{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T17:39:48Z","timestamp":1791999588214,"version":"4.4.0"},"reference-count":83,"publisher":"Public Library of Science (PLoS)","issue":"8","license":[{"start":{"date-parts":[[2025,8,6]],"date-time":"2025-08-06T00:00:00Z","timestamp":1754438400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000865","name":"Bill and Melinda Gates Foundation","doi-asserted-by":"publisher","award":["INV-047051"],"award-info":[{"award-number":["INV-047051"]}],"id":[{"id":"10.13039\/100000865","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:p>Malaria in pregnancy (MIP) remains a global health challenge, affecting approximately 40% of pregnant women. Despite malaria control efforts by the Nigerian Government and its partners, regional disparities in health outcomes and malaria incidence trends among pregnant women remain under-studied. This study objectives were to assess MIP variability compared to general malaria cases, and forecast short-term MIP incidence over two years. This was achieved by analyzing malaria in pregnancy (MIP) variability across Nigeria from January 2015 to January 2025, using wavelet coherence, patterns of transmission cycles and selecting best modelling approach by comparing ARIMA and SARIMAX models to assess temporal trends before the forecast of short-term MIP incidence. Findings showed significant regional variability, with Cross River peaking in 2017 and 2019, while Enugu recorded its lowest trough in 2017. Malaria peaks in southern states remained lower than troughs in northern regions. Strong cross-correlations between MIP and general malaria transmission cycles were observed in Kebbi, Niger, Yobe, and Ondo, indicating persistent trends, while South-South and South-East exhibited weaker correlations, likely due to intervention fluctuations. SARIMAX models captured MIP trends more effectively, except Kebbi, where ARIMA fit better, and Niger, where SARIMAX exaggerated forecasts due to sensitivity to exogenous variables. Thus, SARIMAX was adopted for Cross River, Enugu, Ondo, and Yobe; while ARIMA was used for Kebbi and Niger States. It was discovered that Cross River and Enugu exhibited intervention-driven malaria fluctuations, Ondo, Niger, and Yobe displayed unstable or cyclical trends, reinforcing the importance of climate-sensitive forecasting models and seasonal interventions for improving malaria prediction accuracy. South-South and South-East need improved healthcare access, North-Central and North-West require seasonality forecasting, while North-East demands urgent control measures. Targeted malaria interventions are crucial to support achievement of the Nigeria\u2019s National Malaria Elimination Programme (NMEP) goals.<\/jats:p>","DOI":"10.1371\/journal.pone.0328888","type":"journal-article","created":{"date-parts":[[2025,8,6]],"date-time":"2025-08-06T17:40:05Z","timestamp":1754502005000},"page":"e0328888","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":7,"title":["Time series analysis of malaria in pregnancy, using wavelet and SARIMAX models"],"prefix":"10.1371","volume":"20","author":[{"given":"Dolapo Oluwaseun","family":"Oniyelu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olaiya","family":"Folorunsho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lawrence","family":"Adewole","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7257-421X","authenticated-orcid":true,"given":"Emmanuel Afolabi","family":"Bakare","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chukwu","family":"Okoronkwo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nelson","family":"Eze","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"with ICAMMDA Team","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,8,6]]},"reference":[{"key":"pone.0328888.ref001","doi-asserted-by":"crossref","DOI":"10.18332\/popmed\/164040","article-title":"Malaria endemicity in sub-Saharan Africa: Past and present issues in public health","volume":"5","author":"K Eniola","year":"2023","journal-title":"Popul Med."},{"issue":"1","key":"pone.0328888.ref002","doi-asserted-by":"crossref","first-page":"1940639","DOI":"10.1080\/2331205X.2021.1940639","article-title":"Malaria interventions and control programes in Sub-Saharan Africa: a narrative review","volume":"8","author":"AB Orok","year":"2021","journal-title":"Cogent Med."