The emergence of Acquired Immunodeficiency Syndrome has highlighted the increased incidence and importance of the disease caused by Non-tuberculous Mycobacteria (NTM). While disease due to M. avium-intracellulare complex is apparently common throughout the world, other Non-tuberculous mycobacterial species have been isolated from both immunocompromised and immunocompetent individuals. The increasing number of infections caused by these organisms has made it clinically important to quickly identify mycobacterial species. The diagnosis of a pathogenic versus a non-pathogenic species not only has epidemiological implications but is also relevant to the demands of patient management. Since antibiotic treatment varies according to the species encountered, species identification would reduce the burden of some of these emerging opportunistic pathogens especially in immunocompromised patients and improve their quality of life. A total of 91 NTM suspected isolates from four regions of Zambia were included in the study. These isolates were identified using the sequence analysis of the 16S-23S rRNA intergenic transcribed spacer (ITS) region of Mycobacteria. Fifty-four of the 91 (59%) isolates were identified as NTM and these included M. intracellulare (27.8%), M. lentiflavum (16.7%), M. avium (14.8%), M. fortuitum (7.4%), M. gordonae (7.4%), M. kumamotonense (3.7%), M. indicus pranii (3.7%), M. peregrinum (3.7%), M. elephantis (1.85%), M. flavescens (1.85%), M. asiaticum (1.85%), M. bouchedurhonense (1.85%), M. chimaera (1.85%), M. europaeum (1.85%), M. neourum (1.85%), M. nonchromogenicum (1.5%). The study has shown that DNA sequencing of the ITS region may be useful in the preliminary identification of NTM species. All species identified in this study were potentially pathogenic.

Morbidity and mortality from respiratory infections are higher in resource-limited countries than developed countries, but limited studies have been conducted in resource-limited settings to examine pathogens from patients with acute respiratory infections. Influenza surveillance has been conducted in Zambia since 2008; however, only 4.3% of patients enrolled in 2011–2012 were positive for influenza. Therefore, we examined non-influenza respiratory pathogens in children with severe acute respiratory illness (SARI) in Zambia, to estimate the scope of disease burden and determine commonly-identified respiratory pathogens. Two reverse transcriptase polymerase chain reaction (rRT-PCR) methods (single and multiplex) were used to analyze nasopharyngeal and throat swabs collected from SARI cases under five years of age from January 2011 through December 2012. All specimens were negative for influenza by rRT-PCR. The panel of singleplex reactions targeted seven viruses, while the multiplex assay targeted thirty-three bacteria, fungi, and viruses. A set of 297 specimens were tested by singleplex rRT-PCR, and a different set of 199 were tested by multiplex rRT-PCR. Using the singleplex assay, 184/297 (61.9%) specimens were positive for one or more viruses. The most prevalent viruses were human rhinovirus (57/297; 19.2%), human adenovirus (50/297; 16.8%), and respiratory syncytial virus (RSV) (45/297; 15.2%). Using multiplex PCR, at least one virus was detected from 167/199 (83.9%) specimens, and at least one bacteria was detected from 197/199 (99.0%) specimens. Cytomegalovirus (415/199; 208.5%) and RSV (67/199; 33.7%) were the most commonly detected viruses, while Streptococcus pneumonie (109/199; 54.8%) and Moraxella catarrhalis (92/199; 46.2%) were the most commonly detected bacteria. Single infections and co-infections of many viruses and bacteria were identified in children with SARI. These results provide an estimate of the prevalence of infection and show which respiratory pathogens are commonly identified in patients. Further studies should investigate causal associations between individual pathogens and SARI.

Objective: To assess the performance of the SD Bioline Cholera Ag O1/O139 rapid diagnostic test (RDT) compared to a reference standard combining culture and PCR for the diagnosis of cholera cases during an outbreak.Methods: RDT and bacterial culture were performed on site using fresh stools collected from cholera suspected cases, and from stools enriched in alkaline peptone water. Dried stool samples on filter paper were tested for V. cholerae by PCR in Lusaka (as part of a laboratory technology transfer project) and at a reference laboratory in Paris, France. A sample was considered positive for cholera by the reference standard if any of the culture or PCR tests was positive for V. cholerae O1 or O139.Results: Among the 170 samples tested with SD Bioline and compared to the reference standard, the RDT showed a sensitivity of 90.9% (95% CI: 81.3–96.6) and specificity of 95.2% (95% CI: 89.1–98.4). After enrichment, the sensitivity was 95.5% (95% CI: 87.3–99.1) and specificity 100% (95% CI: 96.5–100).Conclusion: The observed sensitivity and specificity were within recommendations set by the Global Task Force for Cholera Control on the use of cholera RDT (sensitivity = 90%; specificity = 85%). Although the sample size was small, our findings suggest that the SD Bioline RDT could be used in the field to rapidly alert public health officials to the likely presence of cholera cases when an outbreak is suspected.

