Background. The balance between the choices of UTI diagnostic tools in most primary care settings has been settled for by the more rapid, less labour-intensive dipstick. This study aimed to evaluate the effectiveness of dipstick for diagnosing UTI. Method. A total of 429 urine samples were collected from patients suspected of UTI; cultured on cysteine-lactose-electrolyte-deficient (CLED) agar, blood agar, and MacConkey agar; and incubated at 37°C overnight. Urine cultures with bacteria count ≥10⁵ cfu/ml were classified as “positive” for UTI. A dipstick was used to screen for the production of nitrite (NIT) and leucocyte esterase (LE), following the manufacturer’s instructions. Biochemical reactions of nitrite and leucocyte esterase > “trace” were classified as “positive.” A quantitative urine culture was used as the gold standard. Results. The highest sensitivity value and negative predictive value were recorded for the combined “NIT+ or LE+” dipstick results. The highest specificity value, positive predictive value, positive likelihood ratio, and negative likelihood ratio were recorded for “nitrite-positive and leucocyte esterase-positive” results. Combined “nitrite-positive or leucocyte-positive” result was relatively the best indicator for accurate dipstick diagnosis, with AUC = 0.7242. Cohen’s kappa values between dipstick diagnosis and quantitative culture were <0.6. Conclusion. Combined performance of nitrite and leucocyte esterase results appeared better than the solo performance of nitrite and leucocyte esterase. However, little confidence should be placed on dipstick diagnosis; hence, request for quantity culture should be encouraged in the primary healthcare settings.

Background. Despite the recent advancement in diagnostic methods, the smear microscopy remains the gold standard for the diagnosis of pulmonary tuberculosis in high burden countries like Ghana. Notwithstanding, fluorescence staining technique provides a more efficient option for the detection of Mycobacterium tuberculosis positive smears. This study therefore aimed at assessing the diagnostic performance of fluorescence microscopy (FM) and Ziehl-Neelsen (ZN) staining techniques in the diagnosis of pulmonary tuberculosis. Methods. A comparative study was carried out on 100 patients who reported at the Out Patients Department (OPD) or the Directly Observed Therapy (DOT) center of the Kade Government Hospital and were suspected of having pulmonary tuberculosis. Two (2) sputum samples each were collected. This included one spot and one morning sample. The smears were prepared and stained with FM and ZN staining techniques. Xpert MTB/RIF assay was also performed. Results. Of the 200 samples analyzed, 71 (35.5%), 46 (23.0%), and 84 (42.0%) were positive for pulmonary tuberculosis when FM, ZN, and XPERT MTB/RIF assays were used, respectively. The mean reading time of FM was three times faster than the ZN technique with very good acceptance (1.5min: 4.6min). The sensitivity and specificity of fluorescent staining to that of XPERT MTB/RIF assay were 84.5% and 100%, respectively, while those of ZN staining were 54.8% and 100%, respectively. Conclusion. For a routine laboratory test in a resource-limited setting, our study has demonstrated that fluorescence staining technique is a more sensitive test for the diagnosis of pulmonary tuberculosis as compared to the conventional ZN technique.

β-Lactam-resistant Klebsiella isolates continue to cause multidrug resistance infections worldwide. This study aimed to describe the geographical distribution of extended spectrum β-lactamase (ESBL), AmpC β-lactamase (AmpC), and carbapenemase production among 139 Klebsiella isolates recovered from patients at major referral health facilities in Ghana. The phenotypic methods of combined disc diffusion test, modified three-dimensional test, modified Hodge test (MHT), and combined disc test were performed for each isolate to detect ESBL, AmpC, carbapenemase, and metallo-β-lactamase (MBL) producers, respectively. Except for MBL, all other β-lactam resistance mechanisms were highest in the healthcare facilities situated in the northern belt of Ghana. Significant regional difference of ESBL producers was observed between the northern and middle belts as well as the northern and southern belts. Genotypic detection with polymerase chain reaction (PCR) revealed the presence of bla TEM 36/139 (25.9%), bla SHV 40/139 (28.8%), bla CTX-M 37/139 (26.6%), bla OXA-48 3/139 (2.16%), and bla NDM 1/139 (0.72%) genotypes. In conclusion, there were variations in β-lactam resistance among Klebsiella spp. from health facilities situated in the northern, middle, and southern belts of Ghana. The study provides preliminary evidence that emphasizes the need to direct more attention to antimicrobial resistance control, especially in the northern belt of Ghana. Findings from this study may be critical for creating and fine-tuning effective antimicrobial resistance control strategies and for informing accurate antibiotic prescription by practitioners.

