Interrupted Time Series Analysis of Monthly Birth Count in Obio Cottage Hospital Port Harcourt in the Pre- and Post-COVID-19 Era

Abstract

The emergence of a pandemic Covid-19 that affected the globe in the year 2019 introduced a shift in lifestyle and posed unparalleled challenges to global health care systems. This necessitated a rapid adaptation to a new way of doing things and a modification in lifestyle. Due to high contagious nature of the scourge, government of different nations introduced policies to curb the spread and limit fatalities. Access to health care was regulated hence, understanding fertility dynamics is essential for effective population planning and public health policy formulation. This study examines the impact of COVID-19 on monthly birth counts using descriptive statistics and time-series analysis covering the period before and after the declaration of Covid-19 in 2020 from January 2014 to December 2024, using both descriptive statistics and a Seasonal Autoregressive Integrated Moving Average modelling approach with an intervention variable. Descriptive analysis revealed a marked decline in birth outcomes following the pandemic. The mean monthly births decreased from 296.03 in the pre-COVID-19 period to 247.22 in the post-COVID-19 period, representing an approximate 16.5% reduction. The total number of births also fell from 17,762 to 14,833, while the maximum and minimum monthly counts dropped significantly. The post-pandemic distribution exhibited a slight shift toward symmetry and lower peaks, reflecting both the reduction in overall fertility and increased variability in monthly birth counts. Time series plots further highlighted cyclical fluctuations in births, with the post-COVID period showing lower levels and greater volatility compared to the pre-pandemic period. These findings suggest that the pandemic substantially altered reproductive behaviour, likely due to economic uncertainty, health concerns, and disruptions to healthcare services. The SARIMA(2,0,2)(2,0,2)[12] model with an intervention variable quantified the magnitude of the COVID-19 effect, estimating a negative intervention coefficient of −28.52, indicating that the pandemic reduced average monthly births by approximately 29. The inclusion of the intervention improved model fit, as shown by a decrease in residual variance from 781.6 to 637.1, confirming that the pandemic accounted for a significant portion of birth variability. Seasonal and autoregressive parameters indicate that monthly births continue to exhibit predictable cyclical patterns influenced by past values, despite the pandemic shock. The results demonstrate that COVID- 19 imposed a moderate but statistically meaningful decline in fertility at the hospital, highlighting the sensitivity of birth patterns to major public health crises. Based on the findings E- ISSN 2489-009X , of this study, it was recommended that policymakers and health planners should anticipate demographic shifts and ensure continued access to reproductive health services during periods of societal disruption.

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