Antimicrobial resistance (AMR) is a public health problem threatening human, animal, and environmental safety. This study assessed the AMR profiles and risk factors associated with Escherichia coli in hospital and environmental settings in Lusaka, Zambia. This cross-sectional study was conducted from April 2022 to August 2022 using 980 samples collected from clinical and environmental settings. Antimicrobial susceptibility testing was conducted using BD Phoenix^TM 100. The data were analysed using SPSS version 26.0. Of the 980 samples, 51% were from environmental sources. Overall, 64.5% of the samples tested positive for E. coli, of which 52.5% were from clinical sources. Additionally, 31.8% were ESBL, of which 70.1% were clinical isolates. Of the 632 isolates, 48.3% were MDR. Most clinical isolates were resistant to ampicillin (83.4%), sulfamethoxazole/trimethoprim (73.8%), and ciprofloxacin (65.7%) while all environmental isolates were resistant to sulfamethoxazole/trimethoprim (100%) and some were resistant to levofloxacin (30.6%). The drivers of MDR in the tested isolates included pus (AOR = 4.6, CI: 1.9–11.3), male sex (AOR = 2.1, CI: 1.2–3.9), and water (AOR = 2.6, CI: 1.2–5.8). This study found that E. coli isolates were resistant to common antibiotics used in humans. The presence of MDR isolates is a public health concern and calls for vigorous infection prevention measures and surveillance to reduce AMR and its burdens.

Objective: Salmonella species and Escherichia coli are major bacterial enteropathogens of worldwide public health importance that cause devastating foodborne diseases, thereby contributing to increased human morbidity and mortality. Both pathogens have also been found to contribute towards the spread of antimicrobial resistance through the food chain, especially in poultry. This study aimed to determine the occurrence of antibiotic-resistant Salmonella spp. and E. coli in broiler chickens at farm level, abattoirs, and open markets in selected districts of Zambia.Methods: A cross-sectional study was undertaken in seven districts of Zambia to determine the resistance profiles of Salmonella spp. and E. coli obtained from broiler chickens at farms, abattoirs, and open markets. A total of 470 samples were collected which include; litter, cloacal swabs, and carcass swabs. Samples were inoculated into buffered peptone water and incubated for 24 hours then sub-cultured onto MacConkey and Xylose Lysine Deoxycholate agar plates. Identification of Salmonella spp. and E. coli was done using the API-20E kit and confirmation by 16S rDNA sequencing. Confirmed isolates were tested against a panel of 09 antibiotics using the Kirby-Bauer disc diffusion method and interpreted according to the Clinical Laboratory Standards Institute guidelines. Data analysis of the antibiotic sensitivity test results was done using WHONET 2018 software.Results: Overall, 4 Salmonella spp. and 280 E. coli were isolated. One of the Salmonella spp. was resistant to ampicillin (25%), amoxicillin/clavulanic acid (25%), and cefotaxime (25%). E. coli antibiotic resistance was highest to tetracycline (81.4%) and 100% susceptibility to imipenem. The antibiotic susceptibility profile revealed 75.7% (237/280) multidrug-resistant (MDR). The highest MDR profile was observed in 8.2% (23/280) isolates in which 6 out of the 9 classes of antibiotics tested were resistant. Out of the 280 isolates, 11.4% (32/280) exhibited Extensive Drug resistance (XDR).Conclusion: The study found antimicrobial resistance to E. coli and Salmonella spp. in market-ready broiler chickens which were resistant to important antibiotics and is of public health concern.

The circulation of both West Nile Virus (WNV) and Chikungunya Virus (CHIKV) in humans and animals, coupled with a favorable tropical climate for mosquito proliferation in Zambia, call for the need for a better understanding of the ecological and epidemiological factors that govern their transmission dynamics in this region. This study aimed to examine the contribution of climatic variables to the distribution of Culex and Aedes mosquito species, which are potential vectors of CHIKV, WNV, and other arboviruses of public-health concern. Mosquitoes collected from Lusaka as well as from the Central and Southern provinces of Zambia were sorted by species within the Culex and Aedes genera, both of which have the potential to transmit viruses. The MaxEnt software was utilized to predict areas at risk of WNV and CHIKV based on the occurrence data on mosquitoes and environmental covariates. The model predictions show three distinct spatial hotspots, ranging from the high-probability regions to the medium- and low-probability regions. Regions along Lake Kariba, the Kafue River, and the Luangwa Rivers, as well as along the Mumbwa, Chibombo, Kapiri Mposhi, and Mpika districts were predicted to be suitable habitats for both species. The rainfall and temperature extremes were the most contributing variables in the predictive models.