COVID-19 mortality rate and its associated factors during the first and second waves in Nigeria.

COVID-19 mortality rate has not been formally assessed in Nigeria. Thus, we aimed to address this gap and identify associated mortality risk factors during the first and second waves in Nigeria. This was a retrospective analysis of national surveillance data from all 37 States in Nigeria between February 27, 2020, and April 3, 2021. The outcome variable was mortality amongst persons who tested positive for SARS-CoV-2 by Reverse-Transcriptase Polymerase Chain Reaction. Incidence rates of COVID-19 mortality was calculated by dividing the number of deaths by total person-time (in days) contributed by the entire study population and presented per 100,000 person-days with 95% Confidence Intervals (95% CI). Adjusted negative binomial regression was used to identify factors associated with COVID-19 mortality. Findings are presented as adjusted Incidence Rate Ratios (aIRR) with 95% CI. The first wave included 65,790 COVID-19 patients, of whom 994 (1∙51%) died; the second wave included 91,089 patients, of whom 513 (0∙56%) died. The incidence rate of COVID-19 mortality was higher in the first wave [54∙25 (95% CI: 50∙98-57∙73)] than in the second wave [19∙19 (17∙60-20∙93)]. Factors independently associated with increased risk of COVID-19 mortality in both waves were: age ≥45 years, male gender [first wave aIRR 1∙65 (1∙35-2∙02) and second wave 1∙52 (1∙11-2∙06)], being symptomatic [aIRR 3∙17 (2∙59-3∙89) and 3∙04 (2∙20-4∙21)], and being hospitalised [aIRR 4∙19 (3∙26-5∙39) and 7∙84 (4∙90-12∙54)]. Relative to South-West, residency in the South-South and North-West was associated with an increased risk of COVID-19 mortality in both waves. In conclusion, the rate of COVID-19 mortality in Nigeria was higher in the first wave than in the second wave, suggesting an improvement in public health response and clinical care in the second wave. However, this needs to be interpreted with caution given the inherent limitations of the country's surveillance system during the study.

Assessing the capacity of symptom scores to predict COVID-19 positivity in Nigeria: a national derivation and validation cohort study.

OBJECTIVES: This study aimed to develop and validate a symptom prediction tool for COVID-19 test positivity in Nigeria. DESIGN: Predictive modelling study. SETTING: All Nigeria States and the Federal Capital Territory. PARTICIPANTS: A cohort of 43 221 individuals within the national COVID-19 surveillance dataset from 27 February to 27 August 2020. Complete dataset was randomly split into two equal halves: derivation and validation datasets. Using the derivation dataset (n=21 477), backward multivariable logistic regression approach was used to identify symptoms positively associated with COVID-19 positivity (by real-time PCR) in children (≤17 years), adults (18-64 years) and elderly (≥65 years) patients separately. OUTCOME MEASURES: Weighted statistical and clinical scores based on beta regression coefficients and clinicians' judgements, respectively. Using the validation dataset (n=21 744), area under the receiver operating characteristic curve (AUROC) values were used to assess the predictive capacity of individual symptoms, unweighted score and the two weighted scores. RESULTS: Overall, 27.6% of children (4415/15 988), 34.6% of adults (9154/26 441) and 40.0% of elderly (317/792) that had been tested were positive for COVID-19. Best individual symptom predictor of COVID-19 positivity was loss of smell in children (AUROC 0.56, 95% CI 0.55 to 0.56), either fever or cough in adults (AUROC 0.57, 95% CI 0.56 to 0.58) and difficulty in breathing in the elderly (AUROC 0.53, 95% CI 0.48 to 0.58) patients. In children, adults and the elderly patients, all scoring approaches showed similar predictive performance. CONCLUSIONS: The predictive capacity of various symptom scores for COVID-19 positivity was poor overall. However, the findings could serve as an advocacy tool for more investments in resources for capacity strengthening of molecular testing for COVID-19 in Nigeria.

Research as a pillar of Lassa fever emergency response: lessons from Nigeria.

