Performance evaluation of SARS-CoV-2 rapid diagnostic tests in Nigeria: A cross-sectional study.

The COVID-19 pandemic challenged health systems globally. Reverse transcription polymerase chain reaction (RT-PCR) is the gold standard for detecting the presence of SARS-CoV-2 in clinical samples. Rapid diagnostic test (RDT) kits for COVID-19 have been widely used in Nigeria. This has greatly improved test turnover rates and significantly decreased the high technical demands of RT-PCR. However, there is currently no nationally representative evaluation of the performance characteristics and reliability of these kits. This study assessed the sensitivity, specificity, and predictive values of ten RDT kits used for COVID-19 testing in Nigeria. This large multi-centred cross-sectional study was conducted across the 6 geo-political zones of Nigeria over four months. Ten antigen (Ag) and antibody (Ab) RDT kits were evaluated, and the results were compared with RT-PCR. One thousand, three hundred and ten (1,310) consenting adults comprising 767 (58.5%) males and 543 (41.5%) females participated in the study. The highest proportion, 757 (57.7%), were in the 20-39 years' age group. In terms of diagnostic performance, Lumira Dx (61.4, 95% CI: 52.4-69.9) had the highest sensitivity while MP SARS and Panbio (98.5, 95% CI: 96.6-99.5) had the highest specificity. For predictive values, Panbio (90.7, 95% CI: 79.7-96.9) and Lumira Dx (81.2, 95% CI: 75.9-85.7) recorded the highest PPV and NPV respectively. Ag-RDTs had better performance characteristics compared with Ab-RDTs; however, the sensitivities of all RDTs in this study were generally low. The relatively high specificity of Ag-RDTs makes them useful for the diagnosis of infection in COVID-19 suspected cases where positive RDT may not require confirmation by molecular testing. There is therefore the need to develop RDTs in-country that will take into consideration the unique environmental factors, interactions with other infectious agents, and strains of the virus circulating locally. This may enhance the precision of rapid and accurate diagnosis of COVID-19 in Nigeria.

Predictors of Lassa fever diagnosis in suspected cases reporting to health facilities in Nigeria.

Lassa fever (LF) remains endemic in Nigeria with the country reporting the highest incidence and mortality globally. Recent national data suggests increasing incidence and expanding geographic spread. Predictors of LF case positivity in Nigeria have been sparsely studied. We thus sought to determine the sociodemographic and clinical determinants of LF positivity amongst suspected cases presenting to health facilities from 2018 to 2021. A secondary analysis of the national LF surveillance data between January 2018 and December 2021. Socio-demographic and clinical data of 20,027 suspected LF cases were analysed using frequencies and Chi-square statistics with significant p-value set at p < 0.05. The outcome variable was LF case status (positive or negative). Predictors of LF case positivity were assessed using multiple logistic regression models with 95% confidence intervals (CI). Case positivity rate (CPR) for the four years was 15.8% with higher odds of positivity among age group 40-49 years (aOR = 1.40; 95% CI 1.21-1.62), males (aOR = 1.11; 95% CI 1.03-1.20), those with formal education (aOR = 1.33; 95% CI 1.13-1.56), artisans (aOR = 1.70; 95% CI 1.28-2.27), religious leaders (aOR = 1.62; 95% CI 1.04-2.52), farmers (aOR = 1.48; 95% CI 1.21-1.81), and symptomatic individuals (aOR = 2.36; 95% CI 2.09-2.68). Being a health worker (aOR = 0.69; 95% CI 0.53-0.91), a teacher (aOR = 0.69; 95% CI 0.53-0.89) and cases reporting in the 3rd quarter (aOR = 0.79; 95% CI 0.69-0.92) had lower odds. In a sex-disaggregated analysis, female farmers had higher odds of positivity (aOR = 2.43; 95% CI 1.76-3.38; p < 0.001) than male farmers (aOR = 1.52; 95% CI 1.19-1.96; p < 0.01). Fever (aOR = 2.39; 95% CI 2.00-2.84) and gastrointestinal (GI) symptoms (aOR = 2.15; 95% CI 1.94-2.37) had the highest odds among symptoms. Combination of fever and GI symptoms (aOR = 2.15; 95% CI 1.50-3.10), fever and neurological symptoms (aOR = 6.37; 95% CI 1.49-27.16), fever and musculo-skeletal symptoms (aOR = 2.95; 95% CI 1.37-6.33), fever and cardiopulmonary symptoms (aOR = 1.81; 95% CI 1.24-2.64), and cardiopulmonary and general symptoms (aOR = 1.50; 95% CI 1.19-1.89) were also predictive. Cumulative LF CPR appears high with clearly identified predictors. Targeted interventions with heightened index of suspicion for sociodemographic categories predictive of LF in suspected cases are recommended. Ethnographic and further epidemiological studies could aid better understanding of these associations.

