024,

    A systematic review of sample size estimation accuracy on power in malaria cluster randomised trials measuring epidemiological outcomes

    , BMC Medical Research Methodology, Vol: 24, ISSN: 1471-2288

    IntroductionCluster randomised trials (CRTs) are the gold standard for measuring the community-wide impacts of malaria control tools. CRTs rely on well-defined sample size estimations to detect statistically significant effects of trialled interventions, however these are often predicted poorly by triallists. Here, we review the accuracy of predicted parameters used in sample size calculations for malaria CRTs with epidemiological outcomes.MethodsWe searched for published malaria CRTs using four online databases in March 2022. Eligible trials included those with malaria-specific epidemiological outcomes which randomised at least six geographical clusters to study arms. Predicted and observed sample size parameters were extracted by reviewers for each trial. Pair-wise Spearman’s correlation coefficients (rs) were calculated to assess the correlation between predicted and observed control-arm outcome measures and effect sizes (relative percentage reductions) between arms. Among trials which retrospectively calculated an estimate of heterogeneity in cluster outcomes, we recalculated study power according to observed trial estimates.ResultsOf the 1889 records identified and screened, 108 articles were eligible and comprised of 71 malaria CRTs. Among 91.5% (65/71) of trials that included sample size calculations, most estimated cluster heterogeneity using the coefficient of variation (k) (80%, 52/65) which were often predicted without using prior data (67.7%, 44/65). Predicted control-arm prevalence moderately correlated with observed control-arm prevalence (rs: 0.44, [95%CI: 0.12,0.68], p-value < 0.05], with 61.2% (19/31) of prevalence estimates overestimated. Among the minority of trials that retrospectively calculated cluster heterogeneity (20%, 13/65), empirical values contrasted with those used in sample size estimations and often compromised study power. Observed effect sizes were often smaller than had been predicted at the sample size stage

  • Journal article
    Scachetti GC, Forato J, Claro IM, Hua X, Salgado BB, Vieira A, Simeoni CL, Barbosa ARC, Rosa IL, de Souza GF, Fernandes LCN, de Sena ACH, Oliveira SC, Singh CML, de Lima STS, de Jesus R, Costa MA, Kato RB, Rocha JF, Santos LC, Rodrigues JT, Cunha MP, Sabino EC, Faria NR, Weaver SC, Romano CM, Lalwani P, Proenca-Modena JL, de Souza WMet al., 2024,

    Re-emergence of Oropouche virus between 2023 and 2024 in Brazil: an observational epidemiological study.

    , Lancet Infect Dis

    BACKGROUND: Oropouche virus is an arthropod-borne virus that has caused outbreaks of Oropouche fever in central and South America since the 1950s. This study investigates virological factors contributing to the re-emergence of Oropouche fever in Brazil between 2023 and 2024. METHODS: In this observational epidemiological study, we combined multiple data sources for Oropouche virus infections in Brazil and conducted in-vitro and in-vivo characterisation. We collected serum samples obtained in Manaus City, Amazonas state, Brazil, from patients with acute febrile illnesses aged 18 years or older who tested negative for malaria and samples from people with previous Oropouche virus infection from Coari municipality, Amazonas state, Brazil. Basic clinical and demographic data were collected from the Brazilian Laboratory Environment Management System. We calculated the incidence of Oropouche fever cases with data from the Brazilian Ministry of Health and the 2022 Brazilian population census and conducted age-sex analyses. We used reverse transcription quantitative PCR to test for Oropouche virus RNA in samples and subsequently performed sequencing and phylogenetic analysis of viral isolates. We compared the phenotype of the 2023-24 epidemic isolate (AM0088) with the historical prototype strain BeAn19991 through assessment of titre, plaque number, and plaque size. We used a plaque reduction neutralisation test (PRNT50) to assess the susceptibility of the novel isolate and BeAn19991 isolate to antibody neutralisation, both in serum samples from people previously infected with Oropouche virus and in blood collected from mice that were inoculated with either of the strains. FINDINGS: 8639 (81·8%) of 10 557 laboratory-confirmed Oropouche fever cases from Jan 4, 2015, to Aug 10, 2024, occurred in 2024, which is 58·8 times the annual median of 147 cases (IQR 73-325). Oropouche virus infections were reported in all 27 federal units, with 8182 (77·5%) of

  • Journal article
    Sangkaew S, Tumviriyakul H, Cheranakhorn C, Songumpai N, Pinpathomrat N, Seeyankem B, Yasharad K, Loomcharoen P, Pakdee W, Changawej C, Dumrongkullachart D, Limheng A, Dorigatti Iet al., 2024,

    Unveiling post-COVID-19 syndrome: incidence, biomarkers, and clinical phenotypes in a Thai population

