Existing cost-effectiveness analyses for diseases caused by Group A Streptococcus: A systematic review to guide future research

Lee, Jung-Seok; Kim, Sol; Excler, Jean Louis; Kim, Jerome; Mogasale, Vittal

doi:10.12688/wellcomeopenres.17116.1

Cited by 4 publications

(2 citation statements)

References 49 publications

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“…Bacterial infections have emerged as a significant global healthcare concern, imposing a substantial economic burden [37]. The annual treatment cost for several bacterial infections reached $4.6 billion in the United States [38].…”

Section: Discussionmentioning

confidence: 99%

Advancing virulence factor prediction using protein language models

Liu,

Cao,

et al. 2024

Preprint

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Background Bacterial infections have emerged as the second leading cause of death globally, with their virulence factors (VFs) playing a critical role. Accurate prediction of VFs serves not only to elucidate the mechanisms of bacterial pathogenicity, but also offers new avenues for treating bacterial diseases. Machine learning (ML) stands out as a powerful tool for swiftly and precisely identifying VFs. However, a persistent challenge with existing ML methods is the use of outdated embedding techniques and a lack of differentiation between VFs of Gram-positive and Gram-negative bacteria. Results In this study, we introduced pLM4VF, a predictive framework that utilized ESM protein language models to extract VF characteristics of G+ and G- bacteriaseparately, and further integrated the models using the stacking strategy. The top-performing ensemble models, constructed using ESM pLMs, for both types of bacteria collectively constituted pLM4VF. Extensive benchmarking experiments on the independent test demonstrated that pLM4VF outperformed state-of-the-art methods. Biological validations through cytotoxicity and acute toxicity assays further corroborated the reliability of pLM4VF. An online tool (http://139.9.105.117:8081/) has been developed that enables inexperienced researchers on ML to obtain VFs of various bacteria at the whole-genome scale. Conclusion We believe that pLM4VF will offer substantial support in uncovering pathogenic mechanisms, developing novel antibacterial treatments and vaccines, thereby aiding in the prevention and management of bacterial diseases.

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Section: Discussionmentioning

confidence: 99%

Advancing virulence factor prediction using protein language models

Liu,

Cao,

et al. 2024

Preprint

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“…In addition, premature mortality from Strep A diseases removes individuals from participation in the labor force. Estimated average productivity loss due to premature mortality per episode of RHD ranges from $9637 in low-income countries to $72,097 in high-income countries 32 .…”

Section: Introductionmentioning

confidence: 99%

The full health, economic, and social benefits of prospective Strep A vaccination

Cadarette,

Ferranna,

Cannon

et al. 2023

npj Vaccines

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Recent research has documented a wide range of health, economic, and social benefits conferred by vaccination, beyond the direct reductions in morbidity, mortality, and future healthcare costs traditionally captured in economic evaluations. In this paper, we describe the societal benefits that would likely stem from widespread administration of safe and effective vaccines against Streptococcus pyogenes (Strep A), which was estimated to be the fifth-leading cause of infectious disease deaths globally prior to the COVID-19 pandemic. We then estimate the global societal gains from prospective Strep A vaccination through a value-per-statistical-life approach. Estimated aggregate lifetime benefits for 30 global birth cohorts range from $1.7 to $5.1 trillion, depending on the age at which vaccination is administered and other factors. These results suggest that the benefits of Strep A vaccination would be large and justify substantial investment in the vaccines’ development, manufacture, and delivery.

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Global economic burden per episode for multiple diseases caused by group A Streptococcus

et al. 2023

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Considering the lack of existing evidence on economic burden for diseases caused by group A Streptococcus, we estimated the economic burden per episode for selected diseases. Each cost component of direct medical costs (DMCs), direct non-medical costs (DNMCs), and indirect costs (ICs) was separately extrapolated and aggregated to estimate the economic burden per episode by income group as classified by the World Bank. Adjustment factors for DMC and DNMC were generated to overcome related data insufficiencies. To address uncertainty surrounding input parameters, a probabilistic multivariate sensitivity was carried out. The average economic burden per episode ranged from $22 to $392 for pharyngitis, $25 to $2,903 for impetigo, $47 to $2,725 for cellulitis, $662 to $34,330 for invasive and toxin-mediated infections, $231 to $6,332 for acute rheumatic fever (ARF), $449 to $11,717 for rheumatic heart disease (RHD), and $949 to $39,560 for severe RHD across income groups. The economic burden for multiple Group A Streptococcus diseases underscores an urgent need to develop effective prevention strategies including vaccines.

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Existing cost-effectiveness analyses for diseases caused by Group A Streptococcus: A systematic review to guide future research

Cited by 4 publications

References 49 publications

Advancing virulence factor prediction using protein language models

Advancing virulence factor prediction using protein language models

The full health, economic, and social benefits of prospective Strep A vaccination

Global economic burden per episode for multiple diseases caused by group A Streptococcus

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