Uropathogenic Escherichia coli (E. coli) is an important urinary tract infection (UTI) that has been associated with both complicated and uncomplicated disease conditions. The global emergence of multiple drug-resistant (MDR) and extended-spectrum β-lactamase (ESBL) is of public health concern as the resistance limits the current treatment options. The objective of this study was to analyze the antibiotic-resistant patterns among the uropathogenic E. coli isolates at the University of Cape Coast (UCC) hospital between 2013 and 2015 as baseline data to understand the current antibiotic resistance situation within UCC and its environs. A retrospective cross-sectional study of bacteria isolates at UCC hospital from January 2013 to December 2015 were analyzed. A standard biochemical and antibiotic susceptibility tests were performed using Kirby-Bauer NCCLs modified disc diffusion technique. The network of interaction between pathogenic isolates and antibiotic resistance was performed using Cytoscape software. Statistical significance was tested using ANOVA and one-sample Wilcoxon test. The overall E. coli prevalence was 15.76% (32/203); females had the highest infection of 17.33% (26/150) compared to male subjects who had 11.32% (6/53) out of all the pathogenic infections. The E. coli prevalence among the age categories were 2/21 (9.52%), 27/154 (17.53%) and 4/21 (19.05%) among ≤20 years, 21–40 years and 41–60 years respectively. The isolated resistant pathogens exhibited different antibiotic resistance patterns. An interaction network of nodes connecting to other nodes indicating positive correlations between the pathogens and antibiotic resistance was established. Escherichia coli, Citrobacter spp, Klebsiella spp among other isolated pathogens formed higher centrality in the network of interaction with antibiotic resistance. The individual E. coli isolates showed a significant difference in the mean ± SD (95% CI) pattern of antibiotic resistance, 2.409±1.205 (1.828–2.990), χ2 = 36.68, p<0.0001. In conclusion, the study reports the interaction of E. coli isolates at UCC hospital and its antibiotic-resistant status between 2013 and 2015. This data forms the baseline information for assessing the current antibiotic status in UCC and its environs.

Background: Modelling and forecasting demand for future emergency healthcare services is increasingly gaining wide attention in the emergency healthcare industry worldwide. This aids hospital managers in looking into various options to appropriately plan and allocate available scarce resources for optimal and swift performance. Despite its importance, our knowledge of daily patient flow into the Accident and Emergency Department (AED) of the University of Cape Coast Hospital is incomprehensive, and even the model that best explains its movements remains unknown. Methods: Using daily periodicity of 517 time-series observations on daily patient arrivals sourced from the AED register over January 2020 through May 2021 the autoregressive integrated moving average (ARIMA) of the classical Box-Jenkins methods of time series analysis was used to analyse the data. Results: This study revealed twenty-five non-seasonal candidate models for the hospital AED and ARIMA (0, 1, 2) emerged as the best fitting model. The study results showed that the daily patient arrivals at the AED section of the University Hospital witnessed a 50% decline on average within the study period and a further 33% decline in the forecast region. The findings also revealed very high volatility in daily patient arrivals with an average of eight patient arrivals per day. Conclusion Non-seasonal ARIMA (0, 1, 2) was identified as the best model. Thus, for policy, intervention, and future research direction, it is recommended that steps are taken to investigate the highly volatile nature of patient arrivals as well as the steady downward trending of the daily patient flow at the Accident and Emergency Department of the University Hospital

Introduction: the World Health Organization recommends that the gold standard for diagnosing typhoid fever is the use of blood cultures. However, under real-world conditions in low-resource settings, there are lack of culture facilities as well as expertise, and usually, patients report late after prior antibiotic exposure. This study sought to evaluate the performance of typhoid rapid diagnostic tests, blood, and stool cultures as well as polymerase chain reaction (PCR) under such settings. Methods: This cross-sectional study involved the use of blood and stool samples from 400 consenting outpatients suspected of typhoid fever by attending clinicians at the University of Cape Coast Hospital, Ghana. Results: out of the 400 participants, 171 (42.8%) tested positive to at least one of the RDTs. Even though many of the participants had a history of fever, all of them were afebrile as none presented with a temperature of 380C and above. There was a high (48.0%) history of antibiotic use within two weeks before presentation. No participant was a culture or PCR positive for S. typhi and paratyphi. However, in 7(1.8%) participants, other salmonella species were detected by PCR. Also, citrobacter and proteus vulgaris were cultured in 13(3.3%) and 10(2.5%) participants respectively using stool samples. In blood samples, there was a 7(1.8%) growth of Staphylococcus aureus. Conclusion: under real-world conditions where patients usually present without typical symptoms such as high temperatures probably after prior antibiotic use, cultures and PCR perform poorly. There is therefore a need for further studies aimed at improving the yields of these important diagnostic tests in such settings.