},{"key":"pone.0328888.ref003","doi-asserted-by":"crossref","first-page":"3219","DOI":"10.2147\/IDR.S312519","article-title":"Prevalence, parasite density and determinants of falciparum malaria among febrile children in some Peri-Urban communities in southwestern nigeria: a cross-sectional study","volume":"14","author":"OB Awosolu","year":"2021","journal-title":"IDR."},{"issue":"1","key":"pone.0328888.ref004","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/S0035-9203(03)90012-5","article-title":"Importance and prevention of malaria in pregnancy","volume":"97","author":"CE Shulman","year":"2003","journal-title":"Trans Roy Soc Tropic Med Hygiene."},{"key":"pone.0328888.ref005","volume-title":"WHO policy brief for the implementation of intermittent preventive treatment of malaria in pregnancy using sulfadoxine-pyrimethamine (IPTp-SP)","author":"World Health Organization","year":"2014"},{"issue":"4","key":"pone.0328888.ref006","article-title":"Community delivery of IPTp: coverage in four sub-Saharan countries","volume":"11","author":"R Gonz\u00e1lez","year":"2023","journal-title":"Lancet Glob Health."},{"key":"pone.0328888.ref007","unstructured":"National Malaria Elimination Programme (NMEP), National Population Commission (NPC), ICF. Nigeria Malaria Indicator Survey 2021: Final Report. Abuja, Nigeria, and Rockville, Maryland, USA: NMEP, NPC, and ICF; 2022."},{"key":"pone.0328888.ref008","volume-title":"World Malaria Report 2018","author":"World Health Organization","year":"2019"},{"key":"pone.0328888.ref009","volume-title":"Report on Malaria in Nigeria 2022","author":"World Health Organization","year":"2023"},{"key":"pone.0328888.ref010","unstructured":"National Malaria Elimination Programme, National Population Commission, National Bureau of Statistics, ICFI. Nigeria Malaria Indicator Survey 2015 : Final Report. Abuja, Nigeria: National Malaria Elimination Programme; 2016. https:\/\/dhsprogram.com\/publications\/"},{"key":"pone.0328888.ref011","unstructured":"National Malaria Elimination Programme (NMEP). National Malaria Strategic Plan 2021\u20132025. Abuja, Nigeria: Federal Ministry of Health, Nigeria; 2021. https:\/\/nmcp.gov.ng\/"},{"issue":"3","key":"pone.0328888.ref012","first-page":"95","article-title":"Replacement campaign of LLINs in Ondo State, Nigeria","volume":"15","author":"W Adegbenro","year":"2018","journal-title":"Divers Equal Health Care."},{"key":"pone.0328888.ref013","unstructured":"National Federal Ministry of Health. Adoption of Intermittent Preventive Treatment in Pregnancy (IPTp). 2005."},{"issue":"1","key":"pone.0328888.ref014","first-page":"2325304","article-title":"Revised IPTp-SP effectiveness in Northern Ghana","volume":"2020","author":"YN Agyeman","year":"2020","journal-title":"J Trop Med."},{"key":"pone.0328888.ref015","first-page":"1","article-title":"IPTp uptake and outcomes in Geita district, Tanzania","volume":"13","author":"FJ Mpogoro","year":"2014","journal-title":"Malaria J."},{"issue":"9","key":"pone.0328888.ref016","article-title":"IPTp-SP and sub-microscopic malaria in Cameroon","volume":"17","author":"TO Apinjoh","year":"2022","journal-title":"PLoS One."},{"key":"pone.0328888.ref017","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1475-2875-10-227","article-title":"Community-directed interventions to prevent malaria in pregnancy: Akwa Ibom case study","volume":"10","author":"JC Okeibunor","year":"2011","journal-title":"Malaria J."},{"issue":"1","key":"pone.0328888.ref018","first-page":"6402947","article-title":"Malaria prevention survey among pregnant women in Nnewi, Nigeria","volume":"2019","author":"D Bhalla","year":"2019","journal-title":"Sci World J."},{"issue":"4","key":"pone.0328888.ref019","doi-asserted-by":"crossref","first-page":"1359","DOI":"10.4103\/jfmpc.jfmpc_295_18","article-title":"Knowledge, perception, and prevention of malaria in pregnancy in Nigeria","volume":"8","author":"IP Okafor","year":"2019","journal-title":"J Fam Med Prim Care."},{"key":"pone.0328888.ref020","first-page":"1","article-title":"Malaria prevention and delivery outcomes in Northeastern Nigeria","volume":"15","author":"HU Muhammad","year":"2016","journal-title":"Malaria J."