Predictive Analysis and Time Series Modeling of Canine Parvoviral Enteritis: A Case Study from Ibadan, Nigeria.

Abstract

Canine parvoviral enteritis (CPE) is a highly contagious and often fatal disease, particularly affecting young, unvaccinated dogs. Although anecdotal reports suggest seasonal variation in CPE incidence in Nigeria, comprehensive time series analyses remain scarce. This study analyzed clinical records of CPE cases-diagnosed either clinically or via laboratory confirmation-collected from three veterinary clinics in Ibadan, Nigeria, between January 2018 and December 2024. Temporal patterns were decomposed into trend, seasonal, and random components. Stationarity and temporal autocorrelation were assessed using the Augmented Dickey-Fuller and Ljung-Box tests, respectively. An Autoregressive Integrated Moving Average (ARIMA) model was selected using the auto.arima function implemented in R (Vienna, Austria), and subsequently used to forecast CPE incidence over a 24-month horizon. The Box-Pierce test on residuals (P = 0.9409) confirmed the model's adequacy. CPE incidence showed distinct seasonal peaks during the dry months, best captured by the ARIMA (1,1,1)(1,0,0) (model non-seasonal autoregressive order =1, differencing order =1, and moving average order =1; seasonal autoregressive order =1, differencing order = 0, and moving average order = 0; monthly seasonality = 12), and exhibited a negative correlation with historical average monthly rainfall (r = -0.55). However, forecasts for 2025-2026 suggest a gradual decline in incidence and a transition toward year-round occurrence with less pronounced seasonal peaks. These findings underscore the need for continuous preventive efforts. Veterinary practitioners should maintain a high index of suspicion for CPE, especially in young dogs with incomplete vaccination status.