Prevalence, Serotype Distribution and Antimicrobial Resistance of Non-Typhoidal Salmonella in Hospitalized Patients in Conghua District of Guangzhou, China

Salmonella infection is a major public health concern worldwide, has contributed to an increased economic burden on the health systems. Non-typhoidal Salmonella (NTS) is a common cause of bacterial enteritis in humans, causing 93.8 million cases of gastroenteritis globally each year, with 155,000 deaths. Guangzhou city is situated in the south of China and has a sub-tropical climate, the heat and heavy rainfall helps the spread of NTS. However, no information of NTS infection is available in humans in Conghua District, the largest administrative district of Guangzhou. To understand the prevalence, serotype distribution, risk factors and drug resistance of NTS infection in humans in the survey area, an epidemiological investigation was conducted in hospitalized patients in Conghua District in Guangzhou, China. A total of 255 fecal specimens were collected from hospitalized patients (one each), with a questionnaire for each participant, and NTS infection was identified by culture, as well as serotypes confirmed by slide agglutination tests. An average prevalence of 20.39% (52/255) was observed and three serogroups were identified-serogroup B (n = 46), serogroup C1 (n = 4) and serogroup D1 (n = 2). Among them, Salmonella Typhimurium (n = 39) was the most common serotype. Children aged <3 years were observed to have a statistically higher prevalence of NTS infection than adults (25.15% versus 4.65%, P = 0.006); children with artificial feeding had a statistically higher prevalence than those with breastfeeding (30.77% versus 8.33%, P = 0.044). Antimicrobial resistance testing revealed that the majority of strains were resistant to ampicillin (92.16%), as well as 47.06% of all strains were multi-drug resistant. Therefore, it is necessary to continuous monitoring and rational use of antibiotics, which will be helpful to reduce the prevalence of resistant strains. These data will aid in making efficient control strategies to intervene with and prevent occurrence of salmonellosis.