Positivity Rate as a Performance Indicator for COVID-19 Response in Edo State, Nigeria
Andrew Ifeanyichukwu Obi, Pius Ononigwe, Faith Ireye, Patrick Okundia, Osamuyi Irowa, Helen Eboreime, Ekaete Tobin, Lauretta Iruobe, Bruce Osa, Uwa Okhuarobo, Kester Okoduwa
Asian Journal of Research in Infectious Diseases · pp. 24–30 · Published 10 Nov 2021
10.9734/ajrid/2021/v8i330240Abstract
Background: Positivity rate is a very reliable indicator in determining the effectiveness of public health interventions of infectious disease magnitude. Aim: To use positivity rate as performance indicator of effectiveness of COVID-19 Control measures in Edo State, Southern Nigeria. Materials and Methods: Laboratory based record review of 20,220 Polymerase Chain Reaction (PCR) based laboratory results from COVID-19 line-list analysed from the four (4) NCDC accredited molecular laboratory within Edo State. The weekly COVID-19 test positivity was computed in relation to the total samples tested between 23rd March to 30th November, 2020. Data collected were analysed using IBM SPSS version 20.0 software with statistical significance set at p˂0.050 and 95% Confidence Interval. Results: A total of 20,220 PCR results reviewed with 2696 (13.3%) COVID-19 cases identified while 17,524 (86.7%) were negative. The average weekly sample collection and testing was 552.28 ± 369.98, with average weekly COVID-19 case yield and positivity rate (%) of 77.89 ±106.23 and 12.20±13.75% respectively. A statistically significant positive correlation was identified between sample tested and COVID-19 case yield (R = 0.569; < 0.01). The first wave of the COVID-19 in Edo State witnessed a consistent and progressive decline in test positivity rate till it deepened at 0.6 % by the end of November, 2020. Conclusion: Increasing sample testing has significant positive correlation with COVID-19 case detection in Edo State. Positivity rate was a good indicator to monitor COVID-19 outbreak response in Edo State. Targeted surveillance and sample collection for testing can significantly help improve the quality and case yield during epidemic outbreak response. Bridging the gap in sample collection for testing can greatly influence how quickly an epidemic outbreak response and control is achieved.
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