{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:49:43Z","timestamp":1753883383567,"version":"3.41.2"},"reference-count":43,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["MDM Policy &amp; Practice"],"published-print":{"date-parts":[[2024,1]]},"abstract":"<jats:p> Background. Blood cannot be artificially manufactured, and there is currently no substitute for human blood. The supply of blood in transfusion facilities requires constant and timely collection of blood from donors. Modeling and forecasting trends in blood collections are critical for determining both the current and future capacity requirements and appropriate models of adequate blood provision. Objectives. The objective of this study is to determine blood collection or donation patterns and develop time-series models that can be updated and refined in predicting future blood donations in Zimbabwe when given the historical data. Materials and Methods. Monthly blood donation data for the period 2009 to 2019 were collected retrospectively from the National Blood Service Zimbabwe database. Time-series models (i.e., the Seasonal Autoregressive Integrated Moving Average [SARIMA] and Error, Trend and Seasonal [ETS]) models were applied and compared. The models were chosen because of their ability to handle the seasonality and other time-series components evident in the blood donation data. Expert opinions and experience were used in selecting the models and in making inferences in the analysis. Results. Time-series plots of blood donations showed seasonal patterns, with significant drops in blood donations in months associated with Zimbabwe\u2019s school holidays (April, August, and December) and public holidays. During these holidays, there is a reduced number of school donors, while at about the same time, there is increasing blood demand as a result of road accidents. Model identification procedures established the [Formula: see text] model as the appropriate model for forecasting total blood donation in Zimbabwe. The results and forecasts show an upward trend in blood donations. According to the accuracy measures used, the SARIMA model outperforms the ETS model. Conclusions. Expert knowledge in the blood donation process, coupled with statistical models, can help explain trends exhibited in blood donation data in Zimbabwe. These findings help the blood authorities plan for blood donor campaign drives. The findings are key indicators of where to allocate more resources toward blood donation and when to collect more blood units. The increasing blood donation projections ensure a stable blood bank inventory in the near future. <\/jats:p><jats:sec><jats:title>Highlights<\/jats:title><jats:p> A SARIMA model can be used to predict the flow of blood donations in Zimbabwe. The seasonal blood donation pattern peaks in the months of March, June\/July, and September. The donations troughs are in the months of April, August, December, and January. These are the months coinciding with school holidays in Zimbabwe. Both the SARIMA and ETS models provided similar forecasts, but measures of fit and expert knowledge gave a slight preference to the [Formula: see text] model in predicting the flow of blood donations in Zimbabwe. These model results are useful for guiding allocation of blood donation resources and blood donation drive timing. <\/jats:p><\/jats:sec>","DOI":"10.1177\/23814683231222483","type":"journal-article","created":{"date-parts":[[2024,1,19]],"date-time":"2024-01-19T06:31:56Z","timestamp":1705645916000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Application of Time-Series Analysis and Expert Judgment in Modeling and Forecasting Blood Donation Trends in Zimbabwe"],"prefix":"10.1177","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0624-9136","authenticated-orcid":false,"given":"Coster","family":"Chideme","sequence":"first","affiliation":[{"name":"Department of Mathematical Statistics and Actuarial Sciences, University of the Free State, Bloemfontein, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Delson","family":"Chikobvu","sequence":"additional","affiliation":[{"name":"Department of Mathematical Statistics and Actuarial Sciences, University of the Free State, Bloemfontein, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2024,1,18]]},"reference":[{"volume-title":"Recommendations for Estimating the Need for Blood and Blood Components","year":"2010","author":"Pan American Health Organization","key":"bibr1-23814683231222483"},{"key":"bibr2-23814683231222483","unstructured":"World Health Organization. Towards 100% voluntary blood donation: a global framework for action. Way of comparing the amount of blood available in different countries. 2010. Available from: https:\/\/www.ncbi.nlm.nih.gov\/books\/NBK305667\/pdf\/Bookshelf_NBK305667.pdf"},{"volume-title":"Global Status Report on Blood Safety and Availability 2016","year":"2017","author":"World Health Organization","key":"bibr3-23814683231222483"},{"key":"bibr4-23814683231222483","doi-asserted-by":"publisher","DOI":"10.1111\/j.1751-2824.2012."},{"key":"bibr5-23814683231222483","volume":"323","author":"Bahel D","year":"2017","journal-title":"Comput Sci"},{"key":"bibr6-23814683231222483","doi-asserted-by":"publisher","DOI":"10.1186\/s13104-017-2618-5"},{"key":"bibr7-23814683231222483","doi-asserted-by":"publisher","DOI":"10.2450\/2014.0101-14"},{"key":"bibr8-23814683231222483","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1714097114"},{"key":"bibr9-23814683231222483","unstructured":"Tapko JB, Mainuka P, Diarra-Nama AJ. Status of blood safety in the WHO African region: report of the 2010 survey. 2014. Available from: https:\/\/who.insomnation.com\/sites\/default\/files\/pdf\/status-of-blood-safety-in-the-who-african-region.pdf [Accessed 11 May, 2019]."},{"key":"bibr10-23814683231222483","doi-asserted-by":"publisher","DOI":"10.4103\/njcp.njcp_346_17"},{"key":"bibr11-23814683231222483","unstructured":"Mawere T. Crisis as national blood service is hit by blood shortage ahead of Christmas. ZimEye. December 16, 2015. 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