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Strain-specific estimation of epidemic success provides insights into the transmission dynamics of tuberculosis.

ABSTRACT: The transmission dynamics of tuberculosis involves complex interactions of socio-economic and, possibly, microbiological factors. We describe an analytical framework to infer factors of epidemic success based on the joint analysis of epidemiological, clinical and pathogen genetic data. We derive isolate-specific, genetic distance-based estimates of epidemic success, and we represent success-related time-dependent concepts, namely epidemicity and endemicity, by restricting analysis to specific time scales. The method is applied to analyze a surveillance-based cohort of 1,641 tuberculosis patients with minisatellite-based isolate genotypes. Known predictors of isolate endemicity (older age, native status) and epidemicity (younger age, sputum smear positivity) were identified with high confidence (P?

SUBMITTER: Rasigade JP

PROVIDER: S-EPMC5368603 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Strain-specific estimation of epidemic success provides insights into the transmission dynamics of tuberculosis.

Rasigade Jean-Philippe JP Barbier Maxime M Dumitrescu Oana O Pichat Catherine C Carret Gérard G Ronnaux-Baron Anne-Sophie AS Blasquez Ghislaine G Godin-Benhaim Christine C Boisset Sandrine S Carricajo Anne A Jacomo Véronique V Fredenucci Isabelle I Pérouse de Montclos Michèle M Flandrois Jean-Pierre JP Ader Florence F Supply Philip P Lina Gérard G Wirth Thierry T

Scientific reports 20170328

The transmission dynamics of tuberculosis involves complex interactions of socio-economic and, possibly, microbiological factors. We describe an analytical framework to infer factors of epidemic success based on the joint analysis of epidemiological, clinical and pathogen genetic data. We derive isolate-specific, genetic distance-based estimates of epidemic success, and we represent success-related time-dependent concepts, namely epidemicity and endemicity, by restricting analysis to specific ti ...[more]

PMID: 28349973

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Project description:BackgroundFrom March to June 2022, an Omicron BA.2 epidemic occurred in Shanghai. We aimed to better understand the transmission dynamics and identify age-specific transmission characteristics for the epidemic.MethodsData on COVID-19 cases were collected from the Shanghai Municipal Health Commission during the period from 20th February to 1st June. The effective reproductive number (Rt) and transmission distance between cases were calculated. An age-structured SEIR model with social contact patterns was developed to reconstruct the transmission dynamics and evaluate age-specific transmission characteristics. Least square method was used to calibrate the model. Basic reproduction number (R0) was estimated with next generation matrix.ResultsR0 of Omicron variant was 7.9 (95% CI: 7.4 to 8.4). With strict interventions, Rt had dropped quickly from 3.6 (95% CI: 2.7 to 4.7) on 4th March to below 1 on 18th April. The mean transmission distance of the Omicron epidemic in Shanghai was 13.4 km (95% CI: 11.1 to 15.8 km), which was threefold longer compared with that of epidemic caused by the wild-type virus in Wuhan, China. The model estimated that there would have been a total 870,845 (95% CI: 815,400 to 926,289) cases for the epidemic from 20th February to 15th June, and 27.7% (95% CI: 24.4% to 30.9%) cases would have been unascertained. People aged 50-59 years had the highest transmission risk 0.216 (95% CI: 0.210 to 0.222), and the highest secondary attack rate (47.62%, 95% CI: 38.71% to 56.53%).ConclusionsThe Omicron variant spread more quickly and widely than other variants and resulted in about one third cases unascertained for the recent outbreak in Shanghai. Prioritizing isolation and screening of people aged 40-59 might suppress the epidemic more effectively. Routine surveillance among people aged 40-59 years could also provide insight into the stage of the epidemic and the timely detection of new variants.Trial registrationWe did not involve clinical trial.

Project description:The Philippines has a high incidence of tuberculosis disease (TB), with an increasing prevalence of multidrug-resistant Mycobacterium tuberculosis (MDR-TB) strains making its control difficult. Although the M. tuberculosis "Manila" ancient lineage 1 strain-type is thought to be prevalent in the country, with evidence of export to others, little is known about the genetic diversity of circulating strains. By whole genome sequencing (WGS) 178 isolates from the Philippines National Drug Resistance Survey, we found the majority (143/178; 80.3%) belonged to the lineage 1 Manila clade, with the minority belonging to lineages 4 (European-American; n = 33) and 2 (East Asian; n = 2). A high proportion were found to be multidrug-resistant (34/178; 19.1%), established through highly concordant laboratory drug susceptibility testing and in silico prediction methods. Some MDR-TB isolates had near identical genomic variation, providing potential evidence of transmission. By placing the Philippine isolates within a phylogeny of global M. tuberculosis (n > 17,000), we established that they are genetically similar to those observed outside the country, including a clade of Manila-like strain-types in Thailand. An analysis of the phylogeny revealed a set of ~200 SNPs that are specific for the Manila strain-type, and a subset can be used within a molecular barcode. Sixty-eight mutations known to be associated with 10 anti-TB drug resistance were identified in the Philippine strains, and all have been observed in other populations. Whilst nine putative streptomycin resistance conferring markers in gid (8) and rrs (1) genes appear to be novel and with functional consequences. Overall, this study provides an important baseline characterisation of M. tuberculosis genetic diversity for the Philippines, and will fill a gap in global datasets and aid the development of a nation-wide database for epidemiological studies and clinical decision making. Further, by establishing a molecular barcode for detecting Manila strains it will assist with the design of diagnostic tools for disease control activities.

Project description:Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance.To investigate the potential utility of these approaches, we analysed the genomes of 144 Mycobacterium tuberculosis clinical isolates from The Special Programme for Research and Training in Tropical Diseases (TDR) collection sourced from 20 countries in four continents. A genome-wide approach was applied to 127 isolates to identify polymorphisms associated with minimum inhibitory concentrations for first-line anti-tuberculosis drugs. In addition, the effect of identified candidate mutations on protein stability and interactions was assessed quantitatively with well-established computational methods.The analysis revealed that mutations in the genes rpoB (rifampicin), katG (isoniazid), inhA-promoter (isoniazid), rpsL (streptomycin) and embB (ethambutol) were responsible for the majority of resistance observed. A subset of the mutations identified in rpoB and katG were predicted to affect protein stability. Further, a strong direct correlation was observed between the minimum inhibitory concentration values and the distance of the mutated residues in the three-dimensional structures of rpoB and katG to their respective drugs binding sites.Using the TDR resource, we demonstrate the usefulness of whole genome association and convergent evolution approaches to detect known and potentially novel mutations associated with drug resistance. Further, protein structural modelling could provide a means of predicting the impact of polymorphisms on drug efficacy in the absence of phenotypic data. These approaches could ultimately lead to novel resistance mutations to improve the design of tuberculosis control measures, such as diagnostics, and inform patient management.

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Strain-specific estimation of epidemic success provides insights into the transmission dynamics of tuberculosis.

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Strain-specific estimation of epidemic success provides insights into the transmission dynamics of tuberculosis.

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