},{"key":"pone.0328888.ref021","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12936-021-03586-5","article-title":"Health education to improve malaria preventive practices and pregnancy outcomes","volume":"20","author":"AD Balami","year":"2021","journal-title":"Malaria J."},{"issue":"1","key":"pone.0328888.ref022","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1186\/s12916-020-01559-0","article-title":"A systematic review of changing malaria disease burden in sub-Saharan Africa since 2000 : comparing model predictions and empirical observations","volume":"18","author":"A Kamau","year":"2020","journal-title":"BMC Med."},{"issue":"5","key":"pone.0328888.ref023","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1053\/j.semperi.2019.03.018","article-title":"An overview of malaria in pregnancy","volume":"43","author":"M Bauserman","year":"2019","journal-title":"Semin Perinatol."},{"issue":"1","key":"pone.0328888.ref024","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12936-015-1044-1","article-title":"Spatially variable risk factors for malaria in a geographically heterogeneous landscape, Western Kenya: an explorative study","volume":"15","author":"T Homan","year":"2016","journal-title":"Malar J."},{"key":"pone.0328888.ref025","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1007\/978-1-4939-2782-1_9","volume-title":"Applications of dynamical systems in biology and medicine","author":"MI Teboh-Ewungkem","year":"2015"},{"issue":"3","key":"pone.0328888.ref026","doi-asserted-by":"crossref","first-page":"44","DOI":"10.12691\/ajeid-12-3-3","article-title":"Geospatial and path analysis for enhancing Malaria control and primary healthcare delivery in low-income nations: a case study of Uganda","volume":"12","author":"M Assumpta Komugabe","year":"2024","journal-title":"AJEID."},{"issue":"1","key":"pone.0328888.ref027","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2379776.2379788","article-title":"Time-series data mining","volume":"45","author":"P Esling","year":"2012","journal-title":"ACM Comput Surv."},{"key":"pone.0328888.ref028","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1007\/s10618-007-0077-7","article-title":"Data mining with temporal abstractions: learning rules from time series","volume":"15","author":"L Sacchi","year":"2007","journal-title":"Data Min Knowl Discov."},{"key":"pone.0328888.ref029","doi-asserted-by":"crossref","first-page":"91896","DOI":"10.1109\/ACCESS.2021.3091162","article-title":"Forecast methods for time series data: a survey","volume":"9","author":"Z Liu","year":"2021","journal-title":"IEEE Access."},{"key":"pone.0328888.ref030","doi-asserted-by":"crossref","unstructured":"Huang HS, Liu CL, Tseng VS. Multivariate time series early classification using multi-domain deep neural network. In: 2018 IEEE International Conference on Data Science and Advanced Analytics (DSAA). 2018. p. 90\u20138.","DOI":"10.1109\/DSAA.2018.00019"},{"key":"pone.0328888.ref031","first-page":"280","volume-title":"Interest rate models... sovereign wealth funds","author":"H Steehouwer","year":"2010"},{"key":"pone.0328888.ref032","first-page":"3","article-title":"Impact of non-pharmacological initiatives for COVID-19 on pediatric respiratory illness admissions","volume":"39","author":"S Chiapinotto","year":"2021","journal-title":"Paediatr Respir Rev."},{"issue":"4","key":"pone.0328888.ref033","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1080\/13658816.2019.1684500","article-title":"GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond","volume":"34","author":"K Janowicz","year":"2019","journal-title":"Int J Geograph Inf Sci."},{"key":"pone.0328888.ref034","doi-asserted-by":"crossref","unstructured":"Kohli PS, Arora S. Application of machine learning in disease prediction. In: 2018 International Conference on Computing, Communication and Automation (ICCCA), 2018. p. 1\u20134.","DOI":"10.1109\/CCAA.2018.8777449"},{"key":"pone.0328888.ref035","article-title":"Machine learning in clinical decision-making","author":"TJ Loftus","year":"2023","journal-title":"Frontiers Media SA."},{"issue":"12","key":"pone.0328888.ref036","doi-asserted-by":"crossref","first-page":"1300","DOI":"10.1080\/10106049.2018.1478890","article-title":"Understanding spatial variations of malaria in Vietnam using remotely sensed data integrated into GIS and machine learning classifiers","volume":"34","author":"Q-T Bui","year":"2018","journal-title":"Geocarto Int."