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Background Diverse environmental exposures and risk factors have been implicated in the transmission of Salmonella Typhi, but the dominant transmission pathways through the environment to susceptible humans remain unknown. Here, we use spatial, bacterial genomic, and hydrological data to refine our view of typhoid transmission in an endemic setting. Methods A total of 546 patients presenting to Queen Elizabeth Central Hospital in Blantyre, Malawi, with blood culture–confirmed typhoid fever between April 2015 and January 2017 were recruited to a cohort study. The households of a subset of these patients were geolocated, and 256 S. Typhi isolates were whole-genome sequenced. Pairwise single-nucleotide variant distances were incorporated into a geostatistical modeling framework using multidimensional scaling. Results Typhoid fever was not evenly distributed across Blantyre, with estimated minimum incidence ranging across the city from 100 cases per 100 000 population per year. Pairwise single-nucleotide variant distance and physical household distances were significantly correlated (P = .001). We evaluated the ability of river catchment to explain the spatial patterns of genomics observed, finding that it significantly improved the fit of the model (P = .003). We also found spatial correlation at a smaller spatial scale, of households living Conclusions These findings reinforce the emerging view that hydrological systems play a key role in the transmission of typhoid fever. By combining genomic and spatial data, we show how multifaceted data can be used to identify high incidence areas, explain the connections between them, and inform targeted environmental surveillance, all of which will be critical to shape local and regional typhoid control strategies.

Background Typhoid fever remains a major source of morbidity and mortality in low-income settings. Its most feared complication is intestinal perforation. However, due to the paucity of diagnostic facilities in typhoid-endemic settings, including microbiology, histopathology, and radiology, the etiology of intestinal perforation is frequently assumed but rarely confirmed. This poses a challenge for accurately estimating burden of disease. Methods We recruited a prospective cohort of patients with confirmed intestinal perforation in 2016 and performed enhanced microbiological investigations (blood and tissue culture, plus tissue polymerase chain reaction [PCR] for Salmonella Typhi). In addition, we used a Poisson generalized linear model to estimate excess perforations attributed to the typhoid epidemic, using temporal trends in S. Typhi bloodstream infection and perforated abdominal viscus at Queen Elizabeth Central Hospital from 2008–2017. Results We recruited 23 patients with intraoperative findings consistent with intestinal perforation. 50% (11/22) of patients recruited were culture or PCR positive for S. Typhi. Case fatality rate from typhoid-associated intestinal perforation was substantial at 18% (2/11). Our statistical model estimates that culture-confirmed cases of typhoid fever lead to an excess of 0.046 perforations per clinical typhoid fever case (95% CI, .03–.06). We therefore estimate that typhoid fever accounts for 43% of all bowel perforation during the period of enhanced surveillance. Conclusions The morbidity and mortality associated with typhoid abdominal perforations are high. By placing clinical outcome data from a cohort in the context of longitudinal surgical registers and bacteremia data, we describe a valuable approach to adjusting estimates of the burden of typhoid fever.

Background Typhoid fever has been endemic on the island nation of Samoa (2016 population, 195 979) since the 1960s and has persisted through 2019, despite economic development and improvements in water supply and sanitation. Methods Salmonella enterica serovar Typhi isolates from the 2 hospitals with blood culture capability and matched patient demographic and clinical data from January 2008 through December 2019 were analyzed. Denominators to calculate incidence by island, region, and district came from 2011 and 2016 censuses and from 2017–2019 projections from Samoa’s Bureau of Statistics. Data were analyzed to describe typhoid case burden and incidence from 2008 to 2019 by time, place, and person. Results In sum, 53–193 blood culture-confirmed typhoid cases occurred annually from 2008 to 2019, without apparent seasonality. Typhoid incidence was low among children age Conclusions Typhoid has been endemic in Samoa in the period 2008–2019. Interventions, including mass vaccination with a Vi-conjugate vaccine coadministered with measles vaccine are planned.

Typhoid conjugate vaccine (TCV) has been shown to be costeffective in some settings, but to make the most of limited healthcare funds, the WHO recommends that decisions about when and where to introduce TCV should be based on local evidence of transmission. Further, Gavi, The Vaccine Alliance, recommends that countries request TCV funding based on epidemiological data from within-country. Since few countries have reliable case reporting, we considered environmental surveillance as a decision-support tool for vaccine introduction choices. Environmental surveillance methods are still in development and this analysis assesses its potential as a decision support tool. We combined a disease transmission simulation model with an economic model, to quantify the value of surveillance. The disease transmission model is fit to historical case reporting from Blantyre, Malawi. The economic model takes a social perspective and incorporates the cost of environmental surveillance, vaccination, and both direct and indirect cost of care for acute typhoid cases. We find that the use of time-limited environmental surveillance to differentiate low- from high-endemicity areas is low cost relative to potential savings, especially if it is paired with a locally targeted vaccination campaign. These findings are robust to the uncertainty of cost model parameters and underlying endemicity.

Background Typhoid fever remains a major cause of morbidity and mortality in low- and middle-income settings. In the last 10 years, several reports have described the reemergence of typhoid fever in southern and eastern Africa, associated with multidrug-resistant H58 Salmonella Typhi. Here, we identify risk factors for pediatric typhoid fever in a large epidemic in Blantyre, Malawi. Methods A case-control study was conducted between April 2015 and November 2016. Cases were recruited at a large teaching hospital, and controls were recruited from the community, matched by residential ward. Stepwise variable selection and likelihood ratio testing were used to select candidate risk factors for a final logistic regression model. Results Use of river water for cooking and cleaning was highly associated with risk of typhoid fever (odds ratio [OR], 4.6 [95% confidence interval {CI}, 1.7–12.5]). Additional risk factors included protective effects of soap in the household (OR, 0.6 [95% CI, .4–.98]) and >1 water source used in the previous 3 weeks (OR, 3.2 [95% CI, 1.6–6.2]). Attendance at school or other daycare was also identified as a risk factor (OR, 2.7 [95% CI, 1.4–5.3]) and was associated with the highest attributable risk (51.3%). Conclusions These results highlight diverse risk factors for typhoid fever in Malawi, with implications for control in addition to the provision of safe drinking water. There is an urgent need to improve our understanding of transmission pathways of typhoid fever, both to develop tools for detecting S. Typhi in the environment and to inform water, sanitation, and hygiene interventions.

Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach developed with formal software support. The epidemiological modeling software, EMOD, has undergone a decade of software development. It is structured so that a majority of code is shared across disease modeling including malaria, HIV, tuberculosis, dengue, polio and typhoid. In additional to implementation efficiency, the sharing increases code usage and testing. The freely available codebase also includes hundreds of regression tests, scientific feature tests and component tests to help verify functionality and avoid inadvertent changes to functionality during future development. Here we describe the levels of detail, flexible configurability and modularity enabled by EMOD and the role of software development principles and processes in its development., To address multi-scale questions in infectious disease transmission, a multi-disease modeling platform EMOD has been developed with modularity, code sharing across diseases, and formal software development and testing processes.