Predicting Salmonella Typhi incidence using prevalence metrics from sentinel studies of community-onset bloodstream infections: a secondary analysis of observational data
Year: 2026
Type: article
Abstract: BACKGROUND: Typhoid fever incidence estimates are central to policy decisions on vaccine introduction and investments in non-vaccine prevention and control but are often unavailable. We explored whether prevalence metrics from sentinel studies of community-onset bloodstream infections could accurately predict local Salmonella enterica serovar Typhi (Salmonella Typhi) incidence. METHODS: Using a previous systematic review (January 2018-December 2024), we identified studies reporting both typhoid incidence and prevalence of community-onset bloodstream infections from sentinel sites. From authors, we requested data on blood culture isolates and analysed four metrics: (i) Salmonella Typhi prevalence among probable pathogens, (ii) Salmonella Typhi rank order, (iii) Salmonella Typhi to Escherichia coli ratio, and (iv) Salmonella Typhi to 'stably endemic' organisms ratio. Typhoid incidence was categorized as low (<10), medium (10-100) or high (>100) per 100,000 person-years. We used univariate ordinal regression to assess the association between each metric and typhoid incidence level. The model performance was evaluated by the c-statistic, sensitivity, and specificity. RESULTS: Analysis of 29 study sites (20 Africa, 9 Asia) yielded 4625 probable pathogens. The median (IQR) typhoid incidence was 140 (28-319) per 100,000 person-years. All metrics were associated with increased typhoid incidence level: for each 1% increase in Salmonella Typhi prevalence OR 1.07 (95%CI 1.02-1.15); for each unit increase in rank order OR 0.25 (95%CI 0.06-0.64); for each unit increase in the log Salmonella Typhi to E. coli ratio OR 2.88 (95%CI 1.48-7.39) for each unit increase in the log Salmonella Typhi to 'stably endemic' organisms ratio OR 3.74 (95%CI 1.80-10.7). A parsimonious model using Salmonella Typhi prevalence alone achieved c-statistics of 0.87 (0.58-0.97), 0.76 (0.51-0.91), and 0.88 (0.69-0.96) for low, medium, and high incidence, respectively. CONCLUSION: Sentinel prevalence metrics from bloodstream infections, particularly Salmonella Typhi prevalence among probable pathogens, could be useful for inferring local typhoid fever incidence where direct data are unavailable.
Source: Vaccine
Authors: Nienke N. Hagedoorn, Shruti Murthy, Christian S. Marchello, Jonathan Williman, Faisal Ahmmed, Jason R. Andrews, Buddha Basnyat, Alice S. Carter, Shrimati Datta, Irum Fatima Dehraj, Kate Doyle, Denise O. Garrett, Jobin Jacob, Hyonjin Jeon, Jacob John, Farhana Khanam, Jooah Lee, Xinxue Liu, Florian Marks, Shiva R. Naga, Kathleen M. Neuzil, Paul N. Newton, Priyanka D. Patel, Andrew J. Pollard, Firdausi Qadri, Farah Naz Qamar, Tamalee Roberts, Jessica C. Seidman, Mila Shakya, Suchita Shrestha, Birkneh T. Tadesse, Dipesh Tamrakar, Manivanh Vongsouvath, Merryn Voysey, Mohammad Tahir Yousafzai, John A. Crump
Institutions: University of Otago, International Centre for Diarrhoeal Disease Research, Stanford Medicine, Stanford University, Patan Academy of Health Sciences, Oxford University Clinical Research Unit Nepal, Sabin Vaccine Institute, University of Maryland, Baltimore, Aga Khan University, Christian Medical College, Vellore, International Vaccine Institute, University of Antananarivo, University of Cambridge, The University of Queensland, University of Oxford, Heidelberg University, Heidelberg Institute of Global Health, Dhulikhel Hospital, Kathmandu University, Mahosot Hospital, Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, University of Liverpool, NIHR Oxford Biomedical Research Centre, Karolinska Institutet, Addis Ababa University
Language: English
Subfield: Food Science
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $3,620
OpenAlex ID: W7161502694