},{"issue":"2","key":"pone.0328888.ref037","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1109\/MGRS.2019.2912563","article-title":"Deep learning for classification of hyperspectral data: a comparative review","volume":"7","author":"N Audebert","year":"2019","journal-title":"IEEE Geosci Remote Sens Mag."},{"issue":"4","key":"pone.0328888.ref038","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1080\/19475683.2018.1534890","article-title":"Spatial prediction based on third law of geography","volume":"24","author":"AX Zhu","year":"2018","journal-title":"Ann GIS."},{"issue":"8","key":"pone.0328888.ref039","doi-asserted-by":"crossref","first-page":"3681","DOI":"10.1109\/TKDE.2020.3025580","article-title":"Deep learning for spatio-temporal data mining: a survey","volume":"34","author":"S Wang","year":"2022","journal-title":"IEEE Trans Knowl Data Eng."},{"issue":"7","key":"pone.0328888.ref040","doi-asserted-by":"crossref","first-page":"2891","DOI":"10.1109\/TCYB.2020.2990162","article-title":"Predicting COVID-19 in China using hybrid AI model","volume":"50","author":"N Zheng","year":"2020","journal-title":"IEEE Trans Cybern."},{"issue":"8","key":"pone.0328888.ref041","doi-asserted-by":"crossref","first-page":"1596","DOI":"10.3390\/ijerph15081596","article-title":"Predicting infectious disease using deep learning and big data","volume":"15","author":"S Chae","year":"2018","journal-title":"IJERPH."},{"key":"pone.0328888.ref042","article-title":"Forecasting COVID-19 dynamics in top 15 countries using ARIMA ML","author":"P Kumar","year":"2020","journal-title":"MedRxiv."},{"issue":"3","key":"pone.0328888.ref043","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0230405","article-title":"Modelling and forecasting the COVID-19 outbreak","volume":"15","author":"C Anastassopoulou","year":"2020","journal-title":"PLoS One."},{"key":"pone.0328888.ref044","doi-asserted-by":"crossref","unstructured":"Gupta A, Kumar A. Mid term daily load forecasting using ARIMA, wavelet-ARIMA, machine learning. In: 2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC\/I&CPS Europe). 2020. p. 1\u20135. https:\/\/doi.org\/10.1109\/eeeic\/icpseurope49358.2020.9160563","DOI":"10.1109\/EEEIC\/ICPSEurope49358.2020.9160563"},{"issue":"4","key":"pone.0328888.ref045","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.1111\/rssb.12377","article-title":"Visualizing predictor variable effects in black box models","volume":"82","author":"DW Apley","year":"2020","journal-title":"J R Stat Soc Ser B."},{"issue":"6","key":"pone.0328888.ref046","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1016\/j.tig.2020.03.005","article-title":"Interpretable machine learning for geneticists","volume":"36","author":"CB Azodi","year":"2020","journal-title":"Trends in Genetics."},{"key":"pone.0328888.ref047","doi-asserted-by":"crossref","first-page":"1847979018808673","DOI":"10.1177\/1847979018808673","article-title":"Forecasting of demand using ARIMA model","volume":"10","author":"J Fattah","year":"2018","journal-title":"Int J Eng Bus Manag."},{"issue":"1","key":"pone.0328888.ref048","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.dsp.2010.09.001","article-title":"Optimization approach to adapt Kalman filters for... accelerometer and gyroscope signals\u2019 filtering","volume":"21","author":"C Kownacki","year":"2011","journal-title":"Digit Signal Process."},{"key":"pone.0328888.ref049","doi-asserted-by":"crossref","unstructured":"Akujuobi CM. Wavelets and wavelet transform systems and their applications. Berlin\/Heidelberg, Germany: Springer; 2022.","DOI":"10.1007\/978-3-030-87528-2"},{"issue":"6","key":"pone.0328888.ref050","first-page":"56","article-title":"Univariate and vector autocorrelation time series models for some sectors in Nigeria","volume":"20","author":"GD Amadi","year":"2020","journal-title":"Glob J Sci Front Res: Math Decis Sci."},{"issue":"6","key":"pone.0328888.ref051","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0303890","article-title":"Anomaly detection in multivariate time series data using deep ensemble models","volume":"19","author":"A Iqbal","year":"2024","journal-title":"PLoS ONE."