Predictive signs and symptoms of bacterial meningitis isolates in Northern Ghana.

Cerebrospinal meningitis (CSM) is a public health burden in Ghana that causes up to 10% mortality in confirmed cases annually. About 20% of those who survive the infection suffer permanent sequelae. The study sought to understand the predictive signs and symptoms of bacterial meningitis implicated in its outcomes. Retrospective data from the Public Health Division, Ghana Health Service on bacterial meningitis from 2015 to 2019 was used for this study. A pre-tested data extraction form was used to collect patients' information from case-based forms kept at the Disease Control Unit from 2015 to 2019. Data were transcribed from the case-based forms into a pre-designed Microsoft Excel template. The data was cleaned and imported into SPSS version 26 for analysis. Between 2015 and 2019, a total of 2446 suspected bacterial meningitis cases were included in the study. Out of these, 842 (34.4%) were confirmed. Among the confirmed cases, males constituted majority with 55.3% of the cases. Children below 14 years of age were most affected (51.4%). The pathogens commonly responsible for bacterial meningitis were Neisseria meningitidis (43.7%) and Streptococcus pneumoniae (53.0%) with their respective strains Nm W135 (36.7%), Nm X (5.1%), Spn St. 1 (26.2%), and Spn St. 12F/12A/12B/44/4 (5.3%) accounting for more than 70.0% of the confirmed cases. The presence of neck stiffness (AOR = 1.244; C.I 1.026-1.508), convulsion (AOR = 1.338; C.I 1.083-1.652), altered consciousness (AOR = 1.516; C.I 1.225-1.876), and abdominal pains (AOR = 1.404; C.I 1.011-1.949) or any of these signs and symptoms poses a higher risk for testing positive for bacterial meningitis adjusting for age. Patients presenting one and/or more of these signs and symptoms (neck stiffness, convulsion, altered consciousness, and abdominal pain) have a higher risk of testing positive for bacterial meningitis after statistically adjusting for age.

Trends in Neisseria meningitidis serogroups amongst patients with suspected cerebrospinal meningitis in the meningitis belt of Ghana: a 5-year retrospective study.

BACKGROUND: Serogroup A Neisseria meningitidis was the major cause of meningococcal meningitis epidemics in the African meningitis belt before 2010 when the monovalent meningococcal A conjugate vaccine (MenAfriVac) was introduced in the region. Therefore, this study aimed to establish the trends in N. meningitidis serogroups from 2016 to 2020 in Ghana's meningitis belt. METHODS: Polymerase chain reaction (PCR) confirmed laboratory results of suspected cases of cerebrospinal meningitis from January, 2016 to March, 2020 were obtained from the Tamale Public Health Laboratory. The data were subjected to trend analysis using Statistical Package for the Social Sciences version 25. Differences between discrete variables were analyzed using the Cochran-Armitage trend test. RESULTS: Of the 2,426 suspected cases, 395 (16.3%) were confirmed positive for N. meningitidis using PCR. Serogroup X showed a significant upward trend (P < 0.01), and serogroup W showed a downward trend (P < 0.01). However, no significant trend was observed for any other serogroup. CONCLUSION: This study showed the emergence of serogroup X, a non-vaccine type, as the predominant N. meningitidis serogroup in the wake of a declining serogroup W in Ghana's meningitis belt.

Bacterial infections epidemiology and factors associated with multidrug resistance in the northern region of Ghana.

Bacterial infections caused by multidrug resistant organisms are a major global threat. There is still a knowledge gap on this situation in the Northern Region of Ghana. This study determined the prevalence and resistance profile of bacterial infections. It also identified factors associated with multidrug resistance in the study area. This was a retrospective cross-sectional design and it analyzed data from the samples received at the Tamale Zonal Public Health Reference Laboratory from June 2018 to May 2022. The data were analyzed using the R software version 4.2.0. Univariate and multivariable binary logistic regression analyses were used to determine the factors associated with multidrug resistance. The samples included all specimen types possible. The specimens were collected for the purpose of clinical bacteriology diagnostics. Overall a total of 1222 isolates were obtained. The three (3) main bacteria responsible for infections were: Klebsiella spp. (27%), Moraxella spp. (22%), Escherichia spp. (16%). High resistance levels were found against the tested antibiotics and about 41.60% of the bacterial strains isolated were multidrug resistant. Hospitalization was associated with multidrug resistance in univariate (COR 1.96; 95% CI 1.43-2.71; P-value < 0.001) and multivariable analyses (AOR 1.78; 95% CI 1.28-2.49; P-value < 0.001). There is the need for further research on the molecular epidemiology of antibiotic resistance genes in the study area to effectively control the spread of multidrug resistant pathogens. In addition, efforts to build the capacity of health professionals on infection prevention and control as well as diagnostic and antimicrobial stewardship needs urgent attention.

Performance of COVID-19 associated symptoms and temperature checking as a screening tool for SARS-CoV-2 infection.

INTRODUCTION: Coronavirus disease-19 (COVID-19), which started in late December, 2019, has spread to affect 216 countries and territories around the world. Globally, the number of cases of SARS-CoV-2 infection has been growing exponentially. There is pressure on countries to flatten the curves and break transmission. Most countries are practicing partial or total lockdown, vaccination, massive education on hygiene, social distancing, isolation of cases, quarantine of exposed and various screening approaches such as temperature and symptom-based screening to break the transmission. Some studies outside Africa have found the screening for fever using non-contact thermometers to lack good sensitivity for detecting SARS-CoV-2 infection. The aim of this study was to determine the usefulness of clinical symptoms in accurately predicting a final diagnosis of COVID-19 disease in the Ghanaian setting. METHOD: The study analysed screening and test data of COVID-19 suspected, probable and contacts for the months of March to August 2020. A total of 1,986 participants presenting to Tamale Teaching hospital were included in the study. Logistic regression and receiver operator characteristics (ROC) analysis were carried out. RESULTS: Overall SARS-CoV-2 positivity rate was 16.8%. Those with symptoms had significantly higher positivity rate (21.6%) compared with asymptomatic (17.0%) [chi-squared 15.5, p-value, <0.001]. Patients that were positive for SARS-CoV-2 were 5.9 [3.9-8.8] times more likely to have loss of sense of smell and 5.9 [3.8-9.3] times more likely to having loss of sense of taste. Using history of fever as a screening tool correctly picked up only 14.8% of all true positives of SARS-CoV-2 infection and failed to pick up 86.2% of positive cases. Using cough alone would detect 22.4% and miss 87.6%. Non-contact thermometer used alone, as a screening tool for COVID-19 at a cut-off of 37.8 would only pick 4.8% of positive SARS-CoV-2 infected patients. CONCLUSION: The use of fever alone or other symptoms individually [or in combination] as a screening tool for SARS-CoV-2 infection is not worthwhile based on ROC analysis. Use of temperature check as a COVID-19 screening tool to allow people into public space irrespective of the temperature cut-off is of little benefit in diagnosing infected persons. We recommend the use of facemask, hand hygiene, social distancing as effective means of preventing infection.