Surveillance of Salmonella enterica serovar Typhi in Colombia, 2012-2015

Abstract

Salmonella Typhi (S. Typhi) is the causative agent of typhoid fever; a systemic disease affecting ~20 million people per year globally. There are little data regarding the contemporary epidemiology of typhoid in Latin America. Consequently, we aimed to describe some recent epidemiological aspects of typhoid in Colombia using cases reported to the National Public Health Surveillance System (Sivigila) between 2012 and 2015. Over the four-year reporting period there were 836 culture confirmed cases of typhoid in Colombia, with the majority (676/836; 80.1%) of reported cases originated from only seven departments. We further characterized 402 S. Typhi isolates with available corresponding data recovered from various departments of Colombia through antimicrobial susceptibility testing and molecular subtyping. The majority (235/402; 58.5%) of these typhoid cases occurred in males and were most commonly reported in those aged between 10 and 29 years (218/402; 54.2%); there were three (0.74%) reported fatalities. The overwhelming preponderance (339/402; 84.3%) of S. Typhi were susceptible to all tested antimicrobials. The most common antimicrobial to which the organisms exhibited non-susceptibility was ampicillin (30/402;7.5%), followed by nalidixic acid (23/402, 5.7%). Molecular subtyping identified substantial genetic diversity, which was well distributed across the country. Despite the diffuse pattern of S. Typhi genotypes, we identified various geographical hotspots of disease associated with local dominant genotypes. Notably, we found limited overlap of Colombian genotypes with organisms reported in other Latin American countries. Our work highlights a substantial burden of typhoid in Colombia, characterized by sustained transmission in some regions and limited epidemics in other departments. The disease is widely distributed across the country and associated with multiple antimicrobial susceptible genotypes that appear to be restricted to Colombia. This study provides a current perspective for typhoid in Latin America and highlights the importance of pathogen-specific surveillance to add insight into the limited epidemiology of typhoid in this region.

Fig 1. The location of 402 cases of typhoid fever in Colombia (2012–2015).

Map of Colombia with a 1:25,000 scale base cartography and a Kernel function bandwidth outputs scale of 480 Km. Colored dots represents the residential location and number of typhoid fever cases throughout the country by PFGE genotype (COINJPPX01-) (see key). The seven departments with the greatest number of cases are labelled and the departments are color coded according to their mean minimum incidence per 100,000 people over the study period (S1 Table, see key). Political division map constructed in ArcGIS 9.3 software (ESRI, Redlands, CA, USA) from polygon shapefile accessed from https://www.diva-gis.org/.

Fig 2. The distribution of major PFGE types Colombia (2012–2015).

A) A PFGE-XbaI dendrogram of S. Typhi isolates in Colombia 2012–1015 indicating clusters I-IV (color coded); key genotypes are indicated (genetic similarity 49.7%) B) The geographical distribution of major S. Typhi PFGE types by Colombian department. Top left (purple); the seven departments in which cluster I (3 PFGE patterns) isolates were identified. Top right (yellow); the six departments in which cluster II (21 PFGE patterns) isolates were identified. Bottom right (green); the fourteen departments in which cluster III (82 PFGE patterns) isolates were identified. Bottom left (orange); the four departments in which cluster IV (6 PFGE patterns) isolates were identified. Political division maps constructed in R studio (VERSION) from polygon shapefiles accessed from DIVA-gis (https://www.diva-gis.org/gdata).

Fig 3. Clustering of typhoid fever in Cucutá city.

15 km Kernel density plot map of Cucutá city in Norte de Santander province bordering Venezuela showing the spatial clustering of typhoid fever cases. The darker blue shows a higher intensity of cases. Red dots highlight the individual typhoid cases and their corresponding PFGE-XbaI digestion patterns. Map manually constructed in ArcGIS 9.3 software (ESRI, Redlands, CA, USA).

Fig 4. The geographic distribution of typhoid fever in specific Colombian departments.

Colored dots represent the residential location and number of typhoid fever cases throughout the country by PFGE genotype (COINJPPX01-) (see key). A) Map of Antioquia department showing the location of typhoid cases by municipality; Apartadó (n = 69) and Turbo (n = 19). B) Map of Huila department showing the location of typhoid cases by municipality; Garzon (n = 15) and Agrado, Gigante, Palermo, and Neiva (all n = 5). C) Map of Meta department showing the location of typhoid cases by municipality; Granada; (n = 19), and Villavicencio, Mesetas, El Castillo, and Fuente de Oro (all n = 6). Political division maps constructed in ArcGIS 9.3 software (ESRI, Redlands, CA, USA) from polygon shapefiles accessed from https://www.diva-gis.org/. Kernel function bandwidth with a scale of outputs of 80Km.

Fig 5. Colombian Salmonella Typhi in a Latin American context.

Dendrogram of PFGE-XbaI S. Typhi digestions in the context of regional PFGE patterns, from the PNLA&C Database. The shared PFGE patterns between Chile ALJPPX01.0050, ALJPPX01.0045, Argentina and Chile ALJPPX01.0048, Venezuela ALJPPX01.0191, ALJPPX01.0076, Peru ALJPPX01.0195, and Argentina ALJPPX01.0089 with those found circulating in Colombia (COINXXJPPX01- and INS-S-596) are highlighted on the right of the diagram.