Blood donors as a sentinel population for real-time malaria surveillance using the Sysmex XN-31: a one-year review from the National Blood Transfusion Centre in Burkina Faso

Abstract

Background: The World Health Organization malaria burden estimates produced from incomplete clinical case reporting and often outdated household asymptomatic parasitaemia surveys in children < 5 years old, are unreliable. Surveillance target groups need to be expanded in line with the epidemiological shift in malaria-eliminating countries towards adults, and particularly men. Furthermore, new tools that can provide granular and timely data, critical to understanding geographic heterogeneity and enabling timely decision-making at the operational level, are needed. This prospective study aimed to demonstrate that blood donor malaria screening could serve as a time-sensitive complementary source of highly detailed malaria surveillance data.

Methods: Consecutive blood donations received from 16 August 2023 to 31 August 2024 at the Ouagadougou and Bobo-Dioulasso Regional Blood Transfusion Centres in Burkina Faso, covering 5 of 13 regions, were screened for malaria using the Sysmex XN-31 automated analyser. XN-31 results, donor age, sex, place of residence, collection date, were analysed using descriptive statistics, chi-squared, and logistic regression tests. Seasonal malaria patterns were compared with publicly available rainfall data.

Results: Donor malaria prevalence was 5.91% (3164/53575) overall. Key predictors of malaria identified were age ≤ 30 years (odds ratio (OR) 2.85, p < 0.001), male sex (OR 1.47, p < 0.001) and rural residency (OR 2.40, p < 0.001), with regional location having a strong influence on the latter. Strong seasonal variability, mirroring that of rainfall with a 3-month lag, was observed with different peak periods and rate of change over time at provincial level. Hot-spots were observed within both Bobo-Dioulasso and Ouagadougou. There were no age or sex-based differences in parasite density or gametocyte carriage, and both measures were directly proportional to malaria prevalence. Only males showed striking seasonal variability in gametocyte carriage (low season 1.39%, 14/1006; high season 4.42%, 66/1494; p < 0.001).

Conclusions: The large data set and spatiotemporal malaria prevalence information, not possible with episodic household malaria surveys, facilitated highly granular analysis and demonstrated the potential to provide dynamic real-time information on the malaria burden using automated XN-31 blood donor malaria screening.

Keywords: Asymptomatic blood donors; Automated malaria detection; Burkina Faso; Malaria surveillance; XN-31.

Fig. 1

Catchment area of Bobo-Dioulasso and Ouagadougou regional blood transfusion services

Fig. 2

Asymptomatic malaria prevalence in blood donors by age and sex. The error bars represent the 95% confidence interval of donor malaria prevalence

Fig. 3

Donor malaria parasite positivity by region. The error bars represent the 95% confidence interval of donor malaria prevalence

Fig. 4

Map of Ouagadougou showing the sector boundaries and the malaria prevalence of the West, East and Central regions of the city

Fig. 5

Donor malaria parasite prevalence and rainfall by month. The error bars represent the 95% confidence interval of donor malaria prevalence

Fig. 6

Asymptomatic malaria prevalence in male and female donors over time. The error bars represent the 95% confidence interval of donor malaria prevalence

Fig. 7

Donor asymptomatic malaria prevalence trends and rainfall over time for Centre and Hauts-Bassins regions. a Malaria prevalence and rainfall for Centre region (Ouagadougou weather station identifier 65,503). b Malaria prevalence and rainfall for Hauts-Bassins region (Bobo-Dioulasso weather station identifier 65,510). As there were only 6 samples, the July 24 data point for Hauts-Bassins was omitted

Fig. 8

Asymptomatic malaria prevalence of donors residing in provinces within the catchment areas of Bobo-Dioulasso and Ouagadougou regional blood transfusion centres over time. Provinces in light grey are outside the RBTC catchment areas. (Bougour = Bougouriba; Ganzour = Ganzourgou Kour = Kourweogo; Oubrit = Oubritenga; Zoundw = Zoundweogo). Created with paintmaps.com

Fig. 9

Donor asymptomatic malaria prevalence over time by urban and rural locations. The error bars represent the 95% confidence interval of donor malaria prevalence

Fig. 10

Donor asymptomatic malaria prevalence over time by urban and rural locations for Centre and Hauts-Bassins regions. The error bars represent the 95% confidence interval of donor malaria prevalence. No prevalence is shown if the sample size was less than 30

Fig. 11

Median Malaria-infected red blood cell (MI-RBC) count by month for all asymptomatic malaria donors. MI-RBC = malaria-infected red blood cells. The error bars represent the 95% confidence interval of the MI-RBC median value

Fig. 12

Donor asymptomatic malaria prevalence and gametocyte carriage trends over time. The error bars repesent the 95% confidence interval of malaria prevalence and gametocyte carriage percentage