Chikobvu Delson, Chideme Coster
Department of Mathematical Statistics and Actuarial Sciences University of the Free State Bloemfontein South Africa.
Health Sci Rep. 2022 Oct 7;5(6):e867. doi: 10.1002/hsr2.867. eCollection 2022 Nov.
Blood service agencies depend upon the availability of regular blood donors for sustainability. The knowledge and understanding of the stochastic behavior of donors is the first step toward sustaining the blood supply. Analyzing the changes in the donor status within the donor pool will help the blood service authorities to manage the blood donation process.
The study presents a multistate Markov jump model in analyzing the changes in blood donor status during their blood donation career. Relevant covariates are used to aid in explaining the transitions.
The status of a blood donor that can be in one of four states = {1; 2; 3; 4}. A new donor ( = 1), repeat/regular donor ( = 2), occasional donor ( = 3), and lapsed donor ( = 4). A Continuous-time Markov model was used to estimate blood donor progression during their blood donation career. Frequencies of blood donations made in a given time interval determines the state occupied.
In the early years of blood donation career, first-time donors have a higher likelihood of becoming regular donors. Donor attrition increases with time whilst donor retention decreases with time. The results show that when the jump process is currently in an occasional state, the probability that it moves into lapsed state when it leaves the occasional state is given as 69.06%. Similarly, donors are forecasted to spend 21.193 months (1.8 years) in the occasional state before lapsing. Repeat donors can spend 39.342 months (3.3 years) in the regular state before the transition to other states. The study established that donor-specific demographic factors such as age and gender are critical in donor status transitions.
With the passage of time, donor status evolves, with trend inclined towards reduction in the frequency of blood donations as more donors become inactive or lapsed. The transition of donors in various states can be described by a time homogeneous Markov model.
血液服务机构的可持续发展依赖于定期献血者的可获得性。了解和认识献血者的随机行为是维持血液供应的第一步。分析献血者库中献血者状态的变化将有助于血液服务机构管理献血过程。
本研究提出了一个多状态马尔可夫跳跃模型，用于分析献血者在其献血生涯中献血者状态的变化。使用相关协变量来辅助解释状态转换。
献血者的状态可处于四种状态之一={1；2；3；4}。新献血者（=1）、重复/定期献血者（=2）、偶尔献血者（=3）和流失献血者（=4）。使用连续时间马尔可夫模型来估计献血者在其献血生涯中的进展。在给定时间间隔内的献血频率决定了所处的状态。
在献血生涯的早期，首次献血者成为定期献血者的可能性更高。献血者流失率随时间增加而献血者留存率随时间降低。结果表明，当跳跃过程当前处于偶尔献血状态时，其离开偶尔献血状态时进入流失状态的概率为69.06%。同样，预计献血者在进入流失状态之前在偶尔献血状态下会花费21.193个月（1.8年）。重复献血者在转换到其他状态之前可以在定期献血状态下花费39.342个月（3.3年）。该研究确定，献血者特定的人口统计学因素，如年龄和性别，在献血者状态转换中至关重要。
随着时间的推移，献血者状态会发生变化，趋势是随着越来越多的献血者变得不活跃或流失，献血频率降低。不同状态下献血者的转换可以用一个时间齐次马尔可夫模型来描述。