    , BMC Infectious Diseases, Vol: 24, ISSN: 1471-2334

    BackgroundPost-COVID- 19 syndrome (PCS) significantly impacts the quality of life of survivors. There is, however, a lack of a standardized approach to PCS diagnosis and management. Our bidirectional cohort study aimed to estimate PCS incidence, identify risk factors and biomarkers, and classify clinical phenotypes for enhanced management to improve patient outcomes.MethodsA bidirectional prospective cohort study was conducted at five medical sites in Hatyai district in Songkhla Province, Thailand. Participants were randomly selected from among the survivors of COVID-19 aged≥18 years between May 15, 2022, and January 31, 2023. The selected participants underwent a scheduled outpatient visit for symptom and health assessments 12 to 16 weeks after the acute onset of infection, during which PCS was diagnosed and blood samples were collected for hematological, inflammatory, and serological tests. PCS was defined according to the World Health Organization criteria. Univariate and multiple logistic regression analyses were used to identify biomarkers associated with PCS. Moreover, three clustering methods (agglomerative hierarchical, divisive hierarchical, and K-means clustering) were applied, and internal validation metrics were used to determine clustering and similarities in phenotypes.FindingsA total of 300 survivors were enrolled in the study, 47% of whom developed PCS according to the World Health Organization (WHO) definition. In the sampled cohort, 66.3% were females, and 79.4% of them developed PCS (as compared to 54.7% of males, p-value <0.001). Comorbidities were present in 19% (57/300) of all patients, with 11% (18/159) in the group without PCS and 27.7% (39/141) in the group with PCS. The incidence of PCS varied depending on the criteria used and reached 13% when a quality of life indicator was added to the WHO definition. Common PCS symptoms were hair loss (22%) and fatigue (21%), while mental health symptoms were less frequent (insomnia 3%, dep

  • Journal article
    Rhodes J, Jacobs J, Dennis EK, Manjari SR, Banavali NK, Marlow R, Rokebul MA, Chaturvedi S, Chaturvedi Vet al., 2024,

    What makes Candida auris pan-drug resistant? Integrative insights from genomic, transcriptomic, and phenomic analysis of clinical strains resistant to all four major classes of antifungal drugs

    , Antimicrobial Agents and Chemotherapy, Vol: 68, ISSN: 0066-4804

    The global epidemic of drug-resistant Candida auris continues unabated. The initial report on pan-drug resistant (PDR) C. auris strains in a hospitalized patient in New York was unprecedented. PDR C. auris showed both known and unique mutations in the prominent gene targets of azoles, amphotericin B, echinocandins, and flucytosine. However, the factors that allow C. auris to acquire pan-drug resistance are not known. Therefore, we conducted a genomic, transcriptomic, and phenomic analysis to better understand PDR C. auris. Among 1,570 genetic variants in drug-resistant C. auris, 299 were unique to PDR strains. The whole-genome sequencing results suggested perturbations in genes associated with nucleotide biosynthesis, mRNA processing, and nuclear export of mRNA. Whole transcriptome sequencing of PDR C. auris revealed two genes to be significantly differentially expressed—a DNA repair protein and DNA replication-dependent chromatin assembly factor 1. Of 59 novel transcripts, 12 transcripts had no known homology. We observed no fitness defects among multi-drug resistant (MDR) and PDR C. auris strains grown in nutrient-deficient or -enriched media at different temperatures. Phenotypic profiling revealed wider adaptability to nitrogenous nutrients and increased utilization of substrates critical in upper glycolysis and tricarboxylic acid cycle. Structural modeling of a 33-amino acid deletion in the gene for uracil phosphoribosyl transferase suggested an alternate route in C. auris to generate uracil monophosphate that does not accommodate 5-fluorouracil as a substrate. Overall, we find evidence of metabolic adaptations in MDR and PDR C. auris in response to antifungal drug lethality without deleterious fitness costs.

  • Journal article
    Aliaga-Samanez A, Romero D, Murray K, Cobos-Mayo M, Segura M, Real R, Olivero Jet al., 2024,

    Climate change is aggravating dengue and yellow fever transmission risk

    , Ecography, Vol: 2024, ISSN: 0906-7590

    Dengue and yellow fever have complex cycles, involving urban and sylvatic mosquitoes, and non-human primate hosts. To date, efforts to assess the effect of climate change on these diseases have neglected the combination of such crucial factors. Recent studies only considered urban vectors. This is the first study to include them together with sylvatic vectors and the distribution of primates to analyse the effect of climate change on these diseases. We used previously published models, based on machine learning algorithms and fuzzy logic, to identify areas where climatic favourability for the relevant transmission agents could change: 1) favourable areas for the circulation of the viruses due to the environment and to non-human primate distributions; 2) the favourability for urban and sylvatic vectors. We obtained projections of future transmission risk for two future periods and for each disease, and implemented uncertainty analyses to test for predictions reliability. Areas currently favourable for both diseases could keep being climatically favourable, while global favourability could increase a 7% for yellow fever and a 10% increase for dengue. Areas likely to be more affected in the future for dengue include West Africa, South Asia, the Gulf of Mexico, Central America and the Amazon basin. A possible spread of dengue could take place into Europe, the Mediterranean basin, the UK and Portugal; and, in Asia, into northern China. For yellow fever, climate could become more favourable in Central and Southeast Africa; India; and in north and southeast South America, including Brazil, Paraguay, Bolivia, Peru, Colombia and Venezuela. In Brazil, favourability for yellow fever will probably increase in the south, the west and the east. Areas where the transmission risk spread is consistent to the dispersal of vectors are highlighted in respect of areas where the expected spread is directly attributable to environmental changes. Both scenarios could involve different prev

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