Epidemiological trends of Lassa fever in Nigeria, 2018-2021.

BACKGROUND: Lassa fever is a viral haemorrhagic fever endemic in Nigeria. Improved surveillance and testing capacity have revealed in an increased number of reported cases and apparent geographic spread of Lassa fever in Nigeria. We described the recent four-year trend of Lassa fever in Nigeria to improve understanding of its epidemiology and inform the design of appropriate interventions. METHODS: We analysed the national surveillance data on Lassa fever maintained by the Nigeria Centre for Diseases Control (NCDC) and described trends, sociodemographic, geographic distribution, and clinical outcomes. We compared cases, positivity, and clinical outcomes in the period January 2018 to December 2021. RESULTS: We found Lassa fever to be reported throughout the year with more than half the cases reported within the first quarter of the year, a recent increase in numbers and geographic spread of the virus, and male and adult (>18 years) preponderance. Case fatality rates were worse in males, the under-five and elderly, during off-peak periods, and among low reporting states. CONCLUSION: Lassa fever is endemic in Nigeria with a recent increase in numbers and geographical distribution. Sustaining improved surveillance, enhanced laboratory diagnosis and improved case management capacity during off-peak periods should remain a priority. Attention should be paid to the very young and elderly during outbreaks. Further research efforts should identify and address specific factors that determine poor clinical outcomes.

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.

Epidemiological comparison of the first and second waves of the COVID-19 pandemic in Nigeria, February 2020-April 2021.

BACKGROUND: With reports of surges in COVID-19 case numbers across over 50 countries, country-level epidemiological analysis is required to inform context-appropriate response strategies for containment and mitigation of the outbreak. We aimed to compare the epidemiological features of the first and second waves of COVID-19 in Nigeria. METHODS: We conducted a retrospective analysis of the Surveillance Outbreak Response Management and Analysis System data of the first and second epidemiological waves, which were between 27 February and 24 October 2020, and 25 October 2020 to 3 April 2021, respectively. Descriptive statistical measures including frequencies and percentages, test positivity rate (TPR), cumulative incidence (CI) and case fatality rates (CFRs) were compared. A p value of <0.05 was considered statistically significant. All statistical analyses were carried out in STATA V.13. RESULTS: There were 802 143 tests recorded during the study period (362 550 and 439 593 in the first and second waves, respectively). Of these, 66 121 (18.2%) and 91 644 (20.8%) tested positive in the first and second waves, respectively. There was a 21.3% increase in the number of tests conducted in the second wave with TPR increasing by 14.3%. CI during the first and second waves were 30.3/100 000 and 42.0/100 000 respectively. During the second wave, confirmed COVID-19 cases increased among females and people 30 years old or younger and decreased among urban residents and individuals with travel history within 14 days of sample collection (p value <0.001). Most confirmed cases were asymptomatic at diagnosis during both waves: 74.9% in the first wave; 79.7% in the second wave. CFR decreased during the second wave (0.7%) compared with the first wave (1.8%). CONCLUSION: Nigeria experienced a larger but less severe second wave of COVID-19. Continued implementation of public health and social measures is needed to mitigate the resurgence of another wave.