Assessing the global risk of typhoid outbreaks caused by extensively drug resistant Salmonella Typhi

Recent approaches in computational modelling for controlling pathogen threats

In this review, we assess the status of computational modelling of pathogens. We focus on three disparate but interlinked research areas that produce models with very different spatial and temporal scope. First, we examine antimicrobial resistance (AMR). Many mechanisms of AMR are not well understood. As a result, it is hard to measure the current incidence of AMR, predict the future incidence, and design strategies to preserve existing antibiotic effectiveness. Next, we look at how to choose the finite number of bacterial strains that can be included in a vaccine. To do this, we need to understand what happens to vaccine and non-vaccine strains after vaccination programmes. Finally, we look at within-host modelling of antibody dynamics. The SARS-CoV-2 pandemic produced huge amounts of antibody data, prompting improvements in this area of modelling. We finish by discussing the challenges that persist in understanding these complex biological systems.

The origins of haplotype 58 (H58) Salmonella enterica serovar Typhi

Antimicrobial resistance (AMR) poses a serious threat to the clinical management of typhoid fever. AMR in Salmonella Typhi (S. Typhi) is commonly associated with the H58 lineage, a lineage that arose comparatively recently before becoming globally disseminated. To better understand when and how H58 emerged and became dominant, we performed detailed phylogenetic analyses on contemporary genome sequences from S. Typhi isolated in the period spanning the emergence. Our dataset, which contains the earliest described H58 S. Typhi organism, indicates that ancestral H58 organisms were already multi-drug resistant (MDR). These organisms emerged spontaneously in India in 1987 and became radially distributed throughout South Asia and then globally in the ensuing years. These early organisms were associated with a single long branch, possessing mutations associated with increased bile tolerance, suggesting that the first H58 organism was generated during chronic carriage. The subsequent use of fluoroquinolones led to several independent mutations in gyrA. The ability of H58 to acquire and maintain AMR genes continues to pose a threat, as extensively drug-resistant (XDR; MDR plus resistance to ciprofloxacin and third generation cephalosporins) variants, have emerged recently in this lineage. Understanding where and how H58 S. Typhi originated and became successful is key to understand how AMR drives successful lineages of bacterial pathogens. Additionally, these data can inform optimal targeting of typhoid conjugate vaccines (TCVs) for reducing the potential for emergence and the impact of new drug-resistant variants. Emphasis should also be placed upon the prospective identification and treatment of chronic carriers to prevent the emergence of new drug resistant variants with the ability to spread efficiently.

Characterising global antimicrobial resistance research explains why One Health solutions are slow in development: An application of AI-based gap analysis

The global health crisis posed by increasing antimicrobial resistance (AMR) implicitly requires solutions based a One Health approach, yet multisectoral, multidisciplinary research on AMR is rare and huge knowledge gaps exist to guide integrated action. This is partly because a comprehensive survey of past research activity has never performed due to the massive scale and diversity of published information. Here we compiled 254,738 articles on AMR using Artificial Intelligence (AI; i.e., Natural Language Processing, NLP) methods to create a database and information retrieval system for knowledge extraction on research perfomed over the last 20 years. Global maps were created that describe regional, methodological, and sectoral AMR research activities that confirm limited intersectoral research has been performed, which is key to guiding science-informed policy solutions to AMR, especially in low-income countries (LICs). Further, we show greater harmonisation in research methods across sectors and regions is urgently needed. For example, differences in analytical methods used among sectors in AMR research, such as employing culture-based versus genomic methods, results in poor communication between sectors and partially explains why One Health-based solutions are not ensuing. Therefore, our analysis suggest that performing culture-based and genomic AMR analysis in tandem in all sectors is crucial for data integration and holistic One Health solutions. Finally, increased investment in capacity development in LICs should be prioritised as they are places where the AMR burden is often greatest. Our open-access database and AI methodology can be used to further develop, disseminate, and create new tools and practices for AMR knowledge and information sharing.

Typhoid Fever and Non-typhoidal Salmonella Outbreaks: A Portrait of Regional Socioeconomic Inequalities in Brazil

Typhoid fever occurs in an endemic form in Brazil and is a serious public health problem in some regions. In this scenario, further research is urgently needed to identify the associations between socioeconomic factors and typhoid fever, contributing to guiding policy decisions in the country. We aimed to investigate the influence of socioeconomic disparities on the prevalence of typhoid fever and non-typhoidal Salmonella (NTS) in Brazil. A search for data from 2010 to 2019 was carried out with the national health and human development agencies. As milk and derivatives are the fourth food incriminated in food outbreaks in Brazil, analyses for detecting Salmonella spp. in commercial dairy products allowed us to assess whether the outbreaks associated with these foods are due to inadequacies in sanitary control in dairy establishments or whether they are mainly home-based outbreaks. Predictive models validated by the bootstrapping method demonstrate an association of NTS prevalence reduction with improvements in the Sanitation Service Index (Rv ≥  -8 0.686; p ≤ 0.01) and Municipal Human Development Index - MHDI - (Rv =  -0.789; p ≤ 0.02). In the North, typhoid fever prevalence had seasonal variability with the rainfall, while sanitation services (Rv ≥-0.684; p ≤ 0.04) and MHDI (Rv ≥-0.949; p ≤ 0.003) directly influenced Northeast and South Brazil. Thus, the unequal distribution of investments in the sanitation sector contributed to disparities in typhoid fever prevalence among Brazilian regions. The absence of Salmonella spp. in commercial samples ratified the collected data that the outbreaks of Salmonella spp. in the Brazilian population occur mainly at residences. These findings show that implementing public health education and increasing investments in sanitation in regions with poor service can control outbreaks of Salmonella spp. in Brazilian endemic areas.