},{"issue":"4","key":"pone.0328888.ref052","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0297391","article-title":"Demand forecasting for platelet usage: from univariate time series to multivariable models","volume":"19","author":"M Motamedi","year":"2024","journal-title":"PLoS ONE."},{"key":"pone.0328888.ref053","unstructured":"Hyndman RJ, Athanasopoulos G. Forecasting: principles and practice. OTexts; 2018."},{"key":"pone.0328888.ref054","volume-title":"The spectral analysis of time series","author":"LH Koopmans","year":"1995"},{"issue":"9","key":"pone.0328888.ref055","article-title":"CL-Informer: Long time series prediction model based on continuous wavelet transform","volume":"19","author":"B Liu","year":"2024","journal-title":"PLoS ONE."},{"key":"pone.0328888.ref056","doi-asserted-by":"crossref","first-page":"58869","DOI":"10.1109\/ACCESS.2022.3179517","article-title":"A review of wavelet analysis and its applications: challenges and opportunities","volume":"10","author":"T Guo","year":"2022","journal-title":"IEEE Access."},{"issue":"1","key":"pone.0328888.ref057","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0146790","article-title":"Birdsong denoising using wavelets","volume":"11","author":"N Priyadarshani","year":"2016","journal-title":"PLoS ONE."},{"issue":"7","key":"pone.0328888.ref058","article-title":"Weibo sentiments and stock return: a time-frequency view","volume":"12","author":"Y Xu","year":"2017","journal-title":"PLoS ONE."},{"key":"pone.0328888.ref059","first-page":"1","article-title":"Simultaneous denoising and heterogeneity learning for time series data","author":"X Jiang","year":"2023","journal-title":"Stat Biosci."},{"key":"pone.0328888.ref060","first-page":"109866","article-title":"Hybrid wavelet ARIMA model for forecasting COVID-19 casualties","volume":"135","author":"S Singh","year":"2020","journal-title":"Chaos Solitons Fractals."},{"key":"pone.0328888.ref061","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1007\/s40822-023-00243-x","article-title":"Forecasting volatility by using wavelet transform, ARIMA and GARCH models","volume":"13","author":"L Rubio","year":"2023","journal-title":"Eurasian Econ Rev."},{"issue":"4","key":"pone.0328888.ref062","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0282621","article-title":"Using discrete wavelet transform for optimizing COVID-19 new cases and deaths prediction worldwide with deep neural networks","volume":"18","author":"EG Sperandio Nascimento","year":"2023","journal-title":"PLoS ONE."},{"key":"pone.0328888.ref063","first-page":"2024","article-title":"Statistical analysis of COVID-19 trends: ARIMA, regression, and spatial models","volume":"2024","author":"Z Lei","year":"2024","journal-title":"medRxiv."},{"issue":"1","key":"pone.0328888.ref064","doi-asserted-by":"crossref","first-page":"2356342","DOI":"10.1080\/21645515.2024.2356342","article-title":"Childhood vaccination trends during 2019 to 2022 in Tanzania and the impact of the COVID-19 pandemic","volume":"20","author":"RZ Sangeda","year":"2024","journal-title":"Human Vaccines Immunotherap."},{"key":"pone.0328888.ref065","unstructured":"National Malaria Data Repository. National Malaria Data Repository - Contact us@ nmdrhelpdesk@nmep.gov.ng [cited in 2025 May 22]. https:\/\/nmdrnigeria.ng\/dhis-web-commons\/security\/login.action"},{"key":"pone.0328888.ref066","unstructured":"GADM. GADM Maps, Data and Version X. [cited 2024 ]. https:\/\/gadm.org"},{"issue":"3","key":"pone.0328888.ref067","doi-asserted-by":"crossref","first-page":"100979","DOI":"10.1016\/j.gendis.2023.04.018","article-title":"Pretreating and normalizing metabolomics data for statistical analysis","volume":"11","author":"J Sun","year":"2024","journal-title":"Genes Dis."},{"issue":"2","key":"pone.0328888.ref068","first-page":"106","article-title":"Inflation study using unit root tests: Bukittinggi City 2014 \u20132019","volume":"23","author":"A Roza","year":"2022","journal-title":"EKSAKTA."},{"key":"pone.0328888.ref069","doi-asserted-by":"crossref","first-page":"101625","DOI":"10.1016\/j.frl.2020.101625","article-title":"Co-movement of COVID-19 and Bitcoin: evidence from wavelet coherence analysis","volume":"38","author":"JW Goodell","year":"2021","journal-title":"Finance Res Lett."