Emerging and re-emerging infectious diseases are becoming more frequent and developing countries are especially at increased risk. A recurring infectious disease outbreak in Nigeria has been that of Lassa fever (LF), a disease that is endemic in Nigeria and other West African countries. Nigeria, between 1st January and 27th October 2019, reported 743 confirmed cases of LF and 157 deaths in confirmed cases. Lassa fever outbreaks continue to be recurrent after fifty years of its identification. The true burden of the disease in Nigeria is unknown while gaps in knowledge about the infection still persist. Based on the Nigeria national Lassa fever research agenda and the World Health Organisation's roadmap initiative for accelerating research and product development which enables effective and timely emergency response to LF disease epidemics among other infectious diseases; a research pillar was added to the seven existing LF emergency operations centre response pillars in 2019. We describe lessons learnt from the integration of a research pillar into the LF national emergency response.

Patient characteristics associated with COVID-19 positivity and fatality in Nigeria: retrospective cohort study.

OBJECTIVE: Despite the increasing disease burden, there is a dearth of context-specific evidence on the risk factors for COVID-19 positivity and subsequent death in Nigeria. Thus, the study objective was to identify context-specific factors associated with testing positive for COVID-19 and fatality in Nigeria. DESIGN: Retrospective cohort study. SETTING: COVID-19 surveillance and laboratory centres in 36 states and the Federal Capital Territory reporting data to the Nigeria Centre for Disease Control. PARTICIPANTS: Individuals who were investigated for SARS-CoV-2 using real-time PCR testing during the study period 27 February-8 June 2020. METHODS: COVID-19 positivity and subsequent mortality. Multivariable logistic regression analyses were performed to identify factors independently associated with both outcome variables, and findings are presented as adjusted ORs (aORs) and 95% CIs. RESULTS: A total of 36 496 patients were tested for COVID-19, with 10 517 confirmed cases. Of 3215 confirmed cases with available clinical outcomes, 295 died. Factors independently associated with COVID-19 positivity were older age (p value for trend<0.0001), male sex (aOR 1.11, 95% CI 1.04 to 1.18) and the following presenting symptoms: cough (aOR 1.23, 95% CI 1.13 to 1.32), fever (aOR 1.45, 95% CI 1.45 to 1.71), loss of smell (aOR 7.78, 95% CI 5.19 to 11.66) and loss of taste (aOR 2.50, 95% CI 1.60 to 3.90). An increased risk of mortality following COVID-19 was observed in those aged ≥51 years, patients in farming occupation (aOR 7.56, 95% CI 1.70 to 33.53) and those presenting with cough (aOR 2.06, 95% CI 1.41 to 3.01), breathing difficulties (aOR 5.68, 95% CI 3.77 to 8.58) and vomiting (aOR 2.54, 95% CI 1.33 to 4.84). CONCLUSION: The significant risk factors associated with COVID-19 positivity and subsequent mortality in the Nigerian population are similar to those reported in studies from other countries and should guide clinical decisions for COVID-19 testing and specialist care referrals.

Preponderance of bacterial isolates in urine of HIV-positive malaria-infected pregnant women with urinary tract infection.

INTRODUCTION: This study examined HIV and malaria co-infection as a risk factor for urinary tract infections (UTIs) in pregnancy. The study group included 74 pregnant women, 20 to 42 years of age, who attended the antenatal clinic at the Specialist Hospital at Akure, Ondo State, Nigeria. METHODOLOGY: Forty-four of the pregnant women were either HIV seropositive with malaria infection (HIV+Mal+) or HIV seropositive without malaria (HIV+Mal-). The remaining thirty pregnant women served as controls and included women HIV seronegative but with malaria (HIV-Mal+) and women HIV seronegative without malaria. UTI was indicated by a bacterial colony count of greater than 105/mL of urine, using cysteine lactose electrolyte deficient medium (CLED) as the primary isolation medium. Bacterial isolates were characterized using convectional bacteriological methods, and antibiotics sensitivity tests were carried out using the disk diffusion method. RESULTS: A total of 246 bacterial isolates were recovered from the cultures, with a mean of 3.53 isolates per subject. Women who were HIV+Mal+ had the most diverse group of bacterial isolates and the highest frequency of UTIs. The bacterial isolates from the HIV+Mal+ women also showed the highest degree of antibiotic resistance. CONCLUSIONS: While pregnancy and HIV infection may each represent a risk factor for UTI, HIV and malaria co-infection may increase its frequency in pregnancy. The higher frequency of multiple antibiotic resistance observed among the isolates, particularly isolates from HIV+Mal+ subjects, poses a serious public health concern as these strains may aggravate the prognosis of both UTI and HIV infection.