Background: Blood donors’ behaviour towards blood donation is not easily predictable and can be considered to be a stochastic random variable. A four-state Markov chain technique was defined and adopted in this study. The transition probabilities of blood donation within the four identified states, viz: new, regular, occasional, and lapsed donor were used to make further inferences of the dynamics in blood donation in Harare, Zimbabwe. Objectives: The paper presents a four-state Discrete Time Markov Chain (DTMC) model in analysing the changes in blood donation status over the four-year study period. Methodology: A transition probabilities matrix was developed and parameters estimated using the maximum likelihood method and two other approaches, and inferences were made based on the resultant transition matrix. Results: About 56% of new donors made at least one repeat donation and become regular donors within the first year, and the numbers gradually declined with time, whilst the lapsed donors increased from 35.6% in second year to 55.6% in year 4. The long run probabilities tell the same, with 80.9% of blood donations becoming lapsed in the long run. Depending on the current state of donation, new or regular donations are likely to move to the regular donation state in the following time step (year). On the other end, occasional and lapsed donations have a higher probability of entering the lapsed donation state in the following time step (year). Conclusion: The paper provides useful insights on the Markovian transition probabilities among the blood donation states, and this has implications on future blood donors’ pool and blood bank inventory in Zimbabwe. The decline in numbers of donors who make repeat donations is a worrisome trend, since regular donations are the lifeline of any blood service centres.

Background: 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.Objectives: 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. Materials and Methods:The status of a blood donor i that can be in one of four states S = {1; 2; 3; 4}. A new donor (s = 1), repeat/regular donor (s = 2), occasional donor (s = 3), and lapsed donor (s = 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.Results: 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.Conclusions: 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.