STRUCTURAL BREAKS AND VOLATILITY SHIFTS IN MONTHLY MALARIA CASE COUNTS AT FMC ASABA,NIGERIA: A TIME-SERIES ANALYSIS, 2010–2022
DOI:
https://doi.org/10.60787/tnamp.v25.714Keywords:
malaria, time series, Structural break Volatility, hospital surveillance, NigeriaAbstract
Facility-level malaria records can reveal operational changes that annual summaries may miss. This study analysed de-identified monthly outpatient malaria counts from Federal Medical Centre (FMC) Asaba, Nigeria, January 2010–December 2022. After auditing the records, a continuous panel of 156 months was analysed; 147 months were observed and nine missing months were linearly imputed. The total series was log-transformed, decomposed by STL, tested for stationarity, and evaluated with CUSUM, BIC-selected segmented regression, Brown-Forsythe variance tests, ARCH- LM diagnostics, and subgroup break searches. Monthly total counts ranged from 107 to 1,829 (mean = 606.55). Three mean-level breaks were retained: October 2013, June 2015, and June 2019. Mean counts declined from 650.42 to 320.52 across the first three regimes, then rose to 962.23 after June 2019. Residual volatility increased after April 2021. These statistical shifts support break-sensitive facility surveillance, while not identifying causal drivers.
Downloads
References
World Health Organization. World malaria report 2023. Geneva: World Health Organization; 2023. Available from: https://www.who.int/teams/global- alaria- programme/reports/world-malaria-report-2023
Amadi M, Erandi KKWH. Assessing the relationship between malaria incidence levels and meteorological factors using cluster-integrated regression. BMC Infectious Diseases. 2024;24:664. doi: 10.1186/s12879-024-09570-z
Oniyelu DO, Folorunsho O, Adewole L, Bakare EA, Okoronkwo C, Eze N, et al. Time series analysis of malaria in pregnancy, using wavelet and SARIMAX models. PLOS ONE. 2025;20(8):e0328888. doi: 10.1371/journal.pone.0328888
Bakare EA, Dukundane D, Salako KV, Kakaï RG, Okoronkwo C, Nelson E. Modelling the association of rainfall and temperature with malaria incidence in Adamawa State, Nigeria. Scientific Reports. 2026;16:8761. doi: 10.1038/ 41598-026-38705-2 21 Aghamie et al., - Transactions of NAMP 25 (2026) 13-22
Bakare EA, Mogbojuri OA, Bakare DA, Odewusi OJ. Exploring the past and forecasting the future of malaria in selected Nigerian states: A time series modelling approach using wavelet and SARIMA. PLOS ONE. 2026;21(4):e0337791. doi: 10.1371/journal.pone.0337791
Jalloh SW, Malenje B, Imboga H, Hodges MH, et al. Forecasting malaria cases using climate variability in Sierra Leone. Malaria Journal. 2025;24:158. doi: 10.1186/s12936-025-05389-4
Armando CJ, Rocklöv J, Sidat M, Tozan Y, Mavume AF, Sewe MO. Spatio- temporal modelling and prediction of malaria incidence in Mozambique using climatic indicators from 2001 to 2018. Scientific Reports. 2025;15:11971. doi: 10.1038/s41598-025- 97072-6
Singh MP, Rajvanshi H, Bharti PK, Anvikar AR, Lal AA. Time series analysis of malaria cases to assess the impact of various interventions over the last three decades and forecast malaria in India towards the 2030 elimination goals. Malaria Journal. 2024;23:50. doi: 10.1186/s12936-024-04872-8
Cleveland RB, Cleveland WS, McRae JE, Terpenning I. STL: A seasonal-trend decomposition procedure based on Loess. Journal of Official Statistics. 1990;6(1):3–73.
Dickey DA, Fuller WA. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association. 1979;74(366a):427–431. doi: 10.2307/2286348
Kwiatkowski D, Phillips PCB, Schmidt P, Shin Y. Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics. 1992;54(1– 3): 59–178. doi: 10.1016/0304-4076(92)90104-Y
Bai J, Perron P. Computation and analysis of multiple structural change models. Journal of Applied Econometrics. 2003;18(1):1–22. doi: 10.1002/jae.659
Brown MB, Forsythe AB. Robust tests for the equality of variances. Journal of the American Statistical Association. 1974;69(346):364–367. doi: 10.1080/01621459.1974.10482955
Engle RF. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica. 1982;50(4):987–1007. doi: 10.2307/1912773
Downloads
Published
Issue
Section
License
Copyright (c) 2026 The Transactions of the Nigerian Association of Mathematical Physics
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