The growing demand for Global Navigation Satellite System (GNSS) technology has necessitated the establishment of a vast and ever-growing network of International GNSS Service (IGS) tracking stations worldwide. The IGS provides highly accurate and highly reliable daily time-series Zenith Tropospheric Delay (ZTD) products using data from the member sites towards the use of GNSS for precise geodetic, climatological, and meteorological applications. However, if for reasons like poor internet connectivity, equipment failure, and power outages, the IGS station is inaccessible or malfunctioning, and gaps are created in the data archive resulting in degrading the quality of the ZTD and precipitable water vapour (PWV) estimation. To address this challenge as a means of providing an alternative data source to improve the continuous availability of ZTD data and as a backup data in the event that the IGS site data are missing or unavailable in West Africa, this paper compares the sitewise operational Vienna Mapping Functions 3 (VMF3) ZTD product with the IGS final ZTD product over five IGS stations in West Africa. Eight different statistical evaluation metrics, such as the mean bias (MB), mean absolute error (MAE), root mean squared error (RMSE), Pearson correlation coefficient (r), coefficient of determination (r²), refined index of agreement (IA_r), NashSutcliffe coefficient of efficiency (NSE), and the fraction of prediction within a factor of two (FAC2), are employed to determine the degree of agreement between the VMF3 and IGS tropospheric products. The results show that the VMF3-ZTD product performed excellently and matches very well with the IGS final ZTD product with an average MB, MAE, RMSE, r, r², NSE, IA_r, and FAC2 of 0.38cm, 0.87cm, 1.11cm, 0.988, 0.976, 0.967, 0.992, and 1.00 (100), respectively. This result is an indication that the VMF3-ZTD product is accurate enough to be used as an alternative source of ZTD data to augment the IGS final ZTD product for positioning and meteorological applications in West Africa.

Background. Regardless of the global concerted effort to control the development and spread of antimicrobial resistance, increasing cases are continually documented at many medical centres. This situation is reinforced by inadequate information on the trend of resistance resulting from lack of regular antimicrobial resistance surveillance. The present study sought to detect the number of multidrug-resistant (MDR), extended drug-resistant (XDR), and pandrug-resistant (PDR) bacterial isolates at a health facility in Ghana from January 2018 to July 2020. Method. A total of 800 data on antimicrobial testing results were extracted from the records of the health facility. The extracted data were explored for the detection of MDR, XDR, and PDR. The study further determined the use of antibiotics using the multiple-drug resistance index (MDRI). Results. Except for Staphylococcus and Neisseria spp., all bacterial isolates showed extremely high (100) proportion of MDR. Although only Staphylococcus spp. (38 (4.8)) was observed to be XDR, the rest of the bacteria showed the potential to attain the status of XDR or PDR. MDRI indicated high use of antibiotics in the health facility. Conclusion. The high antimicrobial resistance observed by the study underscores the need for prompt and effective antibiotic resistance control strategies.

The ability to precisely and accurately model and predict tropospheric delay is essential for precise global navigation satellite system (GNSS) and meteorological applications. The International GNSS Service (IGS) provides highly accurate and highly reliable daily time series zenith tropospheric delay (ZTD) products for all its member sites using data from each IGS site. Nevertheless, if for reasons such as poor internet connectivity, equipment failure, and power outages the IGS station is inaccessible, gaps are created in the data archive, resulting in degrading the quality of the ZTD estimation, as well as inhibits the quality of precipitable water vapour (PWV) estimation, needed for precise positioning applications, meteorological studies, and weather forecasting. To address this challenge, five regression models are proposed in this study to model and predict daily ZTDs using daily datasets from four IGS stations in West Africa over a period of 5 years (2015–2019). The site‐specific Vienna Mapping Functions 3 (VMF3) products (ZTD, pressure, temperature, water vapour partial pressure) and stations' coordinates (latitudes and longitudes) are used as the predictors, while the IGS final ZTD product as the response variable in fitting the models. Several performance measures are calculated to compare the predictive performance of the models. The results show that the five regression models performed outstandingly and agree very well with the IGS‐ZTD data, and hence provide a useful alternative for ZTD predictions and also in the event the West African IGS stations' ZTD data are unavailable. Nonetheless, the support vector regression model outperformed the remaining four models.