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

Elimian, Kelly Osezele; Aderinola, Olaolu; Gibson, Jack; Myles, Puja; Ochu, Chinwe Lucia; King, Carina; Okwor, Tochi; Gaudenzi, Giulia; Olayinka, Adebola; Zaiyad, Habib Garba; Ohonsi, Cornelius; Ebhodaghe, Blessing; Dan-Nwafor, Chioma; Nwachukwu, William; Abdus-salam, Ismail Adeshina; Akande, Oluwatosin Wuraola; Falodun, Olanrewaju; Arinze, Chinedu; Ezeokafor, Chidiebere; Jafiya, Abubakar; Ojimba, Anastacia; Aremu, John Tunde; Joseph, Emmanuel; Bowale, Abimbola; Mutiu, Bamidele; Saka, Babatunde; Jinadu, Arisekola; Hamza, Khadeejah; Ibeh, Christian; Bello, Shaibu; Asuzu, Michael; Mba, Nwando; Oladejo, John; Ilori, Elsie; Alfvén, Tobias; Igumbor, Ehimario; Ihekweazu, Chikwe

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.