},{"issue":"1","key":"pone.0328888.ref070","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/j.eneco.2011.10.007","article-title":"Co-movement of energy commodities revisited: evidence from wavelet coherence analysis","volume":"34","author":"L Vacha","year":"2012","journal-title":"Energy Econ."},{"issue":"7","key":"pone.0328888.ref071","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.3390\/app9071345","article-title":"Wavelet transform application for\/in non-stationary time-series analysis: a review","volume":"9","author":"M Rhif","year":"2019","journal-title":"Appl Sci."},{"key":"pone.0328888.ref072","doi-asserted-by":"crossref","unstructured":"Sundararajan D. Fourier analysis\u2014a signal processing approach. Singapore: Springer; 2018.","DOI":"10.1007\/978-981-13-1693-7"},{"key":"pone.0328888.ref073","doi-asserted-by":"crossref","unstructured":"Gomes J, Velho L. From Fourier analysis to wavelets. New York: Springer; 2015.","DOI":"10.1007\/978-3-319-22075-8"},{"issue":"2","key":"pone.0328888.ref074","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.matcom.2004.10.005","article-title":"Numerical solution of differential equations using Haar wavelets","volume":"68","author":"U Lepik","year":"2005","journal-title":"Math Comput Simul."},{"key":"pone.0328888.ref075","first-page":"0972150920988653","article-title":"An application of ARIMA model to forecast the dynamics of COVID-19 epidemic in India","author":"R Katoch","year":"2021","journal-title":"Glob Bus Rev."},{"key":"pone.0328888.ref076","doi-asserted-by":"crossref","first-page":"688969","DOI":"10.3389\/fdata.2021.688969","article-title":"Principles and practice of explainable machine learning","volume":"4","author":"V Belle","year":"2021","journal-title":"Front Big Data."},{"issue":"4","key":"pone.0328888.ref077","first-page":"18","article-title":"Sentiment analysis of Twitter discourse on the 2023 Nigerian general elections","volume":"12","author":"K Attai","year":"2024","journal-title":"Eur J Comput Sci Inf Technol."},{"issue":"11","key":"pone.0328888.ref078","doi-asserted-by":"crossref","first-page":"1487","DOI":"10.3390\/ijerph21111487","article-title":"Impact of climate variability and interventions on Malaria incidence and forecasting in Burkina Faso","volume":"21","author":"N Traor\u00e9","year":"2024","journal-title":"IJERPH."},{"issue":"1631","key":"pone.0328888.ref079","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1098\/rspb.2007.1068","article-title":"Shifting patterns: malaria dynamics and rainfall variability in an African highland","volume":"275","author":"M Pascual","year":"2007","journal-title":"Proc R Soc B."},{"key":"pone.0328888.ref080","unstructured":"Rehal V. Heteroscedasticity: causes and Consequences. [cited 2025 May 22]. https:\/\/spureconomics.com\/heteroscedasticity-causes-and-consequences\/"},{"issue":"1","key":"pone.0328888.ref081","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pmed.1000221","article-title":"Quantifying the number of pregnancies at risk of Malaria in 2007 : a demographic study","volume":"7","author":"S Dellicour","year":"2010","journal-title":"PLoS Med."},{"key":"pone.0328888.ref082","unstructured":"Abdulkadir AA. Predicting malaria incidence in Kenya using ARIMA and SARIMA models. Strathmore University Research Repository; 2020. https:\/\/su-plus.strathmore.edu\/server\/api\/core\/bitstreams\/0d99d4f2-f1bc-40ac-bd86-9a7d696cdb71\/content"},{"issue":"1","key":"pone.0328888.ref083","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1175\/1520-0477(1998)079<0061:APGTWA>2.0.CO;2","article-title":"A practical guide to wavelet analysis","volume":"79","author":"C Torrence","year":"1998","journal-title":"Bull Am Meteorol Soc."}],"container-title":["PLOS One"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0328888","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,6]],"date-time":"2025-08-06T17:40:21Z","timestamp":1754502021000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0328888"}},"subtitle":[],"editor":[{"given":"Clement","family":"Ameh Yaro","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2025,8,6]]},"references-count":83,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2025,8,6]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0328888","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,6]]}}}