Phenotypic and genotypic profiling reveals a high prevalence of methicillin-resistant Staphylococcus aureus isolated from hospitals, houseflies and adjacent informal food retailers in Botswana.

The increasing occurrence of methicillin-resistant Staphylococcus aureus (MRSA) in the environment, food and healthcare systems is a global public health concern. MRSA is reported to cause food poisoning, osteomyelitis and pyogenic infections of the skin, and consequently has been categorized as a high-priority pathogen by the World Health Organization. Here, we determined the presence of MRSA in clinical (n=56), food (n=150) and housefly samples (n=970) collected from two hospitals in Botswana. Characterization based on phenotypic (antimicrobial resistance, biofilm production) and genotypic (antimicrobial resistance genes and integrons) profiles were performed on all isolates. Of the total samples tested, 64 were positive for MRSA following conventional culture methods and PCR amplification of the mecA and mecC genes for confirmation of presumptive MRSA isolates. The confirmed isolates included 71 % (95 % CI 83.2-59.6) from clinical, 9 % (95 % CI 14--4.8) from food, and 1 % (95 % CI 1.6-0.4) collected from housefly samples. In total 89 % (n=57) isolates in the current study showed a multidrug resistance phenotype, among these, resistance to ß-lactams and glycoside antibiotic classes were predominant. Genotypic characterization showed the domination of the blatem gene (95 %) followed by fox (63 %) and tetO (19 %) whilst vanA was only reported in 13 % of the isolates. Integrons were detected in 50 % (32/64) of the total MRSA isolates, and we report a high prevalence of etd gene, detected in 67 % (43/64) of the isolates followed by eta 38 % (24/64) whilst tsst-1 (3%) was the least detected genetic determinant. The genes etb and PVL were not detected in a ll the tested MRSA isolates. We provide the first report on the prevalence of MRSA isolated from the clinical-food-vector nexus harbouring biofilm and blatem genes, and antibiotic resistance profiles in Botswana. These results are significant for risk-assessment analysis and the development of improved MRSA infection prevention and control strategies.

Antimicrobial Resistance Profiles of Salmonella spp. from Agricultural Environments in Fruit Production Systems.

Foodborne disease outbreaks involving fresh produce have increased in recent years. The risk of infection from contaminated food is worsened by the increased prevalence of antibiotic-resistant strains. This study evaluated the prevalence of antibiotic resistance in Salmonella isolates (n = 263) from agricultural production systems through to the final packed product. Salmonella isolates were preliminarily identified by matrix-assisted laser desorption ionization-time-of-flight mass spectroscopy (MALDI-TOF MS) and API 20E and identities confirmed by invA gene polymerase chain reaction. Antimicrobial susceptibility was performed with 15 antimicrobial agents using the Kirby-Bauer disk diffusion test. Of the 263 Salmonella isolates assessed, 59.3% were resistant to one or more antimicrobials. The most frequently detected resistance was against chloramphenicol and kanamycin (46.7%), trimethoprim-sulfamethoxazole (28%), and streptomycin (14%), and the less frequently detected resistance was toward ampicillin (1.14%), amikacin (0.76%), and amoxicillin-clavulanic acid (0.38%). Multiple antimicrobial resistance (MAR) (resistance to ≥3 antibiotics) was found in 48.7% (76/156) isolates. The most common MAR phenotype was to chloramphenicol and trimethoprim/sulfamethoxazole-kanamycin (43.6%). Resistance to chloramphenicol, kanamycin, or trimethoprim/sulfamethoxazole was only observed in MAR phenotypes. All isolates were susceptible to ceftiofur, cefoxitin, ceftriaxone, ciprofloxacin, nalidixic acid, gentamicin, and tetracycline. This study confirms the importance of fresh produce production environments as potential reservoirs and fresh produce as carriers of antibiotic-resistant Salmonella spp. with significant clinical importance. Further studies to evaluate the actual level of health risk from these pathogens should include characterization of the antibiotic resistance determinant genes among the isolates.

Potential Exposure to Respiratory and Enteric Bacterial Pathogens among Wastewater Treatment Plant Workers, South Africa.

Wastewater handling has been associated with an increased risk of developing adverse health effects, including respiratory and gastrointestinal illnesses. However, there is a paucity of information in the literature, and occupational health risks are not well quantified. Grab influent samples were analysed using Illumina Miseq 16S amplicon sequencing to assess potential worker exposure to bacterial pathogens occurring in five municipal wastewater treatment plants (WWTPs). The most predominant phyla were Bacteroidota, Campilobacterota, Proteobacteria, Firmicutes, and Desulfobacterota, accounting for 85.4% of the total bacterial community. Taxonomic analysis showed a relatively low diversity of bacterial composition of the predominant genera across all WWTPs, indicating a high degree of bacterial community stability in the influent source. Pathogenic bacterial genera of human health concern included Mycobacterium, Coxiella, Escherichia/Shigella, Arcobacter, Acinetobacter, Streptococcus, Treponema, and Aeromonas. Furthermore, WHO-listed inherently resistant opportunistic bacterial genera were identified. These results suggest that WWTP workers may be occupationally exposed to several bacterial genera classified as hazardous biological agents for humans. Therefore, there is a need for comprehensive risk assessments to ascertain the actual risks and health outcomes among WWTP workers and inform effective intervention strategies to reduce worker exposure.

The role of wastewater-based epidemiology for SARS-CoV-2 in developing countries: Cumulative evidence from South Africa supports sentinel site surveillance to guide public health decision-making.

The uptake of wastewater-based epidemiology (WBE) for SARS-CoV-2 as a complementary tool for monitoring population-level epidemiological features of the COVID-19 pandemic in low-and-middle-income countries (LMICs) is low. We report on the findings from the South African SARS-CoV-2 WBE surveillance network and make recommendations regarding the implementation of WBE in LMICs. Eight laboratories quantified influent wastewater collected from 87 wastewater treatment plants in all nine South African provinces from 01 June 2021 to 31 May 2022 inclusive, during the 3rd and 4th waves of COVID-19. Correlation and regression analyses between wastewater levels of SARS-CoV-2 and district laboratory-confirmed caseloads were conducted. The sensitivity and specificity of novel 'rules' based on WBE data to predict an epidemic wave were determined. Amongst 2158 wastewater samples, 543/648 (85 %) samples taken during a wave tested positive for SARS-CoV-2 compared with 842 positive tests from 1512 (55 %) samples taken during the interwave period. Overall, the regression-co-efficient was 0,66 (95 % confidence interval = 0,6-0,72, R2 = 0.59), ranging from 0.14 to 0.87 by testing laboratory. Early warning of the 4th wave of SARS-CoV-2 in Gauteng Province in November-December 2021 was demonstrated. A 50 % increase in log copies of SARS-CoV-2 compared with a rolling mean over the previous five weeks was the most sensitive predictive rule (58 %) to predict a new wave. Our findings support investment in WBE for SARS-CoV-2 surveillance in LMICs as an early warning tool. Standardising test methodology is necessary due to varying correlation strengths across laboratories and redundancy across testing plants. A sentinel site model can be used for surveillance networks without affecting WBE finding for decision-making. Further research is needed to identify optimal test frequency and the need for normalisation to population size to identify predictive and interpretive rules to support early warning and public health action.